anton-l/python_sample_10k · Datasets at Hugging Face

szollosova/webstrom

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7a86ebce0cc05d831421c0af1bac7a7ed47cb528

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/user/forms.py

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[]

no_license

https://github.com/szollosova/webstrom

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refs/heads/master

2022-07-16T15:16:51.556206

2020-05-17T07:36:32

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2020-05-11T15:52:32

2020-05-11T15:52:31

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from django import forms from django.contrib.auth.password_validation import validate_password from competition.models import Grade from user.models import County, District, Profile, User class UserCreationForm(forms.ModelForm): class Meta: model = User fields = ('email',) password1 = forms.CharField(label='Heslo', widget=forms.PasswordInput) password2 = forms.CharField( label='Potvrdenie hesla', widget=forms.PasswordInput) def clean_password1(self): password1 = self.cleaned_data['password1'] validate_password(password1) return password1 def clean_password2(self): password1 = self.cleaned_data.get('password1') password2 = self.cleaned_data.get('password2') if password1 and password2 and password1 != password2: raise forms.ValidationError('Heslá sa nezhodujú') return password2 def save(self, commit=True): user = super(UserCreationForm, self).save(commit=False) user.set_password(self.cleaned_data['password1']) if commit: user.save() return user class ProfileCreationForm(forms.ModelForm): class Meta: model = Profile fields = ['first_name', 'last_name', 'nickname', 'school_not', 'county', 'district', 'school', 'school_name', 'school_not_found', 'school_info', 'grade', 'phone', 'parent_phone', 'gdpr', ] grade = forms.ModelChoiceField( queryset=Grade.objects.filter(is_active=True), label='Ročník', help_text='V prípade, že je leto, zadaj ročník, ' 'ktorý končíš (školský rok začína septembrom).') school_not = forms.BooleanField( required=False, label='Už nie som študent základnej ani strednej školy.') school_name = forms.CharField( required=False, label='Škola*') school_not_found = forms.BooleanField( required=False, label='Moja škola sa v zozname nenachádza.') school_info = forms.CharField( required=False, widget=forms.Textarea, label='povedz nám, kam chodíš na školu, aby sme ti ju mohli dodatočne pridať') county = forms.ModelChoiceField( required=False, queryset=County.objects, label='Kraj školy') district = forms.ModelChoiceField( required=False, queryset=District.objects, label='Okres školy') def __init__(self, *args, **kwargs): super(ProfileCreationForm, self).__init__(*args, **kwargs) self.fields['county'].queryset = County.objects.all_except_unspecified() self.fields['school'].widget = forms.HiddenInput() def clean_gdpr(self): gdpr = self.cleaned_data['gdpr'] if not gdpr: raise forms.ValidationError( 'Súhlas so spracovaním osobných údajov je nutnou podmienkou registrácie') return gdpr def save(self, commit=True): profile = super(ProfileCreationForm, self).save(commit=False) profile.year_of_graduation = \ self.cleaned_data['grade'].get_year_of_graduation_by_date() if commit: profile.save() return profile

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forms.py

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MatthewBenjamin/fsnd-blog

858,993,489,370

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/models.py

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[]

no_license

https://github.com/MatthewBenjamin/fsnd-blog

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8ab0b4ed159f8ca96c6a8c82415b2e339d0ae936

refs/heads/master

2020-04-06T06:58:10.158739

2016-09-08T19:09:44

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# models.py - appengine datastore models from google.appengine.ext import ndb from string import letters import hashlib import random def make_salt(length=5): return ''.join(random.choice(letters) for x in xrange(length)) def make_pw_hash(name, pw, salt=None): if not salt: salt = make_salt() h = hashlib.sha256(name + pw + salt).hexdigest() return '%s,%s' % (salt, h) def valid_pw(name, password, h): salt = h.split(',')[0] return h == make_pw_hash(name, password, salt) class User(ndb.Model): username = ndb.StringProperty(required=True) pw_hash = ndb.StringProperty(required=True) email = ndb.StringProperty() liked_posts = ndb.KeyProperty(repeated=True) liked_comments = ndb.KeyProperty(repeated=True) @classmethod def register_user(cls, username, password, email): pw_hash = make_pw_hash(username, password) return User(username=username, pw_hash=pw_hash, email=email) @classmethod def user_by_name(cls, name): user = User.query(User.username == name).get() return user @classmethod def login(cls, name, password): user = cls.user_by_name(name) if user and valid_pw(name, password, user.pw_hash): return user class Post(ndb.Model): """Blog post""" subject = ndb.StringProperty(required=True) content = ndb.TextProperty(required=True) created = ndb.DateTimeProperty(auto_now_add=True) modified = ndb.DateTimeProperty(auto_now=True) likes = ndb.IntegerProperty(default=0, required=True) # TODO: tags = repeated string property @property def serialize(self): """Return object data in an easily serializable format.""" return { 'subject': self.subject, 'content': self.content, 'created:': str(self.created), 'modified': str(self.modified), 'likes': self.likes } class Comment(ndb.Model): content = ndb.TextProperty(required=True) author = ndb.StringProperty(required=True) likes = ndb.IntegerProperty(default=0)

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Python

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NGG-kang/PythonPractice

1,425,929,183,258

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/For.py

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[]

no_license

https://github.com/NGG-kang/PythonPractice

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refs/heads/main

2023-03-02T11:35:41.989193

2021-01-29T23:29:32

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# for문 for 변수 in 리스트(또는 튜플, 문자열): # 리스트 넣을 시 변수에는 리스트의 요소가 들어간다 for i in range(5): # 5까지 for i in range(1,5): # 1부터 5까지 for i in range(5,0, -1): # 5부터 0까지 -1씩 까짐 # 리스트 내 포 사용하기 # 이건 좀 기니까 예시로 대체 numbers = [1, 2, 3, 4, 5] result = [] for n in numbers: if n % 2 == 1: result.append(n*2) # for문을 result = [n*2 for n in numbers if n%2 == 1] # 로 대체한다

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uwcirg/true_nth_usa_portal

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/tests/test_next_step.py

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refs/heads/master

2021-04-03T01:12:01.841170

2021-04-02T02:09:18

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from flask_webtest import SessionScope import pytest from werkzeug.exceptions import BadRequest from portal.database import db from portal.models.intervention import Intervention from portal.models.next_step import NextStep from tests import TestCase def test_validate(): assert NextStep.validate('decision_support') def test_invalid(): with pytest.raises(BadRequest): NextStep.validate('bogus') class TestNextStep(TestCase): def test_decision_support(self): # w/o strategy setup, will get back indeterminate ds match test_link = 'http://test.me' ds_p3p = Intervention.query.filter_by( name='decision_support_p3p').one() ds_wc = Intervention.query.filter_by( name='decision_support_wisercare').one() for ds in ds_p3p, ds_wc: ds.link_url = test_link with SessionScope(db): db.session.commit() assert test_link == NextStep.decision_support(self.test_user)

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test_next_step.py

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ngotest/ebmr_proj

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/music_player/playlist/urls.py

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[]

no_license

https://github.com/ngotest/ebmr_proj

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refs/heads/master

2023-03-01T02:19:25.297879

2021-02-04T05:28:53

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from django.contrib import admin from django.urls import path,include from . import views app_name='playlist' urlpatterns = [ path('',views.general,name='general'), path('<int:type>/',views.emotion,name='emotion'), path('songupload/<int:type>/',views.song_upload,name='songupload'), path('up-song/',views.up_song,name='song'), path('fav/<int:id>',views.fav,name="fav"), path('delete/<int:type>/<int:id>/',views.delete,name='delete'), path('playsong/<int:sid>/',views.playsong,name='playsong'), ]

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annijanora/meiginajums1102-1

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fffb3bff816bc34358c29d82fd27bc32711000aa

/main.py

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[]

no_license

https://github.com/annijanora/meiginajums1102-1

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refs/heads/master

2023-05-11T10:48:34.463438

2020-02-18T20:17:27

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2023-05-02T22:47:00

2020-02-18T20:19:43

2020-02-18T20:19:51

2023-05-02T22:47:00

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from flask import Flask, render_template, request app = Flask(__name__) @app.route('/') def home(): return render_template('sakums.html') @app.route('/viens') def viens(): return render_template('viens.html') @app.route('/divi') def divi(): return render_template('divi.html') @app.route('/tris') def tris(): return render_template('tris.html') @app.route('/sakums') def sakums(): return render_template('sakums.html') app.run(host='0.0.0.0',port=8020)

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main.py

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victorsemenov1980/WordCound_RabbitMQ_SQLalchemyORM

9,869,834,890,713

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36420c31e002b47faaa344afaac580c583e7b0b5

/producer.py

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permissive

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refs/heads/main

2023-05-04T13:47:53.879247

2021-05-28T06:56:40

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#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Thu May 20 19:32:19 2021 @author: Viktor Semenov """ from os import listdir from os.path import isfile, join import mimetypes from datetime import datetime import pika params=pika.URLParameters('amqps://____your link here') #txt_dir = ('TXTfiles') def publish_good(file_name): connection = pika.BlockingConnection(params) channel = connection.channel() channel.queue_declare(queue='new_files') # Declare a queue message = file_name channel.basic_publish(exchange='', routing_key='new_files', body=message) print(" [x] Sent %r" % message) connection.close() def publish_bad(file_name): connection = pika.BlockingConnection(params) channel = connection.channel() channel.queue_declare(queue='errors') # Declare a queue message = file_name channel.basic_publish(exchange='', routing_key='errors', body=message) print(" [x] Sent %r" % message) connection.close() def file_check(dir_): file_list=[] with open('filelist.txt','r+') as file: for line in file: file_list.append(line.rstrip('\n')) file.write(str(datetime.now())) file.write('\n') onlyfiles = [f for f in listdir(dir_) if isfile(join(dir_, f))] for i in onlyfiles: if i not in file_list: file_type=mimetypes.guess_type(i) if file_type[0] != 'text/plain': print('ALERT',' filename: ', i) publish_bad(i) else: print(i,'-->',file_type[0]) publish_good(i) with open('filelist.txt','a') as file: file.write(i) file.write('\n') else: print('Found already processed file ',i)

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Python

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producer.py

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nishizumi-lab/sample

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/python/opencv/basic/ex10.py

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no_license

https://github.com/nishizumi-lab/sample

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refs/heads/master

2023-08-22T15:52:04.998574

2023-08-20T04:09:08

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2023-02-02T09:03:50

2020-03-18T12:14:34

2023-01-18T21:29:33

2023-02-02T09:03:45

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#-*- coding:utf-8 -*- import cv2 import numpy as np width = 200 height = 100 img = np.zeros((height, width, 3), np.uint8) # 画像の書き込み cv2.imwrite("/Users/github/sample/python/opencv/basic/ex10.png", img)

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Chris35Wills/python_functions

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/dem_point_operations.py

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[]

no_license

https://github.com/Chris35Wills/python_functions

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refs/heads/master

2020-04-16T02:11:09.535516

2017-07-19T15:40:53

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import sys import numpy as np import pandas as pd sys.path.append('./georaster') import georaster """ DEM and point operations """ def extract_values(dem, points, extracted_col_header='extracted_z'): """ Extracts points from a dem at point locations - binds them to a pandas dataframe Variables: dem : a georaster object points : a pandas dataframe with headers of "x" and "y" Returns: points (pandas dataframe) """ dem_tl_x=dem.extent[0] *-1 #-800000 #*-1 << must do this dem_tl_y=dem.extent[3] #-599500. post=dem.xres pnt_x=points['x'].values pnt_y=points['y'].values ix=np.floor((pnt_x+dem_tl_x)/post) # origin is top left iy=np.floor(((dem_tl_y)-pnt_y)/post) # origin is top left dem_values=dem.r[list(iy),list(ix)] points[extracted_col_header]=pd.Series(dem_values, index=points.index) return points

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amandasystems/msc-polonius-fact-study

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/benchmark-solving.py

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[]

no_license

https://github.com/amandasystems/msc-polonius-fact-study

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refs/heads/master

2022-02-12T17:03:37.219351

2019-09-10T15:16:30

null

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#!/usr/bin/env python3 # benchmark a release version of Polonius on a number of directories containing # nll-facts. # benchmark-solving <my-crate> <my-other-crate> import csv import os import sys import timeit from pathlib import Path from benchmark import inputs_or_workdir, run_command POLONIUS_OPTIONS = ["--skip-timing"] POLONIUS_PATH = "../polonius/target/release/polonius" POLONIUS_COMMAND = [POLONIUS_PATH, *POLONIUS_OPTIONS] NR_REPEATS = 2 HARD_TIMEOUT = "10m" SOFT_TIMEOUT = "5m" ALGORITHMS = ["Naive", "Hybrid", "DatafrogOpt"] def run_with_timeout(command): return run_command( ["timeout", f"--kill-after={HARD_TIMEOUT}", SOFT_TIMEOUT, *command]) def benchmark_crate_fn(p, algorithm): """ Perform benchmarks on a function's input data, located in p """ benchmark_timer = timeit.Timer( lambda: run_with_timeout([*POLONIUS_COMMAND, "-a", algorithm, "--", str(p)])) try: return min(benchmark_timer.repeat(NR_REPEATS, number=1)) except RuntimeError: return None def benchmark_crate_fns(facts_path): return ([p.stem, *[benchmark_crate_fn(p, a) for a in ALGORITHMS]] for p in facts_path.iterdir() if p.is_dir() and not p.stem[0] == ".") def benchmark_crate_folder(p): assert isinstance(p, Path) assert p.is_dir(), f"{p} must be a directory!" facts_path = p / "nll-facts" if not facts_path.is_dir(): facts_path = p program_name = p.stem for fn_name_and_runtimes in benchmark_crate_fns(facts_path): yield [program_name, *fn_name_and_runtimes] def benchmark_crates_to_csv(dirs, out_fp): writer = csv.writer(out_fp) writer.writerow([ "program", "function", *[f"min({NR_REPEATS}) {a} runtime" for a in ALGORITHMS] ]) for crate_count, c in enumerate(dirs, start=1): print( f"processing crate #{crate_count}/{len(dirs)}: {c.stem}"\ .ljust(os.get_terminal_size(0).columns), file=sys.stderr, end="\r") writer.writerows(benchmark_crate_folder(c)) if __name__ == '__main__': crate_fact_list = inputs_or_workdir() benchmark_crates_to_csv(crate_fact_list, sys.stdout)

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JohnWestonNull/RaspberryPiWithScreen

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/screen_off.py

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[]

no_license

https://github.com/JohnWestonNull/RaspberryPiWithScreen

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refs/heads/master

2020-12-13T00:33:13.134745

2020-01-16T08:33:53

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from App import App class ScreenOff(App): def __init__(self): super().__init__(name="Screen Off") def render(self): self.draw.rectangle(((0, 0),(127, 63)), fill=1) if self.driver is not None: self.driver.refresh()

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yashpupneja/Coding-Problems

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/Leetcode Problems/02. Number of consecutive ones.py

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[]

no_license

https://github.com/yashpupneja/Coding-Problems

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refs/heads/master

2023-02-10T15:48:23.098878

2021-01-06T18:41:07

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# -*- coding: utf-8 -*- """ Given a binary array, find the maximum number of consecutive 1s in this array. Example 1: Input: [1,1,0,1,1,1] Output: 3 Explanation: The first two digits or the last three digits are consecutive 1s. The maximum number of consecutive 1s is 3. Note: The input array will only contain 0 and 1. The length of input array is a positive integer and will not exceed 10,000 """ def findMaxConsecutiveOnes(nums): count=0 res=0 for i in range(len(nums)): if nums[i]==0: count=0 else: count=count+1 res=max(res,count) return res def main(): num=list(map(int,input().split())) print(findMaxConsecutiveOnes(num)) if __name__=='__main__': main()

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srikanth3006/Python

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/DataStructures/Graphs/DFS_in_Graphs.py

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[]

no_license

https://github.com/srikanth3006/Python

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refs/heads/master

2020-06-19T14:08:19.393909

2019-07-28T18:47:12

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2

null

class Node(object): def __init__(self, name): self.name = name self.adjacencyList = list() self.visited = None class DepthFirstSearch(object): def dfs(self, starting_node): print("%s" % starting_node.name) starting_node.visited = True for node in starting_node.adjacencyList: if not node.visited: self.dfs(node) def dfs_using_Stack(self, starting_node): stack = list() stack.append(starting_node) while stack: node = stack.pop() print("%s" % node.name) for n in node.adjacencyList: if not n.visited: n.visited = True stack.append(n) node1 = Node('A') node2 = Node('B') node3 = Node('C') node4 = Node('D') node5 = Node('E') node1.adjacencyList.append(node2) node1.adjacencyList.append(node3) node2.adjacencyList.append(node4) node4.adjacencyList.append(node5) dfs = DepthFirstSearch() dfs.dfs(node1)

UTF-8

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1,009

py

47

DFS_in_Graphs.py

46

0.583746

0.569871

0

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24.25

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gubjanos/gravity-test

16,870,631,549,254

035ac55494613480ca7fb5a95063195ef28ee84b

6fef56670700919113f15505c25cd1d95df187d6

/load_data.py

d15459998a52b0b164e36554ad3f01e74fc9ac7e

[]

no_license

https://github.com/gubjanos/gravity-test

5caab9c955343f5c734491ae90f14958f69b27fd

2dedf62056704614c7e8506d0b3f882b36f5f8a9

refs/heads/master

2016-09-08T00:41:13.718894

2014-06-22T12:06:18

null

0

null

def load_data(path): from numpy import loadtxt instances = loadtxt(path) y = [] x = [] for j in xrange(len(instances)): y.append(instances[j][0]) x.append(instances[j][1:]) return x, y

UTF-8

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225

py

5

load_data.py

5

0.564444

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0

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36

oumkale/test-python

3,736,621,597,087

9f9b206c84972a23f62ef73d92914756cf6257fc

9a52dd6961c033d06174921de2955be5f9035f03

/pkg/types/types.py

50a1b48fb83f0db26b6149b81a9f8d8c3b03fd79

[ "Apache-2.0" ]

permissive

https://github.com/oumkale/test-python

f4ef58e3751b1ef1626e77c7c02833e4b1b9d237

1f3d3e42ffbe1bf5ed9df8a0c6038e50129b2c4d

refs/heads/main

2023-08-13T01:30:40.624522

2021-10-12T06:14:08

416,193,482

1

0

null

# PreChaosCheck initial stage of experiment check for health before chaos injection PreChaosCheck = "PreChaosCheck" # PostChaosCheck pre-final stage of experiment check for health after chaos injection PostChaosCheck = "PostChaosCheck" # Summary final stage of experiment update the verdict Summary = "Summary" # ChaosInject this stage refer to the main chaos injection ChaosInject = "ChaosInject" # AwaitedVerdict marked the start of test AwaitedVerdict = "Awaited" # PassVerdict marked the verdict as passed in the end of experiment PassVerdict = "Pass" # FailVerdict marked the verdict as failed in the end of experiment FailVerdict = "Fail" # StoppedVerdict marked the verdict as stopped in the end of experiment StoppedVerdict = "Stopped" #ResultDetails is for collecting all the chaos-result-related details class ResultDetails(object): def __init__(self, Name=None, Verdict=None, FailStep=None, Phase=None, PassedProbeCount=None, UID=None): self.Name = Name self.Verdict = Verdict self.FailStep = FailStep self.Phase = Phase self.ResultUID = UID self.PassedProbeCount = PassedProbeCount # EventDetails is for collecting all the events-related details class EventDetails(object): def __init__(self, Message=None, Reason=None, ResourceName=None, ResourceUID=None, Type=None, UID=None): self.Message = Message self.Reason = Reason self.ResourceName = ResourceName self.ResourceUID = UID self.Type = Type # AppDetails contains all the application related envs class AppDetails(object): def __init__(self, Namespace=None, Label=None, Kind=None, AnnotationCheck=None, AnnotationKey=None, AnnotationValue=None): self.Namespace = Namespace self.Label = Label self.Kind = Kind self.AnnotationCheck = AnnotationCheck self.AnnotationKey = AnnotationKey self.AnnotationValue = AnnotationValue # ChaosDetails is for collecting all the global variables class ChaosDetails(object): def __init__(self, ChaosPodName=None, ChaosNamespace=None, EngineName=None, InstanceID=None, ExperimentName=None, Timeout=None, Delay=None, ChaosDuration=None, JobCleanupPolicy=None, Randomness=None, ParentsResources=None, Namespace=None, Label=None, Kind=None, AnnotationCheck=None, AnnotationKey=None, AnnotationValue=None, UID=None ): self.ChaosUID = UID self.ChaosNamespace = ChaosNamespace self.ChaosPodName = ChaosPodName self.EngineName = EngineName self.InstanceID = InstanceID self.ExperimentName = ExperimentName self.Timeout = Timeout self.Delay = Delay self.AppDetail = AppDetails(Namespace, Label, Kind, AnnotationCheck, AnnotationKey, AnnotationValue) self.ChaosDuration = ChaosDuration self.JobCleanupPolicy = JobCleanupPolicy self.Randomness = Randomness self.ParentsResources = [] def append(self, value): self.ParentsResources.append(value) #SetResultAttributes initialise all the chaos result ENV def SetResultAttributes(ResultDetails , ChaosDetails): ResultDetails.Verdict = "Awaited" ResultDetails.Phase = "Running" ResultDetails.FailStep = "N/A" ResultDetails.PassedProbeCount = 0 if ChaosDetails.EngineName != "": ResultDetails.Name = ChaosDetails.EngineName + "-" + ChaosDetails.ExperimentName else: ResultDetails.Name = ChaosDetails.ExperimentName if ChaosDetails.InstanceID != "": ResultDetails.Name = ResultDetails.Name + "-" + ChaosDetails.InstanceID #SetResultAfterCompletion set all the chaos result ENV in the EOT def SetResultAfterCompletion(ResultDetails, verdict, phase, failStep): ResultDetails.Verdict = verdict ResultDetails.Phase = phase ResultDetails.FailStep = failStep #SetEngineEventAttributes initialise attributes for event generation in chaos engine def SetEngineEventAttributes(EventDetails, Reason, Message, Type , ChaosDetails): EventDetails.Reason = Reason EventDetails.Message = Message EventDetails.ResourceName = ChaosDetails.EngineName EventDetails.ResourceUID = ChaosDetails.ChaosUID EventDetails.Type = Type #SetResultEventAttributes initialise attributes for event generation in chaos result def SetResultEventAttributes(EventDetails, Reason, Message, Type, ResultDetails): EventDetails.Reason = Reason EventDetails.Message = Message EventDetails.ResourceName = ResultDetails.Name EventDetails.ResourceUID = ResultDetails.ResultUID EventDetails.Type = Type

UTF-8

Python

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py

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types.py

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0.756524

0.756303

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42.057143

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cryzed/Feedbuffer

7,258,494,758,895

f339bcfba12855a9ce9c276f0cfec355b8a1db43

63f50c6742d1cdcc1b64a69828b3acbf493f2ce1

/feedbuffer/database.py

f9a6f31c3d029e4cf431a0b19c481311db1f1006

[ "MIT" ]

permissive

https://github.com/cryzed/Feedbuffer

bc3faedae83d6c7ffe65e70e8ffdc81c5f87aedf

0f258bbc7fbcdb39e19fd7d26192a45098b1fc68

refs/heads/master

2021-01-15T15:25:39.979230

2016-07-02T19:12:38

52,744,909

20

1

null

import concurrent.futures import functools import peewee from feedbuffer import settings, log _database = peewee.SqliteDatabase(settings.DATABASE_PATH) _logger = log.get_logger(__name__) # Easy way to queue function calls and execute them in a single thread, without having to manually write # producer-consumer logic. _database_executor = concurrent.futures.ThreadPoolExecutor(max_workers=1) class Model(peewee.Model): class Meta: database = _database class Feed(Model): url = peewee.TextField(unique=True) update_interval = peewee.IntegerField(default=settings.DEFAULT_UPDATE_INTERVAL) data = peewee.TextField() class FeedItem(Model): id_ = peewee.TextField(unique=True) data = peewee.TextField() feed = peewee.ForeignKeyField(Feed, related_name='entries') _database.create_tables([Feed, FeedItem], safe=True) def _execute_in(executor): def decorator(function): @functools.wraps(function) def wrapper(*args, **kwargs): future = executor.submit(function, *args, **kwargs) return future.result() return wrapper return decorator def _get_feed_query(url): return Feed.select().where(Feed.url == url) def _feed_item_exists(feed, id_): return FeedItem.select().where(FeedItem.feed == feed and FeedItem.id_ == id_).exists() def _feed_exists(url): return _get_feed_query(url).exists() def _get_feed(url): return _get_feed_query(url).get() @_execute_in(_database_executor) def feed_exists(url): return _get_feed_query(url).exists() @_execute_in(_database_executor) def get_feed(url): return _get_feed(url) @_execute_in(_database_executor) def update_feed(url, feed_data, entries): if _feed_exists(url): feed = _get_feed(url) else: feed = Feed(url=url, data=feed_data) feed.save() data_source = [ {'id_': id_, 'data': entry, 'feed': feed} for (id_, entry) in entries if not _feed_item_exists(feed, id_) ] _logger.info('Updating feed: %s with %d new entries...', url, len(data_source)) with _database.atomic(): FeedItem.insert_many(data_source).execute() feed.data = feed_data feed.save() @_execute_in(_database_executor) def flush_feed(feed): query = FeedItem.delete().where(FeedItem.feed == feed) query.execute() # Generic way to update data in a model instance using the write executor @_execute_in(_database_executor) def update_model_data(model, **kwargs): for key, value in kwargs.items(): setattr(model, key, value) model.save()

UTF-8

Python

false

2,585

py

8

database.py

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0.670793

0.670406

0

106

23.386792

113

rqdzs/EasyTutoring

10,471,130,278,814

a6979b894b8e41f6c32fcf062d884e4d53c3eceb

feab6c3e0dc419d1a22e01c8cdab1d6ae2dc4a44

/turmas/migrations/0004_turma_disciplina.py

46eeeffd1ca5886d3c0808a985a26d2194164827

[]

no_license

https://github.com/rqdzs/EasyTutoring

3c35b6547c22f86ec03d955f057daeee1e146d26

53fcec8e17bb950049ad3379ee63658c23aa3f38

refs/heads/master

2021-08-16T16:42:34.532149

2017-11-20T02:55:32

null

0

null

# -*- coding: utf-8 -*- # Generated by Django 1.11.5 on 2017-10-26 13:07 from __future__ import unicode_literals from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('disciplinas', '0001_initial'), ('turmas', '0003_remove_turma_disciplina'), ] operations = [ migrations.AddField( model_name='turma', name='disciplina', field=models.ForeignKey(null=True, on_delete=django.db.models.deletion.CASCADE, related_name='disciplinas', to='disciplinas.Disciplina'), ), ]

UTF-8

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629

py

98

0004_turma_disciplina.py

69

0.6407

0.600954

0

22

27.590909

149

heimagithub/par

6,691,559,075,498

88b4def2f8e22ac8d58cb5493169a13ec8e06aab

0da45639cca5b4631ef8f167cb457eee0da29cab

/180227_6_sqlite_del.py

a9dfb2ea6e08c29e25facb46f5440f9e67da8e3a

[]

no_license

https://github.com/heimagithub/par

9450af8f7ce87cf13bd58608a6e81813e95b359c

9e5efc1904ec32f337e3f1ae7fe9ea7330fe4f39

refs/heads/master

2021-01-25T14:33:11.459379

2018-03-03T03:04:31

123,708,172

0

null

import os import sqlite3 dbpath = '/home/heima/Databases/NewDB.db' conn = sqlite3.connect(dbpath) c = conn.cursor() c.execute('DELETE from LAND where ID = 4838674') conn.commit() conn.close()

UTF-8

Python

false

196

py

25

180227_6_sqlite_del.py

23

0.72449

0.678571

0

13

14.153846

48

gratcliff/Happy_Cup_Server

18,966,575,604,375

9b310b5e888872484e4a4c596f52b738c63d9516

d050ed3ce3742a3de82606d8eb5a20ffe5173e0b

/apps/products/migrations/0001_initial.py

fafcf726f5d7bcaa1a9fe05386e5753a3a67e2da

[]

no_license

https://github.com/gratcliff/Happy_Cup_Server

59f5871cd47516c9f7f73b3d4c649aacdebc29b6

bd93c58e0015f55142fad14b7fba25abc639c626

refs/heads/master

2021-01-11T02:38:45.701336

2016-12-02T02:43:18

70,946,723

0

null

# -*- coding: utf-8 -*- # Generated by Django 1.10.2 on 2016-11-03 17:51 from __future__ import unicode_literals from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ ('product_options', '0001_initial'), ] operations = [ migrations.CreateModel( name='Coffee', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('created_at', models.DateTimeField(auto_now=True)), ('updated_at', models.DateTimeField(auto_now_add=True)), ('name', models.CharField(max_length=24)), ('description', models.TextField()), ('image_url', models.URLField()), ('price_factor', models.SmallIntegerField(default=0, verbose_name='Increase or decrease the base price by the following percentage. Use negative values to decrease price.')), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='Merchandise', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('created_at', models.DateTimeField(auto_now=True)), ('updated_at', models.DateTimeField(auto_now_add=True)), ('name', models.CharField(max_length=24)), ('description', models.TextField()), ('image_url', models.URLField()), ('price', models.DecimalField(decimal_places=2, max_digits=5)), ], options={ 'verbose_name_plural': 'Merchandise', }, ), migrations.CreateModel( name='ProductPromotion', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('created_at', models.DateTimeField(auto_now=True)), ('updated_at', models.DateTimeField(auto_now_add=True)), ('description', models.CharField(max_length=64)), ('discount', models.PositiveSmallIntegerField(default=15, help_text='Positive, whole numbers only', verbose_name='Percent discount')), ('expiration_date', models.DateTimeField(help_text='Server timezone is UTC (Coordinated Universal Time)', verbose_name='Date and time that promotion ends')), ('expired', models.BooleanField(default=False)), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='Subscription', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('created_at', models.DateTimeField(auto_now=True)), ('updated_at', models.DateTimeField(auto_now_add=True)), ('frequency', models.PositiveSmallIntegerField(verbose_name='Number of weeks between each shipment')), ('price', models.DecimalField(decimal_places=2, max_digits=5)), ('coffees', models.ManyToManyField(to='products.Coffee')), ], options={ 'abstract': False, }, ), migrations.CreateModel( name='VarietyPack', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('created_at', models.DateTimeField(auto_now=True)), ('updated_at', models.DateTimeField(auto_now_add=True)), ('name', models.CharField(max_length=24)), ('description', models.TextField()), ('image_url', models.URLField()), ('coffee_qty', models.PositiveSmallIntegerField(default=0, verbose_name='Number of bags of coffee in variety pack (if applicable)')), ('price', models.DecimalField(decimal_places=2, max_digits=5)), ('coffees', models.ManyToManyField(blank=True, to='products.Coffee', verbose_name='Coffees in variety pack (if applicable)')), ('featured', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to='products.ProductPromotion', verbose_name='To feature this product, select a promotional deal.')), ('merchandise', models.ManyToManyField(blank=True, to='products.Merchandise', verbose_name='Merchandise in variety pack (if applicable)')), ], options={ 'abstract': False, }, ), migrations.AddField( model_name='merchandise', name='featured', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to='products.ProductPromotion', verbose_name='To feature this product, select a promotional deal.'), ), migrations.AddField( model_name='merchandise', name='sizes', field=models.ManyToManyField(blank=True, to='product_options.ShirtSize', verbose_name='Shirt Sizes available (if applicable)'), ), migrations.AddField( model_name='coffee', name='featured', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to='products.ProductPromotion', verbose_name='To feature this product, select a promotional deal.'), ), migrations.AddField( model_name='coffee', name='grinds', field=models.ManyToManyField(to='product_options.CoffeeGrind'), ), migrations.AddField( model_name='coffee', name='roast', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='product_options.CoffeeRoast'), ), migrations.AddField( model_name='coffee', name='sizes', field=models.ManyToManyField(to='product_options.CoffeeVolume'), ), ]

UTF-8

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false

6,235

py

126

0001_initial.py

103

0.578348

0.572093

0

126

48.484127

217

Al3x-BB/Unidad3-Ejercicio1

2,860,448,257,172

74b2582d064907147b8bd3965e1d369de5139c46

533d68e3993c246b159abd50eae7be1e1e5e43be

/ManejaLibros.py

1e8bfff49f4d36966fecb3db9b114fedea8fa7bc

[]

no_license

https://github.com/Al3x-BB/Unidad3-Ejercicio1

0aad51a2bee955154b2a874759afb6a96639568f

eef9d10a09b1e149c9fb4e04d47987b11ec27cfc

refs/heads/main

2023-05-03T00:38:21.373599

2021-05-24T14:35:51

370,382,547

0

null

from Libro import claseLibro import re import csv class claseManejaLibros: __lista = [] def __init__(self, lista = []): self.__lista = lista def crearLista(self): band = False archi = open('ArchivoLibros.csv') reader = csv.reader(archi, delimiter = ';') for fila in reader: if(band == False): fila[0] = fila[0][3:] if(re.match('^[0-9]', fila[0].lower())): unLibro =claseLibro(fila[0], fila[1], fila[2], fila[3], fila[4], fila[5]) unLibro.crearListaCap(reader) self.__lista.append(unLibro) band = True else: if(re.match('^[0-9]', fila[0].lower())): unLibro = claseLibro(fila[0], fila[1], fila[2], fila[3], fila[4], fila[5]) unLibro.crearListaCap(reader) self.__lista.append(unLibro) def punto1(self, id): acum = 0 i = 0 #buscar el libro en la lista while(i<len(self.__lista)): if (id == self.__lista[i].getId()): break i+=1 #tarea print('|----{}----|'.format(self.__lista[i].getTitulo())) for x in range(len(self.__lista[i].getCaps())): print('-> {}'.format(self.__lista[i].getCaps()[x].getTitulo())) acum += int(self.__lista[i].getCaps()[x].getPags()) print('Contiene {} páginas'.format(acum)) def punto2(self, palabra): band = [False, False] for i in range(len(self.__lista)): #busca la palabra en el libro band[0] = False for j in range(len(self.__lista[i].getCaps())): #busca la palabra en los capítulos if(palabra in self.__lista[i].getTitulo() and band[0] == False): print('|----{}----|\nAutor: {}'.format(self.__lista[i].getTitulo(), self.__lista[i].getAutor())) band = [True, True] #detecta que la palabra se econtró y que se econtró en el título if(palabra in self.__lista[i].getCaps()[j].getTitulo()): print('|----{}----|\nAutor: {}'.format(self.__lista[i].getCaps()[j].getTitulo(), self.__lista[i].getAutor())) band[1] = True #detecta que la palabra se econtró if(band[1] == False): print('ERROR: palabra no encontrada') def mostrar(self): for i in range(len(self.__lista)): self.__lista[i].mostrar()

UTF-8

Python

false

2,623

py

6

ManejaLibros.py

5

0.479557

0.468093

0

55

45.618182

116

KarthikMAM/AVSR

19,533,511,265,860

d08645eba043a023eae15863c9dcd079ac09068a

56682fb5b73a2b4c22fb8c3ea75d05a919d998ad

/align_file_indexer.py

9575d7436718ed49dd0fdd4fa2c6901cf72de5af

[]

no_license

https://github.com/KarthikMAM/AVSR

7aeefb80a197aa189846846f6a5cf8fe8cd93033

2ad53ef3dc7a32104a28827cc4faa6128ba0f095

refs/heads/master

2023-07-09T22:36:49.891147

2023-06-30T21:02:28

87,597,032

0

null

import os from os import path, listdir, makedirs import numpy as np from config import ALIGN_RAW, ALIGN_TEXT, ALIGN_INDEXED def map_letters(letters): return np.array(list(map( lambda x: 0 if x == " " else ord(x) - ord("a") + 1, list(letters) ))) print("\n\n", "INDEXING ALIGN FILES:START".center(100, "-"), sep="", end="\n\n\n") for speaker in listdir(ALIGN_RAW): for align_file in listdir(path.join(ALIGN_RAW, speaker)): if align_file.endswith(".align"): with open(path.join(ALIGN_RAW, speaker, align_file)) as inp: contents = " ".join(list(map(lambda line: line.split()[-1], inp.readlines()[1:-1]))) makedirs(path.join(ALIGN_TEXT, speaker), exist_ok=True) makedirs(path.join(ALIGN_INDEXED, speaker), exist_ok=True) print(contents, end="", file=open(path.join(ALIGN_TEXT, speaker, align_file.split(".")[0] + ".txt"), "w")) np.save(path.join(ALIGN_INDEXED, speaker, align_file.split(".")[0]), map_letters(contents)) print("\n\n", "INDEXING ALIGN FILES:SUCCESS".center(100, "-"), sep="", end="\n\n\n")

UTF-8

Python

false

1,151

py

16

align_file_indexer.py

15

0.596872

0.585578

0

27

41.666667

122

JulesBelveze/wikipedia-pages-suggestion

13,675,175,889,773

66cf9adedaf72ea51c8435f3babc0811c80f7acc

5f329b39a638d88a3c046570f0f2e79926c25c19

/testers/PageRankTest.py

430f1bdd607498a85c3de6b7f5f72841cc10a610

[]

no_license

https://github.com/JulesBelveze/wikipedia-pages-suggestion

3abc3963a38cd6090ba99929c913cabf08dba7ea

ed9b4af493a257fca2d440027b4647f9d442b350

refs/heads/master

2020-03-31T18:35:09.466225

2019-05-06T06:28:19

152,464,264

0

null

import networkx as nx import sys sys.path.append('..') import PageRank G = nx.DiGraph() G.add_nodes_from([1,2,3,4,5,6,7,8,9,10,11]) G.add_edge(1,2) G.add_edge(1,4) G.add_edge(1,3) G.add_edge(2,3) G.add_edge(4,3) G.add_edge(1,5) G.add_edge(2,1) G.add_edge(5,2) G.add_edge(3,4) G.add_edge(2,4) PR = PageRank.PageRank(G) PR.constructDispersionMatrix(G) print(PR.getPageRank()) print(sum(PR.getPageRank()))

UTF-8

Python

false

406

py

16

PageRankTest.py

13

0.679803

0.598522

0

24

15.958333

43

SeoDongMyeong/tbot

8,366,596,342,653

820d55f7d3dd07ad3d69b6fc110818e2d80cf59e

3928ac6c2253928c27a4814eaf2fee92973e80cd

/run.py

610b5c168fcc46c67224136ecb71be2e9c5b207d

[]

no_license

https://github.com/SeoDongMyeong/tbot

77ee8095a1e76614cdb0ed67d65551ad0b842480

c4c67a0912b183fcbdee06a7d39f4e3ab62bc3e6

refs/heads/master

2021-05-20T17:56:05.111025

2016-06-20T06:41:26

61,489,341

0

null

# -*- coding: utf-8 -*- import requests import logging import re import os from uuid import uuid4 from urllib2 import quote from bs4 import BeautifulSoup from telegram.ext import Updater, CommandHandler from PIL import Image, ImageDraw, ImageFont from io import BytesIO from config import get_config logging.basicConfig(format='%(asctime)s - %(name)s - %(levelname)s - %(message)s', level=logging.INFO) logger = logging.getLogger(__name__) def get_image_from_url(url): r = requests.get(url) img = Image.open(BytesIO(r.content)) img = img.resize((150, 150), Image.NEAREST) return img def get_font(mode='key'): if not mode in ['key', 'value'] : raise ValueError('NOT MODE') size = 35 if mode == 'key' : size = 40 font = ImageFont.truetype('static/nanum.ttf', size) return font def get_overlog_uid(query): url = 'https://overlog.net/leaderboards/global/score?q=%s' % quote(query.encode('utf-8')) r = requests.get(url) soup = BeautifulSoup(r.text, 'html.parser') t = soup.find('table', class_='table-striped').find('tbody') tr = t.find('tr') if not tr.has_attr('data-uid'): return False return tr['data-uid'] def overlog_renew(uid): headers = {'content-type' : 'application/x-www-form-urlencoded; charset=UTF-8', 'origin' : 'https://overlog.net', 'referer' : 'https://overlog.net/detail/overview/' + uid, 'user-agent' : 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/51.0.2704.103 Safari/537.36'} url = 'https://overlog.net/detail/renew' body = {'uid' : uid} rv = requests.post(url, headers=headers, data=body).json() def get_overlog_hero_detail(uid, hero_id): entry = {} headers = {'content-type' : 'application/x-www-form-urlencoded; charset=UTF-8', 'origin' : 'https://overlog.net', 'referer' : 'https://overlog.net/detail/overview/' + uid, 'user-agent' : 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/51.0.2704.103 Safari/537.36'} url = 'https://overlog.net/detail/hero/%s' % hero_id body = {'uid' : uid} rv = requests.post(url, headers=headers, data=body).json() if rv['error'] != 0: return False html = rv['html'] soup = BeautifulSoup(html, 'html.parser') verts = soup.find_all(text=re.compile(u'영웅 기술')) entry['skill'] = [] for vert in verts: vert = vert.parent.parent skill_name = vert.find('h4').get_text().split(u'영웅 기술:')[1] tmp_skill = vert.find('dl') entry['skill'].append({ 'name' : skill_name, 'key' : tmp_skill.find('dt').get_text(), 'value' : tmp_skill.find('dd').get_text().strip() }) tmp_kill = soup.find('h4', text=re.compile(u'처치')).parent.find('dl') entry['kill'] = { 'key' : tmp_kill.find('dt').get_text(), 'value' : tmp_kill.find('dd').get_text().strip() } tmp_deal = soup.find(text=re.compile(u'딜량')).parent.parent.find_all('dl')[2] entry['deal'] = { 'key' : tmp_deal.find('dt').get_text().replace(u'게임당 평균 ', ''), 'value' : tmp_deal.find('dd').get_text().strip() } return entry def get_overlog_data(uid): entries = {'data' : []} url = 'https://overlog.net/detail/overview/%s' % uid r = requests.get(url) soup = BeautifulSoup(r.text, 'html.parser') character = soup.find('div', class_='character') entries['playerIcon'] = character.find('img', class_='portrait')['src'] entries['displayName'] = character.find('p', class_='displayName').contents[0].strip() entries['level'] = character.find(text=re.compile('Level')) heros = soup.find_all(class_='heroList')[1] basics = heros.find_all(class_='heroBasic') details = heros.find_all(class_='heroDetail') idx = 0 for basic in basics: entry = {} idx += 1 entry['idx'] = idx entry['name'] = basic.find('span', class_='name').get_text() check_point = basic.find('td', class_='not_available') if check_point : entry['text'] = check_point.get_text() else : entry['playTime'] = basic.find('td', class_='timePlayed').get_text().strip() entry['kda'] = basic.find('span', class_='rate').get_text() entry['ratio'] = basic.find('span', class_='ratio').get_text() entry['objective'] = basic.find(class_='objective').contents[2].strip() entry['img'] = basic.find('img')['src'] hero_id = basic['data-hero'] entry['info'] = get_overlog_hero_detail(uid, hero_id) entries['data'].append(entry) return entries def overlog(bot, update): chat_id = update.message.chat_id query = update.message.text.split('/w')[1].strip() uid = get_overlog_uid(query) if not uid: bot.sendMessage(update.message.chat_id, text='등록된 프로필이 없습니다. "Overwatch#1234"와 같이 뒤에 숫자까지 함께 입력하여 검색하시기 바랍니다. 대소문자를 구분합니다') return overlog_renew(uid) bot.sendMessage(update.message.chat_id, text=u'%s님 데이터가 갱신되었습니다.' % (query)) entries = get_overlog_data(uid) text = '%s[%s]' % (entries['displayName'], entries['level']) text += '\n\n' for entry in entries['data'][:3] : text += '%d. %s(%s)\n' % (entry['idx'], entry['name'], entry['playTime']) text += 'kda : %s %s : %s %s : %s\n' % (entry['kda'], '승률'.decode('utf-8'), entry['ratio'], '평균 임무기여'.decode('utf-8'), entry['objective']) text += '%s : %s\n' % (entry['info']['kill']['key'], entry['info']['kill']['value']) text += '%s : %s\n' % (entry['info']['deal']['key'], entry['info']['deal']['value']) for skill in entry['info']['skill'] : text += '%s(%s) : %s\n' % (skill['name'], skill['key'], skill['value']) text += '\n' bot.sendMessage(update.message.chat_id, text=text) def add_text(draw, key, value, bg_w=50, bg_h=50): key_font = get_font('key') val_font = get_font('value') k_w, k_h = key_font.getsize(key) # keyword width, keyword height v_w, v_h = val_font.getsize(value) # value width, value height draw.text((bg_w, bg_h), key,fill='white', font=key_font) draw.text((bg_w, bg_h + k_h), value, fill='white', font=val_font) bg_w += k_w + 20 if k_w > v_w else v_w + 20 # margin width return bg_w def overlog_img(bot, update): chat_id = update.message.chat_id query = update.message.text.split('/wi')[1].strip() uid = get_overlog_uid(query) if not uid: bot.sendMessage(update.message.chat_id, text='등록된 프로필이 없습니다. "Overwatch#1234"와 같이 뒤에 숫자까지 함께 입력하여 검색하시기 바랍니다. 대소문자를 구분합니다') return overlog_renew(uid) bot.sendMessage(update.message.chat_id, text=u'%s님 데이터가 갱신되었습니다.' % (query)) bot.sendMessage(update.message.chat_id, text=u'%s님 데이터 수집을 시작합니다.' % query) entries = get_overlog_data(uid) bg_img = Image.open('static/background-1.jpg') draw = ImageDraw.Draw(bg_img) img = get_image_from_url(entries['playerIcon']) bg_img.paste(img, (90, 90)) add_text(draw, entries['displayName'], entries['level'], 260, 90) bg_w, bg_h = 90, 310 for entry in entries['data'][:5]: if 'text' in entry.keys(): continue img = get_image_from_url(entry['img']) bg_img.paste(img, (bg_w, bg_h)) bg_w += 170 bg_w = add_text(draw, entry['name'], entry['playTime'], bg_w, bg_h) bg_w = add_text(draw, 'KDA', entry['kda'], bg_w, bg_h) bg_w = add_text(draw, u'승률', entry['ratio'], bg_w, bg_h) bg_w = add_text(draw, entry['info']['deal']['key'], entry['info']['deal']['value'], bg_w, bg_h) for skill in entry['info']['skill'] : key = '%s(%s)' % (skill['name'], skill['key']) bg_w = add_text(draw, key, skill['value'], bg_w, bg_h) # initialize bg_w = 90 # bg_h += 170 bg_h += 220 filename = '%s.jpeg' % str(uuid4().hex) bg_img.save(filename, quality=60, optimize=True, progressive=True) bot.sendMessage(update.message.chat_id, text=u'데이터 수집이 완료되었습니다. 이미지 업로드를 시작합니다.') bot.send_photo(update.message.chat_id, photo=open(filename, 'rb')) os.remove(filename) def echo(bot, update): bot.sendMessage(update.message.chat_id, text='Hi!') def main() : updater = Updater(get_config('token')) dp = updater.dispatcher dp.add_handler(CommandHandler('echo', echo)) dp.add_handler(CommandHandler('w', overlog)) dp.add_handler(CommandHandler('wi', overlog_img)) updater.start_polling() updater.idle() if __name__ == '__main__' : main()

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syurskyi/Python_Topics

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e23a4f57ce5474d468258e5e63b9e23fb6011188

/105_network/002_requests_library/_exercises/templates/Python HTTP Guide. Requests library/003_.py

f1210ab0b92fbaec2e35cde3ff03b3412821485d

[]

no_license

https://github.com/syurskyi/Python_Topics

52851ecce000cb751a3b986408efe32f0b4c0835

be331826b490b73f0a176e6abed86ef68ff2dd2b

refs/heads/master

2023-06-08T19:29:16.214395

2023-05-29T17:09:11

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null

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2023-02-16T03:08:10

2019-11-09T02:58:47

2022-11-03T01:22:28

2023-02-16T03:08:09

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2

33

Python

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# # В простых методах запросов значительных отличий у них не имеется. Но давайте взглянем на работы с Basic Auth: # # ______ u__.r__ # password_mgr _ ?.r__.H_PMWDR.. # top_level_url _ 'https://httpbin.org/basic-auth/user/passwd' # password_mgr.a_p.. N.. ? 'user', 'passwd' # handler _ ?.r__.H_BAH.. ? # opener _ ?.r__.b_o.. ? # response _ ?.o.. t_.. # print(?.g_c.. # # 200 # print ?.r.. # # b'{\n "authenticated": true, \n "user": "user"\n}\n' # # # ______ r__ # response _ ?.g.. 'https://httpbin.org/basic-auth/user/passwd' a.._('user', 'passwd' # print ?.c.. # # b'{\n "authenticated": true, \n "user": "user"\n}\n' # print ?.j.. # # {'user': 'user', 'authenticated': True} # # # А теперь чувствуется разница между pythonic и non-pythonic? Я думаю разница на лицо. # # И несмотря на тот факт, что requests ничто иное как обёртка над urllib3, # # а последняя является надстройкой над стандартными средствами Python, # # удобство написания кода в большинстве случаев является приоритетом номер один. # # # # В requests имеется: # # # # Множество методов http аутентификации # # Сессии с куками # # Полноценная поддержка SSL # # Различные методы-плюшки вроде .json(), которые вернут данные в нужном формате # # Проксирование # # Грамотная и логичная работа с исключениями

UTF-8

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003_.py

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hpham-broadsoft/Cloudqa

4,956,392,300,365

192c736fa0d9d9b92b1bef26c50b519573440823

68d7f806a2d49093c92b34150f81f4b03198d6c8

/utils/RialtoQA/RialtoAutomationTestReport/Engineers.py

469662c901a2fb6da230c4e9d7c1481ac861164a

[]

no_license

https://github.com/hpham-broadsoft/Cloudqa

c1344166baf9382f90e11c39605e71c3636965ae

5d1fd3934972924de9b04c49958ec8d34bf01486

refs/heads/master

2019-04-29T04:28:50.231114

2017-06-20T23:25:46

94,146,466

0

null

#from requests.auth import HTTPBasicAuth import requests from xml.etree import ElementTree as ET import getpass import csv import datetime import getpass from selenium import webdriver from selenium.webdriver.common.keys import Keys import os.path import sys import sqlite3 as db #username=sys.argv[1] #password=sys.argv[2] #username=raw_input("Enter Username:") #password=getpass.getpass("Enter Password:") List_Files=['Rialto-PartyManager','Rialto-MyPhone','Rialto-MyReports','Rialto-SP Portal','Rialto-SP Portal2','Rialto-MySite'] Final_Last_Build=[] Build_Data=[] for i in List_Files: print i url="http://10.242.148.135:9090/job/"+i+"/lastBuild/" headers = {'Authorization':'Basic Z3ZlbmthdGVzd2FyYW46cWFzdm5yZXBv'} resp = requests.get(url,headers=headers,verify = False) string1=resp.content Last_Build=string1.split('</title>') Last_Build=Last_Build[0].split('<title>') Last_Build=Last_Build[1].split('#') Last_Build=Last_Build[1].split('[Jenkins]') Last_Build=Last_Build[0].split(' ') Final_Last_Build.append(int(Last_Build[0])) #print Last_Build print Final_Last_Build url="http://10.242.148.135:9090/api/xml" headers = {'Authorization':'Basic Z3ZlbmthdGVzd2FyYW46cWFzdm5yZXBv'} r = requests.get(url,headers=headers,verify = False) #print r.content with open("colour.xml","w") as f: f.write(r.content) print "Successfully Created Color.xml" doc = ET.parse("colour.xml").getroot() jobname=doc.findall("job") for filename in jobname: color=filename.find("color").text name=filename.find("name").text if 'anime' in color: if name in List_Files: l=List_Files.index(name) print Final_Last_Build[l] Final_Last_Build[l]=Final_Last_Build[l]-1 print Final_Last_Build[l] for files, build in zip(List_Files, Final_Last_Build): try: build=str(build) url="http://10.242.148.135:9090/job/"+files+"/"+build+"/robot/report/output.xml" headers = {'Authorization':'Basic Z3ZlbmthdGVzd2FyYW46cWFzdm5yZXBv'} r = requests.get(url,headers=headers,verify = False) #print r.content Filename=files+".xml" with open(Filename,"w") as f: f.write(r.content) print "Successfully Created" + files except Exception as e: print e now = datetime.datetime.now() print str(now) #from bs4 import BeautifulSoup FList = [] RLTO = [] Only_RLTO=[] FINAL_LIST=[] Person = [] DictList = [] FatalError=[] Not_Present=[] File_list=[] String1=[] class Testnew1(): doc = ET.parse("Finaloutput.xml").getroot() filename=doc.findall("Filename") for filename in filename: fname=filename.get('key') #print fname doc1 = ET.parse(fname).getroot() logentries = doc1.findall("suite") for logentry in logentries: parentsuite=logentry.get('name') print parentsuite suites=logentry.findall("suite") for suite in suites: childsuite=suite.get('name') #print childsuite test=suite.findall("test") for test in test: name=test.attrib["name"] #print name status = test.find("status") #print status s=status.get('status') if s=="PASS": msg=test.find("status").text string1=parentsuite,msg,"PASS" FINAL_LIST.append(string1) RLTO.append(name) if s=="FAIL": msg=test.find("status").text string1=parentsuite,msg,"FAIL" FINAL_LIST.append(string1) RLTO.append(name) #print FINAL_LIST print "Total Testcase Passed:" +str(len(FINAL_LIST)) for i in range(len(RLTO)): if "RLTOQA" in RLTO[i].split(":")[0]: RLTO[i]=RLTO[i].split(":")[0] else: RLTO[i]=RLTO[i].split(":")[1] for i in range(len(RLTO)): if "-" in RLTO[i]: Only_RLTO1=RLTO[i]=RLTO[i].split("-")[1] if "_" in RLTO[i]: Only_RLTO1=RLTO[i]=RLTO[i].split("_")[1] if "RLTOQA"in Only_RLTO1: Only_RLTO1=RLTO[i]=RLTO[i].split(",")[0] #print Only_RLTO1 Only_RLTO.append(Only_RLTO1) continue if " " in Only_RLTO1: Only_RLTO1=RLTO[i]=RLTO[i].split(" ")[0] #print Only_RLTO1 Only_RLTO.append(Only_RLTO1) else: Only_RLTO.append(Only_RLTO1) ####print Only_RLTO ####print len(Only_RLTO) for i in range(len(Only_RLTO)): string2=Only_RLTO[i],FINAL_LIST[i] FList.append(string2) #print FList with open("RIALTO-AUTOMATION STATUS - REGRESSION.csv", 'rb') as f: reader = csv.reader(f) row2 = list(reader) length=len(row2) for row in row2: for rlto in Only_RLTO: if rlto in row[0]: if rlto==row[0]: ####print row[0] +'Present in '+ rlto + "Owner" + row[3] String2=row[0],row[3] Person.append(String2) Not_Present.append(row[0]) print Person print len(Person) for i in Only_RLTO: if i not in Not_Present: String2=i,"Unassigned" Person.append(String2) #print Person #print len(Person) dict_tuples2 = dict(FList) string=[(int, str, dict_tuples2.get(int, 0)) for int, str in Person] #print string #print len(string) conn = db.connect("TestAnalysisTool.db") c=conn.cursor() #c.execute("CREATE TABLE AnalysisEngineerTable(Id INTEGER PRIMARY KEY AUTOINCREMENT,RLTOQAID INTEGER NOT NULL UNIQUE,FileName Varchar(60),Engineer Varchar(20),Date2 Date,Status Varchar(15));") for ids,name,msg in string: parentname=msg[0] Fmsg=msg[1] Status=msg[2] print ids,name,parentname,Fmsg,Status #c.execute("SELECT * FROM AnalysisEngineerTable WHERE RLTOQAID = ?;",(int(ids))) #row=len(c.fetchall()) #if row==0: try: c.execute("INSERT INTO AnalysisEngineerTable(RLTOQAID,FileName,Engineer,Date2,Status) VALUES(?,?,?,?,?)",(ids,parentname,name,now,Status)) except Exception as e: print e conn.commit() conn.close()

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Engineers.py

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SahibSingh1311/Session_3

12,575,664,288,174

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/session12a.py

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[]

no_license

https://github.com/SahibSingh1311/Session_3

2b5574d6ba9c352aee8d602ae7aa8e6ec11076f1

41ab1cbca13e251c318bd657cbe3aa87f284f52e

refs/heads/master

2022-01-12T10:18:54.134755

2019-06-24T05:23:32

null

0

null

""" Database: mySQL prog Lang: SQL -> Structured Query Language 1. Create Database Database is collection of Tables Tables can be related to each other : 1 to 1 relation or 1 to many relationship 2. Create Table Table is collection of rows and columns eg: Excel Sheet ORM: Object relation mapping Your object's attribute should be your table column name but in tables we have 1 additional column and we call it as Primary Key 1 2 3 4....... code: CREATE TABLE customer( cid int PRIMARY KEY AUTO_INCREMENT, name varchar (256), phone varchar (20), email varchar (256) ) 3. Insert Data in Table cref = customer("John","9999988888","john@example.com") insert into customer(Null, "John","9999988888","john@example.com") 4. Install Library mysql-connector 5. Create a DBHelper 6. Update data in table """ import mysql.connector class DBHelper: def saveCustomerInDB(self, customer): #1. Create SQL Statement sqlInsert = "insert into customer values (Null, '{}', '{}','{}') ".format(customer.name,customer.phone, customer.email) #2 Create Connection con = mysql.connector.connect(user = "root", password = "", host ="localhost", database = "customer") #3 Obtain cursor or execute SQL statements {ACID} cursor = con.cursor() cursor.execute(sqlInsert) con.commit() print(customer.name, "SAVED!!") def updateCustomerInDB(self, customer): sql = "update customer set name = '{}', phone = '{}', email = '{}' where cid = '{}'".format(customer.name, customer.phone, customer.email, customer.cid ) con = mysql.connector.connect(user = "root", password ="", host = "localhost", database = "customer") cursor = con.cursor() cursor.execute(sql) con.commit() print("Customer Updated") def deleteCustomerDetails(self,customer): sql = "delete from customer where cid = {}".format(customer.cid) con = mysql.connector.connect(user="root", password="", host="localhost", database="customer") cursor = con.cursor() cursor.execute(sql) con.commit() def fetchAllCustomer(self): sql = "select * from customer" con = mysql.connector.connect(user="root", password="", host="localhost", database="customer") cursor = con.cursor() cursor.execute(sql) # row = cursor.fetchone() # print(row) # row = cursor.fetchone() # print(row) rows = cursor.fetchall() #print(rows) #Rows is a List of Tuples, 1 Tuple Represent 1 Row for row in rows: print(row) def fetchCustomer(self, cid): sql = "select * from customer where cid = {}".format(cid) con = mysql.connector.connect(user="root", password="", host="localhost", database="customer") cursor = con.cursor() cursor.execute(sql) row = cursor.fetchone() print(row) class customer: def __init__(self, name, phone, email): self.name = name self.phone = phone self.email = email def showCustomerDetails(self): print(">>Name: {} Phone: {} Email: {}".format(self.name, self.phone, self.email )) """ print("Options: ") print("1. Create New Customer") print("2. Update Customer") print("3. Delete Customer") print("4. Show All Customers") print("5. Show Particular Customers") choice = int(input("Enter Choice: ")) if choice == 1: cRef = customer(None, None, None) cRef.name = input("Enter Customer Name : ") cRef.phone = input("Enter Customer Phone : ") cRef.email = input("Enter Customer Email : ") cRef.showCustomerDetails() save = input("Do you want to Save Customer:(yes / no) ") if save == "yes": db = DBHelper() db.saveCustomerInDB(cRef) elif choice == 2: cRef = customer(None, None, None) cRef.cid = int(input("Enter Customer ID : ")) #You NEED TO KNOW THE CUSTOMER ID cRef.name = input("Enter Customer Name : ") cRef.phone = input("Enter Customer Phone : ") cRef.email = input("Enter Customer Email : ") cRef.showCustomerDetails() save = input("Do you want to Save Customer:(yes / no) ") if save == "yes": db = DBHelper() db.updateCustomerInDB(cRef) elif choice == 3: cRef = customer(None, None, None) cRef.cid = int(input("Enter Customer ID : ")) # You NEED TO KNOW THE CUSTOMER ID save = input("Do you want to delete Customer:(yes / no) ") if save == "yes": db = DBHelper() db.deleteCustomerDetails(cRef) print("Customer Deleted") elif choice == 4: db = DBHelper() db.fetchAllCustomer() elif choice == 5: cRef = customer(None, None, None) cRef.cid = int(input("Enter Customer ID: ")) db = DBHelper() db.fetchCustomer(cRef.cid) """

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Gillepool/Coursera

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/movieReccomendations.py

1c7fa4aac3aa0eea637d961acb1158d112bc7469

[]

no_license

https://github.com/Gillepool/Coursera

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refs/heads/master

2020-09-11T08:18:00.440936

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null

import scipy.io import numpy as np import scipy.optimize as op import matplotlib.pyplot as plt def cofiCostFunc(params, Y, R, num_users, num_movies, num_features, Lamnda): X = params[0:num_movies*num_features].reshape(num_movies, num_features) Theta = params[num_movies*num_features:].reshape(num_users, num_features) J = 0 X_grad = np.zeros((np.shape(X))) Theta_grad = np.zeros((np.shape(Theta))) J_temporary = (X.dot(Theta.T) - Y)**2 J = np.sum(np.sum(J_temporary[R == 1]))/2 + Lamnda/2 * np.sum(np.sum(Theta**2)) + Lamnda/2 * np.sum(np.sum(X**2)) X_grad = ((X.dot(Theta.T) - Y ) *R ).dot(Theta) + Lamnda*X Theta_grad = ((X.dot(Theta.T) - Y) * R).T.dot(X) + Lamnda*Theta grad = np.append(X_grad.flatten(), Theta_grad.flatten()) return J, grad def computeNumericalGradient(J, theta): numgrad = np.zeros((np.shape(theta))) perturb = np.zeros((np.shape(theta))) e = 1e-4 for p in range(len(theta.flatten())): perturb[p] = e loss1, grad1 = J(theta - perturb) loss2, grad2 = J(theta + perturb) numgrad[p] = (loss2 - loss1)/(2*e) perturb[p] = 0 return numgrad def checkCostFunction(Lambda = None): if Lambda == None: Lambda = 0 X_t = np.random.rand(4,3) theta_t = np.random.rand(5,3) Y = X_t.dot(theta_t.T) Y[np.random.rand(np.shape(Y)[0]) > 0.5] = 0 R = np.zeros((np.shape(Y))) R[Y != 0] = 1 m, n = np.shape(X_t) X = np.random.randn(m,n) a, b = np.shape(theta_t) theta = np.random.randn(a,b) num_users = np.shape(Y)[1] num_movies = np.shape(Y)[0] num_features = np.shape(theta_t)[1] def J(t): return cofiCostFunc(t, Y, R, num_users, num_movies, \ num_features, Lambda) numgrad = computeNumericalGradient(J, \ np.append(X.flatten(), theta.flatten())) cost, grad = cofiCostFunc(np.append(X.flatten(), \ theta.flatten()), Y, R, num_users, \ num_movies, num_features, Lambda) #print numgrad, grad #print 'The above two columns you get should be very similar.' #print '(Left-Your Numerical Gradient, Right-Analytical Gradient)' #diff = np.linalg.norm(numgrad-grad)/np.linalg.norm(numgrad+grad) #print 'If your backpropagation implementation is correct, then \ #the relative difference will be small (less than 1e-9).\ #Relative Difference: ', diff def LoadMovieList(): counter = 0 movielist = {} with open('data/movie_ids.txt', 'rb') as fid: lines = fid.readlines() for line in lines: movielist[counter] = line.split(' ', 1)[1] counter += 1 return movielist def normalizeRatings(Y, R): [m, n] = np.shape(Y) Ymean = np.zeros((m, 1)) YNorm = np.zeros(np.shape(Y)) for i in range(m): idx = np.where(R[i, :] == 1) Ymean[i] = np.mean(Y[i, idx]) YNorm[i, idx] = Y[i, idx] - Ymean[i] return YNorm, Ymean print 'Loading movie ratings dataset.' data = scipy.io.loadmat('data/ex8_movies.mat') R = data['R'] # R is a 1682x943 matrix. R[i, j] where i is movie and j is user. R(i, j) = 1 id user j gave a rating to movie i Y = data['Y'] # A matrix 1682x943 with 1682 moies annd 943 users #R[0, :] movie number 0, which is Toy story, checking for all users print 'Average rating for movie 1 (Toy Story): %8.8f/5 ' \ %np.mean(Y[0,np.where(R[0,:] -1 == 0)]) plt.figure(figsize=(5, 5)) plt.imshow(Y) #plt.show() #Debugging the collaborative filtering cost function data1 = scipy.io.loadmat('data/ex8_movieParams.mat') X = data1['X'] theta = data1['Theta'] # Reduce the data set size so that this runs faster num_users = 4 num_movies = 5 num_features = 3 X = X[0:num_movies, 0:num_features] theta = theta[0:num_users, 0:num_features] Y = Y[0:num_movies, 0:num_users] R = R[0:num_movies, 0:num_users] #Evaluate the costfunction J, grad = cofiCostFunc(np.append(X.flatten(), theta.flatten()), Y, R, num_users, num_movies, num_features, 0) print(J) checkCostFunction(0) J, grad = cofiCostFunc(np.append(X.flatten(), theta.flatten()), Y, R, num_users, num_movies, num_features, 1.5) print(J) checkCostFunction(1.5) #Main code for learning movie recommendations and categories goes here...... movieList = LoadMovieList() my_ratings = np.zeros((1682,1)) #Ratings of a few random movies my_ratings[1] = 4 # Toy story, rating 4... my_ratings[98] = 2 my_ratings[7] = 3 my_ratings[12]= 5 my_ratings[54] = 4 my_ratings[64] = 5 my_ratings[66] = 3 my_ratings[69] = 5 my_ratings[183] = 4 my_ratings[226] = 5 my_ratings[335] = 5 my_ratings[2] = 5 my_ratings[3] = 1 my_ratings[99] = 5 my_ratings[123]= 5 my_ratings[333] = 4 my_ratings[76] = 5 my_ratings[97] = 3 my_ratings[212] = 5 my_ratings[200] = 4 my_ratings[90] = 1 my_ratings[330] = 1 print("\n\nNew User Ratings:\n") for i in range(len(my_ratings)): if my_ratings[i] > 0: print("Rated %d for %s\n", my_ratings[i], movieList[i-1]) print 'Training collaborative filtering...' data = scipy.io.loadmat('data/ex8_movies.mat') R = data['R'] Y = data['Y'] #Add my own ratings toe the data matirces Y = np.append(my_ratings, Y, 1) R = np.append((my_ratings != 0), R, 1) #Normaliz ratings [Ynorm, Ymean] = normalizeRatings(Y, R) #Usefule values num_users = np.shape(Y)[1] num_movies = np.shape(Y)[0] num_features = 10 # number of "unknown" categpries(features) #set init params (Theta, X) X = np.random.randn(num_movies, num_features) Theta = np.random.randn(num_users, num_features) initital_parameters = np.append(X.flatten(), Theta.flatten()) Lambda = 10 cost = lambda params: cofiCostFunc(params, Y, R, num_users, num_movies, num_features, Lambda)[0] grad = lambda params: cofiCostFunc(params, Y, R, num_users, num_movies, num_features, Lambda)[1] theta = op.minimize(cost, np.append(X.flatten(), Theta.flatten()), method='CG', jac=grad, options={'disp':True, 'maxiter':50}) theta = theta.x print(theta) #Unfold the theta X = theta[:num_movies*num_features].reshape(num_movies, num_features) Theta = theta[num_movies*num_features:].reshape(num_users, num_features) p = X.dot(Theta.T) my_predictions = p[:, 0]+Ymean.flatten() movieList = LoadMovieList() ix = my_predictions.argsort()[::-1] print(R) for i in range(len(movieList)): j = ix[i] print("Predicting rating %.1f for movie %s" % (my_predictions[j]/2, movieList[j]))

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MostafaOkasha/orc

13,374,528,180,442

3adcc5aa06d3682cc97bf41eee3ba0634f0033e2

9e0607d3cc71c1e890b558742305f2669777b8b4

/database.py

7894a89d83dfdc09d9ec00da53d98b169559b829

[]

no_license

https://github.com/MostafaOkasha/orc

9858111d841ee052b57a69becd3812257ec11d02

d4829cbcb698e037cd741a61a0eaf501aa2da708

refs/heads/master

2020-04-09T15:11:01.261873

2016-11-04T20:05:58

null

0

null

#!/usr/bin/python import sqlite3 import datetime # TODO catch DB errors # Setup sql Instructions ''' To setup sqlite3 to make it more readable when running queries run the following .header on .mode column .timer on To setup the databases USER TABLE CREATE TABLE IF NOT EXISTS `users` ( `id` float NOT NULL, `name` varchar(30) NOT NULL, `pw_hash` varchar(60) NOT NULL, `bad_pw_count` varchar(60) NOT NULL, `game_wins` int(11) NOT NULL, `game_total` int(11) NOT NULL, `game_inprogress` tinyint(1) NOT NULL, `date_joined` date NOT NULL, `last_connected` date NOT NULL, `account_locked` tinyint(1) NOT NULL, `locked_date` date NOT NULL, `require_pw_change` tinyint(1) NOT NULL, PRIMARY KEY (`id`) ); GAME TABLE CREATE TABLE IF NOT EXISTS `game` ( `id` float NOT NULL, `player_1` float NOT NULL, `player_2` float NOT NULL, `date_started` date NOT NULL, `date_ended` date NOT NULL, `player_move` float NOT NULL, `game_winner` float NOT NULL, PRIMARY KEY (`id`,`date_started`) ); MOVES TABLE CREATE TABLE IF NOT EXISTS `moves` ( `move_id` int(11) NOT NULL, `id` int(11) NOT NULL, `from` int(11) NOT NULL, `to` int(11) NOT NULL, `date` int(11) NOT NULL, `time` int(11) NOT NULL, PRIMARY KEY (`move_id`) ); INSERT DATA into Users table INSERT INTO `users` (`id`, `name`, `pw_hash`,`bad_pw_count`, `game_wins`, `game_total`, `game_inprogress`, `date_joined`, `last_connected`, `account_locked`, `locked_date`,`require_pw_change`) VALUES (1, 'shane', '1',0, 0, 0, 0, '2016-04-11', '2016-04-11', 0, 0, 0), (2, '2', 'c4ca4238a0b9',0, 0, 0, 0, '2016-04-18', '2016-04-18', 0, 0, 0); ''' # To use SQLLite Instructions ''' .tables - Will list out the tables .schema [tablename] - Will show the CREATE statement(s) for a table or tables ''' def authuser(uname, pw): print("authing user") toreturn = False sql = 'SELECT * from users where name = "'+uname+'" AND pw_hash = "'+pw+'";' data = (runquery(sql)) if len(data) != 0: if data[9] != 1: # account not locked? sql = "UPDATE users SET last_connected = " + '"' + datetime.datetime.now().strftime("%Y-%m-%d") + '"' + ' WHERE name = "' + uname + '";' updatedatabase(sql) toreturn = True else: toreturn = "Account locked" if toreturn != True: print("Username/Pasword didn't match - looking for username") sql = 'SELECT * from users where name = "' + uname + '";' data = (runquery(sql)) if len(data) != 0: # Found username print("found username") badpwcount = int(data[3]) + 1 if badpwcount <= 5: sql = "UPDATE users SET bad_pw_count = " + str(badpwcount) + ' WHERE name = "' + str(uname) + ";" toreturn = "Incorrect username password combination" else: sql = "UPDATE users SET account_locked = 1, locked_date = " + '"' + datetime.datetime.now().strftime("%Y-%m-%d") + '"' + ' WHERE name = "' + str(uname) +'";' toreturn = "Account locked" updatedatabase(sql) return toreturn def updatedatabase(sqlstatement): try: con = sqlite3.connect('orc.db') cur = con.cursor() cur.execute(sqlstatement) con.commit() except sqlite3.Error: if con: con.rollback() finally: if con: con.close def runquery(sqlstatement): con = sqlite3.connect('orc.db') cur = con.cursor() cur.execute(sqlstatement) data = cur.fetchall() if len(data) != 0: data = data[0] # convert to a Tuple else: data = "" con.close() return data

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py

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database.py

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trucker-su/Django-Blog-With-Quiz-Game

10,909,216,942,518

f38e8fc5cfc19a7356708a87fc66e4707ae9a77d

06d8496178d209b2c7914ff1b2c2cc3aecf7829b

/blog/migrations/0016_article_slug.py

097b5245319ad72223e027c77c1eef6786f54e2f

[]

no_license

https://github.com/trucker-su/Django-Blog-With-Quiz-Game

111d5f87d0f573e15e1c1baec9f23fa4029b380b

e45d692414829e20722b400d53fa129312b4918f

refs/heads/master

2023-04-03T22:24:52.821470

2021-03-19T06:28:02

null

0

null

# Generated by Django 3.0.5 on 2020-06-01 16:27 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('blog', '0015_article_article_text2'), ] operations = [ migrations.AddField( model_name='article', name='slug', field=models.SlugField(blank=True, max_length=250, null=True), ), ]

UTF-8

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407

py

35

0016_article_slug.py

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0.592138

0.535627

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18

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ioppermann/munin-contrib

14,766,097,586,745

ff7e541c9dccf7d0e949e12d9000c214a4209663

c4c5ee3612c37ba495fcc41836635fd10191b926

/plugins/weather/weather_

d91580b7b7ec3db6eb848695278c9ea2ce0a38af

[]

no_license

https://github.com/ioppermann/munin-contrib

9ef935303baab10c3c453a1887d718a0b9d4af68

c9157be3fe0bdcc3fb54855056e1cebe94e4dcd5

refs/heads/master

2021-01-24T03:37:46.738509

2018-02-24T21:58:04

2018-02-24T21:58:50

21,696,221

7

3

null

true

2015-01-07T18:02:47

2014-07-10T14:01:37

2014-09-10T05:39:59

2015-01-07T18:02:45

4,938

3

1

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Perl

null

#!/usr/bin/python import os import re import sys import urllib url = 'http://www.weather.com/weather/today/%s' re_tmp = re.compile('realTemp: "(\d+)"') re_hum = re.compile('relativeHumidity: "(\d+)"') re_loc = re.compile('locName: "([\w ]+)"') #code = sys.argv[0][(sys.argv[0].rfind('_') + 1):] code = os.environ.get('code', sys.argv[0][(sys.argv[0].rfind('_') + 1):]) if code == None: sys.exit(1) if len(sys.argv) == 2 and sys.argv[1] == "autoconf": print "yes" elif len(sys.argv) == 2 and sys.argv[1] == "config": u = urllib.urlopen(url % code) txt = u.read() u.close() LOC_list = re_loc.findall(txt) if len(LOC_list): LOC = LOC_list[0] else: LOC = "Unknown" print 'graph_title Weather in %s' % LOC print 'graph_vlabel Temperature and Humidity' print 'graph_category sensors' print 'temperature.label Temperature' print 'humidity.label Humidity' print 'graph_args --base 1000 -l 0' else: u = urllib.urlopen(url % code) txt = u.read() u.close() TMP_F_list = re_tmp.findall(txt) HUM_list = re_hum.findall(txt) if len(HUM_list): HUM = HUM_list[0] else: sys.exit(1) if len(TMP_F_list): TMP_F = TMP_F_list[0] TMP_C = (int(TMP_F) - 32) * 5/9 else: sys.exit(1) print 'temperature.value %s' % TMP_C print 'humidity.value %s' % HUM

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Python

false

1,279

806

weather_

499

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0.608288

0

61

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TheKinshu/100-Days-Python

8,744,553,426,205

e12e6aa86ada66e9b77a3702eceed1cf100e2ad9

0c7ff0ec35ba2bb38f99ef6ecb261ec33466dd52

/Day45/MovieToWatch.py

5be19e2e5e47ed622655b39619f209ed9e9a8c9e

[]

no_license

https://github.com/TheKinshu/100-Days-Python

15cbacc608ee349cc9733a7032e10a359bebb731

293ad6b3e5f5208da84efbc5b2d2d395a5a53421

refs/heads/master

2023-04-18T08:21:30.361800

2021-05-02T18:48:39

351,582,416

0

null

from bs4 import BeautifulSoup import requests URL = "https://www.empireonline.com/movies/features/best-movies-2/" response = requests.get(URL) website_html = response.text soup = BeautifulSoup(website_html, "html.parser") content = soup.find(name="div", class_="jsx-3821216435 block-item listicle-container") movies = content.find_all(name='a') reviewsMovies = [movie.getText() for movie in movies if "Read Empire's" in (movie.getText())] movieList = [] for movie in reviewsMovies: temp = movie.split() movieList.append(' '.join(temp[4:])) movieL = (movieList[::-1]) with open("./Day45/movie.txt", "w") as file: for movie in movieL: file.write(f"{movie}\n")

UTF-8

Python

false

687

py

110

MovieToWatch.py

90

0.697234

0.673945

0

27

24.481481

93

yanbinbi/leetcode

463,856,489,633

74029cb32b649d0f9a08c0294195485ca1cde5a3

5afd733a5c1f753601c69b8b4eae1b49edfbae7c

/101-200/119.py

93cf5d2bee16f95dc9da01e38c24bd119d1fb339

[]

no_license

https://github.com/yanbinbi/leetcode

9dcd4a0160be915006455b83d6b7cd39e9819811

616a868bfa7bdd00195067b0477b0236a72d23e0

refs/heads/master

2021-05-13T19:34:17.222576

2017-11-12T02:04:31

null

0

null

class Solution(object): def getRow(self, rowIndex): """ :type rowIndex: int :rtype: List[int] """ if rowIndex < 0: return [] ret = [1] for i in range(1, rowIndex+1): for j in range(i-1): ret.append(ret.pop(0)+ret[0]) ret.append(1) return ret

UTF-8

Python

false

362

py

219

119.py

218

0.444751

0.422652

0

14

24.857143

45

bianzheng123/NN_as_Classification

7,198,365,221,981

2443726509aad27c37d791600d25d25a03de6133

fafecccce95eb60bebbb3fb9a12dc0517bd0e8ff

/config_batch_run.py

6ab5e9209207f99f98428d57ba87840752e96d9c

[]

no_license

https://github.com/bianzheng123/NN_as_Classification

92d41a9845e7d6ab1bf7c129a4ae6341b0d535cc

57c56d196c54d41b9f3a5fece5664c68c5f07faf

refs/heads/master

2023-05-02T05:06:50.856257

2021-05-19T04:38:54

314,740,560

0

null

import os from util import send_email def run_nohup(long_config_dir, short_config_dir, dataset_name, fname, _type, k): os.system('nohup python3 -u run.py --long_term_config_dir %s --short_term_config_dir %s --type %s --k %d > ' './log/%s/%s_%s.log 2>&1 &' % ( long_config_dir, short_config_dir, _type, k, _type, dataset_name, fname)) def run_frontend(long_config_dir, short_config_dir, _type, k): os.system('python3 -u run.py --long_term_config_dir %s --short_term_config_dir %s --type %s --k %d' % ( long_config_dir, short_config_dir, _type, k)) ''' nn_classification short_config_fname_arr = ['1_hnsw_16', '1_kmeans_independent_16', '1_kmeans_multiple_16', '1_knn_16', '1_lsh_16', '1_random_hash_16'] pq_nn short_config_fname_arr = ['1_hnsw_16', '1_kmeans_independent_16', '1_knn_16', '1_lsh_16', '1_random_hash_16'] counting_index short_config_fname_arr = ['1_kmeans_independent_16', '1_kmeans_multiple_16', '1_e2lsh_16'] ''' if __name__ == '__main__': ds_fname = 'deep' k = 10 _type = 'nn_classification' # pq_nn nn_classification counting_index base_config_dir = '/home/zhengbian/NN_as_Classification/config/%s/big_ds/' % _type long_config_dir = base_config_dir + ds_fname + '.json' # para_l = ['two_block_512_dim', 'two_block_1024_dim', 'one_block_2048_dim', 'one_block_512_dim', # 'two_block_512_dim_no_bn_dropout', 'res_net'] # cnn two_block_8192_dim_no_bn_dropout para_l = ['kaffpa'] # cnn two_block_8192_dim_no_bn_dropout # para_l = [1, 2, 3] method_l = ['knn'] para_name = 'partition_type' n_classifier = 4 for method in method_l: for para in para_l: fname = '{}_{}_256_{}_{}.json'.format(n_classifier, method, para_name, para) short_config_dir = base_config_dir + fname # run_nohup(long_config_dir, short_config_dir, ds_fname, fname, _type, k) run_frontend(long_config_dir, short_config_dir, _type, k) # send_email.send("glove increase weight complete")

UTF-8

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false

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py

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config_batch_run.py

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SalatskySal/osbs-client

10,728,828,353,923

6c59b869ae6bf0899d2d58f5dff96b19a56735b8

5e100133ec454150f20e97ed9e47df7f08468c3d

/tests/utils/test_yaml.py

5385d667f5fea9c4f005ae42d665cfade0e136a1

[ "BSD-3-Clause" ]

permissive

https://github.com/SalatskySal/osbs-client

460774e3cac5552edb26c5fdfcd421ee3c916cd7

b66e19eb5ffe0e6cf97cb5c0c2f57403a862a0cf

refs/heads/master

2021-02-12T17:11:29.599698

2020-04-27T19:21:45

2020-04-29T13:55:09

244,610,612

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BSD-3-Clause

true

2020-03-03T10:47:08

2020-03-03T10:47:07

2020-02-26T16:22:06

2020-03-02T20:35:30

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""" Copyright (c) 2020 Red Hat, Inc All rights reserved. This software may be modified and distributed under the terms of the BSD license. See the LICENSE file for details. """ from __future__ import absolute_import from flexmock import flexmock from osbs.utils.yaml import read_yaml, read_yaml_from_file_path import json import os import pkg_resources import pytest import yaml def test_read_yaml_file_ioerrors(tmpdir): config_path = os.path.join(str(tmpdir), 'nosuchfile.yaml') with pytest.raises(IOError): read_yaml_from_file_path(config_path, 'schemas/nosuchfile.json') @pytest.mark.parametrize('from_file', [True, False]) @pytest.mark.parametrize('config', [ ("""\ compose: modules: - mod_name:mod_stream:mod_version """), ]) def test_read_yaml_file_or_yaml(tmpdir, from_file, config): expected = yaml.safe_load(config) if from_file: config_path = os.path.join(str(tmpdir), 'config.yaml') with open(config_path, 'w') as fp: fp.write(config) output = read_yaml_from_file_path(config_path, 'schemas/container.json') else: output = read_yaml(config, 'schemas/container.json') assert output == expected def test_read_yaml_bad_package(caplog): with pytest.raises(ImportError): read_yaml("", 'schemas/container.json', package='bad_package') assert 'Unable to find package bad_package' in caplog.text def test_read_yaml_file_bad_extract(tmpdir, caplog): class FakeProvider(object): def get_resource_stream(self, pkg, rsc): raise IOError # pkg_resources.resource_stream() cannot be mocked directly # Instead mock the module-level function it calls. (flexmock(pkg_resources) .should_receive('get_provider') .and_return(FakeProvider())) config_path = os.path.join(str(tmpdir), 'config.yaml') with open(config_path, 'w'): pass with pytest.raises(IOError): read_yaml_from_file_path(config_path, 'schemas/container.json') assert "unable to extract JSON schema, cannot validate" in caplog.text def test_read_yaml_file_bad_decode(tmpdir, caplog): (flexmock(json) .should_receive('load') .and_raise(ValueError)) config_path = os.path.join(str(tmpdir), 'config.yaml') with open(config_path, 'w'): pass with pytest.raises(ValueError): read_yaml_from_file_path(config_path, 'schemas/container.json') assert "unable to decode JSON schema, cannot validate" in caplog.text

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2,539

py

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test_yaml.py

3

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thomas536/alltheplaces

14,963,666,099,195

3b81b7cb024a0f04a65ac1f52cdebfc9b90fa475

251f5c092d4b7760cec8c2b6324e5290b917721f

/locations/spiders/chrome_industries.py

05d92544eb10d5ec370da9e9f6832e93cf406db3

[ "MIT", "CC0-1.0" ]

permissive

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663a2441054ba62df6d6e070c19b1ba91f2f4f1f

ac4d4783572d55c0799fe6aeb5f6c0e72fad55fb

refs/heads/master

2021-11-27T12:21:46.387422

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import scrapy import re import json import lxml from locations.items import GeojsonPointItem class ChromeIndustriesSpider(scrapy.Spider): name = "chrome_industries" item_attributes = { 'brand': "Chrome Industries" } allowed_domains = ["www.chromeindustries.com"] start_urls = ( 'https://www.chromeindustries.com/on/demandware.store/Sites-chrome_na-Site/en_US/Stores-Search?latitude=32.7269669&longitude=-117.16470939999999&maxDistance=50000000', ) def parse(self, response): json_data = json.loads(response.body_as_unicode().replace('null' , '""')) for item in json_data['locations']: properties = { 'addr_full': item['address'] + ' '+item['address2'], 'phone': item['phone'], 'name' : item['name'], 'city': item['city'], 'state': item['state'], 'postcode': item['zipcode'], 'ref': item['id'], 'website': "https://www.chromeindustries.com/stores/", 'lat': float(item['latitude']), 'lon': float(item['longitude']) } yield GeojsonPointItem(**properties)

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/mxgraph/graph.py

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2020-07-06T14:02:55.025690

2019-08-18T16:20:45

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import numpy as np import scipy.sparse as ss import logging import mxgraph._graph_sampler as _graph_sampler def set_seed(seed): """Set the random seed of the inner sampling handler Parameters ---------- seed : int Returns ------- ret : bool """ return _graph_sampler.set_seed(seed) class CSRMat(object): """A simple wrapper of the CSR Matrix Apart from the traditoinal CSR format, we use two additional arrays: row_ids and col_ids to track the original ids of the row/col indices We use the C++ API to accelerate the speed if possible """ def __init__(self, end_points, ind_ptr, row_ids, col_ids, values=None, force_contiguous=False): self.end_points = end_points self.ind_ptr = np.ascontiguousarray(ind_ptr, dtype=np.int32) self.values = None if values is None else values.astype(np.float32) self.row_ids = row_ids self.col_ids = col_ids assert self.ind_ptr.size == len(self.row_ids) + 1 if force_contiguous: self.end_points = np.ascontiguousarray(self.end_points, dtype=np.int32) self.ind_ptr = np.ascontiguousarray(self.ind_ptr, dtype=np.int32) if self.values is not None: self.values = np.ascontiguousarray(self.values, dtype=np.float32) self.row_ids = np.ascontiguousarray(self.row_ids, dtype=np.int32) self.col_ids = np.ascontiguousarray(self.col_ids, dtype=np.int32) self._row_id_reverse_mapping = -1 * np.ones(self.row_ids.max() + 1, dtype=np.int32) self._col_id_reverse_mapping = -1 * np.ones(self.col_ids.max() + 1, dtype=np.int32) self._row_id_reverse_mapping[self.row_ids] = np.arange(self.row_ids.size, dtype=np.int32) self._col_id_reverse_mapping[self.col_ids] = np.arange(self.col_ids.size, dtype=np.int32) # self._row_id_reverse_mapping = dict() # self._col_id_reverse_mapping = dict() # for (i, ele) in enumerate(self.row_ids): # self._row_id_reverse_mapping[ele] = i # for (i, ele) in enumerate(self.col_ids): # self._col_id_reverse_mapping[ele] = i def to_spy(self): """Convert to the scipy csr matrix Returns ------- ret : ss.csr_matrix """ if self.values is None: values = np.ones(shape=self.end_points.shape, dtype=np.float32) else: values = self.values return ss.csr_matrix((values, self.end_points, self.ind_ptr), shape=(self.row_ids.size, self.col_ids.size)) @staticmethod def from_spy(mat): """ Parameters ---------- mat : ss.csr_matrix Returns ------- ret : CSRMat """ return CSRMat(end_points=mat.indices, ind_ptr=mat.indptr, row_ids=np.arange(mat.shape[0], dtype=np.int32), col_ids=np.arange(mat.shape[1], dtype=np.int32), values=mat.data, force_contiguous=True) @property def nnz(self): return self.end_points.size def reverse_row_map(self, node_ids): """Maps node ids back to row indices in the CSRMat Parameters ---------- node_ids : np.ndarray or list or tuple or int Returns ------- ret : np.ndarray """ # if isinstance(node_ids, (np.ndarray, list, tuple)): # return np.array(list(map(lambda ele: self._row_id_reverse_mapping[ele], node_ids)), # dtype=np.int32) # else: return self._row_id_reverse_mapping[node_ids] def reverse_col_map(self, node_ids): """Maps node ids back to col indices in the CSRMat Parameters ---------- node_ids : np.ndarray or list or tuple or int Returns ------- ret : np.ndarray """ # if isinstance(node_ids, (np.ndarray, list, tuple)): # return np.array(list(map(lambda ele: self._col_id_reverse_mapping[ele], node_ids)), # dtype=np.int32) # else: return self._col_id_reverse_mapping[node_ids] def submat(self, row_indices=None, col_indices=None): """Get the submatrix of the corresponding row/col indices Parameters ---------- row_indices : np.ndarray or None col_indices : np.ndarray or None Returns ------- ret : CSRMat """ row_indices = None if row_indices is None else row_indices.astype(np.int32) col_indices = None if col_indices is None else col_indices.astype(np.int32) dst_end_points, dst_values, dst_ind_ptr, dst_row_ids, dst_col_ids\ = _graph_sampler.csr_submat(self.end_points, self.values, self.ind_ptr, self.row_ids, self.col_ids, row_indices, col_indices) return CSRMat(end_points=dst_end_points, ind_ptr=dst_ind_ptr, row_ids=dst_row_ids, col_ids=dst_col_ids, values=dst_values) def summary(self): print(self.info()) def info(self): info_str = "Summary" + \ "\n Row={}, Col={}, NNZ={}".format(self.row_ids.size, self.col_ids.size, self.end_points.size) return info_str class SimpleGraph(object): """A simple graph container We use the CSR format to store the adjacency matrix """ def __init__(self, node_ids, node_types, undirected=True, end_points=None, ind_ptr=None, edge_weight=None, adj=None, edge_features=None): """Initialize a SimpleGraph Parameters ---------- node_ids : np.ndarray Maps the indices to the real node_ids node_types : np.ndarray Types of the nodes, 1 --> Train, 2 --> Valid, 3 --> Test undirected : bool end_points : np.ndarray Indices of the end-points of the connections ind_ptr : np.ndarray Pointer to the beginning of end_points for a specific array adj : CSRMat The CSR matrix that stores the value edge_features : None or np.ndarray The edge features, should be None or have shape (node_num, edge_feature_dim) """ if adj is not None: self.adj = adj else: assert end_points is not None and ind_ptr is not None self.adj = CSRMat(end_points=end_points, ind_ptr=ind_ptr, row_ids=node_ids, col_ids=node_ids, values=edge_weight) self.degrees = np.floor(np.array(self.adj.to_spy().sum(axis=1))).astype(np.int32).reshape((-1,)) self.node_ids = node_ids.astype(np.int32) self.node_types = node_types.astype(np.int32) self.undirected = undirected self.edge_features = edge_features self._node_id_reverse_mapping = -1 * np.ones(shape=self.node_ids.max() + 1, dtype=np.int32) self._node_id_reverse_mapping[self.node_ids] = np.arange(self.node_ids.size, dtype=np.int32) # self._node_id_reverse_mapping = dict() # for (i, ele) in enumerate(self.node_ids): # self._node_id_reverse_mapping[ele] = i @property def end_points(self): return self.adj.end_points.astype(np.int32) @property def ind_ptr(self): return self.adj.ind_ptr.astype(np.int32) @property def node_num(self): return self.node_ids.size @property def edge_num(self): return self.adj.end_points.size if not self.undirected else self.adj.end_points.size / 2 @property def avg_degree(self): return self.adj.end_points.size / self.node_ids.size def to_networkx(self): """Convert to a networkx graph Returns ------- ret: networkx.Graph """ raise NotImplementedError def reverse_map(self, node_ids): """Maps node ids back to indices in the graph Parameters ---------- node_ids : np.ndarray or list or tuple or int Returns ------- ret : np.ndarray """ return self._node_id_reverse_mapping[node_ids] # if isinstance(node_ids, (np.ndarray, list, tuple)): # return np.array(list(map(lambda ele: self._node_id_reverse_mapping[ele], node_ids)), # dtype=np.int32) # else: # return self._node_id_reverse_mapping[node_ids] def subgraph_by_indices(self, indices): """Obtain subgraph by index values, i.e., 0, 1, 2, ... Parameters ---------- indices Returns ------- """ subgraph_adj = self.adj.submat(row_indices=indices, col_indices=indices) subgraph_node_ids = self.node_ids[indices] subgraph_node_types = self.node_types[indices] if self.edge_features is not None: new_edge_features = self.edge_features[indices, :] else: new_edge_features = None return SimpleGraph(node_ids=subgraph_node_ids, node_types=subgraph_node_types, undirected=self.undirected, adj=subgraph_adj, edge_features=new_edge_features) def subgraph_by_node_ids(self, node_ids): """Obtain subgraph by the node_ids For example, the original graph has node ids: (2, 7, 9, 11) and you decide to take a look at the subgraph that contains nodes (2, 9), call G.subgraph_by_node_ids([2, 9]) Parameters ---------- real_ids Returns ------- """ return self.subgraph_by_indices(self.reverse_map(node_ids)) def save(self, fname): return np.savez_compressed(fname, node_ids=self.node_ids, node_types=self.node_types, end_points=self.adj.end_points, ind_ptr=self.adj.ind_ptr, undirected=np.array((self.undirected,), dtype=np.bool)) @staticmethod def load(fname): G_data = np.load(fname) if 'undirected' in G_data.keys(): if isinstance(G_data['undirected'], list): undirected = G_data['undirected'][0] else: undirected = G_data['undirected'] else: undirected = True # default value of undirected is true return SimpleGraph(node_ids=G_data['node_ids'], node_types=G_data['node_types'], undirected=undirected, end_points=G_data['end_points'], ind_ptr=G_data['ind_ptr']) @property def train_indices(self): all_indices = np.arange(0, self.node_num, dtype=np.int32) return all_indices[self.node_types == 1] @property def train_node_ids(self): return self.node_ids[self.train_indices] def fetch_train(self): return self.subgraph_by_indices(indices=self.train_indices) @property def valid_indices(self): all_indices = np.arange(0, self.node_num, dtype=np.int32) return all_indices[self.node_types == 2] @property def valid_node_ids(self): return self.node_ids[self.valid_indices] def fetch_valid(self): return self.subgraph_by_indices(indices=self.valid_indices) @property def test_indices(self): all_indices = np.arange(0, self.node_num, dtype=np.int32) return all_indices[self.node_types == 3] @property def test_node_ids(self): return self.node_ids[self.test_indices] def fetch_test(self): return self.subgraph_by_indices(indices=self.test_indices) @property def train_valid_indices(self): all_indices = np.arange(0, self.node_num, dtype=np.int32) return all_indices[self.node_types <= 2] @property def train_valid_node_ids(self): return self.node_ids[self.train_valid_indices] def fetch_train_valid(self): return self.subgraph_by_indices(indices=self.train_valid_indices) def summary(self, graph_name="Graph"): logging.info(self.info(graph_name)) def info(self, graph_name="Graph", indent_token="\t"): info_str = indent_token + "Summary of {}\n".format(graph_name) + \ indent_token + indent_token + "Undirected=%s\n" %str(self.undirected) + \ indent_token + indent_token + "Node Number={}, Train={}, Valid={}, Test={}\n".format(self.node_num, (self.node_types == 1).sum(), (self.node_types == 2).sum(), (self.node_types == 3).sum()) + \ indent_token + indent_token + "Edge Number={}\n".format(self.edge_num) + \ indent_token + indent_token + "Avg Degree={}".format(self.avg_degree) if self.edge_features is not None: info_str += indent_token + indent_token + "Edge Features Shape={}".format(self.edge_features.shape) return info_str def random_walk(self, initial_node=-1, walk_length=10000, return_prob=None, max_node_num=-1, max_edge_num=-1): """Random Walk At every step, we will return to the initial node with return_p. Otherwise, we will jump randomly to a conneted node. Ref: [KDD06] Sampling from Large Graphs Parameters ---------- initial_node : int or None walk_length : int return_prob : float or None max_node_num : int or None max_edge_num : int or None Returns ------- G_sampled : SimpleGraph """ if initial_node is None: initial_node = -1 if max_node_num is None: max_node_num = -1 if max_edge_num is None: max_edge_num = -1 if return_prob is None: return_prob = 0.15 subgraph_end_points, subgraph_ind_ptr, subgraph_node_ids =\ _graph_sampler.random_walk(self.end_points, self.ind_ptr, self.node_ids, int(self.undirected), initial_node, walk_length, return_prob, max_node_num, max_edge_num) indices = self.reverse_map(subgraph_node_ids) subgraph_node_types = self.node_types[indices] return SimpleGraph(node_ids=subgraph_node_ids, node_types=subgraph_node_types, undirected=self.undirected, end_points=subgraph_end_points, ind_ptr=subgraph_ind_ptr) class HeterGraph(SimpleGraph): def __init__(self, node_ids, node_types, num_set, node_sets, node_indices_in_set, undirected=True, end_points=None, ind_ptr=None, adj=None, edge_weight=None, edge_features=None, edge_types=None): super(HeterGraph, self).__init__(node_ids=node_ids, node_types=node_types, undirected=undirected, end_points=end_points, ind_ptr=ind_ptr, edge_weight=edge_weight, adj=adj, edge_features=edge_features) self._num_set = int(num_set) self.node_sets = node_sets ## which node set the node belongs to self.node_indices_in_set = node_indices_in_set ## the position where the node in its set #self.edge_types = edge_types @property def num_set(self): return self._num_set def subgraph_by_indices(self, indices): subgraph_adj = self.adj.submat(row_indices=indices, col_indices=indices) subgraph_node_ids = self.node_ids[indices] subgraph_node_types = self.node_types[indices] subgraph_node_sets = self.node_sets[indices] subgraph_node_indices_in_set = self.node_indices_in_set[indices] if self.edge_features is not None: new_edge_features = self.edge_features[indices, :] else: new_edge_features = None return HeterGraph(node_ids=subgraph_node_ids, node_types=subgraph_node_types, num_set=self._num_set, node_sets=subgraph_node_sets, node_indices_in_set=subgraph_node_indices_in_set, adj=subgraph_adj, undirected=self.undirected, edge_features=new_edge_features) def subgraph_by_node_ids(self, node_ids): return self.subgraph_by_indices(self.reverse_map(node_ids)) def node_sets_by_indices(self, indices): return self.node_sets[indices] def node_sets_by_node_ids(self, node_ids): return self.node_sets_by_indices(self.reverse_map(node_ids)) def node_indices_in_set_by_indices(self, indices): return self.node_indices_in_set[indices] def node_indices_in_set_by_node_ids(self, node_ids): return self.node_indices_in_set_by_indices(self.reverse_map(node_ids)) @staticmethod def load(fname): print("Loading a Heterogeneous Graph ...") G_data = np.load(fname) if 'undirected' in G_data.keys(): if isinstance(G_data['undirected'], list): undirected = G_data['undirected'][0] else: undirected = G_data['undirected'] else: undirected = True # default value of undirected is true if "adj" in G_data and isinstance(G_data["adj"], CSRMat): return HeterGraph(node_ids=G_data['node_ids'], node_types=G_data['node_types'], num_set=G_data['num_set'], node_sets=G_data['node_sets'], node_indices_in_set=G_data['node_indices_in_set'], adj=G_data['adj'], undirected=undirected) else: return HeterGraph(node_ids=G_data['node_ids'], node_types=G_data['node_types'], num_set=G_data['num_set'], node_sets = G_data['node_sets'], node_indices_in_set=G_data['node_indices_in_set'], end_points=G_data['end_points'], ind_ptr=G_data['ind_ptr'], edge_weight=G_data['edge_weight'], undirected=undirected) def save(self, fname): return np.savez_compressed(fname, node_ids=self.node_ids, node_types=self.node_types, set_num=self._num_set, node_sets=self.node_sets, node_indices_in_set=self.node_indices_in_set, adj=self.adj, undirected=np.array((self.undirected,), dtype=np.bool)) class BiGraph(SimpleGraph): def __init__(self, node_ids, node_types, num_node_set, num_edge_set, node_sets, node_indices_in_set, undirected=True, end_points=None, ind_ptr=None, adj=None, edge_weight=None, edge_features=None): super(BiGraph, self).__init__(node_ids=node_ids, node_types=node_types, undirected=undirected, end_points=end_points, ind_ptr=ind_ptr, edge_weight=edge_weight, adj=adj, edge_features=edge_features) self._num_node_set = int(num_node_set) self._num_edge_set = int(num_edge_set) self.node_sets = node_sets ## which node set the node belongs to SHAPE np.array(num_node, ) self.node_indices_in_set = node_indices_in_set ## the position where the node in its set SHAPE np.array(num_node, ) #self.edge_types = edge_types @property def num_node_set(self): return self._num_node_set @property def num_edge_set(self): return self._num_edge_set def subgraph_by_indices(self, indices): subgraph_adj = self.adj.submat(row_indices=indices, col_indices=indices) subgraph_node_ids = self.node_ids[indices] subgraph_node_types = self.node_types[indices] subgraph_node_sets = self.node_sets[indices] subgraph_node_indices_in_set = self.node_indices_in_set[indices] new_edge_features = self.edge_features[indices, :] if self.edge_features is not None else None return BiGraph(node_ids=subgraph_node_ids, node_types=subgraph_node_types, num_node_set=self._num_node_set, num_edge_set=self._num_edge_set, node_sets=subgraph_node_sets, node_indices_in_set=subgraph_node_indices_in_set, adj=subgraph_adj, undirected=self.undirected, edge_features=new_edge_features) def subgraph_by_node_ids(self, node_ids): return self.subgraph_by_indices(self.reverse_map(node_ids)) def node_sets_by_indices(self, indices): return self.node_sets[indices] def node_sets_by_node_ids(self, node_ids): return self.node_sets_by_indices(self.reverse_map(node_ids)) def node_indices_in_set_by_indices(self, indices): return self.node_indices_in_set[indices] def node_indices_in_set_by_node_ids(self, node_ids): return self.node_indices_in_set_by_indices(self.reverse_map(node_ids)) @staticmethod def load(fname): print("Loading a Bipartite Graph ...") G_data = np.load(fname) if 'undirected' in G_data.keys(): if isinstance(G_data['undirected'], list): undirected = G_data['undirected'][0] else: undirected = G_data['undirected'] else: undirected = True # default value of undirected is true if "adj" in G_data and isinstance(G_data["adj"], CSRMat): return BiGraph(node_ids=G_data['node_ids'], node_types=G_data['node_types'], num_node_set=G_data['num_node_set'], num_edge_set=G_data['num_edge_set'], node_sets=G_data['node_sets'], node_indices_in_set=G_data['node_indices_in_set'], adj=G_data['adj'], undirected=undirected) else: return BiGraph(node_ids=G_data['node_ids'], node_types=G_data['node_types'], num_node_set=G_data['num_node_set'][0], num_edge_set=G_data['num_edge_set'][0], node_sets = G_data['node_sets'], node_indices_in_set=G_data['node_indices_in_set'], end_points=G_data['end_points'], ind_ptr=G_data['ind_ptr'], edge_weight=G_data['edge_weight'], undirected=undirected) def save(self, fname): return np.savez_compressed(fname, node_ids=self.node_ids, node_types=self.node_types, num_node_set=self._num_node_set, num_edge_set=self._num_edge_set, node_sets=self.node_sets, node_indices_in_set=self.node_indices_in_set, adj=self.adj, undirected=np.array((self.undirected,), dtype=np.bool)) def check_subgraph(G_sampled, G_all): """Check whether G_sampled is a subgraph of G_all Parameters ---------- G_sampled : SimpleGraph G_all : SimpleGraph Returns ------- correct : bool """ correct = True for id_index in range(G_sampled.node_ids.size): sampled_node_id = G_sampled.node_ids[id_index] sampled_node_neighbor_id = G_sampled.node_ids[G_sampled.end_points[G_sampled.ind_ptr[id_index]: G_sampled.ind_ptr[id_index + 1]]] # print("sampled_node_id: {}".format(sampled_node_id),"\n", # "\t sampled_neighbor_ids: {}".format(sampled_node_neighbor_id)) G_all_idx = G_all.reverse_map(sampled_node_id) node_neighbor_id = frozenset(G_all.node_ids[G_all.end_points[G_all.ind_ptr[G_all_idx]: G_all.ind_ptr[G_all_idx + 1]]].tolist()) # print("node_id: {}".format(node_id), "\n", # "\t neighbor_ids: {}".format(node_neighbor_id)) for end_id in sampled_node_neighbor_id: if end_id not in node_neighbor_id: print("Wrong edge:", G_sampled.node_ids[id_index], end_id) return False return correct if __name__ == '__main__': from mxgraph.config import cfg import cProfile, pstats cfg.DATA_NAME = 'ppi' from mxgraph.iterators import cfg_data_loader import time set_seed(100) G_all, features, labels, num_class = cfg_data_loader() ######################################################## ############# Run Graph Sampling Algorithm ############# ######################################################## G_train = G_all.fetch_train() # pr = cProfile.Profile() # pr.enable() start = time.time() G_sampled_small = G_train.random_walk(initial_node=None, return_prob=0.0, walk_length=10000, max_node_num=2000, max_edge_num=None) end = time.time() print('Time spent for random walk sampling, sample %d nodes: %g'%(2000, end - start)) G_sampled_sub_set = G_train.subgraph_by_node_ids(G_sampled_small.node_ids) G_sampled_sub_set.summary("Random Walk Node Subgraph") G_sampled_random_node = G_train.subgraph_by_node_ids(np.random.choice(G_train.node_ids, size=2000, replace=False)) G_sampled_random_node.summary("Random Node Subgraph") start = time.time() G_sampled = G_train.random_walk(initial_node=None, return_prob=0.15, walk_length=2000, max_node_num=None, max_edge_num=None) end = time.time() # pr.disable() # ps = pstats.Stats(pr).sort_stats('cumulative') # ps.print_stats(10) print('Time spent for random walk:', end - start) G_sampled.summary('Random Walk Subgraph') print("==================================== Graph Sampling Finished ============================================\n") ######################################################## ### testing the correctness of the samping algorithm ### ######################################################## print("Testing the correctness of the samping algorithm...") correct = check_subgraph(G_sampled=G_sampled, G_all=G_train) if correct: print("Correctness Test Passed, G_sampled is a subgraph of G_train!") else: raise RuntimeError("Fail Test!") correct = check_subgraph(G_sampled=G_sampled, G_all=G_all) if correct: print("Correctness Test Passed, G_sampled is a subgraph of G_all!") else: raise RuntimeError("Fail Test!") print("==================================== Sampling Correctness Test Finished! ============================================\n")

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2021-01-28T22:26:05

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#Generates a shifted waterless_model, map, and mask and also shifts the original model by the same amount #inputs are waterless_pdb_file and original_pdb_file import sys import os from iotbx.data_manager import DataManager # load in DataManager dm = DataManager() # Get an initialized version as dm dm.set_overwrite(True) from iotbx.map_model_manager import map_model_manager # load in the map_model_manager mmm=map_model_manager() # get an initialized instance of the map_model_manager no_water_pdb = sys.argv[1] model_filename = sys.argv[2] #create map from waterless model and write new files file_basename = os.path.basename(model_filename).split('.pdb')[0] mmm.generate_map(file_name=no_water_pdb, map_id='new_map', box_cushion=1) mmm.write_model("%s_shifted.pdb" % file_basename) mmm.write_map("%s_shifted_map.mrc" % file_basename) mmm.create_mask_around_atoms() # create binary mask around atoms in the model mmm.apply_mask_to_maps() dm.write_real_map_file(mmm.map_manager() ,filename="%s_shifted_masked.mrc" % file_basename) # masked #shift coords of model_file with solvent model = dm.get_model("%s_shifted.pdb" % file_basename) #shifted and waterless with_water_model = dm.get_model(model_filename) sites_cart = with_water_model.get_sites_cart() # get coordinates of atoms in Angstroms from scitbx.matrix import col # import a tool that handles vectors shift = tuple(i - j for i,j in zip(model.get_sites_cart()[0], with_water_model.get_sites_cart()[0])) sites_cart += col(shift) with_water_model.set_sites_cart(sites_cart) print(with_water_model.get_sites_cart()[0]) # print coordinate of first atom dm.write_model_file(with_water_model, "shifted_with_water.pdb", overwrite=True)

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py

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ensem_cctbx_mapmask.py

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zilani-09/Task_String_with_Python

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dd34a06366df03da881452b10836727d72474a35

/listComprehension.py

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[]

no_license

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ebcbae36d3bc1c43fc563602afd8c0a38b595c92

33e9dc75ec37822bf4c8b744202e9e4c69d2b16b

refs/heads/master

2023-02-21T02:50:06.999599

2020-01-29T08:24:51

null

0

null

a = [2,3,4] d = [i*i for i in a] print(d)

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Python

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listComprehension.py

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Anova07/Competitive-programing

11,862,699,717,639

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/HackerRank/HalloweenSales.py

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permissive

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refs/heads/main

2023-08-12T20:00:37.924824

2021-10-15T06:32:19

417,391,339

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Unlicense

true

2021-10-15T06:29:57

2021-10-15T06:29:56

2021-10-10T10:38:36

2021-10-14T14:32:18

458

0

null

false

import sys import math def howManyGames(p, d, m, s): t_l = 0 if p % d != 0: t_l = p % d else: t_l = d d = -d t_n = ((t_l-p)/d) + 1 t_sum = (t_n*(p+t_l))/2 if s > t_sum: n = ((m-p)/d) + 1 l = p+((n-1)*d) sn = (n*(p+l))/2 return n+((s-sn)/m) else: x1 = abs(int(((-((2*p)-d))+math.sqrt((((2*p)-d)**2)-((4*d)*(-(2*s)))))/(2*d))) x2 = abs(int(((-((2*p)-d))-math.sqrt((((2*p)-d)**2)-((4*d)*(-(2*s)))))/(2*d))) l = p+((x1-1)*d) s1 = (x1*(p+l))/2 l = p+((x2-1)*d) s2 = (x2*(p+l))/2 if s1 <= s: return x1 else: return x2 if __name__ == "__main__": p, d, m, s = raw_input().strip().split(' ') p, d, m, s = [int(p), int(d), int(m), int(s)] answer = howManyGames(p, d, m, s) print answer

UTF-8

Python

false

867

py

21

HalloweenSales.py

21

0.355248

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winksaville/fuchsia

4,827,543,250,562

ccc51e4c0c91ce8853d84c6cb32382eddb916476

5499e8b91353ef910d2514c8a57a80565ba6f05b

/tools/fidl/difl/comparator.py

edc2dd8eb3b8ed3ce10e7a168444951ca62e1b14

[ "BSD-3-Clause" ]

permissive

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refs/heads/master

2022-11-01T11:57:38.343655

2019-11-01T17:06:19

223,695,500

3

2

BSD-3-Clause

false

2022-10-13T13:47:02

2019-11-24T05:08:59

2020-08-07T10:10:53

2022-10-13T13:47:02

428,325

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C++

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# Copyright 2019 The Fuchsia Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. from difl.ir import * import typing __all__ = ['Comparator'] class Comparator: def __init__(self): self.identifier_shapes_match: typing.Dict[str, bool] = {} self.identifier_constraints_match: typing.Dict[str, bool] = {} # notice cycles when comparing shapes & contraints self.shape_match_stack: typing.List[str] = [] self.constraint_match_stack: typing.List[str] = [] def shapes_match(self, before: Type, after: Type) -> bool: ''' Compares two types for shape ''' if isinstance(before, IdentifierType) and \ isinstance(after, IdentifierType) and \ before.identifier == after.identifier and \ not before.is_nullable and not before.is_nullable: if before.identifier not in self.identifier_shapes_match: assert before.identifier not in self.shape_match_stack self.shape_match_stack.append(before.identifier) self.identifier_shapes_match[ before.identifier] = self._shapes_match(before, after) assert before.identifier == self.shape_match_stack.pop() return self.identifier_shapes_match[before.identifier] return self._shapes_match(before, after) def _shapes_match(self, before: Type, after: Type) -> bool: # identical types are identical if before == after and not isinstance(before, IdentifierType): return True # different sized types are incompatible if before.inline_size != after.inline_size: return False ########## Handles, Protocols and Requests # handles are compatible with handles if isinstance(before, (ProtocolIdentifierType, RequestType, HandleType)) and \ isinstance(after, (ProtocolIdentifierType, RequestType, HandleType)): return True ########## Primitives # compare primitives if isinstance(before, PrimitiveType) and \ isinstance(after, PrimitiveType): return before.inline_size == after.inline_size and before.is_float == after.is_float ########## Enums and Bits # compare enums, bits and integer primitives if isinstance(before, (PrimitiveType, EnumIdentifierType, BitsIdentifierType)) and \ isinstance(after, (PrimitiveType, EnumIdentifierType, BitsIdentifierType)): # get the primitive or underlying type b_prim = before if isinstance(before, PrimitiveType) else before.primitive a_prim = after if isinstance(after, PrimitiveType) else after.primitive assert b_prim.inline_size == a_prim.inline_size return b_prim.is_float == a_prim.is_float ########## Arrays if isinstance(before, ArrayType) != isinstance(after, ArrayType): # arrays and not-arrays are incompatible return False if isinstance(before, ArrayType) and isinstance(after, ArrayType): if before.count != after.count: # changing the size is incompatible return False # compatibility is based on the member types return self.shapes_match(before.element_type, after.element_type) ########## Vectors and Strings if isinstance(before, (VectorType, StringType)) and \ isinstance(after, (VectorType, StringType)): return self.shapes_match(before.element_type, after.element_type) ########## Identifiers if isinstance(before, IdentifierType) and \ isinstance(after, IdentifierType): if type(before) != type(after): # identifier types changing is a different shape return False if before.identifier != after.identifier: # TODO: deal with renames? return False if isinstance(before, (XUnionIdentifierType, TableIdentifierType)): # never a shape change return True if before.is_nullable or after.is_nullable: if before.is_nullable != after.is_nullable: if isinstance(before, XUnionIdentifierType): # Nullability is soft change for xunions return True else: # No other types should have nullability assert isinstance( before, (StructIdentifierType, UnionIdentifierType)) # Nullability changes layout for structs and unions return False else: # both nullable, no layout change return True # both not-nullable if isinstance(before, StructIdentifierType) and \ isinstance(after, StructIdentifierType): # TODO: support shape-compatible struct member changes here? like joins & splits? b_members = before.declaration.members a_members = after.declaration.members if len(b_members) != len(a_members): return False if len(b_members) == 0: # all empty structs are the same return True return all( self.shapes_match(b.type, a.type) for b, a in zip(b_members, a_members)) if isinstance(before, UnionIdentifierType) and \ isinstance(after, UnionIdentifierType): b_union_members = before.declaration.members a_union_members = after.declaration.members if len(b_union_members) != len(a_union_members): return False return all( self.shapes_match(b.type, a.type) for b, a in zip(b_union_members, a_union_members)) raise NotImplementedError( "Don't know how to compare shape for %r (%r) and %r (%r)" % (type(before), before, type(after), after)) def constraints_match(self, before: Type, after: Type) -> bool: ''' Compares two types for constraints ''' if isinstance(before, IdentifierType) and \ isinstance(after, IdentifierType) and \ before.identifier == after.identifier: if before.identifier not in self.identifier_constraints_match: if before.identifier in self.constraint_match_stack: # hit a cycle return True self.constraint_match_stack.append(before.identifier) self.identifier_constraints_match[before.identifier] = \ self._constraints_match(before, after) assert before.identifier == self.constraint_match_stack.pop() return self.identifier_constraints_match[before.identifier] return self._constraints_match(before, after) def _constraints_match(self, before: Type, after: Type) -> bool: if not self.shapes_match(before, after): # shape is the ultimate constraint return False if type(before) != type(after): # changing the type of the type breaks constraints return False ########## Primitives if isinstance(before, PrimitiveType) and \ isinstance(after, PrimitiveType): return before.subtype == after.subtype ########## Strings if isinstance(before, StringType) and isinstance(after, StringType): return before.limit == after.limit and \ before.is_nullable == after.is_nullable ########## Vectors if isinstance(before, VectorType) and isinstance(after, VectorType): return before.limit == after.limit and \ before.is_nullable == after.is_nullable and \ self.constraints_match(before.element_type, after.element_type) ########## Arrays if isinstance(before, ArrayType) and isinstance(after, ArrayType): assert before.count == after.count return self.constraints_match(before.element_type, after.element_type) ########## Handles if isinstance(before, HandleType) and isinstance(after, HandleType): return before.handle_type == after.handle_type and \ before.is_nullable == after.is_nullable if isinstance(before, NullableType) and \ isinstance(after, NullableType): # nullability changes are constraints changes if before.is_nullable != after.is_nullable: return False if isinstance(before, RequestType) and isinstance(after, RequestType): return before.protocol == after.protocol if isinstance(before, ProtocolIdentifierType) and \ isinstance(after, ProtocolIdentifierType): return before.identifier == after.identifier if isinstance(before, StructIdentifierType) and \ isinstance(after, StructIdentifierType): b_struct_members = before.declaration.members a_struct_members = after.declaration.members assert len(b_struct_members) == len(a_struct_members) if len(b_struct_members) == 0: # all empty structs are the same return True return all( self.constraints_match(b.type, a.type) for b, a in zip(b_struct_members, a_struct_members)) if isinstance(before, TableIdentifierType) and \ isinstance(after, TableIdentifierType): b_table_members: typing.Dict[int, TableMember] = { m.ordinal: m for m in before.declaration.members } a_table_members: typing.Dict[int, TableMember] = { m.ordinal: m for m in after.declaration.members } for ordinal, b_member in b_table_members.items(): a_member = a_table_members.get(ordinal) if a_member is None: # leaving out an ordinal breaks constraints return False if b_member.reserved or a_member.reserved: # changing to/from reserved is fine continue if not self.constraints_match(b_member.type, a_member.type): return False # it's fine if more members were added to after return True if isinstance(before, UnionIdentifierType) and \ isinstance(after, UnionIdentifierType): b_union_members = before.declaration.members a_union_members = after.declaration.members if len(b_union_members) != len(a_union_members): return False # empty unions are illegal assert len(b_union_members) != 0 return all( self.constraints_match(b.type, a.type) for b, a in zip(b_union_members, a_union_members)) if isinstance(before, XUnionIdentifierType) and \ isinstance(after, XUnionIdentifierType): # Note: this is applying a strict-mode interpretation b_xunion_members = before.declaration.members a_xunion_members = after.declaration.members if len(b_xunion_members) != len(a_xunion_members): return False # empty xunions are illegal assert len(b_xunion_members) > 0 # members by ordinal b_members = {m.ordinal: m for m in b_xunion_members} a_members = {m.ordinal: m for m in a_xunion_members} # they both have the same set of ordinals if frozenset(b_members.keys()) != frozenset(a_members.keys()): return False return all( self.constraints_match(b_members[o].type, a_members[o].type) for o in b_members.keys()) if isinstance(before, EnumIdentifierType) and \ isinstance(after, EnumIdentifierType): # this is the strict-mode interpretation of enums assert len(before.declaration.members) == \ len(after.declaration.members) before_member_values = set( m.value for m in before.declaration.members) after_member_values = set( m.value for m in after.declaration.members) return before_member_values == after_member_values if isinstance(before, BitsIdentifierType) and \ isinstance(after, BitsIdentifierType): # this is the strict-mode interpretation of bits return before.declaration.mask == after.declaration.mask raise NotImplementedError( "Don't know how to compare constraints for %r (%r) and %r (%r)" % (type(before), before, type(after), after))

UTF-8

Python

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topatlant/AdventOfCode-python

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/y2020/test/test_day05.py

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refs/heads/master

2023-01-20T23:48:36.331972

2022-12-22T11:02:48

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from y2020.day05 import * def test_get_row_col(): assert extract_row_col("FBFBBFFRLR") == (44, 5) assert extract_row_col("BFFFBBFRRR") == (70, 7) assert extract_row_col("FFFBBBFRRR") == (14, 7) assert extract_row_col("BBFFBBFRLL") == (102, 4) def test_get_seat_id(): assert get_seat_id("FBFBBFFRLR") == 357 assert get_seat_id("BFFFBBFRRR") == 567 assert get_seat_id("FFFBBBFRRR") == 119 assert get_seat_id("BBFFBBFRLL") == 820

UTF-8

Python

false

463

py

82

test_day05.py

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0.632829

0.565875

0

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52

JabezThian/System_Security

5,111,011,086,699

c0cb1dbe0789282622744876e9b771f09d34abc7

365a3bb8cbbaf38fd204bdb06a22336bc1ba0ae6

/Resend.py

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[]

no_license

https://github.com/JabezThian/System_Security

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dbcf9210583ee79d06495655e678584dc3bbab64

refs/heads/main

2023-07-14T09:29:20.053712

2021-08-21T06:42:48

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null

class Resend: def __init__(self, nric, email, age, gender, nationality, language, phoneno, quali, industry): self.__nric = nric self.__email = email self.__age = age self.__gender = gender self.__nationality = nationality self.__language = language self.__phoneno = phoneno self.__quali = quali self.__industry = industry def get_nric(self): return self.__nric def get_email(self): return self.__email def get_age(self): return self.__age def get_gender(self): return self.__gender def get_nationality(self): return self.__nationality def get_language(self): return self.__language def get_phoneno(self): return self.__phoneno def get_quali(self): return self.__quali def get_industry(self): return self.__industry def set_nric(self, nric): self.__nric = nric def set_email(self, email): self.__email = email def set_gender(self, gender): self.__gender = gender def set_nationality(self, nationality): self.__nationality = nationality def set_langauge(self, language): self.__language = language def set_phoneno(self, phoneno): self.__phoneno = phoneno def set_quali(self, quali): self.__quali = quali def set_industry(self, industry): self.__industry = industry

UTF-8

Python

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py

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Resend.py

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0.582877

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SaileshShahri/ecommerce-site

19,138,374,310,482

1fe6c2f988d6b1b4854faf6cf79ebadde10fa58f

55c94b4dd1ead177b037939df4f8ff13ee1eff8f

/order/models.py

eee2420d1524116693537215163a249515445bfc

[]

no_license

https://github.com/SaileshShahri/ecommerce-site

2062205b54a4e340021e097989b74dfcdf15b6bc

f293af9525b2025a90855aa3098b9f88c66b2a38

refs/heads/master

2022-07-18T23:58:20.764796

2020-05-18T11:55:39

264,920,445

0

null

from django.conf import settings from django.db import models from django.urls import reverse User = settings.AUTH_USER_MODEL from django.utils import timezone from product.models import Product, ProductVariant from address.models import Address # from payment.models import Payment from django.db.models.signals import pre_save, post_save from main.utils import unique_order_id_generator, unique_key_generator PAYMENT_CHOICES = ( ("Pay on Delivery", "Pay on Delivery"), ("Debit Card", "Debit Card"), ("Credit Card", "Credit Card"), ("Net Banking", "Net Banking"), ) class Order(models.Model): user = models.ForeignKey(User, on_delete=models.CASCADE) address = models.ForeignKey(Address, on_delete=models.CASCADE) payment = models.CharField(max_length=50, choices=PAYMENT_CHOICES) order_date = models.DateTimeField(auto_now_add=True) order_id = models.SlugField(null=True, blank=True, unique=True) confirmed = models.BooleanField(default=False) # Seller confirmation class Meta: ordering = ["-order_date"] def get_absolute_url(self): return reverse('order-detail', kwargs={"order_id": self.order_id}) def order_pre_save_receiver(sender, instance, *args, **kwargs): if not instance.order_id: instance.order_id = unique_order_id_generator(instance) pre_save.connect(order_pre_save_receiver, sender=Order) QUANTITY_CHOICES = ( ("1", "1"), ("2", "2"), ("3", "3"), ("4", "4"), ("5", "5"), ("6", "6"), ("7", "7"), ("8", "8"), ("9", "9"), ("10", "10"), ) class OrderProduct(models.Model): order = models.ForeignKey(Order, on_delete=models.CASCADE) product = models.ForeignKey(Product, on_delete=models.CASCADE) variant = models.ForeignKey(ProductVariant, on_delete=models.CASCADE, null=True, blank=True) quantity = models.CharField(default="1", choices=QUANTITY_CHOICES, max_length=2) slug = models.SlugField(null=True, blank=True, unique=True) def get_seller_absolute_url(self): return reverse('seller-order-detail', kwargs={"slug": self.slug}) def order_product_pre_save_receiver(sender, instance, *args, **kwargs): if not instance.slug: instance.slug = unique_key_generator(instance) pre_save.connect(order_product_pre_save_receiver, sender=OrderProduct)

UTF-8

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models.py

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0.6973

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mhgharieb/MILP_Division_Property

1,434,519,083,741

138542da5d7929d76e1e52fa45bab02c7f22a019

3b13edf19c244501fc1d0718aecec69c9019ec4a

/algorithm2/main.py

fcb6a7700ce6947de8fcf42ad537924185c71457

[]

no_license

https://github.com/mhgharieb/MILP_Division_Property

5a780093c972d9b07e1358588914cd3d9aaa4fdc

d1eeebb04e4f2c1959615c15dc683a08786a86e2

refs/heads/master

2021-04-29T15:09:06.137941

2018-02-16T20:37:16

121,791,898

0

1

null

true

2018-02-16T19:31:38

2017-08-08T01:10:04

2016-12-13T01:55:21

163

0

null

false

null

# Algorithm 2 presented in paper "Applyint MILP Method to Searching Integral # Distinguishers based on Division Property for 6 Lightweight Block Ciphers" # Regarding to the paper, please refer to https://eprint.iacr.org/2016/857 # For more information, feedback or questions, pleast contact at xiangzejun@iie.ac.cn # Implemented by Xiang Zejun, State Key Laboratory of Information Security, # Institute Of Information Engineering, CAS from sbox import Sbox if __name__ == "__main__": # PRESENT Sbox cipher = "PRESENT" sbox = [0xc, 0x5, 0x6, 0xb, 0x9, 0x0, 0xa, 0xd, 0x3, 0xe, 0xf, 0x8, 0x4, 0x7, 0x1, 0x2] present = Sbox(sbox) filename = cipher + "_DivisionTrails.txt" present.PrintfDivisionTrails(filename)

UTF-8

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main.py

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SeanZicari/sfxmanager

10,883,447,149,515

b1e275c7c19eb5612930f308f0c6a4d4703ce43e

75635a3621ff9e14ad4e2162e3597d497d19197d

/src/soundserver/server.py

7df2aec68c71ed6ea12cce40e6cf42f8e65f41ef

[]

no_license

https://github.com/SeanZicari/sfxmanager

143e4adfc290fc647a5c9c517010450396846575

6074a1a8c2879127645e0558142729bc87583d5a

refs/heads/master

2016-09-06T12:54:15.698338

2015-04-18T21:48:21

34,175,049

0

null

import sys import zmq from zmq.eventloop import IOLoop from zmq.eventloop.zmqstream import ZMQStream CONTROL_PORT = 5600 class SoundServer(object): def __init__(self): self._context = zmq.Context() self._socket = self._context.socket(zmq.REP) self._socket.bind('tcp://127.0.0.1:{0}'.format(CONTROL_PORT)) self._stream = ZMQStream(self._socket) self._stream.on_recv(self._handle_msg) def start(self): IOLoop.instance().start() def _handle_msg(self, msg): method = '_handler_{0}'.format(msg[0].decode("utf-8")) try: print("Trying method {0}".format(method)) getattr(self, method)() except AttributeError: sys.exit(1) def _handler_hi(self): self._socket.send_string('sup?') def _handler_exit(self): pass if __name__ == '__main__': SoundServer().start()

UTF-8

Python

false

911

py

10

server.py

4

0.588364

0.570801

0

40

21.775

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PatrickDRusk/pdrtools

10,514,079,980,833

e8948b7f67e72e26f23360a301916bf8dc25803e

27982e0aabcd947bc7f26171c1447b16a149bd53

/pdrtools/slim_price_data_reader.py

41e87db2838b92576644d386ffc09267da04c0a4

[]

no_license

https://github.com/PatrickDRusk/pdrtools

9db3c904b2cf4d0e1ef2981204191e27c0fc69ad

958d42fce4d788b2c97611155880001d7755f237

refs/heads/master

2021-01-10T16:03:13.796790

2020-02-26T20:50:16

55,615,425

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null

#! /usr/bin/env python """ Lambda functions for the slim_price_data_reader. To deploy: zip /tmp/slim_price_data_reader.zip slim_price_data_reader.py aws lambda create-function --function-name pdr_price_data --runtime python2.7 \ --role arn:aws:iam::528461152743:role/TradingOpsLambda --handler slim_price_data_reader.main \ --zip-file fileb:///tmp/slim_price_data_reader.zip --publish To delete the functions: for name in string_upcase string_reverse string_concat; do aws lambda delete-function --function-name $name done """ import cPickle import os import time import boto3 current_millis = lambda: int(round(time.time() * 1000)) COMDTYS = ( "CO_COMDTY", ) MAQUILAS = ( "CO_COMDTY:FRONT:V1", ) BUCKET = None PREFIX = 'pdr/blobz' DO_WRITES = False WRITE_CONTRACT_DATA = True RETURN_STRS = [] def read_blob(sec_name, contract_name, category, blob_name): path = os.path.join(*filter(None, [PREFIX, sec_name, category, contract_name, blob_name])) pstr = BUCKET.Object(path).get().get('Body').read() data = cPickle.loads(pstr) return data def log_millis(millis, pattern): delta = current_millis() - millis print(pattern + str(delta)) RETURN_STRS.append(pattern + str(delta)) return current_millis() def read_symbol(sec_name): millis = current_millis() md_dict = read_blob(sec_name, None, None, 'metadata') millis = log_millis(millis, "Time to read %s metadata: " % sec_name) contract_names = sorted(md_dict['expiry_map'].keys()) for contract_name in contract_names: # noinspection PyUnusedLocal contract_df = read_blob(sec_name, contract_name, "DAILY", 'close') log_millis(millis, "Time to read all %s contract prices: " % sec_name) def read_symbol_big(sec_name): millis = current_millis() md_dict = read_blob(sec_name, None, None, 'metadata') millis = log_millis(millis, "Time to read %s metadata: " % sec_name) contract_names = sorted(md_dict['expiry_map'].keys()) for contract_name in contract_names: # noinspection PyUnusedLocal contract_df = read_blob(sec_name, contract_name, "DAILY", 'all') log_millis(millis, "Time to read all %s contract prices (big): " % sec_name) def read_maquila(sec_name, contract_name=None, col='return'): millis = current_millis() data = read_blob(sec_name, contract_name, "DAILY", col) log_millis(millis, "Time to read %s returns: " % sec_name) return data def main(): global BUCKET s3 = boto3.resource('s3') BUCKET = s3.Bucket('cm-engineers') for sec_name in COMDTYS: read_blob(sec_name, None, None, 'metadata') # to prime the timings read_maquila(sec_name, "0000", col='all') read_symbol(sec_name) read_symbol_big(sec_name) for maquila_key in MAQUILAS: read_maquila(maquila_key) return RETURN_STRS if __name__ == '__main__': main()

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slim_price_data_reader.py

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matt-gardner/pnp

16,063,177,692,535

6721bd40211d46d78d2e3e2318e9ffd39c08ad27

a897833e9f71bb03f7117fc5826eb0d48f1a2a52

/experiments/dqa/scripts/generate_diagram_feats.py

412c9fc07e353120568e60da6e31b46529a97f42

[ "Apache-2.0" ]

permissive

https://github.com/matt-gardner/pnp

95824d0dd577ad4a703d9aa70a936263199552de

c6f52697763ec26b614e5d3ca3fad140b4ccad53

refs/heads/master

2021-01-23T06:35:15.006410

2017-03-21T23:39:20

86,379,969

0

null

true

2017-03-27T20:17:13

2017-03-19T13:56:17

2017-03-27T17:05:13

5,887

0

null

#!/usr/bin/python # Generate random feature vectors for each diagram part import sys import ujson as json import random diagram_label_file = sys.argv[1] out_file = sys.argv[2] def label_to_feature_vector(label, xy, width, height): DIMS = 2 vec = [0.0] * DIMS vec[0] = float(xy[0]) / width vec[1] = float(xy[1]) / height return vec # Random with a high-scoring element in a label-specific index. ''' h = label.__hash__() % (DIMS / 2) vec[h] = 3.0 for i in xrange(len(vec)): vec[i] += random.gauss(0.0, 1.0) return vec ''' # One-hot at a label-specific index. ''' h = label.__hash__() % DIMS vec[h] = 1.0 return vec ''' # Random around a mean per label ''' for i in xrange(len(vec)): mean_random = random.Random() mean_random.seed(label.__hash__() * i) mean = mean_random.uniform(-1, 1) vec[i] = random.gauss(mean, 1.0) return vec ''' # Completely random ''' for i in xrange(len(vec)): vec[i] = random.gauss(0.0, 1.0) return vec ''' image_points = {} with open(diagram_label_file, 'r') as f: for line in f: j = json.loads(line) image_id = j["imageId"] width = j["width"] height = j["height"] if not image_id in image_points: image_points[image_id] = {} # print image_id for p in j["points"]: xy = tuple(p["xy"]) label = p["label"] vec = label_to_feature_vector(label, xy, width, height) # print " ", xy, label # print " ", vec image_points[image_id][xy] = vec # Convert dict format to something jsonable image_points_json = [] for image_id in image_points.iterkeys(): point_vectors = [] for point in image_points[image_id]: point_dict = {} point_dict["xy"] = list(point) point_dict["vec"] = image_points[image_id][point] point_vectors.append(point_dict) image_json = {"imageId" : image_id, "points" : point_vectors} image_points_json.append(image_json) with open(out_file, 'wb') as f: for j in image_points_json: print >> f, json.dumps(j)

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Greeshma-Prakasan/Manage_Docker

1,760,936,592,107

73cedd1720903ef906d60687cc4e9d9783d3b879

4e076520ea85693c168758625d8a9617624e7a00

/manage_docker.py

567239a1c7ae4d1fa19ba7ac128e9c0697533751

[]

no_license

https://github.com/Greeshma-Prakasan/Manage_Docker

61f64038e1f9617550ddef7c31c0e04dda9a4c1d

23da875555b56e83e11758e1699fd300d3878a7c

refs/heads/main

2023-08-04T07:48:17.768828

2021-09-20T17:54:49

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import os from rich.console import Console console = Console() def stat_container(): os.system("docker container stats") def download_new_image(): img = input("\tEnter the name of Image : ") os.system(f'docker pull {img}') def run_container(): img = input("\tEnter the image name : ") container = input("\tEnter the container name : ") os.system(f'docker run --name {container} {img}') console.print("\tContainer is running.........",style="bold blue") def del_container(): container = input("\tEnter the container name : ") os.system(f'docker rm {container}') console.print("\tContainer successfully deleted.........",style="bold blue") def nw_details(): res = os.popen("docker network inspect bridge").read() console.print(res,style="bold blue") def modify_nw(): res = os.popen("docker network ls").read() console.print(f"Available networks\n\n{res}",style="bold blue") container = input("Enter the container name : ") os.system(f"docker network disconnect bridge {container}") console.print(f"{container} disconnected...........",style="bold blue") nw = input("Enter the new network name : ") ip = input("Enter the ip : ") os.system(f"sudo docker network create -d bridge --subnet={ip} {nw}") console.print("Network Created...................") os.system(f"docker network connect {nw} {container}") console.print(f"Container connected to new network {nw}") def menu(): console.print("1. Status of containers\n2. Download new Image\n3. Run container\n4. Delete Container\n5. Network details of container\n6. Modify Network details of contaniner\n7. Exit",style="bold yellow") while True: menu() c = int(input("Enter the choice : ")) if c==1: stat_container() elif c==2: download_new_image() elif c==3: run_container() elif c==4: del_container() elif c==5: nw_details() elif c==6: modify_nw() elif c==7: break else: console.print("\tInvalid Choice",style="bold blue")

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manage_docker.py

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209

oksana-yashan/MOPE-5

9,062,381,015,748

8135944ea1a238b22a2465fc63114df9c79e46a8

9cad2261b2f4a2109db13ee8ff680b20ff1a7159

/Lab5.py

c29374b99715553c3be355ab344f6ab4c179a4bb

[]

no_license

https://github.com/oksana-yashan/MOPE-5

1e49e3d475a3104bbf89c4bf66a9a7ab17894a76

a6bfb01c4614dc81c317684aea02f84cf135254d

refs/heads/master

2022-04-25T19:03:30.586509

2020-04-24T15:12:18

257,075,083

0

null

import random import numpy as np import math from functools import reduce from itertools import compress import scipy from scipy.stats import f,t x1min, x2min, x3min = -5, -9, -3 x1max, x2max, x3max = 5, 3, 5 x_min = (x1min + x2min + x3min) / 3 # mean of x1min, x2min, x3min x_max = (x1max + x2max + x3max) / 3 x0_i = [np.average(x1min+x1max),np.average(x2min+x2max),np.average(x3min+x3max)] y_min = round(200 + x_min) y_max = round(200 + x_max) m = 3 N = 8 # from Lab3 without interaction counter = 0 with_interaction = False check = True while (check): # from Lab3 matrix = np.ndarray(shape=(4, 7), dtype=float) matrix[0][0], matrix[1][0], matrix[2][0], matrix[3][0] = 1, 1, 1, 1 matrix[0][1], matrix[1][1], matrix[2][1], matrix[3][1] = -1, -1, 1, 1 matrix[0][2], matrix[1][2], matrix[2][2], matrix[3][2] = -1, 1, -1, 1 matrix[0][3], matrix[1][3], matrix[2][3], matrix[3][3] = -1, 1, 1, -1 matrix_n = np.ndarray(shape=(4, 6), dtype=float) matrix_n[0][0], matrix_n[1][0], matrix_n[2][0], matrix_n[3][0] = x1min, x1min, x1max, x1max matrix_n[0][1], matrix_n[1][1], matrix_n[2][1], matrix_n[3][1] = x2min, x2max, x1min, x2max matrix_n[0][2], matrix_n[1][2], matrix_n[2][2], matrix_n[3][2] = x3min, x3max, x3max, x3min mY_list = [] for i in range(4): for j in range(3, 6): r = np.random.randint(y_min, y_max) matrix_n[i][j], matrix[i][j + 1] = r, r mY_list.append(((matrix_n[i][3] + matrix_n[i][4] + matrix_n[i][5]) / m).__round__(4)) mx1 = np.sum(matrix_n, axis=0)[0] / 4 mx2 = np.sum(matrix_n, axis=0)[1] / 4 mx3 = np.sum(matrix_n, axis=0)[2] / 4 my = (sum(mY_list) / len(mY_list)).__round__(2) a1 = (matrix_n[0][0] * mY_list[0] + matrix_n[1][0] * mY_list[1] + matrix_n[2][0] * mY_list[2] + matrix_n[3][0] * mY_list[3]) / 4 a2 = (matrix_n[0][1] * mY_list[0] + matrix_n[1][1] * mY_list[1] + matrix_n[2][1] * mY_list[2] + matrix_n[3][1] * mY_list[3]) / 4 a3 = (matrix_n[0][2] * mY_list[0] + matrix_n[1][2] * mY_list[1] + matrix_n[2][2] * mY_list[2] + matrix_n[3][2] * mY_list[3]) / 4 a11 = (matrix_n[0][0] ** 2 + matrix_n[1][0] ** 2 + matrix_n[2][0] ** 2 + matrix_n[3][0] ** 2) / 4 a22 = (matrix_n[0][1] ** 2 + matrix_n[1][1] ** 2 + matrix_n[2][1] ** 2 + matrix_n[3][1] ** 2) / 4 a33 = (matrix_n[0][2] ** 2 + matrix_n[1][2] ** 2 + matrix_n[2][2] ** 2 + matrix_n[3][2] ** 2) / 4 a12 = a21 = (matrix_n[0][0] * matrix_n[0][1] + matrix_n[1][0] * matrix_n[1][1] + matrix_n[2][0] * matrix_n[2][1] + matrix_n[3][0] * matrix_n[3][1]) / 4 a13 = a31 = (matrix_n[0][0] * matrix_n[0][2] + matrix_n[1][0] * matrix_n[1][2] + matrix_n[2][0] * matrix_n[2][2] + matrix_n[3][0] * matrix_n[3][2]) / 4 a23 = a32 = (matrix_n[0][1] * matrix_n[0][2] + matrix_n[1][1] * matrix_n[1][2] + matrix_n[2][1] * matrix_n[2][2] + matrix_n[3][1] * matrix_n[3][2]) / 4 b0 = np.linalg.det( np.array([[my, mx1, mx2, mx3], [a1, a11, a12, a13], [a2, a12, a22, a32], [a3, a13, a23, a33]])) / np.linalg.det( np.array([[1, mx1, mx2, mx3], [mx1, a11, a12, a13], [mx2, a12, a22, a32], [mx3, a13, a23, a33]])) b1 = np.linalg.det( np.array([[1, my, mx2, mx3], [mx1, a1, a12, a13], [mx2, a2, a22, a32], [mx3, a3, a23, a33]])) / np.linalg.det( np.array([[1, mx1, mx2, mx3], [mx1, a11, a12, a13], [mx2, a12, a22, a32], [mx3, a13, a23, a33]])) b2 = np.linalg.det( np.array([[1, mx1, my, mx3], [mx1, a11, a1, a13], [mx2, a12, a2, a32], [mx3, a13, a3, a33]])) / np.linalg.det( np.array([[1, mx1, mx2, mx3], [mx1, a11, a12, a13], [mx2, a12, a22, a32], [mx3, a13, a23, a33]])) b3 = np.linalg.det( np.array([[1, mx1, mx2, my], [mx1, a11, a12, a1], [mx2, a12, a22, a2], [mx3, a13, a23, a3]])) / np.linalg.det( np.array([[1, mx1, mx2, mx3], [mx1, a11, a12, a13], [mx2, a12, a22, a32], [mx3, a13, a23, a33]])) print(" Матриця планування") print(" x1 x2 x3 y1 y2 y3 ") for i in range(3): for j in range(6): print("{:>6.1f}".format(matrix_n[i][j]), end=" ") print("\t") print("\n", "y = %.2f + %.2f * x1 + %.2f * x2+ %.2f * x3" % (b0, b1, b2, b3)) print("\nПеревірка:") print((b0 + b1 * matrix_n[0][0] + b2 * matrix_n[0][1] + b3 * matrix_n[0][2]).__round__(3), " ", (b0 + b1 * matrix_n[1][0] + b2 * matrix_n[1][1] + b3 * matrix_n[1][2]).__round__(3), " ", (b0 + b1 * matrix_n[2][0] + b2 * matrix_n[2][1] + b3 * matrix_n[2][2]).__round__(3), " ", (b0 + b1 * matrix_n[3][0] + b2 * matrix_n[3][1] + b3 * +matrix_n[3][2]).__round__(3)) print(mY_list) # Перевірка за Кохреном: s2_y1 = ((matrix[0][4] - mY_list[0]) ** 2 + (matrix[0][5] - mY_list[0]) ** 2 + (matrix[0][6] - mY_list[0]) ** 2) / 3 s2_y2 = ((matrix[1][4] - mY_list[1]) ** 2 + (matrix[1][5] - mY_list[1]) ** 2 + (matrix[1][6] - mY_list[1]) ** 2) / 3 s2_y3 = ((matrix[2][4] - mY_list[2]) ** 2 + (matrix[2][5] - mY_list[2]) ** 2 + (matrix[2][6] - mY_list[2]) ** 2) / 3 s2_y4 = ((matrix[3][4] - mY_list[3]) ** 2 + (matrix[3][5] - mY_list[3]) ** 2 + (matrix[3][6] - mY_list[3]) ** 2) / 3 f1 = m - 1 f2 = N p = 0.95 q = 1 - p Gp = max(s2_y1, s2_y2, s2_y3, s2_y4) / (s2_y1 + s2_y2 + s2_y3 + s2_y4) def cohren_value(f2, f1, q): f2 += 1 partResult1 = q / (f2 - 1) params = [partResult1, f1, (f2 - 1 - 1) * f2] fisher = scipy.stats.f.isf(*params) result = fisher / (fisher + (f2 - 1 - 1)) return result.__round__(3) Gt = cohren_value(f2, f1, q) if (Gp < Gt): print(" Отже, дисперсія однорідна") check = False else: print(" Дисперсія неоднорідна --> m+1") m += 1 # Критерій Стьюдента s2_b = (s2_y1 + s2_y2 + s2_y3 + s2_y4) / 4 s2_bb = s2_b / (4 * m) s_bb = np.sqrt(s2_bb) bb0 = (mY_list[0] * matrix[0][0] + mY_list[1] * matrix[1][0] + mY_list[2] * matrix[2][0] + mY_list[3] * matrix[3][ 0]) / N bb1 = (mY_list[0] * matrix[0][1] + mY_list[1] * matrix[1][1] + mY_list[2] * matrix[2][1] + mY_list[3] * matrix[3][ 1]) / N bb2 = (mY_list[0] * matrix[0][2] + mY_list[1] * matrix[1][2] + mY_list[2] * matrix[2][2] + mY_list[3] * matrix[3][ 2]) / N bb3 = (mY_list[0] * matrix[0][3] + mY_list[1] * matrix[1][3] + mY_list[2] * matrix[2][3] + mY_list[3] * matrix[3][ 3]) / N t = [abs(bb0) / s_bb, abs(bb1) / s_bb, abs(bb2) / s_bb, abs(bb3) / s_bb] f3 = (m - 1) * N # t_t = 2.306 # для значення f3 = 8, t табличне = 2,306 t_t = scipy.stats.t.ppf((1 + (1 - q)) / 2, f3) print("\nt табличне:", t_t) if t[0] < t_t: b0 = 0 print("t0<t_t; b0=0") if t[1] < t_t: b1 = 0 print("t1<t_t; b1=0") if t[2] < t_t: b2 = 0 print("t2<t_t; b2=0") if t[3] < t_t: b3 = 0 print("t3<t_t; b3=0") print("\n", "y = %.2f + %.2f * x1 + %.2f * x2+ %.2f * x3" % (b0, b1, b2, b3)) y1_exp = b0 + b1 * matrix_n[0][0] + b2 * matrix_n[0][1] + b3 * matrix_n[0][2] y2_exp = b0 + b1 * matrix_n[1][0] + b2 * matrix_n[1][1] + b3 * matrix_n[1][2] y3_exp = b0 + b1 * matrix_n[2][0] + b2 * matrix_n[2][1] + b3 * matrix_n[2][2] y4_exp = b0 + b1 * matrix_n[3][0] + b2 * matrix_n[3][1] + b3 * matrix_n[3][2] print(f"y1_exp = {b0:.2f}{b1:+.2f}*x11{b2:+.2f}*x12{b3:+.2f}*x13 " f"= {y1_exp:.2f}") print(f"y2_exp = {b0:.2f}{b1:+.2f}*x21{b2:+.2f}*x22{b3:+.2f}*x23" f" = {y2_exp:.2f}") print(f"y3_exp = {b0:.2f}{b1:+.2f}*x31{b2:+.2f}*x32{b3:+.2f}*x33 " f"= {y3_exp:.2f}") print(f"y4_exp = {b0:.2f}{b1:+.2f}*x41{b2:+.2f}*x42{b3:+.2f}*x43" f" = {y4_exp:.2f}") # Критерій Фішера d = 2 f4 = N - d s2_ad = ((y1_exp - mY_list[0]) ** 2 + (y2_exp - mY_list[1]) ** 2 + (y3_exp - mY_list[2]) ** 2 + ( y4_exp - mY_list[3]) ** 2) / (m / N - d) Fp = s2_ad / s2_b Ft = scipy.stats.f.ppf(1 - q, f4, f3) print("\nFp:", Fp) print("Ft:", Ft) if Fp < Ft: print("Рівняння регресії не адекватно оригіналу при q = 0,05",'\n\n') with_interaction = True print("Рівняння регресії з врахуванням ефекту взаємодії:") else: print("Рівняння регресії адекватно оригіналу при q = 0,05") # Equation with intersection(Lab4) while (with_interaction): m = 3 N = 8 x0 = [1 for i in range(N)] # x1 x2 x3 x12 x13 x23 x123 norm_x_table = [[-1, -1, -1, +1, +1, +1, -1], [-1, +1, +1, -1, -1, +1, -1], [+1, -1, +1, -1, +1, -1, -1], [+1, +1, -1, +1, -1, -1, -1], [-1, -1, +1, +1, -1, -1, +1], [-1, +1, -1, -1, +1, -1, +1], [+1, -1, -1, -1, -1, +1, +1], [+1, +1, +1, +1, +1, +1, +1]] # 1 2 3 12 13 23 123 x_table = [[x1min, x2min, x3min, x1min * x2min, x1min * x3min, x2min * x3min, x1min * x2min * x3min], [x1min, x2max, x3max, x1min * x2max, x1min * x3max, x2max * x3max, x1min * x2max * x3max], [x1max, x2min, x3max, x1max * x2min, x1max * x3max, x2min * x3max, x1max * x2min * x3max], [x1max, x2max, x3min, x1max * x2max, x1max * x3min, x2max * x3min, x1max * x2max * x3min], [x1min, x2min, x3max, x1min * x2min, x1min * x3max, x2min * x3max, x1min * x2min * x3max], [x1min, x2max, x3min, x1min * x2max, x1min * x3min, x2max * x3min, x1min * x2max * x3min], [x1max, x2min, x3min, x1max * x2min, x1max * x3min, x2min * x3min, x1max * x2min * x3min], [x1max, x2max, x3max, x1max * x2max, x1max * x3max, x2max * x3max, x1max * x2max * x3max]] y_arr = [[random.randint(y_min, y_max) for j in range(m)] for i in range(N)] # i rows and j columns print(y_arr) # arrays with x1(i), x2(i),x3(i) x1i = np.array([x_table[i][0] for i in range(8)]) x2i = np.array([x_table[i][1] for i in range(8)]) x3i = np.array([x_table[i][2] for i in range(8)]) yi = np.array([np.average(i) for i in y_arr]) # average for each i row in y_arr def m_ij(*arrays): return np.average(reduce(lambda el_1, el_2: el_1 + el_2, arrays)) # reduce: sums all el in given arrays coefs = [[N, m_ij(x1i), m_ij(x2i), m_ij(x3i), m_ij(x1i * x2i), m_ij(x1i * x3i), m_ij(x2i * x3i), m_ij(x1i * x2i * x3i)], [m_ij(x1i), m_ij(x1i ** 2), m_ij(x1i * x2i), m_ij(x1i * x3i), m_ij(x1i ** 2 * x2i), m_ij(x1i ** 2 * x3i), m_ij(x1i * x2i * x3i), m_ij(x1i ** 2 * x2i * x3i)], [m_ij(x2i), m_ij(x1i * x2i), m_ij(x2i ** 2), m_ij(x2i * x3i), m_ij(x1i * x2i ** 2), m_ij(x1i * x2i * x3i), m_ij(x2i ** 2 * x3i), m_ij(x1i * x2i ** 2 * x3i)], [m_ij(x3i), m_ij(x1i * x3i), m_ij(x2i * x3i), m_ij(x3i ** 2), m_ij(x1i * x2i * x3i), m_ij(x1i * x3i ** 2), m_ij(x2i * x3i ** 2), m_ij(x1i * x2i * x3i ** 2)], [m_ij(x1i * x2i), m_ij(x1i ** 2 * x2i), m_ij(x1i * x2i ** 2), m_ij(x1i * x2i * x3i), m_ij(x1i ** 2 * x2i ** 2), m_ij(x1i ** 2 * x2i * x3i), m_ij(x1i * x2i ** 2 * x3i), m_ij(x1i ** 2 * x2i ** 2 * x3i)], [m_ij(x1i * x3i), m_ij(x1i ** 2 * x3i), m_ij(x1i * x2i * x3i), m_ij(x1i * x3i ** 2), m_ij(x1i ** 2 * x2i * x3i), m_ij(x1i ** 2 * x3i ** 2), m_ij(x1i * x2i * x3i ** 2), m_ij(x1i ** 2 * x2i * x3i ** 2)], [m_ij(x2i * x3i), m_ij(x1i * x2i * x3i), m_ij(x2i ** 2 * x3i), m_ij(x2i * x3i ** 2), m_ij(x1i * x2i ** 2 * x3i), m_ij(x1i * x2i * x3i ** 2), m_ij(x2i ** 2 * x3i ** 2), m_ij(x1i * x2i ** 2 * x3i ** 2)], [m_ij(x1i * x2i * x3i), m_ij(x1i ** 2 * x2i * x3i), m_ij(x1i * x2i ** 2 * x3i), m_ij(x1i * x2i * x3i ** 2), m_ij(x1i ** 2 * x2i ** 2 * x3i), m_ij(x1i ** 2 * x2i * x3i ** 2), m_ij(x1i * x2i ** 2 * x3i ** 2), m_ij(x1i ** 2 * x2i ** 2 * x3i ** 2)]] free_vals = [m_ij(yi), m_ij(yi * x1i), m_ij(yi * x2i), m_ij(yi * x3i), m_ij(yi * x1i * x2i), m_ij(yi * x1i * x3i), m_ij(yi * x2i * x3i), m_ij(yi * x1i * x2i * x3i)] # solution of system of equations(array) b_i = np.linalg.solve(coefs, free_vals) # just arrays from table nat_x1 = np.array([norm_x_table[i][0] for i in range(8)]) nat_x2 = np.array([norm_x_table[i][1] for i in range(8)]) nat_x3 = np.array([norm_x_table[i][2] for i in range(8)]) norm_b_i = [m_ij(yi * 1), m_ij(yi * nat_x1), m_ij(yi * nat_x2), m_ij(yi * nat_x3), m_ij(yi * nat_x1 * nat_x2), m_ij(yi * nat_x1 * nat_x3), m_ij(yi * nat_x2 * nat_x3), m_ij(yi * nat_x1 * nat_x2 * nat_x3)] # main functions def theor_y(x_table, b_coef, importance): x_table = [list(compress(row, importance)) for row in x_table] # update: if importance 0 - get rid of x(ij) b_coef = list(compress(b_coef, importance)) # update: if importance 0 - get rid of b print("X_table :\n", x_table) print("b-coeffs :\n",b_coef) y_vals = np.array([sum(map(lambda x, b: x * b, row, b_coef)) for row in x_table]) return y_vals def student_criteria1(m, N, y_table, norm_x_table): print("\nЗа критерієм Стьюдента: m = {}, N = {} ".format(m, N)) avg_variation = np.average(list(map(np.var, y_table))) # var = mean(abs(y - y.mean())**2) in numpy y_avrg = np.array(list(map(np.average, y_table))) variation_beta_s = avg_variation / N / m deviation_beta_s = math.sqrt(variation_beta_s) x_i = np.array([[el[i] for el in norm_x_table] for i in range(len(norm_x_table))]) coef_beta_s = np.array([round(np.average(y_avrg * x_i[i]), 3) for i in range(len(x_i))]) print("Оцінки коефіцієнтів β(s): " + ", ".join(list(map(str, coef_beta_s)))) t_i = np.array([abs(coef_beta_s[i]) / deviation_beta_s for i in range(len(coef_beta_s))]) print("Коефіцієнти t: " + ", ".join(list(map(lambda i: "{:.2f}".format(i), t_i)))) f3 = (m - 1) * N q = 0.05 t = get_student(f3, q) importance = [True if el>t else False for el in list(t_i)] print("f3 = {}; q = {}; tтабл = {}".format(f3, q, t)) beta_i = ["β0", "β1", "β2", "β3", "β12", "β13", "β23", "β123"] updated_importance = [" - значимий" if i else " - незначимий" for i in importance] to_print = map(lambda x: x[0] + " " + x[1], zip(beta_i, updated_importance)) x_i_names = list(compress(["", " x1", " x2", " x3", " x12", " x13", " x23", " x123"], importance)) # if importance 0 - get rid of it betas_to_print = list(compress(coef_beta_s, importance)) print(*to_print, sep="; ") equation = " ".join(["".join(i) for i in zip(list(map(lambda x: "{:+.2f}".format(x), betas_to_print)), x_i_names)]) print("Рівняння регресії без незначимих членів: y = " + equation) return importance def get_student(f3, q): return (abs(scipy.stats.t.ppf(q / 2, f3))).__round__(3) def get_fisher(f3, f4, q): return (abs(f.isf(q, f4, f3))).__round__(3) def cochran_criteria(m, N, y_table): print("За критерієм Кохрена: m = {}, N = {} ".format(m, N)) y_variations = [np.var(i) for i in y_table] max_y_variation = max(y_variations) gp = max_y_variation / sum(y_variations) f1 = m - 1 f2 = N p = 0.95 q = 1 - p gt = cohren_value(f1, f2, q) print("Gp = {}; Gt = {}; f1 = {}; f2 = {}; q = {:.2f}".format(gp, gt, f1, f2, q)) if gp < gt: print("Gp < Gt => дисперсії рівномірні") return True else: print("Gp > Gt => дисперсії нерівномірні") return False while not cochran_criteria(m, 4, y_arr): m += 1 y_table = [[random.randint(y_min, y_max) for column in range(m)] for row in range(N)] print("Матриця планування:") labels = " x1 x2 x3 x12 x13 x23 x123 y1 y2 y3" rows_table = [list(x_table[i]) + list(y_arr[i]) for i in range(N)] print(labels) print("\n".join([" ".join(map(lambda j: "{:<6}".format(j), rows_table[i])) for i in range(len(rows_table))]), "\n") norm_x_table_with_x0 = [[+1] + row for row in norm_x_table] importance = student_criteria1(m, N, y_arr, norm_x_table_with_x0) # shows should each b(ij)*x(i) be in our main equation def fisher_criteria(m, N, d, nat_x_table, y_table, b_coefficients, importance): print("\nЗа критерієм Фішера: m = {}, N = {} ".format(m, N)) f3 = (m - 1) * N f4 = N - d q = 0.05 theoret_y = theor_y(nat_x_table, b_coefficients, importance) print(theoret_y) theor_values_to_print = list(zip(map(lambda x: "x1 = {0[0]}, x2 = {0[1]}, x3 = {0[2]}".format(x), nat_x_table), theoret_y)) print("Теоретичні y:") print("\n".join(["{val[0]}: y = {val[1]}".format(val=el) for el in theor_values_to_print])) y_averages = np.array(list(map(np.average, y_table))) s_ad = m / (N - d) * (sum((theoret_y - y_averages) ** 2)) y_variations = np.array(list(map(np.var, y_table))) s_v = np.average(y_variations) f_p = round(float(s_ad / s_v), 3) f_t = get_fisher(f3, f4, q) print("Fp = {}, Ft = {}".format(f_p, f_t)) print("Fp < Ft --> модель адекватна" if f_p < f_t else "Fp > Ft --> неадекватна") return True if f_p < f_t else False x_table_with_x0 = [[+1] + row for row in x_table] print("rhgjdr",x_table_with_x0) fisher_with_interaction = fisher_criteria(m, N, 1, x_table_with_x0, y_arr, b_i, importance) print(" (при врахуванні взаємодії)\n\n") #with quadratic terms(LAB5) if fisher_with_interaction == False: m = 3 N = 15 x0_i = [(x1max + x1min) / 2, (x2max + x2min) / 2, (x3max + x3min) / 2] y_arr = [[random.randint(y_min, y_max) for _ in range(m)] for _ in range(N)] delta_x_i = [(x1min - x0_i[0]), (x2min - x0_i[1]), (x3min - x0_i[2])] l = 1.215 nat_x_table = [[x1min, x2min, x3min], [x1min, x2max, x3max], [x1max, x2min, x3max], [x1max, x2max, x3min], [x1min, x2min, x3max], [x1min, x2max, x3min], [x1max, x2min, x3min], [x1max, x2max, x3max], [-l * delta_x_i[0] + x0_i[0], x0_i[1], x0_i[2]], [l * delta_x_i[0] + x0_i[0], x0_i[1], x0_i[2]], [x0_i[0], -l * delta_x_i[1] + x0_i[1], x0_i[2]], [x0_i[0], l * delta_x_i[1] + x0_i[1], x0_i[2]], [x0_i[0], x0_i[1], -l * delta_x_i[2] + x0_i[2]], [x0_i[0], x0_i[1], l * delta_x_i[2] + x0_i[2]], [x0_i[0], x0_i[1], x0_i[2]]] x_table = [[-1, -1, -1], [-1, +1, +1], [+1, -1, +1], [+1, +1, -1], [-1, -1, +1], [-1, +1, -1], [+1, -1, -1], [+1, +1, +1], [-l, 0, 0], [+l, 0, 0], [0, -l, 0], [0, +l, 0], [0, 0, -l], [0, 0, +l], [0, 0, 0]] while not cochran_criteria(m, N, y_arr): m += 1 y_arr = [[random.randint(y_min, y_max) for column in range(m)] for row in range(N)] yi = np.array([np.average(i) for i in y_arr]) # average for each i_th row in y_arr mat = np.array(nat_x_table) mat = np.append(mat, [[mat[i][0] * mat[i][1]] for i in range(N)], 1) mat = np.append(mat, [[mat[i][0] * mat[i][2]] for i in range(N)], 1) mat = np.append(mat, [[mat[i][1] * mat[i][2]] for i in range(N)], 1) mat = np.append(mat, [[mat[i][0] * mat[i][1] * mat[i][2]] for i in range(N)], 1) mat = np.append(mat, [[mat[i][0] ** 2] for i in range(N)], 1) mat = np.append(mat, [[mat[i][1] ** 2] for i in range(N)], 1) mat = np.append(mat, [[mat[i][2] ** 2] for i in range(N)], 1) np.set_printoptions(linewidth=150) x = np.transpose(mat) print(x) mx1 = sum(x[0]) / len(x[0]) mx2 = sum(x[1]) / len(x[1]) mx3 = sum(x[2]) / len(x[2]) mx4 = sum(x[3]) / len(x[3]) mx5 = sum(x[4]) / len(x[4]) mx6 = sum(x[5]) / len(x[5]) mx7 = sum(x[6]) / len(x[6]) mx8 = sum(x[7]) / len(x[7]) mx9 = sum(x[8]) / len(x[8]) mx10 = sum(x[9]) / len(x[9]) a11 = sum([x[0][i] * x[0][i] for i in range(N)]) / len(x[0]) a12 = a21 = sum([x[0][i] * x[1][i] for i in range(N)]) / len(x[0]) a13 = a31 = sum([x[0][i] * x[2][i] for i in range(N)]) / len(x[0]) a14 = a41 = sum([x[0][i] * x[3][i] for i in range(N)]) / len(x[0]) a15 = a51 = sum([x[0][i] * x[4][i] for i in range(N)]) / len(x[0]) a16 = a61 = sum([x[0][i] * x[5][i] for i in range(N)]) / len(x[0]) a17 = a71 = sum([x[0][i] * x[6][i] for i in range(N)]) / len(x[0]) a18 = a81 = sum([x[0][i] * x[7][i] for i in range(N)]) / len(x[0]) a19 = a91 = sum([x[0][i] * x[8][i] for i in range(N)]) / len(x[0]) a110 = a101 = sum([x[0][i] * x[9][i] for i in range(N)]) / len(x[0]) a22 = sum([x[1][i] * x[1][i] for i in range(N)]) / len(x[0]) a23 = a32 = sum([x[1][i] * x[2][i] for i in range(N)]) / len(x[0]) a24 = a42 = sum([x[1][i] * x[3][i] for i in range(N)]) / len(x[0]) a25 = a52 = sum([x[1][i] * x[4][i] for i in range(N)]) / len(x[0]) a26 = a62 = sum([x[1][i] * x[5][i] for i in range(N)]) / len(x[0]) a27 = a72 = sum([x[1][i] * x[6][i] for i in range(N)]) / len(x[0]) a28 = a82 = sum([x[1][i] * x[7][i] for i in range(N)]) / len(x[0]) a29 = a92 = sum([x[1][i] * x[8][i] for i in range(N)]) / len(x[0]) a210 = a102 = sum([x[1][i] * x[9][i] for i in range(N)]) / len(x[0]) a33 = sum([x[2][i] * x[2][i] for i in range(N)]) / len(x[0]) a34 = a43 = sum([x[2][i] * x[3][i] for i in range(N)]) / len(x[0]) a35 = a53 = sum([x[2][i] * x[4][i] for i in range(N)]) / len(x[0]) a36 = a63 = sum([x[2][i] * x[5][i] for i in range(N)]) / len(x[0]) a37 = a73 = sum([x[2][i] * x[6][i] for i in range(N)]) / len(x[0]) a38 = a83 = sum([x[2][i] * x[7][i] for i in range(N)]) / len(x[0]) a39 = a93 = sum([x[2][i] * x[8][i] for i in range(N)]) / len(x[0]) a310 = a103 = sum([x[2][i] * x[9][i] for i in range(N)]) / len(x[0]) a44 = sum([x[3][i] * x[3][i] for i in range(N)]) / len(x[0]) a45 = a54 = sum([x[3][i] * x[4][i] for i in range(N)]) / len(x[0]) a46 = a64 = sum([x[3][i] * x[5][i] for i in range(N)]) / len(x[0]) a47 = a74 = sum([x[3][i] * x[6][i] for i in range(N)]) / len(x[0]) a48 = a84 = sum([x[3][i] * x[7][i] for i in range(N)]) / len(x[0]) a49 = a94 = sum([x[3][i] * x[8][i] for i in range(N)]) / len(x[0]) a410 = a104 = sum([x[3][i] * x[9][i] for i in range(N)]) / len(x[0]) a55 = sum([x[4][i] * x[4][i] for i in range(N)]) / len(x[0]) a56 = a65 = sum([x[4][i] * x[5][i] for i in range(N)]) / len(x[0]) a57 = a75 = sum([x[4][i] * x[6][i] for i in range(N)]) / len(x[0]) a58 = a85 = sum([x[4][i] * x[7][i] for i in range(N)]) / len(x[0]) a59 = a95 = sum([x[4][i] * x[8][i] for i in range(N)]) / len(x[0]) a510 = a105 = sum([x[4][i] * x[9][i] for i in range(N)]) / len(x[0]) a66 = sum([x[5][i] * x[5][i] for i in range(N)]) / len(x[0]) a67 = a76 = sum([x[5][i] * x[6][i] for i in range(N)]) / len(x[0]) a68 = a86 = sum([x[5][i] * x[7][i] for i in range(N)]) / len(x[0]) a69 = a96 = sum([x[5][i] * x[8][i] for i in range(N)]) / len(x[0]) a610 = a106 = sum([x[5][i] * x[9][i] for i in range(N)]) / len(x[0]) a77 = sum([x[6][i] * x[6][i] for i in range(N)]) / len(x[0]) a78 = a87 = sum([x[6][i] * x[7][i] for i in range(N)]) / len(x[0]) a79 = a97 = sum([x[6][i] * x[8][i] for i in range(N)]) / len(x[0]) a710 = a107 = sum([x[6][i] * x[9][i] for i in range(N)]) / len(x[0]) a88 = sum([x[7][i] * x[7][i] for i in range(N)]) / len(x[0]) a89 = a98 = sum([x[7][i] * x[8][i] for i in range(N)]) / len(x[0]) a810 = a108 = sum([x[7][i] * x[9][i] for i in range(N)]) / len(x[0]) a99 = sum([x[8][i] * x[8][i] for i in range(N)]) / len(x[0]) a910 = a109 = sum([x[8][i] * x[9][i] for i in range(N)]) / len(x[0]) a1010 = sum([x[9][i] * x[9][i] for i in range(N)]) / len(x[0]) coefficients = [[1, mx1, mx2, mx3, mx4, mx5, mx6, mx7, mx8, mx9, mx10], [mx1, a11, a21, a31, a41, a51, a61, a71, a81, a91, a101], [mx2, a12, a22, a32, a42, a52, a62, a72, a82, a92, a102], [mx3, a13, a23, a33, a43, a53, a63, a73, a83, a93, a103], [mx4, a14, a24, a34, a44, a54, a64, a74, a84, a94, a104], [mx5, a15, a25, a35, a45, a55, a65, a75, a85, a95, a105], [mx6, a16, a26, a36, a46, a56, a66, a76, a86, a96, a106], [mx7, a17, a27, a37, a47, a57, a67, a77, a87, a97, a107], [mx8, a18, a28, a38, a48, a58, a68, a78, a88, a98, a108], [mx9, a19, a29, a39, a49, a59, a69, a79, a89, a99, a109], [mx10, a110, a210, a310, a410, a510, a610, a710, a810, a910, a1010]] free_values = [0 for i in range(11)] free_values[0] = sum(yi) / len(yi) for i in range(1, 11): free_values[i] = sum([x[i - 1][j] * yi[j] for j in range(N)]) / N beta_coefficients = np.linalg.solve(coefficients, free_values) np.set_printoptions(suppress=True, linewidth=200) print(beta_coefficients) def student_criteria2(m, N, y_table, beta_coefficients): print("\nПеревірка значимості коефіцієнтів регресії за критерієм Стьюдента: ".format(m, N)) average_variation = np.average(list(map(np.var, y_table))) print(average_variation) variation_beta_s = average_variation/N/m print(variation_beta_s) standard_deviation_beta_s = math.sqrt(variation_beta_s) t_i = np.array([(abs(beta_coefficients[i])/standard_deviation_beta_s) for i in range(len(beta_coefficients))]) f3 = (m - 1) * N q = 0.05 t = get_student(f3, q) importance = [True if el>t else False for el in list(t_i)] print("\n"+"Оцінки коефіцієнтів βs: " + ", ".join(list(map(lambda x: str(round(float(x), 3)), beta_coefficients)))) print("Коефіцієнти ts: " + ", ".join(list(map(lambda i: "{:.2f}".format(i), t_i)))) print("f3 = {}; q = {}; tтабл = {}".format(f3, q, t)) beta_i = ["β0", "β1", "β2", "β3", "β12", "β13", "β23", "β123", "β11", "β22", "β33"] importance_to_print = ["важливий" if i else "неважливий" for i in importance] to_print = map(lambda x: x[0] + " " + x[1], zip(beta_i, importance_to_print)) x_i_names = list(compress(["", "x1", "x2", "x3", "x12", "x13", "x23", "x123", "x1^2", "x2^2", "x3^2"], importance)) betas_to_print = list(compress(beta_coefficients, importance)) print(*to_print, sep="; ") equation = " ".join(["".join(i) for i in zip(list(map(lambda x: "{:+.2f}".format(x), betas_to_print)), x_i_names)]) print("Рівняння регресії без незначимих членів: y = " + equation) return importance importance = student_criteria2(m, N, y_arr, beta_coefficients) nat_x_table_x0 = [[+1] + row for row in nat_x_table] fisher_last = fisher_criteria(m, N, len(list(filter(None, importance))), nat_x_table_x0, y_arr, beta_coefficients, importance) print(" (при врахуванні квадратичних членів)") with_interaction = False

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yingxingtianxia/python

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#!/usr/bin/python # coding=utf-8 """ python 操作redis是很方便的,直接安装此包注意:在docker中重启redis,导致数据完全丢失 """ import redis r = redis.Redis(host='192.168.99.100', port=46379) def addOne(key): add(key, 1) def add(key, num): val = r.get(key) if val == None: val = 0 else: val = int(r.get(key)) r.set(key, str(val + num)) def getkeys(pattern=""): return r.keys(pattern) def get(key=""): return r.get(key) def addSet(key="", uid=""): r.sadd(key, uid) def getSet(key=""): return r.scard(key)

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zzqzzqzzq0816/FontRecognition

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/rear/FontRecognition/font/api/views.py

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[]

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https://github.com/zzqzzqzzq0816/FontRecognition

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refs/heads/master

2022-12-20T01:53:43.650481

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import os import time from django.views.decorators.csrf import csrf_exempt from rest_framework.response import Response from rest_framework.decorators import api_view def tran_name(image): curr_time = time.strftime("%Y%m%d%H%M%S", time.localtime()) suffix = image.name.split('.')[-1].replace('"', '') image.name = curr_time + '.' + suffix def save_image(image): image_path = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), 'media') full_path = image_path + '/' + image.name with open(full_path, 'wb') as f: for c in image.chunks(): f.write(c) return full_path @csrf_exempt @api_view(['POST']) def get_recognition_result(request): response = {} try: image = request.data['image'] tran_name(image) full_path = save_image(image) response['msg'] = '成功！' response['error_num'] = 0 except Exception as e: response['msg'] = str(e) response['error_num'] = 1 return Response(response)

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snigdharao28/nltk_sentdex

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/newtextclf.py

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[]

no_license

https://github.com/snigdharao28/nltk_sentdex

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refs/heads/master

2020-04-18T01:39:14.512064

2019-01-24T04:57:32

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#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Wed Jan 23 14:24:41 2019 @author: snigdharao """ #!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Tue Jan 22 17:40:35 2019 @author: snigdharao """ import random import pickle import nltk #from nltk.corpus import movie_reviews from nltk.classify.scikitlearn import SklearnClassifier from sklearn.naive_bayes import MultinomialNB, BernoulliNB from sklearn.linear_model import LogisticRegression, SGDClassifier from sklearn.svm import LinearSVC, NuSVC from nltk.classify import ClassifierI from statistics import mode from nltk.tokenize import word_tokenize class VoteClassifier(ClassifierI): def __init__(self, *classifiers): self._classifiers = classifiers def classify(self, features): votes = [] for c in self._classifiers: v = c.classify(features) votes.append(v) return mode(votes) def confidence(self, features): votes = [] for c in self._classifiers: v = c.classify(features) votes.append(v) choice_votes = votes.count(mode(votes)) conf = choice_votes / len(votes) return conf short_pos = open("positive.txt","r").read() short_neg = open("negative.txt","r").read() all_words = [] documents = [] allowed_word_types = ["J"] for r in short_pos.split('\n'): documents.append( (r, "pos") ) words = word_tokenize(r) pos = nltk.pos_tag(words) for w in pos: if w[1][0] in allowed_word_types: all_words.append(w[0].lower()) for r in short_neg.split('\n'): documents.append( (r, "neg") ) words = word_tokenize(r) pos = nltk.pos_tag(words) for w in pos: if w[1][0] in allowed_word_types: all_words.append(w[0].lower()) save_documents = open("pickled_algos/documents.pickle", "wb") pickle.dump(documents, save_documents) save_documents.close() all_words = nltk.FreqDist(all_words) word_features = list(all_words.keys())[:5000] save_word_features = open("pickled_algos/word_features5k.pickle", "wb") pickle.dump(word_features, save_word_features) save_word_features.close() def find_features(document): words = word_tokenize(document) features = {} for w in word_features: features[w] = (w in words) return features featuresets = [(find_features(rev), category) for (rev, category) in documents] random.shuffle(featuresets) print(len(featuresets)) training_set = featuresets[:10000] test_set = featuresets[10000:] #original naive bayes classifier = nltk.NaiveBayesClassifier.train(training_set) classifier.show_most_informative_features(15) print("Original Classifier accuracy percent:", (nltk.classify.accuracy(classifier, test_set))*100) #saving originalnaivebayes save_classifier = open("pickled_algos/originalnaivebayes5k.pickle","wb") pickle.dump(classifier, save_classifier) save_classifier.close() #Multinomial NB MNB_classifier = SklearnClassifier(MultinomialNB()) MNB_classifier.train(training_set) print("MultinomialNB accuracy percent:",nltk.classify.accuracy(MNB_classifier,test_set)*100) #saving multinomial NB save_classifier = open("pickled_algos/MNB_classifier5k.pickle","wb") pickle.dump(MNB_classifier, save_classifier) save_classifier.close() #Bernoulli NB BNB_classifier = SklearnClassifier(BernoulliNB()) BNB_classifier.train(training_set) print("BernoulliNB accuracy percent:",nltk.classify.accuracy(BNB_classifier, test_set)*100) #saving Bernoulli NB save_classifier = open("pickled_algos/BNB_classifier5k.pickle","wb") pickle.dump(BNB_classifier, save_classifier) save_classifier.close() #Logistic Regression LogisticRegression_classifier = SklearnClassifier(LogisticRegression()) LogisticRegression_classifier.train(training_set) print("LogisticRegression_classifier accuracy percent:",nltk.classify.accuracy(LogisticRegression_classifier, test_set)*100) #saving LogisticRegression save_classifier = open("pickled_algos/LogisticRegression5k.pickle","wb") pickle.dump(LogisticRegression_classifier, save_classifier) save_classifier.close() #SGDClassifier ( stochastic gradient descent) SGDClassifier_classifier = SklearnClassifier(SGDClassifier()) SGDClassifier_classifier.train(training_set) print("SGDClassifier_classifier accuracy percent:",nltk.classify.accuracy(SGDClassifier_classifier, test_set)*100) #saving SGDClassifier save_classifier = open("pickled_algos/SGDClassifier5k.pickle", "wb") pickle.dump(SGDClassifier_classifier, save_classifier) save_classifier.close() #Support Vector classifier # ============================================================================= # SVC_classifier = SklearnClassifier(SVC()) # SVC_classifier.train(training_set) # print("SVC_classifier accuracy percent:",nltk.classify.accuracy(SVC_classifier, test_set)*100) # ============================================================================= #Linear SVC LinearSVC_classifier = SklearnClassifier(LinearSVC()) LinearSVC_classifier.train(training_set) print("LinearSVC_classifier accuracy percent:",nltk.classify.accuracy(LinearSVC_classifier, test_set)*100) #saving LinearSVC save_classifier = open("pickled_algos/LinearSVClassifier5k.pickle","wb") pickle.dump(LinearSVC_classifier, save_classifier) save_classifier.close() #NuSVC (number of units) #NuSVC_classifier = SklearnClassifier(NuSVC()) #NuSVC_classifier.train(training_set) #print("NuSVC_classifier accuracy percent:",nltk.classify.accuracy(NuSVC_classifier, test_set)*100) #new voted classifier #voted_classifier = VoteClassifier(NuSVC_classifier, # LinearSVC_classifier, # MNB_classifier, # BNB_classifier, # LogisticRegression_classifier) # #print("voted_classifier accuracy percent:", (nltk.classify.accuracy(voted_classifier, test_set))*100) #print("Classification:", voted_classifier.classify(test_set[0][0]), "Confidence %:", voted_classifier.confidence(test_set[0][0])*100) #print("Classification:", voted_classifier.classify(test_set[1][0]), "Confidence %:", voted_classifier.confidence(test_set[1][0])*100) #print("Classification:", voted_classifier.classify(test_set[2][0]), "Confidence %:", voted_classifier.confidence(test_set[2][0])*100) #print("Classification:", voted_classifier.classify(test_set[3][0]), "Confidence %:", voted_classifier.confidence(test_set[3][0])*100) #print("Classification:", voted_classifier.classify(test_set[4][0]), "Confidence %:", voted_classifier.confidence(test_set[4][0])*100) #print("Classification:", voted_classifier.classify(test_set[5][0]), "Confidence %:", voted_classifier.confidence(test_set[5][0])*100)

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MadhavKMadhu/C4-SMP-ML

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import numpy as np from sigmoid import sigmoid def costFunction(theta, X, y): '''Returns Cost for theta, X, y''' m = y.size h = sigmoid(np.dot(X,theta)) J = [-(1/m) * (np.sum((y.T)*np.log(h) + (1-(y.T))*np.log(1-h)))] if np.isnan(J[0]): return(np.inf) return(J[0]) def gradient(theta, X, y): '''Calculate Gradient Descent for Logistic Regression''' m = y.size theta = theta.reshape(-1,1) h = sigmoid(np.dot(X,theta)) grad = ((1/m) * np.dot(X.T, (h-y)) ) return(grad.flatten())

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stlk/django-toolbox

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import logging from time import time from django.conf import settings timing_logger = logging.getLogger("django.request") SETTINGS = {"EXCLUDED_PATHS": set(), "LONG_REQUEST_THRESHOLD": 1000} SETTINGS.update(getattr(settings, "METRICS", {})) SETTINGS["EXCLUDED_PATHS"] = {path.strip("/") for path in SETTINGS["EXCLUDED_PATHS"]} class TimingMiddleware: def __init__(self, get_response=None): self.get_response = get_response def process_request(self, request): if request.path.strip("/") in SETTINGS["EXCLUDED_PATHS"]: return request setattr(request, "_metrics_start_time", time()) def process_response(self, request, response): if hasattr(request, "_metrics_start_time"): duration = time() - request._metrics_start_time duration_ms = int(round(duration * 1000)) if duration_ms > SETTINGS["LONG_REQUEST_THRESHOLD"]: timing_logger.warning(f"Long request. duration_ms: {duration_ms}") else: timing_logger.info(f"duration_ms: {duration_ms}") return response def __call__(self, request): self.process_request(request) response = self.get_response(request) self.process_response(request, response) return response

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jukim-greenventory/python-practice

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https://github.com/jukim-greenventory/python-practice

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2021-06-10T12:38:57

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""" base form: - parse_args(['option','value']) other forms: For long options (options with names longer than a single character), the option and value can also be passed as a single command-line argument, using = to separate them: - parse_args(['--option=value']) For short options (options only one character long), the option and its value can be concatenated: - parse_args(['-optionvalue']) About dest: - dest allows a custom attribute name to be provided: (in our case "integers") About metavar: - metavar only changes the displayed name - the name of the attribute on the parse_args() object is still determined by the dest value. About const: - About nargs: N (an integer). - N arguments from the command line will be gathered together into a list. For example: '+' - Just like '*', all command-line args present are gathered into a list. Additionally, an error message will be generated if there wasn’t at least one command-line argument present. '*' - '?' - One argument will be consumed from the command line if possible, and produced as a single item. If no command-line argument is present, the value from default will be produced. """ import argparse parser = argparse.ArgumentParser(description="Process some integers.") parser.add_argument( "integers", metavar="N", type=int, nargs="+", help="an integer for the accumulator" ) parser.add_argument( "--sum", dest="accumulate", action="store_const", const=sum, default=max, help="sum the integers (default: find the max)", ) args = parser.parse_args() print(args) print(args.accumulate(args.integers))

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kevinkraydich/showerthoughts

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/bot/bot.py

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refs/heads/master

2020-07-10T23:11:22.934416

2020-05-06T04:08:19

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""" Python module for Reddit bot. Kevin Kraydich <kraydich@umich.edu> """ # Import third party modules import os import configparser import sys path = os.path.join(os.getcwd(), 'bot/', 'utils/') sys.path.append(path) # Import local modules import scraper import text config = configparser.ConfigParser() settings_path = os.path.join(os.getcwd(), 'bot/', 'settings.ini') config.read(settings_path) class Bot: def __init__(self): subreddit = config.get('default', 'subreddit_name') num_posts = config.getint('default', 'max_posts') print("Loading scraper") self._scraper = scraper.Scraper(subreddit, num_posts) self._numbers = [] def add_number(self, num): self._numbers.append(num) def send_texts(self): print("Grabbing random showerthought") contents = self._scraper.get_random_post() for num in self._numbers: msg = text.Text(num) msg.send(contents)

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FranciszekPin/gravity-field-simulator

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/BallsManager.py

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no_license

https://github.com/FranciszekPin/gravity-field-simulator

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refs/heads/main

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null

import numpy from panda3d.core import LPoint3, LVector3 from physics.Ball import Ball from physics.PhysicsManager import PhysicsManager class BallsManager: balls = [] speed = 100000 def __init__(self, showBase): self.showBase = showBase self.add_balls_to_render() self.showBase.taskMgr.add(self.update_balls_task, "updateBallsTask") self.lastDeltaTime = 0 def add_balls_to_render(self): """ Adds balls to simulator """ self.add_ball(numpy.array([0., 0., 0.]), numpy.array([0, 0.0, 0.0]), False, 333000, "sun") self.add_ball(numpy.array([0., 0., 100]), numpy.array([0.0004713, 0, 0]), False, 1, "earth") self.add_ball(numpy.array([0., 0., 50]), numpy.array([0.0006665, 0, 0]), False, 1, "mars") self.add_ball(numpy.array([0., 0., 25]), numpy.array([0.0009426, 0, 0]), False, 1, "mercury") def add_ball(self, position, velocity, static, mass, texName): """ Adds chosen ball to simulator """ ball_model = self.showBase.loader.loadModel("models/ball") ball_model.setScale(5) if texName == "sun": tex = self.showBase.loader.loadTexture("models/sun_1k_tex.jpg") ball_model.setScale(15) elif texName == "earth": tex = self.showBase.loader.loadTexture("models/earth_1k_tex.jpg") elif texName == "mercury": tex = self.showBase.loader.loadTexture("models/mercury_1k_tex.jpg") elif texName == "mars": tex = self.showBase.loader.loadTexture("models/mars_1k_tex.jpg") elif texName == "moon": tex = self.showBase.loader.loadTexture("models/moon_1k_tex.jpg") ball_model.setScale(2) else: tex = 0 ball_model.setTexture(tex) ball_model.reparentTo(self.showBase.render) ball_model.setPos(LVector3(position[0], position[1], position[2])) self.balls.append(Ball(position, ball_model, static, velocity, mass)) def add_planet_square(self, position, radius, distance_between_balls): """ Colors the area with small balls """ for x in numpy.arange(-radius, radius + 1e-9, distance_between_balls): for y in numpy.arange(-radius, radius + 1e-9, distance_between_balls): self.add_ball(numpy.array([x+position[0], 0.0, y+position[2]]), numpy.array([0.00001, 0.0, 0.0]), False, 1000, "earth") def update_balls_task(self, task): """ Takes care of changing phsyics values of all objects """ delta_time = (task.time - self.lastDeltaTime) * self.speed PhysicsManager().update(self.balls, delta_time) self.update_balls_positions(delta_time) self.lastDeltaTime = task.time return task.cont def update_balls_positions(self, delta_time): """ Moves all balls by their velocities """ for ball in self.balls: ball.move(LVector3(ball.velocity[0], ball.velocity[1], ball.velocity[2]) * delta_time)

UTF-8

Python

false

2,995

py

7

BallsManager.py

5

0.620033

0.583306

0

72

40.597222

135

giorgiberia/gitlearn

16,423,954,974,636

f20b1b4fc502b3788ef41b7ad8af13860ea65ab8

71c6a5dcf59a9388e23c468ad716ab807454bb8a

/app/OrbiUser/managers.py

46092bf856f6ee3cb4561fb73306274866bf6c0d

[ "MIT" ]

permissive

https://github.com/giorgiberia/gitlearn

0b63c21d93ae7b7313b2634294d579e75cc772f7

447b1ccd6279bd5accf92336c446e3340d8e8181

refs/heads/master

2020-06-21T07:26:20.586610

2019-07-18T11:49:52

null

0

null

from django.contrib.auth.base_user import BaseUserManager class UserManager(BaseUserManager): use_in_migrations = True def create_user(self, username,fullname, date_of_birth, password=None): user = self.model( username=username, date_of_birth=date_of_birth, fullname=fullname, ) user.set_password(password) user.save(using=self._db) return user def create_staffuser(self, fullname, date_of_birth, password): user = self.create_user( password=password, date_of_birth=date_of_birth, fullname=fullname, ) user.staff = True user.save(using=self._db) return user def create_superuser(self,username,fullname, date_of_birth, password): user = self.create_user( username=username, password=password, date_of_birth=date_of_birth, fullname=fullname, ) user.staff = True user.admin = True user.save(using=self._db) return user

UTF-8

Python

false

1,085

py

7

managers.py

6

0.588018

0

37

28.324324

75

NeerajaLanka/100daysofcode

8,083,128,464,577

f2a4ca0811ea330f58ee483e495a6a5dade187c7

103d5c372371ceb8235becd0b66e504594b61e4b

/Day15coffee_Machine.py

5913a299df8cb792ea98207f1dd87093581e2151

[]

no_license

https://github.com/NeerajaLanka/100daysofcode

29dc194742a9b14565e50f8674724aed85380f18

5a42fa02c773f4949ad1acc07c88cef9c702f088

refs/heads/master

2023-07-09T04:45:02.757056

2021-08-19T19:56:06

327,458,893

0

null

#flavours = input("what would you like?(espresso/latte/cappuccino:") MENU = { "espresso": { "ingredients": { "water": 50, "coffee": 18, }, "cost": 1.5, }, "latte": { "ingredients": { "water": 200, "milk": 150, "coffee": 24, }, "cost": 2.5, }, "cappuccino": { "ingredients": { "water": 250, "milk": 100, "coffee": 24, }, "cost": 3.0, } } #print(MENU["cappuccino"]["ingredients"]["milk"]) resources = { "water": 25, "milk": 200, "coffee": 100, } for i in MENU.values(): print(i) W = i["ingredients"]["water"] W_r = resources["water"] #M = i["ingredients"]["milk"] #M_r = resources["milk"] C = i["ingredients"]["coffee"] C_r = resources["coffee"] c_type = input("which type do you want?") def compare(): if c_type == "espresso": if W <= W_r and C <=C_r : print("take coffee") elif c_type == "latte" : if W <= W_r and C <=C_r : print("enjoy your coffee") elif c_type == "cappuccino": if W <= W_r and C <=C_r : print("enjoy good coffee") else: print("not possible") coffee_type(W,W_r,C,C_r)

UTF-8

Python

false

1,384

py

92

Day15coffee_Machine.py

92

0.427023

0.402457

0

59

22.457627

68

Aasthaengg/IBMdataset

16,466,904,660,324

e8ef5e615f58b78dd2d64dde919b0c2670160012

ca7aa979e7059467e158830b76673f5b77a0f5a3

/Python_codes/p02665/s564559024.py

0cbbd9ba9d053be1d913e709cc91d4285f6558f2

[]

no_license

https://github.com/Aasthaengg/IBMdataset

7abb6cbcc4fb03ef5ca68ac64ba460c4a64f8901

f33f1c5c3b16d0ea8d1f5a7d479ad288bb3f48d8

refs/heads/main

2023-04-22T10:22:44.763102

2021-05-13T17:27:22

367,112,348

0

null

n=int(input()) l=list(map(int,input().split())) k=l[n] count=1 sumleaf=1 flag=True i0=0 suml=[] for i in l: i0+=i suml.append(i0) if l[0]>2 or l[0]==1 and n>=1: print(-1) flag=False elif n==0 and l[0]!=1: print(-1) flag=False else: for i in range(1,n+1): sumleaf*=2 if i==n and sumleaf<k: flag=False print(-1) break elif i==n: count+=k else: if sumleaf<=l[i]: flag=False print(-1) break else: sumlnew=suml[n]-suml[i-1] count+=min(sumlnew,sumleaf) sumleaf=min(sumlnew,sumleaf)-l[i] if flag==True: print(count)

UTF-8

Python

false

851

py

202,060

s564559024.py

202,055

0.398355

0.372503

0

44

18.363636

49

imfede/py-project-euler

7,112,465,883,775

152c206c9634cb556ac378c3d9b0d1a45fa7bc87

cceeebcfe1df8a849216917217ee413d1ed715b2

/003.py

0508dec0e94bb45a4a52b572d406fd9614021d6c

[]

no_license

https://github.com/imfede/py-project-euler

d97861bde90a0bde74041aa29beb071cec6921ac

6aaf5daf7be962db35bb1284915da76b396bb672

refs/heads/master

2021-01-01T19:24:48.072243

2015-07-25T13:53:05

35,602,711

0

null

#!/usr/bin/python # what is the largest prime factor of 600851475143 import math def isPrime(n): x = 2 while (x < math.ceil(math.sqrt(n)) ): if( n%x == 0): return False x += 1 return True def number_from_factors(factors): p = 1 for i in range( len(factors) ): p *= factors[i] return p n = 600851475143 n2 = n factors = [] i = 2 while( number_from_factors(factors) != n2 ): if( isPrime(i) and n%i==0 ): factors.append(i) n = n // i i = 2 else: i += 1 print( max( factors ) )

UTF-8

Python

false

580

py

39

003.py

39

0.525862

0.467241

0

33

16.575758

50

Jorsorokin/JAGA_software

6,064,493,823,488

e571566f43818b29c269cf50979b38f23c887c73

e713cdc626f2d1bc97cbc8744a071bca0b66b823

/Python/packet_buffer.py

b196729cfaa9258a72e3d1573f589769a681b58c

[]

no_license

https://github.com/Jorsorokin/JAGA_software

bc605f48ae08a1f9c1954e64fbd88bfa25a4f481

b9b6efd6aaef5a163af0e1c1197655dd439c9f64

refs/heads/master

2021-01-19T15:14:35.674545

2017-04-16T19:43:16

88,206,238

0

null

__author__ = 'Markus De Shon' import copy import packet import sys class PacketBuffer(): MIN_FILL = 100 MAX_FILL = 1000 SKIP_COUNT = 10 # Skip initial packets when calculating start time because their timing is odd. LATENCY = 0.003 # Latency of packet delivery on the network. def __init__(self, filename, debug=False): self.fh = open(filename, 'rb') self.channels = None self.first_seconds = None self.last_seconds = None self.first_sample_count = None self.last_sample_count = None self.start_time = None self.total_lost = 0 self.crc_received = 0 self.samples_per_packet = None self.samples_per_second = None self.packets_received = 0 self.packets_recovered = 0 self.packet_array = [] self.packet_array_index = 0 self.lost_since_last_crc = 0 self.debug = debug def __del__(self): self.fh.close() def __iter__(self): return self def next(self): if len(self.packet_array) < PacketBuffer.MIN_FILL: self._fill_array() try: p = self.packet_array.pop(0) # FIFO if (self.first_seconds is not None and self.first_sample_count is not None and self.start_time is not None): p.set_start_time(start_time=self.start_time, first_sequence=self.first_sample_count, first_seconds=self.first_seconds) return p except IndexError: # No packets left. raise StopIteration def _read_next(self): try: p = packet.Packet(self.fh, channels=self.channels) if p.crc: self.crc_received += 1 return p, 0 if self.channels is None and p.channels: self.channels = p.channels self.samples_per_packet = p.samples_per_packet self.samples_per_second = p.samples_per_second self.packets_received += 1 lost_packets = 0 if p.V0: if self.last_seconds: lost_packets = self._count_lost_packets(p) self.last_seconds = p.seconds self.last_sample_count = p.sample_count else: # V3 packets if self.last_sample_count: lost_packets = self._count_lost_packets(p) self.last_sample_count = p.sample_count return p, lost_packets except ValueError: # Ran out of data. return None, 0 except AttributeError: # The first packet in the file is a CRC packet, so self.channels is not set yet. sys.stderr.write("WARNING: First packet was a CRC, seeking next packet to continue.\n") self._seek_channels() assert(self.channels is not None) # We've set self.channels from the next packet, so try again to read the leading CRC packet. return self._read_next() def _seek_channels(self): # The first packet was a CRC, so we need to find the channel count in the next packet. for length in packet.Packet.possible_packet_lengths_v3(): self.fh.seek(length) try: sys.stderr.write("Trying offset " + str(length) + "\n") p = packet.Packet(self.fh) sys.stderr.write("Next packet header was found... continuing.\n") self.channels = p.channels # We found the right offset and set the self.channels value, so go back to the beginning. self.fh.seek(0) return except Exception as e: sys.stderr("WARNING: Exception received: " + e.message + "\n") # Try the next offset. continue sys.stderr.write("ERROR: Next packet header could not be found. Exiting.\n") sys.exit(1) def _count_lost_packets(self, p): assert (not p.crc) if p.V0: increment = self.samples_per_second * (p.seconds - self.last_seconds) increment += p.sample_count - self.last_sample_count else: increment = p.sample_count - self.last_sample_count lost = (increment / self.samples_per_packet) - 1 if self.debug and lost > 0: sys.stderr.write(str(lost) + " packets lost.\n") return (increment / self.samples_per_packet) - 1 def _fill_array(self): p, lost_packets = self._read_next() timestamps = [] if self.first_sample_count is None: if p.V0: self.first_seconds = 0 self.first_sample_count = (p.seconds * p.samples_per_second) + p.sample_count else: self.first_seconds = 0 self.first_sample_count = p.sample_count while p and len(self.packet_array) < PacketBuffer.MAX_FILL - 1: array_length = len(self.packet_array) timestamps.append(p.timestamp) if lost_packets > 0: self.lost_since_last_crc += lost_packets self.total_lost += lost_packets if p.crc: if (array_length > p.crc_interval) and self.lost_since_last_crc > 0: # Reconstruct a single missing packet. Need at least 1 packet of history before window. if self.debug: sys.stderr.write("Attempting to reconstruct packet using CRC.\n") start_window = array_length - p.crc_interval + 1 # Only works for one lost packet. end_window = array_length if self.debug: sys.stderr.write("start_window " + str(start_window) + " end_window " + str(end_window) + "\n") (missing_index, missing_count, xor) = self._xor_over_window(start_window, end_window) if self.debug: sys.stderr.write("missing_index " + str(missing_index) + " missing_count " + str(missing_count) + "\n") if missing_count == 1 and missing_index and start_window <= missing_index <= end_window: if self.debug: sys.stderr.write("Single missing packet found before sample_count " + str(self.packet_array[missing_index].sample_count) + "\n") self._reconstruct_packet(p, missing_index, xor=xor) else: if self.debug: sys.stderr.write("Could not reconstruct packet, missing " + str(missing_count) + " packets.\n") self.lost_since_last_crc = 0 else: self.packet_array.append(p) p, lost_packets = self._read_next() if p and not p.crc: self.packet_array.append(p) # The last valid packet that was read. if not self.start_time: if len(timestamps) > PacketBuffer.MIN_FILL * 2: timestamps = timestamps[PacketBuffer.MIN_FILL:] # Drop the first MIN_FILL if we can. self.start_time = (sum(timestamps) / float(len(timestamps))) - PacketBuffer.LATENCY def _xor_over_window(self, start_window, end_window): xor = None missing_index = None missing_count = 0 for i in range(start_window, end_window): interval = (self.packet_array[i].sample_count - self.packet_array[i - 1].sample_count) if (((self.packet_array[i].sample_count - self.packet_array[i - 1].sample_count) / self.samples_per_packet) - 1 == 1): missing_index = i missing_count += 1 if xor: self._xor_arrays(xor, self.packet_array[i].all_samples) else: # xor not defined yet, set to the samples from the first packet. xor = copy.deepcopy(self.packet_array[i].all_samples) return missing_index, missing_count, xor def _reconstruct_packet(self, crc_packet, missing_index=None, xor=None, start_window=None, end_window=None): # Reconstruct packet that would have appeared before missing_index within window # Two usage modes: # 1) set xor, missing_index and optionally start_window, end_window OR # 2) only set start_window, end_window (need to calculate xor and find missing_index). if not xor: # Need to calculate xor over the window. assert (start_window is not None and start_window >= 1) assert (end_window is not None and end_window >= start_window) (missing_index, missing_count, xor) = self._xor_over_window(start_window, end_window) new_packet = copy.deepcopy(self.packet_array[missing_index - 1]) # Start with an existing packet. new_packet.timestamp = (self.packet_array[missing_index].timestamp + self.packet_array[ missing_index - 1].timestamp) / 2.0 new_packet.sample_count = new_packet.sample_count + self.samples_per_packet self._xor_arrays(xor, crc_packet.all_samples) new_packet.all_samples = xor self.packet_array.insert(missing_index, new_packet) self.packets_recovered += 1 def _xor_arrays(self, a, b): assert (len(a) == len(b)) for i in range(len(b)): for j in range(len(b[i])): a[i][j] ^= b[i][j]

UTF-8

Python

false

9,654

py

7

packet_buffer.py

6

0.553967

0.547856

0

206

45.864078

112

j5int/pyslet

18,098,992,196,401

f7e5e2626116048929ddd21136f9b4c7f88b2bc8

c2b35211fab6b1f8a4a51b3245f540512b76cc6c

/pyslet/streams.py

65badddf89dac569bf46f0a56455a1b6520ff38a

[ "BSD-3-Clause" ]

permissive

https://github.com/j5int/pyslet

08ed591f8ca6347225d9404c4fe16f8afc03d476

ef27dd6bb6fbd6d47687a349508cd4ab2989a0ad

refs/heads/master

2021-05-23T11:30:31.713515

2016-07-25T09:10:32

68,193,782

2

null

true

2021-04-06T09:14:05

2016-09-14T09:40:27

2016-10-19T11:15:54

2021-04-06T09:14:05

7,646

0

2

0

Python

false

#! /usr/bin/env python """This module add some useful stream classes""" import errno import io import logging import os import threading import time from .py26 import memoryview if hasattr(errno, 'WSAEWOULDBLOCK'): _blockers = set((errno.EAGAIN, errno.EWOULDBLOCK, errno.WSAEWOULDBLOCK)) else: _blockers = set((errno.EAGAIN, errno.EWOULDBLOCK)) def io_blocked(err): """Returns True if IO operation is blocked err An IOError exception (or similar object with errno attribute). Bear in mind that EAGAIN and EWOULDBLOCK are not necessarily the same value and that when running under windows WSAEWOULDBLOCK may be raised instead. This function removes this complexity making it easier to write cross platform non-blocking IO code.""" return err.errno in _blockers if hasattr(errno, 'WSAETIMEDOUT'): _timeouts = set((errno.ETIMEDOUT, errno.WSAETIMEDOUT)) else: _timeouts = set((errno.ETIMEDOUT, )) def io_timedout(err): """Returns True if an IO operation timed out err An IOError exception (or similar object with errno attribute). Tests for ETIMEDOUT and when running under windows WSAETIMEDOUT too.""" return err.errno in _timeouts class BufferedStreamWrapper(io.RawIOBase): """A buffered wrapper for file-like objects. src A file-like object, we only require a read method buffsize The maximum size of the internal buffer On construction the src is read until an end of file condition is encountered or until buffsize bytes have been read. EOF is signaled by an empty string returned by src's read method. Instances then behave like readable streams transparently reading from the buffer or from the remainder of the src as applicable. Instances behave differently depending on whether or not the entire src is buffered. If it is they become seekable and set a value for the length attribute. Otherwise they are not seekable and the length attribute is None. If src is a non-blocking data source and it becomes blocked, indicated by read returning None rather than an empty string, then the instance reverts to non-seekable behaviour.""" def __init__(self, src, buffsize=io.DEFAULT_BUFFER_SIZE): self.src = src self.buff = io.BytesIO() self.bsize = 0 self.overflow = False self.length = None while True: nbytes = buffsize - self.bsize if nbytes <= 0: # we've run out of buffer space self.overflow = True break data = src.read(nbytes) if data is None: # blocked, treat as overflow self.overflow = True break elif data: self.buff.write(data) self.bsize += len(data) else: # EOF break self.pos = 0 self.buff.seek(0) if not self.overflow: self.length = self.bsize def readable(self): return True def writable(self): return False def seekable(self): return not self.overflow def tell(self): if self.overflow: raise io.UnsupportedOperation else: return self.pos def seek(self, offset, whence=io.SEEK_SET): if self.overflow: raise io.UnsupportedOperation elif whence == io.SEEK_SET: self.pos = offset elif whence == io.SEEK_CUR: self.pos += offset elif whence == io.SEEK_END: self.pos = self.length + offset else: raise ValueError("unrecognized whence value in seek: %s" % repr(whence)) self.buff.seek(self.pos) def readinto(self, b): if self.pos < self.bsize: # read from the buffer data = self.buff.read(len(b)) elif self.overflow: # read from the original source data = self.src.read(len(b)) if data is None: # handle blocked read return None else: # end of file data = b'' self.pos += len(data) b[0:len(data)] = data return len(data) def peek(self, nbytes): """Read up to nbytes without advancing the position If the stream is not seekable and we have read past the end of the internal buffer then an empty string will be returned.""" if self.pos < self.bsize: data = self.buff.read(nbytes) # reset the position of the buffer self.buff.seek(self.pos) return data else: return b'' class Pipe(io.RawIOBase): """Buffered pipe for inter-thread communication The purpose of this class is to provide a thread-safe buffer to use for communicating between two parts of an application that support non-blocking io while reducing to a minimum the amount of byte-copying that takes place. Essentially, write calls with immutable byte strings are simply cached without copying (and always succeed) enabling them to be passed directly through to the corresponding read operation in streaming situations. However, to improve flow control a canwrite method is provided to help writers moderate the amount of data that has to be held in the buffer:: # data producer thread while busy: wmax = p.canwrite() if wmax: data = get_at_most_max_bytes(wmax) p.write(data) else: # do something else while the pipe is blocked spin_the_beach_ball() bsize The buffer size, this is used as a guide only. When writing immutable bytes objects to the pipe the buffer size may be exceeded as these can simply be cached and returned directly to the reader more efficiently than slicing them up just to adhere to the buffer size. However, if the buffer already contains bsize bytes all calls to write will block or return None. Defaults to io.DEFAULT_BUFFER_SIZE. rblocking Controls the blocking behaviour of the read end of this pipe. True indicates reads may block waiting for data, False that they will not and read may return None. Defaults to True. wblocking Controls the blocking behaviour of the write end of the this pipe. True indicates writes may block waiting for data, False that they will not and write may return None. Defaults to True. timeout The number of seconds before a blocked read or write operation will timeout. Defaults to None, which indicates 'wait forever'. A value of 0 is not the same as placing both ends of the pipe in non-blocking mode (though the effect may be similar). name An optional name to use for this pipe, the name is used when raising errors and when logging""" def __init__(self, bsize=io.DEFAULT_BUFFER_SIZE, rblocking=True, wblocking=True, timeout=None, name=None): #: the name of the pipe self.name = name # the maximum buffer size, used for flow control, this # is not a hard limit self.max = bsize # buffered strings of bytes self.buffer = [] # the total size of all strings in the buffer self.bsize = 0 # offset into self.buffer[0] self.rpos = 0 # eof indicator self._eof = False self.rblocking = rblocking # an Event that flags the arrival of a reader self.rflag = None self.wblocking = wblocking # timeout duration self.timeout = timeout # lock for multi-threading self.lock = threading.Condition() # state values used for monitoring changes self.wstate = 0 self.rstate = 0 super(Pipe, self).__init__() def __repr__(self): if self.name: return self.name else: return super(Pipe, self).__repr__() def close(self): """closed the Pipe This implementation works on a 'reader closes' principle. The writer should simply write the EOF marker to the Pipe (see :meth:`write_eof`. If the buffer still contains data when it is closed a warning is logged.""" # throw away all data logging.debug("Pipe.close %s", repr(self)) with self.lock: if self.buffer: logging.warning("Pipe.close for %s discarded non-empty buffer", repr(self)) self.buffer = [] self.bsize = 0 self.rpos = 0 self._eof = True # kill anyone waiting self.rstate += 1 self.wstate += 1 self.lock.notify_all() super(Pipe, self).close() # if someone is waiting for a reader - wake them as the reader # will never come if self.rflag is not None: self.rflag.set() def readable(self): """Pipe's are always readable""" return True def writable(self): """Pipe's are always writeable""" return True def readblocking(self): """Returns True if reads may block""" return self.rblocking def set_readblocking(self, blocking=True): """Sets the readblocking mode of the Pipe. blocking A boolean, defaults to True indicating that reads may block.""" with self.lock: self.rblocking = blocking def writeblocking(self): """Returns True if writes may block""" return self.wblocking def set_writeblocking(self, blocking=True): """Sets the writeblocking mode of the Pipe. blocking A boolean, defaults to True indicating that writes may block.""" with self.lock: self.wblocking = blocking def wait(self, timeout, method): if timeout is not None: tstart = time.time() with self.lock: while not method(): if timeout is None: twait = None else: twait = (tstart + timeout) - time.time() if twait < 0: logging.warning("Pipe.wait timedout on %s", repr(self)) raise IOError(errno.ETIMEDOUT, os.strerror(errno.ETIMEDOUT), "pyslet.http.server.Pipe.wait") logging.debug("Pipe.wait waiting for %s", repr(self)) self.lock.wait(twait) def empty(self): """Returns True if the buffer is currently empty""" with self.lock: if self.buffer: return False else: return True def buffered(self): """Returns the number of buffered bytes in the Pipe""" with self.lock: return self.bsize - self.rpos def canwrite(self): """Returns the number of bytes that can be written. This value is the number of bytes that can be written in a single non-blocking call to write. 0 indicates that the pipe's buffer is full. A call to write may accept more than this but *the next* call to write will always accept at least this many. This class is fully multithreaded so in situations where there are multiple threads writing this call is of limited use. If called on a pipe that has had the EOF mark written then IOError is raised.""" with self.lock: if self.closed or self._eof: raise IOError( errno.EPIPE, "canwrite: can't write past EOF on Pipe object") wlen = self.max - self.bsize + self.rpos if wlen <= 0: wlen = 0 if self.rflag is not None: self.rflag.clear() return wlen def set_rflag(self, rflag): """Sets an Event triggered when a reader is detected. rflag An Event instance from the threading module. The event will be set each time the Pipe is read. The flag may be cleared at any time by the caller but as a convenience it will always be cleared when :py:meth:`canwrite` returns 0. The purpose of this flag is to allow a writer to use a custom event to monitor whether or not the Pipe is ready to be written. If the Pipe is full then the writer will want to wait on this flag until a reader appears before attempting to write again. Therefore, when canwrite indicates that the buffer is full it makes sense that the flag is also cleared. If the pipe is closed then the event is set as a warning that the pipe will never be read. (The next call to write will then fail.)""" with self.lock: self.rflag = rflag if self.closed: self.rflag.set() def write_wait(self, timeout=None): """Waits for the pipe to become writable or raises IOError timeout Defaults to None: wait forever. Otherwise the maximum number of seconds to wait for.""" self.wait(timeout, self.canwrite) def flush_wait(self, timeout=None): """Waits for the pipe to become empty or raises IOError timeout Defaults to None: wait forever. Otherwise the maximum number of seconds to wait for.""" self.wait(timeout, self.empty) def canread(self): """Returns True if the next call to read will *not* block. False indicates that the pipe's buffer is empty and that a call to read will block. Note that if the buffer is empty but the EOF signal has been given with :py:meth:`write_eof` then canread returns True! The next call to read will not block but return an empty string indicating the EOF.""" with self.lock: if self.closed: raise IOError( errno.EPIPE, "can't read from a closed Pipe object") if self.buffer or self._eof: return True else: return False def read_wait(self, timeout=None): """Waits for the pipe to become readable or raises IOError timeout Defaults to None: wait forever. Otherwise the maximum number of seconds to wait for.""" self.wait(timeout, self.canread) def write(self, b): """writes data to the pipe The implementation varies depending on the type of b. If b is an immutable bytes object then it is accepted even if this overfills the internal buffer (as it is not actually copied). If b is a bytearray then data is copied, up to the maximum buffer size.""" if self.timeout is not None: tstart = time.time() with self.lock: if self.closed or self._eof: raise IOError(errno.EPIPE, "write: can't write past EOF on Pipe object") if isinstance(b, memoryview): # catch memory view objects here b = b.tobytes() wlen = self.max - self.bsize + self.rpos while wlen <= 0: # block on write or return None if self.wblocking: if self.timeout is None: twait = None else: twait = (tstart + self.timeout) - time.time() if twait < 0: logging.warning("Pipe.write timed out for %s", repr(self)) raise IOError(errno.ETIMEDOUT, os.strerror(errno.ETIMEDOUT), "pyslet.http.server.Pipe.write") logging.debug("Pipe.write waiting for %s", repr(self)) self.lock.wait(twait) # check for eof again! if self.closed or self._eof: raise IOError(errno.EPIPE, "write: EOF or pipe closed after wait") # recalculate the writable space wlen = self.max - self.bsize + self.rpos else: return None if isinstance(b, bytes): nbytes = len(b) if nbytes: self.buffer.append(b) self.bsize += nbytes self.wstate += 1 self.lock.notify_all() return nbytes elif isinstance(b, bytearray): nbytes = len(b) if nbytes > wlen: nbytes = wlen # partial copy, creates transient bytearray :( self.buffer.append(bytes(b[:nbytes])) else: self.buffer.append(bytes(b)) self.bsize += nbytes self.wstate += 1 self.lock.notify_all() return nbytes else: raise TypeError(repr(type(b))) def write_eof(self): """Writes the EOF flag to the Pipe Any waiting readers are notified and will wake to process the Pipe. After this call the Pipe will not accept any more data.""" with self.lock: self._eof = True self.wstate += 1 self.lock.notify_all() def flush(self): """flushes the Pipe The intention of flush to push any written data out to the destination, in this case the thread that is reading the data. In write-blocking mode this call will wait until the buffer is empty, though if the reader is idle for more than :attr:`timeout` seconds then it will raise IOError. In non-blocking mode it simple raises IOError with EWOULDBLOCK if the buffer is not empty. Given that flush is called automatically by :meth:`close` for classes that inherit from the base io classes our implementation of close discards the buffer rather than risk an exception.""" if self.timeout is not None: tstart = time.time() with self.lock: blen = self.bsize - self.rpos while self.buffer: if self.wblocking: if self.timeout is None: twait = None else: new_blen = self.bsize - self.rpos if new_blen < blen: # making progress, restart the clock blen = new_blen tstart = time.time() twait = (tstart + self.timeout) - time.time() if twait < 0: logging.warning("Pipe.flush timed out for %s", repr(self)) logging.debug("Pipe.flush found stuck data: %s", repr(self.buffer)) raise IOError(errno.ETIMEDOUT, os.strerror(errno.ETIMEDOUT), "pyslet.http.server.Pipe.flush") logging.debug("Pipe.flush waiting for %s", repr(self)) self.lock.wait(twait) else: raise io.BlockingIOError( errno.EWOULDBLOCK, "Pipe.flush write blocked on %s" % repr(self)) def readall(self): """Overridden to take care of non-blocking behaviour. Warning: readall always blocks until it has read EOF, regardless of the rblocking status of the Pipe. The problem is that, if the Pipe is set for non-blocking reads then we seem to have the choice of returning a partial read (and failing to signal that some of the data is still in the pipe) or raising an error and losing the partially read data. Perhaps ideally we'd return None indicating that we are blocked from reading the entire stream but this isn't listed as a possible return result for io.RawIOBase.readall and it would be tricky to implement anyway as we still need to deal with partially read data. Ultimately the safe choices are raise an error if called on a non-blocking Pipe or simply block. We do the latter on the basis that anyone calling readall clearly intends to wait. For a deep discussion of the issues around non-blocking behaviour see http://bugs.python.org/issue13322""" data = [] with self.lock: save_rblocking = self.rblocking try: self.rblocking = True while True: part = self.read(io.DEFAULT_BUFFER_SIZE) if not part: # end of stream return b''.join(data) else: data.append(part) finally: self.rlocking = save_rblocking def _consolidate_buffer(self): with self.lock: if self.buffer: if self.rpos: self.buffer[0] = self.buffer[0][self.rpos:] self.rpos = 0 self.buffer = [b''.join(self.buffer)] def readmatch(self, match=b'\r\n'): """Read until a byte string is matched match A binary string, defaults to CRLF. This operation will block if the string is not matched unless the buffer becomes full without a match, in which case IOError is raised with code ENOBUFS.""" with self.lock: pos = -1 while pos < 0: if self.buffer: # take care of a special case first pos = self.buffer[0].find(match, self.rpos) if pos < 0: # otherwise consolidate the buffer self._consolidate_buffer() pos = self.buffer[0].find(match) # rpos is now 0 if pos >= 0: src = self.buffer[0] result = src[self.rpos:pos + len(match)] self.rpos += len(result) if self.rpos >= len(src): # discard src self.buffer = self.buffer[1:] self.bsize = self.bsize - len(src) self.rpos = 0 self.rstate += 1 # success, set the reader flag if self.rflag is not None: self.rflag.set() self.lock.notify_all() return result else: if self._eof: return b'' # not found, should we block? if self.canwrite(): # no match, but the buffer is not full so # set the reader flag to indicate that we # are now waiting to accept data. if self.rflag is not None: self.rflag.set() if self.rblocking: # we wait for something to happen on the # Pipe hopefully a write operation! cstate = self.wstate logging.debug("Pipe.readmatch waiting for %s", repr(self)) self.lock.wait(self.timeout) if self.wstate == cstate: logging.warning( "Pipe.readmatch timed out for %s", repr(self)) raise IOError( errno.ETIMEDOUT, os.strerror(errno.ETIMEDOUT), "pyslet.http.server.Pipe.readmatch") # go round the loop again else: # non-blocking readmatch returns None return None else: # we can't write so no point in waiting raise IOError(errno.ENOBUFS, os.strerror(errno.ENOBUFS), "pyslet.http.server.Pipe.readmatch") def read(self, nbytes=-1): """read data from the pipe May return fewer than nbytes if the result can be returned without copying data. Otherwise :meth:`readinto` is used.""" if nbytes < 0: return self.readall() else: with self.lock: if self.buffer and self.rpos == 0: # take care of one special case src = self.buffer[0] if len(src) <= nbytes: self.buffer = self.buffer[1:] self.bsize = self.bsize - len(src) self.rstate += 1 # successful read if self.rflag is not None: self.rflag.set() self.lock.notify_all() return src b = bytearray(nbytes) nbytes = self.readinto(b) if nbytes is None: return None else: return bytes(b[:nbytes]) def readinto(self, b): """Reads data from the Pipe into a bytearray. Returns the number of bytes read. 0 indicates EOF, None indicates an operation that would block in a Pipe that is non-blocking for read operations. May return fewer bytes than would fit into the bytearray as it returns as soon as it has at least some data.""" if self.timeout is not None: tstart = time.time() with self.lock: nbytes = len(b) # we're now reading if self.rflag is not None: self.rflag.set() while not self.buffer: if self._eof: return 0 elif self.rblocking: if self.timeout is None: twait = None else: twait = (tstart + self.timeout) - time.time() if twait < 0: logging.warning("Pipe.read timed out for %s", repr(self)) raise IOError(errno.ETIMEDOUT, os.strerror(errno.ETIMEDOUT), "pyslet.http.server.Pipe.read") logging.debug("Pipe.read waiting for %s", repr(self)) self.lock.wait(twait) else: return None src = self.buffer[0] rlen = len(src) - self.rpos if rlen < nbytes: nbytes = rlen if nbytes: b[:nbytes] = src[self.rpos:self.rpos + nbytes] self.rpos += nbytes if self.rpos >= len(src): # discard src self.buffer = self.buffer[1:] self.bsize = self.bsize - len(src) self.rpos = 0 if nbytes: self.rstate += 1 self.lock.notify_all() return nbytes

UTF-8

Python

false

28,375

py

132

streams.py

101

0.530044

0.52793

0

750

36.833333

79

rrsilaya/springer_books

11,854,109,750,593

0158b56aace7fda6db770cab22e3486d94f2b7d1

cf865985f3513142725904ec4297ef189563ce74

/downloader.py

c0e411ec2dcdf28bee76ae9214606e76eda6eafa

[]

no_license

https://github.com/rrsilaya/springer_books

95ed77605e43f09fb0e223154888d76c20d77163

26d83f3f2696d0d1eaf57171a439bfd33ae0ac21

refs/heads/master

2022-05-29T04:34:30.269377

2020-04-27T12:05:36

259,287,721

0

null

true

2020-04-27T11:01:11

2020-04-27T11:01:10

2020-04-27T08:54:36

2020-04-27T03:32:16

87

0

null

false

import csv import os, sys from axel import axel if not os.path.exists('Books'): os.mkdir('Books') elif not os.path.isdir('Books'): print('Error: a file named "Books" cannot be in the execution directory.') sys.exit(0) links = 'downloads.csv' with open(links) as file: reader = csv.reader(file, delimiter=',') for idx, row in enumerate(reader): print('%i: [%s] Downloading %s' % (idx + 1, row[0], row[1])) os.system('wget %s -O "Books/[%s] %s.pdf"' % (row[2], row[0], row[1]))

UTF-8

Python

false

516

py

4

downloader.py

1

0.612403

0.598837

0

18

27.666667

78

GinormousSalmon/SC2020

18,760,417,176,001

4bae90ea50eb9787d74c35107f87437152af7a7d

42e332e06748752ef38514ee30f16221533fcca7

/examples/encoding_test.py

d4e0bcaf6f937886360daec236d8a3726980b34c

[]

no_license

https://github.com/GinormousSalmon/SC2020

a082baece81dd65bd41b45dd33967ebbcc493aa7

6ac3a1807e35dc673654dd97d7bf5a7601d12b7b

refs/heads/master

2022-10-18T17:34:51.251938

2020-06-08T15:45:23

259,367,410

0

null

string = "кок" enc = str(string.encode('utf-8')) print(enc) dec = (enc).decode('utf-8') print(dec)

UTF-8

Python

false

102

py

27

encoding_test.py

18

0.636364

0.616162

0

5

18.8

33

justanhduc/AugmentedCycleGAN

7,017,976,583,936

0f8ec0809d50d8c69f7fb9051ac75b99be3444b6

632d82d996d8b0d3dc14317ee6e7b3db6712dc78

/train.py

35921d02fed385e3f998ca6e0ca0ae8b90ef2590

[ "Unlicense" ]

permissive

https://github.com/justanhduc/AugmentedCycleGAN

1df2c97d5cb267c7a4e60bcd6ab7bdd9223e3977

4a83c2a370842a713ec1d7ebf20cbd71f4039093

refs/heads/master

2020-04-11T06:45:11.512754

2018-12-13T06:23:25

161,590,717

2

0

null

import argparse parser = argparse.ArgumentParser('Augmented CycleGAN') parser.add_argument('--test', action='store_true', default=False, help='Train or test') parser.add_argument('--latent_dim', type=int, default=16, help='Latent dimension') parser.add_argument('--n_gen_filters', type=int, default=32, help='Number of initial filters in generators') parser.add_argument('--n_dis_filters', type=int, default=64, help='Number of initial filters in discriminators') parser.add_argument('--n_enc_filters', type=int, default=32, help='Number of initial filters in encoders') parser.add_argument('--use_dropout', action='store_true', default=False, help='Whether to use dropout in conditional resblock') parser.add_argument('--use_sigmoid', action='store_true', default=False, help='Whether to use orginal sigmoid GAN') parser.add_argument('--use_latent_gan', action='store_true', default=False, help='Whether to use GAN on latent codes') parser.add_argument('--bs', type=int, default=80, help='Batchsize') parser.add_argument('--lr', type=float, default=2e-4, help='Learning rate') parser.add_argument('--lambda_A', type=float, default=1., help='Weight for cycle loss of domain A') parser.add_argument('--lambda_B', type=float, default=1., help='Weight for cycle loss of domain B') parser.add_argument('--lambda_z_B', type=float, default=.025, help='Weight for cycle loss of latent of B') parser.add_argument('--max_norm', type=float, default=500., help='Maximum gradient norm') parser.add_argument('--beta1', type=float, default=.5, help='Momentum coefficient') parser.add_argument('--n_epochs', type=int, default=25, help='Number of training epochs without lr decay') parser.add_argument('--n_epochs_decay', type=int, default=25, help='Number of training epochs with lr decay') parser.add_argument('--print_freq', type=int, default=200, help='Logging frequency') parser.add_argument('--valid_freq', type=int, default=600, help='Validation frequency') parser.add_argument('--n_multi', type=int, default=10, help='Number of noise samples to generate multiple images given one image') parser.add_argument('--n_imgs_to_save', type=int, default=20, help='Number of images to save in each iteration') parser.add_argument('--gpu', type=int, default=0, help='Which GPU to be used') parser.add_argument('--param_file_version', type=int, default=-1, help='Weight file version to use to testing') args = parser.parse_args() import os os.environ['CUDA_VISIBLE_DEVICES'] = str(args.gpu) import neuralnet as nn from theano import tensor as T import numpy as np from networks import AugmentedCycleGAN from data_loader import Edges2Shoes, image_size testing = args.test latent_dim = args.latent_dim n_gen_filters = args.n_gen_filters n_dis_filters = args.n_dis_filters n_enc_filters = args.n_enc_filters use_dropout = args.use_dropout use_sigmoid = args.use_sigmoid use_latent_gan = args.use_latent_gan bs = args.bs lr = args.lr lambda_A = args.lambda_A lambda_B = args.lambda_B lambda_z_B = args.lambda_z_B max_norm = args.max_norm beta1 = args.beta1 n_epochs = args.n_epochs n_epochs_decay = args.n_epochs_decay print_freq = args.print_freq valid_freq = args.valid_freq n_multi = args.n_multi n_imgs_to_save = args.n_imgs_to_save # for testing param_file_version = args.param_file_version def unnormalize(x): return x / 2. + .5 def pre_process(x): downsample = nn.DownsamplingLayer((None, 3, image_size * 4, image_size * 4), 4) return downsample(x.dimshuffle(0, 3, 1, 2)) / 255. * 2. - 1. def train(): X_A_full = T.tensor4('A') X_B_full = T.tensor4('B') X_A = pre_process(X_A_full) X_B = pre_process(X_B_full) z = nn.utils.srng.normal((bs, latent_dim)) idx = T.scalar('iter') X_A_ = nn.placeholder((bs, 3, image_size*4, image_size*4), name='A_plhd') X_B_ = nn.placeholder((bs, 3, image_size*4, image_size*4), name='B_plhd') lr_ = nn.placeholder(value=lr, name='lr_plhd') net = AugmentedCycleGAN((None, 3, image_size, image_size), latent_dim, n_gen_filters, n_dis_filters, n_enc_filters, 3, use_dropout, use_sigmoid, use_latent_gan) nn.set_training_on() updates_dis, updates_gen, dis_losses, dis_preds, gen_losses, grad_norms = net.learn(X_A, X_B, z, lambda_A, lambda_B, lambda_z_B, lr=lr_, beta1=beta1, max_norm=max_norm) train_dis = nn.function([], list(dis_losses.values()), updates=updates_dis, givens={X_A_full: X_A_, X_B_full: X_B_}, name='train discriminators') train_gen = nn.function([], list(gen_losses.values()), updates=updates_gen, givens={X_A_full: X_A_, X_B_full: X_B_}, name='train generators') discriminate = nn.function([], list(dis_preds.values()), givens={X_A_full: X_A_, X_B_full: X_B_}, name='discriminate') compute_grad_norms = nn.function([], list(grad_norms.values()), givens={X_A_full: X_A_, X_B_full: X_B_}, name='compute grad norms') nn.anneal_learning_rate(lr_, idx, 'linear', num_iters=n_epochs_decay) train_dis_decay = nn.function([idx], list(dis_losses.values()), updates=updates_dis, givens={X_A_full: X_A_, X_B_full: X_B_}, name='train discriminators with decay') nn.set_training_off() fixed_z = T.constant(np.random.normal(size=(bs, latent_dim)), dtype='float32') fixed_multi_z = T.constant(np.repeat(np.random.normal(size=(n_multi, latent_dim)), bs, 0), dtype='float32') visuals = net.generate_cycle(X_A, X_B, fixed_z) multi_fake_B = net.generate_multi(X_A, fixed_multi_z) visualize_single = nn.function([], list(visuals.values()), givens={X_A_full: X_A_, X_B_full: X_B_}, name='visualize single') visualize_multi = nn.function([], multi_fake_B, givens={X_A_full: X_A_}, name='visualize multi') train_data = Edges2Shoes((X_A_, X_B_), bs, n_epochs + n_epochs_decay + 1, 'train', True) val_data = Edges2Shoes((X_A_, X_B_), bs, 1, 'val', False, num_data=bs) mon = nn.Monitor(model_name='Augmented_CycleGAN', print_freq=print_freq) print('Training...') for it in train_data: epoch = 1 + it // (len(train_data) // bs) with mon: res_dis = train_dis() if epoch <= n_epochs else train_dis_decay(epoch - n_epochs) res_gen = train_gen() preds = discriminate() grads_ = compute_grad_norms() mon.plot('lr', lr_.get_value()) for j, k in enumerate(dis_losses.keys()): mon.plot(k, res_dis[j]) for j, k in enumerate(gen_losses.keys()): mon.plot(k, res_gen[j]) for j, k in enumerate(dis_preds.keys()): mon.hist(k, preds[j]) for j, k in enumerate(grad_norms.keys()): mon.plot(k, grads_[j]) if it % valid_freq == 0: for _ in val_data: vis_single = visualize_single() vis_multi = visualize_multi() for j, k in enumerate(visuals.keys()): mon.imwrite(k, vis_single[j][:n_imgs_to_save], callback=unnormalize) for j, fake_B in enumerate(vis_multi): mon.imwrite('fake_B_multi_%d.jpg' % j, fake_B, callback=unnormalize) mon.dump(nn.utils.shared2numpy(net.netG_A_B.params), 'gen_A_B.npy', 5) mon.dump(nn.utils.shared2numpy(net.netG_B_A.params), 'gen_B_A.npy', 5) mon.dump(nn.utils.shared2numpy(net.netD_A.params), 'dis_A.npy', 5) mon.dump(nn.utils.shared2numpy(net.netD_B.params), 'dis_B.npy', 5) mon.dump(nn.utils.shared2numpy(net.netE_B.params), 'enc_B.npy', 5) if use_latent_gan: mon.dump(nn.utils.shared2numpy(net.netD_z_B.params), 'dis_z_B.npy', 5) mon.flush() mon.dump(nn.utils.shared2numpy(net.netG_A_B.params), 'gen_A_B.npy') mon.dump(nn.utils.shared2numpy(net.netG_B_A.params), 'gen_B_A.npy') mon.dump(nn.utils.shared2numpy(net.netD_A.params), 'dis_A.npy') mon.dump(nn.utils.shared2numpy(net.netD_B.params), 'dis_B.npy') mon.dump(nn.utils.shared2numpy(net.netE_B.params), 'enc_B.npy') if use_latent_gan: mon.dump(nn.utils.shared2numpy(net.netD_z_B.params), 'dis_z_B.npy') print('Training finished!') if __name__ == '__main__': if testing: if args.param_file_version < 0: raise ValueError('A checkpoint version should be provided.') from test import test test() else: train()

UTF-8

Python

false

8,710

py

5

train.py

4

0.626406

0.615155

0

181

47.121547

130

UmashankarTriforce/CUDAImageManipulation

12,558,484,396,884

ab5c19bfd289ffff0ff61ce9ff49d2e8875d101e

2bb157ac4f3b5e53cdf2a06c9a0b858d5c3ec938

/gpu/server.py

fb2b28ba48a83e804c7b3b3968ce5d7a21043f27

[]

no_license

https://github.com/UmashankarTriforce/CUDAImageManipulation

983a3eb1988a70e6ec062a422078bb84cc9b134a

f281c09fa1845331b6f66c1505d120e819eecc78

refs/heads/master

2023-01-09T18:41:05.904684

2019-12-08T04:11:21

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2023-01-04T05:04:12

2019-07-02T17:45:44

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from flask import Flask, request, jsonify, Response from flops import work import pycuda.driver as cuda app = Flask(__name__) def initialize(): cuda.init() DeviceID = 0 device = cuda.Device(DeviceID) ctx = device.make_context() return ctx def destroy(ctx): ctx.pop() @app.route('/bench', methods = ["GET", "POST"]) def gauss(): content = request.json m = int(content['m']) k = int(content['k']) n = int(content['n']) ctx = initialize() out = work(m, k, n) output = { "Single" : out[0], "Double" : out[1] } destroy(ctx) return jsonify(output) app.run('0.0.0.0',debug=True, port = 80)

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paepcke/tableauNetworkLayout

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/setup.py

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[]

no_license

https://github.com/paepcke/tableauNetworkLayout

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refs/heads/master

2021-08-17T06:28:05.024486

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import multiprocessing from setuptools import setup, find_packages setup( name = "tableauNetworkLayout", version = "0.01", packages = find_packages(), # Dependencies on other packages: # Couldn't get numpy install to work without # an out-of-band: sudo apt-get install python-dev setup_requires = ['nose>=1.1.2'], install_requires = ['networkx>=2.0', 'numpy>=1.13.3', 'configparser>=3.3.0r2', 'argparse>=1.2.1', ], tests_require = ['sentinels>=0.0.6', 'nose>=1.0'], # Unit tests; they are initiated via 'python setup.py test' #test_suite = 'json_to_relation/test', test_suite = 'nose.collector', package_data = { # If any package contains *.txt or *.rst files, include them: # '': ['*.txt', '*.rst'], # And include any *.msg files found in the 'hello' package, too: # 'hello': ['*.msg'], }, # metadata for upload to PyPI author = "Andreas Paepcke", #author_email = "me@example.com", description = "Lays out nodes of a small network for visualization in Tableau.", license = "BSD", keywords = "network, nodes, layout", url = "git@github.com/tableauNetworkLayout", # project home page, if any )

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dwaipayanbiswas2017/photo_uploader

4,355,096,849,499

a053af7154558c353297b4f20a33c0b99d8d4e43

bdfb9ede57cf273d92e4ab5c0d483907a3c2a6a9

/index.py

832c4aaf4b660bfd232951c220aa7bb5f083ca21

[]

no_license

https://github.com/dwaipayanbiswas2017/photo_uploader

98548a10fdbd3938f87f03e10997ac9fd39d5638

5a1eb006fff9551e0354badfb4968d4a5bb805cd

refs/heads/master

2020-08-10T02:57:56.234829

2019-10-10T15:30:00

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2019-10-10T17:05:22

2019-10-10T17:05:21

2019-10-10T17:03:07

2019-10-10T15:32:06

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from PyQt5 import uic from PyQt5.QtWidgets import * import sys UI_file = "ui.ui" class PhotoUploader(QMainWindow): def __init__(self, ui_file): super(PhotoUploader, self).__init__() uic.loadUi('ui.ui', self) self.setFixedSize(self.size()) self.console_data = "" self.tabs = self.findChild(QTabWidget, "tabWidget") self.browse_btn = self.findChild(QPushButton, "BrowseButton") self.select_tab_next_btn = self.findChild(QPushButton, "Select_tab_next_btn") self.list_view = self.findChild(QTextEdit, "textEdit_3") self.console = self.findChild(QTextEdit, "console") self.browse_btn.clicked.connect(self.file_browse_event) self.select_tab_next_btn.clicked.connect(lambda: self.tab_next_event(1)) self.add_console_data("Photo Uploader By Python", "white", 'c') self.show() def file_browse_event(self): files = QFileDialog.getOpenFileNames() print(files[0]) file_list = "" index = 1 for file in files[0]: f = file.split("/")[-1] print(f) file_list += str(index) + " : " + str(f) + "\n" index += 1 self.list_view.setText(file_list) def tab_next_event(self,tab_num): QTabWidget.setCurrentIndex(self.tabs, tab_num) def add_console_data(self, text, color='white', alignment='l'): f_alignment = "" if alignment == 'c' or alignment == 'C': f_alignment = "align = 'center'" elif alignment == 'r' or alignment == 'R': f_alignment = "align = 'right'" elif alignment == 'j' or alignment == 'J': f_alignment = "align = 'justify'" else: f_alignment = "align = 'left'" f_color = 'color:' + color prefix = "<!DOCTYPE HTML PUBLIC '-//W3C//DTD HTML 4.0//EN' 'http://www.w3.org/TR/REC-html40/strict.dtd'>" \ "<html><head><meta name='qrichtext' content='1' /><style type='text/css'>" \ "p, li { white-space: pre-wrap; }</style></head>" \ "<body style='font-size:11pt;font-weight:400; font-style:normal;'bgcolor='#04242F'>" suffix = "</body></html>" self.console_data += "<p " + f_alignment + " style='margin-top:12px; margin-bottom:12px; " \ "margin-left:0px; margin-right:0px; -qt-block-indent:0;" \ "text-indent:0px;'><span style='font-weight:600; " + f_color + ";'>" self.console_data += str(text) self.console_data += "</span></p>" self.console.setText(prefix + self.console_data + suffix) scroll = self.console.verticalScrollBar() scroll.setValue(scroll.maximum()) if __name__ == '__main__': app = QApplication(sys.argv) biometric = PhotoUploader(UI_file) sys.exit(app.exec_())

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smartxworks/cloudtower-python-sdk

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873551a415af1ed5270e3281910b07beb15afbdf

/cloudtower/models/content_library_vm_template_where_input.py

5a3a6fce13513df5beb476f22261ada686e9f4d5

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permissive

https://github.com/smartxworks/cloudtower-python-sdk

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da8cdca0e869278f83d33207b1fc77c6d785ac15

refs/heads/master

2023-08-08T07:49:10.503674

2023-08-01T11:38:37

2023-08-01T11:39:41

438,103,300

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ISC

false

2023-09-01T03:36:45

2021-12-14T03:22:32

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# coding: utf-8 try: from inspect import getfullargspec except ImportError: from inspect import getargspec as getfullargspec import pprint import re # noqa: F401 import six from cloudtower.configuration import Configuration class ContentLibraryVmTemplateWhereInput(object): """NOTE: This class is auto generated by OpenAPI Generator. Ref: https://openapi-generator.tech Do not edit the class manually. """ """ Attributes: openapi_types (dict): The key is attribute name and the value is attribute type. attribute_map (dict): The key is attribute name and the value is json key in definition. """ openapi_types = { '_and': 'list[ContentLibraryVmTemplateWhereInput]', 'architecture': 'Architecture', 'architecture_in': 'list[Architecture]', 'architecture_not': 'Architecture', 'architecture_not_in': 'list[Architecture]', 'cloud_init_supported': 'bool', 'cloud_init_supported_not': 'bool', 'clusters_every': 'ClusterWhereInput', 'clusters_none': 'ClusterWhereInput', 'clusters_some': 'ClusterWhereInput', 'created_at': 'str', 'created_at_gt': 'str', 'created_at_gte': 'str', 'created_at_in': 'list[str]', 'created_at_lt': 'str', 'created_at_lte': 'str', 'created_at_not': 'str', 'created_at_not_in': 'list[str]', 'description': 'str', 'description_contains': 'str', 'description_ends_with': 'str', 'description_gt': 'str', 'description_gte': 'str', 'description_in': 'list[str]', 'description_lt': 'str', 'description_lte': 'str', 'description_not': 'str', 'description_not_contains': 'str', 'description_not_ends_with': 'str', 'description_not_in': 'list[str]', 'description_not_starts_with': 'str', 'description_starts_with': 'str', 'entity_async_status': 'EntityAsyncStatus', 'entity_async_status_in': 'list[EntityAsyncStatus]', 'entity_async_status_not': 'EntityAsyncStatus', 'entity_async_status_not_in': 'list[EntityAsyncStatus]', 'id': 'str', 'id_contains': 'str', 'id_ends_with': 'str', 'id_gt': 'str', 'id_gte': 'str', 'id_in': 'list[str]', 'id_lt': 'str', 'id_lte': 'str', 'id_not': 'str', 'id_not_contains': 'str', 'id_not_ends_with': 'str', 'id_not_in': 'list[str]', 'id_not_starts_with': 'str', 'id_starts_with': 'str', 'labels_every': 'LabelWhereInput', 'labels_none': 'LabelWhereInput', 'labels_some': 'LabelWhereInput', 'memory': 'int', 'memory_gt': 'int', 'memory_gte': 'int', 'memory_in': 'list[int]', 'memory_lt': 'int', 'memory_lte': 'int', 'memory_not': 'int', 'memory_not_in': 'list[int]', 'name': 'str', 'name_contains': 'str', 'name_ends_with': 'str', 'name_gt': 'str', 'name_gte': 'str', 'name_in': 'list[str]', 'name_lt': 'str', 'name_lte': 'str', 'name_not': 'str', 'name_not_contains': 'str', 'name_not_ends_with': 'str', 'name_not_in': 'list[str]', 'name_not_starts_with': 'str', 'name_starts_with': 'str', '_not': 'list[ContentLibraryVmTemplateWhereInput]', '_or': 'list[ContentLibraryVmTemplateWhereInput]', 'os': 'str', 'os_contains': 'str', 'os_ends_with': 'str', 'os_gt': 'str', 'os_gte': 'str', 'os_in': 'list[str]', 'os_lt': 'str', 'os_lte': 'str', 'os_not': 'str', 'os_not_contains': 'str', 'os_not_ends_with': 'str', 'os_not_in': 'list[str]', 'os_not_starts_with': 'str', 'os_starts_with': 'str', 'size': 'int', 'size_gt': 'int', 'size_gte': 'int', 'size_in': 'list[int]', 'size_lt': 'int', 'size_lte': 'int', 'size_not': 'int', 'size_not_in': 'list[int]', 'vcpu': 'int', 'vcpu_gt': 'int', 'vcpu_gte': 'int', 'vcpu_in': 'list[int]', 'vcpu_lt': 'int', 'vcpu_lte': 'int', 'vcpu_not': 'int', 'vcpu_not_in': 'list[int]', 'vm_templates_every': 'VmTemplateWhereInput', 'vm_templates_none': 'VmTemplateWhereInput', 'vm_templates_some': 'VmTemplateWhereInput' } attribute_map = { '_and': 'AND', 'architecture': 'architecture', 'architecture_in': 'architecture_in', 'architecture_not': 'architecture_not', 'architecture_not_in': 'architecture_not_in', 'cloud_init_supported': 'cloud_init_supported', 'cloud_init_supported_not': 'cloud_init_supported_not', 'clusters_every': 'clusters_every', 'clusters_none': 'clusters_none', 'clusters_some': 'clusters_some', 'created_at': 'createdAt', 'created_at_gt': 'createdAt_gt', 'created_at_gte': 'createdAt_gte', 'created_at_in': 'createdAt_in', 'created_at_lt': 'createdAt_lt', 'created_at_lte': 'createdAt_lte', 'created_at_not': 'createdAt_not', 'created_at_not_in': 'createdAt_not_in', 'description': 'description', 'description_contains': 'description_contains', 'description_ends_with': 'description_ends_with', 'description_gt': 'description_gt', 'description_gte': 'description_gte', 'description_in': 'description_in', 'description_lt': 'description_lt', 'description_lte': 'description_lte', 'description_not': 'description_not', 'description_not_contains': 'description_not_contains', 'description_not_ends_with': 'description_not_ends_with', 'description_not_in': 'description_not_in', 'description_not_starts_with': 'description_not_starts_with', 'description_starts_with': 'description_starts_with', 'entity_async_status': 'entityAsyncStatus', 'entity_async_status_in': 'entityAsyncStatus_in', 'entity_async_status_not': 'entityAsyncStatus_not', 'entity_async_status_not_in': 'entityAsyncStatus_not_in', 'id': 'id', 'id_contains': 'id_contains', 'id_ends_with': 'id_ends_with', 'id_gt': 'id_gt', 'id_gte': 'id_gte', 'id_in': 'id_in', 'id_lt': 'id_lt', 'id_lte': 'id_lte', 'id_not': 'id_not', 'id_not_contains': 'id_not_contains', 'id_not_ends_with': 'id_not_ends_with', 'id_not_in': 'id_not_in', 'id_not_starts_with': 'id_not_starts_with', 'id_starts_with': 'id_starts_with', 'labels_every': 'labels_every', 'labels_none': 'labels_none', 'labels_some': 'labels_some', 'memory': 'memory', 'memory_gt': 'memory_gt', 'memory_gte': 'memory_gte', 'memory_in': 'memory_in', 'memory_lt': 'memory_lt', 'memory_lte': 'memory_lte', 'memory_not': 'memory_not', 'memory_not_in': 'memory_not_in', 'name': 'name', 'name_contains': 'name_contains', 'name_ends_with': 'name_ends_with', 'name_gt': 'name_gt', 'name_gte': 'name_gte', 'name_in': 'name_in', 'name_lt': 'name_lt', 'name_lte': 'name_lte', 'name_not': 'name_not', 'name_not_contains': 'name_not_contains', 'name_not_ends_with': 'name_not_ends_with', 'name_not_in': 'name_not_in', 'name_not_starts_with': 'name_not_starts_with', 'name_starts_with': 'name_starts_with', '_not': 'NOT', '_or': 'OR', 'os': 'os', 'os_contains': 'os_contains', 'os_ends_with': 'os_ends_with', 'os_gt': 'os_gt', 'os_gte': 'os_gte', 'os_in': 'os_in', 'os_lt': 'os_lt', 'os_lte': 'os_lte', 'os_not': 'os_not', 'os_not_contains': 'os_not_contains', 'os_not_ends_with': 'os_not_ends_with', 'os_not_in': 'os_not_in', 'os_not_starts_with': 'os_not_starts_with', 'os_starts_with': 'os_starts_with', 'size': 'size', 'size_gt': 'size_gt', 'size_gte': 'size_gte', 'size_in': 'size_in', 'size_lt': 'size_lt', 'size_lte': 'size_lte', 'size_not': 'size_not', 'size_not_in': 'size_not_in', 'vcpu': 'vcpu', 'vcpu_gt': 'vcpu_gt', 'vcpu_gte': 'vcpu_gte', 'vcpu_in': 'vcpu_in', 'vcpu_lt': 'vcpu_lt', 'vcpu_lte': 'vcpu_lte', 'vcpu_not': 'vcpu_not', 'vcpu_not_in': 'vcpu_not_in', 'vm_templates_every': 'vm_templates_every', 'vm_templates_none': 'vm_templates_none', 'vm_templates_some': 'vm_templates_some' } def __init__(self, **kwargs): # noqa: E501 """ContentLibraryVmTemplateWhereInput - a model defined in OpenAPI""" # noqa: E501 self.local_vars_configuration = kwargs.get("local_vars_configuration", Configuration.get_default_copy()) self.__and = None self._architecture = None self._architecture_in = None self._architecture_not = None self._architecture_not_in = None self._cloud_init_supported = None self._cloud_init_supported_not = None self._clusters_every = None self._clusters_none = None self._clusters_some = None self._created_at = None self._created_at_gt = None self._created_at_gte = None self._created_at_in = None self._created_at_lt = None self._created_at_lte = None self._created_at_not = None self._created_at_not_in = None self._description = None self._description_contains = None self._description_ends_with = None self._description_gt = None self._description_gte = None self._description_in = None self._description_lt = None self._description_lte = None self._description_not = None self._description_not_contains = None self._description_not_ends_with = None self._description_not_in = None self._description_not_starts_with = None self._description_starts_with = None self._entity_async_status = None self._entity_async_status_in = None self._entity_async_status_not = None self._entity_async_status_not_in = None self._id = None self._id_contains = None self._id_ends_with = None self._id_gt = None self._id_gte = None self._id_in = None self._id_lt = None self._id_lte = None self._id_not = None self._id_not_contains = None self._id_not_ends_with = None self._id_not_in = None self._id_not_starts_with = None self._id_starts_with = None self._labels_every = None self._labels_none = None self._labels_some = None self._memory = None self._memory_gt = None self._memory_gte = None self._memory_in = None self._memory_lt = None self._memory_lte = None self._memory_not = None self._memory_not_in = None self._name = None self._name_contains = None self._name_ends_with = None self._name_gt = None self._name_gte = None self._name_in = None self._name_lt = None self._name_lte = None self._name_not = None self._name_not_contains = None self._name_not_ends_with = None self._name_not_in = None self._name_not_starts_with = None self._name_starts_with = None self.__not = None self.__or = None self._os = None self._os_contains = None self._os_ends_with = None self._os_gt = None self._os_gte = None self._os_in = None self._os_lt = None self._os_lte = None self._os_not = None self._os_not_contains = None self._os_not_ends_with = None self._os_not_in = None self._os_not_starts_with = None self._os_starts_with = None self._size = None self._size_gt = None self._size_gte = None self._size_in = None self._size_lt = None self._size_lte = None self._size_not = None self._size_not_in = None self._vcpu = None self._vcpu_gt = None self._vcpu_gte = None self._vcpu_in = None self._vcpu_lt = None self._vcpu_lte = None self._vcpu_not = None self._vcpu_not_in = None self._vm_templates_every = None self._vm_templates_none = None self._vm_templates_some = None self.discriminator = None self._and = kwargs.get("_and", None) self.architecture = kwargs.get("architecture", None) self.architecture_in = kwargs.get("architecture_in", None) self.architecture_not = kwargs.get("architecture_not", None) self.architecture_not_in = kwargs.get("architecture_not_in", None) self.cloud_init_supported = kwargs.get("cloud_init_supported", None) self.cloud_init_supported_not = kwargs.get("cloud_init_supported_not", None) self.clusters_every = kwargs.get("clusters_every", None) self.clusters_none = kwargs.get("clusters_none", None) self.clusters_some = kwargs.get("clusters_some", None) self.created_at = kwargs.get("created_at", None) self.created_at_gt = kwargs.get("created_at_gt", None) self.created_at_gte = kwargs.get("created_at_gte", None) self.created_at_in = kwargs.get("created_at_in", None) self.created_at_lt = kwargs.get("created_at_lt", None) self.created_at_lte = kwargs.get("created_at_lte", None) self.created_at_not = kwargs.get("created_at_not", None) self.created_at_not_in = kwargs.get("created_at_not_in", None) self.description = kwargs.get("description", None) self.description_contains = kwargs.get("description_contains", None) self.description_ends_with = kwargs.get("description_ends_with", None) self.description_gt = kwargs.get("description_gt", None) self.description_gte = kwargs.get("description_gte", None) self.description_in = kwargs.get("description_in", None) self.description_lt = kwargs.get("description_lt", None) self.description_lte = kwargs.get("description_lte", None) self.description_not = kwargs.get("description_not", None) self.description_not_contains = kwargs.get("description_not_contains", None) self.description_not_ends_with = kwargs.get("description_not_ends_with", None) self.description_not_in = kwargs.get("description_not_in", None) self.description_not_starts_with = kwargs.get("description_not_starts_with", None) self.description_starts_with = kwargs.get("description_starts_with", None) self.entity_async_status = kwargs.get("entity_async_status", None) self.entity_async_status_in = kwargs.get("entity_async_status_in", None) self.entity_async_status_not = kwargs.get("entity_async_status_not", None) self.entity_async_status_not_in = kwargs.get("entity_async_status_not_in", None) self.id = kwargs.get("id", None) self.id_contains = kwargs.get("id_contains", None) self.id_ends_with = kwargs.get("id_ends_with", None) self.id_gt = kwargs.get("id_gt", None) self.id_gte = kwargs.get("id_gte", None) self.id_in = kwargs.get("id_in", None) self.id_lt = kwargs.get("id_lt", None) self.id_lte = kwargs.get("id_lte", None) self.id_not = kwargs.get("id_not", None) self.id_not_contains = kwargs.get("id_not_contains", None) self.id_not_ends_with = kwargs.get("id_not_ends_with", None) self.id_not_in = kwargs.get("id_not_in", None) self.id_not_starts_with = kwargs.get("id_not_starts_with", None) self.id_starts_with = kwargs.get("id_starts_with", None) self.labels_every = kwargs.get("labels_every", None) self.labels_none = kwargs.get("labels_none", None) self.labels_some = kwargs.get("labels_some", None) self.memory = kwargs.get("memory", None) self.memory_gt = kwargs.get("memory_gt", None) self.memory_gte = kwargs.get("memory_gte", None) self.memory_in = kwargs.get("memory_in", None) self.memory_lt = kwargs.get("memory_lt", None) self.memory_lte = kwargs.get("memory_lte", None) self.memory_not = kwargs.get("memory_not", None) self.memory_not_in = kwargs.get("memory_not_in", None) self.name = kwargs.get("name", None) self.name_contains = kwargs.get("name_contains", None) self.name_ends_with = kwargs.get("name_ends_with", None) self.name_gt = kwargs.get("name_gt", None) self.name_gte = kwargs.get("name_gte", None) self.name_in = kwargs.get("name_in", None) self.name_lt = kwargs.get("name_lt", None) self.name_lte = kwargs.get("name_lte", None) self.name_not = kwargs.get("name_not", None) self.name_not_contains = kwargs.get("name_not_contains", None) self.name_not_ends_with = kwargs.get("name_not_ends_with", None) self.name_not_in = kwargs.get("name_not_in", None) self.name_not_starts_with = kwargs.get("name_not_starts_with", None) self.name_starts_with = kwargs.get("name_starts_with", None) self._not = kwargs.get("_not", None) self._or = kwargs.get("_or", None) self.os = kwargs.get("os", None) self.os_contains = kwargs.get("os_contains", None) self.os_ends_with = kwargs.get("os_ends_with", None) self.os_gt = kwargs.get("os_gt", None) self.os_gte = kwargs.get("os_gte", None) self.os_in = kwargs.get("os_in", None) self.os_lt = kwargs.get("os_lt", None) self.os_lte = kwargs.get("os_lte", None) self.os_not = kwargs.get("os_not", None) self.os_not_contains = kwargs.get("os_not_contains", None) self.os_not_ends_with = kwargs.get("os_not_ends_with", None) self.os_not_in = kwargs.get("os_not_in", None) self.os_not_starts_with = kwargs.get("os_not_starts_with", None) self.os_starts_with = kwargs.get("os_starts_with", None) self.size = kwargs.get("size", None) self.size_gt = kwargs.get("size_gt", None) self.size_gte = kwargs.get("size_gte", None) self.size_in = kwargs.get("size_in", None) self.size_lt = kwargs.get("size_lt", None) self.size_lte = kwargs.get("size_lte", None) self.size_not = kwargs.get("size_not", None) self.size_not_in = kwargs.get("size_not_in", None) self.vcpu = kwargs.get("vcpu", None) self.vcpu_gt = kwargs.get("vcpu_gt", None) self.vcpu_gte = kwargs.get("vcpu_gte", None) self.vcpu_in = kwargs.get("vcpu_in", None) self.vcpu_lt = kwargs.get("vcpu_lt", None) self.vcpu_lte = kwargs.get("vcpu_lte", None) self.vcpu_not = kwargs.get("vcpu_not", None) self.vcpu_not_in = kwargs.get("vcpu_not_in", None) self.vm_templates_every = kwargs.get("vm_templates_every", None) self.vm_templates_none = kwargs.get("vm_templates_none", None) self.vm_templates_some = kwargs.get("vm_templates_some", None) @property def _and(self): """Gets the _and of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The _and of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: list[ContentLibraryVmTemplateWhereInput] """ return self.__and @_and.setter def _and(self, _and): """Sets the _and of this ContentLibraryVmTemplateWhereInput. :param _and: The _and of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type _and: list[ContentLibraryVmTemplateWhereInput] """ self.__and = _and @property def architecture(self): """Gets the architecture of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The architecture of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: Architecture """ return self._architecture @architecture.setter def architecture(self, architecture): """Sets the architecture of this ContentLibraryVmTemplateWhereInput. :param architecture: The architecture of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type architecture: Architecture """ self._architecture = architecture @property def architecture_in(self): """Gets the architecture_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The architecture_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: list[Architecture] """ return self._architecture_in @architecture_in.setter def architecture_in(self, architecture_in): """Sets the architecture_in of this ContentLibraryVmTemplateWhereInput. :param architecture_in: The architecture_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type architecture_in: list[Architecture] """ self._architecture_in = architecture_in @property def architecture_not(self): """Gets the architecture_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The architecture_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: Architecture """ return self._architecture_not @architecture_not.setter def architecture_not(self, architecture_not): """Sets the architecture_not of this ContentLibraryVmTemplateWhereInput. :param architecture_not: The architecture_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type architecture_not: Architecture """ self._architecture_not = architecture_not @property def architecture_not_in(self): """Gets the architecture_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The architecture_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: list[Architecture] """ return self._architecture_not_in @architecture_not_in.setter def architecture_not_in(self, architecture_not_in): """Sets the architecture_not_in of this ContentLibraryVmTemplateWhereInput. :param architecture_not_in: The architecture_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type architecture_not_in: list[Architecture] """ self._architecture_not_in = architecture_not_in @property def cloud_init_supported(self): """Gets the cloud_init_supported of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The cloud_init_supported of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: bool """ return self._cloud_init_supported @cloud_init_supported.setter def cloud_init_supported(self, cloud_init_supported): """Sets the cloud_init_supported of this ContentLibraryVmTemplateWhereInput. :param cloud_init_supported: The cloud_init_supported of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type cloud_init_supported: bool """ self._cloud_init_supported = cloud_init_supported @property def cloud_init_supported_not(self): """Gets the cloud_init_supported_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The cloud_init_supported_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: bool """ return self._cloud_init_supported_not @cloud_init_supported_not.setter def cloud_init_supported_not(self, cloud_init_supported_not): """Sets the cloud_init_supported_not of this ContentLibraryVmTemplateWhereInput. :param cloud_init_supported_not: The cloud_init_supported_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type cloud_init_supported_not: bool """ self._cloud_init_supported_not = cloud_init_supported_not @property def clusters_every(self): """Gets the clusters_every of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The clusters_every of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: ClusterWhereInput """ return self._clusters_every @clusters_every.setter def clusters_every(self, clusters_every): """Sets the clusters_every of this ContentLibraryVmTemplateWhereInput. :param clusters_every: The clusters_every of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type clusters_every: ClusterWhereInput """ self._clusters_every = clusters_every @property def clusters_none(self): """Gets the clusters_none of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The clusters_none of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: ClusterWhereInput """ return self._clusters_none @clusters_none.setter def clusters_none(self, clusters_none): """Sets the clusters_none of this ContentLibraryVmTemplateWhereInput. :param clusters_none: The clusters_none of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type clusters_none: ClusterWhereInput """ self._clusters_none = clusters_none @property def clusters_some(self): """Gets the clusters_some of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The clusters_some of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: ClusterWhereInput """ return self._clusters_some @clusters_some.setter def clusters_some(self, clusters_some): """Sets the clusters_some of this ContentLibraryVmTemplateWhereInput. :param clusters_some: The clusters_some of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type clusters_some: ClusterWhereInput """ self._clusters_some = clusters_some @property def created_at(self): """Gets the created_at of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The created_at of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._created_at @created_at.setter def created_at(self, created_at): """Sets the created_at of this ContentLibraryVmTemplateWhereInput. :param created_at: The created_at of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type created_at: str """ self._created_at = created_at @property def created_at_gt(self): """Gets the created_at_gt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The created_at_gt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._created_at_gt @created_at_gt.setter def created_at_gt(self, created_at_gt): """Sets the created_at_gt of this ContentLibraryVmTemplateWhereInput. :param created_at_gt: The created_at_gt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type created_at_gt: str """ self._created_at_gt = created_at_gt @property def created_at_gte(self): """Gets the created_at_gte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The created_at_gte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._created_at_gte @created_at_gte.setter def created_at_gte(self, created_at_gte): """Sets the created_at_gte of this ContentLibraryVmTemplateWhereInput. :param created_at_gte: The created_at_gte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type created_at_gte: str """ self._created_at_gte = created_at_gte @property def created_at_in(self): """Gets the created_at_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The created_at_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: list[str] """ return self._created_at_in @created_at_in.setter def created_at_in(self, created_at_in): """Sets the created_at_in of this ContentLibraryVmTemplateWhereInput. :param created_at_in: The created_at_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type created_at_in: list[str] """ self._created_at_in = created_at_in @property def created_at_lt(self): """Gets the created_at_lt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The created_at_lt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._created_at_lt @created_at_lt.setter def created_at_lt(self, created_at_lt): """Sets the created_at_lt of this ContentLibraryVmTemplateWhereInput. :param created_at_lt: The created_at_lt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type created_at_lt: str """ self._created_at_lt = created_at_lt @property def created_at_lte(self): """Gets the created_at_lte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The created_at_lte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._created_at_lte @created_at_lte.setter def created_at_lte(self, created_at_lte): """Sets the created_at_lte of this ContentLibraryVmTemplateWhereInput. :param created_at_lte: The created_at_lte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type created_at_lte: str """ self._created_at_lte = created_at_lte @property def created_at_not(self): """Gets the created_at_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The created_at_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._created_at_not @created_at_not.setter def created_at_not(self, created_at_not): """Sets the created_at_not of this ContentLibraryVmTemplateWhereInput. :param created_at_not: The created_at_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type created_at_not: str """ self._created_at_not = created_at_not @property def created_at_not_in(self): """Gets the created_at_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The created_at_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: list[str] """ return self._created_at_not_in @created_at_not_in.setter def created_at_not_in(self, created_at_not_in): """Sets the created_at_not_in of this ContentLibraryVmTemplateWhereInput. :param created_at_not_in: The created_at_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type created_at_not_in: list[str] """ self._created_at_not_in = created_at_not_in @property def description(self): """Gets the description of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The description of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._description @description.setter def description(self, description): """Sets the description of this ContentLibraryVmTemplateWhereInput. :param description: The description of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type description: str """ self._description = description @property def description_contains(self): """Gets the description_contains of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The description_contains of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._description_contains @description_contains.setter def description_contains(self, description_contains): """Sets the description_contains of this ContentLibraryVmTemplateWhereInput. :param description_contains: The description_contains of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type description_contains: str """ self._description_contains = description_contains @property def description_ends_with(self): """Gets the description_ends_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The description_ends_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._description_ends_with @description_ends_with.setter def description_ends_with(self, description_ends_with): """Sets the description_ends_with of this ContentLibraryVmTemplateWhereInput. :param description_ends_with: The description_ends_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type description_ends_with: str """ self._description_ends_with = description_ends_with @property def description_gt(self): """Gets the description_gt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The description_gt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._description_gt @description_gt.setter def description_gt(self, description_gt): """Sets the description_gt of this ContentLibraryVmTemplateWhereInput. :param description_gt: The description_gt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type description_gt: str """ self._description_gt = description_gt @property def description_gte(self): """Gets the description_gte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The description_gte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._description_gte @description_gte.setter def description_gte(self, description_gte): """Sets the description_gte of this ContentLibraryVmTemplateWhereInput. :param description_gte: The description_gte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type description_gte: str """ self._description_gte = description_gte @property def description_in(self): """Gets the description_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The description_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: list[str] """ return self._description_in @description_in.setter def description_in(self, description_in): """Sets the description_in of this ContentLibraryVmTemplateWhereInput. :param description_in: The description_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type description_in: list[str] """ self._description_in = description_in @property def description_lt(self): """Gets the description_lt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The description_lt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._description_lt @description_lt.setter def description_lt(self, description_lt): """Sets the description_lt of this ContentLibraryVmTemplateWhereInput. :param description_lt: The description_lt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type description_lt: str """ self._description_lt = description_lt @property def description_lte(self): """Gets the description_lte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The description_lte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._description_lte @description_lte.setter def description_lte(self, description_lte): """Sets the description_lte of this ContentLibraryVmTemplateWhereInput. :param description_lte: The description_lte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type description_lte: str """ self._description_lte = description_lte @property def description_not(self): """Gets the description_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The description_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._description_not @description_not.setter def description_not(self, description_not): """Sets the description_not of this ContentLibraryVmTemplateWhereInput. :param description_not: The description_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type description_not: str """ self._description_not = description_not @property def description_not_contains(self): """Gets the description_not_contains of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The description_not_contains of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._description_not_contains @description_not_contains.setter def description_not_contains(self, description_not_contains): """Sets the description_not_contains of this ContentLibraryVmTemplateWhereInput. :param description_not_contains: The description_not_contains of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type description_not_contains: str """ self._description_not_contains = description_not_contains @property def description_not_ends_with(self): """Gets the description_not_ends_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The description_not_ends_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._description_not_ends_with @description_not_ends_with.setter def description_not_ends_with(self, description_not_ends_with): """Sets the description_not_ends_with of this ContentLibraryVmTemplateWhereInput. :param description_not_ends_with: The description_not_ends_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type description_not_ends_with: str """ self._description_not_ends_with = description_not_ends_with @property def description_not_in(self): """Gets the description_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The description_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: list[str] """ return self._description_not_in @description_not_in.setter def description_not_in(self, description_not_in): """Sets the description_not_in of this ContentLibraryVmTemplateWhereInput. :param description_not_in: The description_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type description_not_in: list[str] """ self._description_not_in = description_not_in @property def description_not_starts_with(self): """Gets the description_not_starts_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The description_not_starts_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._description_not_starts_with @description_not_starts_with.setter def description_not_starts_with(self, description_not_starts_with): """Sets the description_not_starts_with of this ContentLibraryVmTemplateWhereInput. :param description_not_starts_with: The description_not_starts_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type description_not_starts_with: str """ self._description_not_starts_with = description_not_starts_with @property def description_starts_with(self): """Gets the description_starts_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The description_starts_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._description_starts_with @description_starts_with.setter def description_starts_with(self, description_starts_with): """Sets the description_starts_with of this ContentLibraryVmTemplateWhereInput. :param description_starts_with: The description_starts_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type description_starts_with: str """ self._description_starts_with = description_starts_with @property def entity_async_status(self): """Gets the entity_async_status of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The entity_async_status of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: EntityAsyncStatus """ return self._entity_async_status @entity_async_status.setter def entity_async_status(self, entity_async_status): """Sets the entity_async_status of this ContentLibraryVmTemplateWhereInput. :param entity_async_status: The entity_async_status of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type entity_async_status: EntityAsyncStatus """ self._entity_async_status = entity_async_status @property def entity_async_status_in(self): """Gets the entity_async_status_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The entity_async_status_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: list[EntityAsyncStatus] """ return self._entity_async_status_in @entity_async_status_in.setter def entity_async_status_in(self, entity_async_status_in): """Sets the entity_async_status_in of this ContentLibraryVmTemplateWhereInput. :param entity_async_status_in: The entity_async_status_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type entity_async_status_in: list[EntityAsyncStatus] """ self._entity_async_status_in = entity_async_status_in @property def entity_async_status_not(self): """Gets the entity_async_status_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The entity_async_status_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: EntityAsyncStatus """ return self._entity_async_status_not @entity_async_status_not.setter def entity_async_status_not(self, entity_async_status_not): """Sets the entity_async_status_not of this ContentLibraryVmTemplateWhereInput. :param entity_async_status_not: The entity_async_status_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type entity_async_status_not: EntityAsyncStatus """ self._entity_async_status_not = entity_async_status_not @property def entity_async_status_not_in(self): """Gets the entity_async_status_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The entity_async_status_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: list[EntityAsyncStatus] """ return self._entity_async_status_not_in @entity_async_status_not_in.setter def entity_async_status_not_in(self, entity_async_status_not_in): """Sets the entity_async_status_not_in of this ContentLibraryVmTemplateWhereInput. :param entity_async_status_not_in: The entity_async_status_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type entity_async_status_not_in: list[EntityAsyncStatus] """ self._entity_async_status_not_in = entity_async_status_not_in @property def id(self): """Gets the id of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The id of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._id @id.setter def id(self, id): """Sets the id of this ContentLibraryVmTemplateWhereInput. :param id: The id of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type id: str """ self._id = id @property def id_contains(self): """Gets the id_contains of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The id_contains of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._id_contains @id_contains.setter def id_contains(self, id_contains): """Sets the id_contains of this ContentLibraryVmTemplateWhereInput. :param id_contains: The id_contains of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type id_contains: str """ self._id_contains = id_contains @property def id_ends_with(self): """Gets the id_ends_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The id_ends_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._id_ends_with @id_ends_with.setter def id_ends_with(self, id_ends_with): """Sets the id_ends_with of this ContentLibraryVmTemplateWhereInput. :param id_ends_with: The id_ends_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type id_ends_with: str """ self._id_ends_with = id_ends_with @property def id_gt(self): """Gets the id_gt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The id_gt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._id_gt @id_gt.setter def id_gt(self, id_gt): """Sets the id_gt of this ContentLibraryVmTemplateWhereInput. :param id_gt: The id_gt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type id_gt: str """ self._id_gt = id_gt @property def id_gte(self): """Gets the id_gte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The id_gte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._id_gte @id_gte.setter def id_gte(self, id_gte): """Sets the id_gte of this ContentLibraryVmTemplateWhereInput. :param id_gte: The id_gte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type id_gte: str """ self._id_gte = id_gte @property def id_in(self): """Gets the id_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The id_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: list[str] """ return self._id_in @id_in.setter def id_in(self, id_in): """Sets the id_in of this ContentLibraryVmTemplateWhereInput. :param id_in: The id_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type id_in: list[str] """ self._id_in = id_in @property def id_lt(self): """Gets the id_lt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The id_lt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._id_lt @id_lt.setter def id_lt(self, id_lt): """Sets the id_lt of this ContentLibraryVmTemplateWhereInput. :param id_lt: The id_lt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type id_lt: str """ self._id_lt = id_lt @property def id_lte(self): """Gets the id_lte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The id_lte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._id_lte @id_lte.setter def id_lte(self, id_lte): """Sets the id_lte of this ContentLibraryVmTemplateWhereInput. :param id_lte: The id_lte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type id_lte: str """ self._id_lte = id_lte @property def id_not(self): """Gets the id_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The id_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._id_not @id_not.setter def id_not(self, id_not): """Sets the id_not of this ContentLibraryVmTemplateWhereInput. :param id_not: The id_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type id_not: str """ self._id_not = id_not @property def id_not_contains(self): """Gets the id_not_contains of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The id_not_contains of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._id_not_contains @id_not_contains.setter def id_not_contains(self, id_not_contains): """Sets the id_not_contains of this ContentLibraryVmTemplateWhereInput. :param id_not_contains: The id_not_contains of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type id_not_contains: str """ self._id_not_contains = id_not_contains @property def id_not_ends_with(self): """Gets the id_not_ends_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The id_not_ends_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._id_not_ends_with @id_not_ends_with.setter def id_not_ends_with(self, id_not_ends_with): """Sets the id_not_ends_with of this ContentLibraryVmTemplateWhereInput. :param id_not_ends_with: The id_not_ends_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type id_not_ends_with: str """ self._id_not_ends_with = id_not_ends_with @property def id_not_in(self): """Gets the id_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The id_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: list[str] """ return self._id_not_in @id_not_in.setter def id_not_in(self, id_not_in): """Sets the id_not_in of this ContentLibraryVmTemplateWhereInput. :param id_not_in: The id_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type id_not_in: list[str] """ self._id_not_in = id_not_in @property def id_not_starts_with(self): """Gets the id_not_starts_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The id_not_starts_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._id_not_starts_with @id_not_starts_with.setter def id_not_starts_with(self, id_not_starts_with): """Sets the id_not_starts_with of this ContentLibraryVmTemplateWhereInput. :param id_not_starts_with: The id_not_starts_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type id_not_starts_with: str """ self._id_not_starts_with = id_not_starts_with @property def id_starts_with(self): """Gets the id_starts_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The id_starts_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._id_starts_with @id_starts_with.setter def id_starts_with(self, id_starts_with): """Sets the id_starts_with of this ContentLibraryVmTemplateWhereInput. :param id_starts_with: The id_starts_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type id_starts_with: str """ self._id_starts_with = id_starts_with @property def labels_every(self): """Gets the labels_every of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The labels_every of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: LabelWhereInput """ return self._labels_every @labels_every.setter def labels_every(self, labels_every): """Sets the labels_every of this ContentLibraryVmTemplateWhereInput. :param labels_every: The labels_every of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type labels_every: LabelWhereInput """ self._labels_every = labels_every @property def labels_none(self): """Gets the labels_none of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The labels_none of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: LabelWhereInput """ return self._labels_none @labels_none.setter def labels_none(self, labels_none): """Sets the labels_none of this ContentLibraryVmTemplateWhereInput. :param labels_none: The labels_none of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type labels_none: LabelWhereInput """ self._labels_none = labels_none @property def labels_some(self): """Gets the labels_some of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The labels_some of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: LabelWhereInput """ return self._labels_some @labels_some.setter def labels_some(self, labels_some): """Sets the labels_some of this ContentLibraryVmTemplateWhereInput. :param labels_some: The labels_some of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type labels_some: LabelWhereInput """ self._labels_some = labels_some @property def memory(self): """Gets the memory of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The memory of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: int """ return self._memory @memory.setter def memory(self, memory): """Sets the memory of this ContentLibraryVmTemplateWhereInput. :param memory: The memory of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type memory: int """ self._memory = memory @property def memory_gt(self): """Gets the memory_gt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The memory_gt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: int """ return self._memory_gt @memory_gt.setter def memory_gt(self, memory_gt): """Sets the memory_gt of this ContentLibraryVmTemplateWhereInput. :param memory_gt: The memory_gt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type memory_gt: int """ self._memory_gt = memory_gt @property def memory_gte(self): """Gets the memory_gte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The memory_gte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: int """ return self._memory_gte @memory_gte.setter def memory_gte(self, memory_gte): """Sets the memory_gte of this ContentLibraryVmTemplateWhereInput. :param memory_gte: The memory_gte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type memory_gte: int """ self._memory_gte = memory_gte @property def memory_in(self): """Gets the memory_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The memory_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: list[int] """ return self._memory_in @memory_in.setter def memory_in(self, memory_in): """Sets the memory_in of this ContentLibraryVmTemplateWhereInput. :param memory_in: The memory_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type memory_in: list[int] """ self._memory_in = memory_in @property def memory_lt(self): """Gets the memory_lt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The memory_lt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: int """ return self._memory_lt @memory_lt.setter def memory_lt(self, memory_lt): """Sets the memory_lt of this ContentLibraryVmTemplateWhereInput. :param memory_lt: The memory_lt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type memory_lt: int """ self._memory_lt = memory_lt @property def memory_lte(self): """Gets the memory_lte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The memory_lte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: int """ return self._memory_lte @memory_lte.setter def memory_lte(self, memory_lte): """Sets the memory_lte of this ContentLibraryVmTemplateWhereInput. :param memory_lte: The memory_lte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type memory_lte: int """ self._memory_lte = memory_lte @property def memory_not(self): """Gets the memory_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The memory_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: int """ return self._memory_not @memory_not.setter def memory_not(self, memory_not): """Sets the memory_not of this ContentLibraryVmTemplateWhereInput. :param memory_not: The memory_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type memory_not: int """ self._memory_not = memory_not @property def memory_not_in(self): """Gets the memory_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The memory_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: list[int] """ return self._memory_not_in @memory_not_in.setter def memory_not_in(self, memory_not_in): """Sets the memory_not_in of this ContentLibraryVmTemplateWhereInput. :param memory_not_in: The memory_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type memory_not_in: list[int] """ self._memory_not_in = memory_not_in @property def name(self): """Gets the name of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The name of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._name @name.setter def name(self, name): """Sets the name of this ContentLibraryVmTemplateWhereInput. :param name: The name of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type name: str """ self._name = name @property def name_contains(self): """Gets the name_contains of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The name_contains of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._name_contains @name_contains.setter def name_contains(self, name_contains): """Sets the name_contains of this ContentLibraryVmTemplateWhereInput. :param name_contains: The name_contains of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type name_contains: str """ self._name_contains = name_contains @property def name_ends_with(self): """Gets the name_ends_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The name_ends_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._name_ends_with @name_ends_with.setter def name_ends_with(self, name_ends_with): """Sets the name_ends_with of this ContentLibraryVmTemplateWhereInput. :param name_ends_with: The name_ends_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type name_ends_with: str """ self._name_ends_with = name_ends_with @property def name_gt(self): """Gets the name_gt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The name_gt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._name_gt @name_gt.setter def name_gt(self, name_gt): """Sets the name_gt of this ContentLibraryVmTemplateWhereInput. :param name_gt: The name_gt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type name_gt: str """ self._name_gt = name_gt @property def name_gte(self): """Gets the name_gte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The name_gte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._name_gte @name_gte.setter def name_gte(self, name_gte): """Sets the name_gte of this ContentLibraryVmTemplateWhereInput. :param name_gte: The name_gte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type name_gte: str """ self._name_gte = name_gte @property def name_in(self): """Gets the name_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The name_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: list[str] """ return self._name_in @name_in.setter def name_in(self, name_in): """Sets the name_in of this ContentLibraryVmTemplateWhereInput. :param name_in: The name_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type name_in: list[str] """ self._name_in = name_in @property def name_lt(self): """Gets the name_lt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The name_lt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._name_lt @name_lt.setter def name_lt(self, name_lt): """Sets the name_lt of this ContentLibraryVmTemplateWhereInput. :param name_lt: The name_lt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type name_lt: str """ self._name_lt = name_lt @property def name_lte(self): """Gets the name_lte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The name_lte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._name_lte @name_lte.setter def name_lte(self, name_lte): """Sets the name_lte of this ContentLibraryVmTemplateWhereInput. :param name_lte: The name_lte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type name_lte: str """ self._name_lte = name_lte @property def name_not(self): """Gets the name_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The name_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._name_not @name_not.setter def name_not(self, name_not): """Sets the name_not of this ContentLibraryVmTemplateWhereInput. :param name_not: The name_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type name_not: str """ self._name_not = name_not @property def name_not_contains(self): """Gets the name_not_contains of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The name_not_contains of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._name_not_contains @name_not_contains.setter def name_not_contains(self, name_not_contains): """Sets the name_not_contains of this ContentLibraryVmTemplateWhereInput. :param name_not_contains: The name_not_contains of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type name_not_contains: str """ self._name_not_contains = name_not_contains @property def name_not_ends_with(self): """Gets the name_not_ends_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The name_not_ends_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._name_not_ends_with @name_not_ends_with.setter def name_not_ends_with(self, name_not_ends_with): """Sets the name_not_ends_with of this ContentLibraryVmTemplateWhereInput. :param name_not_ends_with: The name_not_ends_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type name_not_ends_with: str """ self._name_not_ends_with = name_not_ends_with @property def name_not_in(self): """Gets the name_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The name_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: list[str] """ return self._name_not_in @name_not_in.setter def name_not_in(self, name_not_in): """Sets the name_not_in of this ContentLibraryVmTemplateWhereInput. :param name_not_in: The name_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type name_not_in: list[str] """ self._name_not_in = name_not_in @property def name_not_starts_with(self): """Gets the name_not_starts_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The name_not_starts_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._name_not_starts_with @name_not_starts_with.setter def name_not_starts_with(self, name_not_starts_with): """Sets the name_not_starts_with of this ContentLibraryVmTemplateWhereInput. :param name_not_starts_with: The name_not_starts_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type name_not_starts_with: str """ self._name_not_starts_with = name_not_starts_with @property def name_starts_with(self): """Gets the name_starts_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The name_starts_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._name_starts_with @name_starts_with.setter def name_starts_with(self, name_starts_with): """Sets the name_starts_with of this ContentLibraryVmTemplateWhereInput. :param name_starts_with: The name_starts_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type name_starts_with: str """ self._name_starts_with = name_starts_with @property def _not(self): """Gets the _not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The _not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: list[ContentLibraryVmTemplateWhereInput] """ return self.__not @_not.setter def _not(self, _not): """Sets the _not of this ContentLibraryVmTemplateWhereInput. :param _not: The _not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type _not: list[ContentLibraryVmTemplateWhereInput] """ self.__not = _not @property def _or(self): """Gets the _or of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The _or of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: list[ContentLibraryVmTemplateWhereInput] """ return self.__or @_or.setter def _or(self, _or): """Sets the _or of this ContentLibraryVmTemplateWhereInput. :param _or: The _or of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type _or: list[ContentLibraryVmTemplateWhereInput] """ self.__or = _or @property def os(self): """Gets the os of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The os of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._os @os.setter def os(self, os): """Sets the os of this ContentLibraryVmTemplateWhereInput. :param os: The os of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type os: str """ self._os = os @property def os_contains(self): """Gets the os_contains of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The os_contains of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._os_contains @os_contains.setter def os_contains(self, os_contains): """Sets the os_contains of this ContentLibraryVmTemplateWhereInput. :param os_contains: The os_contains of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type os_contains: str """ self._os_contains = os_contains @property def os_ends_with(self): """Gets the os_ends_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The os_ends_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._os_ends_with @os_ends_with.setter def os_ends_with(self, os_ends_with): """Sets the os_ends_with of this ContentLibraryVmTemplateWhereInput. :param os_ends_with: The os_ends_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type os_ends_with: str """ self._os_ends_with = os_ends_with @property def os_gt(self): """Gets the os_gt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The os_gt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._os_gt @os_gt.setter def os_gt(self, os_gt): """Sets the os_gt of this ContentLibraryVmTemplateWhereInput. :param os_gt: The os_gt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type os_gt: str """ self._os_gt = os_gt @property def os_gte(self): """Gets the os_gte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The os_gte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._os_gte @os_gte.setter def os_gte(self, os_gte): """Sets the os_gte of this ContentLibraryVmTemplateWhereInput. :param os_gte: The os_gte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type os_gte: str """ self._os_gte = os_gte @property def os_in(self): """Gets the os_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The os_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: list[str] """ return self._os_in @os_in.setter def os_in(self, os_in): """Sets the os_in of this ContentLibraryVmTemplateWhereInput. :param os_in: The os_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type os_in: list[str] """ self._os_in = os_in @property def os_lt(self): """Gets the os_lt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The os_lt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._os_lt @os_lt.setter def os_lt(self, os_lt): """Sets the os_lt of this ContentLibraryVmTemplateWhereInput. :param os_lt: The os_lt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type os_lt: str """ self._os_lt = os_lt @property def os_lte(self): """Gets the os_lte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The os_lte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._os_lte @os_lte.setter def os_lte(self, os_lte): """Sets the os_lte of this ContentLibraryVmTemplateWhereInput. :param os_lte: The os_lte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type os_lte: str """ self._os_lte = os_lte @property def os_not(self): """Gets the os_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The os_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._os_not @os_not.setter def os_not(self, os_not): """Sets the os_not of this ContentLibraryVmTemplateWhereInput. :param os_not: The os_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type os_not: str """ self._os_not = os_not @property def os_not_contains(self): """Gets the os_not_contains of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The os_not_contains of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._os_not_contains @os_not_contains.setter def os_not_contains(self, os_not_contains): """Sets the os_not_contains of this ContentLibraryVmTemplateWhereInput. :param os_not_contains: The os_not_contains of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type os_not_contains: str """ self._os_not_contains = os_not_contains @property def os_not_ends_with(self): """Gets the os_not_ends_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The os_not_ends_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._os_not_ends_with @os_not_ends_with.setter def os_not_ends_with(self, os_not_ends_with): """Sets the os_not_ends_with of this ContentLibraryVmTemplateWhereInput. :param os_not_ends_with: The os_not_ends_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type os_not_ends_with: str """ self._os_not_ends_with = os_not_ends_with @property def os_not_in(self): """Gets the os_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The os_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: list[str] """ return self._os_not_in @os_not_in.setter def os_not_in(self, os_not_in): """Sets the os_not_in of this ContentLibraryVmTemplateWhereInput. :param os_not_in: The os_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type os_not_in: list[str] """ self._os_not_in = os_not_in @property def os_not_starts_with(self): """Gets the os_not_starts_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The os_not_starts_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._os_not_starts_with @os_not_starts_with.setter def os_not_starts_with(self, os_not_starts_with): """Sets the os_not_starts_with of this ContentLibraryVmTemplateWhereInput. :param os_not_starts_with: The os_not_starts_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type os_not_starts_with: str """ self._os_not_starts_with = os_not_starts_with @property def os_starts_with(self): """Gets the os_starts_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The os_starts_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: str """ return self._os_starts_with @os_starts_with.setter def os_starts_with(self, os_starts_with): """Sets the os_starts_with of this ContentLibraryVmTemplateWhereInput. :param os_starts_with: The os_starts_with of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type os_starts_with: str """ self._os_starts_with = os_starts_with @property def size(self): """Gets the size of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The size of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: int """ return self._size @size.setter def size(self, size): """Sets the size of this ContentLibraryVmTemplateWhereInput. :param size: The size of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type size: int """ self._size = size @property def size_gt(self): """Gets the size_gt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The size_gt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: int """ return self._size_gt @size_gt.setter def size_gt(self, size_gt): """Sets the size_gt of this ContentLibraryVmTemplateWhereInput. :param size_gt: The size_gt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type size_gt: int """ self._size_gt = size_gt @property def size_gte(self): """Gets the size_gte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The size_gte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: int """ return self._size_gte @size_gte.setter def size_gte(self, size_gte): """Sets the size_gte of this ContentLibraryVmTemplateWhereInput. :param size_gte: The size_gte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type size_gte: int """ self._size_gte = size_gte @property def size_in(self): """Gets the size_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The size_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: list[int] """ return self._size_in @size_in.setter def size_in(self, size_in): """Sets the size_in of this ContentLibraryVmTemplateWhereInput. :param size_in: The size_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type size_in: list[int] """ self._size_in = size_in @property def size_lt(self): """Gets the size_lt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The size_lt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: int """ return self._size_lt @size_lt.setter def size_lt(self, size_lt): """Sets the size_lt of this ContentLibraryVmTemplateWhereInput. :param size_lt: The size_lt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type size_lt: int """ self._size_lt = size_lt @property def size_lte(self): """Gets the size_lte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The size_lte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: int """ return self._size_lte @size_lte.setter def size_lte(self, size_lte): """Sets the size_lte of this ContentLibraryVmTemplateWhereInput. :param size_lte: The size_lte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type size_lte: int """ self._size_lte = size_lte @property def size_not(self): """Gets the size_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The size_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: int """ return self._size_not @size_not.setter def size_not(self, size_not): """Sets the size_not of this ContentLibraryVmTemplateWhereInput. :param size_not: The size_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type size_not: int """ self._size_not = size_not @property def size_not_in(self): """Gets the size_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The size_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: list[int] """ return self._size_not_in @size_not_in.setter def size_not_in(self, size_not_in): """Sets the size_not_in of this ContentLibraryVmTemplateWhereInput. :param size_not_in: The size_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type size_not_in: list[int] """ self._size_not_in = size_not_in @property def vcpu(self): """Gets the vcpu of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The vcpu of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: int """ return self._vcpu @vcpu.setter def vcpu(self, vcpu): """Sets the vcpu of this ContentLibraryVmTemplateWhereInput. :param vcpu: The vcpu of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type vcpu: int """ self._vcpu = vcpu @property def vcpu_gt(self): """Gets the vcpu_gt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The vcpu_gt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: int """ return self._vcpu_gt @vcpu_gt.setter def vcpu_gt(self, vcpu_gt): """Sets the vcpu_gt of this ContentLibraryVmTemplateWhereInput. :param vcpu_gt: The vcpu_gt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type vcpu_gt: int """ self._vcpu_gt = vcpu_gt @property def vcpu_gte(self): """Gets the vcpu_gte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The vcpu_gte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: int """ return self._vcpu_gte @vcpu_gte.setter def vcpu_gte(self, vcpu_gte): """Sets the vcpu_gte of this ContentLibraryVmTemplateWhereInput. :param vcpu_gte: The vcpu_gte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type vcpu_gte: int """ self._vcpu_gte = vcpu_gte @property def vcpu_in(self): """Gets the vcpu_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The vcpu_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: list[int] """ return self._vcpu_in @vcpu_in.setter def vcpu_in(self, vcpu_in): """Sets the vcpu_in of this ContentLibraryVmTemplateWhereInput. :param vcpu_in: The vcpu_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type vcpu_in: list[int] """ self._vcpu_in = vcpu_in @property def vcpu_lt(self): """Gets the vcpu_lt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The vcpu_lt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: int """ return self._vcpu_lt @vcpu_lt.setter def vcpu_lt(self, vcpu_lt): """Sets the vcpu_lt of this ContentLibraryVmTemplateWhereInput. :param vcpu_lt: The vcpu_lt of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type vcpu_lt: int """ self._vcpu_lt = vcpu_lt @property def vcpu_lte(self): """Gets the vcpu_lte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The vcpu_lte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: int """ return self._vcpu_lte @vcpu_lte.setter def vcpu_lte(self, vcpu_lte): """Sets the vcpu_lte of this ContentLibraryVmTemplateWhereInput. :param vcpu_lte: The vcpu_lte of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type vcpu_lte: int """ self._vcpu_lte = vcpu_lte @property def vcpu_not(self): """Gets the vcpu_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The vcpu_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: int """ return self._vcpu_not @vcpu_not.setter def vcpu_not(self, vcpu_not): """Sets the vcpu_not of this ContentLibraryVmTemplateWhereInput. :param vcpu_not: The vcpu_not of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type vcpu_not: int """ self._vcpu_not = vcpu_not @property def vcpu_not_in(self): """Gets the vcpu_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The vcpu_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: list[int] """ return self._vcpu_not_in @vcpu_not_in.setter def vcpu_not_in(self, vcpu_not_in): """Sets the vcpu_not_in of this ContentLibraryVmTemplateWhereInput. :param vcpu_not_in: The vcpu_not_in of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type vcpu_not_in: list[int] """ self._vcpu_not_in = vcpu_not_in @property def vm_templates_every(self): """Gets the vm_templates_every of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The vm_templates_every of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: VmTemplateWhereInput """ return self._vm_templates_every @vm_templates_every.setter def vm_templates_every(self, vm_templates_every): """Sets the vm_templates_every of this ContentLibraryVmTemplateWhereInput. :param vm_templates_every: The vm_templates_every of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type vm_templates_every: VmTemplateWhereInput """ self._vm_templates_every = vm_templates_every @property def vm_templates_none(self): """Gets the vm_templates_none of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The vm_templates_none of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: VmTemplateWhereInput """ return self._vm_templates_none @vm_templates_none.setter def vm_templates_none(self, vm_templates_none): """Sets the vm_templates_none of this ContentLibraryVmTemplateWhereInput. :param vm_templates_none: The vm_templates_none of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type vm_templates_none: VmTemplateWhereInput """ self._vm_templates_none = vm_templates_none @property def vm_templates_some(self): """Gets the vm_templates_some of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :return: The vm_templates_some of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :rtype: VmTemplateWhereInput """ return self._vm_templates_some @vm_templates_some.setter def vm_templates_some(self, vm_templates_some): """Sets the vm_templates_some of this ContentLibraryVmTemplateWhereInput. :param vm_templates_some: The vm_templates_some of this ContentLibraryVmTemplateWhereInput. # noqa: E501 :type vm_templates_some: VmTemplateWhereInput """ self._vm_templates_some = vm_templates_some def to_dict(self, serialize=False): """Returns the model properties as a dict""" result = {} def convert(x): if hasattr(x, "to_dict"): args = getfullargspec(x.to_dict).args if len(args) == 1: return x.to_dict() else: return x.to_dict(serialize) else: return x for attr, _ in six.iteritems(self.openapi_types): value = getattr(self, attr) attr = self.attribute_map.get(attr, attr) if serialize else attr if isinstance(value, list): result[attr] = list(map( lambda x: convert(x), value )) elif isinstance(value, dict): result[attr] = dict(map( lambda item: (item[0], convert(item[1])), value.items() )) else: result[attr] = convert(value) return result def to_str(self): """Returns the string representation of the model""" return pprint.pformat(self.to_dict()) def __repr__(self): """For `print` and `pprint`""" return self.to_str() def __eq__(self, other): """Returns true if both objects are equal""" if not isinstance(other, ContentLibraryVmTemplateWhereInput): return False return self.to_dict() == other.to_dict() def __ne__(self, other): """Returns true if both objects are not equal""" if not isinstance(other, ContentLibraryVmTemplateWhereInput): return True return self.to_dict() != other.to_dict()

UTF-8

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false

91,732

py

367

content_library_vm_template_where_input.py

361

0.628428

0.617494

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racharyy/BERT_humor

7,954,279,432,193

0021216bd49b05b406fd7312df13e136bc3ec09e

e7b02652f394f12ec166d89e98d0ed520761d067

/humor_bert_embedding_property.py

e1b0860542c538301d708e3c284a1b23fd78503d

[]

no_license

https://github.com/racharyy/BERT_humor

a95c732b0c64210bb2c4ed7052533dd491480fda

6f135866fe29b635a9aaf05fd0c08cfb9554d073

refs/heads/master

2022-11-09T13:27:00.409531

2019-10-30T20:51:41

199,521,323

0

null

false

2022-10-25T14:02:42

2019-07-29T20:18:36

2019-10-30T20:51:53

2019-10-30T20:51:50

1,143

0

1

Python

false

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Thu Oct 3 16:14:01 2019 @author: mhasan8 """ import pickle as pkl dev_data=pkl.load(open("humor_bert_embeddings_dev.pkl","rb")) train_data=pkl.load(open("humor_bert_embeddings_train.pkl","rb")) test_data=pkl.load(open("humor_bert_embeddings_test.pkl","rb")) humor_cls_embeddings=[] for humor_inst in train_data: inst={'cls_embedding':humor_inst['cls_embedding'],'label':humor_inst['label']} humor_cls_embeddings.append(inst) for humor_inst in dev_data: inst={'cls_embedding':humor_inst['cls_embedding'],'label':humor_inst['label']} humor_cls_embeddings.append(inst) for humor_inst in test_data: inst={'cls_embedding':humor_inst['cls_embedding'],'label':humor_inst['label']} humor_cls_embeddings.append(inst) pkl.dump(humor_cls_embeddings,open("humor_bert_cls_embeddings.pkl","wb"))

UTF-8

Python

false

896

py

21

humor_bert_embedding_property.py

20

0.686384

0.670759

0

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82

nharringtonwasatch/WasatchUSB

9,096,740,751,244

65ed0f357ac8fc1ba92499ff75359ecd74946487

50469576929509d5845aaa0177c2d563e91b1f60

/scripts/stroker.py

34fc7789adc89901110640d67523eb13f5345aca

[]

no_license

https://github.com/nharringtonwasatch/WasatchUSB

00294a34ae21812851bf4535f7faa319794f9fbb

2576ded56704736c8f0d6d6de3613840fce3662f

refs/heads/master

2020-04-12T08:01:45.651896

2017-09-22T21:43:07

40,848,538

0

null

#!/usr/bin/env python2 """ Bare bones script to connect to a Wasatch Photonics device that supports the stroker series protocol. Will print version information of any device connected. communication for devices from Wasatch Photonics. Stroker in this case is an homage to automotive performance: https://en.wikipedia.org/wiki/Stroker_kit """ import sys import logging log = logging.getLogger() strm = logging.StreamHandler(sys.stderr) log.addHandler(strm) log.setLevel(logging.WARN) graph_available = True try: from diagram import DGWrapper, DOption except ImportError as exc: graph_available = False log.warn("No diagram module - lineplots disabled.") log.warn("See: https://github.com/WasatchPhotonics/diagram") log.warn("Exception: %s", exc) from wasatchusb import stroker_protocol def print_device(): """ Print the default set of data from the device. To diagnose these individually, see the wasatchusb/test/test_stroker_fx2_protocol.py file. """ dev_list = stroker_protocol.ListDevices() result = dev_list.get_all() if result == []: print "No devices found!" sys.exit(1) dev_count = 0 for item in dev_list.get_all(): print "Device: %s VID: %s PID: %s" \ % (dev_count, item[0], item[1]) dev_count += 1 last_device = dev_list.get_all()[-1] last_pid = int(last_device[1], 16) device = stroker_protocol.StrokerProtocolDevice(pid=last_pid) device.connect() print "Serial: %s" % device.get_serial_number() print "SWCode: %s" % device.get_standard_software_code() print "FPGARev: %s" % device.get_fpga_revision() print "Gain: %s" % device.get_ccd_gain() print "Int Time: %s" % device.get_integration_time() return device def print_data(device): data = device.get_line() avg_data = sum(data) / len(data) print "" points = [] values = [] subsample_size = len(data) / 80 for item in data[::subsample_size]: points.append(float(item)) values.append(None) if graph_available: gram = DGWrapper(data=[points, values]) gram.show() else: print "Min: %s Max: %s Avg: %s" \ % (min(data), max(data), avg_data) if __name__ == "__main__": device = print_device() print_data(device)

UTF-8

Python

false

2,365

py

20

stroker.py

19

0.635941

0.630444

0

83

27.493976

72

karlicoss/orger

13,383,118,118,031

039d70ee1e3ab039eb43d8dc77c68af6c2ed6ef7

3dc867d0c91c69d3cfdad7ffc94976820056e48f

/modules/reddit_all.py

3e6abf265f412fcf562eed6e70cd21eed61d3b9a

[ "MIT" ]

permissive

https://github.com/karlicoss/orger

12d698a88a7c1b8354106a296ccfeb94a8b9e989

9c4fb4b252aa7abd09bfed6c580781ebe4ceef70

refs/heads/master

2022-11-11T04:30:11.130043

2022-10-19T20:38:12

2022-10-19T20:44:12

186,183,159

287

16

MIT

false

2022-10-19T20:44:13

2019-05-11T21:30:23

2022-10-09T15:08:48

2022-10-19T20:44:12

182

256

11

7

Python

false

#!/usr/bin/env python3 """ Read-only reddit mirror of comments, submissions and upvoted posts; everything except saved """ from orger import Mirror from orger.inorganic import node, link, Quoted from orger.common import dt_heading from my.reddit import upvoted, submissions, comments class RedditAllView(Mirror): def get_items(self) -> Mirror.Results: yield node( 'Submissions', children=[node( # TODO can also be iterable? dt_heading(s.created, link(title=s.title, url=s.url)), body=Quoted(s.text), ) for s in submissions()] ) yield node( 'Comments', # todo parent thread?? children=[node( dt_heading(c.created, link(title=c.url, url=c.url)), body=Quoted(c.text), ) for c in comments()], ) yield node( 'Upvoted', children=[node( dt_heading(u.created, link(title=u.title, url=u.url)), body=Quoted(u.text), ) for u in upvoted()] ) if __name__ == '__main__': RedditAllView.main() # todo not sure if for reddit worth converting bodies from md to org? I guess quoting is ok for now?

UTF-8

Python

false

1,247

py

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reddit_all.py

39

0.57097

0.570168

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100

samwar/python-class

17,334,488,033,203

d07878093fdda9b497de33513a0ddf8cd8a61302

f1e9e47ca30d63f7b787b38af64aaeadede63221

/lab03.py

336d4d894f864a893b8cb30cff6ab9015879e2f0

[]

no_license

https://github.com/samwar/python-class

0e967c67d17d897fbaf33faab852f0b8d0d8e3b6

8696b84d8e3070d3d38bcce0586d40a03492baf0

refs/heads/master

2021-01-15T23:40:00.948787

2014-04-10T22:04:23

null

0

null

__author__ = 'samu6978' x = 4 print x print int(5) y = [1,2,3] print y.count(3) y.index(1) foo = {1:'foo', 2:'bar', 3:'baz'} for x in foo.iteritems(): print x print y y.extend([4,5]) print y y.append([4,5]) print y z = "foo" # z.ap("bar") # z.ex z += "bar" print z

UTF-8

Python

false

271

py

24

lab03.py

24

0.560886

0.494465

0

23

10.826087

33

DRAR444/poei-python

7,533,372,637,454

34b164d219120454e2c48243ab00279c7059b4a5

8854a2851cdd0666965d324a6123c0f4a7b08050

/voiture.py

eec02f1134c9efeef3bc62ad6d408d0a11060585

[]

no_license

https://github.com/DRAR444/poei-python

ce72b46f1a258a1f34743cb28336bcea4af55fcc

63c55314e3d8a2e7233da00f5aefebfa9ab93138

refs/heads/master

2020-03-19T08:07:14.445816

2018-06-16T08:44:03

136,177,167

0

null

#!/usr/bin/env python # coding: utf-8 class Voiture: def vitesseMax(self): return "500km/h" ma_voiture = Voiture() print(ma_voiture.vitesseMax()) # def __init__(self): #self.nom = "Ferrari" #self.origine = "Italienne" #elf.couleur = "Rouge" #ma_voiture = Voiture() #print("Ma voiture est : " + ma_voiture.nom + " " +"elle est " + ma_voiture.origine + " "+ "et elle est de couleur " +ma_voiture.couleur)

UTF-8

Python

false

436

py

8

voiture.py

8

0.614679

0.605505

0

17

24.705882

138

Hackman238/ZenPacks.ShaneScott.ipSLA

10,892,037,081,896

e8ce4866991ac533221f2f32ab1e75224bcad435

a5b6b8c079e5dd8480db9685295bae5b7e07fcb0

/ZenPacks/ShaneScott/ipSLA/routers.py

dd4e92a3b1bfd7e1424fb79ded0a66bd6151dd65

[]

no_license

https://github.com/Hackman238/ZenPacks.ShaneScott.ipSLA

8b654a083726455430734a5dc171ff749f34d245

ec3185dc9ea4ea2f4233b5e95dfb0bb62d626dff

refs/heads/master

2020-12-24T14:35:24.139328

2012-10-08T17:41:37

6,128,426

1

3

null

from Products.ZenUtils.Ext import DirectRouter, DirectResponse from Products import Zuul class SLARouter(DirectRouter): def _getFacade(self): return Zuul.getFacade('sla', self.context) def manage_delSLAs(self, rttIndex, deviceIp, community): facade = self._getFacade() success, message = facade.manage_delSLAs(rttIndex, deviceIp, community) if success: return DirectResponse.succeed(jobId=message) else: return DirectResponse.fail(message) def manage_writeMemSLAs(self, deviceIp, community): facade = self._getFacade() success, message = facade.manage_writeMemSLAs(deviceIp, community) if success: return DirectResponse.succeed(jobId=message) else: return DirectResponse.fail(message) def manage_addTcpSLAs(self, newId, rttIndex, deviceIp, community, rttMonEchoAdminTargetAddress, rttMonEchoAdminTargetPort, rttMonScheduleAdminRttStartTime=1, rttMonCtrlAdminOwner="zenoss"): facade = self._getFacade() success, message = facade.manage_addTcpSLAs(newId, rttIndex, deviceIp, community, rttMonEchoAdminTargetAddress, rttMonEchoAdminTargetPort, rttMonScheduleAdminRttStartTime=1, rttMonCtrlAdminOwner="zenoss") if success: return DirectResponse.succeed(jobId=message) else: return DirectResponse.fail(message) def manage_addJitterSLAs(self, newId, rttIndex, deviceIp, community, rttMonEchoAdminTargetAddress, rttMonEchoAdminTargetPort, rttMonEchoAdminInterval=60, rttMonEchoAdminNumPackets=100, rttMonScheduleAdminRttStartTime=1, rttMonCtrlAdminOwner="zenoss"): facade = self._getFacade() success, message = facade.manage_addJitterSLAs(newId, rttIndex, deviceIp, community, rttMonEchoAdminTargetAddress, rttMonEchoAdminTargetPort, rttMonEchoAdminInterval=60, rttMonEchoAdminNumPackets=100, rttMonScheduleAdminRttStartTime=1, rttMonCtrlAdminOwner="zenoss") if success: return DirectResponse.succeed(jobId=message) else: return DirectResponse.fail(message) def manage_addDnsSLAs(self, newId, rttIndex, deviceIp, community, rttMonEchoAdminNameServer, rttMonEchoAdminTargetAddressString, rttMonScheduleAdminRttStartTime=1, rttMonCtrlAdminOwner="zenoss"): facade = self._getFacade() success, message = facade.manage_addDnsSLAs(newId, rttIndex, deviceIp, community, rttMonEchoAdminNameServer, rttMonEchoAdminTargetAddressString, rttMonScheduleAdminRttStartTime=1, rttMonCtrlAdminOwner="zenoss") if success: return DirectResponse.succeed(jobId=message) else: return DirectResponse.fail(message) def manage_addDhcpSLAs(self, newId, rttIndex, deviceIp, community, rttMonScheduleAdminRttStartTime=1, rttMonCtrlAdminOwner="zenoss"): facade = self._getFacade() success, message = facade.manage_addDhcpSLAs(newId, rttIndex, deviceIp, community, rttMonScheduleAdminRttStartTime=1, rttMonCtrlAdminOwner="zenoss") if success: return DirectResponse.succeed(jobId=message) else: return DirectResponse.fail(message) def manage_addEchoSLAs(self, newId, rttIndex, deviceIp, community, rttMonEchoAdminTargetAddress, rttMonScheduleAdminRttStartTime=1, rttMonCtrlAdminFrequency=60, rttMonCtrlAdminOwner="zenoss", rttMonCtrlAdminThreshold=5000, rttMonCtrlAdminTimeout=5): facade = self._getFacade() success, message = facade.manage_addEchoSLAs(newId, rttIndex, deviceIp, community, rttMonEchoAdminTargetAddress, rttMonScheduleAdminRttStartTime=1, rttMonCtrlAdminFrequency=60, rttMonCtrlAdminOwner="zenoss", rttMonCtrlAdminThreshold=5000, rttMonCtrlAdminTimeout=5) if success: return DirectResponse.succeed(jobId=message) else: return DirectResponse.fail(message) def manage_addHttpSLAs(self, newId, rttIndex, deviceIp, community, rttMonEchoAdminURL, rttMonScheduleAdminRttStartTime=1, rttMonCtrlAdminFrequency=60, rttMonCtrlAdminOwner="zenoss", rttMonCtrlAdminThreshold=5000, rttMonCtrlAdminTimeout=5): facade = self._getFacade() success, message = facade.manage_addHttpSLAs(newId, rttIndex, deviceIp, community, rttMonEchoAdminURL, rttMonScheduleAdminRttStartTime=1, rttMonCtrlAdminFrequency=60, rttMonCtrlAdminOwner="zenoss", rttMonCtrlAdminThreshold=5000, rttMonCtrlAdminTimeout=5) if success: return DirectResponse.succeed(jobId=message) else: return DirectResponse.fail(message)

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routers.py

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Customer1-Everforce/Repo1

15,539,191,700,856

97c6bad2f8ab706b0a1ffbe428098cd6651dc2dd

8b6fdd216e2a8eed2faa20fe82bf444b135dcc05

/create_issue.py

df65786278880311007d60a60ec911f4a41ee9f4

[]

no_license

https://github.com/Customer1-Everforce/Repo1

2e1dc7b7e4d6db3e94811469ef52372c1d5d449d

5fc74c7060bb2795f80fbd0e92fcec481e8a1ff4

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2023-07-16T03:47:16.557060

2021-09-03T04:21:48

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HTML

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from github import Github import requests import os from pprint import pprint token = os.getenv('GITHUB_TOKEN', '5b80cd6dd28577ed249e762207a2d9831cf8c727') #repo = "API_test" #repo = "everforce_editors" owner = "everforce-github" g = Github(token) #repo = g.get_repo("{owner}/{repo}") repo = g.get_repo("everforce-github/API_test") #repo = g.get_repo("API_test/everforce-github") i = repo.create_issue( title="Issue Title-s2", body="Text of the body.", #assignee="Gri_Vidi", labels=[ repo.get_label("good first issue") ] ) print("Issue created:\n",i) """ g = Github(token) repo = g.get_repo("MartinHeinz/python-project-blueprint") i = repo.create_issue( title="Issue Title", body="Text of the body.", assignee="MartinHeinz", labels=[ repo.get_label("good first issue") ] ) pprint(i) """

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create_issue.py

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Jackiu1997/gcransac-python

11,106,785,449,778

2870fd1d2ac8a9858553d2a1507fd592753baac8

e115ea0da47f88e8d1b0bbe19c2af5e63ea80266

/ransac/ransac_api.py

df492873131ac1d67456e28cb2fbcbf261084d7c

[]

no_license

https://github.com/Jackiu1997/gcransac-python

8264d4efa2eafebcd9664a2692476a3bd54d76f1

050ee2c31f24f90551a0adb2f51aed988f39b16a

refs/heads/master

2022-09-19T00:25:23.234923

2020-06-05T04:17:46

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import math import cv2 import numpy as np from estimator import (EstimatorEssential, EstimatorFundamental, EstimatorHomography) from model import * from sampler import UniformSampler from solver import (SolverEssentialMatrixEightPoint, SolverEssentialMatrixFivePointStewenius, SolverFundamentalMatrixEightPoint, SolverFundamentalMatrixSevenPoint, SolverHomographyFourPoint) from .ransac import RANSAC def __transformInliersToMask(inliers, point_number): """ 转换 inliers 内点序号列表为 cv2 match 所需的 mask 参数 -------- inliers : list 内点序号列表 point_number : int 点集的数目返回 -------- list 包含 0 1 的 mask 列表 """ mask = [] for i in range(point_number): if i in inliers: mask.append(1) else: mask.append(0) mask = np.array(mask) return mask """ 用于特征点匹配，对应矩阵求解的函数 """ def findHomography(src_points, dst_points, threshold=1.0, conf=0.95, max_iters=10000): """ 单应矩阵求解参数 -------- src_points : numpy 源图像特征点集合 dst_points : numpy 目标图像特征点集合 h1, w1: int, int 源图像高度和宽度 h2, w2: int, int 目标图像高度和宽度 threshold : float 决定内点和外点的阈值 conf : float RANSAC置信参数 max_iters : int RANSAC算法最大迭代次数返回 -------- numpy, list 基础矩阵，标注内点和外点的mask """ # 合并points到同个矩阵： # src在前两列，dst在后两列 points = np.c_[src_points, dst_points] ''' GC-RANSAC过程 ''' # 设置模型估计器和模型 estimator = EstimatorHomography(SolverHomographyFourPoint, SolverHomographyFourPoint) model = Homography() # 设置全局采样 main_sampler = UniformSampler(points) # 检查样本是否成功初始化 if not main_sampler.initialized: print("采样器初始化失败\n") return None # 设置GC-RANSAC算法参数 gcransac = RANSAC() gcransac.settings.threshold = threshold gcransac.settings.confidence = conf gcransac.settings.max_iteration_number = max_iters # 运行GC-RANSAC算法 model, inliers = gcransac.run(points, estimator, main_sampler) print(f'Number of iterations = {gcransac.statistics.iteration_number}') # 获取特征点匹配结果（变换矩阵和模型对应内点） H = model.descriptor mask = __transformInliersToMask(inliers, gcransac.point_number) return H, mask

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ransac_api.py

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Saurabh2509/CloudCompare-PythonPlugin

13,194,139,574,869

1a6208724b12bb4ffcfaa586584f983078971092

ad6b36d1b0e0692ec2c3715f95d85f0935d680ec

/script_examples/merge_script.py

c2c9cac2fcd1a3f4b21bb95b3b66408ad19cedc4

[]

no_license

https://github.com/Saurabh2509/CloudCompare-PythonPlugin

6e1e2db8820b3c75d3d4727a238c8c4ad5df61d6

a90b32b599883b1e12391996073e404d2c6a65a8

refs/heads/master

2023-08-15T20:14:20.921088

2021-09-30T09:28:13

null

0

null

import pycc def merge(clouds): total_num_points = sum(cloud.size() for cloud in clouds) merge_result = pycc.ccPointCloud("MergeResult") merge_result.reserve(total_num_points) for cloud_idx, cloud in enumerate(clouds): for point_idx in range(cloud.size()): merge_result.addPoint(cloud.getPoint(point_idx)) pos = 0 for cloud in clouds: for i in range(cloud.getNumberOfScalarFields()): scalarFieldName = cloud.getScalarFieldName(i) idx = merge_result.getScalarFieldIndexByName(scalarFieldName) if idx == -1: idx = merge_result.addScalarField(scalarFieldName) if idx == -1: raise RuntimeError("Failed to add ScalarField") scalarField = cloud.getScalarField(i) sf = merge_result.getScalarField(idx) sf.asArray()[pos: pos + scalarField.size()] = scalarField.asArray()[:] sf.computeMinAndMax() pos += cloud.size() return merge_result def main(): CC = pycc.GetInstance() clouds = CC.getSelectedEntities() merged_cloud = merge(clouds) CC.addToDB(merged_cloud) if __name__ == '__main__': main()

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py

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merge_script.py

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xiaming9880/Curvature-Learning-Framework

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1dcb23afe2b907636345ac5f94552eca12c53999

/examples/hgcn/data_utils.py

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permissive

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db1be0b7ed57f046bc5b359dbb0155708cd94611

refs/heads/main

2023-08-26T18:48:48.821531

2021-11-15T06:14:09

null

0

null

# Copyright (C) 2016-2021 Alibaba Group Holding Limited # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== import os import sys sys.path.append('.') import numpy as np import pickle as pkl import tensorflow as tf import scipy.sparse as sp from config import training_config def normalize(mx): rowsum = np.array(mx.sum(1)) r_inv = np.power(rowsum, -1).flatten() r_inv[np.isinf(r_inv)] = 0. r_mat_inv = sp.diags(r_inv) mx = r_mat_inv.dot(mx) return mx def augment(adj, features): deg = np.squeeze(np.sum(adj, axis=0).astype(int)) deg[deg > 5] = 5 deg_onehot = np.array(np.eye(6)[deg], dtype=np.float32).squeeze() const_f = np.ones((features.shape[0], 1)) features = np.concatenate([features, deg_onehot, const_f], axis=1) return features def process(adj, features, normalize_adj, normalize_feats): if sp.isspmatrix(features): features = np.array(features.todense()) if normalize_feats: features = normalize(features) adj = adj + sp.eye(adj.shape[0]) if normalize_adj: adj = normalize(adj) adj = np.array(adj.toarray(), dtype=np.float32) return adj, features def mask_edges(adj, val_prop): x, y = sp.triu(adj).nonzero() pos_edges = np.array(list(zip(x, y))) np.random.shuffle(pos_edges) x, y = sp.triu(sp.csr_matrix(1. - adj.toarray())).nonzero() neg_edges = np.array(list(zip(x, y))) np.random.shuffle(neg_edges) m_pos = len(pos_edges) n_val = int(m_pos * val_prop) val_edges, train_edges = pos_edges[-n_val:], pos_edges[:-n_val] val_edges_false = neg_edges[-n_val:] train_edges_false = np.concatenate([neg_edges, val_edges], axis=0) adj_train = sp.csr_matrix((np.ones(train_edges.shape[0]), (train_edges[:, 0], train_edges[:, 1])), shape=adj.shape) adj_train = adj_train + adj_train.T return adj_train, train_edges, train_edges_false, val_edges, val_edges_false def load_data_airport(data_path, normalize_adj, normalize_feat): adj = pkl.load(open(os.path.join(data_path, "adj.pkl"), 'rb')) features = pkl.load(open(os.path.join(data_path, "features.pkl"), 'rb')) adj = sp.csr_matrix(adj) data = {'adj_train': adj, 'features': features} adj_train, train_edges, train_edges_false, val_edges, val_edges_false = mask_edges(adj, 0.2) data['adj_train'] = adj_train data['train_edges'], data['train_edges_false'] = train_edges, train_edges_false data['val_edges'] = [list(p) + [1] for p in val_edges] + [list(p) + [0] for p in val_edges_false] data['adj_train_norm'], data['features'] = process(data['adj_train'], data['features'], normalize_adj, normalize_feat) data['features'] = np.array(augment(data['adj_train'], data['features']), dtype=np.float32) return data def get_train_batch(pos_edge_set, neg_edge_set): pos_dataset = tf.data.Dataset.from_tensor_slices(pos_edge_set) pos_dataset = pos_dataset.shuffle(buffer_size=training_config["shuffle_buffer"]).batch( training_config["batch_size"], drop_remainder=False) pos_dataset = pos_dataset.repeat() pos_iter = pos_dataset.make_one_shot_iterator() pos_batch = pos_iter.get_next() pos_label = tf.ones(shape=(tf.shape(pos_batch)[0])) neg_dataset = tf.data.Dataset.from_tensor_slices(neg_edge_set) neg_dataset = neg_dataset.shuffle(buffer_size=training_config["shuffle_buffer"]).batch( training_config["neg_samples"] * training_config["batch_size"], drop_remainder=False) neg_dataset = neg_dataset.repeat() neg_iter = neg_dataset.make_one_shot_iterator() neg_batch = neg_iter.get_next() batch = tf.concat([pos_batch, neg_batch], axis=0) neg_label = tf.zeros(shape=(tf.shape(neg_batch)[0])) label = tf.concat([pos_label, neg_label], axis=0) return batch, label def get_test_batch(edge_set_with_label): dataset = tf.data.Dataset.from_tensor_slices(edge_set_with_label).batch(training_config["batch_size"], drop_remainder=False) data_iter = dataset.make_initializable_iterator() batch = data_iter.get_next() init = data_iter.initializer return batch, init

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MerlinAu/leetcode-python

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/code/Template/DP.py

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[]

no_license

https://github.com/MerlinAu/leetcode-python

caa2da9ebe10988aa88bc64bf50be6d5b2fb6b87

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refs/heads/master

2020-05-24T08:05:46.912648

2019-08-30T07:28:54

null

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null

'''template of dynamic programming''' # 状态定义 # dp = new int [m + 1][n + 1]; # 初始状态 # dp[0][0] = x; # dp[0][1] = y; # ... # DP状态的推导 ''' for i = 0; i <= n; ++i { for j = 0; j <= m; ++j { ... dp[i][j] = min {dp[i - 1][j], dp[i][j - 1], etc.} } } ''' # return dp[m][n]; 最优解

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BDNYC/astrodbkit

15,178,414,426,317

58f1299b64c63323323dc587bf51c6e3efa54d7b

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/astrodbkit/__init__.py

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permissive

https://github.com/BDNYC/astrodbkit

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refs/heads/master

2021-04-19T00:03:14.527412

2020-05-28T13:01:25

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2018-05-03T19:57:01

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from .astrodb import * from .astrocat import * from .votools import * from pkg_resources import get_distribution __version__ = '0.6.6'

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connectthefuture/psdmrepo

5,669,356,860,204

3b6e5ce83aeb6aaab9ceb4823fdf00126a5f401f

786de89be635eb21295070a6a3452f3a7fe6712c

/psddl/tags/V00-08-06/tags/andy-20101027-01/psddl/src/Type.py

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[]

no_license

https://github.com/connectthefuture/psdmrepo

85267cfe8d54564f99e17035efe931077c8f7a37

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refs/heads/master

2021-01-13T03:26:35.494026

2015-09-03T22:22:11

null

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#-------------------------------------------------------------------------- # File and Version Information: # $Id$ # # Description: # Module Type... # #------------------------------------------------------------------------ """DDL class representing a type (class). This software was developed for the SIT project. If you use all or part of it, please give an appropriate acknowledgment. @see RelatedModule @version $Id$ @author Andrei Salnikov """ #------------------------------ # Module's version from CVS -- #------------------------------ __version__ = "$Revision$" # $Source$ #-------------------------------- # Imports of standard modules -- #-------------------------------- import sys #--------------------------------- # Imports of base class module -- #--------------------------------- #----------------------------- # Imports for other modules -- #----------------------------- #---------------------------------- # Local non-exported definitions -- #---------------------------------- #------------------------ # Exported definitions -- #------------------------ #--------------------- # Class definition -- #--------------------- class Type ( object ) : #---------------- # Constructor -- #---------------- def __init__ ( self, name, **kw ) : self.name = name self.version = kw.get('version') self.type_id = kw.get('type_id') self.levels = kw.get('levels') self.comment = kw.get('comment') self.package = kw.get('package') self.size = kw.get('size') self.align = kw.get('align') self.pack = kw.get('pack') if self.pack : self.pack = int(self.pack) self.enums = [] self.constants = [] self.xtcConfig = [] self.attributes = [] self.methods = [] self.repeat = None def __str__(self): return "<Type(%s)>" % self.__dict__ def __repr__(self): return "<Type(%s)>" % self.name # # In case someone decides to run this module # if __name__ == "__main__" : # In principle we can try to run test suite for this module, # have to think about it later. Right now just abort. sys.exit ( "Module is not supposed to be run as main module" )

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majdigital/bigworldgraph

7,550,552,535,505

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/backend/bwg/tasks/relation_merging.py

2e6766f7abc59b0a452afcfa269bead98b7c32c0

[ "LicenseRef-scancode-unknown-license-reference", "MIT" ]

permissive

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refs/heads/master

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# -*- coding: utf-8 -*- """ Defining a pipeline task that merges relation extracted from different tasks, e.g. participation extraction or naive open relation extraction. """ # EXT import luigi # PROJECT from bwg.decorators import time_function from bwg.mixins import ArticleProcessingMixin from bwg.serializing import serialize_relation from bwg.tasks.naive_ore import NaiveOpenRelationExtractionTask from bwg.tasks.participation_extraction import ParticipationExtractionTask class RelationMergingTask(luigi.Task, ArticleProcessingMixin): """ Merge relations gained from OpenRelationExtractionTask and ParticipationExtractionTask. """ def requires(self): return ParticipationExtractionTask(task_config=self.task_config),\ NaiveOpenRelationExtractionTask(task_config=self.task_config) def output(self): text_format = luigi.format.TextFormat(self.task_config["CORPUS_ENCODING"]) output_path = self.task_config["RELATION_MERGING_OUTPUT_PATH"] return luigi.LocalTarget(output_path, format=text_format) @time_function(is_classmethod=True) def run(self): with self.input()[0].open("r") as pe_file, self.input()[1].open("r") as ore_file, \ self.output().open("w") as output_file: for pe_line, ore_line in zip(pe_file, ore_file): self.process_articles( (pe_line, ore_line), new_state="merged_relations", serializing_function=serialize_relation, output_file=output_file ) def task_workflow(self, article, **workflow_resources): article_data = article["data"] for sentence_id, sentence_json in article_data.items(): sentence_dates = sentence_json["data"] sentence = sentence_dates["data_extracted_participations"]["data"]["sentence"] relations = self._get_relations_from_sentence_json(sentence_dates["data_extracted_participations"]) relations.extend(self._get_relations_from_sentence_json(sentence_dates["data_extracted_relations"])) serializing_arguments = { "sentence_id": sentence_id, "sentence": sentence, "relations": relations, "infix": "ORE:PE" } yield serializing_arguments @staticmethod def _get_relations_from_sentence_json(sentence_json): """ Create relation tuples based on a sentence JSON object. :param sentence_json: Sentence as JSON object. :type sentence_json: dict :return: List of relations as tuples. :rtype: list """ return [ ( relation_json["data"]["subject_phrase"], relation_json["data"]["verb"], relation_json["data"]["object_phrase"] ) for relation_id, relation_json in sentence_json["data"]["relations"].items() ] def _is_relevant_article(self, article): """ Override ArticleProcessingMixin's relevance criterion. :return: Result of check. :rtype: bool """ return len(article["data"]) > 0 def _is_relevant_sentence(self, sentence): """ Override ArticleProcessingMixin's relevance criterion. :return: Result of check. :rtype: bool """ # Separate sentence from sentence ID sentence = list(sentence.values())[0] return len(sentence["data"]["relations"]) > 0

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Mehedi109/Ambulance-Service

17,944,373,371,456

3fecc9057a188da6ceb7c77d5e2832c64d7e7158

49e7d8a7574ada9bdfc8cb66a5e1afb0eab8eb57

/project_app/views.py

dae15c8302d36a39e0fd149d33fdfe1f528422e4

[]

no_license

https://github.com/Mehedi109/Ambulance-Service

bd5bbfc7317a5f6efd7556411202fc26487666f2

eaa1b8bb52ee5239a89e235fdd3db5eb186ec9e4

refs/heads/main

2023-01-13T01:17:24.284389

2020-11-12T11:49:26

304,373,928

0

null

from django.views.generic import ListView from django.shortcuts import render,redirect,HttpResponse,get_object_or_404 from django.core.paginator import Paginator from django.db.models import Q from . models import Category from . models import Quot from . models import ability_top from . models import ability_bottom from . models import slider from . models import service_category from . models import service_section from .models import service_area from .models import service_area_body from .models import border_top from .models import border_bottom #from . forms import articleForm from .forms import articleForm from .models import article '''from .models import user''' from .forms import rent_detailsForm from . models import rent_details #from .forms import userCommentForm #from . models import userComment from . models import freezer,general,ICU,emergency from .models import postComment from .forms import postCommentForm #from .models import reply #from .forms import replyForm class HomeView(ListView): template_name="index.html" model=Quot #model=service_category #model=service_section def get_queryset(self): query_set=super().get_queryset() return query_set.select_related ('Category') def index(request): post=service_category.objects.all content=service_section.objects.all quote=Quot.objects.all s_a_c=service_area.objects.all s_a_b=service_area_body.objects.all slider_post=slider.objects.all border_top_post=get_object_or_404(border_top) #border_bottom_post=border_bottom.objects.all border_bottom_post=border_bottom.objects.all ability_top_post=get_object_or_404(ability_top) ability_bottom_post=ability_bottom.objects.all emergency_post=get_object_or_404(emergency) context={ "post":post, "content":content, "quote":quote, "s_a_c":s_a_c, "sab":s_a_b, "post2":border_top_post, "border_bottom_post":border_bottom_post, "post3":ability_top_post, "ability_bottom_post":ability_bottom_post, #"post4":ability_bottom_post "slider_post":slider_post, "post4":emergency_post, } return render (request,"index.html",context) def terms(request): quote=Quot.objects.all post2=slider.objects.all() context={ "quote":quote, "post2":post2 } return render(request,"terms.html",context) def ac_post(request): post=get_object_or_404(general) post2=slider.objects.all context={ "post":post, "post2":post2 } return render(request,"ac.html",context) def general_post(request): post=get_object_or_404(freezer) post2=slider.objects.all context={ "post":post, "post2":post2 } return render(request,"general.html",context) def icu_post(request): post=get_object_or_404(ICU) post2=slider.objects.all context={ "post":post, "post2":post2 } return render(request,"icu.html",context) def contact(request): return render(request,"contact.html") def post(request): if request.user.is_authenticated: form=articleForm(request.POST or None) if form.is_valid(): instance=form.save(commit=False) instance.save(); return redirect('/blog') return render (request,"post.html",{"form":form}) def post_update(request,id): #if request.user.is_authenticated: if request.user.is_staff or request.user.is_superuser: post=get_object_or_404(article,id=id) #post=article.objects.get(id=id) form=articleForm(request.POST or None,instance=post) if form.is_valid(): instance=form.save(commit=False) instance.save() #messages.success(request,'Updated Successfully') return redirect('/author_blog') return render(request,"post.html",{"form":form}) return HttpResponse() def blog_update(request,id): post=get_object_or_404(article,id=id) #post=article.objects.get(id=id) return redirect('/blog') return render(request,"blog.html",{"post":post}) #return HttpResponse() def delete(request,id): #if request.user.is_authenticated: if request.user.is_staff or request.user.is_superuser: post=get_object_or_404(article,id=id) post.delete() return redirect('/author_blog') def blog(request): post=article.objects.all().order_by('id') ##post=get_object_or_404(article,id=id) #getComment=userComment.objects.filter() #form=userCommentForm(request.POST or None) #if form.is_valid(): #instance=form.save(commit=False) #instance.post=post #instance.save() context={ "post":post, #"form":form, #"comment":getComment } return render(request,"blog.html",context) #return HttpResponse() def single_blog(request,id): #post=article.objects.all() #post=article.objects.get(id=id) post=get_object_or_404(article,id=id) #post=article.objects.get(id=postid) getComment=postComment.objects.filter(post=id) '''getComment=userComment.objects.filter(post=id)#reply=none user''' #getReply=reply.objects.filter(post=id) if request.method=="POST": form=postCommentForm(request.POST or None) '''form=userCommentForm(request.POST or None) user''' if form.is_valid(): instance=form.save(commit=False) instance.post=post parent_id = request.POST.get('comment_id') #reply-section comment_qs=None if parent_id: comment_qs = postComment.objects.get(id=parent_id) instance.save() '''parent_obj=None try: parent_id=int(request.POST.get('parent_id')) except: parent_id=None if parent_id: parent_obj=postComment.objects.get(parent_id) if parent_obj: replay_comment=form.save(commit=False) replay_comment.parent=parent_obj''' '''reply_id = request.POST.get('comment_id') #reply-section comment_qs=None if reply_id: comment_qs = userComment.objects.get(id=reply_id) comment = userComment.objects.create(post=post, user=request.user, content=content, reply=comment_qs) comment.save()''' return redirect('single_blog',id) else: '''form=userCommentForm() user''' form=postCommentForm() context={ "post":post, "form":form, "comment":getComment, #"reply":replay_comment, #"comment":getComment, user } return render(request,"single_blog.html",context) #return HttpResponse() def post_comment(request,id): if request.method=="POST": comment=request.POST.get("comment") postid=request.POST.get("postid") post=article.objects.get(id=postid) parentid=request.POST.get("parentid") if parentid== "": comment=postComment(comment=comment,post=post) else: parent=postComment.objects.get(id=parentid) comment=postComment(comment=comment,post=post,parent=parent) comment.save() return redirect('single_blog',id) return render(request,"single_blog.html",context) def comment_delete(request,id): post=get_object_or_404(postComment,id=id) post.delete() return redirect('single_blog',id) return HttpResponse() def rent_show(request): post=rent_details.objects.all() search=request.POST.get('q') if search: post=post.filter( Q(From__icontains=search) ) paginator = Paginator(post, 5) # Show 25 contacts per page. page = request.GET.get('page') total_post = paginator.get_page(page) context={ #"post":post, "post":total_post } return render(request,"rent.html",context) def rent(request): #post=get_object_or_404(rent_details,id=id) post=rent_details.objects.all() first=rent_details.objects.first() last=rent_details.objects.last() search=request.POST.get('q') if search: post=post.filter( Q(From__icontains=search) | Q(To__icontains=search) ) paginator = Paginator(post, 10) # Show 25 contacts per page. page = request.GET.get('page') total_post = paginator.get_page(page) context={ "post":total_post, "first":first, "last":last, } return render(request,"rent.html",context) def rent_post(request): if request.user.is_authenticated: form=rent_detailsForm(request.POST or None) if form.is_valid(): instance=form.save(commit=False) instance.save(); return redirect('/author_rent') return render (request,"rental.html",{"form":form}) def rent_update(request,id): if request.user.is_authenticated: post=get_object_or_404(rent_details,id=id) #post=article.objects.get(id=id) form=rent_detailsForm(request.POST or None,instance=post) if form.is_valid(): instance=form.save(commit=False) instance.save() return redirect('/author_rent') return render(request,"rental.html",{"form":form}) return HttpResponse() def rent_delete(request,id): if request.user.is_authenticated: post=get_object_or_404(rent_details,id=id) post.delete() return redirect('/author_rent')

UTF-8

Python

false

8,425

py

43

views.py

22

0.727596

0.719169

0

297

27.367003

104

MathactwFX/python

19,335,942,778,069

0924f256d030359d157e7fda448cb999f49577c9

a249beaa5dd9f7838b2c44364c88fc7056814033

/language/python_overview.py

da3f3b33d5da9262764ffa171980158426b853fc

[]

no_license

https://github.com/MathactwFX/python

0d3254d9741b0d6f0570f885d53d86e7e44c267e

a0f2797feebc5188921d1e5850008c5811e9c9b8

refs/heads/master

2019-07-10T06:56:10.717252

2017-06-29T02:01:13

91,102,622

0

null

#!/usr/bin/env python # -*- coding: utf-8 -*- """a test module""" # content ref = Python教程 | http://www.liaoxuefeng.com/wiki/001374738125095c955c1e6d8bb493182103fac9270762a000 # ******** 关键字 ******** # g = lambda x: x^1 # print(g(2)) # # def make_counter(): # count = 1 # def counter(): # nonlocal count # count += 2 # return count # return counter # def make_counter_test(): # mc = make_counter() # print(mc()) # print(mc()) # print(mc()) # make_counter_test() # # def g(n): # for i in range(5): # yield i**3 # for i in g(5): # print(i, ':') # # def fab(max): # a,b=0,1 # while a < max: # yield a # a,b=b,a+b # for a in fab(20): # print(a,',','end') # a=fab(7) # # size = 20 # def fab_rec(x,y): # # global size # size=30 # if x>size: # return # print(x) # fab_rec(y,x+y) # fab_rec(0,1) # print(size) # # assert size > 50 # # from sys import * # print('path:', path) # ******** 基础 ******** # a = u"中文" # print(a, end='\n\n') # print(u'中'.encode('utf-8')) # print(b'\xcb\xea\xca\xb1\xb8\xc3\xd6\xaa\xb5\xc0\xb5\xc4'.decode('utf-8')) # print(b'zhong'.decode('utf-8')) # print(len(u'中')) # print("hi,%s,you\n have%d %%" % ('michael', 11)) # list是一种有序的集合 can by dynamic add or remove # classmates = ['hha', 2, [1, 2], 3, 4] # classmates.insert(1,'e') # classmates.pop() # classmates2 = ['1','3','5','4','2'] # classmates2.sort() # print(classmates2) # classmates[2]='replace' # print(classmates) # classmates.append(1.2) # print(classmates[-1]) # print(len(classmates)) # print(classmates[2]) # tuple ordered list, but couldn't be changed, the pointer is never changed # t = (1, [1,2]) # t[1][1]=3 # print(t) # for x in t: # print(x) # age = 20 # if age >= 8: # print("teenager") # elif age >= 18: # print("adult") # else: # print(True) # y=range(5) # print(y.count(1)) # for x in y: # print(x) # birth = input('birth: ') # if int(birth) < 2000: # print('00前') # else: # print('00后') # d={'michael':18,'bob':11, "jane":25} # print(d['jane']) # d['wng']=19 # d.pop('wng') # print(d.get('wg')) # print(d) # print(d.items()) # s = set([1,23,3,4,5,3]) # s.add(6) # s.add(2) # s.remove(7) # print(s) # s2=set([3,4,5,111,222]) # print(s | s2) # s2.add([1,2]) # s2.add((1,2)) # print(s2) # s3=set((1,2,3)) # print(s3) # ******** function ******** # s = abs(-1) # print(s) # # def myabs(x): # pass # if not isinstance(x, (int, float)): # raise TypeError('bad operand type') # else: # if x >= 0: # return x # else: # return -x # # def mynonefunc(): # pass # # # try: # print(myabs('a')) # except TypeError: # print("bad operand") # finally: # print("arrive finally") # print(mynonefunc()) # # import math # def move(x, y, step, angle=0): # nx = x + step*math.cos(angle) # ny = y + step*math.sin(angle) # return nx, ny # r = move(1, 2, 3, 45*math.pi/180.0) # print(r) # # def myclosure(): # def inner(): # return [1,2,3] # return inner # print(myclosure()()) # def calc(*numbers): # sum = 0 # for n in numbers: # sum = sum + n * n # return sum # list = [1,2,3] # print(calc(*list)) # print('1','2',3,']') # # def person(name, age, **kw): # print('name:', name, 'age:', age, 'other:', kw) # hah={'nan':12,"jj":'hah'} # person(12,13,hha=12,ll='121') # # def fact(n): # if n==1: # return 1 # return n * fact(n - 1) # print(fact(3)) # # 尾递归 # def fact_tail(n): # return fact_iter(1, 1, n) # def fact_iter(product, count, max): # if count > max: # return product # return fact_iter(product * count, count + 1, max) # print(fact_tail(1000)) # ******** 高级特性 ******** # L = ['Michael', 'Sarah', 'Tracy', 'Bob', 'Jack'] # print(L[-2:]) # print(L[:2]) # # L = range(0,100) # print(list(L[:10:2])) # print('afsdf'[:3]) # d = {'a': 1, 'b': 2, 'c': 3} # for key in d: # print(key) # for value in d.values(): # print(value) # from collections import Iterable # print(isinstance(d, Iterable)) # for i, key in enumerate(d): # print(i,key) # # print(list(range(1,11))) # print([x*x for x in range(1,11) if x%2==1]) # print([m+n for n in 'abc' for m in '123']) # import os # print([d for d in os.listdir('.')]) # for k,v in d.items(): # print(k,'=',v) # print([k+'='+chr(v) for k,v in d.items()]) # yint = 123 # print(isinstance(yint, str)) # # g=(x*x for x in range(10)) # # print(g.__next__()) # # print(g.__next__()) # for n in g: # print(n) # ******** 函数式编程 ******** # print(abs) # # abs = 2 # print(abs(-2)) # # def add(x, y, f): # return f(x) + f(y) # print(add(-5, 6, abs)) # # def f(x): # return x * x # L=[1,2,3] # print(list(map(f, L))) # print(list(map(str, L))) # # from functools import reduce # def add(x,y): # return x+y # print(reduce(add,[1,2,3,4])) # print(sum([1,2])) # # def char2num(s): # return {'0': 0, '1': 1, '2': 2, '3': 3, '4': 4, '5': 5, '6': 6, '7': 7, '8': 8, '9': 9}[s] # def str2int(s): # return reduce(lambda x,y:x*10+y,map(char2num,s)) # print(str2int('13579')) # # def prod(x,y): # return x*y # print(reduce(prod,[1,2,3,6])) # # def norm(s): # return '%s%s' % (str.upper(s[0]), str.lower(s[1:])) # # return list(s[0].upper()) + list(map(str.lower, s[1:])) # print(list(map(norm,['adam', 'LISA', 'barT']))) # # def is_odd(n): # return n %2 ==1 # print(list(filter(is_odd,[1,2,3,4]))) # # def not_empty(s): # return s and s.strip() # # def reversed_cmp(x, y): # if x > y: # return -1 # if x < y: # return 1 # return 0 # # # print(sorted([36, 5, 12, 9, 21], lambda x:x,True)) # print([36, 5, 12, 9, 21].sort) # # def lazy_sum(*args): # def sum(): # ax = 0 # for n in args: # ax = ax + n # return ax # return sum # f1 = lazy_sum(1, 3, 5, 7, 9) # f2 = lazy_sum(1, 3, 5, 7, 9) # print(f1) # print(f2) # print(f1 is f2) # # print(lazy_sum.__name__) # # # def log(func): # # def wrapper(*args, **kw): # # print('call %s():' % func.__name__) # # return func(*args, **kw) # # return wrapper # import functools # def log(*hah): # def decorator(func): # @functools.wraps(func) # def wrapper(*args, **kw): # print('%s %s():' % (hah[0], func.__name__)) # f = func(*args, **kw) # print('%s %s():' % (hah[1], func.__name__)) # return f # return wrapper # return decorator # # @log('execute','end') # def now(): # print('2013-12-25') # now() # print(now.__name__) # print(int('111', 2)) # # import sys # print(sys.argv) # print(__doc__) # ******** 模块 ******** # import Image, ImageFilter # im = Image.open("C:\\Users\\jrm\\Desktop\\01.jpg") # # print(im.format, im.size, im.mode) # # im.thumbnail((200,50)) # im2 = im.filter(ImageFilter.BLUR) # im2.save('C:\\Users\\jrm\\Desktop\\01_thumb.jpg', 'JPEG') # ******** OOP ******** # class Student(object): # # __slots__ = ('__name', '__score') # def __init__(self, name, score): # self.__name = name # self.__score = score # def print_score(self): # print('%s: %s' % (self.__name, self.__score)) # bart=Student('Bart Simpson', 59) # lisa = Student('lisa Simpson', 87) # bart.__name = 'changed' # bart.print_score() # lisa.print_score() # print(bart.__name) # print(bart._Student__name) # print(bart) # print(Student) # # class Animal(object): # def run(self): # print('Animal is running...') # class Dog(Animal): # def run(self): # print('Dog is running') # class Cat(Animal): # def run(self): # print('Cat is running') # dog = Dog() # cat = Cat() # dog.run() # cat.run() # def run_twice(hh): # hh.run() # hh.run() # run_twice(dog) # run_twice(cat) # # print(type('12')) # # import types # print(type(int)) # print(dir(cat)) # print('abc'.__doc__) # print(len('abc'), 'abc'.__len__()+1) # print('abc'.upper()) # # print(callable(dog.run)) # ******** 错误、调试和测试 ******** # import logging # logging.basicConfig(level=logging.INFO) # try: # print('try...') # r = 10 / 0 # print('result:', r) # except ZeroDivisionError as e: # # print('except:', e) # logging.info('af') # logging.exception(e) # else: # print('no fault') # finally: # print('finally...') # print('END') # ******** IO编程 ******** # with open('/path/to/file', 'r') as f: # print(f.read()) # import os # print(os.name, os.getenv('path')) # print([x for x in os.listdir('.') if os.path.isdir(x)]) # # try: # import cPickle as pickle # except ImportError: # import pickle # # d = dict(name='Bob', age=20, score=88) # # f = open('dump.txt', 'wb') # # pickle.dump(d, f) # with open('dump.txt', 'rb') as f: # d = pickle.load(f) # # f.close() # print(d) # import json # d = dict(name='Bob', age=20, score=None) # print(json.dumps(d)) # ******** 进程和线程 ******** # ******** 正则表达式 ******** # import re # print(re.match(r'^\d{3}\-\d{3,8}', '010-12345')) # if re.match(r'^\d{3}\-\d{3,8}', '010-12345'): # print('ok') # ******** 常用内建模块 ******** # from collections import * # namedtuple # deque # defaultdict # OrderedDict # c = Counter() # for ch in 'programming': # c[ch] = c[ch] + 1 # print(c) # # from HTMLParser import HTMLParser # # from htmlentitydefs import name2codepoint # # class MyHTMLParser(HTMLParser): # # def handle_starttag(self, tag, attrs): # print('<%s>' % tag) # # def handle_endtag(self, tag): # print('</%s>' % tag) # # def handle_startendtag(self, tag, attrs): # print('<%s/>' % tag) # # def handle_data(self, data): # print('data') # # def handle_comment(self, data): # print('') # # def handle_entityref(self, name): # print('&%s;' % name) # # def handle_charref(self, name): # print('&#%s;' % name) # # parser = MyHTMLParser() # print(parser.feed('<html><head></head><body><p>Some <a href=\"#\">html</a> tutorial...<br>END</p></body></html>')) # import base64 # base64.encode('fasd') # import struct # print(struct.pack('>I', 10240099)) # import hashlib # md5 = hashlib.md5() # md5.update(b'how are you') # sha1 = hashlib.sha512() # sha1.update(b'how fsdf fsadf fdsa f as fasd sdfa 0b064373fb4dd7356db6e83ec9c39e31ba9c335c') # print(md5.hexdigest()) # print(sha1.hexdigest()) # ******** GUI ******** # from tkinter import * # class Application(Frame): # def __init__(self, master=None): # Frame.__init__(self, master) # self.pack() # self.createWidgets() # # def createWidgets(self): # self.helloLabel = Label(self, text='Hello, world!') # self.helloLabel.pack() # self.quitButton = Button(self, text='Quit', command=self.quit) # self.quitButton.pack() # app = Application() # # 设置窗口标题: # app.master.title('Hello World') # # 主消息循环: # app.mainloop() # ******** 网络编程 ******** # 导入socket库: # import socket # # 创建一个socket: # s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) # # 建立连接: # s.connect(('www.sina.com.cn', 80)) # # 发送数据: # s.send(b'GET / HTTP/1.1\r\nHost: www.sina.com.cn\r\nConnection: close\r\n\r\n') # # 接收数据: # buffer = [] # while True: # # 每次最多接收1k字节: # d = s.recv(1024) # if d: # buffer.append(d) # else: # break # data = b''.join(buffer) # print(data) # # 关闭连接: # s.close() # header, html = data.split(b'\r\n\r\n', 1) # print(header) # # 把接收的数据写入文件: # with open('C:\\Users\\jrm\\Desktop\\sina.html', 'wb') as f: # f.write(html) # ******** 数据库 ******** # import mysql.connector # conn = mysql.connector.connect(user='root', password='root', database='test', use_unicode=True) # # cursor = conn.cursor() # # print(cursor) # # cursor.execute('create table user (id varchar(20) primary key, name varchar(20))') # # cursor.execute('insert into user (id, name) values (%s, %s)', ['1', 'Michael']) # # print(cursor.rowcount) # # conn.commit() # # cursor.close() # # # cursor = conn.cursor() # cursor.execute('select * from user where id = %s' % '1') # values = cursor.fetchall() # print(values) # # cursor.close() # print('123') # # 导入: # from sqlalchemy import Column, String, create_engine # from sqlalchemy.orm import sessionmaker # from sqlalchemy.ext.declarative import declarative_base # # # 创建对象的基类: # Base = declarative_base() # # # 定义User对象: # class User(Base): # # 表的名字: # __tablename__ = 'user' # # # 表的结构: # id = Column(String(20), primary_key=True) # name = Column(String(20)) # # # 初始化数据库连接: # engine = create_engine('mysql+mysqlconnector://root:root@localhost:3306/test') # # 创建DBSession类型: # DBSession = sessionmaker(bind=engine) # # 创建session对象: # session = DBSession() # # 创建新User对象: # new_user = User(id='8', name='Bobbbbb') # # 添加到session: # session.add(new_user) # # 提交即保存到数据库: # session.commit() # # 关闭session: # session.close() # 创建Session: # session = DBSession() # # 创建Query查询，filter是where条件，最后调用one()返回唯一行，如果调用all()则返回所有行: # user = session.query(User).filter(User.id=='5').one() # # 打印类型和对象的name属性: # print('type:', type(user)) # print('name:', user.name) # # 关闭Session: # session.close() # ******** web开发 ******** # hello.py # def application(environ, start_response): # start_response('200 OK', [('Content-Type', 'text/html')]) # return '<h1>Hello, web!</h1>' # # # server.py # # 从wsgiref模块导入: # from wsgiref.simple_server import make_server # # 导入我们自己编写的application函数: # # from hello import application # # # 创建一个服务器，IP地址为空，端口是8000，处理函数是application: # httpd = make_server('localhost', 8000, application) # print("Serving HTTP on port 8000...") # # 开始监听HTTP请求: # httpd.serve_forever() # from flask import Flask # from flask import request # from flask import render_template # # app = Flask(__name__) # # @app.route('/', methods=['GET', 'POST']) # def home(): # return '<h1>Home</h1>' # # @app.route('/signin', methods=['GET']) # def signin_form(): # return '''<form action="/signin" method="post"> # <p><input name="username"></p> # <p><input name="password" type="password"></p> # <p><button type="submit">Sign In</button></p> # </form>''' # # @app.route('/signin', methods=['POST']) # def signin(): # # 需要从request对象读取表单内容： # if request.form['username']=='admin' and request.form['password']=='password': # return '<h3>Hello, admin!</h3>' # return '<h3>Bad username or password.</h3>' # # if __name__ == '__main__': # app.run() # ******** web开发 ******** # ******** 实战 ******** # db orm mvc 前端模板部署移动app and so on

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MrDeff/bitrix-crest

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from setuptools import setup setup( name='bitrix-crest', version='0.0.1', packages=['b24rest'], url='https://github.com/MrDeff/bitrix-crest', license='MIT', author='Evgeniy Pedan', author_email='e.pedan@gmail.com', description='Библиотека для работы с rest Bitrix24' )

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larkspur78/capstone

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[]

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from django.apps import AppConfig class VirtualtrainerConfig(AppConfig): name = 'virtualtrainer'

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UVA-DSI-2019-Capstones/ARL

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from sklearn.ensemble import RandomForestClassifier from sklearn.metrics import classification_report, confusion_matrix, accuracy_score, f1_score from gensim.corpora.dictionary import Dictionary from gensim.models import LdaModel from shorttext.utils import standard_text_preprocessor_1 import pandas as pd import os dir = os.getcwd() #Create test set corpus test = pd.read_csv('test_set.csv') pre = standard_text_preprocessor_1() test['processed'] = test['response_text'].apply(pre) test_corpus = test['processed'].apply(lambda x : x.split(' ')) dict_test = Dictionary(test_corpus) bow_corpus_test = [dict_test.doc2bow(doc) for doc in test_corpus] #Create training set corpus train = pd.read_csv('train_set.csv') train['processed'] = train['response_text'].apply(pre) train_corpus = train['processed'].apply(lambda x : x.split(' ')) dict_train = Dictionary(train_corpus) bow_corpus_train = [dict_train.doc2bow(doc) for doc in train_corpus] df_results = pd.DataFrame(columns = ['n_estimaters', 'depth', 'accuracy', 'f1','num_topics']) #Load LDA model for number_of_topics in range(2,30): temp_file = 'LDA_{}_topic.model'.format(number_of_topics) temp_file = os.path.join(dir, 'LDA_models', temp_file) lda = LdaModel.load(temp_file) test_df = pd.DataFrame() train_df = pd.DataFrame() for i in range(0, len(bow_corpus_test)): test_df = pd.concat([test_df, pd.DataFrame(lda.get_document_topics(bow = bow_corpus_test[i], minimum_probability=0.000001))[1]], axis = 1) for i in range(0, len(bow_corpus_train)): train_df = pd.concat([train_df, pd.DataFrame(lda.get_document_topics(bow = bow_corpus_train[i], minimum_probability=0.000001))[1]], axis = 1) test_df = test_df.transpose() train_df = train_df.transpose() print('Start of Tree') for m_depth in range(2, 30, 2): print(m_depth) for n_est in range(100,300,50): print(str(m_depth) + ' - ' + str(n_est)) clf = RandomForestClassifier(n_estimators=n_est, max_depth=m_depth, random_state=3214) clf.fit(train_df, train['response_round_score']) y_pred = clf.predict(test_df) print('Number of topics {}'.format(number_of_topics)) f1 = f1_score(test['response_round_score'], y_pred, average = 'weighted') accuracy = accuracy_score(test['response_round_score'], y_pred) print('Score: {}'.format(accuracy_score(test['response_round_score'], y_pred))) df_results = pd.concat([df_results, pd.DataFrame([n_est, m_depth, accuracy, f1, number_of_topics])], axis = 1) df_results = df_results.transpose() df_results.to_csv('Decision_trees_results.csv')

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xuhui1994/craft_onnx_tensorrt

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/export_onnx.py

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[]

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https://github.com/xuhui1994/craft_onnx_tensorrt

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""" Copyright (c) 2019-present NAVER Corp. MIT License """ # -*- coding: utf-8 -*- import sys import os import time import argparse import torch import torch.nn as nn import torch.backends.cudnn as cudnn from torch.autograd import Variable from PIL import Image import cv2 from skimage import io import numpy as np import craft_utils import imgproc import file_utils import json import zipfile import random from craft import CRAFT from collections import OrderedDict def copyStateDict(state_dict): if list(state_dict.keys())[0].startswith("module"): start_idx = 1 else: start_idx = 0 new_state_dict = OrderedDict() for k, v in state_dict.items(): name = ".".join(k.split(".")[start_idx:]) new_state_dict[name] = v return new_state_dict def str2bool(v): return v.lower() in ("yes", "y", "true", "t", "1") parser = argparse.ArgumentParser(description='CRAFT Text Detection') parser.add_argument('--trained_model', default='weights/craft_mlt_25k.pth', type=str, help='pretrained model') parser.add_argument('--text_threshold', default=0.7, type=float, help='text confidence threshold') parser.add_argument('--low_text', default=0.4, type=float, help='text low-bound score') parser.add_argument('--link_threshold', default=0.4, type=float, help='link confidence threshold') parser.add_argument('--cuda', default=True, type=str2bool, help='Use cuda for inference') parser.add_argument('--canvas_size', default=1280, type=int, help='image size for inference') parser.add_argument('--mag_ratio', default=1.5, type=float, help='image magnification ratio') parser.add_argument('--poly', default=False ,action='store_true', help='enable polygon type') parser.add_argument('--show_time', default=False, action='store_true', help='show processing time') parser.add_argument('--test_folder', default='data/', type=str, help='folder path to input images') parser.add_argument('--refine', default=False, action='store_true', help='enable link refiner') parser.add_argument('--refiner_model', default='weights/craft_refiner_CTW1500.pth', type=str, help='pretrained refiner model') args = parser.parse_args() """ For test images in a folder """ image_list, _, _ = file_utils.get_files(args.test_folder) print(image_list) result_folder = './result/' if not os.path.isdir(result_folder): os.mkdir(result_folder) def chinese_num(line): total = 0 for u_char in line: if (u_char >= u'\u2f00' and u_char<=u'\u2fd5') or (u_char >= u'\u4e00' and u_char<=u'\u9fa5'): total += 1 return total def test_net(net, image, text_threshold, link_threshold, low_text, cuda, poly, refine_net=None): t0 = time.time() # resize img_resized, target_ratio, size_heatmap = imgproc.resize_aspect_ratio(image, args.canvas_size, interpolation=cv2.INTER_LINEAR, mag_ratio=args.mag_ratio) ratio_h = ratio_w = 1 / target_ratio # preprocessing x = imgproc.normalizeMeanVariance(img_resized) x = torch.from_numpy(x).permute(2, 0, 1) # [h, w, c] to [c, h, w] x = Variable(x.unsqueeze(0)) # [c, h, w] to [b, c, h, w] if cuda: x = x.cuda() # forward pass with torch.no_grad(): y, feature = net(x) # make score and link map score_text = y[0,:,:,0].cpu().data.numpy() score_link = y[0,:,:,1].cpu().data.numpy() # refine link if refine_net is not None: with torch.no_grad(): y_refiner = refine_net(y, feature) score_link = y_refiner[0,:,:,0].cpu().data.numpy() t0 = time.time() - t0 t1 = time.time() # Post-processing boxes, polys = craft_utils.getDetBoxes(score_text, score_link, text_threshold, link_threshold, low_text, poly) #Cords_list = [] #for i,box in enumerate(boxes): # Cords = craft_utils.getVerticalCord(box,score_link,link_threshold,i) # Cords = craft_utils.adjustResultCoordinates(Cords, ratio_w, ratio_h) # Cords_list.append(Cords) # coordinate adjustment boxes = craft_utils.adjustResultCoordinates(boxes, ratio_w, ratio_h) polys = craft_utils.adjustResultCoordinates(polys, ratio_w, ratio_h) for k in range(len(polys)): if polys[k] is None: polys[k] = boxes[k] t1 = time.time() - t1 # render results (optional) render_img = score_text.copy() render_img = np.hstack((render_img, score_link)) ret_score_text = imgproc.cvt2HeatmapImg(render_img) if args.show_time : print("\ninfer/postproc time : {:.3f}/{:.3f}".format(t0, t1)) #print(boxes, polys, ret_score_text) #return boxes, polys, ret_score_text ,Cords_list return boxes, polys, ret_score_text def find_one_line(array_dic): #list_1 = list_1_array[0] final_res = {} flag = 0 for index in sorted(txt_result.keys()): if index in txt_result: list_1 = txt_result[index] final_res[index] = [] #txt_result.pop(index) y0 = (list_1[0][1] + list_1[0][7]) / 2 w = abs(list_1[0][7] - list_1[0][1]) for index_t in sorted(txt_result.keys()): item = txt_result[index_t] y = (item[0][1] + item[0][7]) / 2 if abs(y - y0) < w/2: final_res[index].append(item) txt_result.pop(index_t) print(final_res) return final_res def sorted_by_y(array): y_list = [] for i in range(len(array)): y_list.append(int(array[i][0][0])) index_list = np.argsort(y_list) return index_list if __name__ == '__main__': # load net #res = open('res.txt','w',encoding='utf8') net = CRAFT() # initialize print('Loading weights from checkpoint (' + args.trained_model + ')') if args.cuda: net.load_state_dict(copyStateDict(torch.load(args.trained_model))) else: net.load_state_dict(copyStateDict(torch.load(args.trained_model, map_location='cpu'))) if args.cuda: net = net.cuda() input_batch = 1 input_channel = 3 input_h = 448 input_w = 448 output_batch = input_batch output_h = input_h / 2 output_w = input_w / 2 inputc = torch.randn(input_batch, input_channel, \ input_h, input_w, device='cuda') outputc = net(inputc.cuda()) dynamic_axes = {'inputc': {0: 'input_batch', 1: 'input_channel', 2: "input_h", 3: 'input_w'},'outputc': {0: 'output_batch', 1: "output_h", 2: 'output_w'}} output_names = ["output1","output2"] input_names = ["input"] torch.onnx.export( net, inputc, 'craft.onnx', verbose=True, input_names=input_names, output_names=output_names, #dynamic_axes=dynamic_axes, ) net = torch.nn.DataParallel(net) cudnn.benchmark = False net.eval()

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janlindblad/eantc20

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/work-packages/f5500/python/f5500/CiscoIOSXRPerfMeasCfg_ns.py

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[]

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# # BEWARE BEWARE BEWARE BEWARE BEWARE BEWARE BEWARE BEWARE BEWARE # This file has been auto-generated by the confdc compiler. # Source: ../load-dir/Cisco-IOS-XR-perf-meas-cfg.fxs # BEWARE BEWARE BEWARE BEWARE BEWARE BEWARE BEWARE BEWARE BEWARE # # Autogenerated namespace class for YANG module Cisco-IOS-XR-perf-meas-cfg.yang class ns(object): hash = 1478311931 id = "_f5500-nc-1.0:f5500-nc-1.0#http://cisco.com/ns/yang/Cisco-IOS-XR-perf-meas-cfg" uri = "_f5500-nc-1.0:f5500-nc-1.0#http://cisco.com/ns/yang/Cisco-IOS-XR-perf-meas-cfg" prefix = "Cisco-IOS-XR-perf-meas-cfg" Cisco_IOS_XR_perf_meas_cfg_interface = 221572658 Cisco_IOS_XR_perf_meas_cfg_interface_ = "interface" Cisco_IOS_XR_perf_meas_cfg_delay_measurement = 65222513 Cisco_IOS_XR_perf_meas_cfg_delay_measurement_ = "delay-measurement" Cisco_IOS_XR_perf_meas_cfg_enable = 448570367 Cisco_IOS_XR_perf_meas_cfg_enable_ = "enable" Cisco_IOS_XR_perf_meas_cfg_interface_name = 1322899300 Cisco_IOS_XR_perf_meas_cfg_interface_name_ = "interface-name" Cisco_IOS_XR_perf_meas_cfg_delay_profile_interface = 62000313 Cisco_IOS_XR_perf_meas_cfg_delay_profile_interface_ = "delay-profile-interface" Cisco_IOS_XR_perf_meas_cfg_accelerated = 2081546535 Cisco_IOS_XR_perf_meas_cfg_accelerated_ = "accelerated" Cisco_IOS_XR_perf_meas_cfg_count = 180894398 Cisco_IOS_XR_perf_meas_cfg_count_ = "count" Cisco_IOS_XR_perf_meas_cfg_interval = 559952988 Cisco_IOS_XR_perf_meas_cfg_interval_ = "interval" Cisco_IOS_XR_perf_meas_cfg_enable_performance_measurement = 606861816 Cisco_IOS_XR_perf_meas_cfg_enable_performance_measurement_ = "enable-performance-measurement" Cisco_IOS_XR_perf_meas_cfg_periodic = 538465825 Cisco_IOS_XR_perf_meas_cfg_periodic_ = "periodic" Cisco_IOS_XR_perf_meas_cfg_enable_interface = 1988108391 Cisco_IOS_XR_perf_meas_cfg_enable_interface_ = "enable-interface" Cisco_IOS_XR_perf_meas_cfg_threshold = 1161930343 Cisco_IOS_XR_perf_meas_cfg_threshold_ = "threshold" Cisco_IOS_XR_perf_meas_cfg_burst = 1259488663 Cisco_IOS_XR_perf_meas_cfg_burst_ = "burst" Cisco_IOS_XR_perf_meas_cfg_enable_delay_measurement = 1777392156 Cisco_IOS_XR_perf_meas_cfg_enable_delay_measurement_ = "enable-delay-measurement" Cisco_IOS_XR_perf_meas_cfg_advertise_delay = 654832865 Cisco_IOS_XR_perf_meas_cfg_advertise_delay_ = "advertise-delay" Cisco_IOS_XR_perf_meas_cfg_performance_measurement = 1340772040 Cisco_IOS_XR_perf_meas_cfg_performance_measurement_ = "performance-measurement" Cisco_IOS_XR_perf_meas_cfg_disable = 330763859 Cisco_IOS_XR_perf_meas_cfg_disable_ = "disable" Cisco_IOS_XR_perf_meas_cfg_one_way_measurement = 519889523 Cisco_IOS_XR_perf_meas_cfg_one_way_measurement_ = "one-way-measurement" Cisco_IOS_XR_perf_meas_cfg_interfaces = 321503962 Cisco_IOS_XR_perf_meas_cfg_interfaces_ = "interfaces" Cisco_IOS_XR_perf_meas_cfg_probe = 1118433712 Cisco_IOS_XR_perf_meas_cfg_probe_ = "probe" Cisco_IOS_XR_perf_meas_cfg_advertisement = 2100959827 Cisco_IOS_XR_perf_meas_cfg_advertisement_ = "advertisement" Cisco_IOS_XR_perf_meas_cfg_minimum_change = 1794400902 Cisco_IOS_XR_perf_meas_cfg_minimum_change_ = "minimum-change"

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from django.contrib import admin from to.models import LOU from to.models import Staffer admin.site.register(LOU) admin.site.register(Staffer)

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null

# Copyright 2015 Zuercher Hochschule fuer Angewandte Wissenschaften # All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. __author__ = 'ernm' import json import requests from .machine import SmartMachine, KVMMachine, Machine from .job import Job from .package import Package class DataCenter(object): APIS = ['sapi', 'vmapi', 'fwapi', 'imgapi', 'napi', 'papi', 'workflow'] default_headers = {'Content-Type': 'application/json'} STATE_RUNNING = Machine.STATE_RUNNING STATE_FAILED = Machine.STATE_FAILED STATE_DESTROYED = Machine.STATE_DESTROYED STATE_PROVISIONING = Machine.STATE_PROVISIONING STATE_STOPPED = Machine.STATE_STOPPED def request(self, method, api, path, headers=None, data=None, **kwargs): full_path = getattr(self, api) + path request_headers = {} request_headers.update(self.default_headers) if headers: request_headers.update(headers) jdata = None if data: jdata = json.dumps(data) resp = requests.request(method, full_path, headers=request_headers, data=jdata, **kwargs) if resp.content: if resp.headers['content-type'] == 'application/json': return (json.loads(resp.content), resp) else: return (resp.content, resp) else: return (None, resp) def get_ip_for_service(self, service): resp, _ = self.request('GET', 'sapi', '/services', params={'name': service}) if not resp: raise EnvironmentError('Could not receive service information for service %s' % service) service = resp.pop() resp, _ = self.request('GET', 'sapi', '/instances', params={'service_uuid': service.get('uuid')}) if not resp: raise EnvironmentError('Could not retrieve instance information for service uuid %s' % service.get('uuid')) instance = resp.pop() return instance.get('metadata').get('ADMIN_IP') def __init__(self, sapi, vmapi=None, fwapi=None, imgapi=None, napi=None, papi=None, workflow=None): self.sapi = 'http://' + sapi self.vmapi = 'http://' + (vmapi or self.get_ip_for_service('vmapi')) self.fwapi = 'http://' + (fwapi or self.get_ip_for_service('fwapi')) self.imgapi = 'http://' + (imgapi or self.get_ip_for_service('imgapi')) self.napi = 'http://' + (napi or self.get_ip_for_service('napi')) self.papi = 'http://' + (papi or self.get_ip_for_service('papi')) self.workflow = 'http://' + (workflow or self.get_ip_for_service('workflow')) def healthcheck_vmapi(self): health_data, _ = self.request('GET', 'vmapi', '/ping') return health_data.get('status') == 'OK' # FIXME: Code smell, duplication def list_smart_machines(self, owner_uuid=None, state=None): params = {'brand': 'joyent'} if owner_uuid: params.update({'owner_uuid': owner_uuid}) if state: params.update({'state': state}) raw_vms = self.__list_machines(params) return [SmartMachine(datacenter=self, data=raw_vm) for raw_vm in raw_vms] def list_machines(self, owner_uuid=None, state=None): smart_machines = self.list_smart_machines(owner_uuid, state) kvm_machines = self.list_kvm_machines(owner_uuid, state) return smart_machines + kvm_machines def list_kvm_machines(self, owner_uuid=None, state=None): params = {'brand': 'kvm'} if owner_uuid: params.update({'owner_uuid': owner_uuid}) if state: params.update({'state': state}) raw_vms = self.__list_machines(params) return [KVMMachine(datacenter=self, data=raw_vm) for raw_vm in raw_vms] def __list_machines(self, params): vms, _ = self.request('GET', 'vmapi', '/vms', params=params) return vms def create_smart_machine(self, owner, networks, package, image, alias=None, user_script=""): params = {'brand': 'joyent', 'owner_uuid': owner, 'networks': networks, 'billing_id': package, 'image_uuid': image} if alias: params.update({'alias': alias}) metadata = {} if user_script: metadata.update({'user-script': user_script}) raw_job_data = self.__create_machine(params) # TODO: error handling if not raw_job_data.get('vm_uuid'): raise Exception('Could not create SmartMachine') vm_uuid = raw_job_data.get('vm_uuid') vm = self.get_smart_machine(vm_uuid) vm.creation_job_uuid = raw_job_data.get('job_uuid') return vm def create_kvm_machine(self, owner, networks, package, image, alias=None, user_script=""): package_obj = Package(datacenter=self, uuid=package) params = {'brand': 'kvm', 'owner_uuid': owner, 'networks': networks, 'billing_id': package, 'disks': [{'image_uuid': image}, {'size': package_obj.quota}]} if alias: params.update({'alias': alias}) metadata = {} if user_script: metadata.update({'user-script': user_script}) raw_job_data = self.__create_machine(params) if not raw_job_data.get('vm_uuid'): raise Exception('Could not create KVM VM') vm_uuid = raw_job_data.get('vm_uuid') vm = self.get_kvm_machine(vm_uuid) vm.creation_job_uuid = raw_job_data.get('job_uuid') return vm def __create_machine(self, params): raw_job_data, _ = self.request('POST', 'vmapi', '/vms', data=params) return raw_job_data def get_smart_machine(self, uuid): return SmartMachine(self, self.get_machine_raw(uuid)) def get_kvm_machine(self, uuid): return KVMMachine(self, self.get_machine_raw(uuid)) def get_machine_raw(self, uuid): raw_vm_data, _ = self.request('GET', 'vmapi', '/vms/' + uuid) return raw_vm_data def get_machine(self, uuid): raw_vm_data = self.get_machine_raw(uuid) if raw_vm_data.get('brand') == 'joyent': return SmartMachine(self, raw_vm_data) if raw_vm_data.get('brand') == 'kvm': return KVMMachine(self, raw_vm_data) return None def list_jobs(self): raw_job_data, _ = self.request('GET', 'workflow', '/jobs') return [Job(datacenter=self, data=job) for job in raw_job_data] def get_job(self, uuid): return Job(self, self.get_job_raw(uuid)) def get_job_raw(self, uuid): raw_job_data, _ = self.request('GET', 'workflow', '/jobs/' + uuid) return raw_job_data def list_packages(self): raw_package_data, _ = self.request('GET', 'papi', '/packages') return [Package(datacenter=self, data=package) for package in raw_package_data] def get_package(self, uuid): return Package(self, self.get_package_raw(uuid)) def get_package_raw(self, uuid): raw_package_data, _ = self.request('GET', 'papi', '/packages/' + uuid) return raw_package_data

UTF-8

Python

false

7,678

py

7

datacenter.py

7

0.605105

0.604064

0

195

38.379487

119

Simranjeet96/MovRec

4,071,629,005,754

4ecd9e0ca724236675bb1545992e410dfaf22e0f

b65cb15f70b8c3a4108a75cfaa0a7675ece11830

/src/web/views.py

132b623baea160485ffa56390fc33cfb0a743ceb

[]

no_license

https://github.com/Simranjeet96/MovRec

1c26f9c91dd99ce9f43f9af01300709c70bb64a1

e731b3a430eaa9409ab22ad98ba222faa7e862e6

refs/heads/master

2020-05-15T06:03:53.325938

2019-04-19T14:18:00

182,112,844

0

1

null

from django.contrib.auth import authenticate, login from django.contrib.auth import logout from django.shortcuts import render,get_object_or_404,redirect from django.db.models import Q from django.http import Http404 from .models import Movie,Myrating from django.contrib import messages from .forms import UserForm from .MovieRecmEng import Myrecommend def recommend(request): if not request.user.is_authenticated: return redirect("login") if not request.user.is_active: raise Http404 current_user_id= request.user.id user_id_similar_to_current_user_id=Myrecommend(current_user_id) print('*'*20,user_id_similar_to_current_user_id) movie_list=list(Movie.objects.filter(myrating__user_id=user_id_similar_to_current_user_id,myrating__rating__gte=4)) # print(Movie.objects.filter(myrating__user_id=current_user_id,myrating__rating__gte=4).values()) return render(request,'web/recommend.html',{'movie_list':movie_list}) # List view def index(request): movies = Movie.objects.all() query = request.GET.get('q') if query: movies = Movie.objects.filter(Q(title__icontains=query)).distinct() return render(request,'web/list.html',{'movies':movies}) return render(request,'web/list.html',{'movies':movies}) # detail view def detail(request,movie_id): if not request.user.is_authenticated: return redirect("login") if not request.user.is_active: raise Http404 movies = get_object_or_404(Movie,id=movie_id) #for rating if request.method == "POST": rate = request.POST['rating'] ratingObject = Myrating() ratingObject.user = request.user ratingObject.movie = movies ratingObject.rating = rate ratingObject.save() messages.success(request,"Your Rating is submited ") return redirect("index") return render(request,'web/detail.html',{'movies':movies}) # Register user def signUp(request): form =UserForm(request.POST or None) if form.is_valid(): user = form.save(commit=False) username = form.cleaned_data['username'] password = form.cleaned_data['password'] user.set_password(password) user.save() user = authenticate(username=username,password=password) if user is not None: if user.is_active: login(request,user) return redirect("index") context ={ 'form':form } return render(request,'web/signUp.html',context) # Login User def Login(request): if request.method=="POST": username = request.POST['username'] password = request.POST['password'] user = authenticate(username=username,password=password) if user is not None: if user.is_active: login(request,user) return redirect("index") else: return render(request,'web/login.html',{'error_message':'Your account disable'}) else: return render(request,'web/login.html',{'error_message': 'Invalid Login'}) return render(request,'web/login.html') #Logout user def Logout(request): logout(request) return redirect("login")

UTF-8

Python

false

2,905

py

5

views.py

2

0.732874

0.726334

0

94

29.861702

116

sasha0/episodes

3,307,124,832,523

a2bf78fb19e8b2db572183a21e5fef111a43f0be

9b50ec9706ae68b12daa56c549dd8efe8e83dc05

/app/api_views.py

0018f8ed3afa1458314e1fa812bdde850ccf45e1

[]

no_license

https://github.com/sasha0/episodes

a60c84608224d85ef9491ef165bcb4ea6fe98a32

43667ed4f26bb6bb0bd3e5a60b2c235868b9df42

refs/heads/master

2021-01-25T12:14:19.592495

2015-03-28T21:51:29

30,326,633

0

null

# -*- coding: utf-8 -*- """REST API controllers, powered by flask-restful.""" from flask.ext.restful import Api, Resource, fields, marshal_with, marshal from flask.ext.restful import reqparse from flask.ext.security import current_user from app import api, es, QueryStringQuery, MultiMatchQuery, TermQuery from app.resource_fields import * from models import db, Episode, TVChannel, TVSeries, TVSeriesFeed parser = reqparse.RequestParser() class TVSeriesList(Resource): """Paginated list of available TV shows, including indication if current user subscribed to given TV shows.""" def get(self, page_id=1): pagination = TVSeries.query.paginate(page_id) user_id = getattr(current_user, 'id', None) data = dict(marshal(pagination.items, tvseries_resource_fields, envelope='items')) data['pagination_items'] = list(pagination.iter_pages()) data['user_id'] = user_id if user_id: feed = TVSeriesFeed.query.filter(TVSeriesFeed.user_id == user_id) for tvseries in data['items']: if tvseries['id'] in [f.tvseries_id for f in feed]: tvseries['is_subscribed'] = True else: tvseries['is_subscribed'] = False return data class TVSeriesDetail(Resource): """Page with detailed information about single TV show.""" def get(self, tvseries_id): tvseries = TVSeries.query.get(tvseries_id) user_id = getattr(current_user, 'id', None) data = dict(marshal(tvseries, tvseries_resource_fields)) data['roles'] = marshal(tvseries.roles.all(), role_resource_fields) data['episodes'] = marshal(tvseries.episodes, episode_resource_fields) data['user_id'] = user_id if user_id: feed = TVSeriesFeed.query.filter(TVSeriesFeed.user_id == user_id) if data['id'] in [f.tvseries_id for f in feed]: data['is_subscribed'] = True else: data['is_subscribed'] = False return data class TVChannelsList(Resource): """List of available TV channels.""" @marshal_with(tvchannel_resource_fields) def get(self): return TVChannel.query.all() class TVSeriesForChannelList(Resource): """List of TV series, produced by given TV channel.""" def get(self, tvchannel_id): tvchannel = TVChannel.query.get(tvchannel_id) tvseries_for_channel_resource_fields = tvchannel_resource_fields tvseries_for_channel_resource_fields.pop('popular_tvseries', None) tvseries = list(tvchannel.tvseries.all()) data = dict(marshal(tvchannel, tvseries_for_channel_resource_fields)) data['tvseries'] = marshal(tvseries, tvseries_resource_fields) return data class UpcomingEpisodesList(Resource): """List of episodes, to be aired in the nearest future.""" def get(self, page_id=1): pagination = Episode.query.filter(Episode.showed_at >= datetime.date.today())\ .order_by(db.desc(Episode.showed_at))\ .paginate(page_id) data = dict(marshal(pagination.items, upcoming_episode_resource_fields, envelope='items')) data['pagination_items'] = list(pagination.iter_pages()) return data class EpisodesList(Resource): """List of all available episodes for the given TV show.""" @marshal_with(episode_resource_fields) def get(self, tvseries_id): return list(Episode.query.filter(Episode.tvseries_id == tvseries_id)\ .order_by(Episode.season_number, Episode.episode_number, )) class TVSeriesSearch(Resource): """Full-text search of TV series, powered by Elasticsearch.""" @marshal_with(tvseries_resource_fields) def get(self): parser.add_argument('q', type=str) params = parser.parse_args() q = MultiMatchQuery(['title', 'description'], params['q']) r = es.search(query=q) return list(r) class Subscriptions(Resource): """List of TV shows, user subscribed to. Ability to subscribe to given TV show to get updates.""" def post(self): success = False parser.add_argument('tvseries_id', type=int) params = parser.parse_args() if TVSeriesFeed.query.filter(TVSeriesFeed.user_id == current_user.id, TVSeriesFeed.tvseries_id == params['tvseries_id']).count() == 0: feed = TVSeriesFeed(user_id=current_user.id, tvseries_id=params['tvseries_id']) db.session.add(feed) db.session.commit() success = True return {'success': success} def get(self, page_id=1): user_id = getattr(current_user, 'id', None) if user_id: feed = TVSeriesFeed.query.filter(TVSeriesFeed.user_id == user_id) tvseries_ids = [f.tvseries_id for f in feed] pagination = Episode.query.filter(Episode.showed_at >= datetime.date.today(), Episode.tvseries_id.in_(tvseries_ids))\ .order_by(db.desc(Episode.showed_at))\ .paginate(page_id) data = dict(marshal(pagination.items, upcoming_episode_resource_fields, envelope='items')) data['pagination_items'] = list(pagination.iter_pages()) return data return {} api.add_resource(TVSeriesList, '/series', '/series/<int:page_id>') api.add_resource(TVSeriesDetail, '/series/i/<int:tvseries_id>') api.add_resource(TVChannelsList, '/channels/') api.add_resource(TVSeriesForChannelList, '/channels/<int:tvchannel_id>/tvseries') api.add_resource(EpisodesList, '/series/i/<int:tvseries_id>/episodes') api.add_resource(UpcomingEpisodesList, '/episodes/upcoming/', '/episodes/upcoming/<int:page_id>') api.add_resource(TVSeriesSearch, '/series/search') api.add_resource(Subscriptions, '/subscriptions', '/subscriptions/<int:page_id>')

UTF-8

Python

false

6,017

py

17

api_views.py

10

0.632874

0.632043

0

144

40.791667

114

korylprince/BeagleCommand

2,250,562,876,144

7b18c964d86f40c561a87a877a5873bb46f4bf87

124423867d4278e7bef4463c6a7e05d9fa52346d

/client/__init__.py

743e8e8af953bda16190be1babcc68aac83a34c8

[]

no_license

https://github.com/korylprince/BeagleCommand

b39ae000a38cf1dd204388eaa2b987025f2199dc

0b130684cba41b12c8ac3ca141520f081ae12185

refs/heads/master

2016-09-05T16:36:47.517357

2013-07-20T13:41:26

null

0

null

import signal, os from Queue import Empty from multiprocessing import Process, Queue from BeagleCommand import QuitinTime # create message passing queues SerialIn = Queue() StorageIn = Queue() MessageBox = Queue() QueueOwners = {'serial':SerialIn,'storage':StorageIn} # wait until objects are defined to initialize workers from storage import Storage from serial import Serial def run(): """Run main server loop""" # create signal handler def signal_handler(sig, frame): print '\nCaught signal {0}... Quitin\' Time!'.format(str(sig)) flaskProcess.terminate() flaskProcess.join() QuitinTime.set() signal.signal(signal.SIGINT, signal_handler) signal.signal(signal.SIGTERM, signal_handler) # create and start worker threads StorageThread = Storage(StorageIn,MessageBox) SerialThread = Serial(SerialIn,MessageBox) StorageThread.start() SerialThread.start() # start web server def f(MessageBox): from web import app app.MessageBox = MessageBox try: app.run(debug=True, use_reloader=False) except AttributeError: pass flaskProcess = Process(target=f, args=[MessageBox]) flaskProcess.start() # pass messages until program is ended while True: # check to see if it's time to quit if QuitinTime.is_set(): break try: # use timeout so that main thread can catch signals msg = MessageBox.get(timeout=0.5) for owner in msg.to: QueueOwners[owner].put(msg.msg) except Empty: pass except IOError: pass

UTF-8

Python

false

1,677

py

15

__init__.py

10

0.645796

0.644007

0

61

26.491803

70

andy5macht/service.odroidn2.oled

9,543,417,353,603

01a71c1bd54a350518bcad65f2f138cd187bbd58

d35bf0fba626a4ab8e5bb71f689d9a5f863deb5d

/lib/settings.py

49836367f0fecb0adc9af271b7bd956bf9696758

[ "MIT" ]

permissive

https://github.com/andy5macht/service.odroidn2.oled

a0cd3d0d1a25ae07bd30207d028d88d66dca1340

60b91680da8d8918e7dea466cf5e91d9b80e9ca4

refs/heads/master

2023-06-09T14:46:49.738050

2020-08-22T16:10:07

348,997,189

0

MIT

true

2021-03-18T08:33:02

2021-03-18T08:33:01

2021-03-05T05:02:45

2021-02-25T17:35:16

200

0

null

false

import xbmcaddon from lib.logging import * addon = xbmcaddon.Addon(id="service.odroidn2.oled") def getSetting(id): return addon.getSetting(id).lower() def getBool(id): value = getSetting(id).lower() if (value == "true"): return True else: return False def getInt(id): return int(getSetting(id)) def getHex(id): return int(getSetting(id), 16) class OledSettings: def __init__(self): self.readSettings() def readSettings(self): self._settingI2CAddress = getHex("i2c.address") self._settingdisplayType = getSetting("display.type") self._settingShortFormat = getBool("display.shortformat") self._settingBrightness = getInt("display.brightness") self._settingPlaybackBrightness = getInt("display.playbackbrightness") self._settingFont = getSetting("display.font") self._settingFlipDisplay = getBool("display.flip") self._settingClockOnlyMode = getBool("display.clockonlymode") self._settingTimeMode = getSetting("display.timemode") self._settingHideIcons = getBool("display.hideicons") self._settingHideSDRIcon = getBool("display.hidesdricon") self._settingIconType = getSetting("display.icontype") def i2cAddress(self): return self._settingI2CAddress def displayType(self): return self._settingdisplayType def shortFormat(self): return self._settingShortFormat def brightness(self): return self._settingBrightness def playbackBrightness(self): return self._settingPlaybackBrightness def font(self): return self._settingFont def flipDisplay(self): return self._settingFlipDisplay def clockOnlyMode(self): return self._settingClockOnlyMode def displayTimeElapsed(self): if self._settingTimeMode == 'elapsed': return True else: return False def hideIcons(self): return self._settingHideIcons def hideSRDIcon(self): return self._settingHideSDRIcon def iconType(self): if self._settingIconType == "solid": return True else: return False

UTF-8

Python

false

2,297

py

11

settings.py

7

0.632564

0.629517

0

85

25.023529

78

davemcg/Rosalind

13,572,096,656,801

062fb8d1ca721c0baecfa42f0896bd42c510a7b8

05a980609170614e4aeb10d73acc1bb29ec0580a

/PROT.py

649724fc77a020fa9f10aef5cb5727d2e89ba278

[]

no_license

https://github.com/davemcg/Rosalind

19536ec78594b8755c63c25e449aadb53c09102b

d4f2bad0835c410e6030ca59288f2686b97f8ef0

refs/heads/master

2021-01-19T07:18:52.387106

2015-03-13T19:50:44

31,798,561

0

null

#!/usr/bin/env python3 """ Given: An RNA string s corresponding to a strand of mRNA (of length at most 10 kbp). Return: The protein string encoded by s. """ from Bio.Seq import Seq from Bio.Alphabet import generic_rna import fileinput for line in fileinput.input(): seq = Seq(line[:-1], generic_rna) print(seq.translate())

UTF-8

Python

false

333

py

12

PROT.py

11

0.714715

0.702703

0

19

16.526316

84

toszter/afecomputing

9,921,374,484,196

6229b3fa099d7f367a2a8424fd0a1fa365cf481f

5e104bdd7b9178ebba44a1c613a5a6a4f5a320e1

/connect4/connect4.py

35e9e9a5d77b2de7481f0f99a21f4f6d4f4b7e2f

[]

no_license

https://github.com/toszter/afecomputing

c716ef461b5be033bb8278d4a097bd1a3c6ca8c4

2a96546af62ee9756e8ec2f86d389bdb08d1511a

refs/heads/master

2021-01-20T13:48:37.594743

2013-03-22T18:56:49

null

0

null

# Connect 4 # AFE Python Class Spring 2013 # # Use Lists to represent positions of X and O's on a 7x6 Board # [[],[],[],[]] # # How do we check for a winning condition (4 in a row up/down/diag) # [[],['x','x'],['o','x'],['x','o','x'],['o','x','o','x'],[],[]] # 0 1 2 3 # Columns are named 1 - 7. # To take a turn, type the column number you want to add to. If the column is # full, you get a message to try again. class Board(object): def __init__(self, columns=7, rows=6): self.columns = [[] for x in range(columns)] self.rows = rows def is_full(self): '''Check if all the columns are full.''' return all(len(x) == self.rows for x in self.columns) def check_winner(self, col): '''Checks the board for a 4 in a row connection.''' winner = None # Check for 4 in a row win_count = 0 row = 0 col = self.columns[col] # Condition 1 - Vertical if len(col) >= 4: try: while win_count < 4: if col[row+1] == col[row]: win_count += 1 winner = col[row] else: win_count = 1 winner = None row += 1 except IndexError: winner = None win_count = 0 # Condition 2 - Horizontal return winner # Condition 2 - Horizontal # Condition 3 - Z Diagonal # Condition 4 - S Diagonal class Connect4(object): def __init__(self, columns=None, rows=None): self.board = Board() self.players = ["X","O"] self.current_player = 0 def take_turn(self): '''Take a turn by slotting an "x" or "o"''' current_player = self.players[self.current_player] print "Player '{0}', your turn...".format(current_player) col = raw_input("Which column deserves an '{0}'?? ".format(current_player)) self.current_col = int(col)-1 try: target_col = self.board.columns[self.current_col] except ValueError: print "Oops. Looks like that's not a column number. Try again." except IndexError: print "Whoa. That's out of my range. Try again." else: # Check if the column is full if len(target_col) == self.board.rows: # rows is int print "Dude. That column is full, brah. Try again." else: # Add player's chip to the board target_col.append(current_player) # Switch to the next player if self.current_player == 1: self.current_player = 0 else: self.current_player = 1 def print_board(self): '''prints the board so you can decide your next move.''' # 1 2 3 4 5 6 7 # +===+===+===+===+===+===+===+ # | | | | | | | |5 # | O | O | | | | | |4 # | O | O | | | | | |3 # | O | O | | | | | |2 # | X | X | | | | | |1 # | X | O | | | | | |0 # +===+===+===+===+===+===+===+ cols = len(self.board.columns) rows = self.board.rows print " " + " ".join(str(x+1).center(3) for x in range(cols)) border = "+===" * cols + "+" print border for r in reversed(range(rows)): # 5, 4, 3, 2, 1, 0 row = [] # use r as a reverse column index for c in range(cols): try: value = self.board.columns[c][r].center(3) except IndexError: value = "".center(3) row.append(value) print "|" + "|".join(row) + "|" print border print def check_winner(self): '''Checks for a winner.''' # Check for a winner winner = self.board.check_winner(self.current_col) # Check for a draw if winner is None and self.board.is_full(): winner = "draw" return winner def run(self): '''Runs the game until exit or win!''' winner = None self.print_board() while winner is None: self.take_turn() self.print_board() winner = self.check_winner() # Break out in two cases # Win or Draw if winner == "draw": print "Yarrr, the cat took the game." else: print "{0} wins!".format(winner) if __name__ == "__main__": game = Connect4() game.run()

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connect4.py

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NickSwainston/misc_scripts

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af0c01986f6228c9b0c8da53527d757be84e8de5

/spectra_paper/fit_pulsar_spectral_models_and_doc.py

957e6c5d9fa12ea2aa3ae9e96baf90c1c43d6591

[]

no_license

https://github.com/NickSwainston/misc_scripts

9f304e304a42e624f77cd9bc1163263e537af944

5d61fa2e869e06d09326360484734c4fd24275eb

refs/heads/master

2023-05-27T20:51:49.301058

2023-05-16T02:03:55

187,352,432

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import pandas as pd import os import matplotlib.pyplot as plt import psrqpy import numpy as np import shutil from PIL import Image import glob import torch.multiprocessing as mp from functools import partial from tqdm import tqdm import yaml from pulsar_spectra.spectral_fit import find_best_spectral_fit, estimate_flux_density from pulsar_spectra.catalogue import collect_catalogue_fluxes, CAT_DIR from pulsar_spectra.models import model_settings df = pd.read_csv("{}/../survey_paper/SMART_pulsars.csv".format(os.path.dirname(os.path.realpath(__file__)))) pulsar_obsid_df = pd.read_csv("{}/pulsar_best_obs.csv".format(os.path.dirname(os.path.realpath(__file__)))) #print(df['Pulsar'].tolist()) #pulsars = list(dict.fromkeys(df['Pulsar'].tolist())) with open(f"{CAT_DIR}/Bhat_2022.yaml", "r") as stream: cat_dict = yaml.safe_load(stream) pulsars = cat_dict.keys() print(len(pulsars)) cat_list = collect_catalogue_fluxes(exclude=["Bhat_2022"]) query = psrqpy.QueryATNF().pandas results_record = [] #for output csv output_df = pd.DataFrame( columns=[ "Pulsar", "ObservationID", "ATNF Period (s)", "ATNF DM", "ATNF B_surf (G)", "ATNF E_dot (ergs/s)", "Offset (degrees)", "Flux Density (mJy)", "Flux Density Uncertainty (mJy)", "Flux Density Scintilation Uncertainty (mJy)", "Estimated Flux Density (mJy)", "Estimated Flux Density Uncertainty (mJy)", "Model", "Model before MWA", "Probability Best", "Min freq before MWA (MHz)", "Max freq before MWA (MHz)", "N data flux", "pl_a" , "pl_u_a" , "pl_c" , "pl_u_c" , "bpl_vb" , "bpl_u_vb" , "bpl_a1" , "bpl_u_a1" , "bpl_a2" , "bpl_u_a2" , "bpl_c" , "bpl_u_c" , "hfco_vc" , "hfco_u_vc" , "hfco_c" , "hfco_u_c" , "lfto_vpeak" , "lfto_u_vpeak" , "lfto_a" , "lfto_u_a" , "lfto_c" , "lfto_u_c" , "lfto_beta" , "lfto_u_beta" , "dtos_vpeak" , "dtos_u_vpeak" , "dtos_vc" , "dtos_u_vc" , "dtos_a" , "dtos_u_a" , "dtos_c" , "dtos_u_c" , "dtos_beta" , "dtos_u_beta" , "pre_pl_a" , "pre_pl_u_a" , "pre_pl_c" , "pre_pl_u_c" , "pre_bpl_vb" , "pre_bpl_u_vb" , "pre_bpl_a1" , "pre_bpl_u_a1" , "pre_bpl_a2" , "pre_bpl_u_a2" , "pre_bpl_c" , "pre_bpl_u_c" , "pre_hfco_vc" , "pre_hfco_u_vc" , "pre_hfco_c" , "pre_hfco_u_c" , "pre_lfto_vpeak" , "pre_lfto_u_vpeak" , "pre_lfto_a" , "pre_lfto_u_a" , "pre_lfto_c" , "pre_lfto_u_c" , "pre_lfto_beta" , "pre_lfto_u_beta" , "pre_dtos_vpeak" , "pre_dtos_u_vpeak" , "pre_dtos_vc" , "pre_dtos_u_vc" , "pre_dtos_a" , "pre_dtos_u_a" , "pre_dtos_c" , "pre_dtos_u_c" , "pre_dtos_beta" , "pre_dtos_u_beta" , ] ) model_dict = model_settings() def fit_and_plot(pulsar): #for pulsar in pulsars: scale_figure = 0.9 fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(5.5*scale_figure,4*scale_figure)) # if pulsar != "J1136+1551": # continue # if os.path.exists(f"{os.path.dirname(os.path.realpath(__file__))}/../docs/{pulsar}.rst"): # continue # Grab all rows with pulsar then grab their fluxes pulsar_df = df.loc[df['Pulsar'] == pulsar] mwa_freqs = [] mwa_fluxs = [] mwa_flux_errors = [] pulsar_plots = [] models = None pre_models = None estimate_flux = "" estimate_flux_err = "" for index, row in pulsar_df.iterrows(): if row["Plot location"] == "" or isinstance(row["Plot location"], float): continue if not np.isnan(row['Flux Density (mJy)']) and row['Flux Density (mJy)'] != 0: mwa_freqs.append(154.24) mwa_fluxs.append(row['Flux Density (mJy)']) mwa_flux_errors.append(row['Flux Density Uncertainty (mJy)']) # Move files on_pulse_fit = glob.glob(f"{os.path.dirname(os.path.realpath(__file__))}/../docs/on_pulse_plots/{row['ObservationID']}_{pulsar}_*_bins_gaussian_components.png") if len(on_pulse_fit) == 0: on_pulse_fit = glob.glob(f"{os.path.dirname(os.path.realpath(__file__))}/../survey_paper/{row['ObservationID']}_{pulsar}_*_bins_gaussian_components.png") if len(on_pulse_fit) == 0: on_pulse_fit = [""] else: #os.rename(on_pulse_fit[0], f"{os.path.dirname(os.path.realpath(__file__))}/../docs/on_pulse_plots/{on_pulse_fit[0]}") shutil.copyfile(on_pulse_fit[0], f"{os.path.dirname(os.path.realpath(__file__))}/../docs/on_pulse_plots/{os.path.basename(on_pulse_fit[0])}") on_pulse_fit = glob.glob(f"{os.path.dirname(os.path.realpath(__file__))}/../docs/on_pulse_plots/{row['ObservationID']}_{pulsar}_*_bins_gaussian_components.png") if row["Plot location"].endswith("ps"): basename = row["Plot location"].split("/")[-1][:-2] png_basename = f"{basename}png" detection_plot = glob.glob(f"{os.path.dirname(os.path.realpath(__file__))}/../docs/detection_plots/{png_basename}") if len(detection_plot) == 0: # doesn't exist so make a png print(f"gs -sDEVICE=eps2write -dSAFER -dBATCH -dNOPAUSE -dEPSCrop -r600 -sDEVICE=pngalpha -sOutputFile={os.path.dirname(os.path.realpath(__file__))}/../docs/detection_plots/{png_basename} {row['Plot location']}") os.system(f"gs -sDEVICE=eps2write -dSAFER -dBATCH -dNOPAUSE -dEPSCrop -r600 -sDEVICE=pngalpha -sOutputFile={os.path.dirname(os.path.realpath(__file__))}/../docs/detection_plots/{png_basename} {row['Plot location']}") img = Image.open(f"{os.path.dirname(os.path.realpath(__file__))}/../docs/detection_plots/{png_basename}") # rotate by 90 degrees rot_img = img.transpose(Image.ROTATE_270) rot_img.save(f"{os.path.dirname(os.path.realpath(__file__))}/../docs/detection_plots/{png_basename}") detection_plot = glob.glob(f"{os.path.dirname(os.path.realpath(__file__))}/../docs/detection_plots/{png_basename}") else: basename = os.path.basename(row["Plot location"]) detection_plot = glob.glob(f"{os.path.dirname(os.path.realpath(__file__))}/../docs/detection_plots/{basename}") if len(detection_plot) == 0: # cp print(row["Plot location"]) shutil.copyfile(row["Plot location"], f"{os.path.dirname(os.path.realpath(__file__))}/../docs/detection_plots/{os.path.basename(row['Plot location'])}") detection_plot = glob.glob(f"{os.path.dirname(os.path.realpath(__file__))}/../docs/detection_plots/{basename}") pulsar_plots.append((detection_plot[0], on_pulse_fit[0])) freq_all, band_all, flux_all, flux_err_all, ref_all = cat_list[pulsar] freqs = freq_all + [154.24] fit_range = (np.log10(min(freqs)), np.log10(max(freqs))) pre_pl_a = None pre_pl_u_a = None pre_pl_c = None pre_pl_u_c = None pre_bpl_vb = None pre_bpl_u_vb = None pre_bpl_a1 = None pre_bpl_u_a1 = None pre_bpl_a2 = None pre_bpl_u_a2 = None pre_bpl_c = None pre_bpl_u_c = None pre_hfco_vc = None pre_hfco_u_vc = None pre_hfco_c = None pre_hfco_u_c = None pre_lfto_vpeak = None pre_lfto_u_vpeak = None pre_lfto_a = None pre_lfto_u_a = None pre_lfto_c = None pre_lfto_u_c = None pre_lfto_beta = None pre_lfto_u_beta = None pre_dtos_vpeak = None pre_dtos_u_vpeak = None pre_dtos_vc = None pre_dtos_u_vc = None pre_dtos_a = None pre_dtos_u_a = None pre_dtos_c = None pre_dtos_u_c = None pre_dtos_beta = None pre_dtos_u_beta = None pl_a = None pl_u_a = None pl_c = None pl_u_c = None bpl_vb = None bpl_u_vb = None bpl_a1 = None bpl_u_a1 = None bpl_a2 = None bpl_u_a2 = None bpl_c = None bpl_u_c = None hfco_vc = None hfco_u_vc = None hfco_c = None hfco_u_c = None lfto_vpeak = None lfto_u_vpeak = None lfto_a = None lfto_u_a = None lfto_c = None lfto_u_c = None lfto_beta = None lfto_u_beta = None dtos_vpeak = None dtos_u_vpeak = None dtos_vc = None dtos_u_vc = None dtos_a = None dtos_u_a = None dtos_c = None dtos_u_c = None dtos_beta = None dtos_u_beta = None if len(freq_all) > 0: pre_models, pre_iminuit_results, pre_fit_infos, pre_p_best, pre_p_catagory = find_best_spectral_fit( pulsar, freq_all, band_all, flux_all, flux_err_all, ref_all, plot_best=True, alternate_style=True, axis=ax, secondary_fit=True ) else: pre_models = pre_iminuit_results = pre_fit_infos = pre_p_best = pre_p_catagory = None if pre_models is not None: estimate_flux, estimate_flux_err = estimate_flux_density(154.24, pre_models, pre_iminuit_results) # record model specific bits if pre_models == "simple_power_law": pre_pl_a = pre_iminuit_results.values["a"] pre_pl_u_a = pre_iminuit_results.errors["a"] pre_pl_c = pre_iminuit_results.values["c"] pre_pl_u_c = pre_iminuit_results.errors["c"] elif pre_models == "broken_power_law": #vb, a1, a2, b pre_bpl_vb = pre_iminuit_results.values["vb"] pre_bpl_u_vb = pre_iminuit_results.errors["vb"] pre_bpl_a1 = pre_iminuit_results.values["a1"] pre_bpl_u_a1 = pre_iminuit_results.errors["a1"] pre_bpl_a2 = pre_iminuit_results.values["a2"] pre_bpl_u_a2 = pre_iminuit_results.errors["a2"] pre_bpl_c = pre_iminuit_results.values["c"] pre_bpl_u_c = pre_iminuit_results.errors["c"] elif pre_models == "high_frequency_cut_off_power_law": pre_hfco_vc = pre_iminuit_results.values["vc"] pre_hfco_u_vc = pre_iminuit_results.errors["vc"] pre_hfco_c = pre_iminuit_results.values["c"] pre_hfco_u_c = pre_iminuit_results.errors["c"] elif pre_models == "low_frequency_turn_over_power_law": # vc, a, b, beta pre_lfto_vpeak = pre_iminuit_results.values["vpeak"] pre_lfto_u_vpeak = pre_iminuit_results.errors["vpeak"] pre_lfto_a = pre_iminuit_results.values["a"] pre_lfto_u_a = pre_iminuit_results.errors["a"] pre_lfto_c = pre_iminuit_results.values["c"] pre_lfto_u_c = pre_iminuit_results.errors["c"] pre_lfto_beta = pre_iminuit_results.values["beta"] pre_lfto_u_beta = pre_iminuit_results.errors["beta"] elif pre_models == "double_turn_over_spectrum": # vc, a, b, beta pre_dtos_vc = pre_iminuit_results.values["vc"] pre_dtos_u_vc = pre_iminuit_results.errors["vc"] pre_dtos_vc = pre_iminuit_results.values["vpeak"] pre_dtos_u_vc = pre_iminuit_results.errors["vpeak"] pre_dtos_a = pre_iminuit_results.values["a"] pre_dtos_u_a = pre_iminuit_results.errors["a"] pre_dtos_c = pre_iminuit_results.values["c"] pre_dtos_u_c = pre_iminuit_results.errors["c"] pre_dtos_beta = pre_iminuit_results.values["beta"] pre_dtos_u_beta = pre_iminuit_results.errors["beta"] # calc offset # find obsid using for this pulsar #pulsar_obsid_df = pulsar_obsid_df[pulsar_obsid_df['Jname'].str.contains(pulsar)] this_df = pulsar_obsid_df.loc[pulsar == pulsar_obsid_df['Jname']].reset_index() obsid = this_df['ObsID'][0] query_id = list(query['PSRJ']).index(pulsar) # obsid, ra, dec, dura, [xdelays, ydelays], centrefreq, channels = get_common_obs_metadata(obsid) # print("coords") # print(ra,dec) # obs_beam = SkyCoord(ra, dec, unit=(u.deg,u.deg)) # query_id = list(query['PSRJ']).index(pulsar) # print(query["RAJ"][query_id], query["DECJ"][query_id]) # pulsar_coord = SkyCoord(query["RAJ"][query_id], query["DECJ"][query_id], unit=(u.hourangle,u.deg)) # offset = pulsar_coord.separation(obs_beam).deg offset = None print(f"\n{pulsar}") if len(mwa_fluxs) == 0: print(f"No fluxes") else: # Adjust uncertanty to take into account scintillation and number of detections # Average data S_mean = np.mean(mwa_fluxs) u_S_mean = np.sqrt(np.sum(np.array(mwa_flux_errors)**2)) # using 728 MHz values from table 4 a = -0.47 b = 0.21 d0 = 200 d = float(row['ATNF DM']) # Equation 18 modultaion index m_r_v = b* (d/d0)**a # Equation 4 u_scint = m_r_v * S_mean # Equation 2 robust standard deviation computed using the interquartile range std_r_v = 0.9183 * (np.quantile(mwa_fluxs, 0.75) - np.quantile(mwa_fluxs, 0.25)) N = len(mwa_fluxs) # Equation 3 u_S = np.sqrt( u_S_mean**2 + std_r_v**2/N + (6/(5*N) - 1/5)*u_scint**2) #print(u_S, mwa_flux_errors) # freq_all = np.array(mwa_freqs + cat_list[pulsar][0]) # flux_all = np.array(mwa_fluxs + cat_list[pulsar][1]) # flux_err_all = np.array(mwa_flux_errors + cat_list[pulsar][2]) # ref_all = np.array(["SMART"]*len(mwa_freqs) + cat_list[pulsar][3]) freq_all = np.array([154.24] + cat_list[pulsar][0]) band_all = np.array([30.72] + cat_list[pulsar][1]) flux_all = np.array([S_mean] + cat_list[pulsar][2]) flux_err_all = np.array([u_S] + cat_list[pulsar][3]) ref_all = np.array(["SMART"] + cat_list[pulsar][4]) #for freq, flux, flux_err in zip(freq_all, flux_all, flux_err_all): #print(freq, flux, flux_err) models, iminuit_results, fit_infos, p_best, p_catagory = find_best_spectral_fit( pulsar, freq_all, band_all, flux_all, flux_err_all, ref_all, plot_best=True, alternate_style=True, axis=ax ) plt.tight_layout(pad=2.5) #plt.savefig(f"{pulsar}_fit.pdf", bbox_inches='tight', dpi=300) plt.savefig(f"{pulsar}_fit.png", bbox_inches='tight', dpi=300) models, iminuit_results, fit_infos, p_best, p_catagory = find_best_spectral_fit(pulsar, freq_all, band_all, flux_all, flux_err_all, ref_all, plot_compare=True) if models is not None: if len(models) > 0: shutil.move(f"{pulsar}_fit.png", f"{os.path.dirname(os.path.realpath(__file__))}/../docs/best_fits/{pulsar}_fit.png") print(f"{pulsar}_comparison_fit.png", f"{os.path.dirname(os.path.realpath(__file__))}/../docs/comparison_fits/{pulsar}_comparison_fit.png") shutil.move(f"{pulsar}_comparison_fit.png", f"{os.path.dirname(os.path.realpath(__file__))}/../docs/comparison_fits/{pulsar}_comparison_fit.png") # Record data results_record.append((pulsar, row['ATNF DM'], models, iminuit_results, fit_infos, p_best, p_catagory, len(mwa_fluxs), S_mean, u_S, u_S_mean, u_scint, m_r_v)) # record model specific bits if models == "simple_power_law": pl_a = iminuit_results.values["a"] pl_u_a = iminuit_results.errors["a"] pl_c = iminuit_results.values["c"] pl_u_c = iminuit_results.errors["c"] elif models == "broken_power_law": #vb, a1, a2, b bpl_vb = iminuit_results.values["vb"] bpl_u_vb = iminuit_results.errors["vb"] bpl_a1 = iminuit_results.values["a1"] bpl_u_a1 = iminuit_results.errors["a1"] bpl_a2 = iminuit_results.values["a2"] bpl_u_a2 = iminuit_results.errors["a2"] bpl_c = iminuit_results.values["c"] bpl_u_c = iminuit_results.errors["c"] elif models == "high_frequency_cut_off_power_law": hfco_vc = iminuit_results.values["vc"] hfco_u_vc = iminuit_results.errors["vc"] hfco_c = iminuit_results.values["c"] hfco_u_c = iminuit_results.errors["c"] elif models == "low_frequency_turn_over_power_law": # vc, a, b, beta lfto_vpeak = iminuit_results.values["vpeak"] lfto_u_vpeak = iminuit_results.errors["vpeak"] lfto_a = iminuit_results.values["a"] lfto_u_a = iminuit_results.errors["a"] lfto_c = iminuit_results.values["c"] lfto_u_c = iminuit_results.errors["c"] lfto_beta = iminuit_results.values["beta"] lfto_u_beta = iminuit_results.errors["beta"] elif models == "double_turn_over_spectrum": # vc, a, b, beta dtos_vc = iminuit_results.values["vc"] dtos_u_vc = iminuit_results.errors["vc"] dtos_vc = iminuit_results.values["vpeak"] dtos_u_vc = iminuit_results.errors["vpeak"] dtos_a = iminuit_results.values["a"] dtos_u_a = iminuit_results.errors["a"] dtos_c = iminuit_results.values["c"] dtos_u_c = iminuit_results.errors["c"] dtos_beta = iminuit_results.values["beta"] dtos_u_beta = iminuit_results.errors["beta"] if len(cat_list[pulsar][0]) == 0: min_freq = None max_freq = None else: min_freq = min(cat_list[pulsar][0]) max_freq = max(cat_list[pulsar][0]) with open(f'{os.path.dirname(os.path.realpath(__file__))}/../docs/{pulsar}.rst', 'w') as file: file.write(f".. _{pulsar}:\n{pulsar}\n") file.write("="*len(pulsar)) # Fit with out data if models is not None: print(iminuit_results.values) file.write(f''' Best Fit -------- .. image:: best_fits/{pulsar}_fit.png :width: 800 .. csv-table:: {pulsar} fit results ''') header_str = ' :header: "model",' data_str = f' "{models}",' for p, v, e in zip(iminuit_results.parameters, iminuit_results.values, iminuit_results.errors): if p.startswith('v'): header_str += f'"{p} (MHz)",' data_str += f'"{int(v/1e6):d}±{int(e/1e6):d}",' else: header_str += f'"{p}",' data_str += f'"{v:.2f}±{e:.2f}",' file.write(f'''{header_str[:-1]} {data_str[:-1]}''') else: file.write(f''' Best Fit -------- Only {len(mwa_freqs)} MWA data and {len(cat_list[pulsar][0])} cat data available ''') # Fit without our data if pre_models is not None: file.write(f''' Fit Before MWA -------------- .. csv-table:: {pulsar} before fit results ''') header_str = ' :header: "model",' data_str = f' "{pre_models}",' for p, v, e in zip(pre_iminuit_results.parameters, pre_iminuit_results.values, pre_iminuit_results.errors): if p.startswith('v'): header_str += f'"{p} (MHz)",' data_str += f'"{int(v/1e6):d}±{int(e/1e6):d}",' else: header_str += f'"{p}",' data_str += f'"{v:.2f}±{e:.2f}",' file.write(f'''{header_str[:-1]} {data_str[:-1]}''') file.write(f''' Flux Density Results -------------------- .. csv-table:: {pulsar} flux density total results :header: "N obs", "Flux Density (mJy)", "u_S_mean", "u_scint", "m_r_v" "{len(mwa_fluxs)}", "{S_mean:.1f}±{u_S:.1f}", "{u_S_mean:.1f}", "{u_scint:.1f}", "{m_r_v:.3f}" .. csv-table:: {pulsar} flux density individual results :header: "ObsID", "Flux Density (mJy)" ''') for index, row in pulsar_df.iterrows(): file.write(f''' "{row['ObservationID']}", "{row['Flux Density (mJy)']:.1f}±{row['Flux Density Uncertainty (mJy)']:.1f}"\n''') # Comparison fit if models is not None: file.write(f''' Comparison Fit -------------- .. image:: comparison_fits/{pulsar}_comparison_fit.png :width: 800 ''') # Detection plots file.write(f''' Detection Plots --------------- ''') for detection_plot, on_pulse_fit in pulsar_plots: file.write(f''' .. image:: detection_plots/{os.path.basename(detection_plot)} :width: 800 .. image:: on_pulse_plots/{os.path.basename(on_pulse_fit)} :width: 800''') # Record data for csv #output_df = output_df.append({ return { "Pulsar":pulsar, "ObservationID":obsid, "ATNF Period (s)": row['ATNF Period (s)'], "ATNF DM": row['ATNF DM'], "ATNF B_surf (G)":query["BSURF"][query_id], "ATNF E_dot (ergs/s)":query["EDOT"][query_id], "Offset (degrees)":offset, "Flux Density (mJy)":S_mean, "Flux Density Uncertainty (mJy)":u_S_mean, "Flux Density Scintilation Uncertainty (mJy)":u_S, "Estimated Flux Density (mJy)":estimate_flux, "Estimated Flux Density Uncertainty (mJy)":estimate_flux_err, "Model":models, "Model before MWA":pre_models, "Probability Best":p_best, "Min freq before MWA (MHz)":min_freq, "Max freq before MWA (MHz)":max_freq, "N data flux": len(flux_all), "pl_a" : pl_a , "pl_u_a" : pl_u_a , "pl_c" : pl_c , "pl_u_c" : pl_u_c , "bpl_vb" : bpl_vb , "bpl_u_vb" : bpl_u_vb , "bpl_a1" : bpl_a1 , "bpl_u_a1" : bpl_u_a1 , "bpl_a2" : bpl_a2 , "bpl_u_a2" : bpl_u_a2 , "bpl_c" : bpl_c , "bpl_u_c" : bpl_u_c , "hfco_vc" : hfco_vc , "hfco_u_vc" : hfco_u_vc , "hfco_c" : hfco_c , "hfco_u_c" : hfco_u_c , "lfto_vpeak" : lfto_vpeak , "lfto_u_vpeak" : lfto_u_vpeak, "lfto_a" : lfto_a , "lfto_u_a" : lfto_u_a , "lfto_c" : lfto_c , "lfto_u_c" : lfto_u_c , "lfto_beta" : lfto_beta, "lfto_u_beta" : lfto_u_beta, "dtos_vpeak" : dtos_vpeak , "dtos_u_vpeak": dtos_u_vpeak, "dtos_vc" : dtos_vc , "dtos_u_vc" : dtos_u_vc, "dtos_a" : dtos_a , "dtos_u_a" : dtos_u_a , "dtos_c" : dtos_c , "dtos_u_c" : dtos_u_c , "dtos_beta" : dtos_beta, "dtos_u_beta" : dtos_u_beta, "pre_pl_a" : pre_pl_a , "pre_pl_u_a" : pre_pl_u_a , "pre_pl_c" : pre_pl_c , "pre_pl_u_c" : pre_pl_u_c , "pre_bpl_vb" : pre_bpl_vb , "pre_bpl_u_vb" : pre_bpl_u_vb , "pre_bpl_a1" : pre_bpl_a1 , "pre_bpl_u_a1" : pre_bpl_u_a1 , "pre_bpl_a2" : pre_bpl_a2 , "pre_bpl_u_a2" : pre_bpl_u_a2 , "pre_bpl_c" : pre_bpl_c , "pre_bpl_u_c" : pre_bpl_u_c , "pre_hfco_vc" : pre_hfco_vc , "pre_hfco_u_vc" : pre_hfco_u_vc , "pre_hfco_c" : pre_hfco_c , "pre_hfco_u_c" : pre_hfco_u_c , "pre_lfto_vpeak" : pre_lfto_vpeak , "pre_lfto_u_vpeak" : pre_lfto_u_vpeak , "pre_lfto_a" : pre_lfto_a , "pre_lfto_u_a" : pre_lfto_u_a , "pre_lfto_c" : pre_lfto_c , "pre_lfto_u_c" : pre_lfto_u_c , "pre_lfto_beta" : pre_lfto_beta, "pre_lfto_u_beta" : pre_lfto_u_beta, "pre_dtos_vpeak" : pre_dtos_vpeak , "pre_dtos_u_vpeak": pre_dtos_u_vpeak, "pre_dtos_vc" : pre_dtos_vc , "pre_dtos_u_vc" : pre_dtos_u_vc, "pre_dtos_a" : pre_dtos_a , "pre_dtos_u_a" : pre_dtos_u_a , "pre_dtos_c" : pre_dtos_c , "pre_dtos_u_c" : pre_dtos_u_c , "pre_dtos_beta" : pre_dtos_beta, "pre_dtos_u_beta" : pre_dtos_u_beta, } #, ignore_index=True) pbar = tqdm(pulsars) # freeze params/function as object fc_ = partial(fit_and_plot) # set number of processes p = mp.Pool(8) # runs mp with params on pbar #results = p.imap(fc_, pbar) results = list(p.imap(fc_, pbar)) #print(results) # close out and join processes p.close() p.join() output_df = pd.DataFrame(results) output_df.to_csv('SMART_pulsars_flux_update.csv', index=False) # Record summary results on homepage with open(f'{os.path.dirname(os.path.realpath(__file__))}/../docs/index.rst', 'w') as file: file.write(f'''.. pulsar_spectra documentation master file, created by sphinx-quickstart on Sat Feb 12 11:03:47 2022. You can adapt this file completely to your liking, but it should at least contain the root `toctree` directive. Welcome to pulsar_spectra's documentation! ========================================== Flux Density Results -------------------- .. csv-table:: :header: "Pulsar", "DM", "N obs", "Flux Density (mJy)", "u_S_mean", "u_scint", "m_r_v" ''') # setp up other tables while I'm looping simple_power_law = [] broken_power_law = [] log_parabolic_spectrum = [] high_frequency_cut_off_power_law = [] low_frequency_turn_over_power_law = [] for pulsar, dm, models, iminuit_results, fit_infos, p_best, p_catagory, n_obs, S_mean, u_S, u_S_mean, u_scint, m_r_v in results_record: file.write(f' ":ref:`{pulsar}<{pulsar}>`", "{dm}", "{n_obs}", "{S_mean:.1f}±{u_S:.1f}", "{u_S_mean:.1f}", "{u_scint:.1f}", "{m_r_v:.3f}"\n') #sort if models == "simple_power_law": simple_power_law.append((pulsar, dm, models, iminuit_results, fit_infos, p_best, p_catagory)) if models == "broken_power_law": broken_power_law.append((pulsar, dm, models, iminuit_results, fit_infos, p_best, p_catagory)) if models == "log_parabolic_spectrum": log_parabolic_spectrum.append((pulsar, dm, models, iminuit_results, fit_infos, p_best, p_catagory)) if models == "high_frequency_cut_off_power_law": high_frequency_cut_off_power_law.append((pulsar, dm, models, iminuit_results, fit_infos, p_best, p_catagory)) if models == "low_frequency_turn_over_power_law": low_frequency_turn_over_power_law.append((pulsar, dm, models, iminuit_results, fit_infos, p_best, p_catagory)) file.write(f''' Single Power Law Results ------------------------ .. csv-table:: :header: "Pulsar", "DM", "a", "b" ''') for pulsar, dm, models, iminuit_results, fit_infos, p_best, p_catagory in simple_power_law: data_str = f' ":ref:`{pulsar}<{pulsar}>`", "{dm}", ' for p, v, e in zip(iminuit_results.parameters, iminuit_results.values, iminuit_results.errors): if p.startswith('v'): data_str += f'"{int(v/1e6):d}±{int(e/1e6):d}", ' else: data_str += f'"{v:.2f}±{e:.2f}", ' file.write(f'{data_str[:-2]}\n') file.write(f''' Broken Power Law Results ------------------------ .. csv-table:: :header: "Pulsar", "DM", "vb (MHz)", "a1", "a2", "b" ''') for pulsar, dm, models, iminuit_results, fit_infos, p_best, p_catagory in broken_power_law: data_str = f' ":ref:`{pulsar}<{pulsar}>`", "{dm}", ' for p, v, e in zip(iminuit_results.parameters, iminuit_results.values, iminuit_results.errors): if p.startswith('v'): data_str += f'"{int(v/1e6):d}±{int(e/1e6):d}", ' else: data_str += f'"{v:.2f}±{e:.2f}", ' file.write(f'{data_str[:-2]}\n') file.write(f''' Log-parabolic spectrum Results ------------------------------ .. csv-table:: :header: "Pulsar", "DM", "a", "b", "c" ''') for pulsar, dm, models, iminuit_results, fit_infos, p_best, p_catagory in log_parabolic_spectrum: data_str = f' ":ref:`{pulsar}<{pulsar}>`", "{dm}", ' for p, v, e in zip(iminuit_results.parameters, iminuit_results.values, iminuit_results.errors): if p.startswith('v'): data_str += f'"{int(v/1e6):d}±{int(e/1e6):d}", ' else: data_str += f'"{v:.2f}±{e:.2f}", ' file.write(f'{data_str[:-2]}\n') file.write(f''' Power law with high-frequency cut-off Results --------------------------------------------- .. csv-table:: :header: "Pulsar", "DM", "vc (MHz)", "a", "b" ''') for pulsar, dm, models, iminuit_results, fit_infos, p_best, p_catagory in high_frequency_cut_off_power_law: data_str = f' ":ref:`{pulsar}<{pulsar}>`", "{dm}", ' for p, v, e in zip(iminuit_results.parameters, iminuit_results.values, iminuit_results.errors): if p.startswith('v'): data_str += f'"{int(v/1e6):d}±{int(e/1e6):d}", ' else: data_str += f'"{v:.2f}±{e:.2f}", ' file.write(f'{data_str[:-2]}\n') file.write(f''' Power law with low-frequency turn-over Results ---------------------------------------------- .. csv-table:: :header: "Pulsar", "DM", "vc (MHz)", "a", "b", "beta" ''') for pulsar, dm, models, iminuit_results, fit_infos, p_best, p_catagory in low_frequency_turn_over_power_law: data_str = f' ":ref:`{pulsar}<{pulsar}>`", "{dm}", ' for p, v, e in zip(iminuit_results.parameters, iminuit_results.values, iminuit_results.errors): if p.startswith('v'): data_str += f'"{int(v/1e6):d}±{int(e/1e6):d}", ' else: data_str += f'"{v:.2f}±{e:.2f}", ' file.write(f'{data_str[:-2]}\n') file.write(f''' .. toctree:: :maxdepth: 1 :caption: Pulsar Fit Results: :glob: J* ''')

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