Reset23/the-stack-v2-blamed2 · Datasets at Hugging Face

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/lekce/lekce_11/json_load.py

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kabezd/pyladies

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refs/heads/master

2021-02-13T16:59:14.144039

2020-07-31T18:18:14

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import json json_string = """ { "name": "Anna", "city": "Brno", "language": ["czech", "english", "Python"], "age": 26 } """ data = json.loads(json_string) print(data) print(data['city'])

[ "bezdekova.k@seznam.cz" ]

bezdekova.k@seznam.cz

99c4e44f477c0bac23afd0bd0105f76f1483e7d6

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/xmudata/DIV2K2018.py

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[]

no_license

SrWYG/channelPruningXMU

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refs/heads/master

2020-03-17T06:47:44.939130

2018-05-14T14:21:47

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from xmudata.data import Data import tensorlayer as tl from xmuutil import utils import os from xmuutil.exception import LargeSizeException class DIV2K2018(Data): def __init__(self, train_truth_dir, train_data_dir, test_truth_dir = None, test_data_dir=None, image_size = 96, scale = 4, train_postfix_len = 3, test_postfix_len = -1, test_per=0.01): Data.__init__(self, train_truth_dir, train_data_dir,test_truth_dir,test_data_dir, train_postfix_len, test_postfix_len, test_per) self.image_size = image_size self.scale = scale def get_image_set(self, image_lr_list,input_dir,ground_truth_dir, postfix_len): y_imgs = [] x_imgs = [] # use 10 threads to read files imgs_lr = tl.visualize.read_images(image_lr_list, input_dir) image_hr_list = utils.get_hrimg_list(image_lr_list, postfix_len) imgs_hr = tl.visualize.read_images(image_hr_list, ground_truth_dir) for i in range(len(imgs_lr)): #crop the image randomly try: x_img,y_img = utils.crop(imgs_lr[i], imgs_hr[i], self.image_size, self.image_size, self.scale, is_random=True) except LargeSizeException as e: print(e) else: y_imgs.append(y_img) x_imgs.append(x_img) return x_imgs, y_imgs

[ "24320142202497@stu.xmu.edu.cn" ]

24320142202497@stu.xmu.edu.cn

0aacd4bb5f93f7cde57b903a1aec981ffb433ed5

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/chapter_8/first_mlp.py

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[]

no_license

pm3310/deep_learning_with_python

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76da1698742b083698803d19d1bcbb0843f7f840

refs/heads/master

2020-12-25T14:13:40.948359

2016-08-17T18:21:12

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from keras.models import Sequential from keras.layers import Dense import numpy from sklearn.cross_validation import StratifiedKFold seed = 7 numpy.random.seed(seed) # load pima indians dataset dataset = numpy.loadtxt("pima-indians-diabetes.csv", delimiter=",") # split into input (X) and output (Y) variables X = dataset[:, 0:8] Y = dataset[:, 8] # define 10-fold cross validation test harness kfold = StratifiedKFold(y=Y, n_folds=10, shuffle=True, random_state=seed) cvscores = [] for i, (train, test) in enumerate(kfold): # create model model = Sequential() model.add(Dense(12, input_dim=8, init='uniform', activation='relu')) model.add(Dense(8, init='uniform', activation='relu')) model.add(Dense(1, init='uniform', activation='sigmoid')) # Compile model model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy']) # Fit the model model.fit(X[train], Y[train], nb_epoch=150, batch_size=10, verbose=0) # evaluate the model scores = model.evaluate(X[test], Y[test], verbose=0) print("%s: %.2f%%" % (model.metrics_names[1], scores[1]*100)) cvscores.append(scores[1] * 100) print("%.2f%% (+/- %.2f%%)" % (numpy.mean(cvscores), numpy.std(cvscores)))

[ "pavlos@workable.com" ]

pavlos@workable.com

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/HeroloDjango/settings.py

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no_license

PazBazak/HeroloDjango

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refs/heads/dev

2023-01-30T16:41:19.500980

2020-12-09T15:40:07

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""" Django settings for HeroloDjango project. Generated by 'django-admin startproject' using Django 3.1.4. 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/ """ import os from pathlib import Path import sys import django_heroku from decouple import config # Build paths inside the project like this: BASE_DIR / 'subdir'. BASE_DIR = Path(__file__).resolve().parent.parent # 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 = config('SECRET_KEY') # SECURITY WARNING: don't run with debug turned on in production! DEBUG = config('DEBUG') ALLOWED_HOSTS = [] # Application definition INSTALLED_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'api.apps.ApiConfig', 'rest_framework', 'rest_framework.authtoken', ] 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 = 'HeroloDjango.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', ], }, }, ] WSGI_APPLICATION = 'HeroloDjango.wsgi.application' # Database # https://docs.djangoproject.com/en/3.1/ref/settings/#databases DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': BASE_DIR / 'db.sqlite3', } } # 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', }, ] AUTH_USER_MODEL = 'api.CustomUser' # rest framework REST_FRAMEWORK = { 'DEFAULT_AUTHENTICATION_CLASSES': [ 'rest_framework.authentication.TokenAuthentication', ], 'DEFAULT_PERMISSION_CLASSES': [ 'rest_framework.permissions.IsAuthenticated', ], } # 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 # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/3.1/howto/static-files/ STATIC_URL = '/static/' # Activate Django-Heroku when not on test!. if sys.argv[1] != 'test': django_heroku.settings(locals())

[ "yolobazak1@gmail.com" ]

yolobazak1@gmail.com

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/detection_nbdev/metrics.py

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Sports-AI-Coaching/detection-nbdev

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# AUTOGENERATED! DO NOT EDIT! File to edit: 02_metrics.ipynb (unless otherwise specified). __all__ = ['bbox_iou', 'hungarian_loss'] # Cell import torch from scipy.optimize import linear_sum_assignment # Cell def bbox_iou(boxA, boxB): # determine the (x, y)-coordinates of the intersection rectangle xA = max(boxA[0], boxB[0]) yA = max(boxA[1], boxB[1]) xB = min(boxA[2], boxB[2]) yB = min(boxA[3], boxB[3]) # compute the area of intersection rectangle interArea = max(0, xB - xA + 1) * max(0, yB - yA + 1) # compute the area of both the prediction and ground-truth # rectangles boxAArea = (boxA[2] - boxA[0] + 1) * (boxA[3] - boxA[1] + 1) boxBArea = (boxB[2] - boxB[0] + 1) * (boxB[3] - boxB[1] + 1) # compute the intersection over union by taking the intersection # area and dividing it by the sum of prediction + ground-truth # areas - the interesection area iou = interArea / float(boxAArea + boxBArea - interArea) # return the intersection over union value return iou # Cell def hungarian_loss(boxesA, boxesB, loss_func=bbox_iou, maximize=True): n = max(len(boxesA), len(boxesB)) cost_matrix = torch.zeros((n,n)) for i, boxA in enumerate(boxesA): for j, boxB in enumerate(boxesB): if boxA is None or boxB is None: cost_matrix[i,j] = int(not maximize) else: cost_matrix[i, j] = bbox_iou(boxA, boxB) row_ind, col_ind = linear_sum_assignment(cost_matrix, maximize=maximize) return cost_matrix[row_ind, col_ind].mean()

[ "atom@phi.asura" ]

atom@phi.asura

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/Simulator.py

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no_license

helgejo/cozmo_rl

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refs/heads/master

2021-01-15T17:15:30.256995

2017-08-10T12:48:37

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#!/usr/bin/env python2 # -*- coding: utf-8 -*- """ Created on Tue Aug 8 21:05:44 2017 @author: bjorland """ class Gym: def __init__(self): self.x = 1 self.observation self.action_space self.observation_space def step(self, action): return observation, reward, done, info def get_new_state(self, action): hsdjkfshj = 1 def get_reward(self, action): def reset(self): def make(self):

[ "Helge.Johannessen-Bjorland@telenor.com" ]

Helge.Johannessen-Bjorland@telenor.com

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/build/turtlebot3_msgs/cmake/turtlebot3_msgs-genmsg-context.py

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bryceustc/ROS

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# generated from genmsg/cmake/pkg-genmsg.context.in messages_str = "/home/bryce/pid_control_ws/src/turtlebot3_msgs/msg/SensorState.msg;/home/bryce/pid_control_ws/src/turtlebot3_msgs/msg/VersionInfo.msg;/home/bryce/pid_control_ws/src/turtlebot3_msgs/msg/Sound.msg" services_str = "" pkg_name = "turtlebot3_msgs" dependencies_str = "std_msgs" langs = "gencpp;geneus;genlisp;gennodejs;genpy" dep_include_paths_str = "turtlebot3_msgs;/home/bryce/pid_control_ws/src/turtlebot3_msgs/msg;std_msgs;/opt/ros/kinetic/share/std_msgs/cmake/../msg" PYTHON_EXECUTABLE = "/usr/bin/python" package_has_static_sources = '' == 'TRUE' genmsg_check_deps_script = "/opt/ros/kinetic/share/genmsg/cmake/../../../lib/genmsg/genmsg_check_deps.py"

[ "bryce@mail.ustc.edu.cn" ]

bryce@mail.ustc.edu.cn

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/utils/DetectClosestColor.py

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no_license

msjun23/Lane-Detection

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refs/heads/master

2023-08-01T06:54:57.708416

2021-09-20T13:56:37

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import cv2 import numpy as np from matplotlib import pyplot as plt from numpy.core.fromnumeric import shape delta_h = 30 delta_sv = 75 def DetectYellow(img): hsv_yellow = np.array([30, 255, 255]) hsv_img = cv2.cvtColor(img, cv2.COLOR_BGR2HSV) dist_img = np.sum((hsv_img - hsv_yellow)**2, axis=2)**(1/2) pixel_min = np.min(dist_img) pixel_max = np.max(dist_img) # Pixel Normalization: 0~255 dist_img = ((dist_img - pixel_min) / (pixel_max - pixel_min)) * 255 yellow_mask = cv2.inRange(dist_img, np.array([0]), np.array([40])) return yellow_mask def DetectWhite(img): hsv_white = np.array([0, 0, 255]) hsv_img = cv2.cvtColor(img, cv2.COLOR_BGR2HSV) dist_img = np.sum((hsv_img - hsv_white)**2, axis=2)**(1/2) pixel_min = np.min(dist_img) pixel_max = np.max(dist_img) # Pixel Normalization: 0~255 dist_img = ((dist_img - pixel_min) / (pixel_max - pixel_min)) * 255 white_mask = cv2.inRange(dist_img, np.array([0]), np.array([20])) return white_mask def DetectYellowWhite(img): yellow_mask = DetectYellow(img) white_mask = DetectWhite(img) return cv2.bitwise_or(yellow_mask, white_mask)

[ "msjun23@gmail.com" ]

msjun23@gmail.com

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/26feb/largest_number_possible.py

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adarhp0/coding

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refs/heads/master

2021-07-10T20:04:54.375292

2021-04-03T15:11:06

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tes=int(input()) for t in range(tes): n,s=map(int,input().split()) if s/n>9 and s!=0: print(-1) else: z={} for i in range(10): z[i]=0 q=9 while s>0: z[q]=int(s/q) s=s-z[q]*q q=q-1 a='' su=0 for i in range(9,0,-1): k=z[i] su=su+k for j in range(k): a=a+str(i) b=n-su for i in range(b): a=a+str(0) print(a) #print(z)

[ "adarshahp0@gmail.com" ]

adarshahp0@gmail.com

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/seed.py

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rmmistry/movie-ratings-

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2021-01-10T05:13:17.863638

2015-10-23T00:58:23

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"""Utility file to seed ratings database from MovieLens data in seed_data/""" from model import User, Movie, Rating # from model import Rating # from model import Movie from model import connect_to_db, db from server import app from datetime import datetime def load_users(): """Load users from u.user into database.""" print "Users" # Delete all rows in table, so if we need to run this a second time, # we won't be trying to add duplicate users User.query.delete() # Read u.user file and insert data for row in open("seed_data/u.user"): row = row.rstrip() user_id, age, gender, occupation, zipcode = row.split("|") user = User(user_id=user_id, age=age, zipcode=zipcode) # We need to add to the session or it won't ever be stored db.session.add(user) # Once we're done, we should commit our work db.session.commit() def load_movies(): """Load movies from u.item into database.""" print "Movies" # Delete all rows in table, so if we need to run this a second time, # we won't be trying to add duplicate users Movie.query.delete() # Read u.user file and insert data for row in open("seed_data/u.item"): row = row.rstrip() row_splitted = row.split("|") ##throwing out rows with no release date or title is unknown movie_id = row_splitted[0] title = row_splitted[1] released_at = row_splitted[2] imdb_url = row_splitted[4] ## FIX LATER: optionally, rstrip('(') - why didn't it work? title = title[:-7] print title if released_at != (''): released_at_ob = datetime.strptime(released_at, '%d-%b-%Y') else: pass movie = Movie(movie_id=movie_id, title=title, released_at=released_at_ob, imdb_url=imdb_url) # We need to add to the session or it won't ever be stored db.session.add(movie) # Once we're done, we should commit our work db.session.commit() def load_ratings(): """Load ratings from u.data into database.""" print "Ratings" # Delete all rows in table, so if we need to run this a second time, # we won't be trying to add duplicate users Rating.query.delete() # Read u.user file and insert data for row in open("seed_data/u.data"): row = row.rstrip() row_splitted=row.split() user_id = row_splitted[0] movie_id = row_splitted[1] score = row_splitted[2] rating = Rating(movie_id=movie_id, user_id=user_id, score=score) # We need to add to the session or it won't ever be stored db.session.add(rating) # Once we're done, we should commit our work db.session.commit() if __name__ == "__main__": connect_to_db(app) # In case tables haven't been created, create them db.create_all() # Import different types of data load_users() load_movies() load_ratings()

[ "info@hackbrightacademy.com" ]

info@hackbrightacademy.com

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/spotify-recommendations/ml/get_feat_playlists_new_albums.py

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restevesd/PROJECTS-DATA-SCIENTIST-TRAINING

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import django import os import logging from spotipy.oauth2 import SpotifyClientCredentials os.environ.setdefault("DJANGO_SETTINGS_MODULE", "spotify_recs.settings") django.setup() from spotify_app.models import Playlist import spotipy import time logger = logging.getLogger('django') logger.setLevel(logging.INFO) def main(): client_credentials_manager = SpotifyClientCredentials( client_id="fd2ae3d3b2d3407da3b02a97376827b5", client_secret="e84c4e18dd2f463aa0c649341d64dbfb" ) sp = spotipy.Spotify(client_credentials_manager=client_credentials_manager) logger.info("Getting featured playlists...") payload = sp.featured_playlists()["playlists"] playlist_total = payload["items"] while payload["next"]: payload = sp.next(payload) playlist_total.extend(payload["items"]) for playlist in playlist_total: temp_obj = Playlist( playlist_id=playlist["id"], playlist_name=playlist["name"], playlist_url=playlist["external_urls"]["spotify"], playlist_num_tracks=playlist["tracks"]["total"], playlist_featured=True, playlist_owner=playlist["owner"]["display_name"].lower(), date_created=time.time(), playlist_img_src=playlist["images"][0]["url"], ) temp_obj.save() if __name__ == "__main__": main()

[ "noreply@github.com" ]

noreply@github.com

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/Lists and Tuples/Tuples/list to tuple.py

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[]

no_license

REGENTMONK97/Python-

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ab8987506dbbae2a9660852c85f21535954738c7

refs/heads/master

2020-03-20T20:56:37.708665

2018-06-18T08:01:38

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a = input("Enter all data separated by comma") a = a.lstrip() a1 = a.split(',') tuple(a1)

[ "sairaghunath97@gmail.com" ]

sairaghunath97@gmail.com

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/typogrify.py

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[]

no_license

curiousleo/kardiopraxis-flask

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refs/heads/master

2021-01-19T03:13:09.666560

2015-05-21T19:58:08

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# Copyright (c) 2007, Christian Metts # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are # met: # # * Redistributions of source code must retain the above copyright # notice, this list of conditions and the following disclaimer. # * Redistributions in binary form must reproduce the above # copyright notice, this list of conditions and the following # disclaimer in the documentation and/or other materials provided # with the distribution. # * Neither the name of the author nor the names of other # contributors may be used to endorse or promote products derived # from this software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS # "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT # LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR # A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT # OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, # SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT # LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, # DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY # THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT # (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. # # This version of typogrify is stripped of all Django-related functions. ''' .. module:: typogrify :synopsis: Prettify web typography. ''' import re def amp(text): '''Wraps apersands in HTML with ``<span class="amp">`` so they can be styled with CSS. Apersands are also normalized to ``&``. Requires ampersands to have whitespace or an `` `` on both sides. >>> amp('One & two') 'One <span class="amp">&</span> two' >>> amp('One & two') 'One <span class="amp">&</span> two' >>> amp('One & two') 'One <span class="amp">&</span> two' >>> amp('One & two') 'One <span class="amp">&</span> two' It won't mess up ampersands that are already wrapped, in entities or URLs. >>> amp('One <span class="amp">&</span> two') 'One <span class="amp">&</span> two' >>> amp('“this” & <a href="/?that&test">that</a>') '“this” <span class="amp">&</span> <a href="/?that&test">that</a>' It should ignore standalone amps that are in attributes >>> amp('<link href="xyz.html" title="One & Two">xyz</link>') '<link href="xyz.html" title="One & Two">xyz</link>' ''' # tag_pattern from http://haacked.com/archive/2004/10/25/usingregularexpressionstomatchhtml.aspx # it kinda sucks but it fixes the standalone amps in attributes bug tag_pattern = '</?\w+((\s+\w+(\s*=\s*(?:".*?"|\'.*?\'|[^\'">\s]+))?)+\s*|\s*)/?>' amp_finder = re.compile(r'(\s| )(&|&|&\#38;)(\s| )') intra_tag_finder = re.compile(r'(?P<prefix>(%s)?)(?P<text>([^<]*))(?P<suffix>(%s)?)' % (tag_pattern, tag_pattern)) def _amp_process(groups): prefix = groups.group('prefix') or '' text = amp_finder.sub(r'''\1<span class="amp">&</span>\3''', groups.group('text')) suffix = groups.group('suffix') or '' return prefix + text + suffix output = intra_tag_finder.sub(_amp_process, text) return output amp.is_safe = True def caps(text): '''Wraps multiple capital letters in ``<span class="caps">`` so they can be styled with CSS. >>> caps('A message from KU') 'A message from <span class="caps">KU</span>' Uses the smartypants tokenizer to not screw with HTML or with tags it shouldn't. >>> caps('<PRE>CAPS</pre> more CAPS') '<PRE>CAPS</pre> more <span class="caps">CAPS</span>' >>> caps('A message from 2KU2 with digits') 'A message from <span class="caps">2KU2</span> with digits' >>> caps('Dotted caps followed by spaces should never include them in the wrap D.O.T. like so.') 'Dotted caps followed by spaces should never include them in the wrap <span class="caps">D.O.T.</span> like so.' All caps with with apostrophes in them shouldn't break. Only handles dump apostrophes though. >>> caps("JIMMY'S") '<span class="caps">JIMMY\\'S</span>' >>> caps('<i>D.O.T.</i>HE34T<b>RFID</b>') '<i><span class="caps">D.O.T.</span></i><span class="caps">HE34T</span><b><span class="caps">RFID</span></b>' ''' try: import smartypants except ImportError: raise Exception, "The Python SmartyPants library isn't installed." return text tokens = smartypants._tokenize(text) result = [] in_skipped_tag = False cap_finder = re.compile(r'''( (\b[A-Z\d]* # Group 2: Any amount of caps and digits [A-Z]\d*[A-Z] # A cap string much at least include two caps (but they can have digits between them) [A-Z\d']*\b) # Any amount of caps and digits or dumb apostsrophes | (\b[A-Z]+\.\s? # OR: Group 3: Some caps, followed by a '.' and an optional space (?:[A-Z]+\.\s?)+) # Followed by the same thing at least once more (?:\s|\b|$)) ''', re.VERBOSE) def _cap_wrapper(matchobj): '''This is necessary to keep dotted cap strings to pick up extra spaces''' if matchobj.group(2): return '''<span class="caps">%s</span>''' % matchobj.group(2) else: if matchobj.group(3)[-1] == ' ': caps = matchobj.group(3)[:-1] tail = ' ' else: caps = matchobj.group(3) tail = '' return '''<span class="caps">%s</span>%s''' % (caps, tail) tags_to_skip_regex = re.compile('<(/)?(?:pre|code|kbd|script|math)[^>]*>', re.IGNORECASE) for token in tokens: if token[0] == 'tag': # Don't mess with tags. result.append(token[1]) close_match = tags_to_skip_regex.match(token[1]) if close_match and close_match.group(1) == None: in_skipped_tag = True else: in_skipped_tag = False else: if in_skipped_tag: result.append(token[1]) else: result.append(cap_finder.sub(_cap_wrapper, token[1])) output = ''.join(result) return output caps.is_safe = True def initial_quotes(text): '''Wraps initial quotes in ``class="dquo"`` for double quotes or ``class="quo"`` for single quotes. Works in these block tags ``(h1-h6, p, li, dt, dd)`` and also accounts for potential opening inline elements ``a, em, strong, span, b, i`` >>> initial_quotes('"With primes"') '<span class="dquo">"</span>With primes"' >>> initial_quotes("'With single primes'") '<span class="quo">\\'</span>With single primes\\'' >>> initial_quotes('<a href="#">"With primes and a link"</a>') '<a href="#"><span class="dquo">"</span>With primes and a link"</a>' >>> initial_quotes('“With smartypanted quotes”') '<span class="dquo">“</span>With smartypanted quotes”' ''' quote_finder = re.compile(r'''((<(p|h[1-6]|li|dt|dd)[^>]*>|^) # start with an opening p, h1-6, li, dd, dt or the start of the string \s* # optional white space! (<(a|em|span|strong|i|b)[^>]*>\s*)*) # optional opening inline tags, with more optional white space for each. (("|“|&\#8220;)|('|‘|&\#8216;)) # Find me a quote! (only need to find the left quotes and the primes) # double quotes are in group 7, singles in group 8 ''', re.VERBOSE) def _quote_wrapper(matchobj): if matchobj.group(7): classname = 'dquo' quote = matchobj.group(7) else: classname = 'quo' quote = matchobj.group(8) return '''%s<span class="%s">%s</span>''' % (matchobj.group(1), classname, quote) output = quote_finder.sub(_quote_wrapper, text) return output initial_quotes.is_safe = True def smartypants(text): '''Applies smarty pants to curl quotes. >>> smartypants('The "Green" man') 'The “Green” man' ''' try: import smartypants except ImportError: raise Exception, "The Python smartypants library isn't installed." return text else: output = smartypants.smartypants(text) return output smartypants.is_safe = True def typogrify(text): '''The super typography filter Applies the following filters: widont, smartypants, caps, amp, initial_quotes >>> typogrify('<h2>"Jayhawks" & KU fans act extremely obnoxiously</h2>') '<h2><span class="dquo">“</span>Jayhawks” <span class="amp">&</span> <span class="caps">KU</span> fans act extremely obnoxiously</h2>' ''' text = amp(text) text = widont(text) text = smartypants(text) text = caps(text) text = initial_quotes(text) return text def widont(text): '''Replaces the space between the last two words in a string with `` `` Works in these block tags ``(h1-h6, p, li, dd, dt)`` and also accounts for potential closing inline elements ``a, em, strong, span, b, i`` >>> widont('A very simple test') 'A very simple test' Single word items shouldn't be changed >>> widont('Test') 'Test' >>> widont(' Test') ' Test' >>> widont('<ul><li>Test</p></li><ul>') '<ul><li>Test</p></li><ul>' >>> widont('<ul><li> Test</p></li><ul>') '<ul><li> Test</p></li><ul>' >>> widont('<p>In a couple of paragraphs</p><p>paragraph two</p>') '<p>In a couple of paragraphs</p><p>paragraph two</p>' >>> widont('<h1><a href="#">In a link inside a heading</i> </a></h1>') '<h1><a href="#">In a link inside a heading</i> </a></h1>' >>> widont('<h1><a href="#">In a link</a> followed by other text</h1>') '<h1><a href="#">In a link</a> followed by other text</h1>' Empty HTMLs shouldn't error >>> widont('<h1><a href="#"></a></h1>') '<h1><a href="#"></a></h1>' >>> widont('<div>Divs get no love!</div>') '<div>Divs get no love!</div>' >>> widont('<pre>Neither do PREs</pre>') '<pre>Neither do PREs</pre>' >>> widont('<div><p>But divs with paragraphs do!</p></div>') '<div><p>But divs with paragraphs do!</p></div>' ''' widont_finder = re.compile(r'''((?:</?(?:a|em|span|strong|i|b)[^>]*>)|[^<>\s]) # must be proceeded by an approved inline opening or closing tag or a nontag/nonspace \s+ # the space to replace ([^<>\s]+ # must be flollowed by non-tag non-space characters \s* # optional white space! (</(a|em|span|strong|i|b)>\s*)* # optional closing inline tags with optional white space after each ((</(p|h[1-6]|li|dt|dd)>)|$)) # end with a closing p, h1-6, li or the end of the string ''', re.VERBOSE) output = widont_finder.sub(r'\1 \2', text) return output widont.is_safe = True def _test(): import doctest doctest.testmod() if __name__ == '__main__': _test()

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/MealRunner/__init__.py

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""" MealRunner package initializer. """ import flask # app is a single object used by all the code modules in this package app = flask.Flask(__name__) # pylint: disable=invalid-name # Read settings from config module (MealRunner/config.py) app.config.from_object('MealRunner.config') # Overlay settings read from file specified by environment variable. This is # useful for using different on development and production machines. # Reference: http://flask.pocoo.org/docs/config/ app.config.from_envvar('MEALRUNNER_SETTINGS', silent=True) # Tell our app about views and model. This is dangerously close to a # circular import, which is naughty, but Flask was designed that way. # (Reference http://flask.pocoo.org/docs/patterns/packages/) We're # going to tell pylint and pycodestyle to ignore this coding style violation. import MealRunner.views # noqa: E402 pylint: disable=wrong-import-position import MealRunner.model # noqa: E402 pylint: disable=wrong-import-position

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mamutahr@umich.edu

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MikeOcc/MyProjectEulerFiles

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def p17(): def lowest_digit(n): return n/10, n%10 def words(n): if n > 999: raise ValueError, "Number too big." digits = [None, 'one', 'two', 'three', 'four', 'five', 'six', 'seven', 'eight', 'nine'] teens = ['ten', 'eleven', 'twelve', 'thirteen', 'fourteen', 'fifteen', 'sixteen', 'seventeen', 'eighteen', 'nineteen'] tens = [None, None, 'twenty', 'thirty', 'forty', 'fifty', 'sixty', 'seventy', 'eighty', 'ninety'] n, o = lowest_digit(n) n, t = lowest_digit(n) n, h = lowest_digit(n) result = [] if t == 1: result.append(teens[o]) else: if o: result.append(digits[o]) if t: result.append(tens[t]) if h: if t or o: result.append('and') result.append('hundred') result.append(digits[h]) #return ''.join(reversed(result)) return ''.join(result) c = 0 for i in range(1,1000): c += len(words(i)) c+=len('onethousand') print c p17()

[ "mike.occhipinti@mlsassistant.com" ]

mike.occhipinti@mlsassistant.com

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/out/gt/real-reinforcement-learning/v2/actor_critic.py

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import argparse import gym import numpy as np from itertools import count from collections import namedtuple import torch import torch.nn as nn import torch.nn.functional as F import torch.optim as optim import torch.autograd as autograd from torch.autograd import Variable import torchvision.transforms as T parser = argparse.ArgumentParser(description='PyTorch actor-critic example') parser.add_argument('--gamma', type=int, default=0.99, metavar='G', help='discount factor (default: 0.99)') parser.add_argument('--seed', type=int, default=543, metavar='N', help='random seed (default: 1)') parser.add_argument('--render', action='store_true', help='render the environment') parser.add_argument('--log-interval', type=int, default=10, metavar='N', help='interval between training status logs (default: 10)') args = parser.parse_args() env = gym.make('CartPole-v0') env.seed(args.seed) torch.manual_seed(args.seed) SavedAction = namedtuple('SavedAction', ['action', 'value']) class Policy(nn.Module): def __init__(self): super(Policy, self).__init__() self.affine1 = nn.Linear(4, 128) self.action_head = nn.Linear(128, 2) self.value_head = nn.Linear(128, 1) self.saved_actions = [] self.rewards = [] def forward(self, x): x = F.relu(self.affine1(x)) action_scores = self.action_head(x) state_values = self.value_head(x) return (F.softmax(action_scores), state_values) model = Policy() optimizer = optim.Adam(model.parameters(), lr=0.03) def select_action(state): state = torch.from_numpy(state).float().unsqueeze(0) (probs, state_value) = model(Variable(state)) action = probs.multinomial() model.saved_actions.append(SavedAction(action, state_value)) return action.data def finish_episode(): R = 0 saved_actions = model.saved_actions value_loss = 0 rewards = [] for r in model.rewards[::-1]: R = r + args.gamma * R rewards.insert(0, R) rewards = torch.Tensor(rewards) rewards = (rewards - rewards.mean()) / rewards.std() for ((action, value), r) in zip(saved_actions, rewards): action.reinforce(r - value.data.squeeze()) value_loss += F.smooth_l1_loss(value, Variable(torch.Tensor([r]))) optimizer.zero_grad() final_nodes = [value_loss] + list(map(lambda p: p.action, saved_actions)) gradients = [torch.ones(1)] + [None] * len(saved_actions) autograd.backward(final_nodes, gradients) print('LOG STMT: Model weights = %s' % model.parameters()) optimizer.step() del model.rewards[:] del model.saved_actions[:] running_reward = 10 for i_episode in count(1): state = env.reset() for t in range(10000): action = select_action(state) (state, reward, done, _) = env.step(action[0, 0]) if args.render: env.render() model.rewards.append(reward) if done: break running_reward = running_reward * 0.99 + t * 0.01 finish_episode() if i_episode % args.log_interval == 0: print('Episode {}\tLast length: {:5d}\tAverage length: {:.2f}'.format(i_episode, t, running_reward)) if running_reward > 200: print('Solved! Running reward is now {} and the last episode runs to {} time steps!'.format(running_reward, t)) break

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gmatute@berkeley.edu

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/selenium_pyPOM/test_dou_pypom.py

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Brombult/Test_Automation

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from selenium import webdriver import pytest from page import DouMainPage, SearchResultPage base_url = 'https://dou.ua/' COMPANY_NAME = 'DOU' INVALID_NAME = '123efdvdfbgfdbfg' driver = webdriver.Chrome() @pytest.fixture(scope='module', autouse=True) def setup_and_teardown(): driver.implicitly_wait(5) driver.get('https://dou.ua/') yield driver.quit() def test_search(): """Searches for company name, then asserts that name is present in search results """ main_page = DouMainPage(driver, base_url).open() main_page.search_for(COMPANY_NAME) result_page = SearchResultPage(driver) result_page.assert_result_found(COMPANY_NAME) def test_invalid_search(): """Searches for company that don't exists, that asserts that nothing was found""" main_page = DouMainPage(driver, base_url).open() main_page.search_for(INVALID_NAME) result_page = SearchResultPage(driver) result_page.assert_no_result_found()

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rickrolled5997@gmail.com

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/python/src/main/python/pyalink/alink/tests/examples/from_docs/test_alsusersperitemrecommbatchop.py

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import unittest from pyalink.alink import * import numpy as np import pandas as pd class TestAlsUsersPerItemRecommBatchOp(unittest.TestCase): def test_alsusersperitemrecommbatchop(self): df_data = pd.DataFrame([ [1, 1, 0.6], [2, 2, 0.8], [2, 3, 0.6], [4, 1, 0.6], [4, 2, 0.3], [4, 3, 0.4], ]) data = BatchOperator.fromDataframe(df_data, schemaStr='user bigint, item bigint, rating double') als = AlsTrainBatchOp().setUserCol("user").setItemCol("item").setRateCol("rating") \ .setNumIter(10).setRank(10).setLambda(0.01) model = als.linkFrom(data) predictor = AlsUsersPerItemRecommBatchOp() \ .setItemCol("item").setRecommCol("rec").setK(1).setReservedCols(["item"]) predictor.linkFrom(model, data).print(); pass

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shaomeng.wang.w@gmail.com

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refs/heads/master

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# automatically generated by the FlatBuffers compiler, do not modify # namespace: graph import flatbuffers class UIOp(object): __slots__ = ['_tab'] @classmethod def GetRootAsUIOp(cls, buf, offset): n = flatbuffers.encode.Get(flatbuffers.packer.uoffset, buf, offset) x = UIOp() x.Init(buf, n + offset) return x # UIOp def Init(self, buf, pos): self._tab = flatbuffers.table.Table(buf, pos) # UIOp def Name(self): o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(4)) if o != 0: return self._tab.String(o + self._tab.Pos) return None # UIOp def OpName(self): o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(6)) if o != 0: return self._tab.String(o + self._tab.Pos) return None # UIOp def Inputs(self, j): o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8)) if o != 0: a = self._tab.Vector(o) return self._tab.String(a + flatbuffers.number_types.UOffsetTFlags.py_type(j * 4)) return "" # UIOp def InputsLength(self): o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(8)) if o != 0: return self._tab.VectorLen(o) return 0 # UIOp def Outputs(self, j): o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(10)) if o != 0: a = self._tab.Vector(o) return self._tab.String(a + flatbuffers.number_types.UOffsetTFlags.py_type(j * 4)) return "" # UIOp def OutputsLength(self): o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(10)) if o != 0: return self._tab.VectorLen(o) return 0 # UIOp def ControlDeps(self, j): o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(12)) if o != 0: a = self._tab.Vector(o) return self._tab.String(a + flatbuffers.number_types.UOffsetTFlags.py_type(j * 4)) return "" # UIOp def ControlDepsLength(self): o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(12)) if o != 0: return self._tab.VectorLen(o) return 0 # UIOp def UiLabelExtra(self): o = flatbuffers.number_types.UOffsetTFlags.py_type(self._tab.Offset(14)) if o != 0: return self._tab.String(o + self._tab.Pos) return None def UIOpStart(builder): builder.StartObject(6) def UIOpAddName(builder, name): builder.PrependUOffsetTRelativeSlot(0, flatbuffers.number_types.UOffsetTFlags.py_type(name), 0) def UIOpAddOpName(builder, opName): builder.PrependUOffsetTRelativeSlot(1, flatbuffers.number_types.UOffsetTFlags.py_type(opName), 0) def UIOpAddInputs(builder, inputs): builder.PrependUOffsetTRelativeSlot(2, flatbuffers.number_types.UOffsetTFlags.py_type(inputs), 0) def UIOpStartInputsVector(builder, numElems): return builder.StartVector(4, numElems, 4) def UIOpAddOutputs(builder, outputs): builder.PrependUOffsetTRelativeSlot(3, flatbuffers.number_types.UOffsetTFlags.py_type(outputs), 0) def UIOpStartOutputsVector(builder, numElems): return builder.StartVector(4, numElems, 4) def UIOpAddControlDeps(builder, controlDeps): builder.PrependUOffsetTRelativeSlot(4, flatbuffers.number_types.UOffsetTFlags.py_type(controlDeps), 0) def UIOpStartControlDepsVector(builder, numElems): return builder.StartVector(4, numElems, 4) def UIOpAddUiLabelExtra(builder, uiLabelExtra): builder.PrependUOffsetTRelativeSlot(5, flatbuffers.number_types.UOffsetTFlags.py_type(uiLabelExtra), 0) def UIOpEnd(builder): return builder.EndObject()

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noreply@github.com

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/mainapp/__init__.py

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no_license

xulongyuan203/leargit

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refs/heads/main

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from flask import Flask import settings app = Flask(__name__) app.config.from_object(settings.Dev)

[ "email@example.com" ]

email@example.com

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/scrapy2019/spiders/ASTRO2.py

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[]

no_license

pavankumar-k/Scrapy2019

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refs/heads/master

2020-05-04T20:32:12.728899

2019-04-04T07:10:47

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# -*- coding: utf-8 -*- import scrapy import logging class AstroSpider(scrapy.Spider): name = 'ASTRO2' url = 'https://www.redjournal.org' # start_urls = ['https://www.redjournal.org/issue/S0360-3016(16)X0010-7'] def parse(self, response): lis = response.css('h2.title > a::attr(href)').extract() logging.info('urlsLENGTH:'+str(len(lis))) for l in lis: yield response.follow(self.url+l,callback = self.product) t = response.css('li.next > a::attr(href)').extract_first() if t is not None: yield response.follow(self.url+t,callback = self.parse) def product(self,response): title = response.css("h1.articleTitle::text").extract_first() doi= ''.join(response.css("div.doi ::text").extract()) text = ''.join(response.css("div.body > div.content ::text").extract()) disc = ''.join(response.css("div.footnotes ::text").extract()) alis = response.css('div.author') affli = ''.join(response.css('div.affiliation ::text').extract()) for a in alis: auth = a.css('a.openAuthorLayer.layerTrigger ::text').extract_first() aff = ';'.join(a.css('ul.affiliations ::text').extract()) if len(aff)==0: aff = affli if aff is None: aff = '' yield{ 'url':response.url, 'author':auth, 'affli':aff, 'title':title, 'doi':doi, 'text':text, 'disc':disc}

[ "noreply@github.com" ]

noreply@github.com

945e1f553c53f149a5257df89cfd0aae397e9d11

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/composeTiendita/dockerTiendita/tiendita/tiendita/wsgi.py

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[]

no_license

xl666/tiendita

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b067fb45a81c56fe84a3ca7ca4176676ac7e098e

refs/heads/master

2020-04-06T20:37:26.079522

2018-11-22T14:57:34

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""" WSGI config for tiendita project. It exposes the WSGI callable as a module-level variable named ``application``. For more information on this file, see https://docs.djangoproject.com/en/1.11/howto/deployment/wsgi/ """ import os from django.core.wsgi import get_wsgi_application os.environ.setdefault("DJANGO_SETTINGS_MODULE", "tiendita.settings") application = get_wsgi_application()

[ "xavier120@hotmail.com" ]

xavier120@hotmail.com

4331fac607aeb690fffb8d9b6f614658cc0f4fe0

e678642002db4882cb4a6641aff40c1b7f1f4348

/chapter3/recommender3.py

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[]

no_license

eks5115/DatamingGuideBook-Codes

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refs/heads/master

2020-03-24T23:14:39.112447

2018-08-01T08:21:19

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import codecs from math import sqrt users2 = {"Amy": {"Taylor Swift": 4, "PSY": 3, "Whitney Houston": 4}, "Ben": {"Taylor Swift": 5, "PSY": 2}, "Clara": {"PSY": 3.5, "Whitney Houston": 4}, "Daisy": {"Taylor Swift": 5, "Whitney Houston": 3}} users = {"Angelica": {"Blues Traveler": 3.5, "Broken Bells": 2.0, "Norah Jones": 4.5, "Phoenix": 5.0, "Slightly Stoopid": 1.5, "The Strokes": 2.5, "Vampire Weekend": 2.0}, "Bill": {"Blues Traveler": 2.0, "Broken Bells": 3.5, "Deadmau5": 4.0, "Phoenix": 2.0, "Slightly Stoopid": 3.5, "Vampire Weekend": 3.0}, "Chan": {"Blues Traveler": 5.0, "Broken Bells": 1.0, "Deadmau5": 1.0, "Norah Jones": 3.0, "Phoenix": 5, "Slightly Stoopid": 1.0}, "Dan": {"Blues Traveler": 3.0, "Broken Bells": 4.0, "Deadmau5": 4.5, "Phoenix": 3.0, "Slightly Stoopid": 4.5, "The Strokes": 4.0, "Vampire Weekend": 2.0}, "Hailey": {"Broken Bells": 4.0, "Deadmau5": 1.0, "Norah Jones": 4.0, "The Strokes": 4.0, "Vampire Weekend": 1.0}, "Jordyn": {"Broken Bells": 4.5, "Deadmau5": 4.0, "Norah Jones": 5.0, "Phoenix": 5.0, "Slightly Stoopid": 4.5, "The Strokes": 4.0, "Vampire Weekend": 4.0}, "Sam": {"Blues Traveler": 5.0, "Broken Bells": 2.0, "Norah Jones": 3.0, "Phoenix": 5.0, "Slightly Stoopid": 4.0, "The Strokes": 5.0}, "Veronica": {"Blues Traveler": 3.0, "Norah Jones": 5.0, "Phoenix": 4.0, "Slightly Stoopid": 2.5, "The Strokes": 3.0} } class recommender: def __init__(self, data, k=1, metric='pearson', n=5): """ initialize recommender currently, if data is dictionary the recommender is initialized to it. For all other data types of data, no initialization occurs k is the k value for k nearest neighbor metric is which distance formula to use n is the maximum number of recommendations to make""" self.k = k self.n = n self.username2id = {} self.userid2name = {} self.productid2name = {} # # The following two variables are used for Slope One # self.frequencies = {} self.deviations = {} # for some reason I want to save the name of the metric self.metric = metric if self.metric == 'pearson': self.fn = self.pearson # # if data is dictionary set recommender data to it # if type(data).__name__ == 'dict': self.data = data def convertProductID2name(self, id): """Given product id number return product name""" if id in self.productid2name: return self.productid2name[id] else: return id def userRatings(self, id, n): """Return n top ratings for user with id""" print("Ratings for " + self.userid2name[id]) ratings = self.data[id] print(len(ratings)) ratings = list(ratings.items())[:n] ratings = [(self.convertProductID2name(k), v) for (k, v) in ratings] # finally sort and return ratings.sort(key=lambda artistTuple: artistTuple[1], reverse=True) for rating in ratings: print("%s\t%i" % (rating[0], rating[1])) def showUserTopItems(self, user, n): """ show top n items for user""" items = list(self.data[user].items()) items.sort(key=lambda itemTuple: itemTuple[1], reverse=True) for i in range(n): print("%s\t%i" % (self.convertProductID2name(items[i][0]), items[i][1])) def loadMovieLens(self, path=''): self.data = {} # # first load movie ratings # i = 0 # # First load book ratings into self.data # # f = codecs.open(path + "u.data", 'r', 'utf8') f = codecs.open(path + "u.data", 'r', 'ascii') # f = open(path + "u.data") for line in f: i += 1 # separate line into fields fields = line.split('\t') user = fields[0] movie = fields[1] rating = int(fields[2].strip().strip('"')) if user in self.data: currentRatings = self.data[user] else: currentRatings = {} currentRatings[movie] = rating self.data[user] = currentRatings f.close() # # Now load movie into self.productid2name # the file u.item contains movie id, title, release date among # other fields # # f = codecs.open(path + "u.item", 'r', 'utf8') f = codecs.open(path + "u.item", 'r', 'iso8859-1', 'ignore') # f = open(path + "u.item") for line in f: i += 1 # separate line into fields fields = line.split('|') mid = fields[0].strip() title = fields[1].strip() self.productid2name[mid] = title f.close() # # Now load user info into both self.userid2name # and self.username2id # # f = codecs.open(path + "u.user", 'r', 'utf8') f = open(path + "u.user") for line in f: i += 1 fields = line.split('|') userid = fields[0].strip('"') self.userid2name[userid] = line self.username2id[line] = userid f.close() print(i) def loadBookDB(self, path=''): """loads the BX book dataset. Path is where the BX files are located""" self.data = {} i = 0 # # First load book ratings into self.data # f = codecs.open(path + "u.data", 'r', 'utf8') for line in f: i += 1 # separate line into fields fields = line.split(';') user = fields[0].strip('"') book = fields[1].strip('"') rating = int(fields[2].strip().strip('"')) if rating > 5: print("EXCEEDING ", rating) if user in self.data: currentRatings = self.data[user] else: currentRatings = {} currentRatings[book] = rating self.data[user] = currentRatings f.close() # # Now load books into self.productid2name # Books contains isbn, title, and author among other fields # f = codecs.open(path + "BX-Books.csv", 'r', 'utf8') for line in f: i += 1 # separate line into fields fields = line.split(';') isbn = fields[0].strip('"') title = fields[1].strip('"') author = fields[2].strip().strip('"') title = title + ' by ' + author self.productid2name[isbn] = title f.close() # # Now load user info into both self.userid2name and # self.username2id # f = codecs.open(path + "BX-Users.csv", 'r', 'utf8') for line in f: i += 1 # separate line into fields fields = line.split(';') userid = fields[0].strip('"') location = fields[1].strip('"') if len(fields) > 3: age = fields[2].strip().strip('"') else: age = 'NULL' if age != 'NULL': value = location + ' (age: ' + age + ')' else: value = location self.userid2name[userid] = value self.username2id[location] = userid f.close() print(i) def computeDeviations(self): # for each person in the data: # get their ratings for ratings in self.data.values(): # for each item & rating in that set of ratings: for (item, rating) in ratings.items(): self.frequencies.setdefault(item, {}) self.deviations.setdefault(item, {}) # for each item2 & rating2 in that set of ratings: for (item2, rating2) in ratings.items(): if item != item2: # add the difference between the ratings to our # computation self.frequencies[item].setdefault(item2, 0) self.deviations[item].setdefault(item2, 0.0) self.frequencies[item][item2] += 1 self.deviations[item][item2] += rating - rating2 for (item, ratings) in self.deviations.items(): for item2 in ratings: ratings[item2] /= self.frequencies[item][item2] def slopeOneRecommendations(self, userRatings): recommendations = {} frequencies = {} # for every item and rating in the user's recommendations for (userItem, userRating) in userRatings.items(): # for every item in our dataset that the user didn't rate for (diffItem, diffRatings) in self.deviations.items(): if diffItem not in userRatings and \ userItem in self.deviations[diffItem]: freq = self.frequencies[diffItem][userItem] recommendations.setdefault(diffItem, 0.0) frequencies.setdefault(diffItem, 0) # add to the running sum representing the numerator # of the formula recommendations[diffItem] += (diffRatings[userItem] + userRating) * freq # keep a running sum of the frequency of diffitem frequencies[diffItem] += freq recommendations = [(self.convertProductID2name(k), v / frequencies[k]) for (k, v) in recommendations.items()] # finally sort and return recommendations.sort(key=lambda artistTuple: artistTuple[1], reverse=True) # I am only going to return the first 50 recommendations return recommendations[:50] def pearson(self, rating1, rating2): sum_xy = 0 sum_x = 0 sum_y = 0 sum_x2 = 0 sum_y2 = 0 n = 0 for key in rating1: if key in rating2: n += 1 x = rating1[key] y = rating2[key] sum_xy += x * y sum_x += x sum_y += y sum_x2 += pow(x, 2) sum_y2 += pow(y, 2) if n == 0: return 0 # now compute denominator denominator = sqrt(sum_x2 - pow(sum_x, 2) / n) * \ sqrt(sum_y2 - pow(sum_y, 2) / n) if denominator == 0: return 0 else: return (sum_xy - (sum_x * sum_y) / n) / denominator def computeNearestNeighbor(self, username): """creates a sorted list of users based on their distance to username""" distances = [] for instance in self.data: if instance != username: distance = self.fn(self.data[username], self.data[instance]) distances.append((instance, distance)) # sort based on distance -- closest first distances.sort(key=lambda artistTuple: artistTuple[1], reverse=True) return distances def recommend(self, user): """Give list of recommendations""" recommendations = {} # first get list of users ordered by nearness nearest = self.computeNearestNeighbor(user) # # now get the ratings for the user # userRatings = self.data[user] # # determine the total distance totalDistance = 0.0 for i in range(self.k): totalDistance += nearest[i][1] # now iterate through the k nearest neighbors # accumulating their ratings for i in range(self.k): # compute slice of pie weight = nearest[i][1] / totalDistance # get the name of the person name = nearest[i][0] # get the ratings for this person neighborRatings = self.data[name] # get the name of the person # now find bands neighbor rated that user didn't for artist in neighborRatings: if not artist in userRatings: if artist not in recommendations: recommendations[artist] = neighborRatings[artist] * \ weight else: recommendations[artist] = recommendations[artist] + \ neighborRatings[artist] * \ weight # now make list from dictionary and only get the first n items recommendations = list(recommendations.items())[:self.n] recommendations = [(self.convertProductID2name(k), v) for (k, v) in recommendations] # finally sort and return recommendations.sort(key=lambda artistTuple: artistTuple[1], reverse=True) return recommendations

[ "eks5115@139.com" ]

eks5115@139.com

61937d51bfde6945241775ba8c469abe3cd44364

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/src/estimations/routes/estimations.py

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[]

no_license

arnulfojr/scrum-estimations-api

38f30dfcc31d8f0708e127b5187b8ff8b13862d1

5b9f645d99035982fd0affda42ec99485f0df46a

refs/heads/master

2023-05-10T23:03:23.815010

2021-05-26T13:13:57

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from http import HTTPStatus from typing import Tuple, Union from cerberus import Validator from flask import jsonify, make_response, request from estimations import schemas from users.models import User from ..app import estimations_app from ..exc import EmptyIdentifier, InvalidRequest, ValueNotFound from ..models import ( Estimation, Sequence, Session, Task, Value, ) @estimations_app.route('/sessions/<session_id>/tasks/<task_id>/estimations', methods=['GET']) def get_estimations(session_id: str, task_id: str): """Get the tasks' estimations. --- tags: - Tasks - Estimations parameters: - in: path name: session_id type: string format: uuid required: True - in: path name: task_id type: string required: True definitions: Estimations: type: array items: $ref: '#/definitions/Estimation' Estimation: type: object properties: value: $ref: '#/definitions/Value' task: $ref: '#/definitions/TaskWithoutSession' user: $ref: '#/definitions/UserWithoutOrganization' created_at: type: string format: datetime responses: 200: description: Task estimations schema: $ref: '#/definitions/Estimations' 404: description: The session or task were not found schema: $ref: '#/definitions/NotFound' """ session, task = get_or_fail(session_id, task_id) payload = [estimation.dump(with_task=False) for estimation in task.estimations] return make_response(jsonify(payload), HTTPStatus.OK) @estimations_app.route('/sessions/<session_id>/tasks/<task_id>/estimations/', methods=['PUT']) def estimate(session_id: str, task_id: str): """Estimate a task. --- tags: - Estimations - Tasks parameters: - in: path name: session_id type: string format: uuid required: True - in: path name: task_id type: string required: True - in: body name: body required: True schema: type: object properties: value: type: object description: 'Only one of the attributes is required. If all given the first priority is the id, then the value and the name at the end.' properties: id: type: string format: uuid description: Provide only one of these name: type: string example: Coffee Break description: Provide only one of these value: type: number format: float example: 2.0 description: Provide only one of these user: type: object properties: id: type: string format: uuid responses: 200: description: The estimation was updated schema: $ref: '#/definitions/Estimation' 201: description: The estimation was created schema: $ref: '#/definitions/Estimation' 400: description: Bad request input schema: $ref: '#/definitions/ValidationErrors' 404: description: The session or task were not found schema: $ref: '#/definitions/NotFound' """ session, task = get_or_fail(session_id, task_id) payload = request.get_json() validator = Validator() if not validator.validate(payload, schemas.CREATE_ESTIMATION): return make_response(jsonify(validator.errors), HTTPStatus.BAD_REQUEST) # FIXME: move the user to the authentication layer user_id = payload['user']['id'] user = User.lookup(user_id) if not user.belongs_to_organization(session.organization): return make_response(jsonify({ 'message': f'This user({user_id}) seems to not be part of the organization\'s session', }), HTTPStatus.UNAUTHORIZED) value_payload = payload['value'] sequence: Sequence = session.sequence if 'id' in value_payload: value = Value.lookup(value_payload['id']) elif 'value' in value_payload: value = sequence.get_value_for_numeric_value(value_payload['value']) elif 'name' in value_payload: value = sequence.get_value_for_value_name(value_payload['name']) else: value = None if not value: raise ValueNotFound('The Value given did not contain a value from the sequence') # did the user already estimated? estimation = Estimation.lookup(task, user) if not estimation: estimation = Estimation(value=value, user=user, task=task) estimation.save(force_insert=True) http_status_code = HTTPStatus.CREATED else: estimation.value = value estimation.save() http_status_code = HTTPStatus.OK return make_response( jsonify(estimation.dump()), http_status_code, ) @estimations_app.route('/sessions/<session_id>/tasks/<task_id>/summary', methods=['GET']) def get_task_summary(session_id: str, task_id: str): """Get the summary of the task. --- tags: - Tasks - Estimations parameters: - in: path name: session_id type: string format: uuid required: True - in: path name: task_id type: string required: True definitions: RuntimeSummary: type: object properties: mean: type: number format: float example: 2.5 description: The task's mean everybody_estimated: type: boolean description: true if all the session members had estimated consensus_met: type: boolean description: If everybody voted for the same value closest_value: $ref: '#/definitions/Value' task: $ref: '#/definitions/TaskWithoutSession' has_non_numeric_estimations: type: boolean description: If somebody voted for a value that does not have a numeric representation non_numeric_estimations: type: array items: $ref: '#/definitions/Estimation' responses: 200: description: Get the task's summary schema: $ref: '#/definitions/RuntimeSummary' 404: description: Task or session were not found schema: $ref: '#/definitions/NotFound' """ session, task = get_or_fail(session_id, task_id) mean_estimation = task.mean_estimation everybody_estimated = task.is_estimated_by_all_members consensus_met = task.consensus_met and everybody_estimated closest_value = session.sequence.closest_possible_value(mean_estimation) non_numeric_estimations = [estimation.dump(with_task=False) for estimation in task.non_numeric_estimations] return make_response(jsonify({ 'mean': float(mean_estimation), 'everybody_estimated': everybody_estimated, 'consensus_met': consensus_met, 'closest_value': closest_value.dump() if closest_value else 0, 'task': task.dump(with_session=False, with_estimations=True), 'has_non_numeric_estimations': task.has_non_numeric_estimations(), 'non_numeric_estimations': non_numeric_estimations, }), HTTPStatus.OK) def get_or_fail(session_id: Union[str, None], task_id: Union[str, None]) -> Tuple[Session, Task]: """Gets the session and task based on their identifiers.""" if not session_id: raise EmptyIdentifier('Please provide a session identifier') if not task_id: raise EmptyIdentifier('Please provide a valid task identifier') session = Session.lookup(session_id) try: task = Task.lookup(task_id, session=session) except (TypeError, ValueError) as e: raise InvalidRequest('We could not infer the Task from the given input...') from e else: return session, task

[ "arnulfojr94@gmail.com" ]

arnulfojr94@gmail.com

77a600b8a161271244c70a072a2ad68e0c19c0f9

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/开班笔记/个人项目/weather/venv/Scripts/pip3-script.py

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[]

no_license

jiyabing/learning

abd82aa3fd37310b4a98b11ea802c5b0e37b7ad9

6059006b0f86aee9a74cfc116d2284eb44173f41

refs/heads/master

2020-04-02T20:47:33.025331

2018-10-26T05:46:10

154,779,387

0

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GB18030

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py

#!E:\学习文件\python学习资料\开班笔记\个人项目\weather\venv\Scripts\python.exe -x # EASY-INSTALL-ENTRY-SCRIPT: 'pip==10.0.1','console_scripts','pip3' __requires__ = 'pip==10.0.1' import re import sys from pkg_resources import load_entry_point if __name__ == '__main__': sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0]) sys.exit( load_entry_point('pip==10.0.1', 'console_scripts', 'pip3')() )

[ "yabing_ji@163.com" ]

yabing_ji@163.com

c7ebb944709b1acfb824b0d6ecea1065b462c1a3

79588ca7cc97b19940101b69e82e562921f9c254

/Lab/bibtex.py

5a3af0cccbebb0729d0b05df3dee0b43a53694fd

[]

no_license

Yifan-Liu-95/SoftwareTestingPandas

1c40761da518ec5a639def28342b3c0af57b2adc

3030fb6ffe8e26d5491fd0156e0c79c50be6cfde

refs/heads/main

2023-05-01T11:16:49.142108

2020-12-16T09:57:06

null

0

null

UTF-8

Python

false

586

py

def extract_author(str): commaSplit = str.split(',') if len(commaSplit) == 1: spaceSplit = str.split(' ') if len(spaceSplit) == 1: result = (str,'') else: result = (spaceSplit[len(spaceSplit)-1],' '.join(spaceSplit[0:(len(spaceSplit)-1)])) else: result = (commaSplit[0], commaSplit[1].strip()) return result def extract_authors(str): andSplit = str.split('and') result = len(andSplit)*[None] for i in range(len(andSplit)): result[i] = extract_author(andSplit[i].strip()) return result

[ "36402231+dannemarre@users.noreply.github.com" ]

36402231+dannemarre@users.noreply.github.com

4ad7c781ebb466cdf938c49be828e1efbcf43234

e8da76ed3458cc3589c6e02a7088550c799651ac

/8lesson/area_circle.py

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[]

no_license

leilahassan/introduction-python-leila

9a8ff8d2d3818c5a3beec15f3a6da9492480faa5

fa86b12e7ff6d2804854c1a17af20dc7a28e4df7

refs/heads/master

2021-01-01T18:13:19.670649

2017-07-25T07:36:45

98,277,540

0

null

UTF-8

Python

false

305

py

import math def area_circle(radius): radius = int(radius) area = math.pi * radius * radius return area user_radius = input("What is the radius of the circle?:") calculated_area = area_circle(user_radius) print("The area of a circle with radius {} is {}".format(user_radius,calculated_area))

[ "hassanleila333@gmail.com" ]

hassanleila333@gmail.com

410d7498c362b982e00c1371ea8e80ffedc787f5

2ecfe0e10d10513917e4f2770e0a56075404c5d8

/oldnumba/tests/test_exceptions.py

80cbe4e56325c6d8248dd39bfb2723c2511aeeb1

[ "BSD-2-Clause" ]

permissive

laserson/numba

84ab7615ea0177b496a63e2a86319f0b12992cd2

35546517b27764a9120f6dfcd82eba7f4dd858cb

refs/heads/master

2020-05-20T23:13:23.011971

2014-12-08T20:16:20

16,754,385

1

0

null

UTF-8

Python

false

632

py

""" >>> boom() Traceback (most recent call last): ... ValueError: invalid literal for int() with base 10: 'boom' >>> boom2() Traceback (most recent call last): ... TypeError: 'object' object is not callable >>> boom3() Traceback (most recent call last): ... TypeError: 'object' object is not callable """ import sys import ctypes from numba import * import numpy as np @autojit(backend='ast') def boom(): return int('boom') @jit(int_()) def boom2(): return object()('boom') @jit(complex128()) def boom3(): return object()('boom') if __name__ == "__main__": import numba numba.testing.testmod()

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from datacenter.models import Passcard from datacenter.models import Visit from django.shortcuts import render def active_passcards_view(request): all_passcards = Passcard.objects.all() active_passcards = Passcard.objects.filter(is_active=True).all() context = { "active_passcards": active_passcards, # люди с активными пропусками } return render(request, 'active_passcards.html', context)

[ "kirill-yablunovskii@mail.ru" ]

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/2020/09September/26PandasDataSeries02.py

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June-fu/python365

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#!/usr/local/bin/python # -*- coding: utf-8 -*- ''' # @ Author: june-fu # @ Create Time: 2020-11-20 23:22:57 # @ Modified by: june-fu # @ Modified time: 2020-11-20 23:23:25 # @ Description: # 2.Write a Pandas program to convert a Panda module Series to Python list and it's type ''' import pandas as pd import numpy as np s = pd.Series(np.arange(10)) print(s) list1= s.to_list() print(list1) print(type(list1))

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mouseProgrammouse/neighborhood_map

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2020-03-21T00:40:18.616868

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import json import os from flask import Flask from yelpapi import YelpAPI from flask import request from flask.json import jsonify from flask_cors import CORS yelp_api = YelpAPI("7LgYxOlDAZm3sQI3jcyxuDnX2KCI1apQAMZkgB1qDlIpjYQgCr-yZ2q1Abeu7C5dE8kxCrPtjbTY_p29v2b2fosjP8evmheO4hDuEoHEkOheEqBBXX5t-Bp8ogYtW3Yx") app = Flask(__name__) CORS(app) def read_json(filename): with open(os.path.join(os.path.dirname(os.path.abspath(__file__)), filename), 'r') as f: return json.loads(f.read()) @app.route("/search") def search_yelp(): term = request.args.get('term') lat = request.args.get('lat') lng = request.args.get('lng') loc = request.args.get('loc') radius = request.args.get('radius') return jsonify(yelp_api.search_query(term=term, latitude=lat, longitude=lng, location=loc, radius=radius)) @app.route("/get_locations") def get_locations(): return jsonify(read_json("backendLocations.json")) @app.route("/get_details") def get_details(): business_id = request.args.get('id') return jsonify(yelp_api.business_query(id=business_id)) if __name__ == '__main__': app.run(host='127.0.0.1', port=5959)

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mouse.programmouse@gmail.com

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/monitor_sdk/model/notify/operation_log_with_meta_pb2.pyi

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easyopsapis/easyops-api-python

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2020-06-26T23:38:27.308803

2020-06-16T07:25:41

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# @generated by generate_proto_mypy_stubs.py. Do not edit! import sys from google.protobuf.descriptor import ( Descriptor as google___protobuf___descriptor___Descriptor, ) from google.protobuf.message import ( Message as google___protobuf___message___Message, ) from monitor_sdk.model.notify.operation_log_pb2 import ( OperationLog as monitor_sdk___model___notify___operation_log_pb2___OperationLog, ) from typing import ( Optional as typing___Optional, Text as typing___Text, Union as typing___Union, ) from typing_extensions import ( Literal as typing_extensions___Literal, ) builtin___bool = bool builtin___bytes = bytes builtin___float = float builtin___int = int if sys.version_info < (3,): builtin___buffer = buffer builtin___unicode = unicode class OperationLogWithMeta(google___protobuf___message___Message): DESCRIPTOR: google___protobuf___descriptor___Descriptor = ... system = ... # type: typing___Text topic = ... # type: typing___Text @property def data(self) -> monitor_sdk___model___notify___operation_log_pb2___OperationLog: ... def __init__(self, *, system : typing___Optional[typing___Text] = None, topic : typing___Optional[typing___Text] = None, data : typing___Optional[monitor_sdk___model___notify___operation_log_pb2___OperationLog] = None, ) -> None: ... if sys.version_info >= (3,): @classmethod def FromString(cls, s: builtin___bytes) -> OperationLogWithMeta: ... else: @classmethod def FromString(cls, s: typing___Union[builtin___bytes, builtin___buffer, builtin___unicode]) -> OperationLogWithMeta: ... def MergeFrom(self, other_msg: google___protobuf___message___Message) -> None: ... def CopyFrom(self, other_msg: google___protobuf___message___Message) -> None: ... def HasField(self, field_name: typing_extensions___Literal[u"data",b"data"]) -> builtin___bool: ... def ClearField(self, field_name: typing_extensions___Literal[u"data",b"data",u"system",b"system",u"topic",b"topic"]) -> None: ...

[ "service@easyops.cn" ]

service@easyops.cn

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/api/allergen/admin.py

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dducluzeaud/Allergen

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from django.contrib import admin from django.contrib.auth.admin import UserAdmin from django.contrib.auth.models import User from .models import ( Additive, Allergen, Category, Ingredient, Nutriment, NutrimentComposeProduct, Product, Trace, Vitamin, VitaminComposeProduct, Profile, ) class CategoryInline(admin.TabularInline): model = Product.categories.through extra = 0 verbose_name_plural = "Categories" class AdditiveInline(admin.TabularInline): model = Product.additives.through extra = 0 verbose_name_plural = "Additifs" class VitaminInline(admin.TabularInline): model = VitaminComposeProduct extra = 0 verbose_name_plural = "Vitamines" class NutrimentInline(admin.TabularInline): model = NutrimentComposeProduct extra = 0 verbose_name_plural = "Nutriments" class IngredientInline(admin.TabularInline): model = Product.ingredients.through extra = 0 verbose_name_plural = "Ingrédients" class AllergenInline(admin.TabularInline): model = Product.allergens.through extra = 0 verbose_name_plural = "Allergènes" class TraceInline(admin.TabularInline): model = Product.traces.through extra = 0 verbose_name_plural = "Traces" class ProfileInline(admin.StackedInline): model = Profile can_delete = False verbose_name_plural = 'Profile' fk_name = 'user' @admin.register(Product) class ProductAdmin(admin.ModelAdmin): list_display = ("product_name", "barcode", "nutrition_grade") fields = ("product_name", "image_url", "url_off", "barcode", "nutrition_grade") inlines = [ CategoryInline, AdditiveInline, VitaminInline, NutrimentInline, IngredientInline, AllergenInline, TraceInline, ] search_fields = ("product_name", "barcode") list_filter = ["nutrition_grade"] def get_readonly_fields(self, request, obj=None): if obj: # editing existing object return self.readonly_fields + ( "product_name", "image_url", "url_off", "barcode", "nutrition_grade", ) return self.readonly_fields @admin.register(Category) class CategoryAdmin(admin.ModelAdmin): ordering = ("category_name",) @admin.register(Additive) class AdditiveAdmin(admin.ModelAdmin): fields = ("additive_name", "description", "risk", "max_permissible_dose") ordering = ("additive_name",) # if an additive already exist we don't want to modify it def get_readonly_fields(self, request, obj=None): if obj: # editing existing object return self.readonly_fields + ("additive_name",) return self.readonly_fields @admin.register(Vitamin) class VitaminAdmin(admin.ModelAdmin): fields = ("vitamin_name", "description", ("daily_quantity_m", "daily_quantity_f")) ordering = ("vitamin_name",) @admin.register(Nutriment) class NutrimentAdmin(admin.ModelAdmin): fields = ('nutriment_name', 'description', 'image', ('daily_quantity_m', 'daily_quantity_f')) ordering = ('nutriment_name',) @admin.register(Ingredient) class IngredientAdmin(admin.ModelAdmin): fields = ("ingredient_name",) ordering = ("ingredient_name",) @admin.register(Allergen) class AllergenAdmin(admin.ModelAdmin): fields = ("allergen_name",) ordering = ("allergen_name",) @admin.register(Trace) class TraceAdmin(admin.ModelAdmin): fields = ("name",) ordering = ("name",) class CustomUserAdmin(UserAdmin): inlines = (ProfileInline,) def get_inline_instances(self, request, obj=None): if not obj: return list() return super(CustomUserAdmin, self).get_inline_instances(request, obj) admin.site.unregister(User) admin.site.register(User, CustomUserAdmin)

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david.ducluzeaud@live.fr

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/backup/user_337/ch8_2020_03_02_19_15_37_237019.py

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gabriellaec/desoft-analise-exercicios

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def calcula_posicao(tempo): posicao = posição inicial + velocidade*(instante t) return posicao

[ "you@example.com" ]

you@example.com

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/tensorflow/mnist/tensorflow-mnist.py

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[]

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jjjhai/Python

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refs/heads/master

2020-03-07T13:52:37.316600

2019-04-30T11:02:35

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# -*- coding: utf-8 -*- """ Created on Mon Jun 25 20:44:01 2018 @author: Administrator """ import input_data mnist = input_data.read_data_sets("MNIST_data/", one_hot=True) import tensorflow as tf x = tf.placeholder("float", [None, 784]) W = tf.Variable(tf.zeros([784,10])) b = tf.Variable(tf.zeros([10])) y = tf.nn.softmax(tf.matmul(x,W) + b) # 计算成本函数：交叉熵 # 计算损失 y_ = tf.placeholder("float", [None,10]) #累加( 实际值*log(预测值) ) cross_entropy = -tf.reduce_sum(y_*tf.log(y)) train_step = tf.train.GradientDescentOptimizer(0.01).minimize(cross_entropy) init = tf.global_variables_initializer() sess = tf.Session() sess.run(init) # 随机梯度下降训练 for i in range(1000): batch_xs, batch_ys = mnist.train.next_batch(100) print(sess.run([train_step, cross_entropy], feed_dict={x: batch_xs, y_: batch_ys})) # argmax找最大值，参数二为纬度，在第二纬度 correct_prediction = tf.equal(tf.argmax(y,1), tf.argmax(y_,1)) # cast类型转换 # reduce_mean求平均值 accuracy = tf.reduce_mean(tf.cast(correct_prediction, "float")) print(sess.run(accuracy, feed_dict={x: mnist.test.images, y_: mnist.test.labels})) sess.close()

[ "1520997976@qq.com" ]

1520997976@qq.com

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/Práctica 7/p7.12a.cuenta.palabras.py

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no_license

a-valado/python

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2020-08-28T02:51:48.745396

2019-11-06T17:50:45

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#Albert Valado Pujol #Práctica 7 - Ejercico 12a #Escribir un programa que lea una frase, #y pase ésta como parámetro a una función que debe contar el número de palabras que contiene. #Debe imprimir el programa principal el resultado. #Asumir que cada palabra está separada por un solo blanco: print("Este programa cuenta el número de palabras de una frase.") frase=input("Introduzca la frase.\n") def cuentaPalabras(a): lista=a.split(" ") numero=len(lista) return numero print("La frase tiene", cuentaPalabras(frase)," palabras.") input()

[ "avalado@cifpfbmoll.eu" ]

avalado@cifpfbmoll.eu

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/strings/zeroMatrix.py

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[]

no_license

roncrisostomo/CrackingTheCodingInterview

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2020-03-27T17:24:13.376234

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def zeroMatrix(m): """ m: a matrix If element in m x n matrix is zero, sets entire row and column to zero e.g. 1 2 3 1 2 0 4 5 0 -> 0 0 0 7 8 9 7 8 0 Modifies matrix m Returns nothing """ # Approach: Iterate over all elements of matrix, add row and column indices # of zero-value elements to lists, then iterate over each list, setting # all values in the row/column index to zero--O(m*n) rowsToZero = [] colsToZero = [] # Find zeroes in matrix for rowNo in range(len(m)): for colNo in range(len(m[rowNo])): # If zero, add row and column indices to lists if m[rowNo][colNo] == 0: if rowNo not in rowsToZero: rowsToZero.append(rowNo) if colNo not in colsToZero: colsToZero.append(colNo) # Set elements in rows/columns with listed indices to zero for rowNo in rowsToZero: for colNo in range(len(m[rowNo])): m[rowNo][colNo] = 0 for colNo in colsToZero: for rowNo in range(len(m)): # Catch cases when matrix is jagged, or rows have different lengths if colNo < len(m[rowNo]): m[rowNo][colNo] = 0 #m = [[1, 2, 3], [4, 5, 0], [7, 8, 9]] # Ans: [[1, 2, 0], [0, 0, 0], [7, 8, 0]] #m = [[0, 2, 3], [4, 5, 0], [7, 8, 9]] # Ans: [[0, 0, 0], [0, 0, 0], [0, 8, 0]] #m = [[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 0]] # Ans: [[1, 2, 0, 4], [5, 6, 0, 8], [0, 0, 0]] m = [[1, 0, 3, 4], [5, 0, 7, 8], [9, 10, 11, 12]] # Ans: [[0, 0, 0, 0], [0, 0, 0, 0], [9, 0, 11, 12]] zeroMatrix(m) print(m)

[ "rlcrisostomo06@gmail.com" ]

rlcrisostomo06@gmail.com

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/test_igseq/test_colors.py

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ShawHahnLab/igseq

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2023-04-28T09:03:09.404590

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from igseq import colors from .util import TestBase class TestColors(TestBase): """Tests for color-related helper functions.""" TRIOS = [ ([255, 0, 0], "#ff0000"), ([0, 0, 0], "#000000"), ([0, 136, 0], "#008800"), ([255, 255, 255], "#ffffff"), ] TEXTS = [ ("#ff0000", [255, 0, 0]), ("#FF0000", [255, 0, 0]), ("FF0000", [255, 0, 0]), ("#008800", [0, 136, 0]), ("#f00", [255, 0, 0]), ("#F00", [255, 0, 0]), ("#080", [0, 136, 0]), ("f00", [255, 0, 0]), ] SCALES = [ # Two colors averaged, no scaling (([[255, 0, 0], [0, 0, 255]], 0), [127, 0, 127]), # Two colors averaged, of 2 total, scales to black (([[255, 0, 0], [0, 0, 255]], 2), [0, 0, 0]), # one color of two, stays the same (([[255, 0, 0]], 2), [255, 0, 0]), # no colors = black by definition (([], 0), [0, 0, 0]), (([], 2), [0, 0, 0]), # two colors of three, averaged + scaled (([[255, 0, 0], [0, 0, 255]], 3), [91, 0, 91]), ] def test_merge_colors(self): """Test blending colors together.""" for case in self.__class__.SCALES: with self.subTest(case=case): self.assertEqual(colors.merge_colors(case[0][0], case[0][1]), case[1]) def test_color_str_to_trio(self): """Test converting color text codes to integer trios.""" for case in self.__class__.TEXTS: with self.subTest(case=case): self.assertEqual(colors.color_str_to_trio(case[0]), case[1]) def test_color_trio_to_str(self): """Test converting integer trios to color text codes.""" for case in self.__class__.TRIOS: with self.subTest(case=case): self.assertEqual(colors.color_trio_to_str(case[0]), case[1])

[ "ancon@upenn.edu" ]

ancon@upenn.edu

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/test/test_put_order_action_trigger_dates_request_type_order_actions.py

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moderndatainc/zuora-client

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2021-09-21T19:17:34.752404

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# coding: utf-8 """ Zuora API Reference # Introduction Welcome to the reference for the Zuora REST API! <a href=\"http://en.wikipedia.org/wiki/REST_API\" target=\"_blank\">REST</a> is a web-service protocol that lends itself to rapid development by using everyday HTTP and JSON technology. The Zuora REST API provides a broad set of operations and resources that: * Enable Web Storefront integration from your website. * Support self-service subscriber sign-ups and account management. * Process revenue schedules through custom revenue rule models. * Enable manipulation of most objects in the Zuora Object Model. Want to share your opinion on how our API works for you? <a href=\"https://community.zuora.com/t5/Developers/API-Feedback-Form/gpm-p/21399\" target=\"_blank\">Tell us how you feel </a>about using our API and what we can do to make it better. ## Access to the API If you have a Zuora tenant, you can access the Zuora REST API via one of the following endpoints: | Tenant | Base URL for REST Endpoints | |-------------------------|-------------------------| |US Production | https://rest.zuora.com | |US API Sandbox | https://rest.apisandbox.zuora.com| |US Performance Test | https://rest.pt1.zuora.com | |EU Production | https://rest.eu.zuora.com | |EU Sandbox | https://rest.sandbox.eu.zuora.com | The Production endpoint provides access to your live user data. API Sandbox tenants are a good place to test code without affecting real-world data. If you would like Zuora to provision an API Sandbox tenant for you, contact your Zuora representative for assistance. **Note:** If you have a tenant in the Production Copy Environment, submit a request at <a href=\"http://support.zuora.com/\" target=\"_blank\">Zuora Global Support</a> to enable the Zuora REST API in your tenant and obtain the base URL for REST endpoints. If you do not have a Zuora tenant, go to <a href=\"https://www.zuora.com/resource/zuora-test-drive\" target=\"_blank\">https://www.zuora.com/resource/zuora-test-drive</a> and sign up for a Production Test Drive tenant. The tenant comes with seed data, including a sample product catalog. # API Changelog You can find the <a href=\"https://community.zuora.com/t5/Developers/API-Changelog/gpm-p/18092\" target=\"_blank\">Changelog</a> of the API Reference in the Zuora Community. # Authentication ## OAuth v2.0 Zuora recommends that you use OAuth v2.0 to authenticate to the Zuora REST API. Currently, OAuth is not available in every environment. See [Zuora Testing Environments](https://knowledgecenter.zuora.com/BB_Introducing_Z_Business/D_Zuora_Environments) for more information. Zuora recommends you to create a dedicated API user with API write access on a tenant when authenticating via OAuth, and then create an OAuth client for this user. See <a href=\"https://knowledgecenter.zuora.com/CF_Users_and_Administrators/A_Administrator_Settings/Manage_Users/Create_an_API_User\" target=\"_blank\">Create an API User</a> for how to do this. By creating a dedicated API user, you can control permissions of the API user without affecting other non-API users. If a user is deactivated, all of the user's OAuth clients will be automatically deactivated. Authenticating via OAuth requires the following steps: 1. Create a Client 2. Generate a Token 3. Make Authenticated Requests ### Create a Client You must first [create an OAuth client](https://knowledgecenter.zuora.com/CF_Users_and_Administrators/A_Administrator_Settings/Manage_Users#Create_an_OAuth_Client_for_a_User) in the Zuora UI. To do this, you must be an administrator of your Zuora tenant. This is a one-time operation. You will be provided with a Client ID and a Client Secret. Please note this information down, as it will be required for the next step. **Note:** The OAuth client will be owned by a Zuora user account. If you want to perform PUT, POST, or DELETE operations using the OAuth client, the owner of the OAuth client must have a Platform role that includes the \"API Write Access\" permission. ### Generate a Token After creating a client, you must make a call to obtain a bearer token using the [Generate an OAuth token](https://www.zuora.com/developer/api-reference/#operation/createToken) operation. This operation requires the following parameters: - `client_id` - the Client ID displayed when you created the OAuth client in the previous step - `client_secret` - the Client Secret displayed when you created the OAuth client in the previous step - `grant_type` - must be set to `client_credentials` **Note**: The Client ID and Client Secret mentioned above were displayed when you created the OAuth Client in the prior step. The [Generate an OAuth token](https://www.zuora.com/developer/api-reference/#operation/createToken) response specifies how long the bearer token is valid for. Call [Generate an OAuth token](https://www.zuora.com/developer/api-reference/#operation/createToken) again to generate a new bearer token. ### Make Authenticated Requests To authenticate subsequent API requests, you must provide a valid bearer token in an HTTP header: `Authorization: Bearer {bearer_token}` If you have [Zuora Multi-entity](https://www.zuora.com/developer/api-reference/#tag/Entities) enabled, you need to set an additional header to specify the ID of the entity that you want to access. You can use the `scope` field in the [Generate an OAuth token](https://www.zuora.com/developer/api-reference/#operation/createToken) response to determine whether you need to specify an entity ID. If the `scope` field contains more than one entity ID, you must specify the ID of the entity that you want to access. For example, if the `scope` field contains `entity.1a2b7a37-3e7d-4cb3-b0e2-883de9e766cc` and `entity.c92ed977-510c-4c48-9b51-8d5e848671e9`, specify one of the following headers: - `Zuora-Entity-Ids: 1a2b7a37-3e7d-4cb3-b0e2-883de9e766cc` - `Zuora-Entity-Ids: c92ed977-510c-4c48-9b51-8d5e848671e9` **Note**: For a limited period of time, Zuora will accept the `entityId` header as an alternative to the `Zuora-Entity-Ids` header. If you choose to set the `entityId` header, you must remove all \"-\" characters from the entity ID in the `scope` field. If the `scope` field contains a single entity ID, you do not need to specify an entity ID. ## Other Supported Authentication Schemes Zuora continues to support the following additional legacy means of authentication: * Use username and password. Include authentication with each request in the header: * `apiAccessKeyId` * `apiSecretAccessKey` Zuora recommends that you create an API user specifically for making API calls. See <a href=\"https://knowledgecenter.zuora.com/CF_Users_and_Administrators/A_Administrator_Settings/Manage_Users/Create_an_API_User\" target=\"_blank\">Create an API User</a> for more information. * Use an authorization cookie. The cookie authorizes the user to make calls to the REST API for the duration specified in **Administration > Security Policies > Session timeout**. The cookie expiration time is reset with this duration after every call to the REST API. To obtain a cookie, call the [Connections](https://www.zuora.com/developer/api-reference/#tag/Connections) resource with the following API user information: * ID * Password * For CORS-enabled APIs only: Include a 'single-use' token in the request header, which re-authenticates the user with each request. See below for more details. ### Entity Id and Entity Name The `entityId` and `entityName` parameters are only used for [Zuora Multi-entity](https://knowledgecenter.zuora.com/BB_Introducing_Z_Business/Multi-entity \"Zuora Multi-entity\"). These are the legacy parameters that Zuora will only continue to support for a period of time. Zuora recommends you to use the `Zuora-Entity-Ids` parameter instead. The `entityId` and `entityName` parameters specify the Id and the [name of the entity](https://knowledgecenter.zuora.com/BB_Introducing_Z_Business/Multi-entity/B_Introduction_to_Entity_and_Entity_Hierarchy#Name_and_Display_Name \"Introduction to Entity and Entity Hierarchy\") that you want to access, respectively. Note that you must have permission to access the entity. You can specify either the `entityId` or `entityName` parameter in the authentication to access and view an entity. * If both `entityId` and `entityName` are specified in the authentication, an error occurs. * If neither `entityId` nor `entityName` is specified in the authentication, you will log in to the entity in which your user account is created. To get the entity Id and entity name, you can use the GET Entities REST call. For more information, see [API User Authentication](https://knowledgecenter.zuora.com/BB_Introducing_Z_Business/Multi-entity/A_Overview_of_Multi-entity#API_User_Authentication \"API User Authentication\"). ### Token Authentication for CORS-Enabled APIs The CORS mechanism enables REST API calls to Zuora to be made directly from your customer's browser, with all credit card and security information transmitted directly to Zuora. This minimizes your PCI compliance burden, allows you to implement advanced validation on your payment forms, and makes your payment forms look just like any other part of your website. For security reasons, instead of using cookies, an API request via CORS uses **tokens** for authentication. The token method of authentication is only designed for use with requests that must originate from your customer's browser; **it should not be considered a replacement to the existing cookie authentication** mechanism. See [Zuora CORS REST](https://knowledgecenter.zuora.com/DC_Developers/REST_API/A_REST_basics/G_CORS_REST \"Zuora CORS REST\") for details on how CORS works and how you can begin to implement customer calls to the Zuora REST APIs. See [HMAC Signatures](https://www.zuora.com/developer/api-reference/#operation/POSTHMACSignature \"HMAC Signatures\") for details on the HMAC method that returns the authentication token. # Requests and Responses ## Request IDs As a general rule, when asked to supply a \"key\" for an account or subscription (accountKey, account-key, subscriptionKey, subscription-key), you can provide either the actual ID or the number of the entity. ## HTTP Request Body Most of the parameters and data accompanying your requests will be contained in the body of the HTTP request. The Zuora REST API accepts JSON in the HTTP request body. No other data format (e.g., XML) is supported. ### Data Type ([Actions](https://www.zuora.com/developer/api-reference/#tag/Actions) and CRUD operations only) We recommend that you do not specify the decimal values with quotation marks, commas, and spaces. Use characters of `+-0-9.eE`, for example, `5`, `1.9`, `-8.469`, and `7.7e2`. Also, Zuora does not convert currencies for decimal values. ## Testing a Request Use a third party client, such as [curl](https://curl.haxx.se \"curl\"), [Postman](https://www.getpostman.com \"Postman\"), or [Advanced REST Client](https://advancedrestclient.com \"Advanced REST Client\"), to test the Zuora REST API. You can test the Zuora REST API from the Zuora API Sandbox or Production tenants. If connecting to Production, bear in mind that you are working with your live production data, not sample data or test data. ## Testing with Credit Cards Sooner or later it will probably be necessary to test some transactions that involve credit cards. For suggestions on how to handle this, see [Going Live With Your Payment Gateway](https://knowledgecenter.zuora.com/CB_Billing/M_Payment_Gateways/C_Managing_Payment_Gateways/B_Going_Live_Payment_Gateways#Testing_with_Credit_Cards \"C_Zuora_User_Guides/A_Billing_and_Payments/M_Payment_Gateways/C_Managing_Payment_Gateways/B_Going_Live_Payment_Gateways#Testing_with_Credit_Cards\" ). ## Concurrent Request Limits Zuora enforces tenant-level concurrent request limits. See <a href=\"https://knowledgecenter.zuora.com/BB_Introducing_Z_Business/Policies/Concurrent_Request_Limits\" target=\"_blank\">Concurrent Request Limits</a> for more information. ## Timeout Limit If a request does not complete within 120 seconds, the request times out and Zuora returns a Gateway Timeout error. ## Error Handling Responses and error codes are detailed in [Responses and errors](https://knowledgecenter.zuora.com/DC_Developers/REST_API/A_REST_basics/3_Responses_and_errors \"Responses and errors\"). # Pagination When retrieving information (using GET methods), the optional `pageSize` query parameter sets the maximum number of rows to return in a response. The maximum is `40`; larger values are treated as `40`. If this value is empty or invalid, `pageSize` typically defaults to `10`. The default value for the maximum number of rows retrieved can be overridden at the method level. If more rows are available, the response will include a `nextPage` element, which contains a URL for requesting the next page. If this value is not provided, no more rows are available. No \"previous page\" element is explicitly provided; to support backward paging, use the previous call. ## Array Size For data items that are not paginated, the REST API supports arrays of up to 300 rows. Thus, for instance, repeated pagination can retrieve thousands of customer accounts, but within any account an array of no more than 300 rate plans is returned. # API Versions The Zuora REST API are version controlled. Versioning ensures that Zuora REST API changes are backward compatible. Zuora uses a major and minor version nomenclature to manage changes. By specifying a version in a REST request, you can get expected responses regardless of future changes to the API. ## Major Version The major version number of the REST API appears in the REST URL. Currently, Zuora only supports the **v1** major version. For example, `POST https://rest.zuora.com/v1/subscriptions`. ## Minor Version Zuora uses minor versions for the REST API to control small changes. For example, a field in a REST method is deprecated and a new field is used to replace it. Some fields in the REST methods are supported as of minor versions. If a field is not noted with a minor version, this field is available for all minor versions. If a field is noted with a minor version, this field is in version control. You must specify the supported minor version in the request header to process without an error. If a field is in version control, it is either with a minimum minor version or a maximum minor version, or both of them. You can only use this field with the minor version between the minimum and the maximum minor versions. For example, the `invoiceCollect` field in the POST Subscription method is in version control and its maximum minor version is 189.0. You can only use this field with the minor version 189.0 or earlier. If you specify a version number in the request header that is not supported, Zuora will use the minimum minor version of the REST API. In our REST API documentation, if a field or feature requires a minor version number, we note that in the field description. You only need to specify the version number when you use the fields require a minor version. To specify the minor version, set the `zuora-version` parameter to the minor version number in the request header for the request call. For example, the `collect` field is in 196.0 minor version. If you want to use this field for the POST Subscription method, set the `zuora-version` parameter to `196.0` in the request header. The `zuora-version` parameter is case sensitive. For all the REST API fields, by default, if the minor version is not specified in the request header, Zuora will use the minimum minor version of the REST API to avoid breaking your integration. ### Minor Version History The supported minor versions are not serial. This section documents the changes made to each Zuora REST API minor version. The following table lists the supported versions and the fields that have a Zuora REST API minor version. | Fields | Minor Version | REST Methods | Description | |:--------|:--------|:--------|:--------| | invoiceCollect | 189.0 and earlier | [Create Subscription](https://www.zuora.com/developer/api-reference/#operation/POST_Subscription \"Create Subscription\"); [Update Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_Subscription \"Update Subscription\"); [Renew Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_RenewSubscription \"Renew Subscription\"); [Cancel Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_CancelSubscription \"Cancel Subscription\"); [Suspend Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_SuspendSubscription \"Suspend Subscription\"); [Resume Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_ResumeSubscription \"Resume Subscription\"); [Create Account](https://www.zuora.com/developer/api-reference/#operation/POST_Account \"Create Account\")|Generates an invoice and collects a payment for a subscription. | | collect | 196.0 and later | [Create Subscription](https://www.zuora.com/developer/api-reference/#operation/POST_Subscription \"Create Subscription\"); [Update Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_Subscription \"Update Subscription\"); [Renew Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_RenewSubscription \"Renew Subscription\"); [Cancel Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_CancelSubscription \"Cancel Subscription\"); [Suspend Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_SuspendSubscription \"Suspend Subscription\"); [Resume Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_ResumeSubscription \"Resume Subscription\"); [Create Account](https://www.zuora.com/developer/api-reference/#operation/POST_Account \"Create Account\")|Collects an automatic payment for a subscription. | | invoice | 196.0 and 207.0| [Create Subscription](https://www.zuora.com/developer/api-reference/#operation/POST_Subscription \"Create Subscription\"); [Update Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_Subscription \"Update Subscription\"); [Renew Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_RenewSubscription \"Renew Subscription\"); [Cancel Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_CancelSubscription \"Cancel Subscription\"); [Suspend Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_SuspendSubscription \"Suspend Subscription\"); [Resume Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_ResumeSubscription \"Resume Subscription\"); [Create Account](https://www.zuora.com/developer/api-reference/#operation/POST_Account \"Create Account\")|Generates an invoice for a subscription. | | invoiceTargetDate | 196.0 and earlier | [Preview Subscription](https://www.zuora.com/developer/api-reference/#operation/POST_SubscriptionPreview \"Preview Subscription\") |Date through which charges are calculated on the invoice, as `yyyy-mm-dd`. | | invoiceTargetDate | 207.0 and earlier | [Create Subscription](https://www.zuora.com/developer/api-reference/#operation/POST_Subscription \"Create Subscription\"); [Update Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_Subscription \"Update Subscription\"); [Renew Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_RenewSubscription \"Renew Subscription\"); [Cancel Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_CancelSubscription \"Cancel Subscription\"); [Suspend Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_SuspendSubscription \"Suspend Subscription\"); [Resume Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_ResumeSubscription \"Resume Subscription\"); [Create Account](https://www.zuora.com/developer/api-reference/#operation/POST_Account \"Create Account\")|Date through which charges are calculated on the invoice, as `yyyy-mm-dd`. | | targetDate | 207.0 and later | [Preview Subscription](https://www.zuora.com/developer/api-reference/#operation/POST_SubscriptionPreview \"Preview Subscription\") |Date through which charges are calculated on the invoice, as `yyyy-mm-dd`. | | targetDate | 211.0 and later | [Create Subscription](https://www.zuora.com/developer/api-reference/#operation/POST_Subscription \"Create Subscription\"); [Update Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_Subscription \"Update Subscription\"); [Renew Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_RenewSubscription \"Renew Subscription\"); [Cancel Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_CancelSubscription \"Cancel Subscription\"); [Suspend Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_SuspendSubscription \"Suspend Subscription\"); [Resume Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_ResumeSubscription \"Resume Subscription\"); [Create Account](https://www.zuora.com/developer/api-reference/#operation/POST_Account \"Create Account\")|Date through which charges are calculated on the invoice, as `yyyy-mm-dd`. | | includeExisting DraftInvoiceItems | 196.0 and earlier| [Preview Subscription](https://www.zuora.com/developer/api-reference/#operation/POST_SubscriptionPreview \"Preview Subscription\"); [Update Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_Subscription \"Update Subscription\") | Specifies whether to include draft invoice items in subscription previews. Specify it to be `true` (default) to include draft invoice items in the preview result. Specify it to be `false` to excludes draft invoice items in the preview result. | | includeExisting DraftDocItems | 207.0 and later | [Preview Subscription](https://www.zuora.com/developer/api-reference/#operation/POST_SubscriptionPreview \"Preview Subscription\"); [Update Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_Subscription \"Update Subscription\") | Specifies whether to include draft invoice items in subscription previews. Specify it to be `true` (default) to include draft invoice items in the preview result. Specify it to be `false` to excludes draft invoice items in the preview result. | | previewType | 196.0 and earlier| [Preview Subscription](https://www.zuora.com/developer/api-reference/#operation/POST_SubscriptionPreview \"Preview Subscription\"); [Update Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_Subscription \"Update Subscription\") | The type of preview you will receive. The possible values are `InvoiceItem`(default), `ChargeMetrics`, and `InvoiceItemChargeMetrics`. | | previewType | 207.0 and later | [Preview Subscription](https://www.zuora.com/developer/api-reference/#operation/POST_SubscriptionPreview \"Preview Subscription\"); [Update Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_Subscription \"Update Subscription\") | The type of preview you will receive. The possible values are `LegalDoc`(default), `ChargeMetrics`, and `LegalDocChargeMetrics`. | | runBilling | 211.0 and later | [Create Subscription](https://www.zuora.com/developer/api-reference/#operation/POST_Subscription \"Create Subscription\"); [Update Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_Subscription \"Update Subscription\"); [Renew Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_RenewSubscription \"Renew Subscription\"); [Cancel Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_CancelSubscription \"Cancel Subscription\"); [Suspend Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_SuspendSubscription \"Suspend Subscription\"); [Resume Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_ResumeSubscription \"Resume Subscription\"); [Create Account](https://www.zuora.com/developer/api-reference/#operation/POST_Account \"Create Account\")|Generates an invoice or credit memo for a subscription. **Note:** Credit memos are only available if you have the Invoice Settlement feature enabled. | | invoiceDate | 214.0 and earlier | [Invoice and Collect](https://www.zuora.com/developer/api-reference/#operation/POST_TransactionInvoicePayment \"Invoice and Collect\") |Date that should appear on the invoice being generated, as `yyyy-mm-dd`. | | invoiceTargetDate | 214.0 and earlier | [Invoice and Collect](https://www.zuora.com/developer/api-reference/#operation/POST_TransactionInvoicePayment \"Invoice and Collect\") |Date through which to calculate charges on this account if an invoice is generated, as `yyyy-mm-dd`. | | documentDate | 215.0 and later | [Invoice and Collect](https://www.zuora.com/developer/api-reference/#operation/POST_TransactionInvoicePayment \"Invoice and Collect\") |Date that should appear on the invoice and credit memo being generated, as `yyyy-mm-dd`. | | targetDate | 215.0 and later | [Invoice and Collect](https://www.zuora.com/developer/api-reference/#operation/POST_TransactionInvoicePayment \"Invoice and Collect\") |Date through which to calculate charges on this account if an invoice or a credit memo is generated, as `yyyy-mm-dd`. | | memoItemAmount | 223.0 and earlier | [Create credit memo from charge](https://www.zuora.com/developer/api-reference/#operation/POST_CreditMemoFromPrpc \"Create credit memo from charge\"); [Create debit memo from charge](https://www.zuora.com/developer/api-reference/#operation/POST_DebitMemoFromPrpc \"Create debit memo from charge\") | Amount of the memo item. | | amount | 224.0 and later | [Create credit memo from charge](https://www.zuora.com/developer/api-reference/#operation/POST_CreditMemoFromPrpc \"Create credit memo from charge\"); [Create debit memo from charge](https://www.zuora.com/developer/api-reference/#operation/POST_DebitMemoFromPrpc \"Create debit memo from charge\") | Amount of the memo item. | | subscriptionNumbers | 222.4 and earlier | [Create order](https://www.zuora.com/developer/api-reference/#operation/POST_Order \"Create order\") | Container for the subscription numbers of the subscriptions in an order. | | subscriptions | 223.0 and later | [Create order](https://www.zuora.com/developer/api-reference/#operation/POST_Order \"Create order\") | Container for the subscription numbers and statuses in an order. | #### Version 207.0 and Later The response structure of the [Preview Subscription](https://www.zuora.com/developer/api-reference/#operation/POST_SubscriptionPreview \"Preview Subscription\") and [Update Subscription](https://www.zuora.com/developer/api-reference/#operation/PUT_Subscription \"Update Subscription\") methods are changed. The following invoice related response fields are moved to the invoice container: * amount * amountWithoutTax * taxAmount * invoiceItems * targetDate * chargeMetrics # Zuora Object Model The following diagram presents a high-level view of the key Zuora objects. Click the image to open it in a new tab to resize it. <a href=\"https://www.zuora.com/wp-content/uploads/2017/01/ZuoraERD.jpeg\" target=\"_blank\"><img src=\"https://www.zuora.com/wp-content/uploads/2017/01/ZuoraERD.jpeg\" alt=\"Zuora Object Model Diagram\"></a> See the following articles for information about other parts of the Zuora business object model: * <a href=\"https://knowledgecenter.zuora.com/CB_Billing/Invoice_Settlement/D_Invoice_Settlement_Object_Model\" target=\"_blank\">Invoice Settlement Object Model</a> * <a href=\"https://knowledgecenter.zuora.com/BC_Subscription_Management/Orders/BA_Orders_Object_Model\" target=\"_blank\">Orders Object Model</a> You can use the [Describe object](https://www.zuora.com/developer/api-reference/#operation/GET_Describe) operation to list the fields of each Zuora object that is available in your tenant. When you call the operation, you must specify the API name of the Zuora object. The following table provides the API name of each Zuora object: | Object | API Name | |-----------------------------------------------|--------------------------------------------| | Account | `Account` | | Accounting Code | `AccountingCode` | | Accounting Period | `AccountingPeriod` | | Amendment | `Amendment` | | Application Group | `ApplicationGroup` | | Billing Run | <p>`BillingRun`</p><p>**Note:** The API name of this object is `BillingRun` in the [Describe object](https://www.zuora.com/developer/api-reference/#operation/GET_Describe) operation and Export ZOQL queries only. Otherwise, the API name of this object is `BillRun`.</p> | | Contact | `Contact` | | Contact Snapshot | `ContactSnapshot` | | Credit Balance Adjustment | `CreditBalanceAdjustment` | | Credit Memo | `CreditMemo` | | Credit Memo Application | `CreditMemoApplication` | | Credit Memo Application Item | `CreditMemoApplicationItem` | | Credit Memo Item | `CreditMemoItem` | | Credit Memo Part | `CreditMemoPart` | | Credit Memo Part Item | `CreditMemoPartItem` | | Credit Taxation Item | `CreditTaxationItem` | | Custom Exchange Rate | `FXCustomRate` | | Debit Memo | `DebitMemo` | | Debit Memo Item | `DebitMemoItem` | | Debit Taxation Item | `DebitTaxationItem` | | Discount Applied Metrics | `DiscountAppliedMetrics` | | Entity | `Tenant` | | Gateway Reconciliation Event | `PaymentGatewayReconciliationEventLog` | | Gateway Reconciliation Job | `PaymentReconciliationJob` | | Gateway Reconciliation Log | `PaymentReconciliationLog` | | Invoice | `Invoice` | | Invoice Adjustment | `InvoiceAdjustment` | | Invoice Item | `InvoiceItem` | | Invoice Item Adjustment | `InvoiceItemAdjustment` | | Invoice Payment | `InvoicePayment` | | Journal Entry | `JournalEntry` | | Journal Entry Item | `JournalEntryItem` | | Journal Run | `JournalRun` | | Order | `Order` | | Order Action | `OrderAction` | | Order ELP | `OrderElp` | | Order Item | `OrderItem` | | Order MRR | `OrderMrr` | | Order Quantity | `OrderQuantity` | | Order TCB | `OrderTcb` | | Order TCV | `OrderTcv` | | Payment | `Payment` | | Payment Application | `PaymentApplication` | | Payment Application Item | `PaymentApplicationItem` | | Payment Method | `PaymentMethod` | | Payment Method Snapshot | `PaymentMethodSnapshot` | | Payment Method Transaction Log | `PaymentMethodTransactionLog` | | Payment Method Update | `UpdaterDetail` | | Payment Part | `PaymentPart` | | Payment Part Item | `PaymentPartItem` | | Payment Run | `PaymentRun` | | Payment Transaction Log | `PaymentTransactionLog` | | Processed Usage | `ProcessedUsage` | | Product | `Product` | | Product Rate Plan | `ProductRatePlan` | | Product Rate Plan Charge | `ProductRatePlanCharge` | | Product Rate Plan Charge Tier | `ProductRatePlanChargeTier` | | Rate Plan | `RatePlan` | | Rate Plan Charge | `RatePlanCharge` | | Rate Plan Charge Tier | `RatePlanChargeTier` | | Refund | `Refund` | | Refund Application | `RefundApplication` | | Refund Application Item | `RefundApplicationItem` | | Refund Invoice Payment | `RefundInvoicePayment` | | Refund Part | `RefundPart` | | Refund Part Item | `RefundPartItem` | | Refund Transaction Log | `RefundTransactionLog` | | Revenue Charge Summary | `RevenueChargeSummary` | | Revenue Charge Summary Item | `RevenueChargeSummaryItem` | | Revenue Event | `RevenueEvent` | | Revenue Event Credit Memo Item | `RevenueEventCreditMemoItem` | | Revenue Event Debit Memo Item | `RevenueEventDebitMemoItem` | | Revenue Event Invoice Item | `RevenueEventInvoiceItem` | | Revenue Event Invoice Item Adjustment | `RevenueEventInvoiceItemAdjustment` | | Revenue Event Item | `RevenueEventItem` | | Revenue Event Item Credit Memo Item | `RevenueEventItemCreditMemoItem` | | Revenue Event Item Debit Memo Item | `RevenueEventItemDebitMemoItem` | | Revenue Event Item Invoice Item | `RevenueEventItemInvoiceItem` | | Revenue Event Item Invoice Item Adjustment | `RevenueEventItemInvoiceItemAdjustment` | | Revenue Event Type | `RevenueEventType` | | Revenue Schedule | `RevenueSchedule` | | Revenue Schedule Credit Memo Item | `RevenueScheduleCreditMemoItem` | | Revenue Schedule Debit Memo Item | `RevenueScheduleDebitMemoItem` | | Revenue Schedule Invoice Item | `RevenueScheduleInvoiceItem` | | Revenue Schedule Invoice Item Adjustment | `RevenueScheduleInvoiceItemAdjustment` | | Revenue Schedule Item | `RevenueScheduleItem` | | Revenue Schedule Item Credit Memo Item | `RevenueScheduleItemCreditMemoItem` | | Revenue Schedule Item Debit Memo Item | `RevenueScheduleItemDebitMemoItem` | | Revenue Schedule Item Invoice Item | `RevenueScheduleItemInvoiceItem` | | Revenue Schedule Item Invoice Item Adjustment | `RevenueScheduleItemInvoiceItemAdjustment` | | Subscription | `Subscription` | | Taxable Item Snapshot | `TaxableItemSnapshot` | | Taxation Item | `TaxationItem` | | Updater Batch | `UpdaterBatch` | | Usage | `Usage` | # noqa: E501 OpenAPI spec version: 2018-08-23 Contact: docs@zuora.com Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import unittest import zuora_client from zuora_client.models.put_order_action_trigger_dates_request_type_order_actions import PUTOrderActionTriggerDatesRequestTypeOrderActions # noqa: E501 from zuora_client.rest import ApiException class TestPUTOrderActionTriggerDatesRequestTypeOrderActions(unittest.TestCase): """PUTOrderActionTriggerDatesRequestTypeOrderActions unit test stubs""" def setUp(self): pass def tearDown(self): pass def testPUTOrderActionTriggerDatesRequestTypeOrderActions(self): """Test PUTOrderActionTriggerDatesRequestTypeOrderActions""" # FIXME: construct object with mandatory attributes with example values # model = zuora_client.models.put_order_action_trigger_dates_request_type_order_actions.PUTOrderActionTriggerDatesRequestTypeOrderActions() # noqa: E501 pass if __name__ == '__main__': unittest.main()

[ "jairo.velasco@alertlogic.com" ]

jairo.velasco@alertlogic.com

457d79392860d7287c6190a1cddadcbd53f1995a

b26406a338263ec6cb6d9391bb628cba0fa9e37b

/summary_ranges.py

930ad9819e1bed87b1cafa1a49f2449508508f25

[]

no_license

nhiggins13/leetcode

096e27d9945439f6b26470a4712102f1c7f290d5

f949a09c6a9251dc167fd807b412b86d5344977f

refs/heads/main

2023-01-29T20:35:41.472210

2020-12-01T23:20:17

302,689,607

0

null

UTF-8

Python

false

759

py

class Solution: def summaryRanges(self, nums: List[int]) -> List[str]: if not nums: return start = nums[0] curr_index = 0 results = [] while (curr_index < len(nums) - 1): curr = nums[curr_index] nxt = nums[curr_index + 1] if nxt != curr + 1: if curr == start: results.append(str(start)) start = nxt else: results.append("%d->%d" % (start, curr)) start = nxt curr_index += 1 if start == nums[-1]: results.append(str(start)) else: results.append("%d->%d" % (start, nums[-1])) return results

[ "n.higgins1313@gmail.com" ]

n.higgins1313@gmail.com

d315787bb6b8a33384f02df4fd9358fc7f3ae68e

f359c953ef823cc44f7d87a3736c3e4fb1817c0b

/EDBRCommon/python/simulation/RunIIDR74X50ns/TTbar/TTaw.py

71536ff1fd213b3a0b0ae79234018df0b109d56f

[]

no_license

jruizvar/ExoDiBosonResonancesRun2

aa613200725cf6cd825d7bcbde60d2e39ba84e39

b407ab36504d0e04e6bddba4e57856f9f8c0ec66

refs/heads/Analysis76X

2021-01-18T20:00:57.358494

2016-05-30T21:30:19

23,619,682

1

null

2016-04-22T18:38:45

2014-09-03T12:41:07

Python

UTF-8

Python

false

1,426

py

import FWCore.ParameterSet.Config as cms maxEvents = cms.untracked.PSet( input = cms.untracked.int32(-1) ) readFiles = cms.untracked.vstring() secFiles = cms.untracked.vstring() source = cms.Source ("PoolSource",fileNames = readFiles, secondaryFileNames = secFiles) readFiles.extend( [ '/store/mc/RunIISpring15DR74/TT_TuneCUETP8M1_13TeV-powheg-pythia8/MINIAODSIM/Asympt50ns_MCRUN2_74_V9A-v4/60000/FAB076ED-590F-E511-B784-0CC47A4DEEBA.root', '/store/mc/RunIISpring15DR74/TT_TuneCUETP8M1_13TeV-powheg-pythia8/MINIAODSIM/Asympt50ns_MCRUN2_74_V9A-v4/60000/FC007331-5E0F-E511-8D0C-0025904B1424.root', '/store/mc/RunIISpring15DR74/TT_TuneCUETP8M1_13TeV-powheg-pythia8/MINIAODSIM/Asympt50ns_MCRUN2_74_V9A-v4/60000/FC9BEF1E-540F-E511-8740-002590E39F36.root', '/store/mc/RunIISpring15DR74/TT_TuneCUETP8M1_13TeV-powheg-pythia8/MINIAODSIM/Asympt50ns_MCRUN2_74_V9A-v4/60000/FCD4075D-6A0F-E511-AA8B-00259073E410.root', '/store/mc/RunIISpring15DR74/TT_TuneCUETP8M1_13TeV-powheg-pythia8/MINIAODSIM/Asympt50ns_MCRUN2_74_V9A-v4/60000/FEC4769D-6E0F-E511-8A65-0025907277E8.root', '/store/mc/RunIISpring15DR74/TT_TuneCUETP8M1_13TeV-powheg-pythia8/MINIAODSIM/Asympt50ns_MCRUN2_74_V9A-v4/60000/FECA6F36-360F-E511-8BA1-0CC47A13D09C.root', '/store/mc/RunIISpring15DR74/TT_TuneCUETP8M1_13TeV-powheg-pythia8/MINIAODSIM/Asympt50ns_MCRUN2_74_V9A-v4/60000/FED5EE4E-C910-E511-91E8-AC853D9DAC41.root' ] );

[ "jruizvar@cern.ch" ]

jruizvar@cern.ch

068db76603c5e98e0f06eb9aa9ea1e6671dd2e65

d0fb46fb2868089663a4af80ea27509b57f55fce

/puffy/views.py

1b8a20418d8d38cfa26fdf400597c4908599f185

[]

no_license

javad-hub/original-puffy

cb90e44d43b5fb391ce7e8686265f2cefddd3852

caac094d2a60d984d7a2747792a35d2c613148f5

refs/heads/main

2023-04-02T19:52:36.364479

2021-04-13T12:57:55

357,553,866

3

0

null

UTF-8

Python

false

293

py

from django.shortcuts import render from django.shortcuts import HttpResponse def about(request): # return HttpResponse('Hello this is puffy network') return render(request , 'About.html') def home(request): # return HttpResponse('Home') return render(request , 'Home.html')

[ "fasanehsepasian@gmail.com" ]

fasanehsepasian@gmail.com

8c739165a6e3e1ef886537f46b1820b695a7ead4

039bcc5f447bf636ff68fbfef9ba461c1aa6b7c9

/lab_4/ex1.py

b1b3897bd49feeaf3b6c5330060b3159273ee1b0

[ "MIT" ]

permissive

davve50/d0009e

06439363feeeac95a52b00d9ccf5d40b0042808c

3af55d7fc9dbdb085a27298961557a60f379b773

refs/heads/main

2023-02-22T00:00:31.703467

2021-01-22T09:13:21

317,813,418

0

null

2021-01-22T09:13:22

2020-12-02T09:34:25

Python

UTF-8

Python

false

2,352

py

def main(): temp = [] book = [] com = [] while True: ch = input("Phonebook> ") com = ch.split() if "add" in com: add(com,book,temp) elif "lookup" in com: lookup(com,book) elif "alias" in com: alias(com,book) elif "change" in com: change(com,book) elif "quit" in com: print("Exiting program...") break elif "save" in com: save(com,book) elif "load" in com: load(com,book) else: print("Enter a valid command!") def add(com,book,temp): for x in book: for y in x: if com[1] == y: print("User already exists!") break elif com[2] == y: print("Number already exists!") break else: temp = [com[1],com[2]] book.append(temp) def lookup(com,book): if(exist(book,com[1])): for x in book: for y in x: if com[1] == y: print(x[1]) break else: print("User not found!") def alias(com,book): if(exist(book,com[1])): if(exist(book,com[2])): print("User already exists!") else: for x in book: for y in x: if com[1] == y: x.append(com[2]) break else: print("User not found!") def change(com,book): if(exist(book,com[1])): for x in book: for y in x: if com[1] == y: x[1] = com[2] break else: print("User not found!") def save(com,book): f = open(com[1], "w") for i in book: for x in i: line = x + ";" f.write(line) f.write("\n") print("Saving...") f.close() def load(com,book): book.clear() f = open(com[1], "r") for line in f: line = line.split(";") line = line[:-1] book.append(line) print("Loading...") f.close() def exist(book,user): for i in book: for x in i: if user == x: return True else: return False if __name__ == "__main__": main()

[ "davarv-7@student.ltu.se" ]

davarv-7@student.ltu.se

3e36c235549137785ce9d51fb36ee188d100364d

bbe7132e45134d015cd96f7ad10f7fd379b8112f

/Functions/TrainingDataCollection/CollectingData_Guided.py

0ed542957cc49c9e5f73e051ff18ec186eacab3b

[]

no_license

lxb1989/DeepClawBenchmark

e8dc770eabe813f87298e3ce9482b1f256f5f331

3f955c9faf82c7c2f20ed8165ef6eb80d1db564d

refs/heads/master

2020-08-25T07:08:50.035336

2019-10-22T09:35:19

216,980,575

0

null

2019-10-23T06:06:27

null

UTF-8

Python

false

3,149

py

import sys sys.path.append('/home/yang/python-urx') sys.path.append('/home/yang/Git/CobotBenchmark/Driver') sys.path.append('/home/yang/Git/CobotBenchmark/Functions') sys.path.append('/home/yang/Git/CobotBenchmark/ToolKit') from fc_predictor import Predictor from realsense_controller import RealsenseController import cv2 from PIL import Image, ImageDraw import time import numpy as np import ur_controller_urx as urc import Calibration_2D as Cali from datetime import datetime from success_label import * import random from random import choice import os import heapq WorkSpace = [-0.21,-0.37,0.21,-0.68] rob = urc.ur5() camera = RealsenseController() hand_eye=Cali.calibration() crop_box = [340,160,980,700] str = '/media/yang/Linux/Data/OriginalData/2-Fingers_Guided' G = Predictor('/home/yang/Git/CobotBenchmark/Functions/checkpoint/fc_cnn(new)/Toys') # /ur5 color_image,depth_image,infrared_L,infrared_R = camera.getImage() rob.homing() rob.close_gripper() with open(str+'/TrainingRecord', 'aw') as f: f.write('i,x,y,rz,success_label'+'\n') for i in range(999): color_image1,depth_image,infrared_L,infrared_R = camera.getImage() if not os.path.exists(str+"/"+"TrialCount_%01d"%i): os.makedirs(str+"/"+"TrialCount_%01d"%i) strnew=str+"/"+"TrialCount_%01d"%i cv2.imwrite(strnew +"/"+"image_01.jpg", color_image1) img = Image.open(strnew+'/image_01.jpg').crop(crop_box) img.save(strnew +"/"+"Croppedimage.jpg") rob.open_gripper() image = np.array(img).reshape(1,(crop_box[3]-crop_box[1]),(crop_box[2]-crop_box[0]),3) y_value = G.eval(image,(crop_box[3]-crop_box[1]),(crop_box[2]-crop_box[0])) angle_patch,probability_patch = G.parse_eval(y_value) probability_patch_sub = [] for j in range(len(probability_patch)): if probability_patch[j] > 0.5: probability_patch_sub.append(j) if len(probability_patch_sub) == 0: max_num_list = map(probability_patch.index, heapq.nlargest(5, probability_patch)) b = random.sample(max_num_list,1) idx = b[0] else: idx = choice(probability_patch_sub) y = (int(idx/y_value.shape[2]))*((crop_box[3]-crop_box[1]-238)/(y_value.shape[1]-1))+111+crop_box[1] x = (idx%y_value.shape[2])*((crop_box[2]-crop_box[0]-238)/(y_value.shape[2]-1))+111+crop_box[0] rz = (-1.57 + (random.sample(range(18),1)[0]+0.5)*(1.57/9)) print(x,y,rz) x,y = hand_eye.cam2rob(x,y) rob.move([x,y,0.25],rz) rob.grasping() rob.homing() time.sleep(5) x2=random.uniform(WorkSpace[0]+0.1,WorkSpace[2]-0.1) y2=random.uniform(WorkSpace[1]-0.1,WorkSpace[3]+0.1) rz2=random.uniform(-1.57,1.57) color_image2,depth_image,infrared_L,infrared_R = camera.getImage() cv2.imwrite(strnew +"/"+"image_02.jpg", color_image2) grasp_label = success_label(color_image1,color_image2) if grasp_label == 1: rob.move([x2, y2, 0.20],rz2) rob.move([x2, y2, 0.15],rz2) rob.open_gripper() rob.homing() rob.close_gripper() with open(str+'/TrainingRecord', 'aw') as f: f.write("%d,"%i+"%f,"%x+"%f,"%y+"%f,"%rz+"%d"%grasp_label+'\n')

[ "11510135@mail.sustech.edu.cn" ]

11510135@mail.sustech.edu.cn

ee00695458ca20ce01b296e151090b8079029e0b

d922f18fe53cf7738d6d536e5c9bfd8f3cb7e202

/F20_3900_851_Group5/asgi.py

4030e48797e6a9f32472657de2a2952339cf06e9

[]

no_license

zhcsteven/public

0b4f075c7f42715c1b892afabfeea5bbfdf834eb

94358b7a256167a542c34f92f149dd93610ec1ec

refs/heads/master

2023-01-01T03:46:48.557855

2020-10-23T19:59:07

306,734,455

0

null

UTF-8

Python

false

415

py

""" ASGI config for F20_3900_851_Group5 project. It exposes the ASGI callable as a module-level variable named ``application``. For more information on this file, see https://docs.djangoproject.com/en/3.1/howto/deployment/asgi/ """ import os from django.core.asgi import get_asgi_application os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'F20_3900_851_Group5.settings') application = get_asgi_application()

[ "zhcsteven@github.com" ]

zhcsteven@github.com

5494e226e3046e745556744498dec3d1c5ebf016

b8b233a47ee590862f3e4e02aabd22c429c34de2

/CLIvmtracker/host.py

8804975187538b5e921fa23e1f40354c433bc7a6

[]

no_license

gskeats/WakeHacks19

91ce7fa0e94cc8eb13492574b98706de5ef2e067

73fc0714df201dd0daea89167bf90596b978e82e

refs/heads/master

2020-05-03T10:28:06.846924

2019-04-04T15:36:12

178,579,590

0

null

UTF-8

Python

false

3,960

py

import subprocess class host: def __init__(self, name, key_type_string, key_string, descrip=None): self.names = name if ',' in self.names: name_split = name.split(',') self.domain_name=name_split[0] self.ip_addr=name_split[1] else: self.domain_name=None self.ip_addr=name self.key=key_string self.key_type=key_type_string self.description=descrip self.username=None class host_manager: def __init__(self): self.host_list=[] def load_host(self,*hosts): for item in hosts[0]: self.host_list.append(item) def delete_host(self,ip=None,domainName=None): entry=self.find_entry(ip,domainName) if entry is not None: self.host_list.remove(entry) return def find_entry(self,ip="",domainName=""): if ip is "" and domainName is "": ip=input("ip address is: ") for entry in self.host_list: if entry.domain_name==domainName or entry.ip_addr==ip: return entry print("Entry not found, check that it does exist and you have entered its identifyng information correctly") return None def add_description(self,ip="",domainName=""): entry=self.find_entry(ip,domainName) entry.description="#"+input("Type the description for this entry here: ") return def write_known_hosts(self): pipe=open("/Users/grahamskeats/.ssh/known_hosts","w") for entry in self.host_list: pipe.write(entry.names+" ") pipe.write(entry.key_type+" ") pipe.write(entry.key) if entry.description is not None: pipe.write("\n") pipe.write(entry.description) if entry.username is not None: pipe.write(" **Username:"+entry.username+"**") pipe.write("\n") pipe.close() return def print_available(self): for entry in self.host_list: if entry.description is not None: print(entry.names+" "+entry.description) else: print(entry.names) def connect(self,host=None): host=self.find_entry(host) username=input("Username: ") host.username=username subprocess.call(['ssh',username+"@"+host.ip_addr]) def readhostsfromfile(self): self.host_list=[] known_hosts_full = subprocess.check_output(['cat', '/Users/grahamskeats/.ssh/known_hosts']) entry = [] known_hosts_full = known_hosts_full.decode('utf-8') host_list = [] line_split = known_hosts_full.split('\n') iter_splits = iter(line_split) for line in iter_splits: if line is '': continue if self.checkforcomment(line): host_list[-1].description = line continue split_line = line.split() for split in split_line: entry.append(split) if '=' in split: new_host = host(entry[0], entry[1], entry[2]) entry = [] host_list.append(new_host) self.load_host(host_list) return host_list def checkforcomment(self,line): if line[0] is '#': return True else: return False def createnewconnection(self,ip=None,username=None): if ip is None: ip=input("What is the ip address or domain name of the machine you would like to connect to: ") if username is None: username=input("What is your username: ") subprocess.call(['ssh',username+"@"+ip]) self.readhostsfromfile() def checkduplicate(self,host): for entry in self.host_list: if host.ip_addr==entry.ip_addr: return True return False

[ "gnskeats@gmail.com" ]

gnskeats@gmail.com

1966651437f609fc2be290d921ab2809c7cb13b0

a73f9df0b7e797a55aa40ce29ca94e981c33543d

/zxcmovies/movie.py

5b45156ef169449a910e18894d1e7d89a7edcd37

[]

no_license

XinuxC/SpiderMan

c7884de144ad9fbdf9e786798e91bcfa71348eb7

d2b193573b870881520bfed970d5c295eaf69e81

refs/heads/master

2021-09-04T02:56:45.838338

2018-01-15T01:01:18

104,993,126

2

0

null

UTF-8

Python

false

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# -*- coding: utf-8 -*- import json import os import time import csv import requests header = { 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8', 'Accept-Language': 'en', 'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_3) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/56.0.2924.87 Safari/537.36', } def spider_movie(): ACTOR = '周星驰' urls = ['http://api.douban.com/v2/movie/search?q={周星驰}&count=20&start=' + str(n) for n in range(0, 120, 20)] for url in urls: r = requests.get(url=url,headers= header) data = json.loads(r.text) item = {} for subject in data['subjects']: casts = [each.get('name') for each in subject.get('casts')] directors = [each.get('name') for each in subject.get('directors')] genres = subject.get('genres') if ACTOR in directors or ACTOR in casts: item['directors'] = '/'.join(directors) item['casts'] = '/'.join(casts) item['genres'] = '/'.join(genres) item['movie_id'] = subject.get('id') item['title'] = subject.get('title') item['rate'] = subject.get('rating').get('average') item['year'] = subject.get('year') yield item time.sleep(2) movie_file = 'movies.csv' # def write2file(movies): # if os.path.exists('movies.json'): # movie_ids = read_csv('movies.json') # # with open('movies.json','a',encoding='utf-8') as f: # for movie in movies: # if movie.get('movie_id') not in movie_ids: # f.write(json.dumps(movie,ensure_ascii=False)) # f.write('\n') # print("Write movie id:{} into file".format(movie.get('movie_id'))) # else: # print("Movie id:{} already in file".format(movie.get('movie_id'))) def read_csv(movie_file): movie_ids = [] with open(movie_file) as csvfile: reader = csv.DictReader(csvfile) for row in reader: movie_ids.append(row['movie_id']) return movie_ids def write_csv(movies): movie_ids = [] if os.path.exists(movie_file): movie_ids = read_csv(movie_file) with open('movies.csv','a',newline='') as csvfile: MOVIES_FIELDS = ['title', 'rate', 'casts', 'genres', 'directors', 'movie_id', 'year', ] writer = csv.DictWriter(csvfile,fieldnames=MOVIES_FIELDS) writer.writeheader() for movie in movies: if movie_ids: if movie.get('movie_id') not in movie_ids: writer.writerow(movie) print("Write movie id:{} into file".format(movie.get('movie_id'))) else: print("Movie id:{} already in file".format(movie.get('movie_id'))) else: writer.writerow(movie) def main(): movies = spider_movie() write_csv(movies) if __name__ == '__main__': main()

[ "pishit2009@gmail.com" ]

pishit2009@gmail.com

e174afa38ec2ea5f548eadf2273ad23fbf7cb7e9

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/solutions_python/Problem_105/324.py

9ddec5819097ba9f1a61905d441b8271fd8d44f7

[]

no_license

dr-dos-ok/Code_Jam_Webscraper

c06fd59870842664cd79c41eb460a09553e1c80a

26a35bf114a3aa30fc4c677ef069d95f41665cc0

refs/heads/master

2020-04-06T08:17:40.938460

2018-10-14T10:12:47

null

0

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UTF-8

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py

class Item(object): def __init__(self, index=0): self.index = index self.parents = [] self.childs = [] def is_source(self): return len(self.parents) > 1 def is_dest(self): return len(self.childs) > 1 def get_dests(self): if len(self.parents): dests = [] for parent in self.parents: dests.extend(parent.get_dests()) return dests else: return [self] if __name__ == '__main__': T = int(raw_input()) for test_index in xrange(1, T+1): N = int(raw_input()) items = [Item(_) for _ in xrange(N+1)] for index in xrange(1, N+1): nums = map(int, raw_input().split()) Mi,Ii = nums[0], nums[1:] for ii in Ii: items[index].parents.append(items[ii]) items[ii].childs.append(items[index]) src_items = filter(lambda item: item.is_source(), items) dst_items = filter(lambda item: item.is_dest(), items) def check_item(item): dests = item.get_dests() for dest in set(dests): if dests.count(dest) > 1: return True return False result = False for src_item in src_items: if check_item(src_item): result = True break print 'Case #%d: %s' % (test_index, 'Yes' if result else 'No')

[ "miliar1732@gmail.com" ]

miliar1732@gmail.com

e06d790514e028de8404d51db547b5b990b4f864

4a5d9f129d5129b34c55171c99f83f0893ae5c11

/archives/migrations/0006_categorie_lien.py

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[ "MIT" ]

permissive

fromdanut/syndicat-riviere

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refs/heads/master

2018-09-04T19:14:40.490656

2018-06-04T10:52:21

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# -*- coding: utf-8 -*- # Generated by Django 1.9.7 on 2016-07-15 06:59 from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('archives', '0005_remove_categorie_lien'), ] operations = [ migrations.AddField( model_name='categorie', name='lien', field=models.CharField(default='default_link', max_length=30, unique=True), preserve_default=False, ), ]

[ "remidelannoy@hotmail.com" ]

remidelannoy@hotmail.com

c135d62f920dc56b65ff40f4fbe07eac168328ba

5b6f2b0ff8828d247885204522a7fe4ad7136f7a

/test_arc4.py

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manicmaniac/arc4

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refs/heads/master

2023-08-16T04:05:42.398404

2023-04-22T03:58:58

149,815,580

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MIT

2023-09-12T09:24:09

2018-09-21T20:40:18

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try: from setuptools.distutils.version import StrictVersion except ImportError: from distutils.version import StrictVersion import doctest import functools import multiprocessing import platform import textwrap import timeit import unittest import arc4 import setup KEY = b'PYTHON3' LOREM = b"""Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do \ eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim \ veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea \ commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit \ esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat \ cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est \ laborum.""" LOREM_ARC4 = b"""\xf0\xa8\x59\xec\xdf\x9d\xbd\x95\x52\x91\x66\x72\x50\x01\x0d\ \x3a\xac\x62\x10\xdc\x58\x0f\x49\x02\xd9\x45\x2a\xad\x3a\x2b\x79\xd5\x2b\x29\ \xe7\x16\xf1\x9c\x93\x58\xcd\xa9\x32\x87\xfc\x9f\x6e\x29\x14\x0a\x59\x12\x21\ \x89\x51\x49\xc7\x3f\x59\x78\x0b\x16\xb6\xb2\xc4\xc3\xc0\x61\xc4\xcd\xcf\x9e\ \xff\x34\x2c\xf2\x28\x14\xf8\xc9\x08\xf0\x1f\x2d\xfa\xe8\xbf\x77\xe0\xeb\xee\ \xa1\x51\xd4\xf3\x86\x66\x60\x1c\xb1\x3a\x14\x86\xf2\x6c\xe5\x47\xf8\xb5\x50\ \xad\xbc\x1c\x64\xeb\xbc\x52\x33\x60\x41\x58\x33\x6f\x58\x8c\xfd\x41\x1b\xb0\ \x05\xb3\xbc\x46\x37\xf3\xa4\x5e\x3e\x1f\x20\xe9\x00\x02\xcc\x31\x07\xe8\x65\ \xbb\x12\x97\x05\xcb\xfd\xba\x50\x9c\x59\x14\x49\xb4\x3c\x12\x2b\x47\x27\x5f\ \x30\x52\x57\xf4\xa2\x70\xc5\x7d\x4a\xf2\x92\x01\x5d\x02\x69\x1d\x74\xff\x43\ \xb1\x73\xb9\x28\xfe\x73\x62\x7f\xbd\xcd\xa1\x53\xa2\x1e\x28\x37\x19\xc4\x59\ \xbc\x81\x93\x79\x05\x13\x07\xc2\x43\xb3\xd1\x2a\x9d\xf7\x3c\xe7\x1e\x63\x4b\ \x70\xc7\xc2\xa6\x80\x31\xc7\xc5\x07\x64\x49\x40\x08\x7a\x4f\x4f\x90\x63\x88\ \x4d\x35\x8b\xd2\x48\xe1\xc2\xfc\xa2\xb5\x47\xca\xaf\x75\x36\x31\x22\xa8\x45\ \x5d\x0f\x03\xb7\xd5\x3b\xff\x47\xbc\x6f\xe0\xa3\x49\xfb\x63\xbe\xfc\xa7\x60\ \x59\x43\x50\x8e\x95\x76\x68\xda\xfa\xdb\x9b\x96\x9d\x1b\x6d\xac\x14\x2c\x12\ \x29\xfd\xf0\xaf\xc4\xba\x12\xdf\x83\xd9\xae\xcc\x19\x80\xfd\xc2\x36\x32\xf4\ \x01\x0b\x6d\xeb\x9e\xff\x74\x2e\xfe\x58\xc7\x91\xa9\x75\xf5\xa0\xc0\x5d\xb7\ \x5e\x6a\x71\x5a\x9c\xd3\x98\xca\x6c\xae\x80\xd6\x0d\xb9\x84\x63\x7f\xdf\x31\ \x1b\x5c\x4f\x07\x4c\x9b\x23\x24\x43\xce\x9e\x4d\x29\x5f\xb9\x3a\x57\x0f\x18\ \xf5\xa0\x5a\x94\x88\xfa\x55\x64\xca\x4f\x74\x9f\x71\x33\xa5\x6d\xd4\xd8\x5a\ \xdd\x51\x66\xad\xf5\x37\xad\x44\xe9\x20\xf2\x31\xd3\x9a\xef\x3e\x47\xd1\x20\ \x88\x2c\x21\x74\xed\xa3\x5c\x7c\xa7\x03\x42\x4d\x21\x50\xe2\x9b\x2b\x99\x88\ \x1e\xd4\x53\xda\x1c\xa2\xc7\x5b\xb5\x94\x5d\xc0""" def raises_deprecation_warning(f): @functools.wraps(f) def decorated(self, *args, **kwargs): with self.assertWarns(DeprecationWarning): return f(self, *args, **kwargs) return decorated def raises_deprecation_warning_if(condition): if condition: return raises_deprecation_warning return lambda x: x def expected_failure_if(condition): if condition: return unittest.expectedFailure return lambda x: x class TestARC4(unittest.TestCase): def test_arc4_module_has_doc(self): self.assertIsNotNone(arc4.__doc__) def test_arc4_version_is_strict_version(self): try: StrictVersion(arc4.__version__) except (AttributeError, ValueError) as e: self.fail(e) def test_arc4_version_is_equal_to_setup_version(self): self.assertEqual(arc4.__version__, setup.VERSION) def test_arc4_class_has_doc(self): self.assertIsNotNone(arc4.ARC4.__doc__) def test_init_with_zero_length_key_raises_error(self): with self.assertRaisesRegex(ValueError, r'^invalid key length: 0$'): arc4.ARC4(b'') def test_init_with_bytes_returns_instance(self): self.assertIsInstance(arc4.ARC4(b'spam'), arc4.ARC4) @raises_deprecation_warning def test_init_with_unicode_returns_instance(self): self.assertIsInstance(arc4.ARC4(u'スパム'), arc4.ARC4) @raises_deprecation_warning_if(platform.python_implementation() == 'PyPy') def test_init_with_bytearray_raises_type_error(self): with self.assertRaisesRegex( TypeError, r'argument 1 must be .*, not bytearray'): arc4.ARC4(bytearray([0x66, 0x6f, 0x6f])) @raises_deprecation_warning_if(platform.python_implementation() == 'PyPy') def test_init_with_memoryview_raises_type_error(self): pattern = r'^argument 1 must be .*, not memoryview$' with self.assertRaisesRegex(TypeError, pattern): arc4.ARC4(memoryview(b'spam')) @expected_failure_if(platform.python_implementation() == 'PyPy') def test_encrypt_has_doc(self): self.assertIsNotNone(arc4.ARC4.encrypt.__doc__) def test_encrypt_with_long_bytes_returns_encrypted_bytes(self): cipher = arc4.ARC4(KEY) self.assertEqual(LOREM_ARC4, cipher.encrypt(LOREM)) def test_encrypt_multiple_times_returns_encrypted_bytes(self): cipher = arc4.ARC4(KEY) encrypted = b'' for c in LOREM: if isinstance(c, int): c = chr(c).encode('utf-8') encrypted += cipher.encrypt(c) self.assertEqual(LOREM_ARC4, encrypted) @raises_deprecation_warning def test_encrypt_with_unicode_returns_encrypted_bytes(self): cipher = arc4.ARC4(b'spam') self.assertEqual(b'Q\xcd\xb1!\xecg', cipher.encrypt(u'ハム')) def test_encrypt_with_bytearray_raises_type_error(self): cipher = arc4.ARC4(b'spam') with self.assertRaisesRegex( TypeError, r'^crypt argument 1 must be .*, not bytearray$'): cipher.encrypt(bytearray(b'ham')) def test_encrypt_with_memoryview_raises_type_error(self): cipher = arc4.ARC4(b'spam') with self.assertRaisesRegex( TypeError, r'^crypt argument 1 must be .*, not memoryview$'): cipher.encrypt(memoryview(b'ham')) def test_encrypt_with_list_raises_type_error(self): cipher = arc4.ARC4(b'spam') message = (r'^crypt argument 1 must be read-only bytes-like ' + r'object, not list') with self.assertRaisesRegex(TypeError, message): cipher.encrypt([0x68, 0x61, 0x6d]) @unittest.skip('takes long time and a bit flaky depends on environment') @unittest.skipIf(multiprocessing.cpu_count() <= 1, 'needs multiple cores') def test_encrypt_thread_performance(self): large_text = 'a' * 10 * 1024 * 1024 number = 100 cpu_count = multiprocessing.cpu_count() setup = textwrap.dedent("""\ from arc4 import ARC4 from threading import Thread def target(): ARC4({key!r}).encrypt({text!r}) """.format(key=KEY, text=large_text)) # Create unused threads to make the similar conditions # between single and multiple threads. code = textwrap.dedent("""\ threads = [] for i in range({}): thread = Thread(target=target) threads.append(thread) for thread in threads: pass target() """.format(cpu_count)) single_thread_elapsed_time = timeit.timeit(code, setup, number=number) code = textwrap.dedent("""\ threads = [] for i in range({}): thread = Thread(target=target) threads.append(thread) thread.start() for thread in threads: thread.join() """.format(cpu_count)) multi_thread_elapsed_time = timeit.timeit(code, setup, number=number // cpu_count) self.assertLess(multi_thread_elapsed_time, single_thread_elapsed_time) @expected_failure_if(platform.python_implementation() == 'PyPy') def test_decrypt_has_doc(self): self.assertIsNotNone(arc4.ARC4.decrypt.__doc__) def test_decrypt_with_long_bytes_returns_decrypted_bytes(self): cipher = arc4.ARC4(KEY) self.assertEqual(LOREM, cipher.decrypt(LOREM_ARC4)) def load_tests(loader, tests, ignore): tests.addTests(doctest.DocTestSuite(arc4)) tests.addTests(doctest.DocFileSuite('README.rst')) return tests

[ "rito.0305@gmail.com" ]

rito.0305@gmail.com

de0ac5a347c783cdbbd4f0a4d1abc51e230dce90

c3646f146bc5e2478f07da7ec004e1b783f48e99

/Server_Final.py

8e28c0e287d9d43cbd56432848154b1ccb4f8e9f

[]

no_license

comnet14/Chat_Program_Final

c6e0408227ce416c538b5802fbb3c8c0dc556ae4

e12ebe3be5b09e67d1536bc07d978c419fd5b1f5

refs/heads/master

2020-06-05T06:55:40.587548

2015-06-07T16:22:01

37,023,174

0

null

UHC

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# socket 과 select 모듈 임포트 from socket import * from select import * import sys from time import ctime # 호스트, 포트와 버퍼 사이즈를 지정 HOST = '' PORT = 56789 BUFSIZE = 1024 ADDR = (HOST, PORT) # 소켓 객체생성 serverSocket = socket(AF_INET, SOCK_STREAM) # 서버 정보를 바인딩 serverSocket.bind(ADDR) # 요청을 기다림(listen) serverSocket.listen(10) connection_list = [serverSocket] print('==============================================') print('Start Server. Waitin connection to %s port....' % str(PORT)) print('==============================================') # 무한 루프를 시작 while connection_list: try: print('Waiting Request...') # select 로 요청을 받고, 10초마다 블럭킹을 해제하도록 함 read_socket, write_socket, error_socket = select(connection_list, [], [], 10) for sock in read_socket: # 새로운 접속 if sock == serverSocket: clientSocket, addr_info = serverSocket.accept() connection_list.append(clientSocket) print('[!] [%s] Client (%s) has connected.' % (ctime(), addr_info[0])) # 클라이언트로 응답을 돌려줌 for socket_in_list in connection_list: if socket_in_list != serverSocket and socket_in_list != sock: try: socket_in_list.send('[%s] Client has connected to room' % ctime()) except Exception as e: socket_in_list.close() connection_list.remove(socket_in_list) # 접속한 사용자(클라이언트)로부터 새로운 데이터 받음 else: data = sock.recv(BUFSIZE) if data: print('[%s] Got data from Client...' % ctime()) for socket_in_list in connection_list: if socket_in_list != serverSocket and socket_in_list != sock: try: socket_in_list.send('[%s] %s' % (ctime(), data)) print('[%s] Sending data to Client...' % ctime()) except Exception as e: print(e.message) socket_in_list.close() connection_list.remove(socket_in_list) continue else: connection_list.remove(sock) sock.close() print('[!][%s] Disconnected...' % ctime()) except KeyboardInterrupt: # 종료하기 serverSocket.close() sys.exit()

[ "skdbsxir@naver.com" ]

skdbsxir@naver.com

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31312e5019ce3efd927216b737808131ce208265

/PyPoll_Challenge.py

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[]

no_license

sabrinajc/Election_Analysis

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4f0f27733dedb3835c8596bd3f8b70a1cad82df1

refs/heads/master

2022-11-29T11:42:52.122278

2020-08-03T02:03:44

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# -*- coding: UTF-8 -*- """PyPoll Homework Challenge Solution.""" # Add our dependencies. import csv import os # Add a variable to load a file from a path. file_to_load = os.path.join("Resources","election_results.csv") # Add a variable to save the file to a path. file_to_save = os.path.join("analysis", "election_analysis.txt") # Initialize a total vote counter. total_votes = 0 # Candidate Options and candidate votes. candidate_options = [] candidate_votes = {} # 1: Create a county list and county votes dictionary. county_options = [] county_votes = {} # Track the winning candidate, vote count and percentage winning_candidate = "" winning_count = 0 winning_percentage = 0 # 2: Track the largest county and county voter turnout. winning_county = "" winning_county_count = 0 winning_county_percentage = 0 # Read the csv and convert it into a list of dictionaries with open(file_to_load) as election_data: reader = csv.reader(election_data) # Read the header header = next(reader) # For each row in the CSV file. for row in reader: # Add to the total vote count total_votes = total_votes + 1 # Get the candidate name from each row. candidate_name = row[2] # 3: Extract the county name from each row. county_name = row[1] # If the candidate does not match any existing candidate add it to # the candidate list if candidate_name not in candidate_options: # Add the candidate name to the candidate list. candidate_options.append(candidate_name) # And begin tracking that candidate's voter count. candidate_votes[candidate_name] = 0 # Add a vote to that candidate's count candidate_votes[candidate_name] += 1 # 4a: Write a decision statement that checks that the # county does not match any existing county in the county list. if county_name not in county_options: # 4b: Add the existing county to the list of counties. county_options.append(county_name) # 4c: Begin tracking the county's vote count. county_votes[county_name] = 0 # 5: Add a vote to that county's vote count. county_votes[county_name] += 1 # Save the results to our text file. with open(file_to_save, "w") as txt_file: # Print the final vote count (to terminal) election_results = ( f"\nElection Results\n" f"-------------------------\n" f"Total Votes: {total_votes:,}\n" f"-------------------------\n\n" f"County Votes:\n") print(election_results, end="") txt_file.write(election_results) # 6a: Write a repetition statement to get the county from the county dictionary. for county_name in county_votes: # 6b: Retrieve the county vote count. county_vote_count = county_votes[county_name] # 6c: Calculate the percent of total votes for the county. county_vote_percentage = float(county_vote_count) / float(total_votes) * 100 county_results = (f"{county_name}: {county_vote_percentage:.1f}% ({county_vote_count:,})\n") # 6d: Print the county results to the terminal. print(county_results) # 6e: Save the county votes to a text file. txt_file.write(county_results) # 6f: Write a decision statement to determine the winning county and get its vote count. if (county_vote_count > winning_county_count) and (county_vote_percentage > winning_county_percentage): winning_county_count = county_vote_count winning_county = county_name winning_county_percentage = county_vote_percentage # 7: Print the county with the largest turnout to the terminal. winning_county_summary = ( f"\n-------------------------\n" f"Largest County Turnout: {winning_county}\n" f"-------------------------\n") print(winning_county_summary) # 8: Save the county with the largest turnout to a text file. txt_file.write(winning_county_summary) # Save the final candidate vote count to the text file. for candidate_name in candidate_votes: # Retrieve vote count and percentage votes = candidate_votes.get(candidate_name) vote_percentage = float(votes) / float(total_votes) * 100 candidate_results = ( f"{candidate_name}: {vote_percentage:.1f}% ({votes:,})\n") # Print each candidate's voter count and percentage to the # terminal. print(candidate_results) # Save the candidate results to our text file. txt_file.write(candidate_results) # Determine winning vote count, winning percentage, and candidate. if (votes > winning_count) and (vote_percentage > winning_percentage): winning_count = votes winning_candidate = candidate_name winning_percentage = vote_percentage # Print the winning candidate (to terminal) winning_candidate_summary = ( f"-------------------------\n" f"Winner: {winning_candidate}\n" f"Winning Vote Count: {winning_count:,}\n" f"Winning Percentage: {winning_percentage:.1f}%\n" f"-------------------------\n") print(winning_candidate_summary) # Save the winning candidate's name to the text file txt_file.write(winning_candidate_summary)

[ "hewang@hedeMacBook-Pro.local" ]

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/app/modules/turtleGrapher/turtle_utils.py

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import urlparse import config # this is the config.py from rdflib import Namespace, URIRef, Literal def generate_hash(filename): from hashlib import sha1 # the 'b' isn't needed less you run this on Windows with open(filename, 'rb') as f: # we apply a sort func to make sure the contents are the same, # regardless of order return sha1(str(sorted(f.readlines()))).hexdigest() def slugify(value): """ from Django Normalizes string, converts to lowercase, removes non-alpha characters, and converts spaces to hyphens. """ import unicodedata import re value = unicode(value) value = unicodedata.normalize('NFKD', value).encode('ascii', 'ignore') value = unicode(re.sub('[^\w\s\/\./:-]', '', value).strip()) value = unicode(re.sub('[-\s]+', '-', value)) return value def generate_uri(uri, s=''): """ Takes a string as one would define for .ttl files and returns a URI for rdflib. Args: uri (str): a string following .ttl convention for a URI ex. g:Identifier as shorthand for http://www.biointerchange.org/gfvo#Identifier Returns: (rdflib.URIRef) with URI needed to add to rdflib.Graph """ # if you call with a uri already if isinstance(uri, URIRef): s = slugify(s) return URIRef(str(uri) + s) elif type(uri) is str and 'http' in uri: # if you called with a string in the form of a url return URIRef(uri) prefix = uri.split(':')[0] postfix = uri.split(':')[1] postfix = slugify(postfix) if prefix == '': # this is our : case return URIRef(config.namespaces['root'] + postfix) else: return URIRef(config.namespaces[prefix] + postfix) def uri_to_basename(uri): ''' This does the reverse of generate_uri(). Converts a rdflib.term.URIRef back to is base. ex. rdflib.term.URIRef(u'https://www.github.com/superphy#4eb02f5676bc808f86c0f014bbce15775adf06ba) gives 4eb02f5676bc808f86c0f014bbce15775adf06ba Args: uri(rdflib.term.URIRef): a URIRef object Returns: (str): just the basestring (ie. everything after the : in rdf syntax) ''' for value in config.namespaces.keys(): if value in uri: return str(uri).strip(value) # if the clean method above fails, default to '/' splitting # this will fail if a path-style uri is used return str(uri).split('/')[-1] def link_uris(graph, uri_towards_spfyid, uri_towards_marker): ''' Links two vertices in a graph as required for inferencing/queries in blazegraph. Blazegraph has problems (hangs after 3-4 uploads) with owl:SymmetricProperty, so we use :hasPart which we apply owl:TransitiveProperty to link everything in :spfyId -> :Marker and use :isFoundIn (same owl:TransitiveProperty) to link everything :Marker -> :spfyId This means that you can't just query a vertex type and look for another vertex type -> you must know the direction you're moving in (think subway trains). We accomadate this by defining a dictionary that maps object types to a given numerical weight so we can do a comparison of weights to determine direction. The owl:TransitiveProperty is defined in generate_graph() under turtle_grapher.py ''' graph.add((uri_towards_spfyid, generate_uri(':hasPart'), uri_towards_marker)) graph.add((uri_towards_marker, generate_uri(':isFoundIn'), uri_towards_spfyid)) return graph

[ "kevin.kent.le@gmail.com" ]

kevin.kent.le@gmail.com

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/scripts/add_book.py

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#! /usr/bin/python3 from io_utils import load_data, save_data, json_path, multiline_input from card_utils import note_card, quote_card, flash_card def get_book_data(): title = input('Title:\n') thesis = input('Thesis:\n') defns = [] print('Abstractions') while True: name = input('Name:\n') if len(name) == 0: break defns.append((name, multiline_input('Definition:'))) notes = multiline_input('Takeaways:') quotes = multiline_input('Quotes:') cards = [] cards.append(flash_card('Thesis', thesis)) for note in notes.split('\n'): if len(note) > 0: cards.append(note_card(note)) for quote in quotes.split('\n'): if len(quote) > 0: cards.append(quote_card(quote)) for defn in defns: cards.append(flash_card(*defn)) data = {} data['title'] = title data['cards'] = cards return data def add_book(data): book = get_book_data() data.append(book) if __name__ == '__main__': print('This script is archived and only included if someone wants to develop on it.') exit() user_data, book_data = load_data(json_path) add_book(book_data) save_data(user_data, book_data, json_path)

[ "grant.skaggs@outlook.com" ]

grant.skaggs@outlook.com

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/explore/2020/september/Evaluate_Division.1.py

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lixiang2017/leetcode

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refs/heads/master

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''' Floyd You are here! Your runtime beats 27.33 % of python submissions. ''' class Solution(object): def calcEquation(self, edges, weights, pairs): graph = collections.defaultdict(lambda: collections.defaultdict(lambda: float('inf'))) for (i, j), weight in itertools.izip(edges, weights): graph[i][i], graph[i][j], graph[j][i], graph[j][j] = 1., weight, 1. / weight, 1. for mid in graph: for i in graph[mid]: for j in graph[mid]: graph[i][j] = min(graph[i][j], graph[i][mid] * graph[mid][j]) return [graph[i][j] if graph[i][j] < float('inf') else -1. for i, j in pairs]

[ "838255715@qq.com" ]

838255715@qq.com

7726a4a36d1e204ff71e6eba409b084dffa76440

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/doclink/clients/requests_.py

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Luoyufu/doclink

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refs/heads/master

2022-12-10T06:49:45.177895

2018-03-04T15:06:17

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# -*- coding: utf-8 -*- import atexit import os import requests from requests_toolbelt import MultipartEncoder from six import string_types class RequestsClient(object): optional_args = ( 'params', 'data', 'headers', 'cookies', 'files', 'auth', 'timeout', 'allow_redirects', 'proxies', 'hooks', 'stream', 'verify', 'cert', 'json', 'multipart') def __init__(self, session=None): if session is None: session = requests.Session() atexit.register(session.close) self._session = session @classmethod def _prepare_optional_args(cls, sending_kwargs, request_meta): for arg in cls.optional_args: value = request_meta.get(arg) if value is not None: if arg == 'auth': sending_kwargs['auth'] = cls._create_auth_arg(value) elif arg == 'files': files_arg = cls._create_files_arg(value) if files_arg: sending_kwargs['files'] = files_arg elif arg == 'multipart': multipart_arg = cls._create_multipart_arg(value) if multipart_arg: encoder = MultipartEncoder(multipart_arg) sending_kwargs['data'] = encoder headers = sending_kwargs.setdefault('headers', {}) headers['Content-Type'] = encoder.content_type else: sending_kwargs[arg] = value @classmethod def _get_sending_kwargs(cls, request_meta): sending_kwargs = {} sending_kwargs.update( method=request_meta['method'], url=request_meta.get_url(), ) cls._prepare_optional_args(sending_kwargs, request_meta) return sending_kwargs @classmethod def _create_files_arg(cls, files_meta): """Create files arg for requests. Args: files_meta (dict): Countain filed name and file_info mapping. Returns: A dict mapping field name to file_item for multipart/form-data """ def create_file_item(file_info): """Nested function to create a file item for files arg. Args: File_info: If it's a file_path str, open it as file_object. Else, pass it to requests files arg. Returns: File instance or file_info tuple. For example: open('report.xls', 'rb') ('report.xls', open('report.xls', 'rb')) """ if isinstance(file_info, string_types): try: return open(file_info, 'rb') # param is file_path except (IOError, TypeError): pass return file_info files_arg = {} for field, file_infos in files_meta.items(): if isinstance(file_infos, list): files_arg[field] = [create_file_item(file_info) for file_info in file_infos] else: files_arg[field] = create_file_item(file_infos) return files_arg @classmethod def _create_auth_arg(cls, auth_meta): if auth_meta['type'] == 'basic': return requests.auth.HTTPBasicAuth(auth_meta['username'], auth_meta['password']) else: return requests.auth.HTTPDigestAuth(auth_meta['username'], auth_meta['password']) @classmethod def _create_multipart_arg(cls, multipart_meta): """Create a MultipartEncoder instance for multipart/form-data. Requests_toolbelt will not try to guess file_name. To encode a file we need to give file_name explicitly. Args: multipart_meta (dict): Map field name to multipart form-data value. """ def create_multipart_item(item_info): """Nested function to create a multipart item for files arg. Args: item_info: If it's a file_path str, open it as file_object as set file_name. Else, pass it to requests_toolbelt MultipartEncoder. Returns: File instance or file_info tuple. For example: ('report.xls', open('report.xls', 'rb')) """ if isinstance(item_info, string_types): try: return (os.path.basename(item_info), open(item_info, 'rb')) # file_path except (IOError, TypeError): pass try: return (os.path.basename(item_info.name), item_info) # file_object except AttributeError: pass return item_info multipart_arg = {} for field, item_infos in multipart_meta.items(): if isinstance(item_infos, list): multipart_arg[field] = [create_multipart_item(item_info) for item_info in item_infos] else: multipart_arg[field] = create_multipart_item(item_infos) return multipart_arg def request(self, request_meta): sending_kwargs = self._get_sending_kwargs(request_meta) return self._session.request(**sending_kwargs)

[ "yufu_luo@163.com" ]

yufu_luo@163.com

687a25694621f2e864b8c7dc5e552473ecff1887

241724e83f5c12ed9d7dd3b825dfe4e2b1b0f777

/pde/pdes/base.py

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[ "MIT" ]

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xuanxu/py-pde

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refs/heads/master

2021-03-09T21:37:13.920717

2020-03-10T12:18:03

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""" Base classes .. codeauthor:: David Zwicker <david.zwicker@ds.mpg.de> """ from abc import ABCMeta, abstractmethod import logging from typing import Callable, Dict, Optional, TYPE_CHECKING # @UnusedImport import numpy as np from ..fields.base import FieldBase from ..trackers.base import TrackerCollectionDataType from ..tools.numba import jit if TYPE_CHECKING: from ..solvers.controller import TRangeType # @UnusedImport class PDEBase(metaclass=ABCMeta): """ base class for solving partial differential equations """ explicit_time_dependence: Optional[bool] = None def __init__(self, noise: float = 0): """ Args: noise (float): Magnitude of the additive Gaussian white noise that is supported by default. If set to zero, a determinitics partial differential equation will be solved. If another noise structure is required the respective methods need to be overwritten. """ self._logger = logging.getLogger(self.__class__.__name__) self.noise = noise @property def is_sde(self) -> bool: """ flag indicating whether this is a stochastic differential equation The :class:`BasePDF` class supports additive Gaussian white noise, whose magnitude is controlled by the `noise` property. In this case, `is_sde` is `True` if `self.noise != 0`. """ # check for self.noise, in case __init__ is not called in a subclass return hasattr(self, 'noise') and self.noise != 0 @abstractmethod def evolution_rate(self, field: FieldBase, t: float = 0) \ -> FieldBase: pass def _make_pde_rhs_numba(self, state: FieldBase) -> Callable: """ create a compiled function for evaluating the right hand side """ raise NotImplementedError def make_pde_rhs(self, state: FieldBase, backend: str = 'auto') -> Callable: """ return a function for evaluating the right hand side of the PDE Args: state (:class:`~pde.fields.FieldBase`): An example for the state from which the grid and other information can be extracted backend (str): Determines how the function is created. Accepted values are 'python` and 'numba'. Alternatively, 'auto' lets the code decide for the most optimal backend. Returns: Function determining the right hand side of the PDE """ if backend == 'auto': try: result = self._make_pde_rhs_numba(state) except NotImplementedError: backend = 'numpy' else: result._backend = 'numba' # type: ignore return result if backend == 'numba': result = self._make_pde_rhs_numba(state) result._backend = 'numba' # type: ignore elif backend == 'numpy': state = state.copy() def evolution_rate_numpy(state_data, t: float): """ evaluate the rhs given only a state without the grid """ state.data = state_data return self.evolution_rate(state, t).data result = evolution_rate_numpy result._backend = 'numpy' # type: ignore else: raise ValueError(f'Unknown backend `{backend}`') return result def noise_realization(self, state: FieldBase, t: float = 0) -> FieldBase: """ returns a realization for the noise Args: state (:class:`~pde.fields.ScalarField`): The scalar field describing the concentration distribution t (float): The current time point Returns: :class:`~pde.fields.ScalarField`: Scalar field describing the evolution rate of the PDE """ if self.noise: data = np.random.normal(scale=self.noise, size=state.data.shape) return state.copy(data=data, label='Noise realization') else: return state.copy(data=0, label='Noise realization') def _make_noise_realization_numba(self, state: FieldBase) -> Callable: """ return a function for evaluating the noise term of the PDE Args: state (:class:`~pde.fields.FieldBase`): An example for the state from which the grid and other information can be extracted Returns: Function determining the right hand side of the PDE """ if self.noise: noise_strength = float(self.noise) data_shape = state.data.shape @jit def noise_realization(state_data: np.ndarray, t: float): """ compiled helper function returning a noise realization """ return noise_strength * np.random.randn(*data_shape) else: @jit def noise_realization(state_data: np.ndarray, t: float): """ compiled helper function returning a noise realization """ return None return noise_realization # type: ignore def _make_sde_rhs_numba(self, state: FieldBase) -> Callable: """ return a function for evaluating the noise term of the PDE Args: state (:class:`~pde.fields.FieldBase`): An example for the state from which the grid and other information can be extracted Returns: Function determining the right hand side of the PDE """ evolution_rate = self._make_pde_rhs_numba(state) noise_realization = self._make_noise_realization_numba(state) @jit def sde_rhs(state_data: np.ndarray, t: float): """ compiled helper function returning a noise realization """ return (evolution_rate(state_data, t), noise_realization(state_data, t)) return sde_rhs # type: ignore def make_sde_rhs(self, state: FieldBase, backend: str = 'auto') \ -> Callable: """ return a function for evaluating the right hand side of the SDE Args: state (:class:`~pde.fields.FieldBase`): An example for the state from which the grid and other information can be extracted backend (str): Determines how the function is created. Accepted values are 'python` and 'numba'. Alternatively, 'auto' lets the code decide for the most optimal backend. Returns: Function determining the deterministic part of the right hand side of the PDE together with a noise realization. """ if backend == 'auto': try: sde_rhs = self._make_sde_rhs_numba(state) except NotImplementedError: backend = 'numpy' else: sde_rhs._backend = 'numba' # type: ignore return sde_rhs if backend == 'numba': sde_rhs = self._make_sde_rhs_numba(state) sde_rhs._backend = 'numba' # type: ignore elif backend == 'numpy': state = state.copy() def sde_rhs(state_data, t: float): """ evaluate the rhs given only a state without the grid """ state.data = state_data return (self.evolution_rate(state, t).data, self.noise_realization(state, t).data) sde_rhs._backend = 'numpy' # type: ignore else: raise ValueError(f'Unknown backend `{backend}`') return sde_rhs def solve(self, state: FieldBase, t_range: "TRangeType", dt: float = None, tracker: TrackerCollectionDataType = ['progress', 'consistency'], method: str = 'auto', **kwargs): """ convenience method for solving the partial differential equation The method constructs a suitable solver (:class:`~pde.solvers.base.SolverBase`) and controller (:class:`~pde.controller.Controller`) to advance the state over the temporal range specified by `t_range`. To obtain full flexibility, it is advisable to construct these classes explicitly. Args: state (:class:`~pde.fields.base.FieldBase`): The initial state (which also defines the grid) t_range (float or tuple): Sets the time range for which the PDE is solved. If only a single value `t_end` is given, the time range is assumed to be `[0, t_end]`. dt (float): Time step of the chosen stepping scheme. If `None`, a default value based on the stepper will be chosen. tracker: Defines a tracker that process the state of the simulation at fixed time intervals. Multiple trackers can be specified as a list. The default value is ['progress', 'consistency'], which displays a progress bar and checks the state for consistency, aborting the simulation when not-a-number values appear. method (:class:`~pde.solvers.base.SolverBase` or str): Specifies a method for solving the differential equation. This can either be an instance of :class:`~pde.solvers.base.SolverBase` or a descriptive name like 'explicit' or 'scipy'. The valid names are given by :meth:`pde.solvers.base.SolverBase.registered_solvers`. **kwargs: Additional keyword arguments are forwarded to the solver class Returns: :class:`~pde.fields.base.FieldBase`: The state at the final time point. """ from ..solvers.base import SolverBase if method == 'auto': method = 'scipy' if dt is None else 'explicit' # create solver if callable(method): solver = method(pde=self, **kwargs) if not isinstance(solver, SolverBase): self._logger.warn('Solver is not an instance of `SolverBase`. ' 'Specified wrong method?') else: solver = SolverBase.from_name(method, pde=self, **kwargs) # create controller from ..solvers import Controller controller = Controller(solver, t_range=t_range, tracker=tracker) # run the simulation return controller.run(state, dt)

[ "david.zwicker@ds.mpg.de" ]

david.zwicker@ds.mpg.de

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/supplies_control/migrations/0001_initial.py

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ProgrammerBaldy/bunkers_backend

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# Generated by Django 3.1.6 on 2021-02-10 13:08 from django.db import migrations, models class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='Product', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=255)), ('measure_unit', models.CharField(max_length=20)), ], ), migrations.CreateModel( name='Product_subproducts', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('productid', models.IntegerField()), ('subproductid', models.IntegerField()), ], ), migrations.CreateModel( name='Product_supplies', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('productid', models.IntegerField()), ('supplyid', models.IntegerField()), ], ), migrations.CreateModel( name='Subproduct', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=255)), ('measure_unit', models.CharField(max_length=20)), ], ), migrations.CreateModel( name='Subproduct_supplies', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('subproductid', models.IntegerField()), ('supplyid', models.IntegerField()), ], ), migrations.CreateModel( name='Supply', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=255)), ('measure_unit', models.CharField(max_length=20)), ], ), ]

[ "tauanegri@corpstek.com.br" ]

tauanegri@corpstek.com.br

604df648d3c490b01fd3ac766baf552625a98caf

22a863f78432baf0cf28a924e3bc26555bef2e35

/test/testagent/HAagent_info.py

f7b855cb018e9d264722bf7072595e215d75d4c4

[]

no_license

Li-Shiang-Chi/atca-test-agent

be7294a1d9bcc30971abc29d8cb3dab080c417ea

441e352a72e085b5988a794ff731694b56fa8a2f

refs/heads/master

2021-01-23T00:40:07.206358

2017-07-10T11:36:00

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#!/usr/bin/python #-*- coding: utf-8 -*- ''' @author: lsc ''' import shell_server import cmd_HAagent import file import json import HAagent_terminal def is_add_primary_success(parser): """ check is primary node add in cluster :param parser is a dict get from base.configure """ is_exists = is_node_exists(parser["Cluster_name"], parser["PrimaryOS_name"], parser) role = get_node_role(parser["PrimaryOS_name"], parser) print "primary node is exists %s" % is_exists print "primary role %s (expeceted 0)" % role if is_exists and role == "primary": # if node exists and the role equals 0(primary) return True return False def is_add_backup_success(parser): """ check is backup node add in cluster :param parser is a dict get from base.configure """ is_exists = is_node_exists(parser["Cluster_name"], parser["BackupOS_name"], parser) role = get_node_role(parser["BackupOS_name"], parser) print "backup node is exists %s" % is_exists print "backup role %s (expeceted 1)" % role if is_exists and role == "backup": # if node exists and the role equals 1(backup) return True return False def is_add_slave_success(parser): """ check is slave node add in cluster :param parser is a dict get from base.configure """ is_exists = is_node_exists(parser["Cluster_name"], parser["SlaveOS_name"], parser) role = get_node_role(parser["SlaveOS_name"], parser) print "slave node is exists %s" % is_exists print "slave role %s (expeceted 2)" % role if is_exists and role == "slave": # if node exists and the role equals 2(slave) return True return False def is_cluster_exist(cluster_name , parser): """ check is cluster in HAagent :param cluster_name : cluster name :param parser is a dict get from base.configure """ ssh = shell_server.get_ssh(parser["NFS_ip"], parser["NFS_usr"] , parser["NFS_pwd"]) # get ssh object #cmd = cmd_HAagent.overview_cmd() #s_stdin, s_stdout, s_stderr = ssh.exec_command(cmd) #overview = s_stdout.read() cluster_file_content = file.get_file_content(parser["cluster_file_path"] , ssh) print cluster_file_content ssh.close() if not cluster_file_content: return False if cluster_name in cluster_file_content: return True return False def is_node_exists(cluster_name , node_name , parser): """ check is node in HAagent :param cluster_name : cluster name :param node_name : node name :param parser : is a dict get from base.configure """ ssh = shell_server.get_ssh(parser["PrimaryOS_ip"], parser["PrimaryOS_usr"], parser["PrimaryOS_pwd"]) # get ssh object cmd = cmd_HAagent.overview_cmd() s_stdin, s_stdout, s_stderr = ssh.exec_command(cmd) overview = s_stdout.read() # get overview in host terminal ssh = shell_server.get_ssh(parser["NFS_ip"], parser["NFS_usr"], parser["NFS_pwd"]) cluster_file_content = file.get_remote_file_content(parser["cluster_file_path"] ,ssh) # get cluster file content in nfs print overview print cluster_file_content ssh.close() if node_name in overview and cluster_file_content: return True return False def get_vm_infofail(node_name , vm_name , parser ,ssh=None): return __get_vm_fail(node_name , vm_name, parser, ssh) def __get_vm_fail(node_name ,vm_name , parser ,ssh=None): cluster_file_content = file.get_file_content(parser["cluster_file_path"], ssh) # get cluster file content print cluster_file_content res = json.loads(cluster_file_content)["nodes"][node_name]["vms"][vm_name]["last_fail"] # get json information return __vm_fail_parse(res) def __vm_fail_parse(fail): fail_model = HAagent_terminal.Vm_lastfail_messages for row in fail_model: key = row[0] # fail type value = row[1] # fail message if value == fail: return key def get_node_infofail(node_name , parser , ssh=None): return __get_node_fail(node_name, parser, ssh) def __get_node_fail(node_name, parser, ssh): cluster_file_content = file.get_file_content(parser["cluster_file_path"], ssh) res = json.loads(cluster_file_content)["nodes"][node_name]["last_fail"] return __node_fail_parse(res) def __node_fail_parse(fail): fail_model = HAagent_terminal.Node_lastfail_messages for key , value in fail_model.iteritems(): if value == fail: return key def get_node_role(name , parser): ssh = shell_server.get_ssh(parser["NFS_ip"], parser["NFS_usr"], parser["NFS_pwd"]) cluster_file_content = file.get_remote_file_content(parser["cluster_file_path"] , ssh) # get cluster file content in nfs try: res = json.loads(cluster_file_content)["nodes"][name]["role"] ssh.close() return role_parse(res) except KeyError: return "Key not found" def role_parse(role): if role == 0: return "primary" elif role == 1: return "backup" elif role == 2: return "slave" else: return "role not found" if __name__ == '__main__': #cluster_file_content = file.get_file_content("/var/ha/images/clusterFile.txt") #jsonString = json.loads(cluster_file_content) #print jsonString["nodes"]["n1"]["role"] #print jsonString["nodes"]["n1"]["role"] == 0 parser["NFS_ip"] = "192.168.1.106" parser["NFS_usr"] = "testagent" parser["NFS_pwd"] = "root" ssh = shell_server.get_ssh(parser["NFS_ip"], parser["NFS_usr"], parser["NFS_pwd"]) cluster_file_content = file.get_remote_file_content(parser["cluster_file_path"] ,ssh) # get cluster file content in nfs

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lsc830621@gmail.com

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yyang116/Leetcode-Journey

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class Solution: def candy(self, ratings: List[int]) -> int: l=len(ratings) if(l<2): return l candy=[1 for x in range(l)] for i in range(l-1): if(ratings[i]<ratings[i+1]): candy[i+1]=candy[i]+1 for i in range(1,l): if(ratings[l-i-1]>ratings[l-i] and candy[l-i-1]<=candy[l-i]): candy[l-i-1]=candy[l-i]+1 return sum(candy)

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noreply@github.com

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sujithksam92/SearchEngineProject

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#!/Users/sujithsam/Documents/Studies/Stevens/Sem-2/BIS-660-Web-Mining/Research_Engine_Project/finalproject/bin/python3.7 # $Id: rst2html4.py 7994 2016-12-10 17:41:45Z milde $ # Author: David Goodger <goodger@python.org> # Copyright: This module has been placed in the public domain. """ A minimal front end to the Docutils Publisher, producing (X)HTML. The output conforms to XHTML 1.0 transitional and almost to HTML 4.01 transitional (except for closing empty tags). """ try: import locale locale.setlocale(locale.LC_ALL, '') except: pass from docutils.core import publish_cmdline, default_description description = ('Generates (X)HTML documents from standalone reStructuredText ' 'sources. ' + default_description) publish_cmdline(writer_name='html4', description=description)

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alseb4991/proyprogweb1.0

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#!c:\users\alan\desktop\finalproy\scripts\python.exe # # The Python Imaging Library. # $Id$ # # a utility to identify image files # # this script identifies image files, extracting size and # pixel mode information for known file formats. Note that # you don't need the PIL C extension to use this module. # # History: # 0.0 1995-09-01 fl Created # 0.1 1996-05-18 fl Modified options, added debugging mode # 0.2 1996-12-29 fl Added verify mode # 0.3 1999-06-05 fl Don't mess up on class exceptions (1.5.2 and later) # 0.4 2003-09-30 fl Expand wildcards on Windows; robustness tweaks # from __future__ import print_function import getopt import glob import logging import sys from PIL import Image if len(sys.argv) == 1: print("PIL File 0.4/2003-09-30 -- identify image files") print("Usage: pilfile [option] files...") print("Options:") print(" -f list supported file formats") print(" -i show associated info and tile data") print(" -v verify file headers") print(" -q quiet, don't warn for unidentified/missing/broken files") sys.exit(1) try: opt, args = getopt.getopt(sys.argv[1:], "fqivD") except getopt.error as v: print(v) sys.exit(1) verbose = quiet = verify = 0 logging_level = "WARNING" for o, a in opt: if o == "-f": Image.init() id = sorted(Image.ID) print("Supported formats:") for i in id: print(i, end=' ') sys.exit(1) elif o == "-i": verbose = 1 elif o == "-q": quiet = 1 elif o == "-v": verify = 1 elif o == "-D": logging_level = "DEBUG" logging.basicConfig(level=logging_level) def globfix(files): # expand wildcards where necessary if sys.platform == "win32": out = [] for file in files: if glob.has_magic(file): out.extend(glob.glob(file)) else: out.append(file) return out return files for file in globfix(args): try: im = Image.open(file) print("%s:" % file, im.format, "%dx%d" % im.size, im.mode, end=' ') if verbose: print(im.info, im.tile, end=' ') print() if verify: try: im.verify() except: if not quiet: print("failed to verify image", end=' ') print("(%s:%s)" % (sys.exc_info()[0], sys.exc_info()[1])) except IOError as v: if not quiet: print(file, "failed:", v) except: import traceback if not quiet: print(file, "failed:", "unexpected error") traceback.print_exc(file=sys.stdout)

[ "Alan Sebastian Fuentes Toscano" ]

Alan Sebastian Fuentes Toscano

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/answers/advent-7.py

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thedude42/adventofcode2020

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refs/heads/main

2023-01-30T00:23:13.544006

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import sys import re from collections import namedtuple from typing import List, Dict class Bag(): ''' class to hold the 'contains' relationship for a particular bag type ''' BagRule = namedtuple('BagRule', ["count", "name"]) name_re = re.compile(r'(\w+ \w+) \w+') rule_re = re.compile(r'\s*(\d+) (\w+ \w+) \w+\.?|(no other bags\.)$') def __init__(self, rule: str): self.rule_spec = rule @property def rule_spec(self): return self.__rule_spec @rule_spec.setter def rule_spec(self, rule: str): self.__rule_spec = rule self.__rules = [] name_part, rules = self.__rule_spec.split(" contain ") m = Bag.name_re.match(name_part) self.name = m.group(1) rules = rules.split(", ") for rule in rules: #print(rule) m = Bag.rule_re.match(rule) #print(m) if m.group(3) == "no other bags.": continue self.__rules.append(Bag.BagRule(int(m.group(1)), m.group(2))) @property def name(self): return self.__name @name.setter def name(self, name): self.__name = name @property def rules(self): return self.__rules def contains(self, bag_name) -> bool: for rule in self.__rules: if rule.name == bag_name: return True return False def __hash__(self): return self.name def __eq__(self, other_bag) -> bool: return other_bag.name == self.name def __repr__(self) -> str: return self.__name def get_bags_containing(bag_list: List, containd_bag_name: str) -> List[Bag]: result = [] for bag in bag_list: if bag.contains(containd_bag_name): result.append(bag) return result def get_nested_sum(bag_index: Dict[str, Bag], bag_name: str, factor: int) -> int: running_sum = 0 for rule in bag_index[bag_name].rules: running_sum += rule.count * factor running_sum += get_nested_sum(bag_index, rule.name, rule.count*factor) return running_sum def main(): if len(sys.argv) != 2: print("Single input filename required, no more, no less.") sys.exit(1) bags = [] with open(sys.argv[1], 'r') as infile: for rule_line in infile: bags.append(Bag(rule_line)) contains_shinygold = get_bags_containing(bags, "shiny gold") contains_shinygold_set = set([ bag.name for bag in contains_shinygold ]) while len(contains_shinygold) != 0: next_bags = [] for bag in contains_shinygold: next_bags += get_bags_containing(bags, bag.name) for bag in next_bags: contains_shinygold_set.add(bag.name) contains_shinygold = next_bags print("Found {} total bags that could contain shiny gold".format(len(contains_shinygold_set))) bagname_index = { b.name:b for b in bags } contained_bags_sum = get_nested_sum(bagname_index, "shiny gold", 1) print("shiny gold bag has {} nested bags".format(contained_bags_sum)) if __name__ == '__main__': main()

[ "sk8rdie42@gmail.com" ]

sk8rdie42@gmail.com

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/wormpose/commands/predict_dataset.py

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#!/usr/bin/env python """ Predicts videos using a trained model """ import logging import multiprocessing as mp import os import random import shutil import tempfile from argparse import Namespace from functools import partial from typing import Tuple import numpy as np import tensorflow as tf from wormpose.commands import _log_parameters from wormpose.commands.utils.results_saver import ResultsSaver from wormpose.commands.utils.time_sampling import resample_results from wormpose.config import default_paths from wormpose.config.default_paths import RESULTS_FILENAME, CONFIG_FILENAME from wormpose.config.experiment_config import load_config, add_config_argument from wormpose.dataset.features import Features from wormpose.dataset.loader import get_dataset_name from wormpose.dataset.loader import load_dataset from wormpose.dataset.loaders.resizer import ResizeOptions from wormpose.images.scoring import BaseScoringDataManager, ScoringDataManager, ResultsScoring from wormpose.machine_learning.best_models_saver import BestModels from wormpose.machine_learning.predict_data_generator import PredictDataGenerator from wormpose.pose.centerline import skeletons_to_angles from wormpose.pose.headtail_resolution import resolve_head_tail from wormpose.pose.results_datatypes import ( ShuffledResults, OriginalResults, BaseResults, ) logging.basicConfig() logger = logging.getLogger(__name__) logger.setLevel(logging.DEBUG) tf.get_logger().setLevel(logging.INFO) def _make_tf_dataset(data_generator, batch_size: int, image_shape): def run(video_name): data_gen = partial(data_generator.run, video_name=video_name) tf_dset = tf.data.Dataset.from_generator( data_gen, tf.float32, tf.TensorShape([batch_size, image_shape[0], image_shape[1], 1]), ) return tf_dset return run def _can_resolve_results(shuffled_results: ShuffledResults, score_threshold: float, video_name: str) -> bool: scores = shuffled_results.scores if np.all(np.isnan(scores)): logger.error(f"Calculated scores are all invalid, stopping analysis for {video_name}") return False if np.max(scores) < score_threshold: logger.error( f"There is not one frame where the error metric is above the threshold {score_threshold} " f"in the whole video {video_name}, stopping analysis. Maybe the model didn't train properly." ) return False return True class _Predictor(object): def __init__(self, results_scoring: ResultsScoring, keras_model): self.keras_model = keras_model self.results_scoring = results_scoring def __call__( self, num_frames: int, input_frames, scoring_data_manager: BaseScoringDataManager, features: Features, ) -> Tuple[OriginalResults, ShuffledResults]: # run all frames through the neural network to get a result theta without head/tail decision network_predictions = self.keras_model.predict(input_frames)[:num_frames] logger.info(f"Predicted {len(network_predictions)} frames") shuffled_results = ShuffledResults(random_theta=network_predictions) original_results = OriginalResults( theta=skeletons_to_angles(features.skeletons, theta_dims=network_predictions.shape[1]), skeletons=features.skeletons, scores=None, ) # calculate image similarity for each frame, for the two solutions self.results_scoring(results=shuffled_results, scoring_data_manager=scoring_data_manager) avg_score = np.max(shuffled_results.scores, axis=1).mean() logger.info(f"Calculated image similarity, average: {avg_score:.4f}") resample_results(shuffled_results, features.timestamp) resample_results(original_results, features.timestamp) return original_results, shuffled_results def _apply_resize_factor(results: BaseResults, resize_factor: float): results.skeletons /= resize_factor def _parse_arguments(dataset_path: str, kwargs: dict): if kwargs.get("work_dir") is None: kwargs["work_dir"] = default_paths.WORK_DIR if kwargs.get("num_process") is None: kwargs["num_process"] = os.cpu_count() if kwargs.get("temp_dir") is None: kwargs["temp_dir"] = tempfile.gettempdir() if kwargs.get("batch_size") is None: kwargs["batch_size"] = 512 if kwargs.get("score_threshold") is None: kwargs["score_threshold"] = 0.7 if kwargs.get("video_names") is None: kwargs["video_names"] = None if kwargs.get("random_seed") is None: kwargs["random_seed"] = None kwargs["temp_dir"] = tempfile.mkdtemp(dir=kwargs["temp_dir"]) dataset_name = get_dataset_name(dataset_path) kwargs["experiment_dir"] = os.path.join(kwargs["work_dir"], dataset_name) if kwargs.get("model_path") is None: default_models_dir = os.path.join(kwargs["experiment_dir"], default_paths.MODELS_DIRS) kwargs["model_path"] = BestModels(default_models_dir).best_model_path if kwargs.get("config") is None: kwargs["config"] = os.path.join(kwargs["experiment_dir"], CONFIG_FILENAME) _log_parameters(logger.info, {"dataset_path": dataset_path}) _log_parameters(logger.info, kwargs) return Namespace(**kwargs) def predict(dataset_path: str, **kwargs): """ Use a trained model to predict the centerlines of worm for videos in a dataset :param dataset_path: Root path of the dataset containing videos of worm """ args = _parse_arguments(dataset_path, kwargs) mp.set_start_method("spawn", force=True) if args.random_seed is not None: os.environ["TF_DETERMINISTIC_OPS"] = "1" random.seed(args.random_seed) np.random.seed(args.random_seed) tf.random.set_seed(args.random_seed) results_root_dir = os.path.join(args.experiment_dir, default_paths.RESULTS_DIR) os.makedirs(results_root_dir, exist_ok=True) config = load_config(args.config) dataset = load_dataset( dataset_loader=config.dataset_loader, dataset_path=dataset_path, selected_video_names=args.video_names, resize_options=ResizeOptions(resize_factor=config.resize_factor), ) keras_model = tf.keras.models.load_model(args.model_path, compile=False) results_saver = ResultsSaver( temp_dir=args.temp_dir, results_root_dir=results_root_dir, results_filename=RESULTS_FILENAME ) tf_dataset_maker = _make_tf_dataset( data_generator=PredictDataGenerator( dataset=dataset, num_process=args.num_process, temp_dir=args.temp_dir, image_shape=config.image_shape, batch_size=args.batch_size, ), batch_size=args.batch_size, image_shape=config.image_shape, ) results_scoring = ResultsScoring( frame_preprocessing=dataset.frame_preprocessing, num_process=args.num_process, temp_dir=args.temp_dir, image_shape=config.image_shape, ) predictor = _Predictor(results_scoring=results_scoring, keras_model=keras_model) for video_name in dataset.video_names: logger.info(f'Processing video: "{video_name}"') features = dataset.features_dataset[video_name] template_indexes = features.labelled_indexes if len(template_indexes) == 0: logger.error( f"Can't calculate image metric, there is no labelled frame in the video to use as a template, " f"stopping analysis for {video_name}." ) continue original_results, shuffled_results = predictor( input_frames=tf_dataset_maker(video_name), num_frames=dataset.num_frames(video_name), features=features, scoring_data_manager=ScoringDataManager( video_name=video_name, frames_dataset=dataset.frames_dataset, features=features, ), ) results = {"original": original_results, "unaligned": shuffled_results} if _can_resolve_results(shuffled_results, video_name=video_name, score_threshold=args.score_threshold,): final_results = resolve_head_tail( shuffled_results=shuffled_results, original_results=original_results, frame_rate=features.frame_rate, score_threshold=args.score_threshold, ) results["resolved"] = final_results _apply_resize_factor(results["resolved"], config.resize_factor) _apply_resize_factor(results["unaligned"], config.resize_factor) results_saver.save(results=results, video_name=video_name) # cleanup shutil.rmtree(args.temp_dir) def main(): import argparse parser = argparse.ArgumentParser() # model infos parser.add_argument( "--model_path", type=str, help="Load model from this path, or use best model from work_dir.", ) parser.add_argument("--batch_size", type=int) # inputs parser.add_argument("dataset_path", type=str) parser.add_argument( "--video_names", type=str, nargs="+", help="Only analyze a subset of videos. If not set, will analyze all videos in dataset_path.", ) add_config_argument(parser) parser.add_argument("--temp_dir", type=str, help="Where to store temporary intermediate results") parser.add_argument("--work_dir", type=str, help="Root folder for all experiments") # multiprocessing params parser.add_argument("--num_process", type=int, help="How many worker processes") # parameters of results processing parser.add_argument( "--score_threshold", type=float, help="Image metric score threshold : discard results scoring lower than this value." " Fine tune this value using the script calibrate_dataset.py", ) parser.add_argument("--random_seed", type=int, help="Optional random seed for deterministic results") args = parser.parse_args() predict(**vars(args)) if __name__ == "__main__": main()

[ "laetitia.hebert@oist.jp" ]

laetitia.hebert@oist.jp

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/FaceRecognition-Webapp/DnnRecognizer.py

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[]

no_license

jbkarle/PyImageConf2018

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be7f080487dbdb99e6f52941cc26b41123882caa

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# License Agreement # 3-clause BSD License # # Copyright (C) 2018, Xperience.AI, all rights reserved. # # Third party copyrights are property of their respective owners. # # Redistribution and use in source and binary forms, with or without modification, # are permitted provided that the following conditions are met: # # * Redistributions of source code must retain the above copyright notice, # this list of conditions and the following disclaimer. # # * Redistributions in binary form must reproduce the above copyright notice, # this list of conditions and the following disclaimer in the documentation # and/or other materials provided with the distribution. # # * Neither the names of the copyright holders nor the names of the contributors # may be used to endorse or promote products derived from this software # without specific prior written permission. # # This software is provided by the copyright holders and contributors "as is" and # any express or implied warranties, including, but not limited to, the implied # warranties of merchantability and fitness for a particular purpose are disclaimed. # In no event shall copyright holders or contributors be liable for any direct, # indirect, incidental, special, exemplary, or consequential damages # (including, but not limited to, procurement of substitute goods or services; # loss of use, data, or profits; or business interruption) however caused # and on any theory of liability, whether in contract, strict liability, # or tort (including negligence or otherwise) arising in any way out of # the use of this software, even if advised of the possibility of such damage. import cv2 import numpy class DnnRecognizer(): def __init__(self, model_path='data/openface.nn4.small2.v1.t7', model_mean = [0, 0, 0], model_in_size = (96, 96), model_scale = 1.0 / 255, conf_threshold = 0.6): self.known_faces = dict() self.model = cv2.dnn.readNetFromTorch(model_path) self.mean = model_mean self.scale = model_scale self.in_size = model_in_size self.confidence = conf_threshold def enroll(self, imageBuffer, name): vec = self._face2vec(imageBuffer) self.known_faces[name] = vec def recognize(self, imageBuffer): vec = self._face2vec(imageBuffer) best_match_name = 'unknown' best_match_score = self.confidence # NOTE: Replace iteritems() method to items() if you use Python3 for name, descriptor in self.known_faces.items(): score = vec.dot(descriptor.T) if (score > best_match_score): best_match_score = score best_match_name = name return best_match_name def _face2vec(self, imageBuffer): dataFromBuffer = numpy.frombuffer(imageBuffer, dtype=numpy.uint8) image = cv2.imdecode(dataFromBuffer, cv2.IMREAD_COLOR) blob = cv2.dnn.blobFromImage(image, self.scale, self.in_size, self.mean, False, False) self.model.setInput(blob) vec = self.model.forward() return vec

[ "spmallick@gmail.com" ]

spmallick@gmail.com

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/app/measurement/migrations/0039_auto_20210423_2203.py

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MIT

2023-04-28T17:01:07

2019-03-18T19:03:32

Python

UTF-8

Python

false

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py

# Generated by Django 3.1.8 on 2021-04-23 22:03 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('measurement', '0038_auto_20210414_1911'), ] operations = [ migrations.AddField( model_name='archiveday', name='p05', field=models.FloatField(default=0), preserve_default=False, ), migrations.AddField( model_name='archiveday', name='p10', field=models.FloatField(default=0), preserve_default=False, ), migrations.AddField( model_name='archiveday', name='p90', field=models.FloatField(default=0), preserve_default=False, ), migrations.AddField( model_name='archiveday', name='p95', field=models.FloatField(default=0), preserve_default=False, ), migrations.AddField( model_name='archivehour', name='p05', field=models.FloatField(default=0), preserve_default=False, ), migrations.AddField( model_name='archivehour', name='p10', field=models.FloatField(default=0), preserve_default=False, ), migrations.AddField( model_name='archivehour', name='p90', field=models.FloatField(default=0), preserve_default=False, ), migrations.AddField( model_name='archivehour', name='p95', field=models.FloatField(default=0), preserve_default=False, ), migrations.AddField( model_name='archivemonth', name='p05', field=models.FloatField(default=0), preserve_default=False, ), migrations.AddField( model_name='archivemonth', name='p10', field=models.FloatField(default=0), preserve_default=False, ), migrations.AddField( model_name='archivemonth', name='p90', field=models.FloatField(default=0), preserve_default=False, ), migrations.AddField( model_name='archivemonth', name='p95', field=models.FloatField(default=0), preserve_default=False, ), migrations.AddField( model_name='archiveweek', name='p05', field=models.FloatField(default=0), preserve_default=False, ), migrations.AddField( model_name='archiveweek', name='p10', field=models.FloatField(default=0), preserve_default=False, ), migrations.AddField( model_name='archiveweek', name='p90', field=models.FloatField(default=0), preserve_default=False, ), migrations.AddField( model_name='archiveweek', name='p95', field=models.FloatField(default=0), preserve_default=False, ), ]

[ "jontconnolly@gmail.com" ]

jontconnolly@gmail.com

7c12aa31b26bf8faa5fa8916f6ea06e98186cba2

f722cfc58ffb73fb336cdbea28eeb264b928b21d

/testwebsite/testwebsite/views.py

c6e387d1d51afd1e3dbc3192827a0606eb18a6fb

[]

no_license

dipeshanandparab/DjangoCertificationProject

46b66626603b71831fcff9a9bdea9fb1ebfc1f76

d046c87d63d5eb1205e2ca189083a6ccd2f58572

refs/heads/master

2020-07-26T09:25:43.890549

2019-09-15T14:13:49

208,603,238

0

null

UTF-8

Python

false

105

py

from django.http import HttpResponse def blogPage(request): return HttpResponse("Blog Home Page")

[ "noreply@github.com" ]

noreply@github.com

5e05b6b9b39006785cc1c655918b72ebd92fe4a6

b7f856717e407c698453b3fddde74dc19cb81ebc

/solve/solver.py

abd766c05f81f527039bc8954dfadcd4ea596b74

[]

no_license

grace0925/sudoku-solver

22702915dbd290c1409d7d0840b93b51772e67f5

7e0a8e94b418dd5a1e3e259828e3b5f545da7369

refs/heads/master

2021-01-09T17:47:50.007917

2020-03-30T04:19:41

242,395,747

0

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UTF-8

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2,499

py

board = [ [2,0,3,8,0,0,0,0,0], [0,9,0,4,0,0,3,6,0], [5,0,0,0,6,3,0,2,0], [6,0,7,0,0,0,0,9,8], [0,0,5,9,0,0,0,1,6], [4,0,0,0,7,0,2,0,3], [0,0,0,3,0,4,0,0,0], [0,0,0,0,2,0,0,0,0], [0,0,8,0,0,0,0,0,0] ] def pretty_print_board(board): for i, row in enumerate(board): if i % 3 == 0 and i != 0: print("- - - - - - - - - - - - -") for j, col in enumerate(row): if j == 8: print(str(board[i][j]) + " ", end="") print("|") elif j % 3 == 0: print("| ", end="") print(str(board[i][j]) + " ", end="") else: print(str(board[i][j]) + " ", end="") def find_empty_square(board): for i in range(len(board)): for j in range(len(board[0])): if board[i][j] == 0: print(i, j) return i, j return None # check if number if valid at certain position on the board def is_valid(board, num, pos): if not check_col(board, num, pos): return False elif not check_row(board, num, pos): return False elif not check_square(board, num, pos): return False return True def check_square(board, num, pos): square_pos = (pos[0]//3*3, pos[1]//3*3) for i in range(square_pos[0], square_pos[0]+3): for j in range(square_pos[1], square_pos[1]+3): if (i,j) != pos and num == board[i][j]: print("False => " + str((i, j))) return False return True def check_row(board, num, pos): for i in range(len(board[0])): if num == board[pos[0]][i] and (pos[0],[i]) != pos: print("False => " + str((pos[0],i))) return False return True def check_col(board, num, pos): for j in range(len(board)): if num == board[j][pos[1]] and (j,pos[1]) != pos: print("False => " + str((j, pos[1]))) return False return True def solve(board): first_empty = find_empty_square(board) # base case: finished filling the board if not first_empty: return True else: row, col = first_empty for i in range(1,10): print("for " + str(i)) if is_valid(board, i, (row,col)): board[row][col] = i if solve(board): return True board[row][col] = 0 return False solve(board) pretty_print_board(board)

[ "graceliu0925@gmail.com" ]

graceliu0925@gmail.com

91bb39e87b153c78a084acbdc38998fcc5de7e04

5a01774b1815a3d9a5b02b26ca4d6ba9ecf41662

/Module 2/Chapter03/django-myproject-03/quotes/models.py

1659b30889e4e5de96390dfb7a8897a216d15bfe

[ "MIT" ]

permissive

PacktPublishing/Django-Web-Development-with-Python

bf08075ff0a85df41980cb5e272877e01177fd07

9f619f56553b5f0bca9b5ee2ae32953e142df1b2

refs/heads/master

2023-04-27T22:36:07.610076

2023-01-30T08:35:11

66,646,080

39

41

MIT

2023-04-17T10:45:45

2016-08-26T12:30:45

Python

UTF-8

Python

false

3,578

py

# -*- coding: UTF-8 -*- from __future__ import unicode_literals import os from PIL import Image from django.db import models from django.utils.timezone import now as timezone_now from django.utils.translation import ugettext_lazy as _ from django.utils.encoding import python_2_unicode_compatible from django.conf import settings from django.core.urlresolvers import reverse from django.core.urlresolvers import NoReverseMatch from django.core.files.storage import default_storage as storage from utils.models import UrlMixin THUMBNAIL_SIZE = getattr(settings, "QUOTES_THUMBNAIL_SIZE", (50, 50)) def upload_to(instance, filename): now = timezone_now() filename_base, filename_ext = os.path.splitext(filename) return "quotes/%s%s" % ( now.strftime("%Y/%m/%Y%m%d%H%M%S"), filename_ext.lower(), ) @python_2_unicode_compatible class InspirationalQuote(UrlMixin): author = models.CharField(_("Author"), max_length=200) quote = models.TextField(_("Quote")) picture = models.ImageField(_("Picture"), upload_to=upload_to, blank=True, null=True) language = models.CharField(_("Language"), max_length=2, blank=True, choices=settings.LANGUAGES) class Meta: verbose_name = _("Inspirational Quote") verbose_name_plural = _("Inspirational Quotes") def __str__(self): return self.quote def get_url_path(self): try: return reverse("quote_detail", kwargs={"id": self.pk}) except NoReverseMatch: return "" def save(self, *args, **kwargs): super(InspirationalQuote, self).save(*args, **kwargs) # generate thumbnail picture version self.create_thumbnail() def create_thumbnail(self): if not self.picture: return "" file_path = self.picture.name filename_base, filename_ext = os.path.splitext(file_path) thumbnail_file_path = "%s_thumbnail.jpg" % filename_base if storage.exists(thumbnail_file_path): # if thumbnail version exists, return its url path return "exists" try: # resize the original image and return url path of the thumbnail version f = storage.open(file_path, 'r') image = Image.open(f) width, height = image.size if width > height: delta = width - height left = int(delta/2) upper = 0 right = height + left lower = height else: delta = height - width left = 0 upper = int(delta/2) right = width lower = width + upper image = image.crop((left, upper, right, lower)) image = image.resize(THUMBNAIL_SIZE, Image.ANTIALIAS) f_mob = storage.open(thumbnail_file_path, "w") image.save(f_mob, "JPEG") f_mob.close() return "success" except: return "error" def get_thumbnail_picture_url(self): if not self.picture: return "" file_path = self.picture.name filename_base, filename_ext = os.path.splitext(file_path) thumbnail_file_path = "%s_thumbnail.jpg" % filename_base if storage.exists(thumbnail_file_path): # if thumbnail version exists, return its url path return storage.url(thumbnail_file_path) # return original as a fallback return self.picture.url def title(self): return self.quote

[ "bhavinsavalia@packtpub.com" ]

bhavinsavalia@packtpub.com

f868eeff27e7b4b07996e98e3f5ae73e36692f8c

f19df7e4cf34af41b17fb636d4c77ab32f93f20f

/Game tutorial/rpg_game/core/Marker.py

0d1bbe0ff377fa34804ba7afd2bb395390e0de79

[]

no_license

Sequd/python

2fcaa60ee0a535619b50ece0eb8bf9a43ad798e2

3a08ab1285b004f57266853384ed9ef4a91163d3

refs/heads/master

2021-07-10T02:19:40.922424

2021-04-04T15:05:15

55,693,736

0

null

2018-05-11T14:39:59

2016-04-07T12:43:40

Python

UTF-8

Python

false

1,051

py

import pygame import random from Constants import * class Marker: def __init__(self, screen, x=250, y=250): self.screen = screen self.x = x self.y = y def update(self): pass def render(self): surface = pygame.Surface((160, 120), pygame.SRCALPHA) shift = 20 pygame.draw.ellipse(surface, (255, 155, 155), (10, 56, 60, 30)) pygame.draw.ellipse(surface, (0, 0, 0), (10, 56, 60, 30), 1) pygame.draw.ellipse(surface, WHITE, (0 + shift, 40 + shift, 40, 20)) pygame.draw.polygon(surface, WHITE, [[0 + shift, 10 + shift], [0 + shift, 50 + shift], [40 + shift, 50 + shift], [40 + shift, 10 + shift]]) pygame.draw.ellipse(surface, (255, 155, 155), (0 + shift, 0 + shift, 40, 20)) pygame.draw.ellipse(surface, (155, 155, 155), (0 + shift, 0 + shift, 40, 20), 1) self.screen.blit(surface, (self.x, self.y))

[ "e.korunov@gmail.com" ]

e.korunov@gmail.com

10f058e9cf7828acf4110b55d6c7158a21525c0c

eeee463b73fe69972401e28ae856e551f4c30567

/Digit Classification/custom_knn_implementation.py

ffccdf770bedcf5d20a3cd04a46c218c67b59b63

[ "MIT" ]

permissive

pushprajsingh14/Digit-classification-knn

828e2823809eb4795b9412bd00a2f315ddc2d7d7

65ae68c764159c8eb49358828e177df47e2b2ee5

refs/heads/master

2022-11-22T07:51:10.314289

2020-07-26T18:31:56

282,705,438

0

null

UTF-8

Python

false

1,844

py

import numpy as np from sklearn.model_selection import train_test_split data = np.load('./datasets/mnist_train_small.npy') x = data[:, 1:] y = data[:, 0] x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.33, random_state=42) class CustomKNN: # constructor def __init__(self, n_neighbours=5): self.n_neighbours = n_neighbours # training function def fit(self, x, y): self._x = (x - x.mean()) / x.std() # standardisation self._y = y # predict point # given a single point, tell me which class it belongs to def predict_point(self, point): # storing the dis of given 'point' from each point in training data list_dist = [] # these points are from my training data for x_point, y_point in zip(self._x, self._y): dist_point = ((point - x_point) ** 2).sum() list_dist.append([dist_point, y_point]) # sorting the list according to the distance sorted_dist = sorted(list_dist) top_k = sorted_dist[:self.n_neighbours] # taking the count items, counts = np.unique(np.array(top_k)[:, 1], return_counts=True) ans = items[np.argmax(counts)] return ans # predict # give me answer for each number in the array def predict(self, x): results = [] x = (x - x.mean()) / x.std() for point in x: results.append(self.predict_point(point)) return np.array(results, dtype=int) # score to measure my accuracy def score(self, x, y): return sum(self.predict(x) == y) / len(y) model = CustomKNN() model.fit(x_train, y_train) print("accuracy is:") print(model.score(x_test[:100], y_test[:100]) * 100, "%") print("thankyou")

[ "noreply@github.com" ]

noreply@github.com

50587eb991551487cd46558996781fa84fa73bdb

030437bc949054b0110a4979276ce19dd03c124e

/game_controller.py

4a8d0ca92170380805d3623c46faa3366238047f

[]

no_license

dusanradivojevic/DeepSeaAdventures

439ede65b705bcf2e8bece546023f8fbaf1ab990

7a6f6efa475469a83ec8c1e02c931a31cf079d36

refs/heads/master

2022-12-24T13:07:42.539056

2020-10-03T13:14:34

253,089,595

0

null

UTF-8

Python

false

5,793

py

import time import math import pygame from sounds import SoundPlayer import game_data as gd import threading import level_data as levels import npc # Changes time lapsed from number of seconds to hours : minutes : seconds format def time_convert(seconds): min = (seconds // 60) % 60 sec = seconds % 60 hours = min // 60 return f'{hours} : {min} : {round(sec,2)}' # Checks whether given array of fish types contains type the same as asked def has_type(array, given_type): if len(array) == 0: return False if array[0] == npc.NpcSprite: return True for tp in array: if tp == given_type: return True return False class TaskController: def __init__(self, task): self.task = task self.fishes = [] self.score = 0 def task_update(self, eaten_fish, score): if self.task.score_needed != 0: self.score += score if has_type(self.task.fish_types, type(eaten_fish)): self.fishes.append(eaten_fish) def get_text_surface(self, font): rows = [ font.render('Tasks:', False, gd.white_color) ] if self.task.score_needed != 0: sc = self.score if self.score < self.task.score_needed else self.task.score_needed text = f'{round(sc)}/{self.task.score_needed}' \ f' Score' rows.append(font.render(text, False, gd.white_color)) # 0/500 Score index = 0 for tp in self.task.fish_types: num = self.number_of_eaten_fish_of_type(tp) if self.number_of_eaten_fish_of_type(tp) < \ self.task.fish_numbers[index] else self.task.fish_numbers[index] text = f'{num}/{self.task.fish_numbers[index]}' \ f' {levels.get_name_of_type(tp)}' rows.append(font.render(text, False, gd.white_color)) # 0/5 BlueFish index += 1 return rows def number_of_eaten_fish_of_type(self, tp): if tp == npc.NpcSprite: return len(self.fishes) count = 0 for fish in self.fishes: if type(fish) == tp: count += 1 return count def is_completed(self): if self.score < self.task.score_needed: return False # for each type of fish needed checks how much of them player has eaten checking_fish_index = 0 for tp in self.task.fish_types: count = self.number_of_eaten_fish_of_type(tp) if count < self.task.fish_numbers[checking_fish_index]: return False checking_fish_index += 1 # next number of eaten fish needed return True class GameController: def __init__(self, list, player, generator): self.level = 1 self.score = 0 self.fish_eaten = [] self.start_time = time.time() self.end_time = time.time() self.played_time = "0" self.fishes = list self.player = player self.generator = generator self.work = True self.call_danger_fish() self.task_controller = TaskController(levels.get_random_task(self.level)) def change_level(self): if self.task_controller.is_completed(): self.level += 1 if self.level > gd.NUM_OF_LEVELS: pygame.event.post(gd.GAME_WIN_EVENT) return self.generator.change_level() self.task_controller = TaskController(levels.get_random_task(self.level)) self.player.change_level_image(self.level) pygame.event.post(gd.LEVEL_CHANGED_EVENT) def stop(self): self.work = False self.end_time = time.time() time_lapsed = self.end_time - self.start_time self.played_time = time_convert(time_lapsed) def start(self): for fish in self.fishes: if self.player.size < ((100 - gd.FISH_SIZE_DIFFERENCE) / 100) * fish.size \ and fish.rect.left < self.player.rect.centerx < fish.rect.right\ and fish.rect.top + 0.2 * fish.rect.height < self.player.rect.centery < \ fish.rect.bottom - 0.2 * fish.rect.height: self.game_over() elif self.player.size > ((100 + gd.FISH_SIZE_DIFFERENCE) / 100) * fish.size\ and self.player.rect.left < fish.rect.centerx < self.player.rect.right\ and self.player.rect.top + 0.2 * self.player.rect.height < fish.rect.centery < \ self.player.rect.bottom - 0.2 * self.player.rect.height: self.eat(fish) def call_danger_fish(self): if not self.work: return if round(time.time() - self.start_time) != 0: self.generator.spawn_danger_fish() threading.Timer(gd.DANGER_FISH_SPAWN_FREQUENCY, self.call_danger_fish).start() def get_score(self): return f'Score: {round(self.score)}' def get_level(self): return f'Level: {self.level}' def get_text_surface(self, font): return self.task_controller.get_text_surface(font) def eat(self, fish): SoundPlayer(gd.eating_sound_path, False).play() fish.stop() score_amount = (gd.SCORE_PERCENT / 100) * fish.size self.score += score_amount self.fish_eaten.append(fish) self.task_controller.task_update(fish, score_amount) self.change_level() # self.player.size += (gd.SIZE_PERCENT / 100) * fish.size def game_over(self): # Show end screen pygame.event.post(gd.GAME_OVER_EVENT) # Raises QUIT event (should be changed so it can be # distinguished from button interruption)

[ "r.dusan97@gmail.com" ]

r.dusan97@gmail.com

da8ab0b242ac7d0fd2aff929e11c271cf5e4f784

94a9c4765e245ad1a12a52e28de919bdbe0cb3b8

/HolaMundo_Channel/remove_unuseless.py

db84d9e3c99e9081f5970eda03edf0966160bb29

[]

no_license

je-castelan/Algorithms_Python

d2b86e7300c8d9a877eb5b4bb507f901e8507967

9056ddebb0c73839430d54d19fcdc5588263cfd4

refs/heads/master

2023-02-26T00:45:30.812225

2021-01-21T06:16:10

301,629,472

0

null

UTF-8

Python

false

382

py

import functools def removeUnuseless(arr): # Remove null or zero elements. Note than filter require to be saved on list initializtion # Challenge of Hola Mundo Channel on https://www.youtube.com/watch?v=MXmQM_Uehtk&t=584s lista = list(filter(lambda x: x ,arr)) return lista if __name__ == "__main__": print(removeUnuseless([5,3,66,False,76,None,45,0,False,0]))

[ "ingkstr@gmail.com" ]

ingkstr@gmail.com

fb5d205f628987e7f8e328d80f149b1bf79740ad

52a42437c4f8f978e1d9da1074d487ce8123d228

/path_sum_3.py

c6645a212c8b62dd26108303729a0e5d2240bacf

[]

no_license

iorzt/leetcode-algorithms

22bc987d76c52817dd6fe94e0a8331b3729e36a1

7508201ac7fe057769100f168bb3e5e598137894

refs/heads/master

2021-05-25T12:09:10.172318

2020-03-26T02:31:13

127,387,116

0

null

UTF-8

Python

false

1,235

py

""" You are given a binary tree in which each node contains an integer value. Find the number of paths that sum to a given value. The path does not need to start or end at the root or a leaf, but it must go downwards (traveling only from parent nodes to child nodes). The tree has no more than 1,000 nodes and the values are in the range -1,000,000 to 1,000,000. Example: root = [10,5,-3,3,2,null,11,3,-2,null,1], sum = 8 10 / \ 5 -3 / \ \ 3 2 11 / \ \ 3 -2 1 Return 3. The paths that sum to 8 are: 1. 5 -> 3 2. 5 -> 2 -> 1 3. -3 -> 11 """ class Solution: def __init__(self): self.result = 0 """ cost: 1124ms >19.33 https://leetcode.com/submissions/detail/210791563/ """ def pathSum(self, root: TreeNode, sum: int) -> int: if not root: return 0 self.helper(root, sum) self.pathSum(root.left, sum) self.pathSum(root.right, sum) return self.result def helper(self, root: TreeNode, sum: int): if not root: return if sum - root.val == 0: self.result += 1 self.helper(root.left, sum - root.val) self.helper(root.right, sum - root.val)

[ "gg.baibo@gmail.com" ]

gg.baibo@gmail.com

6f536a3e58cddf6f23b1f280c0d75a694929f726

476a8b674a76b9925dac4498b2f64cf1dee08910

/deepnet_training.py

5de72a72d09c7cf3e90935fe5490c9ea9f6f64d5

[ "MIT" ]

permissive

jacenfox/pytorch-framework

24905de58352604e24f7ceb6f7a705cb5ad72a5b

771642a6f40b1fa4f4c90ffa40e2cb90c3fd42d4

refs/heads/master

2020-04-30T02:08:35.579186

2019-06-27T17:25:05

176,551,018

0

null

UTF-8

Python

false

8,254

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import torch import os import sys import numpy as np import time import glob from utils import time_elapse_parser import colorama class TrainDeepNet(object): """docstring for TrainDeepNet""" def __init__(self, model_path, model, domain_adapt, learning_rate, callbacks, model_name='LDR2HDR', device='cuda'): self.model_path = model_path if not os.path.exists(model_path): os.makedirs(model_path) print('[Output Path] %s' % (model_path)) self.callbacks = callbacks self.device = device self.model = model self.MODEL_NAME=model_name self.do_domain_adapt = domain_adapt self.optimizer = torch.optim.Adam(self.model.parameters(), lr=learning_rate, weight_decay=0, eps=1e-8) self.epoch = 0 self.epoch_ckpt = 0 self._best_loss = None def map_data_to_device(self, data, is_training): ''' map dataloader data to torch device (cpu, gpu) data: list or dict ''' if type(data) is list: data = [d.to(self.device) for d in data] if type(data) is dict: for key in data.keys(): try: if type(data[key]) is torch.Tensor: data[key] = data[key].to(self.device) if is_training: data[key].requires_grad = True else: data[key].requires_grad = False if data[key].dtype is torch.float64: data[key] = data[key].type(torch.float32) else: # string, fname data[key] = data[key] except TypeError: print('Type Error in processing: ', key, type(data[key]), data[key].shape, data[key].dtype) raise TypeError return data def loop(self, train_loader, test_loader, max_epochs): _start_time = time.time() self.max_epochs = max_epochs for i in range(self.epoch_ckpt, max_epochs): _epoch_start_time = time.time() self.epoch = i self.train(train_loader) self.test(test_loader) print('Epoch [%03d/%03d] Epoch time [%s] Running time [%s]' % (self.epoch, self.max_epochs, time_elapse_parser(time.time() - _epoch_start_time), time_elapse_parser(time.time() - _start_time))) if (i) % 5 == 0: print(colorama.Fore.GREEN + '[Runing CMD] %s' % ' '.join(sys.argv[0:]) + colorama.Style.RESET_ALL) print(colorama.Fore.GREEN + '[Output dir] %s' % self.model_path + colorama.Style.RESET_ALL) print(colorama.Back.CYAN + '='*50 + colorama.Style.RESET_ALL) def train(self, train_loader): # Train the model self.model.train() epoch = self.epoch total_step = len(train_loader) print_list = {'loss':[], 'GPU': [], 'Loading': [], 'CBs': []} _last_batch_end_time = time.time() for i, samples in enumerate(train_loader): print_list['Loading'].append(time.time() - _last_batch_end_time) _avg_gpu_time_start = time.time() # map data to device target = self.map_data_to_device(samples['target'], is_training=True) data = self.map_data_to_device(samples['data'], is_training=True) # forward network_output = self.model(data, epoch, self.max_epochs) loss = self.model.loss(network_output, target) print_list['loss'].append(loss.data.cpu().numpy()) # update self.optimizer.zero_grad() loss.backward() self.optimizer.step() print_list['GPU'].append(time.time() - _avg_gpu_time_start) # callbacks _avg_callback_time_start = time.time() self.after_batch_callbacks(network_output, target, data, loss_dict=self.model.loss_dict, is_training=True) print_list['CBs'].append(time.time() - _avg_callback_time_start) # additional process _last_batch_end_time = time.time() if (i) % np.maximum(1, int(total_step/5)) == 0: print(' Step[%03d/%03d] Loss: [%.4f] Time(s): CPU[%.2f] GPU[%.1f] CBs[%.1f] per batch' % (i, total_step, np.mean(print_list['loss']), np.mean(print_list['Loading']), np.mean(print_list['GPU']), np.mean(print_list['CBs']))) print_list = {'loss':[], 'GPU': [], 'Loading': [], 'CBs': []} self.save_checkpoint(loss.data.cpu().numpy()) self.after_epoch_callbacks(network_output, target, data, loss_dict=self.model.loss_dict, is_training=True) self.model.ibatch = 0 def test(self, test_loader): # Test the model self.model.eval() # In test phase, no gradients (for memory efficiency) print(' Testing', end =" ") _test_time_start = time.time() with torch.no_grad(): for i, samples in enumerate(test_loader): target = self.map_data_to_device(samples['target'], is_training=False) data = self.map_data_to_device(samples['data'], is_training=False) network_output = self.model(data, self.epoch, self.max_epochs) self.after_batch_callbacks(network_output, target, data, loss_dict=self.model.loss_dict, is_training=False) self.after_epoch_callbacks(network_output, target, data, loss_dict=self.model.loss_dict, is_training=False) print('time [%.2f]' % (time.time()-_test_time_start)) self.model.ibatch = 0 def after_batch_callbacks(self, network_output, target, data, loss_dict, is_training): callbacks = self.callbacks for callback_fun in callbacks: callback_fun.batch(self, network_output, target, data, loss_dict, is_training) def after_epoch_callbacks(self, network_output, target, data, loss_dict, is_training): callbacks = self.callbacks for callback_fun in callbacks: callback_fun.epoch(self, network_output, target, data, loss_dict, is_training) def save_checkpoint(self, loss): # Save the model checkpoint log_path = os.path.join(self.model_path, 'log') if not os.path.exists(log_path): os.makedirs(log_path) ckpt_data = {'epoch': self.epoch, 'state_dict': self.model.state_dict(), 'loss': loss, } torch.save(ckpt_data, os.path.join(log_path, '.%s.model.last.ckpt'%(self.MODEL_NAME))) if self.epoch % 50 == 0 or self.epoch >= (self.max_epochs-5): torch.save(ckpt_data, os.path.join(log_path, '.%s.model.%03d.ckpt'%(self.MODEL_NAME, self.epoch))) if (self._best_loss is None) or (self._best_loss > loss): self._best_loss = loss torch.save(ckpt_data, os.path.join(log_path, '.%s.model.best.ckpt'%(self.MODEL_NAME))) def load_checkpoint(self, model_path, epoch=-1): """ :return: """ if (epoch == -1) or (epoch == 'last'): filename = sorted(glob.glob(os.path.join(model_path, 'log', '.%s.model.last.ckpt'%(self.MODEL_NAME))))[-1] elif epoch == 'best': filename = sorted(glob.glob(os.path.join(model_path, 'log', '.%s.model.best.ckpt'%(self.MODEL_NAME))))[-1] else: filename = os.path.join(model_path, 'log', '.%s.model.%03d.ckpt'%(self.MODEL_NAME) % (epoch)) if os.path.exists(filename): print("Loading model from %s" % (filename)) else: print("Cannot load model from %s" % (filename)) return ckpt_data = torch.load(filename) self.model.load_state_dict(ckpt_data['state_dict']) self.epoch_ckpt = ckpt_data['epoch'] self._best_loss = ckpt_data['loss'] if 'loss' in ckpt_data.keys() else None def resume_training(self): self.load_checkpoint(self.model_path, epoch=-1)

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from __future__ import print_function import sys import json import time from pyspark import SparkContext from pyspark.streaming import StreamingContext from pyspark.streaming.kinesis import KinesisUtils, InitialPositionInStream if __name__ == "__main__": applicationName = "PythonStreamingKinesis" streamName= "KinesisDemo" endpointUrl="https://kinesis.us-east-1.amazonaws.com" regionName="us-east-1" sc = SparkContext(appName=applicationName) ssc = StreamingContext(sc, 5) print("appname is" + applicationName + streamName + endpointUrl + regionName) lines = KinesisUtils.createStream(ssc, applicationName, streamName, endpointUrl, regionName, InitialPositionInStream.LATEST, 2) def filter_tweets(x): json_tweet = json.loads(x) if json_tweet.has_key('lang'): if json_tweet['lang'] == 'ar': return True return False lines.foreachRDD(lambda rdd: rdd.filter(filter_tweets).coalesce(1).saveAsTextFile("./tweets/%f" % time.time()) ) ssc.start() ssc.awaitTermination()

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""" University of Minnesota Aerospace Engineering and Mechanics - UAV Lab Copyright 2019 Regents of the University of Minnesota See: LICENSE.md for complete license details Author: Louis Mueller, Chris Regan """ import numpy as np import copy import VspParse import OpenFdm #%% Constants in2m = 0.0254 #%% Aircraft Definition def LoadAircraftDef(load): oFdm = {} #%% Aero Data # Parse VSP files and merge the data into a single set vspData = VspParse.ParseAll(load['Aero']['vspPath'], load['Aero']['aircraftName'], load['Aero']['aeroName']) # vspData['stabTab'] is NOT a copy, values are linked!! # Define some of the model specific conversions for VSP to oFdm convertDef = {} convertDef['Lunit'] = 'm' # Specify the units used in the VSP model. # Surface name converstions convertDef['Surf'] = {} convertDef['Surf']['names'] = vspData['Stab']['surfNames'] convertDef['Surf']['Vsp'] = ['d' + s + '_rad' for s in convertDef['Surf']['names']] convertDef['Surf']['Vsp_Grp'] = ['ConGrp_' + str(d) for d in range(1, 1+len(convertDef['Surf']['Vsp']))] convertDef['Surf']['oFdm'] = ['d' + s + '_rad' for s in convertDef['Surf']['names']] # Convert the VSP Aero data to oFdm oFdm['Aero'] = OpenFdm.LoadVsp(vspData, convertDef) oFdm['Aero']['surfNames'] = vspData['Stab']['surfNames'] #%% Mass Properties - FIXIT - Need external MassProperty Source # Mass Properties, mass has actual. Inertias are scaled from US25e test data. oFdm['MassProp'] = {} # Mass Properties oFdm['MassProp']['mass_kg'] = 3.188 # Measured with Battery and Sony a6000 camera cgX = 0.4645 # Wing 1/4 chord cgY = 0.0 cgZ = 0.0 oFdm['MassProp']['rCG_S_m'] = np.array([cgX, cgY, cgZ]) Ixx = 0.07151 * (oFdm['MassProp']['mass_kg'] / 1.959) Iyy = 0.08636 * (oFdm['MassProp']['mass_kg'] / 1.959) Izz = 0.15364 * (oFdm['MassProp']['mass_kg'] / 1.959) Ixy = 0.0 * (oFdm['MassProp']['mass_kg'] / 1.959) Ixz = 0.0 * (oFdm['MassProp']['mass_kg'] / 1.959) Iyz = 0.0 * (oFdm['MassProp']['mass_kg'] / 1.959) oFdm['MassProp']['inertia_kgm2'] = np.array([[Ixx, Ixy, Ixz], [Ixy, Iyy, Iyz], [Ixz, Iyz, Izz]]) #%% Flight Control System oFdm['FCS'] = {} # Pilot input scaling/sensitivity pilot = {} pilot['kRoll'] = 60.0 * np.pi / 180.0 # Normalized stick to cmdRoll pilot['kPitch'] = -30.0 * np.pi / 180.0 # Normalized stick to cmdPitch pilot['kYaw'] = -10.0 * np.pi / 180.0 # Normalized stick to cmdYaw pilot['kFlap'] = 20.0 * np.pi / 180.0 # Normalized stick to cmdFlap oFdm['FCS']['Pilot'] = pilot # Mixer mixer = {} mixer['surfNames'] = oFdm['Aero']['surfNames'] mixer['inputs'] = ['cmdRoll_rps', 'cmdPitch_rps', 'cmdYaw_rps', 'cmdFlap_rad'] mixer['surfEff'] = [ [ 1.00000,-1.00000, 0.25000,-0.25000], [ 0.00000, 0.00000,-1.00000,-1.00000], [ 0.00000, 0.00000,-1.00000, 1.00000], [ 1.00000, 1.00000, 0.00000, 0.00000] ] mixer['surfMix'] = np.linalg.pinv(mixer['surfEff']) mixer['surfMix'][abs(mixer['surfMix'] / mixer['surfMix'].max()) < 0.05] = 0 oFdm['FCS']['Mixer'] = mixer #%% Actuator dynamic model, second-order with freeplay and limits act = {} for surf in oFdm['Aero']['surfNames']: act[surf] = {} act[surf]['bandwidth_hz'] = 4.0 # Guess act[surf]['bandwidth_rps'] = act[surf]['bandwidth_hz'] * 2*np.pi act[surf]['lag_nd'] = round(200.0 / act[surf]['bandwidth_hz']) # Based on 200 Hz Sim Frame act[surf]['delay_s'] = 0.020 # Guess act[surf]['freeplay_rad'] = 1.0 * np.pi/180.0 # Guess act[surf]['min'] = -30.0 * np.pi/180.0 act[surf]['max'] = 30.0 * np.pi/180.0 oFdm['Act'] = act #%% Create Propulsion data (motor and prop) prop = {} prop['nameMotor'] = 'Power25' prop['rMotor_S_m'] = np.array([43 * in2m, 0, 1 * in2m]) prop['sMotor_deg'] = np.array([0, 0, 0]) prop['nameProp'] = 'APC 12x6e' prop['rProp_S_m'] = prop['rMotor_S_m'] + np.array([2 * in2m, 0, 0]) prop['sProp_deg'] = prop['sMotor_deg'] prop['p_factor'] = 0.0 prop['sense'] = 1.0 oFdm['Prop'] = {} oFdm['Prop']['Main'] = prop #%% Create Sensor data oFdm['Sensor'] = {} ## IMU oFdm['Sensor']['Imu'] = {} # Accel Location and Orientation oFdm['Sensor']['Imu']['Accel'] = {} oFdm['Sensor']['Imu']['Accel']['r_S_m'] = [0,0,0] oFdm['Sensor']['Imu']['Accel']['s_deg'] = [0,0,0] # Accel Error Model Parameters (units are _mps2) oFdm['Sensor']['Imu']['Accel']['delay_s'] = [0,0,0] oFdm['Sensor']['Imu']['Accel']['lag'] = [0,0,0] oFdm['Sensor']['Imu']['Accel']['noiseVar'] = [0,0,0] oFdm['Sensor']['Imu']['Accel']['drift_ps'] = [0,0,0] oFdm['Sensor']['Imu']['Accel']['gain_nd'] = [1,1,1] oFdm['Sensor']['Imu']['Accel']['bias'] = [0,0,0] # Gyro Location and Orientation oFdm['Sensor']['Imu']['Gyro'] = {} oFdm['Sensor']['Imu']['Gyro']['r_S_m'] = oFdm['Sensor']['Imu']['Accel']['r_S_m'] oFdm['Sensor']['Imu']['Gyro']['s_deg'] = oFdm['Sensor']['Imu']['Accel']['s_deg'] # Gyro Error Model Parameters (units are _rps) oFdm['Sensor']['Imu']['Gyro']['delay_s'] = oFdm['Sensor']['Imu']['Accel']['delay_s'] oFdm['Sensor']['Imu']['Gyro']['lag'] = oFdm['Sensor']['Imu']['Accel']['lag'] oFdm['Sensor']['Imu']['Gyro']['noiseVar'] = [0,0,0] oFdm['Sensor']['Imu']['Gyro']['drift_ps'] = [0,0,0] oFdm['Sensor']['Imu']['Gyro']['gain_nd'] = [1,1,1] oFdm['Sensor']['Imu']['Gyro']['bias'] = [0,0,0] # Magnetometer Location and Orientation oFdm['Sensor']['Imu']['Mag'] = {} oFdm['Sensor']['Imu']['Mag']['r_S_m'] = oFdm['Sensor']['Imu']['Accel']['r_S_m'] oFdm['Sensor']['Imu']['Mag']['s_deg'] = oFdm['Sensor']['Imu']['Accel']['s_deg'] # Magnetometer Error Model Parameters (units are _nT) oFdm['Sensor']['Imu']['Mag']['delay_s'] = oFdm['Sensor']['Imu']['Accel']['delay_s'] oFdm['Sensor']['Imu']['Mag']['lag'] = oFdm['Sensor']['Imu']['Accel']['lag'] oFdm['Sensor']['Imu']['Mag']['noiseVar'] = [0,0,0] oFdm['Sensor']['Imu']['Mag']['drift_ps'] = [0,0,0] oFdm['Sensor']['Imu']['Mag']['gain_nd'] = [1,1,1] oFdm['Sensor']['Imu']['Mag']['bias'] = [0,0,0] ## GPS oFdm['Sensor']['Gps'] = {} # Gps Location oFdm['Sensor']['Gps']['r_S_m'] = [0,0,0] # FIXIT - Not currently used # GPS Position Error Model # NOTE units are radians, radians, meters for Lat and Long!! oFdm['Sensor']['Gps']['Pos'] = {} oFdm['Sensor']['Gps']['Pos']['delay_s'] = [0,0,0] oFdm['Sensor']['Gps']['Pos']['lag'] = [0,0,0] oFdm['Sensor']['Gps']['Pos']['noiseVar'] = [0,0,0] oFdm['Sensor']['Gps']['Pos']['drift_ps'] = [0,0,0] oFdm['Sensor']['Gps']['Pos']['gain_nd'] = [1,1,1] oFdm['Sensor']['Gps']['Pos']['bias'] = [0,0,0] # GPS Velocity Error Model oFdm['Sensor']['Gps']['Vel'] = {} oFdm['Sensor']['Gps']['Vel']['delay_s'] = [0,0,0] oFdm['Sensor']['Gps']['Vel']['lag'] = [0,0,0] oFdm['Sensor']['Gps']['Vel']['noiseVar'] = [0,0,0] oFdm['Sensor']['Gps']['Vel']['drift_ps'] = [0,0,0] oFdm['Sensor']['Gps']['Vel']['gain_nd'] = [1,1,1] oFdm['Sensor']['Gps']['Vel']['bias'] = [0,0,0] ## Airdata oFdm['Sensor']['Pitot'] = {} # Airdata Location and Orientation oFdm['Sensor']['Pitot']['r_S_m'] = [0,0,0] oFdm['Sensor']['Pitot']['s_deg'] = [0,0,0] # Airdata Error Model # Pitot Vector - [presStatic_Pa, presTip_Pa, temp_C] oFdm['Sensor']['Pitot']['delay_s'] = [0,0,0] oFdm['Sensor']['Pitot']['lag'] = [0,0,0] oFdm['Sensor']['Pitot']['noiseVar'] = [0,0,0] oFdm['Sensor']['Pitot']['drift_ps'] = [0,0,0] oFdm['Sensor']['Pitot']['gain_nd'] = [1,1,1] oFdm['Sensor']['Pitot']['bias'] = [0,0,0] #%% Create Gear data mainH = 6.5 * in2m mainY = 0.0 * in2m mainX = 8.0 * in2m tailX = 39.0 * in2m tailH = 5.5 * in2m tailY = 0.0 * in2m wingH = -1.5 * in2m wingY = 39.0 * in2m wingX = 25.0 * in2m cgX = oFdm['MassProp']['rCG_S_m'][0] massMain = oFdm['MassProp']['mass_kg'] * (tailX - cgX) / -(mainX - tailX) massTail = oFdm['MassProp']['mass_kg'] * (mainX - cgX) / -(tailX - cgX) massWing = massTail # Needs some mass to compute the spring parameters, but should be 0.0 oFdm['Gear'] = {} # Belly skid oFdm['Gear']['Main'] = {} oFdm['Gear']['Main']['rGear_S_m'] = np.array([mainX, mainY, -mainH]) oFdm['Gear']['Main']['FricStatic'] = 0.8 oFdm['Gear']['Main']['FricDynamic'] = 0.5 oFdm['Gear']['Main']['FricRoll'] = 0.25 wnDesire = 5.0 * 2*np.pi dRatio = 1.0 oFdm['Gear']['Main']['kSpring_Npm'] = wnDesire * wnDesire * massMain oFdm['Gear']['Main']['dampSpring_Nspm'] = 2 * dRatio * wnDesire * massMain # Tail skid oFdm['Gear']['Tail'] = {} oFdm['Gear']['Tail']['rGear_S_m'] = np.array([tailX, tailY, -tailH]) oFdm['Gear']['Tail']['FricStatic'] = 0.8 oFdm['Gear']['Tail']['FricDynamic'] = 0.5 oFdm['Gear']['Tail']['FricRoll'] = 0.25 wnDesire = 5.0 * 2*np.pi dRatio = 1.0 oFdm['Gear']['Tail']['kSpring_Npm'] = wnDesire * wnDesire * massTail oFdm['Gear']['Tail']['dampSpring_Nspm'] = 2 * dRatio * wnDesire * massTail # Wing skid - left oFdm['Gear']['WingL'] = {} oFdm['Gear']['WingL']['rGear_S_m'] = np.array([wingX, -wingY, -wingH]) oFdm['Gear']['WingL']['FricStatic'] = 0.8 oFdm['Gear']['WingL']['FricDynamic'] = 0.5 oFdm['Gear']['WingL']['FricRoll'] = 0.25 wnDesire = 5.0 * 2*np.pi dRatio = 1.0 oFdm['Gear']['WingL']['kSpring_Npm'] = wnDesire * wnDesire * massWing oFdm['Gear']['WingL']['dampSpring_Nspm'] = 2 * dRatio * wnDesire * massWing # Wing skid - right oFdm['Gear']['WingR'] = copy.deepcopy(oFdm['Gear']['WingL']) oFdm['Gear']['WingR']['rGear_S_m'][1] = -oFdm['Gear']['WingL']['rGear_S_m'][1] #%% Return return (oFdm)

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import os class Config(object): SECRET_KEY = os.environ.get("JWT_SECRET_KEY") class TestingConfig(Config): DEBUG = True url ="dbname = 'dfhkvc5kqeh9bi' host = 'ec2-54-235-156-60.compute-1.amazonaws.com' port = '5432' \ user = 'ehiewszseuqzyg' password = 'aff8667735390b9eebe291e92f4ad1d75a255aeefc38b8382f368e7a2a0650bd'" class DevelopmentConfig(Config): DEBUG = True url = os.getenv("URL") config={"test":TestingConfig, "dev":DevelopmentConfig}

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#Chapter2/Example8.py a=10 b=3 print(a//b)

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py

# Copyright 2016 The Chromium Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. import json import os import shutil import tempfile import unittest import mock from telemetry.testing import browser_test_runner from gpu_tests import path_util from gpu_tests import gpu_integration_test path_util.AddDirToPathIfNeeded(path_util.GetChromiumSrcDir(), 'tools', 'perf') from chrome_telemetry_build import chromium_config class GpuIntegrationTestUnittest(unittest.TestCase): def setUp(self): self._test_state = {} def testSimpleIntegrationTest(self): self._RunIntegrationTest( 'simple_integration_unittest', ['unittest_data.integration_tests.SimpleTest.unexpected_error', 'unittest_data.integration_tests.SimpleTest.unexpected_failure'], ['unittest_data.integration_tests.SimpleTest.expected_flaky', 'unittest_data.integration_tests.SimpleTest.expected_failure'], ['unittest_data.integration_tests.SimpleTest.expected_skip'], []) # It might be nice to be more precise about the order of operations # with these browser restarts, but this is at least a start. self.assertEquals(self._test_state['num_browser_starts'], 6) def testIntegrationTesttWithBrowserFailure(self): self._RunIntegrationTest( 'browser_start_failure_integration_unittest', [], ['unittest_data.integration_tests.BrowserStartFailureTest.restart'], [], []) self.assertEquals(self._test_state['num_browser_crashes'], 2) self.assertEquals(self._test_state['num_browser_starts'], 3) def testIntegrationTestWithBrowserCrashUponStart(self): self._RunIntegrationTest( 'browser_crash_after_start_integration_unittest', [], [('unittest_data.integration_tests.BrowserCrashAfterStartTest.restart')], [], []) self.assertEquals(self._test_state['num_browser_crashes'], 2) self.assertEquals(self._test_state['num_browser_starts'], 3) def testRetryLimit(self): self._RunIntegrationTest( 'test_retry_limit', ['unittest_data.integration_tests.TestRetryLimit.unexpected_failure'], [], [], ['--retry-limit=2']) # The number of attempted runs is 1 + the retry limit. self.assertEquals(self._test_state['num_test_runs'], 3) def testRepeat(self): self._RunIntegrationTest( 'test_repeat', [], ['unittest_data.integration_tests.TestRepeat.success'], [], ['--repeat=3']) self.assertEquals(self._test_state['num_test_runs'], 3) def testAlsoRunDisabledTests(self): self._RunIntegrationTest( 'test_also_run_disabled_tests', ['unittest_data.integration_tests.TestAlsoRunDisabledTests.skip', 'unittest_data.integration_tests.TestAlsoRunDisabledTests.flaky'], # Tests that are expected to fail and do fail are treated as test passes [('unittest_data.integration_tests.' 'TestAlsoRunDisabledTests.expected_failure')], [], ['--also-run-disabled-tests']) self.assertEquals(self._test_state['num_flaky_test_runs'], 4) self.assertEquals(self._test_state['num_test_runs'], 6) def testStartBrowser_Retries(self): class TestException(Exception): pass def SetBrowserAndRaiseTestException(): gpu_integration_test.GpuIntegrationTest.browser = ( mock.MagicMock()) raise TestException gpu_integration_test.GpuIntegrationTest.browser = None gpu_integration_test.GpuIntegrationTest.platform = None with mock.patch.object( gpu_integration_test.serially_executed_browser_test_case.\ SeriallyExecutedBrowserTestCase, 'StartBrowser', side_effect=SetBrowserAndRaiseTestException) as mock_start_browser: with mock.patch.object( gpu_integration_test.GpuIntegrationTest, 'StopBrowser') as mock_stop_browser: with self.assertRaises(TestException): gpu_integration_test.GpuIntegrationTest.StartBrowser() self.assertEqual(mock_start_browser.call_count, gpu_integration_test._START_BROWSER_RETRIES) self.assertEqual(mock_stop_browser.call_count, gpu_integration_test._START_BROWSER_RETRIES) def _RunIntegrationTest(self, test_name, failures, successes, skips, additional_args): config = chromium_config.ChromiumConfig( top_level_dir=path_util.GetGpuTestDir(), benchmark_dirs=[ os.path.join(path_util.GetGpuTestDir(), 'unittest_data')]) temp_dir = tempfile.mkdtemp() test_results_path = os.path.join(temp_dir, 'test_results.json') test_state_path = os.path.join(temp_dir, 'test_state.json') try: browser_test_runner.Run( config, [test_name, '--write-full-results-to=%s' % test_results_path, '--test-state-json-path=%s' % test_state_path] + additional_args) with open(test_results_path) as f: test_result = json.load(f) with open(test_state_path) as f: self._test_state = json.load(f) actual_successes, actual_failures, actual_skips = ( self._ExtractTestResults(test_result)) self.assertEquals(set(actual_failures), set(failures)) self.assertEquals(set(actual_successes), set(successes)) self.assertEquals(set(actual_skips), set(skips)) finally: shutil.rmtree(temp_dir) def _ExtractTestResults(self, test_result): delimiter = test_result['path_delimiter'] failures = [] successes = [] skips = [] def _IsLeafNode(node): test_dict = node[1] return ('expected' in test_dict and isinstance(test_dict['expected'], basestring)) node_queues = [] for t in test_result['tests']: node_queues.append((t, test_result['tests'][t])) while node_queues: node = node_queues.pop() full_test_name, test_dict = node if _IsLeafNode(node): if all(res not in test_dict['expected'].split() for res in test_dict['actual'].split()): failures.append(full_test_name) elif test_dict['expected'] == test_dict['actual'] == 'SKIP': skips.append(full_test_name) else: successes.append(full_test_name) else: for k in test_dict: node_queues.append( ('%s%s%s' % (full_test_name, delimiter, k), test_dict[k])) return successes, failures, skips

[ "csineneo@gmail.com" ]

csineneo@gmail.com

e55983dca1feb96f5b4323bc57bdc755ed4a5c17

ca97dafb6309f4ad0f0026ca8473d7db48120459

/apps/utils/wangediter.py

4d48e445b9f80519e83e1c54e7325c6b063a087d

[]

no_license

ITFengShuiMaster/-DjangoRestProject-

6a1aa9bddefa25761c4c0ae16351bb2cb8d93a37

679cf527d850e3ee087dd7e80c976fd29341c291

refs/heads/master

2022-12-16T00:53:12.593745

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null

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2018-10-11T07:54:49

JavaScript

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Python

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1,192

py

# -*- coding:utf-8 _*- __author__ = 'luyue' __date__ = '2018/5/28 14:05' import os from flask import Flask, request,Response UPLOAD_FOLDER = '/TmageUploads' ALLOWED_EXTENSIONS = set(['txt', 'pdf', 'png', 'jpg', 'jpeg', 'gif']) app = Flask(__name__) app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER #文件名合法性验证 def allowed_file(filename): return '.' in filename and \ filename.rsplit('.', 1)[1] in ALLOWED_EXTENSIONS #对文件上传进行相应 app.route("/ImageUpdate",methdos = ["POST"]) def GetImage(): file = request.files[0] if file == None: result = r"error|未成功获取文件，上传失败" res = Response(result) res.headers["ContentType"] = "text/html" res.headers["Charset"] = "utf-8" return res else: if file and allowed_file(file.filename): filename = file.filename file.save(os.path.join(app.config['UPLOAD_FOLDER'], filename)) imgUrl = "http://localhost:5000" + UPLOAD_FOLDER + "/" + filename res = Response(imgUrl) res.headers["ContentType"] = "text/html" res.headers["Charset"] = "utf-8" return res

[ "wxhzq520@sina.com" ]

wxhzq520@sina.com

9040725fac22694501f3f81751cda539d3ce2333

6c6790ff1f940d7bcb35d5b3adec4c8feb0adffd

/url_services/tests/recipes/mommy_recipes.py

c9be044997cbfcb92db83eb7e6907c01caebb811

[]

no_license

alexrosa/django-urlshortener-api

102ea5e16e32c877ed7d3f8469ee3174b0353c9a

eeccb96dccfb8da82052b3899b41bdce2be76662

refs/heads/master

2020-04-17T16:48:14.460993

2019-01-21T13:29:58

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0

null

UTF-8

Python

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278

py

from model_mommy.recipe import Recipe, seq from url_services.models import UrlShortener url_shortener = Recipe(UrlShortener, url_shortener_id=seq(1), absolute_url='www.smartbeans.com.br', short_url='a3b4c5')

[ "alexrosa@gmail.com" ]

alexrosa@gmail.com

5923edf19d7db31a20d3a49ffcc3c7c9da07fe70

3fca5adf482809cf2825b4233362d54917841786

/omnibus/replserver.py

1bcf3d5c805b7e301f99bf048c1c6a934739d6e9

[ "BSD-3-Clause" ]

permissive

wrmsr/omnibus

a5ad19cebd458893b0ae85b5c847761ad6c1ceed

3c4ef5eb17b0fff8593fa6a2284337bf193c18d3

refs/heads/master

2023-01-19T11:50:39.002781

2020-03-12T01:53:53

164,266,924

3

1

BSD-3-Clause

2022-12-26T20:58:22

2019-01-06T01:55:06

Python

UTF-8

Python

false

11,234

py

""" socat - UNIX-CONNECT:repl.sock import sys, threading, pdb, functools def _attach(repl): frame = sys._current_frames()[threading.enumerate()[0].ident] debugger = pdb.Pdb( stdin=repl.conn.makefile('r'), stdout=repl.conn.makefile('w'), ) debugger.reset() while frame: frame.f_trace = debugger.trace_dispatch debugger.botframe = frame frame = frame.f_back debugger.set_step() frame.f_trace = debugger.trace_dispatch """ import ast import codeop import contextlib import errno import functools import logging import os import socket as socket_ import sys import threading import traceback import types import typing as ta import weakref from . import check log = logging.getLogger(__name__) class DisconnectException(Exception): pass class InteractiveSocketConsole: """code.InteractiveConsole but just different enough to not be worth subclassing.""" ENCODING = 'utf-8' def __init__( self, conn: socket_.socket, locals: ta.MutableMapping = None, filename: str = '<console>' ) -> None: super().__init__() if locals is None: locals = { '__name__': '__console__', '__doc__': None, '__console__': self, } self._conn = conn self._locals = locals self._filename = filename self._compiler = codeop.CommandCompiler() self._buffer: ta.List[str] = [] self._count = 0 self._write_count = -1 def reset_buffer(self) -> None: self._buffer = [] @property def conn(self) -> socket_.socket: return self._conn CPRT = 'Type "help", "copyright", "credits" or "license" for more information.' def interact(self, banner: str = None, exitmsg: str = None) -> None: log.info(f'Console {id(self)} on thread {threading.current_thread().ident} interacting') try: ps1 = getattr(sys, 'ps1', '>>> ') ps2 = getattr(sys, 'ps2', '... ') if banner is None: self.write( 'Python %s on %s\n%s\n(%s)\n' % (sys.version, sys.platform, self.CPRT, self.__class__.__name__)) elif banner: self.write('%s\n' % (str(banner),)) more = False while True: try: try: line = self.raw_input(ps2 if more else ps1) except EOFError: self.write('\n') break else: more = self.push_line(line) except KeyboardInterrupt: self.write('\nKeyboardInterrupt\n') self.reset_buffer() more = False if exitmsg is None: self.write('now exiting %s...\n' % self.__class__.__name__) elif exitmsg != '': self.write('%s\n' % exitmsg) except DisconnectException: pass except OSError as oe: if oe.errno == errno.EBADF: pass finally: log.info(f'Console {id(self)} on thread {threading.current_thread().ident} finished') def push_line(self, line: str) -> bool: self._buffer.append(line) source = '\n'.join(self._buffer) more = self.run_source(source, self._filename) if not more: self.reset_buffer() return more def raw_input(self, prompt: str = '') -> str: self.write(prompt) buf = b'' while True: b = self._conn.recv(1) if not b: raise DisconnectException if b == b'\n': break buf += b return buf.decode(self.ENCODING) def write(self, data: str) -> None: self._conn.send(data.encode(self.ENCODING)) def compile( self, source: ta.Union[str, ast.AST], filename: str = '<input>', symbol: str = 'single' ) -> ta.Optional[types.CodeType]: if isinstance(source, ast.AST): return self._compiler.compiler(source, filename, symbol) else: return self._compiler(source, filename, symbol) def run_source( self, source: ta.Union[str, ast.AST], filename: str = '<input>', symbol: str = 'single', ) -> bool: try: code = self.compile(source, filename, symbol) except (OverflowError, SyntaxError, ValueError): # Case 1 (incorrect) self.show_syntax_error(filename) return False if code is None: # Case 2 (incomplete) return True # Case 3 (complete) try: node = ast.parse(source) except (OverflowError, SyntaxError, ValueError): return True if isinstance(node, ast.Module) and node.body and isinstance(node.body[-1], ast.Expr): expr = node.body[-1] source = ast.Interactive( [ *node.body[:-1], ast.Assign( [ast.Name( f'_{self._count}', ast.Store(), lineno=expr.lineno, col_offset=expr.col_offset, )], expr.value, lineno=expr.lineno, col_offset=expr.col_offset, ) ], ) ast.fix_missing_locations(source) self._write_count = self._count code = self.compile(source, filename, symbol) self.run_code(code) return False def run_code(self, code: types.CodeType) -> None: try: exec(code, self._locals) except SystemExit: raise except Exception: self.show_traceback() else: if self._count == self._write_count: self.write(repr(self._locals[f'_{self._count}'])) self.write('\n') self._count += 1 def show_traceback(self) -> None: sys.last_type, sys.last_value, last_tb = ei = sys.exc_info() sys.last_traceback = last_tb try: lines = traceback.format_exception(ei[0], ei[1], last_tb.tb_next) self.write(''.join(lines)) finally: last_tb = ei = None def show_syntax_error(self, filename: str = None) -> None: type, value, tb = sys.exc_info() sys.last_type = type sys.last_value = value sys.last_traceback = tb if filename and type is SyntaxError: # Work hard to stuff the correct filename in the exception try: msg, (dummy_filename, lineno, offset, line) = value.args except ValueError: # Not the format we expect; leave it alone pass else: # Stuff in the right filename value = SyntaxError(msg, (filename, lineno, offset, line)) sys.last_value = value lines = traceback.format_exception_only(type, value) self.write(''.join(lines)) class ReplServer: CONNECTION_THREAD_NAME = 'ReplServerConnection' def __init__( self, path: str, *, file_mode: int = None, poll_interval: float = 0.5, exit_timeout: float = 10.0, ) -> None: super().__init__() self._path = path self._file_mode = file_mode self._poll_interval = poll_interval self._exit_timeout = exit_timeout self._socket: socket_.socket = None self._is_running = False self._consoles_by_threads: ta.MutableMapping[threading.Thread, InteractiveSocketConsole] = weakref.WeakKeyDictionary() # noqa self._is_shut_down = threading.Event() self._should_shutdown = False def __enter__(self): check.state(not self._is_running) check.state(not self._is_shut_down.is_set()) return self def __exit__(self, exc_type, exc_val, exc_tb): if not self._is_shut_down.is_set(): self.shutdown(True, self._exit_timeout) def run(self) -> None: check.state(not self._is_running) check.state(not self._is_shut_down.is_set()) if os.path.exists(self._path): os.unlink(self._path) self._socket = socket_.socket(socket_.AF_UNIX, socket_.SOCK_STREAM) self._socket.settimeout(self._poll_interval) self._socket.bind(self._path) with contextlib.closing(self._socket): self._socket.listen(1) log.info(f'Repl server listening on file {self._path}') self._is_running = True try: while not self._should_shutdown: try: conn, _ = self._socket.accept() except socket_.timeout: continue log.info(f'Got repl server connection on file {self._path}') def run(conn): with contextlib.closing(conn): variables = globals().copy() console = InteractiveSocketConsole(conn, variables) variables['__console__'] = console log.info( f'Starting console {id(console)} repl server connection ' f'on file {self._path} ' f'on thread {threading.current_thread().ident}' ) self._consoles_by_threads[threading.current_thread()] = console console.interact() thread = threading.Thread( target=functools.partial(run, conn), daemon=True, name=self.CONNECTION_THREAD_NAME) thread.start() for thread, console in self._consoles_by_threads.items(): try: console.conn.close() except Exception: log.exception('Error shutting down') for thread in self._consoles_by_threads.keys(): try: thread.join(self._exit_timeout) except Exception: log.exception('Error shutting down') os.unlink(self._path) finally: self._is_shut_down.set() self._is_running = False def shutdown(self, block: bool = False, timeout: float = None) -> None: self._should_shutdown = True if block: self._is_shut_down.wait(timeout=timeout) def _main(): with ReplServer('repl.sock') as repl_server: repl_server.run() if __name__ == '__main__': _main()

[ "timwilloney@gmail.com" ]

timwilloney@gmail.com

266eadfc88787d8d8f35a8ad5c254af232377ec2

54cc98e87d96119571f0d8689d26c4d62d1f84dc

/mywebsite/settings.py

c9d0c7ef9c9819197f8c98ddc1d348acd336a876

[]

no_license

Midnight1/django1

39ae231a5eccf8feae875c7a65c7d6c16de91ffc

a5f3e90a3b5c18b5339296e33a590e118ff0aa9a

refs/heads/master

2021-01-10T20:00:56.007776

2015-09-17T14:43:07

42,661,114

0

null

UTF-8

Python

false

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py

""" Django settings for mywebsite project. Generated by 'django-admin startproject' using Django 1.8.4. For more information on this file, see https://docs.djangoproject.com/en/1.8/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/1.8/ref/settings/ """ # Build paths inside the project like this: os.path.join(BASE_DIR, ...) import os from unipath import Path PROJECT_DIR = Path(__file__).ancestor(2) BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/1.8/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = 'vp+r=_c^+o6j&rmqy!#t+5b&f(6nn7e81m-$d&988k06@+4j5j' # SECURITY WARNING: don't run with debug turned on in production! DEBUG = True ALLOWED_HOSTS = [] # Application definition INSTALLED_APPS = ( 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', ) MIDDLEWARE_CLASSES = ( 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.auth.middleware.SessionAuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', 'django.middleware.security.SecurityMiddleware', ) ROOT_URLCONF = 'mywebsite.urls' TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [PROJECT_DIR.child('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', ], }, }, ] WSGI_APPLICATION = 'mywebsite.wsgi.application' # Database # https://docs.djangoproject.com/en/1.8/ref/settings/#databases DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': os.path.join(BASE_DIR, 'db.sqlite3'), } } # Internationalization # https://docs.djangoproject.com/en/1.8/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/1.8/howto/static-files/ STATIC_URL = '/static/'

[ "hellghost_1@hotmail.com" ]

hellghost_1@hotmail.com

2a3a9ed6867c40b4d06206b52ad915c58b2b2ee5

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/bbs/migrations/0005_comment.py

47635bbb154f2d3b629b00cfe1209892662f4358

[]

no_license

SAKUMAISAO130/python_bbs

4709460290680987de289f88bd1b4b16ffb3dfbb

14028a1f7ca216015089f2c0c549f91e11c21c25

refs/heads/master

2022-09-05T10:31:36.234827

2020-05-27T11:49:35

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0

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2020-05-26T12:45:46

2020-05-25T11:46:50

Python

UTF-8

Python

false

840

py

# Generated by Django 2.1.5 on 2020-05-27 00:49 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('bbs', '0004_auto_20200526_1302'), ] operations = [ migrations.CreateModel( name='Comment', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('category', models.IntegerField(blank=True, default=0, null=True, verbose_name='')), ('user_name', models.CharField(max_length=200, null=True)), ('comment', models.TextField(blank=True, max_length=1000, null=True, verbose_name='')), ('image_path', models.TextField(blank=True, max_length=1000, null=True, verbose_name='')), ], ), ]

[ "colorfullweb@gmail.com" ]

colorfullweb@gmail.com

7278426f46e6ad4358202385753eb0788391aa02

fca96796d913a57b60e5525d0392543c8e5cec24

/node_modules/bcrypt/build/config.gypi

6b7b118899d9539b36b8a36a79d2db03446290cd

[ "MIT" ]

permissive

Sathya4488/login-page-MEAN-stack

817299bd9cafcbad46843a5bb347537c75165598

46fd4388c8a91096616cce8278245208d21a134e

refs/heads/master

2020-05-04T09:57:04.665542

2019-04-24T13:13:57

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UTF-8

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gypi

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[ "sathyamsb91@gmail.com" ]

sathyamsb91@gmail.com

78c967718b00bbe41546036f801047647978a636

aeb8d8e1a25482b1f913aa0b29666d9c024a4bcf

/ccnuoj_webapi/src/__init__.py

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no_license

OutOfCage/CCNUOJ

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f2b07daab6132390ab6fc4d53b01eb528921c244

refs/heads/master

2020-04-01T13:08:05.406472

2018-10-15T17:19:59

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from .global_obj import * from . import model from . import authentication from .authentication import init as authentication_init from . import user from . import judge_scheme from . import problem from . import judge_command from . import judge_request from . import submission

[ "fybmain@gmail.com" ]

fybmain@gmail.com

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/account/urls.py

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[]

no_license

rafiulgits/law

8f8576980a47dc27ef744a9c32447e69630d3eca

42e6e6ac79229b648e023b3ae9c3252919045453

refs/heads/master

2023-03-05T22:05:25.854131

2021-02-20T04:02:52

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from account.views import auth, manage from django.urls import path from django.contrib.auth import views as resetviews from rest_framework_simplejwt.views import TokenRefreshView urlpatterns = [ path('signup/', auth.SignUp.as_view()), path('signin/', auth.SignIn.as_view()), path('access-renew/', TokenRefreshView.as_view()), path('profile/', manage.Profile.as_view()), path('update/', auth.AccountUpdate.as_view()), path('password-change/', auth.PasswordChange.as_view()), path('verify/', auth.VerifyEmail.as_view()), path('password-reset/request/', auth.PasswordResetRequest.as_view()), path('password-reset/verify/', auth.VerifyPasswordRequest.as_view()), path('password-reset/', auth.PasswordResetView.as_view()), ]

[ "avoidcloud@gmail.com" ]

avoidcloud@gmail.com

61da68c0cc57b787ef11ad937a8ba1a75162869f

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/mysite/vehicle_garage/migrations/0005_alter_boat_boat_hin.py

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[]

no_license

aku006/bixly-interview-test

4f4b1a84ca8c5511ccec82ee2f153ce7796667ca

5e5b0767b62ddc31128ca3b0205ea34b707c83c6

refs/heads/main

2023-07-12T21:43:15.841469

2021-08-20T22:28:53

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# Generated by Django 3.2.6 on 2021-08-20 20:50 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('vehicle_garage', '0004_alter_boat_boat_width'), ] operations = [ migrations.AlterField( model_name='boat', name='boat_hin', field=models.CharField(max_length=12), ), ]

[ "aku006@ucr.edu" ]

aku006@ucr.edu

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6358146a22e015791c136f9b018847008ed69d1c

/data_Structure.py

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[]

no_license

kjrendel/HighSchoolCamp

c3942004a6742562d9f3a2818847f1d98a840a93

1969cf4c012415ccc14a12710a2f8c4ef3e187c0

refs/heads/master

2020-06-03T14:22:56.760619

2019-06-14T19:20:55

191,602,802

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""" title: data_Structure author: Kaly date: 2019-06-13 11:32 """ #shakeball # import random # # # def shake_ball(): # inp = input("ask a question") # ans = ("yes definitely","without a doubt",'very doubtful','ask again later',"Don't count on it","Cannot Predict now",\ # "as i see it, yes","No chance in H E double hockey sticks","Literally just no","Come back later I'm busy",\ # "I mean maybe", "I hope so") # return ans[random.randint(0,len(ans))] # print(shake_ball()) #number1 # numbers = [89, 41, 73, 90] # total = 0 # for i in numbers: # total += i # print(total) #number2 # x = list(range(0, 15, 5)) # print(x) #number3 # x = list(range(100, 210, 10)) # print(x) #number4 # x = list(range(80, 32, -8)) # print(x) #number5 # for i in range(3): # print('Alright') # #countdown # countdown_number = 10 # while countdown_number>0: # print(countdown_number, end=" ") # countdown_number-=1

[ "kjrendel@gmail.com" ]

kjrendel@gmail.com

970b980241353efbce82180668a684226303165e

3a41f35d2ce62429627145f74d1558a3e5f5a2c2

/microbots/envs/simple_particle.py

1c42455b69462bdf7d441b7a597530bfd6053e35

[]

no_license

UD-IDS-LAB/Microbot-Control

a90f560aa85c1ed06d2df94a66c514001c6fa2c2

bd80f5b14476ccc6d1faaafac6be0492a60388fa

refs/heads/main

2023-03-19T02:39:09.365863

2021-02-04T01:52:01

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# -*- coding: utf-8 -*- """ Created on Mon Jan 11 15:29:37 2021 @author: Logan """ import gym from gym import spaces import numpy as np import math #material for plotting import matplotlib matplotlib.use('TkAgg') import matplotlib.pyplot as plt import matplotlib.patches as patches class ParticlePlot: def __init__(self, title=None, window_size=[10, 10]): #defualt to array of None so we can call .all() in render() self.last_states = np.array([None, None, None, None]) self.xlim = (window_size[0], window_size[1]) self.ylim = (window_size[0], window_size[1]) #create the plot fig = plt.figure() fig.suptitle(title) #Next, draw a rectangle around the limits rect = patches.Rectangle((self.xlim[0],self.ylim[0]), self.xlim[1]-self.xlim[0], self.ylim[1]-self.ylim[0], linewidth=1,edgecolor='r',facecolor='none') # fig.gca().set(xlim=self.xlim, ylim=self.ylim) fig.gca().add_patch(rect) plt.show(block=False) fig.show() self.fig = fig; def render(self, states): #plot a red circle at the particle's location nextPos = plt.Circle( ( states[0], states[1] ), 0.5, color='r') #get the figure and add the circle fig = plt.gcf() ax = fig.gca() ax.add_patch(nextPos) if (self.last_states != None).all(): dx = states[0] - self.last_states[0] dy = states[1] - self.last_states[1] plt.arrow(self.last_states[0], self.last_states[1], dx, dy, width=0.05, shape='right') plt.pause(.05) self.last_states = states def reset(self): self.last_states = np.array([None, None, None, None]) plt.clf() rect = patches.Rectangle((self.xlim[0],self.ylim[0]), self.xlim[1]-self.xlim[0], self.ylim[1]-self.ylim[0], linewidth=1,edgecolor='r',facecolor='none') # fig.gca().set(xlim=self.xlim, ylim=self.ylim) plt.gca().add_patch(rect) def close(self): plt.show(block=True) class SimpleParticle(gym.Env): """The simple particle model adapted to use opengym""" metadata = {'render.modes': ['human']} def __init__(self, numParticles, phi, stateBounds, dwellTime, maxSteps): super(SimpleParticle, self).__init__() self.visualization = None self.numParticles = numParticles self.phi = phi self.stateBounds = stateBounds #[pMin, pMax, vMin, vMax] self.dwellTime = dwellTime self.maxSteps = maxSteps #action space is 4 discrete values (right, up, left, down) self.action_space = spaces.Discrete(4) #observation space is 4 x numParticles self.observation_space = spaces.Box( np.array([stateBounds[0], stateBounds[2]]), #LB np.array([stateBounds[1], stateBounds[3]]), #UB dtype=np.float32) def reset(self): # Reset the state of the environment to an initial state #### set the state randomly within +- 40% of the bounds #self.states = np.random.default_rng().uniform(low=-1.0, high=1.0, size=self.numParticles*4) #self.states[0:2] = (self.states[0:2] + 1) / 2 * (self.stateBounds[1] - self.stateBounds[0]) + self.stateBounds[0] #self.states[0:2] *= 0.4 #start within 40% of the origin #### set the state to a fixed point self.states = np.array([self.stateBounds[0], self.stateBounds[0], self.stateBounds[3], self.stateBounds[3]]) self.states[0:2] *= 0.4; #scale position to be 40% of max distance # Convert to a 32 bit float to play nice with the pytorch tensors self.states = self.states.astype('float32') self.currentStep = 0 if self.visualization != None: self.visualization.reset() def _next_observation(self): #observe the current state of the particles obs = self.states; return obs #update particle states based on the current action & dynamics def _take_action(self, action): #calculate the velocity (v=vmax always) vMax = self.stateBounds[3]; #determine how the agent would move if the offset was 0 v = np.array([ [vMax], [0] ]) #assume to the right (action = 0) if action == 1: #up v = np.array([ [0], [vMax] ]) if action == 2: #left v = np.array([ [-vMax], [0] ]) if action == 3: #down v = np.array([ [0], [-vMax] ]) #calculate the rotation of the particle c, s = np.cos(self.phi), np.sin(self.phi) R = np.array( [[c, -s], [s, c]] ) #rotate u by angle phi (particle offset) v = np.matmul(R, v) #do the dynamics position = self.states[:2] + np.transpose(v * self.dwellTime) self.states = np.append(position, v) self.states = self.states.astype('float32') def step(self, action): # Execute one time step within the environment self.old_states = self.states self._take_action(action) self.currentStep += 1 #we just advanced by one dwellTime #check if we have reached our timeout or otherwise ended done = False #todo: check if we come within distance of origin if self.currentStep >= self.maxSteps: done = True ### Calculate the Reward ### '''Reward is the minimum distance between the origin and the particle as it moves between the initial and final states''' x0 = self.old_states[0] xf = self.states[0] y0 = self.old_states[1] yf = self.states[1] #calculate slope from dx and dy dx = xf - x0 dy = yf - y0 #first, we can assume cost = distance from final position to origin dist = np.linalg.norm(self.states[0:2]) #check if we are passing by the origin (so we could be closer) if xf*x0 < 0 or yf*y0 < 0: if dx == 0: #moving only vertically dist = abs(x0) if dy == 0: #moving only horizontally dist= abs(y0) if dx != 0 and dy != 0: #moving at an angle m = dy / dx x = (m*m*x0 + m*y0) / (m*m + 1) y = m*(x - x0) + y0 dist = math.min(dist, math.sqrt(x*x + y*y)) #reward the agent by -1 * dist from origin reward = -dist #penalize the agent by 1,000 if it exits the state bounds if xf < self.stateBounds[0] or xf > self.stateBounds[1] or yf < self.stateBounds[0] or yf > self.stateBounds[1]: reward -= 1000; #finally, convert to float32 to play nice with pytorch reward = reward.astype('float32') #finish if we are within 0.01 microns of the goal done = done or (dist < 0.01) newState = self.states #return state, reward, done, next state return self.states, reward, done, newState def _render_to_file(self, filename='data'): # Append the current run to filename (default data.csv) file = open(filename + '.csv', 'a+') file.write(self.dwellTime * self.step, ",", self.states) file.close() def render(self, mode='live', title=None, **kwargs): # Render the environment to the screen or a file if mode == 'file': #render to file (default to data.csv) self._render_to_file(kwargs.get('filename', 'data')) elif mode == 'live': if self.visualization == None: self.visualization = ParticlePlot(title, window_size=self.stateBounds) #scale rendering to the state bounds instead of [-1, 1] in each dim self.visualization.render(self.states) def close(self): super().close() if self.visualization != None: self.visualization.close()

[ "Logiant@users.noreply.github.com" ]

Logiant@users.noreply.github.com

ade3665c82f66c2282de4139af95b6d5e566ae0b

d98fcc71d992c71838eff77c93fba85d2a111e8e

/blog/migrations/0002_comment.py

23dfc71ee25ce73e00d0323ae56562b2584b47d5

[]

no_license

yeimermolina/blog

2a9ae31da35db021abfac233baed93ee0fe7e8b1

900dc89b47aa118089a0aa994058b945e305b5c0

refs/heads/master

2021-05-07T22:14:38.033072

2017-11-01T21:22:56

109,179,291

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py

# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('blog', '0001_initial'), ] operations = [ migrations.CreateModel( name='Comment', fields=[ ('id', models.AutoField(auto_created=True, serialize=False, primary_key=True, verbose_name='ID')), ('name', models.CharField(max_length=80)), ('email', models.EmailField(max_length=254)), ('body', models.TextField()), ('created', models.DateTimeField(auto_now_add=True)), ('updated', models.DateTimeField(auto_now=True)), ('active', models.BooleanField(default=True)), ('post', models.ForeignKey(related_name='comments', to='blog.Post')), ], options={ 'ordering': ('created',), }, ), ]

[ "yeimer.molina@gmail.com" ]

yeimer.molina@gmail.com

d62f0bd20e58a2256dc029f276709c0b9900ded3

0007d76b3a0bb4f5427cba4a00ab1ba244ef7eb2

/RSA_Attack_Padding.py

3919c6d705e4a33ef706def804bfeff363046c37

[]

no_license

hassansallam/RSA_Attack

b4dc4fd8c2d153ebd9c561c201ae03f0f94915d7

650a7f868176186fb5d8c24e9ed0401d960954ef

refs/heads/master

2021-05-31T12:26:43.098089

2016-03-15T10:32:20

null

0

null

UTF-8

Python

false

1,885

py

''' THIS IS RSA ATTACK SYSTEM THAT WORKS IF THE PLAINTEXT IS PADDED ''' import math import binascii # THIS IS THE MAIN METHOD YOUHAVE TO RUN IT TO RUN THE POROGRAM def run(): print'Welcome to RSA attack system' print'Please enter the number you want to factor' n = input("N: ") factor(n) # THIS METHOD FINDS THE MODULO MULTIPLICATVE INVERS def inverse(x, p): inv1 = 1 inv2 = 0 while p != 1: inv1, inv2 = inv2, inv1 - inv2 * (x / p) x, p = p, x % p return inv2 # THIS METHOD FINDS THE INTERGER SUQAURE ROOT OF A NUMBER def intsqrt(n): x = n y = (x + n // x) // 2 while y < x: x = y y = (x + n // x) // 2 return x # THIS METHOD FACTORIZE THE NUMBER TO TO ITS RPRIME FACTORS BASED OF FERMAT FACORING METHOD def factor(n): a = intsqrt(n) b2 = a*a - n b = intsqrt(n) count = 0 while b*b != b2: a = a + 1 b2 = a*a - n b = intsqrt(b2) count += 1 p=a+b q=a-b assert n == p * q print'Factoraizing.........' print'p = ',p print'q = ',q mode = (p-1)*(q-1) print'(p-1)*(q-1)= ',mode e = input("Now enter e: ") print'Finding d .........' d = inverse(e,mode) print'd = ',d ct = input("Enter the cipher text: ") print'Decyption.........' p = pow(ct, d, n) print'The plain text: ',p # IN THIS PART OF THE CODE THE PADDED DIGITS WILL BE REMOVE AND THE PLAIN TEXT WILL BE EXPOSED myp_binary = bin(p) print'The binary representation of plain text: ',myp_binary myp_padd = p % pow(2,200) print'The plain text after removing the paddings: ',myp_padd myp_padd_bin = bin(myp_padd) print'The binary representation of real plain text: ',myp_padd_bin n = int(myp_padd_bin, 2) str = binascii.unhexlify('%x' % n) print'The ASCII representation:',str

[ "hassansalam@outlook.com.com" ]

hassansalam@outlook.com.com

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d1debd994fdcf65e55d278a83ca55600b9baf13e

/Observer-machine/observer_pattern/observable.py

9c8467981cfa4dfc8607671db938d24b80529da8

[]

no_license

JackyCafe/designPettern

885497ce94ddd3f9439f572a34464ab07c93b377

98869087f35bfee102fa96e97062e95f580e8b2c

refs/heads/master

2023-06-15T19:20:04.441605

2021-07-16T05:46:11

381,317,434

0

null

UTF-8

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356

py

from typing import List class Observable: observers: List def __init__(self): self.observers = [] def addObserver(self,observer): self.observers.append(observer) def removeObserver(self,observer): self.observers.remove(observer) def notify(self): for o in self.observers: o.update(self)

[ "powerworker1234@gmail.com" ]

powerworker1234@gmail.com

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514440c0319b0b9bf1ee2a7b5fd128713c68384e

/whyattend/analysis.py

fc88ebc836e0eb0ddaa907e8fa5fe87cfd4d74f5

[ "BSD-2-Clause" ]

permissive

chipsi007/World-of-Tanks-Attendance-Tracker

3af9d68f9b4ea81b61ad35f5a20204c2b098de28

576b32586c402a843b88c49bf432a3e8cb3c62dd

refs/heads/master

2020-03-21T17:02:46.227357

2016-06-19T10:57:39

138,809,761

0

null

UTF-8

Python

false

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import math from collections import namedtuple, defaultdict from . import replays PlayerPerformance = namedtuple('PlayerPerformance', ['battle_count', 'avg_dmg', 'avg_kills', 'avg_spotted', 'survival_rate', 'avg_spot_damage', 'avg_pot_damage', 'win_rate', 'wn7', 'avg_decap', 'avg_tier']) def player_performance(battles, players): """ Player statistics from replay files of given battles and players: damage done, spots, wn7, ... """ battle_count = defaultdict(int) dmg = defaultdict(float) kills = defaultdict(int) survived = defaultdict(int) spotted = defaultdict(int) spot_damage = defaultdict(float) potential_damage = defaultdict(float) wins = defaultdict(int) decap = defaultdict(int) tier = defaultdict(int) for battle in battles: replay_data = battle.replay.unpickle() if not replay_data or not replay_data["second"]: continue replay_version_tokens = replay_data['first']['clientVersionFromExe'].split(".") if len(replay_version_tokens) == 1: # legacy format replay_version_tokens = replay_data['first']['clientVersionFromExe'].split(",") replay_major_version = int(replay_version_tokens[1]) if " " in replay_version_tokens[2]: # very strange version format ... replay_minor_version = int(replay_version_tokens[2].split()[0]) else: replay_minor_version = int(replay_version_tokens[2]) if replay_major_version > 8 or (replay_major_version == 8 and replay_minor_version >= 11): players_perf = replays.player_performance(replay_data['second'], replay_data['second'][0]['vehicles'], replay_data['second'][0]['players']) else: if not replay_data or not 'pickle' in replay_data or not replay_data['pickle']: continue if not isinstance(replay_data['pickle']['vehicles'], dict): continue players_perf = replays.player_performance(replay_data['second'], replay_data['pickle']['vehicles'], replay_data['pickle']['players']) else: if not replay_data or not 'pickle' in replay_data or not replay_data['pickle']: continue if not isinstance(replay_data['pickle']['vehicles'], dict): continue players_perf = replays.player_performance(replay_data['second'], replay_data['pickle']['vehicles'], replay_data['pickle']['players']) for player in battle.get_players(): if not player in players: continue if not str(player.wot_id) in players_perf: # Replay/Players mismatch (account sharing?), skip continue perf = players_perf[str(player.wot_id)] battle_count[player] += 1 dmg[player] += perf['damageDealt'] spot_damage[player] += perf['damageAssistedRadio'] kills[player] += perf['kills'] survived[player] += 1 if perf['survived'] else 0 potential_damage[player] += perf['potentialDamageReceived'] wins[player] += 1 if battle.victory else 0 spotted[player] += perf['spotted'] decap[player] += perf['droppedCapturePoints'] tier[player] += perf['tank_info']['tier'] avg_dmg = defaultdict(float) avg_kills = defaultdict(float) survival_rate = defaultdict(float) avg_spotted = defaultdict(float) avg_spot_damage = defaultdict(float) avg_pot_damage = defaultdict(float) win_rate = defaultdict(float) avg_decap = defaultdict(float) avg_tier = defaultdict(float) for p in players: if battle_count[p] > 0: bc = float(battle_count[p]) avg_dmg[p] = dmg[p] / bc avg_kills[p] = kills[p] / bc survival_rate[p] = survived[p] / bc avg_spotted[p] = spotted[p] / bc avg_spot_damage[p] = spot_damage[p] / bc avg_pot_damage[p] = potential_damage[p] / bc win_rate[p] = wins[p] / bc avg_decap[p] = decap[p] / bc avg_tier[p] = tier[p] / bc wn7 = defaultdict(float) for p in players: if battle_count[p] == 0: continue tier = avg_tier[p] wn7[p] = (1240.0 - 1040.0 / ((min(6, tier)) ** 0.164)) * avg_kills[p] \ + avg_dmg[p] * 530.0 / (184.0 * math.exp(0.24 * tier) + 130.0) \ + avg_spotted[p] * 125.0 * min(tier, 3) / 3.0 \ + min(avg_decap[p], 2.2) * 100.0 \ + ((185 / (0.17 + math.exp((win_rate[p] * 100.0 - 35.0) * -0.134))) - 500.0) * 0.45 \ - ((5.0 - min(tier, 5)) * 125.0) / ( 1.0 + math.exp(( tier - (battle_count[p] / 220.0) ** (3.0 / tier) ) * 1.5)) result = PlayerPerformance( battle_count=battle_count, avg_dmg=avg_dmg, avg_kills=avg_kills, avg_spotted=avg_spotted, survival_rate=survival_rate, avg_spot_damage=avg_spot_damage, avg_pot_damage=avg_pot_damage, win_rate=win_rate, avg_decap=avg_decap, avg_tier=avg_tier, wn7=wn7 ) return result

[ "daniel.diepold@gmail.com" ]

daniel.diepold@gmail.com

41d4be9a41798bf7b2188c2827bb18a60b2d64a8

9a5b3d2ef1fa5c488a0eadb3bbf89df368b82589

/hw12.py

6ca06dd8bd8b0dd4b359cb704de3ed370ba4a6cd

[]

no_license

smax253/cs115

bfb1ef82e10caaa36029cdde5451f47e0e53ef7b

9c670618b274c9c6c883779d6604374c0ba96a4c

refs/heads/master

2022-10-06T09:14:00.406567

2018-12-06T00:22:09

149,790,258

0

null

UTF-8

Python

false

4,694

py

''' Created on 11/24/18 @author: Max Shi Pledge: I pledge my honor that I have abided by the Stevens Honor Code CS115 - Hw 11 - Date class ''' DAYS_IN_MONTH = (0, 31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31) class Date(object): '''A user-defined data structure that stores and manipulates dates.''' # The constructor is always named __init__. def __init__(self, month, day, year): '''The constructor for objects of type Date.''' self.month = month self.day = day self.year = year # The 'printing' function is always named __str__. def __str__(self): '''This method returns a string representation for the object of type Date that calls it (named self). ** Note that this _can_ be called explicitly, but it more often is used implicitly via the print statement or simply by expressing self's value.''' return '%02d/%02d/%04d' % (self.month, self.day, self.year) # Here is an example of a 'method' of the Date class. def isLeapYear(self): '''Returns True if the calling object is in a leap year; False otherwise.''' if self.year % 400 == 0: return True if self.year % 100 == 0: return False if self.year % 4 == 0: return True return False def copy(self): '''Returns a new object with the same month, day, year as the calling object (self).''' dnew = Date(self.month, self.day, self.year) return dnew def equals(self, d2): ''' Decides if self and d2 represent the same calendar date, whether or not they are the in the same place in memory. ''' return self.year == d2.year and self.month == d2.month and \ self.day == d2.day def tomorrow(self): """Changes the object to represent the following day""" if self.day >= DAYS_IN_MONTH[self.month]: if self.month == 2 and self.isLeapYear() and self.day == 28: self.day += 1 elif self.month == 12: self.year += 1 self.month = 1 self.day = 1 else: self.month += 1 self.day = 1 else: self.day += 1 def yesterday(self): """Changes the object to represent the previous day""" if self.day == 1: if self.month == 3 and self.isLeapYear(): self.month -= 1 self.day = 29 elif self.month == 1: self.month = 12 self.year -= 1 self.day = DAYS_IN_MONTH[self.month] else: self.month -= 1 self.day = DAYS_IN_MONTH[self.month] else: self.day -= 1 def addNDays(self, N): """Adds N days to this object""" print(str(self)) for day in range(N): self.tomorrow() print(str(self)) def subNDays(self, N): """Subtracts N days from this object""" print(str(self)) for day in range(N): self.yesterday() print(str(self)) def isAfter(self, d2): """Returns whether this object's date is after d2""" if d2.year < self.year: return True elif d2.year == self.year: if d2.month < self.month: return True elif d2.month == self.month: if d2.day < self.day: return True return False def isBefore(self, d2): """Returns whether this object's date is before d2""" if d2.year > self.year: return True elif d2.year == self.year: if d2.month > self.month: return True elif d2.month == self.month: if d2.day > self.day: return True return False def diff(self, d2): """Returns the difference between two days, will be negative is d2 is before this object's date""" numDiff = 0 copySelf = self.copy() while copySelf.isBefore(d2): copySelf.tomorrow() numDiff -= 1 while copySelf.isAfter(d2): copySelf.yesterday() numDiff += 1 return numDiff def dow(self): """Returns the day of the week of this date""" daysOfWeek = ('Sunday','Monday','Tuesday','Wednesday','Thursday','Friday','Saturday') refSunday = Date(11,25,2018) difference = self.diff(refSunday) return daysOfWeek[difference%7]

[ "smax253@gmail.com" ]

smax253@gmail.com

992eaf158afa97f9840995f5325e13ed645e30f9

6d41b6f01dc7a635424775efbe816f8f835a4287

/programmers.co.kr/Greedy/체육복/main.py

e39a021acd0868db514fcc8a8bdab4197fbe51d7

[]

no_license

Kitsunetic/coding-test

c3a27df19f5816c79aef8823c8a7a04b5dd8114d

0fff44440883d025b1a98f727d1b28a5dbf412e6

refs/heads/master

2023-04-08T06:39:59.174049

2021-04-29T16:01:11

358,499,090

1

0

null

UTF-8

Python

false

472

py

def solution(n, lost, reserve): p = [1 for _ in range(n + 1)] for i in lost: p[i] -= 1 for i in reserve: p[i] += 1 for i in range(1, n + 1): if p[i] == 0: if i != 1 and p[i - 1] > 1: p[i] += 1 p[i - 1] -= 1 elif i != n and p[i + 1] > 1: p[i] += 1 p[i + 1] -= 1 answer = 0 for v in p[1:]: answer += min(v, 1) return answer

[ "shenhaichenhai@gmail.com" ]

shenhaichenhai@gmail.com

c055ae9b12dbbcdd5f6e7c94fd52a313b3e50979

ca58b06353c0a8c0e8a87dd2bcf0d06cf54aded8

/server/resume/about/views.py

88f253845fc5fc2a0dc8a1b42cf9faa181811ab7

[]

no_license

whistlepark/ECE-140A-Resume

ff9e8a67525d1a748c561b6af441f29993a51267

158222e91ddedddcae2fc9520a23f8f54848be5d

refs/heads/main

2023-03-18T23:12:17.005562

2021-03-14T22:25:23

347,766,551

0

null

UTF-8

Python

false

115

py

from django.shortcuts import render, HttpResponse def about(request): return render(request,'about.html',{})

[ "arhanna@ucsd.edu" ]

arhanna@ucsd.edu

c3a9591fd2ff4faec0717a1618d14ca7352353d0

5764b4996e64de37b762d738cd4b5d882294559c

/back_for_face/migrations/0003_auto_20210402_0419.py

f2fecf1a210b681c91cca45fd3d5618478ff6fe3

[]

no_license

Akkutabusova/BackenForFace

447c1bbbb79f9f5001401ef19223c1d58db91dab

a296b9bd189df56e60b75a2b08b5420c13889fe9

refs/heads/master

2023-04-23T06:08:00.082070

2021-05-08T15:23:14

359,457,504

0

null

UTF-8

Python

false

521

py

# Generated by Django 2.2.7 on 2021-04-01 22:19 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('back_for_face', '0002_auto_20210402_0412'), ] operations = [ migrations.RemoveField( model_name='currentuser', name='qr', ), migrations.AddField( model_name='currentuser', name='door_id', field=models.IntegerField(null=True), ), ]

[ "tabusova.a2000@gmail.com" ]

tabusova.a2000@gmail.com

215f7d24162ef80e6174c706bfbe4ecdf7c0d938

c4058241ee3fd2d34e06dc90f83b39b1725a9fa1

/Tienda/celery.py

a16651412f72caf624942b487559ed2e0aaa672e

[]

no_license

aberlanga25/DjangoTienda

ef09ed5c5c3b2c64075318ca102b368b4a3b4bbc

8fcf23d1ac1347ad92e8adc1bc5b2a69e7ecf8f6

refs/heads/master

2020-03-20T06:50:21.317419

2018-06-22T21:45:58

137,262,462

0

null

UTF-8

Python

false

331

py

import os from celery import Celery from django.conf import settings # set the default Django settings module for the 'celery' program. os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'Tienda.settings') app = Celery('tienda') app.config_from_object('django.conf:settings') app.autodiscover_tasks(lambda: settings.INSTALLED_APPS)

[ "berlanga2512@gmail.com" ]

berlanga2512@gmail.com