Datasets:

anton-l

/

python_sample_10k

like 0

ShannonTully/data-structures-and-algorithms

59dc1afd081d0911947f411ad958c2e61fd867cb

1efd977af1638b7afa63c43a36e964ffe5db295a

/challenges/multi-bracket-validation/test_multi_bracket_validation.py

778e33b27d0b67fd8da4b2bdd2d3655aa5cbdfe8

permissive

https://github.com/ShannonTully/data-structures-and-algorithms

847c8fa99b395efa254c364345302ccafaa6e802

f43f24f9f60beb37a2717f387c1050c9fd1ece60

refs/heads/master

MIT

Python

import multi_bracket_validation import pytest def test_basic(): assert multi_bracket_validation.multi_bracket_validation('()') is True def test_fail(): assert multi_bracket_validation.multi_bracket_validation('(}') is False def test_complex(): assert multi_bracket_validation.multi_bracket_validation('[][Code][Fellows](())') is True

UTF-8

Python

py

test_multi_bracket_validation.py

carden-code/python

49500361d80edfa1c0a18a39cf3c780c3ac8f1b5

b6fa182321756b891b84958e2b2c01e63b3f88b2

/stepik/minute_of_genetics.py

47ff69a096d269f31de471f1a7f40f7cf50f22e6

no_license

https://github.com/carden-code/python

872da0dff5466070153cf945c428f1bc8309ea2b

64e4df0d9893255ad362a904bb5d9677a383591c

refs/heads/master

# На вход программе подается строка генетического кода, # состоящая из букв А (аденин), Г (гуанин), Ц (цитозин), Т (тимин). # Напишите программу, которая подсчитывает сколько аденина, гуанина, цитозина и тимина # входит в данную строку генетического кода. # # Формат входных данных # На вход программе подается строка генетического кода, состоящая из символов А, Г, Ц, Т, а, г, ц, т. # # Формат выходных данных # Программа должна вывести сколько гуанина, тимина, цитозина, аденина входит в данную строку генетического кода. # # Примечание. Строка не содержит символов, кроме как А, Г, Ц, Т, а, г, ц, т. string = input().lower() a = string.count('а') b = string.count('г') c = string.count('ц') d = string.count('т') print(f'Аденин: {a}') print(f'Гуанин: {b}') print(f'Цитозин: {c}') print(f'Тимин: {d}')

UTF-8

Python

py

minute_of_genetics.py

dplepage/dfiance

f6e4e8f6f11945286c0848e752dafc19ed1cea44

8f0387b86bde8eb44e593ec16a96338843c83ca0

/dfiance/datetypes.py

cc6a2a0076a3d8368d878e4afa95a9931a4d95cc

no_license

https://github.com/dplepage/dfiance

84a083b325288fb8730f4b20700d738db3792364

3c4c916eadb9fdef1c762491ca40d726f3575258

refs/heads/master

import datetime try: from dateutil.parser import parse as parse_datetime _have_dateutil = True except ImportError: _have_dateutil = False from base import Invalid, Dictifier class DateTime(Dictifier): """ Dictifier for datetimes. The 'format' argument determines what format will be used for serializing, and if the 'require_format' argument is True, only strings in that format will be deserialized. 'require_format' must be true if the dateutil module is not installed. If you have dateutil installed, however, then 'require_format' defaults to False, and DateTime will use dateutil.parser.parse to process dates, so any string dateutil can parse can be undictified: >>> dtfier = DateTime() >>> dtfier.undictify("2003-12-25") datetime.datetime(2003, 12, 25, 0, 0) >>> dtfier.undictify("2003-12-25T14:25:03.1") datetime.datetime(2003, 12, 25, 14, 25, 3, 100000) >>> dtfier.undictify("Dec 25, 2003 2:25:03.1 pm") datetime.datetime(2003, 12, 25, 14, 25, 3, 100000) Invalid strings get specific error messages: >>> dtfier.undictify("200003-12-25") Traceback (most recent call last): ... Invalid: bad_year >>> dtfier.undictify("2003-13-25") Traceback (most recent call last): ... Invalid: bad_month >>> dtfier.undictify("2003-12-32") Traceback (most recent call last): ... Invalid: bad_day >>> dtfier.undictify("2003-12-25T26:25:03.1") Traceback (most recent call last): ... Invalid: bad_hour >>> dtfier.undictify("2003-12-25T14:71:03.1") Traceback (most recent call last): ... Invalid: bad_minute >>> dtfier.undictify("2003-12-25T14:25:93.1") Traceback (most recent call last): ... Invalid: bad_second Non-numbers get generic "bad_format" error messages: >>> dtfier.undictify("2003-hello-12") Traceback (most recent call last): ... Invalid: bad_format >>> dtfier.undictify("Not even remotely a datetime.") Traceback (most recent call last): ... Invalid: bad_format >>> dtfier.undictify(["this", "isn't", "even", "a", "string"]) Traceback (most recent call last): ... Invalid: type_error Dictifying will serialize to self.format, which defaults to "%Y-%m-%dT%H:%M:%S.%f" but can be set to anything. >>> d = datetime.datetime(2003, 12, 25, 14, 21, 3, 100500) >>> DateTime().dictify(d) u'2003-12-25T14:21:03.100500' >>> DateTime(format='%I:%M:%S.%f%p on %h %e, %Y').dictify(d) u'02:21:03.100500PM on Dec 25, 2003' Be warned, though, that you can fail at formatting by entering something which neither datetime.strptime nor dateutil can parse: >>> dumb_format = 'At %I:%M:%S.%f%p on day number %e of the year %Y, in %h' >>> dtfier = DateTime(format=dumb_format) >>> dtfier.dictify(d) u'At 02:21:03.100500PM on day number 25 of the year 2003, in Dec' >>> dtfier.undictify(dtfier.dictify(d)) Traceback (most recent call last): ... Invalid: bad_format Or by entering something that throws away data: >>> dtfier = DateTime(format="%h %e %Y") >>> dtfier.dictify(d) u'Dec 25 2003' >>> dtfier.undictify(dtfier.dictify(d)) datetime.datetime(2003, 12, 25, 0, 0) >>> dtfier.undictify(dtfier.dictify(d)) == d False Validate only approves of datetimes: >>> DateTime().validate(datetime.datetime.now()) >>> DateTime().validate("") Traceback (most recent call last): ... Invalid: type_error Like all good dictifiers, undictify is idempotent: >>> dtfier = DateTime() >>> dt = dtfier.undictify("2003-1-1") >>> dtfier.undictify(dt) == dt True """ _dt_type = datetime.datetime def __init__(self, format="%Y-%m-%dT%H:%M:%S.%f", require_format=not _have_dateutil): self.format = format if not require_format and not _have_dateutil: msg = ("Can't parse dates or times with require_format=False" " unless dateutil is installed.") raise ValueError(msg) def parse_datetime(self, value): '''Parse a formatted datetime. Tries datetime.datetime.strptime; if that fails it falls back to dateutil if present. ''' if not isinstance(value, basestring): raise Invalid("type_error") try: return datetime.datetime.strptime(value, self.format) except ValueError, e: if not _have_dateutil: raise Invalid("bad_format") # If we get here, then we have dateutil - try to use it! try: return parse_datetime(value) except ValueError, e: if e.message.lower() == 'year is out of range': raise Invalid("bad_year") elif e.message.lower() == 'month must be in 1..12': raise Invalid("bad_month") elif e.message.lower() == 'day is out of range for month': raise Invalid("bad_day") elif e.message.lower() == 'hour must be in 0..23': raise Invalid('bad_hour') elif e.message.lower() == 'minute must be in 0..59': raise Invalid('bad_minute') elif e.message.lower() == 'second must be in 0..59': raise Invalid('bad_second') else: raise Invalid("bad_format") def undictify(self, value, **kwargs): if isinstance(value, self._dt_type): return value return self.parse_datetime(value) def validate(self, value, **kwargs): if not isinstance(value, self._dt_type): raise Invalid("type_error") def dictify(self, value, **kwargs): return unicode(value.strftime(self.format)) class Date(DateTime): """ Dictifier for dates. All the notes about DateTime apply: Dateutil parsing: >>> date = Date() >>> date.undictify("2003-12-25") datetime.date(2003, 12, 25) Error msgs for each field that can fail, contingent on dateutil recognizing that something is the field in question: >>> date.undictify("2003-13-25") Traceback (most recent call last): ... Invalid: bad_month >>> date.undictify("2003-12-32") Traceback (most recent call last): ... Invalid: bad_day >>> date.undictify("200000-12-25") Traceback (most recent call last): ... Invalid: bad_year >>> date.undictify("2003-hi-12") Traceback (most recent call last): ... Invalid: bad_format >>> date.undictify("Not a date") Traceback (most recent call last): ... Invalid: bad_format Formats work, but don't choose something dateutil can't read back: >>> date = datetime.date(2003, 12, 25) >>> datefier = Date(format="%h %e '%g") >>> datefier.dictify(date) u"Dec 25 '03" >>> datefier.undictify(datefier.dictify(date)) datetime.date(2003, 12, 25) >>> datefier = Date(format="Day %e of month %h in the year %g") >>> datefier.dictify(date) u'Day 25 of month Dec in the year 03' >>> datefier.undictify(datefier.dictify(date)) Traceback (most recent call last): ... Invalid: bad_format Validate passes only dates: >>> Date().validate(datetime.date.today()) >>> Date().validate(datetime.time()) Traceback (most recent call last): ... Invalid: type_error As a side effect of dateutil, the Date dictifier WILL undictify strings dateutil parses as full datetimes, discarding the time: >>> Date().undictify('2003-12-25 14:21:03.100500') datetime.date(2003, 12, 25) """ _dt_type = datetime.date def __init__(self, format="%Y-%m-%d"): super(Date, self).__init__(format) def undictify(self, value, **kwargs): if isinstance(value, self._dt_type): return value return self.parse_datetime(value).date() class Time(DateTime): """ >>> Time().undictify("14:25:03.1") datetime.time(14, 25, 3, 100000) >>> Time().undictify("26:25:03.1") Traceback (most recent call last): ... Invalid: bad_hour >>> Time().undictify("14:71:03.1") Traceback (most recent call last): ... Invalid: bad_minute >>> Time().undictify("14:25:93.1") Traceback (most recent call last): ... Invalid: bad_second >>> Time().undictify("Not a time") Traceback (most recent call last): ... Invalid: bad_format >>> Time().dictify(datetime.time(14, 25, 3, 100000)) u'14:25:03.100000' >>> Time(format="%I:%M%p").dictify(datetime.time(14, 25, 3, 1)) u'02:25PM' >>> Time().undictify(datetime.time(14, 25, 3, 1)) datetime.time(14, 25, 3, 1) """ _dt_type = datetime.time def __init__(self, format="%H:%M:%S.%f"): super(Time, self).__init__(format) def undictify(self, value, **kwargs): if isinstance(value, self._dt_type): return value return self.parse_datetime(value).time() if __name__ == '__main__': import doctest doctest.testmod()

UTF-8

Python

py

datetypes.py

guillaume-havard/testdjango

6e61c6075490a98a9ce3ba7c46e84ffd2ea70ff9

ecdbbfbbff48a1199e124daf5c97a26826301c72

/sitetest/blog/forms.py

008239a485aa2cff4b6584316e89603539b9d74c

permissive

https://github.com/guillaume-havard/testdjango

41aa84570259f511cd2773c9c691e88df1b0b691

66176f81660715dcb3ef4da083e4ea584762c27d

refs/heads/master

from django import forms from blog.models import Article class ContactForm(forms.Form): sujet = forms.CharField(max_length=100) message = forms.CharField(widget=forms.Textarea) envoyeur = forms.EmailField(label="Votre adresse mail") renvoi = forms.BooleanField(help_text="Cochez si vous souhaitez obtenir une copie du mail envoyé.", required=False) # Pour vérifier un champs # doit dommencer par "clean_" puis continuer avec le nom de la variable à vérifier. # est appelé après le Form.cleaned_data """ def clean_message(self): message = self.cleaned_data['message'] if "pizza" in message: raise forms.ValidationError("On ne veut pas entendre parler de pizza !") return message # Ne pas oublier de renvoyer le contenu du champ traité """ # Pour vérifier plusieurs champs entre eux il faut surcharger la méthode clean. def clean(self): cleaned_data = super(ContactForm, self).clean() sujet = cleaned_data.get('sujet') message = cleaned_data.get('message') if sujet and message: # Est-ce que sujet et message sont valides ? if "pizza" in sujet and "pizza" in message: # Erreur général en haut du formulaire #raise forms.ValidationError("Vous parlez de pizzas dans le sujet ET le message ? Non mais ho !") # Pour l'avoir sur le bon champs : msg = "Vous parlez déjà de pizzas dans le sujet, n'en parlez plus dans le message !" #self.add_error("message", msg) # ou self.add_error("message", forms.ValidationError("Vous parlez de pizzas dans le sujet ET le message ? Non mais ho !")) return cleaned_data # N'oublions pas de renvoyer les données si tout est OK #Pour faire un formulaire depuis un modèle. (/!\ héritage différent) class ArticleForm(forms.ModelForm): class Meta: model = Article #exclude = ('auteur','categorie','slug') # Exclura les champs nommés « auteur », « categorie » et « slug » fields = ('titre', 'auteur', 'categorie', 'contenu') # Pour récupérer des données cel apeut ce faire avec un POST # ou directement en donnant un objet du modele : #form = ArticleForm(instance=article) # article est bien entendu un objet d'Article quelconque dans la base de données # Le champs est ainsi préremplit. # Quand on a recu une bonne formeModele il suffit de save() pour la mettre en base # /!\ S'il faut faire des verifications/modifications avant d'enregistrer il est possible de faire : #form = ArticleForm(donnees) # Pas besoin de spécifier les autres champs, ils ont été exclus #article = form.save(commit=False) # Ne sauvegarde pas directement l'article dans la base de données #article.categorie = Categorie.objects.all()[0] # Nous ajoutons les attributs manquants #article.auteur = "Jean-Albert" #article.save() #Pour les images. class NouveauContactForm(forms.Form): nom = forms.CharField() adresse = forms.CharField(widget=forms.Textarea) photo = forms.ImageField()

UTF-8

Python

py

forms.py

b-liw/cryptopals

c3954b5fdfc304e00636365154dacc9cf960311a

7955547961ddde1c5ea1a1a7390538d9c0d0effb

/set2/byte_at_a_time_ecb_decryption_harder.py

78b1b67343fcced5cf97ab0fbcbacf6a8e09e61e

no_license

https://github.com/b-liw/cryptopals

83b444f30aa459b2ee5d0ec7081b6ca155234def

14e19cfc63ff93a55bec498a1c0b2d4746d639f4

refs/heads/master

import base64 from Crypto.Random import get_random_bytes from set2.aes_ecb import encrypt_aes_128_ecb from set2.pkcs7_pad import pkcs7_pad oracle_global_key = get_random_bytes(16) def brute_force_block_size(ciphertext): for block_size in range(2, 64): if len(ciphertext) % block_size == 0: blocks = [ciphertext[i * block_size:i * block_size + block_size] for i in range(0, len(ciphertext) // block_size)] for i in range(len(blocks) - 1): if blocks[i] == blocks[i + 1]: return block_size return None def ecb_suffix_oracle(plaintext): random_prefix = b"tEOW49TgR2bg7HRhJdFLpjAXX7Ju6iZgxJRbyUdvoWQAETI1Gt5x5Gyp47rjZw" secret_suffix = base64.b64decode( "Um9sbGluJyBpbiBteSA1LjAKV2l0aCBteSByYWctdG9wIGRvd24gc28gbXkgaGFpciBjYW4gYmxvdwpUaGUgZ2lybGllcyBvbiBzdGFuZGJ5IHdhdmluZyBqdXN0IHRvIHNheSBoaQpEaWQgeW91IHN0b3A/IE5vLCBJIGp1c3QgZHJvdmUgYnkK") return encrypt_aes_128_ecb(pkcs7_pad(random_prefix + plaintext + secret_suffix, 16), oracle_global_key) def get_block_size(): ciphertext = ecb_suffix_oracle(b"A" * 100) return brute_force_block_size(ciphertext) def get_offset_and_pad_count_of_prefix(block_size): for pad_count in range(1, block_size + 1): pad_to_align_prefix_to_block_size = b"B" * pad_count ciphertext = ecb_suffix_oracle(pad_to_align_prefix_to_block_size + b"A" * block_size * 2) blocks = [ciphertext[i * block_size:i * block_size + block_size] for i in range(0, len(ciphertext) // block_size)] for i in range(0, len(blocks) - 1): if blocks[i] == blocks[i + 1]: return pad_count, i * block_size return None def break_ecb_suffix_oracle_harder(): retrieved_secret = b"" try: block_size = get_block_size() pad_count, offset = get_offset_and_pad_count_of_prefix(block_size) num_of_blocks = 10 for n in range(1, num_of_blocks * block_size): encrypt_dict = dict() prefix_template = b"B" * pad_count + b"A" * ((block_size * num_of_blocks) - n) for unknown_byte in range(0, 256): prefix = prefix_template + retrieved_secret + chr(unknown_byte).encode() k = ecb_suffix_oracle(prefix) encrypt_dict[k[offset:offset + block_size * num_of_blocks]] = unknown_byte retrieved_secret += chr( encrypt_dict[ecb_suffix_oracle(prefix_template)[offset:offset + block_size * num_of_blocks]]).encode() except ValueError: return retrieved_secret finally: return retrieved_secret

UTF-8

Python

py

byte_at_a_time_ecb_decryption_harder.py

Gunjankushwaha/hackthon2

aa168b49737aa48d65c8ad896bf7389c6e22a583

96f000d16e29fd60199fea8585af515da7818b03

/gunjan.py

14ab45213550b08e4ecd2ded6c0ec1006ccaf74d

no_license

https://github.com/Gunjankushwaha/hackthon2

d80e7b9450398ed1abdca2fc9a49f1cf9c6bc46f

bf7fab859fc45260f7c7aa6f2378deb30d6e616d

refs/heads/main

basic_salary=int(input("enter the basic_salary")) salary=10000 if basic_salary<=10000: # print("basic_salary+hrd+da") hrd=int(input("enter the hrd")) if hrd%10000==20: salary%=salary-20 # print("basic_salary%20") # num2=int(input ("enter the salary")) # if num2<=20000: # c=num2-num2*20/100 # print(c) # num3=int(input("enter the salary")) # if num3>=20000: # e=num3-num3*30/100 # print(e) # else: # print("not right") # else: # print("good") # else: # print("not r # da=int(input("enter the amount")) # if da/10000==80: # print("right amount") # # prin("it is right salary") # basac_salary=int(inpu("enter the basac_salary")) # print("basic_salary") # elif basic_salary<=20000: # hrd=int(input("enter the hrd")) # if hrd==20/: # da=int(input("ente the da")) # if da==90/: # print("it is right salary") # basic_salary==int(input("enter the basic_salary")) # elif basic_salary>=20000: # hrd=int(input("enter the hrd")) # if hrd==30/: # da=int(input("enter the da")) # if da==95/: # print("it is goo salary") # else: # print("right") # else: # print("nice") # else: # print("parphect")

UTF-8

Python

py

gunjan.py

lenchevsky/organikos

ac8972fc2694be1fe320b84409dabfc4ec140ab5

4b15b39222699e85178c88232fb128a90a9e4c08

/organikos_cms/core/views.py

6b55e94c491b356596c54992dcd96ed65eff4b48

permissive

https://github.com/lenchevsky/organikos

118a051bc2c61a04c8eb675ba4167b131cde56b5

bc54234152a0b6c5a0cc68f07119ce8bdcfd1024

refs/heads/master

JavaScript

# @Project: Organikos Git Repositories (OGR) # @Version: 0.6b # @Author: Oleg Snegirev <ol.snegirev@gmail.com> # @Functionality: Views from django.shortcuts import render from django.http import HttpResponse from .models import OGRCore, OGRRepo def allReposIndex(request): # List all repositories found on this Core try: default_core = OGRCore.objects.get(host__exact="localhost") except OGRCore.DoesNotExist: default_core = OGRCore(name="Local Repository", host="localhost") default_core.save() default_core.populateRepoList() all_cores = OGRCore.objects.all() context = {'core': default_core, 'cores_list': all_cores} return render(request, 'core/repo_list.html', context) def repoIndex(request,repo_id): return HttpResponse("Please see paricular repo with id %s." %repo_id) def repoSource(request, repo_id, branch_name): # Display root content of the repository within specified branch repo = OGRRepo.objects.get(id=repo_id) rootSource = repo.fetchRepo(branch_name) context = {'folders': rootSource['folders'], 'files': rootSource['files'], 'repo': repo} return render(request, 'core/source.html', context) def repoSourceByHash(request, repo_id, hash, branch_name): repo = OGRRepo.objects.get(id=repo_id) rootSource = repo.getChilds(hash) context = {'folders': rootSource['folders'], 'files': rootSource['files'], 'repo': repo} return render(request, 'core/source.html', context) def fileContent(request, repo_id, hash): repo = OGRRepo.objects.get(id=repo_id) file_source = repo.getFileContent(hash) context = {'source': file_source} return render(request,'core/content.html',context)

UTF-8

Python

py

views.py

cliffc2/cardano-api-tests

9312ead5d4a3e51be7ccca6d77e9ae2c1046d59d

3f91ee669b928b0cbd82e93c644370066b60bbf7

/ada-ticker.py

c93f355dd9add7d17adf73ce76c66fe9576d119d

no_license

https://github.com/cliffc2/cardano-api-tests

569ceee3f2a736d338473016e293c06aca05a5ca

12120c5e592fc677d0953324988a9cb2acc336a1

refs/heads/master

#this is a bitcoin cardano api test #https://medium.com/@randerson112358/get-bitcoin-price-in-real-time-using-python-98b7393b6152 #Import the requests library import requests TICKER_API_URL = 'https://api.coinmarketcap.com/v1/ticker/' def get_latest_crypto_price(crypto): response = requests.get(TICKER_API_URL+crypto) response_json = response.json() return float(response_json[0]['price_usd']) #Test the function to see if it returns the current price of the crypto currency. get_latest_crypto_price('cardano')

UTF-8

Python

py

ada-ticker.py

MaximHirschmann/project-euler-solutions

1c2cfef21d5016073cb5ee842cdac7b2bb120b8e

aeb8f555ccead132a59553977958954b28ac5350

/Python/798.py

bae2740b3cef3d6cc38f67b93fe4c251faac95ea

no_license

https://github.com/MaximHirschmann/project-euler-solutions

25ed23e945894654c9c90b7d3dbb3c9c4d0f944e

ca5fff4498d6e884d122c97804a6cc37ca6c2feb

refs/heads/master

# NOT FINISHED from collections import defaultdict import functools import itertools from tabulate import tabulate from time import time from sympy import factorint start = time() n = 4 s = 6 def other(player): return -player def filter_deck(visible, deck): smallest_of_suit = [n] * s for num, suit in visible: smallest_of_suit[suit] = min(smallest_of_suit[suit], num) new_deck = [] for num, suit in deck: if num <= smallest_of_suit[suit]: continue else: new_deck.append((num, suit)) return new_deck def filter_visible(visible, deck): biggest_of_suit = [-1] * s for num, suit in deck: biggest_of_suit[suit] = max(biggest_of_suit[suit], num) new_visible = [] for num, suit in visible: if num >= biggest_of_suit[suit]: continue else: new_visible.append((num, suit)) return new_visible # players turn def rec(visible, deck, player = 1, depth = 0): if visible == [(0, 1), (1, 0)]: pass if visible == [] or deck == []: return other(player) #deck = filter_deck(visible, deck) #visible = filter_visible(visible, deck) move_available = False for i in range(len(deck)): num1, suit1 = deck[i] for j in range(len(visible)): num2, suit2 = visible[j] if suit2 != suit1 or num2 > num1: # you cant put that card on top of the other one continue new_visible = [(num1, suit1) if k == j else visible[k] for k in range(len(visible))] new_deck = [deck[k] for k in range(len(deck)) if k != i ] #print(" " * depth, (num1, suit1), "on", (num2, suit2)) res = rec(new_visible, new_deck, other(player), depth + 1) if res == player: return player return other(player) @functools.lru_cache(None) def rec3(higher, depth = 0): higher = tuple(i for i in higher if i != 0) if higher == (): return -1 grouped = defaultdict(int) for i in higher: grouped[i] += 1 g = tuple(sorted(grouped.items())) # iterate over moves for v, _ in g: for i in range(v): new = [] once = False for elem in higher: if elem == v: if once: new.append(elem - 1) else: new.append(i) once = True elif elem < v: if i < elem: new.append(elem - 1) else: new.append(elem) else: new.append(elem - 1) new.sort() new = tuple(new) res = rec3(new, depth + 1) if res == -1: return 1 return -1 def filter_zeros(higher): new = [] for suit in higher: new2 = [] for elem in suit: if elem != 0: new2.append(elem) if new2: new.append(tuple(new2)) return tuple(new) def base2(higher): new = [] for suit in higher: highest = max(suit) c = 0 for i in suit: if i == highest: c += 1 c = min(c, 2) new_suit = [highest for _ in range(c)] new.append(tuple(new_suit)) return tuple(new) mem = {} # input of form ((2, 3, 4), (1, 2), (2)) def rec3_2(higher): higher = filter_zeros(higher) if higher in mem: return mem[higher] if higher == (): return -1 for idx, suit in enumerate(higher): last = None for i in suit: if i == last: continue last = i for value in range(i): new = [] once = False for elem in suit: to_add = 0 if elem == i: if once: to_add = elem - 1 else: to_add = value once = True elif elem < i: if value < elem: to_add = elem - 1 else: to_add = elem else: to_add = elem - 1 if to_add != 0: new.append(to_add) new.sort() new = tuple(new) new2 = [higher[j] if j != idx else new for j in range(len(higher))] new2.sort() #print(new2) res = rec3_2(tuple(new2)) if res == -1: mem[higher] = 1 return 1 mem[higher] = -1 return -1 def who_wins(visible, deck, player = 1): ret = [] for suit in range(s): new_visible = [(num1, suit1) for num1, suit1 in visible if suit1 == suit] new_deck = [(num1, suit1) for num1, suit1 in deck if suit1 == suit] res = who_wins_one_suite(new_visible, new_deck, player) match res: case (False, True): new = 0 case (True, False): new = 1 case (True, True): new = 2 ret.append(new) return ret def split_to_result(splitted): count = [0, 0, 0] for i in splitted: count[i] += 1 if count[1] % 2 == 0 and count[2] % 2 == 0: return -1 else: return 1 def who_wins_one_suite(visible, deck, player = 1): # can i force a win? win = winner_best_play(visible, deck) == 1 # can i force a loss loss = winner_worst_play(visible, deck) == -1 return (win, loss) def winner_best_play(visible, deck, player=1): if visible == [] or deck == []: return other(player) for card_chosen in deck: for stack_chosen in visible: if stack_chosen[1] != card_chosen[1] or stack_chosen[0] > card_chosen[0]: # you cant put that card on top of the other one continue new_visible = [card_chosen if card == stack_chosen else card for card in visible] new_deck = [card for card in deck if card != card_chosen] res = winner_best_play(new_visible, new_deck, other(player)) if res == player: return player return other(player) def winner_worst_play(visible, deck, player=1): if visible == [] or deck == []: return other(player) move_available = False for card_chosen in deck: for stack_chosen in visible: if stack_chosen[1] != card_chosen[1] or stack_chosen[0] > card_chosen[0]: # you cant put that card on top of the other one continue move_available = True new_visible = [card_chosen if card == stack_chosen else card for card in visible] new_deck = [card for card in deck if card != card_chosen] res = winner_worst_play(new_visible, new_deck, other(player)) if res == other(player): return other(player) if not move_available: return other(player) return player cards = list(itertools.product(range(n), range(s))) count = 0 count2 = 0 table = [] for i in range(2**(len(cards))): b = bin(i)[2:].rjust(len(cards), "0") visible = [] deck = [] for j in range(len(cards)): if b[j] == "0": deck.append(cards[j]) else: visible.append(cards[j]) #winner = rec(visible, deck) higher = [] for suit in range(s): add = [] for card in visible: if card[1] != suit: continue count = 0 for card2 in deck: if card2[1] != suit: continue if card2[0] > card[0]: count += 1 add.append(count) if add: higher.append(tuple(add)) higher.sort() higher = tuple(higher) higher = filter_zeros(higher) higher = base2(higher) w = rec3_2(higher) if w == -1: count2 += 1 #table.append((higher, w)) # table.sort() # print(tabulate(table)) print(count2) print(time() - start, "s")

UTF-8

Python

py

798.py

scadding/MyUniverse

d82449329850b834d598df68200cf1e5ed0f6969

6ffde6c22c923e773f791925fa7df6341ccc1402

/Data.old/Tables/Generators/Sites - Mystic Places.py

bd76bb4cf67127ccc7db264ff2e5bcdc9b703c15

no_license

https://github.com/scadding/MyUniverse

e2163b57aefbdc5f2dd2533cf836db26fc19d95c

d2b196bae19592784bfe4315baf76a6954261391

refs/heads/master

from random import choice from random import randint class generator: def version(self): return 1.0 def start(self): result = '' groups = { 0: self.place() + ' of ' + self.thing(), 1: self.adj() + ' ' + self.place(), 2: self.adj() + ' ' + self.place() + ' of ' + self.thing(), } result = groups[randint(0,2)] return result def adj(self): elements = ["Bright", "Burning", "Dead", "Eternal", "Forgotten", "Golden", "Living", "Lost", "Shining", "Silver", "Sunken", "Undying"] return choice(elements) def place(self): elements = ["Castle", "Cave", "Chasm", "City", "Coast", "Desert", "Field", "Forest", "Fortress", "Fountain", "Garden", "Grove", "Hamlet", "Hill", "Isle", "Jungle", "Lake", "Mansion", "Marsh", "Mesa", "Mine", "Mire", "Mountain", "Pillar", "River", "Ruins", "Sea", "Shores", "Shrine", "Source", "Spire", "Stone", "Swamp", "Temple", "Tower", "Valley"] return choice(elements) def thing(self): elements = ["the Abyss", "Blood", "Bronze", "Dawn", "the Dead", "Doom", "Dragons", "Dread", "Dust", "Eternal Peril", "Fire", "Flame", "Frost", "the Gods", "Gold", "Heaven", "Ice", "the Inferno", "Iron", "Lightning", "Maps Edge", "Mists", "Mithril", "No Return", "Runes", "Scales", "the Seven", "Shadow", "Silver", "Skulls", "the Sky", "Stone", "Swords", "Thunder", "Wind", "Youth"] return choice(elements) #x = generator() #print x.start()

UTF-8

Python

py

Sites - Mystic Places.py

l1berov/Switch

41403d6ec7921068f0e0596cfa51c07af8811d3b

5a97f04444c4a05c1e9170a4b751972c550847fa

/liberscripts/fff.py

d226a296f5b609662e49128956f2964325ae93ef

no_license

https://github.com/l1berov/Switch

1aa20b8229a35355d0ded96b81ae5a750ee8badb

3d12c0e132cc06cfd83bf9b7d770c98d91e9787d

refs/heads/main

import colorama, os, time, vk_api, sys from os import system from colorama import Fore , Back , Style os.system('clear') print(Fore.YELLOW+''' ______ _ _ | ____| (_) | | | |__ _ __ _ ___ _ __ __| | | __| '__| |/ _ \ '_ \ / _` | | | | | | | __/ | | | (_| | |_| |_| |_|\___|_| |_|\__,_| by batyarimskiy ''') with open("ids.txt") as f: user_ids = f.read().splitlines() session = vk_api.VkApi(token = input(Fore.GREEN+'Введите токен'+Fore.WHITE+' ~# ')) vk = session.get_api() for user_id in user_ids: vk.friends.add( user_id=user_id ) time.sleep(40)

UTF-8

Python

py

fff.py

OpenDataCubePipelines/opendatacubepipeline.tesp

e83c22a9544c2c1a0f8ffd52dd368e85a3df3b21

6e86c22122a5a0a1bb0119844e4d1244d3b962ee

/bin/ard_pbs

dfbf3fd063891a40dde69b0cf9d5fd1aba7c3a50

no_license

https://github.com/OpenDataCubePipelines/opendatacubepipeline.tesp

4464160cd48e6eacb9921a13653337dbf8d81410

0c20d54adc01f8c6cb370635ab7f4f9c0c4d5929

refs/heads/master

#!/usr/bin/env python """ PBS submission scripts. """ import os import re import json import logging from os.path import join as pjoin, dirname, exists from pathlib import Path import subprocess import uuid import click import math from wagl.tiling import scatter PBS_RESOURCES = ("""#!/bin/bash #PBS -P {project} #PBS -W umask=017 #PBS -q {queue} #PBS -l walltime={walltime},mem={memory}GB,ncpus={ncpus},jobfs={jobfs}GB,other=pernodejobfs #PBS -l wd #PBS -l storage={filesystem_projects} #PBS -me {email} """) NODE_TEMPLATE = ("""{pbs_resources} source {env} {daemon} luigi --module tesp.workflow ARDP --level1-list {scene_list} --workdir {outdir} --pkgdir {pkgdir} --workers {workers} --parallel-scheduling """) SUMMARY_TEMPLATE = ("""{pbs_resources} #PBS -W depend=afterany:{jobids} source {env} batch_summary --indir {indir} --outdir {outdir} # jq queries # concatenate logs to enable querying on a single file find -type f -name 'task-log.jsonl' | xargs cat >> batch-{batchid}-task-log.jsonl find -type f -name 'status-log.jsonl' | xargs cat >> batch-{batchid}-status-log.jsonl # summaries on success and failure records jq 'select(.status == "success") | {{task, level1}}' batch-{batchid}-task-log.jsonl | jq --slurp 'unique_by(.level1, .task) | group_by(.task) | map({{task: .[0].task, count: length}})' > batch-{batchid}-success-task-summary.json jq 'select(.status == "failure") | {{task, level1}}' batch-{batchid}-task-log.jsonl | jq --slurp 'unique_by(.level1, .task) | group_by(.task) | map({{task: .[0].task, count: length}})' > batch-{batchid}-failure-task-summary.json # capture failures and report the exception, level1, task and granule id jq 'select(.status == "failure") | {{level1, exception, task, granule: .params.granule}}' batch-{batchid}-task-log.jsonl | jq --slurp 'unique_by(.level1, .task, .granule)' > batch-{batchid}-exception-log.json # get a listing of which level1-lists from which jobid's had 100% success (all scenes processed through to packaging) jq 'select(.task == "ARDP") | {{task, level1_list: .params.level1_list, status}}' batch-{batchid}-task-log.jsonl | jq --slurp 'unique_by(.level1_list)' > batch-{batchid}-ardp-job-sucess.json # get a listing of level1 datasets and the granule id that packaged successfully (Package is the last task to be done as defined in the luigi workflow) and report that "ard processing is complete" jq 'select(.status == "success" and .task == "Package") | {{level1, granule: .params.granule, notification: "ard processing complete"}}' batch-{batchid}-task-log.jsonl | jq --slurp 'unique_by(.level1, .granule)' > batch-{batchid}-package-success.json # compile a list of successfully packaged datasets (and their path) to pass over to indexing jq 'select(.event == "packaged dataset") | .dataset_path' batch-{batchid}-status-log.jsonl | jq -sr 'unique | .[]' > batch-{batchid}-datasets-to-index.txt """) INDEXING_TEMPLATE = ("""{pbs_resources} #PBS -W depend=afterany:{jobid} source {env} # indexing cat batch-{batchid}-datasets-to-index.txt | parallel -j 47 -m -n 20 --line-buffer datacube dataset add --no-verify-lineage """) ARCHIVING_TEMPLATE = ("""{pbs_resources} source {env} # archiving cat {archive_list} | parallel -j 47 -m -n 20 --line-buffer datacube dataset archive """) FMT1 = 'batchid-{batchid}' FMT2 = 'jobid-{jobid}' FMT3 = 'level1-scenes-{jobid}.txt' FMT4 = 'jobid-{jobid}.bash' FMT5 = 'batch-{batchid}-summary.bash' FMT6 = 'batch-{batchid}-indexing.bash' FMT7 = 'scratch/{f_project}+gdata/{f_project}' FMT8 = 'archiving-{batchid}.bash' DAEMON_FMT = 'luigid --background --logdir {}' def _calc_nodes_req(granule_count, walltime, workers, hours_per_granule=1.5): """ Provides estimation of the number of nodes required to process granule count >>> _calc_nodes_req(400, '20:59', 28) 2 >>> _calc_nodes_req(800, '20:00', 28) 3 """ hours, _, _ = [int(x) for x in walltime.split(':')] return int(math.ceil(float(hours_per_granule * granule_count) / (hours * workers))) def _get_project_for_path(path: Path): """ Get the NCI project used to store the given path, if any. >>> _get_project_for_path(Path('/g/data/v10/some/data/path.txt')) 'v10' >>> _get_project_for_path(Path('/g/data4/fk4/some/data/path.txt')) 'fk4' >>> _get_project_for_path(Path('/scratch/da82/path.txt')) 'da82' >>> _get_project_for_path(Path('/tmp/other/data')) """ posix_path = path.as_posix() if posix_path.startswith('/g/data'): return posix_path.split('/')[3] if posix_path.startswith('/scratch/'): return posix_path.split('/')[2] return None def _filesystem_projects(level1_list: list, env: str, logdir: str, workdir: str, pkgdir: str): """ Collect all the filesystem projects into a set. """ fs_projects = {None} fs_projects.add(_get_project_for_path(Path(workdir))) fs_projects.add(_get_project_for_path(Path(logdir))) fs_projects.add(_get_project_for_path(Path(pkgdir))) fs_projects.add(_get_project_for_path(Path(env))) fs_projects.add(_get_project_for_path(Path(click.__file__))) with open(level1_list, 'r') as src: paths = [p.strip() for p in src.readlines()] for pathname in paths: fs_projects.add(_get_project_for_path(Path(pathname))) fs_projects.remove(None) return fs_projects # pylint: disable=too-many-arguments def _submit_multiple(scattered, env, batch_logdir, batch_outdir, pkgdir, workers, pbs_resources, test): """Submit multiple PBS formatted jobs.""" nci_job_ids = [] # setup and submit each block of scenes for processing for block in scattered: jobid = uuid.uuid4().hex[0:6] jobdir = pjoin(batch_logdir, FMT2.format(jobid=jobid)) job_outdir = pjoin(batch_outdir, FMT2.format(jobid=jobid)) if not exists(jobdir): os.makedirs(jobdir) if not exists(job_outdir): os.makedirs(job_outdir) # write level1 data listing out_fname = pjoin(jobdir, FMT3.format(jobid=jobid)) with open(out_fname, 'w') as src: src.writelines(block) pbs = NODE_TEMPLATE.format(pbs_resources=pbs_resources, env=env, daemon=DAEMON_FMT.format(jobdir), scene_list=out_fname, outdir=job_outdir, pkgdir=pkgdir, workers=workers) # write pbs script out_fname = pjoin(jobdir, FMT4.format(jobid=jobid)) with open(out_fname, 'w') as src: src.write(pbs) if test: click.echo("Mocking... Submitting Job: {} ...Mocking".format(jobid)) click.echo("qsub {}".format(out_fname)) continue os.chdir(dirname(out_fname)) click.echo("Submitting Job: {}".format(jobid)) try: raw_output = subprocess.check_output(['qsub', out_fname]) except subprocess.CalledProcessError as exc: logging.error('qsub failed with exit code %s', str(exc.returncode)) logging.error(exc.output) raise if hasattr(raw_output, 'decode'): matches = re.match(r'^(?P<nci_job_id>\d+\.gadi-pbs)$', raw_output.decode('utf-8')) if matches: nci_job_ids.append(matches.groupdict()['nci_job_id']) # return a list of the nci job ids return nci_job_ids def _submit_summary(indir, outdir, batch_id, pbs_resources, env, job_ids, test): """Summarise the jobs submitted within the batchjob.""" jobids = ":".join([j.split('.')[0] for j in job_ids]) pbs = SUMMARY_TEMPLATE.format(pbs_resources=pbs_resources, env=env, indir=indir, outdir=outdir, jobids=jobids, batchid=batch_id) out_fname = pjoin(indir, FMT5.format(batchid=batch_id)) with open(out_fname, 'w') as src: src.write(pbs) if test: click.echo("Mocking... Submitting Summary Job for batch: {} ...Mocking".format(batch_id)) click.echo("qsub {}".format(out_fname)) return os.chdir(dirname(out_fname)) click.echo("Submitting Summary Job for batch: {}".format(batch_id)) try: raw_output = subprocess.check_output(['qsub', out_fname]) except subprocess.CalledProcessError as exc: logging.error('qsub failed with exit code %s', str(exc.returncode)) logging.error(exc.output) raise if hasattr(raw_output, 'decode'): matches = re.match(r'^(?P<nci_job_id>\d+\.gadi-pbs)$', raw_output.decode('utf-8')) if matches: job_id = matches.groupdict()['nci_job_id'] return job_id def _submit_index(indir, outdir, batch_id, pbs_resources, env, job_id, test): """Submit a job that adds datasets to a datacube index.""" if job_id: jobid = job_id.split('.')[0] else: jobid = '' pbs = INDEXING_TEMPLATE.format(pbs_resources=pbs_resources, env=env, indir=indir, outdir=outdir, jobid=jobid, batchid=batch_id) out_fname = pjoin(indir, FMT6.format(batchid=batch_id)) with open(out_fname, 'w') as src: src.write(pbs) if test: click.echo("Mocking... Submitting Indexing Job for batch: {} ...Mocking".format(batch_id)) return os.chdir(dirname(out_fname)) click.echo("Submitting Indexing Job for batch: {}".format(batch_id)) try: raw_output = subprocess.check_output(['qsub', out_fname]) except subprocess.CalledProcessError as exc: logging.error('qsub failed with exit code %s', str(exc.returncode)) logging.error(exc.output) raise if hasattr(raw_output, 'decode'): matches = re.match(r'^(?P<nci_job_id>\d+\.gadi-pbs)$', raw_output.decode('utf-8')) if matches: job_id = matches.groupdict()['nci_job_id'] return job_id def _submit_archive(indir, outdir, archive_list, batch_id, pbs_resources, env, test): """Submit a job that archives datasets given a file listing UUIDs.""" pbs = ARCHIVING_TEMPLATE.format(pbs_resources=pbs_resources, env=env, indir=indir, outdir=outdir, archive_list=archive_list) out_fname = pjoin(indir, FMT8.format(batchid=batch_id)) with open(out_fname, 'w') as src: src.write(pbs) if test: click.echo("Mocking... Submitting Archiving Job for batch: {} ...Mocking".format(batch_id)) return os.chdir(dirname(out_fname)) click.echo("Submitting Archiving Job for batch: {}".format(batch_id)) try: raw_output = subprocess.check_output(['qsub', out_fname]) except subprocess.CalledProcessError as exc: logging.error('qsub failed with exit code %s', str(exc.returncode)) logging.error(exc.output) raise if hasattr(raw_output, 'decode'): matches = re.match(r'^(?P<nci_job_id>\d+\.gadi-pbs)$', raw_output.decode('utf-8')) if matches: job_id = matches.groupdict()['nci_job_id'] return job_id @click.command() @click.option("--level1-list", type=click.Path(exists=True, readable=True), help="The input level1 scene list.") @click.option("--workdir", type=click.Path(file_okay=False, writable=True), help="The base output working directory.") @click.option("--logdir", type=click.Path(file_okay=False, writable=True), help="The base logging and scripts output directory.") @click.option("--pkgdir", type=click.Path(file_okay=False, writable=True), help="The base output packaged directory.") @click.option("--env", type=click.Path(exists=True, readable=True), help="Environment script to source.") @click.option("--workers", type=click.IntRange(1, 48), default=30, help="The number of workers to request per node.") @click.option("--nodes", default=0, help="The number of nodes to request.") @click.option("--memory", default=192, help="The memory in GB to request per node.") @click.option("--jobfs", default=50, help="The jobfs memory in GB to request per node.") @click.option("--project", required=True, help="Project code to run under.") @click.option("--queue", default='normal', help="Queue to submit the job into, eg normal, express.") @click.option("--walltime", default="48:00:00", help="Job walltime in `hh:mm:ss` format.") @click.option("--email", default="", help="Notification email address.") @click.option("--index-datacube-env", type=click.Path(exists=True, readable=True), help="Datacube specific environment script to source.") @click.option("--archive-list", type=click.Path(exists=True, readable=True), help="UUID's of the scenes to archive. This uses the environment specified in index-datacube-env.") @click.option("--test", default=False, is_flag=True, help=("Test job execution (Don't submit the job to the " "PBS queue).")) # pylint: disable=too-many-arguments def main(level1_list, workdir, logdir, pkgdir, env, workers, nodes, memory, jobfs, project, queue, walltime, email, index_datacube_env, archive_list, test): """ Equally partition a list of scenes across n nodes and submit n jobs into the PBS queue for ARD processing. """ with open(level1_list, 'r') as src: scenes = src.readlines() if nodes == 0: nodes = _calc_nodes_req(len(scenes), walltime, workers) scattered = scatter(scenes, nodes) batchid = uuid.uuid4().hex[0:10] batch_logdir = pjoin(logdir, FMT1.format(batchid=batchid)) batch_outdir = pjoin(workdir, FMT1.format(batchid=batchid)) fs_projects = _filesystem_projects(level1_list, env, logdir, workdir, pkgdir) fsys_projects = '+'.join([FMT7.format(f_project=f) for f in fs_projects]) # optionally set pbs email string pbs_resources = PBS_RESOURCES.format(project=project, queue=queue, walltime=walltime, memory=memory, ncpus=workers, jobfs=jobfs, filesystem_projects=fsys_projects, email=('#PBS -M ' + email) if email else "") if test: click.echo("Mocking... Submitting Batch: {} ...Mocking".format(batchid)) else: click.echo("Submitting Batch: {}".format(batchid)) click.echo("Executing Batch: {}".format(batchid)) nci_job_ids = _submit_multiple(scattered, env, batch_logdir, batch_outdir, pkgdir, workers, pbs_resources, test) # job resources for batch summary pbs_resources = PBS_RESOURCES.format(project=project, queue='express', walltime="00:10:00", memory=6, ncpus=1, jobfs=2, filesystem_projects=''.join(fsys_projects), email=('#PBS -M ' + email) if email else "") job_id = _submit_summary(batch_logdir, batch_logdir, batchid, pbs_resources, env, nci_job_ids, test) nci_job_ids.append(job_id) if index_datacube_env: pbs_resources = PBS_RESOURCES.format(project=project, queue='normal', walltime="00:30:00", memory=192, ncpus=48, jobfs=20, filesystem_projects=''.join(fsys_projects), email=('#PBS -M ' + email) if email else "") index_job_id = _submit_index(batch_logdir, batch_logdir, batchid, pbs_resources, index_datacube_env, job_id, test) nci_job_ids.append(index_job_id) if archive_list: if index_datacube_env: pbs_resources = PBS_RESOURCES.format(project=project, queue='normal', walltime="00:30:00", memory=192, ncpus=48, jobfs=20, filesystem_projects=''.join(fsys_projects), email=('#PBS -M ' + email) if email else "") archive_job_id = _submit_archive(batch_logdir, batch_logdir, archive_list, batchid, pbs_resources, index_datacube_env, test) nci_job_ids.append(archive_job_id) else: logging.error('Archive list given but --index-datacube-env not specified.') job_details = { 'ardpbs_batch_id': batchid, 'nci_job_ids': nci_job_ids } # Enable the job details to be picked up by the calling process click.echo(json.dumps(job_details)) if __name__ == '__main__': main()

UTF-8

Python

ard_pbs

Shakil-1501/Session6

3b8e785de4480e9a0c6eabd0c69d7702af9d3ba0

669677ac5cccf328426ef141cfdb8e99e8127452

/session6.py

8fa1404add9e5fbe962589bfba800e3d8d033e30

no_license

https://github.com/Shakil-1501/Session6

f6679ff5c2530e2c2c3b6ff7ae765a2378a6a2f4

7886602e463b3cb6c01bff7f8d0cb1d1d7bebdf6

refs/heads/master

from typing import List import time import sys import weakref import random from math import tan, pi def poker(vals,suits): ''' returns the list of 52 created cards in a deck ''' k=[] #l=[] for i in vals: for j in suits: k.append((i+j)) return k def pokerstar(no_of_card:'int',no_of_player:'int',sequence_cardsA:'list',sequence_cardsB:'list') ->'winner of the game': """returns p some additional documentation Inputs: number of cards,number of player,sequence_cards for A,sequence_cards for B Outputs: winner of the match """ a=['acehearts','kinghearts','queenhearts','jackhearts','10hearts'] b=['10clubs','9clubs','8clubs','7clubs','6clubs'] c=['queenclubs','queenhearts','queenspades','queendiamonds','5clubs'] d=['acediamonds','acespades','acediamonds','kingspades','kingdiamonds'] e=['kinghearts','8hearts','6hearts','4hearts','2hearts'] f=['8diamonds','7clubs','6diamonds','5spades','4diamonds'] g=['queenclubs','queenhearts','queenspades','7diamonds','2spades'] h=['jackdiamonds','jackspades','9spades','9diamonds','5clubs'] i=['kinghearts','kingspades','9daimonds','8spades','4hearts'] j=['acehearts','queenclubs','6hearts','4spades','2diamonds'] if len(sequence_cardsA)==len(sequence_cardsB): if no_of_player==2: if no_of_card==3: if sequence_cardsA == a[0:3]: p="Player A is winner" elif sequence_cardsA == b[0:3] and sequence_cardsB!=a[0:3] : p="Player A is winner" elif sequence_cardsA == c[0:3] and (sequence_cardsB!=a[0:3] or sequence_cardsB!=b[0:3]): p="Player A is winner" elif sequence_cardsA == d[0:3] and (sequence_cardsB!=a[0:3] or sequence_cardsB!=b[0:3] or sequence_cardsB!=c[0:3]): p="Player A is winner" elif sequence_cardsA == e[0:3] and (sequence_cardsB!=a[0:3] or sequence_cardsB!=b[0:3] or sequence_cardsB!=c[0:3] or sequence_cardsB!=d[0:3]): p="Player A is winner" elif sequence_cardsA == f[0:3] and (sequence_cardsB!=a[0:3] or sequence_cardsB!=b[0:3] or sequence_cardsB!=c[0:3] or sequence_cardsB!=d[0:3] or sequence_cardsB!=e[0:3]): p="Player A is winner" elif sequence_cardsA == g[0:3] and (sequence_cardsB == h[0:3] or sequence_cardsB==i[0:3] or sequence_cardsB==j[0:3]): p="Player A is winner" elif sequence_cardsA == h[0:3] and (sequence_cardsB == i[0:3] or sequence_cardsB==j[0:3]): p="Player A is winner" elif sequence_cardsA ==i[0:3] and sequence_cardsB == j[0:3]: p="Player A is winner" else: p="Player B is winner" elif no_of_card==4: if sequence_cardsA == a[0:4]: p="Player A is winner" elif sequence_cardsA == b[0:4] and sequence_cardsB!=a[0:4] : p="Player A is winner" elif sequence_cardsA == c[0:4] and (sequence_cardsB!=a[0:4] or sequence_cardsB!=b[0:4]): p="Player A is winner" elif sequence_cardsA == d[0:4] and (sequence_cardsB!=a[0:4] or sequence_cardsB!=b[0:4] or sequence_cardsB!=c[0:4]): p="Player A is winner" elif sequence_cardsA == e[0:4] and (sequence_cardsB!=a[0:4] or sequence_cardsB!=b[0:4] or sequence_cardsB!=c[0:4] or sequence_cardsB!=d[0:4]): p="Player A is winner" elif sequence_cardsA == f[0:4] and (sequence_cardsB!=a[0:4] or sequence_cardsB!=b[0:4] or sequence_cardsB!=c[0:4] or sequence_cardsB!=d[0:4] or sequence_cardsB!=e[0:4]): p="Player A is winner" elif sequence_cardsA == g[0:4] and (sequence_cardsB == h[0:4] or sequence_cardsB==i[0:4] or sequence_cardsB==j[0:4]): p="Player A is winner" elif sequence_cardsA == h[0:4] and (sequence_cardsB == i[0:4] or sequence_cardsB==j[0:4]): p="Player A is winner" elif sequence_cardsA ==i[0:4] and sequence_cardsB == j[0:4]: p="Player A is winner" else: p="Player B is winner" elif no_of_card==5: if (sequence_cardsA == a) and (sequence_cardsB!=b or sequence_cardsB!=c or sequence_cardsB!=d or sequence_cardsB!=e or sequence_cardsB!=f or sequence_cardsB!=g or sequence_cardsB!=h or sequence_cardsB!=i or sequence_cardsB!=j): p="Player A is winner" elif (sequence_cardsA == b) and (sequence_cardsB != a) : p="Player A is winner" elif (sequence_cardsA == c) and (sequence_cardsB!=a or sequence_cardsB!=b): print("hello2") p="Player A is winner" elif sequence_cardsA == d and (sequence_cardsB!=a or sequence_cardsB!=b or sequence_cardsB!=c): p="Player A is winner" elif sequence_cardsA == e and (sequence_cardsB!=a or sequence_cardsB!=b or sequence_cardsB!=c or sequence_cardsB!=d): p="Player A is winner" elif sequence_cardsA == f and (sequence_cardsB!=a or sequence_cardsB!=b or sequence_cardsB!=c or sequence_cardsB!=d or sequence_cardsB!=e): p="Player A is winner" elif sequence_cardsA == g and (sequence_cardsB == h or sequence_cardsB==i or sequence_cardsB==j): p="Player A is winner" elif sequence_cardsA == h and (sequence_cardsB == i or sequence_cardsB==j): p="Player A is winner" elif sequence_cardsA ==i and sequence_cardsB == j: p="Player A is winner" else: p="Player B is winner" else: p="please enter correct number of card" else: p="please enter correct number of players" else: p="please enter the same length for sequence of cards for both players" return p

UTF-8

Python

py

session6.py

FeelmyLife-droid/BOT_TG

c62e5483ff2c0adc9ec88052dcd0816039fe2b1e

5548be9aa1bbc8640e35f3e4d43c32876aaea1f7

/Keyboards/default/key_start.py

82cd314be18d267c3c9f3796a162d30fec88984a

no_license

https://github.com/FeelmyLife-droid/BOT_TG

3dab8bfdde9df9493dcf3e3cb287c42161a5e08a

8aec6c83886d0f0fbeb4af020919ae42bbed07ba

refs/heads/master

from aiogram.types import ReplyKeyboardMarkup, KeyboardButton key_start = ReplyKeyboardMarkup( keyboard=[ [ KeyboardButton(text='Новые адреса'), KeyboardButton(text='Блокировка Фирм') ], [ KeyboardButton(text='Данные по ИНН'), KeyboardButton(text='Выписка из ЕГРЛ') ] ], resize_keyboard=True)

UTF-8

Python

py

key_start.py

jonasguan/FSND-movie-project

bd970a4bda3eb13b19a519ef088558a6cebb7dfb

9dcb1e586397536db8e0672056be30fe859c9440

/entertainment_center.py

22ae7ff24707af891c28c868504281bf6066c40e

no_license

https://github.com/jonasguan/FSND-movie-project

89e51e73052d9c425dc44603e6617a518943249f

a6d6aa222a30664a649d4700dbea61e9498a874c

refs/heads/master

import media wreck_it_ralph = media.Movie( "Wreck-it Ralph", "A disliked video game character gains popularity by wrecking things.", "https://upload.wikimedia.org/wikipedia/en/1/15/Wreckitralphposter.jpeg", "https://www.youtube.com/watch?v=OzMJkRwOxjs") the_dark_knight = media.Movie( "The Dark Knight", "Batman faces a new supervillian who throws Gotham into utter chaos.", "https://upload.wikimedia.org/wikipedia/en/8/8a/Dark_Knight.jpg", "https://www.youtube.com/watch?v=u843KNE-exo") interstellar = media.Movie( "Interstellar", "A group of scientists journey into space to save mankind from the brink of extinction.", "https://upload.wikimedia.org/wikipedia/en/b/bc/Interstellar_film_poster.jpg", "https://www.youtube.com/watch?v=lZMzf-SDWP8") the_wolf_of_wall_street = media.Movie( "The Wolf of Wall Street", "Based on the real life of Jordan Belfort, a man rises to wealth but gets" "ultimately consumed by his hubris.", "https://upload.wikimedia.org/wikipedia/en/1/1f/WallStreet2013poster.jpg", "https://www.youtube.com/watch?v=BzpIB5TJ7LI") pulp_fiction = media.Movie( "Pulp Fiction", "Several storylines of bad motherfuckers intertwine in a black comedy masterpiece.", "https://upload.wikimedia.org/wikipedia/en/thumb/3/3b/Pulp_Fiction_%281994%29_poster.jpg/220px-Pulp_Fiction_%281994%29_poster.jpg", "https://www.youtube.com/watch?v=t7cuDVbN_mg")

UTF-8

Python

py

entertainment_center.py

sadxiaohu/icbckg

d7640043f97c642b73e9c032619446fff93b2f29

44e8497b108806d98a2d9bda293cc425ef3305fa

/tools/spider&extract/spider_from_web_demo/getting_nodes_fromweb.py

f7b930b2cfa1e5af5823aafe71b22731e97a5bbb

no_license

https://github.com/sadxiaohu/icbckg

138dacdb581b5bb81508250e437ed70a2918a3ac

d005aaf4d46e0d82a34a3a9318a4021d77a1b5da

refs/heads/master

#coding=utf-8 import requests from bs4 import BeautifulSoup import json import codecs def webNodesGet(word_url_dict): nodes = [] id = 0 for word in word_url_dict: url = 'http://www.icbc.com.cn' url = url+word_url_dict[word] wb_data = requests.get(url).content soup = BeautifulSoup(wb_data,'lxml') datalist1 = soup.select('.more') info = {} attr = [] for data in datalist1 : attr.append(data.get_text().replace('\n','')) info[data.get_text().replace('\n','')]='' datalist2 = soup.select('table > tbody > tr > td ') if len(datalist1) != 0 and len(datalist2) != 0: string='' for i in range(2,len(datalist2)): string += datalist2[i].get_text().strip().replace(' ','') string = string.replace('\r','') string = string.replace('\n','') string = string.replace('\t','') string = string.replace('[返回页首]','') string = string.replace('\u3000','') length = len(attr) for i in range(0,length-1): begin = string.find(attr[i]) end = string.find(attr[i+1]) info[attr[i]] = string[begin+len(attr[i]):end] info[attr[-1]] = string[(string.find(attr[-1]))+len(attr[-1]):] info['name'] = word info['id'] = str(id) #print(info) nodes.append(info) id += 1 josn_data = json.dumps({"nodes":nodes},ensure_ascii=False) with codecs.open('nodesfromweb.json','w',encoding='utf-8') as foo: foo.write(josn_data) #print(id) #个人网上银行部分信息 url1 = 'http://www.icbc.com.cn/ICBC/电子银行/电子银行产品/金融a家产品/个人网上银行/个人网上银行/' wb_data = requests.get(url1).content soup = BeautifulSoup(wb_data,'lxml') datalist1 = soup.select('li > ul > li > ul > li > a') datalist2 = soup.select('li > ul > li > a') datalist1.extend(datalist2) #企业网上银行部分信息 url2 = 'http://www.icbc.com.cn/ICBC/电子银行/企业电子银行产品/工行财e通产品/企业网上银行/' wb_data = requests.get(url2).content soup = BeautifulSoup(wb_data,'lxml') datalist3 = soup.select('li > ul > li > ul > li > a') datalist4 = soup.select('li > ul > li > a') datalist3.extend(datalist4) datalist1.extend(datalist3) entity = {} for data in datalist1: if data.get('href') != None: entity[data.get_text().replace(' >','')] = data['href'] webNodesGet(entity)

UTF-8

Python

py

getting_nodes_fromweb.py

bridgecrewio/checkov

20cedb19c9ce77746822d00300ab8389373c2d63

45e376ae66b78b17788b1d3575b334b2cb1d0b1c

/tests/terraform/checks/data/example_external_dir/extra_checks/DummyExternalDataCheck.py

62f6e4377b92be2f288e9121981992a3d142d5d0

permissive

https://github.com/bridgecrewio/checkov

aeb8febed2ed90e61d5755f8f9d80b125362644d

e64cbd27ffb6f09c2c9f081b45b7a821a3aa1a4d

refs/heads/main

Apache-2.0

Python

from checkov.terraform.checks.data.base_check import BaseDataCheck from checkov.common.models.enums import CheckResult, CheckCategories class DummyExternalDataCheck(BaseDataCheck): def __init__(self): name = "check for terraform data entity" id = "CKV_AWS_999" supported_resources = ['aws_iam_policy_document'] categories = [CheckCategories.IAM] super().__init__(name=name, id=id, categories=categories, supported_data=supported_resources) def scan_data_conf(self, conf): return CheckResult.PASSED scanner = DummyExternalDataCheck()

UTF-8

Python

py

DummyExternalDataCheck.py

Taeheon-Lee/Programmers

fe80b9fbf0ac32c9ddb90c1eae2900cdb84bc470

9b96c37db1f61065094d42bc5c8ad6eb3925961b

/level1/phoneketmon.py

6d1df017d3d2f70bcb0d8c7792409844d7434c9a

no_license

https://github.com/Taeheon-Lee/Programmers

a97589498c866c498c1aa9192fdf8eec9f8e31f4

c38b1c7dc4114c99191b77e5d19af432eaf6177e

refs/heads/master

"폰켓몬" # 문제 링크 "https://programmers.co.kr/learn/courses/30/lessons/1845" def solution(nums): select_num = len(nums) // 2 # 선택할 수 있는 포켓몬 수 types_num = len(set(nums)) # 포켓몬 종류 수 answer = types_num if types_num < select_num else select_num # 종류 수가 선택 수 보다 적을 경우, 최대 선택 가능 종류는 종류 수와 동일하며, 클 경우 선택 수 만큼 종류 수 획득 가능 return answer

UTF-8

Python

py

phoneketmon.py

PuHaoran/jdata

c91752a90a325707a56906543e44380553f1e432

9e908f9ae9aebbc6242706249b9ed65c87d1a6c8

/src/data/concat_action_files.py

8bb21811173e9f62e572bf9bce2074d6c344e2a1

permissive

https://github.com/PuHaoran/jdata

fda13c92b65fc75e7795c64c6988ff91fd40e288

bb8839d7f7a4a10f3ebcdd8f4d1ce2fa29562868

refs/heads/master

""" Concat JData Action Files And Save """ import pandas as pd from .. import DATA_DIR def main(input_dir=DATA_DIR.joinpath("raw"), output_dir=DATA_DIR.joinpath("interim")): file_list = list(input_dir.glob("JData_Action*.csv")) df_list = [pd.read_csv(p) for p in file_list] actions = pd.concat(df_list) actions.to_csv("{}/All_Action.csv".format(output_dir), index=False) if __name__ == "__main__": main()

UTF-8

Python

py

concat_action_files.py

julianfloores/AprendiendoPython

46f89d0e759d1a80bfea3aa9e941f251fd5bcd84

8c810aeb40c76e081982fde262e41133440f5b6f

/Tabla.py

54dc04d672d7f36b3d6ea883d5665f9eaab54a9e

no_license

https://github.com/julianfloores/AprendiendoPython

7e0635c79ab8eb3d506ef1103c5705a6cd32710b

4dad650cfde4ab29c8efce9adf7bfc022704f4fd

refs/heads/master

n=input("Dame un numero del 1 al 9: ") n:int(n) for i in range (1,11): salida="{} X {} = {}" print(salida.format(n,i, i*n)) #Nombre: Francisco Julian Flores Hernandez #Matricula: 1678204

UTF-8

Python

py

Tabla.py

greseam/module5_python_practice_SMG

20bdcb605ff642ee1d18206ac24f6ff550165eeb

b769a3992c2bf0b50f8f5860b5a41def32d4764e

/Module 5/mod5_hw1_task4_SMG.py

af51dff2df501bfefe8acb03726ee10f75075083

no_license

https://github.com/greseam/module5_python_practice_SMG

540178db60af02bfeeb2e61d56e7c707b6fe0541

f13e5422866a07e4a9ba06d0599ce6f0dfedbea3

refs/heads/main

###### #every third word begin # # Sean Gregor # #desc: takes a string and only prints every thrid word ###### def SpaceBegone(): userString = input("Enter in a sentence at least 3 words long: ").split(" ") userEndString = len(userString) for i in range (2, userEndString, 3):#the range is set to grab the third word starting at position 2 in the list and then every three words decode = userString[i] print(decode, end=" ") if __name__ == "__main__": SpaceBegone()

UTF-8

Python

py

mod5_hw1_task4_SMG.py

AhmedSeemal/Eclipsegirls

c339fce952354ca96be2236548e0c76bc8d28d48

e4c97366f620cf4419b2cee370a6a594af90faf8

/djangogirls/urls.py

096b23849f3d2158ffa75499bf47b7be344f1a16

no_license

https://github.com/AhmedSeemal/Eclipsegirls

476115293298b6d555af15f54d00161f89008f4b

1ab03fffb0721804a5ca27e93716d5b775a76eef

refs/heads/master

"""djangogirls URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/1.11/topics/http/urls/ Examples: Function views 1. Add an import: from my_app import views 2. Add a URL to urlpatterns: url(r'^$', views.home, name='home') Class-based views 1. Add an import: from other_app.views import Home 2. Add a URL to urlpatterns: url(r'^$', Home.as_view(), name='home') Including another URLconf 1. Import the include() function: from django.conf.urls import url, include 2. Add a URL to urlpatterns: url(r'^blog/', include('blog.urls')) """ from django.conf.urls import include,url from django.contrib import admin from django.conf import settings from django.conf.urls.static import static urlpatterns = [ url(r'^admin/', admin.site.urls), url(r'', include('blog.urls')), url(r'^dismantle/', include('dismantle.urls')), url(r'^poll/', include('poll.urls')), url(r'^home/', include('newapp.urls')), url(r'^homes/', include('dum.urls')), ] if settings.DEBUG: urlpatterns += static(settings.STATIC_URL, document_root=settings.STATIC_ROOT) urlpatterns += static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT)

UTF-8

Python

py

urls.py

devonproudfoot/vandura

6d15a9f5a758500ad9a4ab7c20e4797a305a7c48

edcce4c7febeba37a91a249a69828f085b84015f

/archivesspace_defaults.py

1fa4fe54cfed4a30d699bc2bcea2fce26cf541a7

no_license

https://github.com/devonproudfoot/vandura

40748819948d5ca526c4d7ed79e9473c0513e865

d1182f8c442510bf7185567707f59d234bdcf42c

refs/heads/master

from vandura.shared.scripts.archivesspace_authenticate import authenticate from vandura.config import aspace_credentials import requests import time import json import getpass from pprint import pprint def make_note_multipart(note_type, note_content): note_multipart = {"type":note_type, "jsonmodel_type":"note_multipart", "publish":True, "subnotes":[{ "content":note_content, "jsonmodel_type":"note_text", "publish":True }]} return note_multipart def resource_template(): resource_template = { "record_type":"resource", "defaults":{ "title":"[Enter a title]", "publish":True, "suppressed":False, "level":"collection", "language":"eng", "finding_aid_title":"Finding aid for the [collection title]", "notes":[ make_note_multipart("accessrestrict","This collection is open for research"), make_note_multipart("bioghist", "Enter a biographical note"), make_note_multipart("accruals", "REMOVE ONE:\r\nNo accruals expected\r\nAccruals expected"), make_note_multipart("prefercite","[item],[box],[folder],[collection], etc.")] } } return json.dumps(resource_template) def add_enum_values(session, aspace_url, enum_set_id, new_values_to_add): enum_address = aspace_url + '/config/enumerations/{}'.format(enum_set_id) existing_enums_json = session.get(enum_address).json() unique_values = [value for value in new_values_to_add if value not in existing_enums_json["values"]] existing_enums_json["values"].extend(unique_values) print(session.post(enum_address, data=json.dumps(existing_enums_json)).json()) def post_defaults(aspace_url, username, password): s = authenticate(aspace_url, username, password) s.headers.update({"Content-type":"application/json"}) bhl_repo = { 'name':'Bentley Historical Library', 'org_code':'MiU-H', 'repo_code':'BHL', 'parent_institution_name':'University of Michigan' } post_repo = s.post(aspace_url + '/repositories',data=json.dumps(bhl_repo)).json() print post_repo mhc_classification = {'title':'Michigan Historical Collections','identifier':'MHC'} uarp_classification = {'title':'University Archives','identifier':'UA'} faculty_classification = {'title':'Faculty Papers', 'identifier':'Faculty'} rcs_classification = {'title':'Records Center Storage','identifier':'RCS'} for classification in [mhc_classification, uarp_classification, faculty_classification, rcs_classification]: classification_post = s.post(aspace_url + '/repositories/2/classifications',data=json.dumps(classification)).json() print classification_post add_enum_values(s, aspace_url, 23, ['lcnaf', 'lctgm', 'aacr2', 'lcgft', 'ftamc', 'fast']) # subject sources add_enum_values(s, aspace_url, 4, ['lcnaf']) # name sources add_enum_values(s, aspace_url, 55, ["on file", "pending", "sent", "n/a", "other"]) # user defined enum 1 values (gift agreement status) add_enum_values(s, aspace_url, 14, ["TB"]) # extent instance_types = s.get("{}/config/enumerations/22".format(aspace_url)).json() for value in instance_types["enumeration_values"]: value_uri = value["uri"] s.post("{0}{1}/suppressed?suppressed=true".format(aspace_url, value_uri)).json() repo_preferences = { 'repository':{'ref':'/repositories/2'}, 'defaults':{'publish':True, 'default_values':True} } repo_preferences_post = s.post(aspace_url + '/repositories/2/preferences',data=json.dumps(repo_preferences)).json() print repo_preferences_post resource_template_post = s.post("{}/repositories/2/default_values/resource".format(aspace_url), data=resource_template()).json() print resource_template_post s.post("{}/logout".format(aspace_url)) def main(): aspace_url, username, password = aspace_credentials() post_defaults(aspace_url, username, password) if __name__ == "__main__": main()

UTF-8

Python

py

archivesspace_defaults.py

vvspearlvvs/CodingTest

5b98146395ad29c6511925bbc47a3402f1251fa2

1e168ced1a4bdb53967021e082b98027aea9d38a

/1.알고리즘정리/정렬/삽입정렬.py

6e0f94afc79ed7d33b51a468d14c6182e85e3d68

no_license

https://github.com/vvspearlvvs/CodingTest

3ebf921308570ac11eb87e6660048ccfcaf90ce4

fc61b71d955f73ef8710f792d008bc671614ef7a

refs/heads/main

#삽입정렬 arr = [7, 5, 9, 0, 3, 1, 6, 2, 4, 8] for i in range(len(arr)): for j in range(i,0,-1): if arr[j]<arr[j-1]: #한칸씩 왼쪽으로 이동 arr[j],arr[j-1]=arr[j-1],arr[j] else: break print(arr) print("최종") print(arr)

UTF-8

Python

py

삽입정렬.py

JoannaPia/Just-ask-

e0011be665b61506fe425bd8d07c4308884569e7

e6a8470a3bf4e9c770aa2810ca3353a5a106ea62

/questions_data.py

faae7bc8d959e44e660ecc7052fe8d0f8f6c188d

no_license

https://github.com/JoannaPia/Just-ask-

6613ef3b1d344925104de15b8f99aa8ea50f71a5

20781a043a8d2a95526262bf32e028e6ecd0a752

refs/heads/main

from psycopg2.extras import RealDictCursor, DictCursor import database_common @database_common.connection_handler def get_all_questions(cursor: RealDictCursor) -> dict: query = """ SELECT id, submission_time, view_number, vote_number, title FROM question ORDER BY submission_time DESC """ cursor.execute(query) questions = cursor.fetchall() return questions @database_common.connection_handler def add_question(cursor: RealDictCursor, sub, view_n, vote_n, title, mess, image, email): query_max_id = """ SELECT MAX(id) FROM question """ cursor.execute(query_max_id) new_id = cursor.fetchone() nid = new_id['max'] query = "INSERT INTO question " \ "VALUES ({},'{}',{},{},'{}','{}','{}','{}')".format(nid+1, sub, view_n, vote_n, title, mess, image, email) cursor.execute(query) return nid+1 @database_common.connection_handler def get_question(cursor: RealDictCursor, question_id: int): query = """ SELECT * From question WHERE id=%(question_id)s """ param = {'question_id': str(question_id)} cursor.execute(query, param) return cursor.fetchone() @database_common.connection_handler def get_question_id(cursor: RealDictCursor, question_id): query = """ SELECT id From question WHERE id = %(question_id)s; """ param = {'question_id': question_id} cursor.execute(query, param) result = cursor.fetchone() print(result) return result['id'] @database_common.connection_handler def save_edit_question(cursor: RealDictCursor, question_id, message, title): command = """ UPDATE question SET message = (%(message)s), title = (%(title)s) WHERE id=%(question_id)s """ param = { 'message': str(message), 'title': str(title), 'question_id': str(question_id) } cursor.execute(command, param) return None @database_common.connection_handler def vote_up_question(cursor: RealDictCursor, item_id): query = """ UPDATE question SET vote_number = vote_number + 1 WHERE id=%(id)s """ param = {'id': item_id} cursor.execute(query, param) return None @database_common.connection_handler def vote_down_question(cursor: RealDictCursor, item_id): query = """ UPDATE question SET vote_number = vote_number - 1 WHERE id=%(id)s """ param = {'id': item_id} cursor.execute(query, param) return None @database_common.connection_handler def delete_question(cursor: RealDictCursor, question_id): command1 = """ DELETE FROM comment WHERE question_id=%(id)s """ command2 = """ DELETE FROM comment_q WHERE question_id=%(id)s """ command3 = """ DELETE FROM answer WHERE question_id=%(id)s """ command4 = """ DELETE FROM question WHERE id=%(id)s """ param = {"id": str(question_id)} cursor.execute(command1, param) cursor.execute(command2, param) cursor.execute(command3, param) cursor.execute(command4, param) return None @database_common.connection_handler def get_five_questions(cursor: RealDictCursor) -> dict: query = """ SELECT id, submission_time, view_number, vote_number, title FROM question ORDER by submission_time DESC LIMIT 5 """ cursor.execute(query) questions = cursor.fetchall() return questions @database_common.connection_handler def get_user_from_question(cursor: RealDictCursor, question_id): query = """ SELECT user_id From question WHERE id = %(question_id)s; """ param = {'question_id': question_id} cursor.execute(query, param) result = cursor.fetchone() print(result) return result['user_id']

UTF-8

Python

py

questions_data.py

nasutionam/Things_In_Python

94c4347e2a33fdeb878ad1361660dd349d1be685

5d37baf1f73fa7ac406afa079c31e5603b3771ad

/wa.py

a19428a269a281b377bc818c0dc5eac3c8ff5999

no_license

https://github.com/nasutionam/Things_In_Python

4ee87bf6af55260892596194f2d27acc4bcb6406

ae01ce6cb42b7cccd737e1186897c4705c5353de

refs/heads/master

import pywhatkit pywhatkit.sendwhatmsg("+6283","test",00,36)

UTF-8

Python

py

wa.py

arcadigonzalez-uoc/M2.951-Practica2

db1934d57515d58af5c9b591d082cbc9ea85d3c9

546eda2426325e42afad5fddb3872b0eda4346c4

/normalize/etl.py

982e7c98875c5e8ec1bd99f56ff905ea9da7fe9c

permissive

https://github.com/arcadigonzalez-uoc/M2.951-Practica2

95ad5d1ba3154ba22dff858633d60e5756b56d59

6993251cb257c87377660ada0fad352ed05b9170

refs/heads/master

from normalize.connection import cursor, client from normalize.custom_sites import monster, indeed, reed i = 0 for item in cursor: if i % 100 == 0: print(i) i += 1 if 'Spider' in item: try: if item['Spider'] == 'Monster': dct = monster.Monster(item['Body'], item['Url']).to_dict() elif item['Spider'] == 'Indeed': dct = indeed.Indeed(item['Body'], item['Url']).to_dict() elif item['Spider'] == 'Reed': dct = reed.Reed(item['Body'], item['Url']).to_dict() else: dct = None except: dct = None if dct: client.jobCrawl.cleanJobs.insert_one(dct)

UTF-8

Python

py

etl.py

Angeliz/text-index

7e66cc29871fd1f4e44c199f65581c772d108fee

92687a5b70d771139ab79b91989b99d5ef666a45

/corpus_to_bunch.py

62dd12d7ad7fba0999ee7d439973f15b9da43e35

no_license

https://github.com/Angeliz/text-index

8a1227a5779ca3edf10824c696c1d99494cb23b8

cce1685669601ea40f0f723e6be638fb5c14485e

refs/heads/master

# encoding=utf-8 import pickle from sklearn.datasets import base from utils import read_file, listdir_nohidden from config_local import seg_path, bunch_path, experiment_seg_path, experiment_bunch_path def corpus_to_bunch(bunch_path, seg_path): ''' :param bunch_path: Bunch存储路径 :param seg_path: 分词后语料库路径 ''' seg_class_list = listdir_nohidden(seg_path) bunch = base.Bunch(target_name=[], label=[], filenames=[], contents=[]) bunch.target_name.extend(seg_class_list) for seg_class_dir in bunch.target_name: seg_class_path = seg_path + "/" + seg_class_dir + "/" seg_file_list = listdir_nohidden(seg_class_path) for seg_file in seg_file_list: seg_full_path = seg_class_path + seg_file bunch.label.append(seg_class_dir) bunch.filenames.append(seg_file) bunch.contents.append(read_file(seg_full_path)) with open(bunch_path, "wb") as file_obj: pickle.dump(bunch, file_obj) print("===================*****====================") print("corpus_to_bunch end") print("===================*****====================") def experiment_corpus_to_bunch(bunch_path, seg_path): ''' :param bunch_path: Bunch存储路径 :param seg_path: 分词后语料库路径 ''' bunch = base.Bunch(target_name=[], label=[], filenames=[], contents=[]) seg_file_list = listdir_nohidden(seg_path) for seg_file in seg_file_list: seg_full_path = seg_path + "/" + seg_file bunch.filenames.append(seg_file) bunch.contents.append(read_file(seg_full_path)) with open(bunch_path, "wb") as file_obj: pickle.dump(bunch, file_obj) print("===================*****====================") print("experiment_corpus_to_bunch end") print("===================*****====================") if __name__ == "__main__": corpus_to_bunch(bunch_path, seg_path) experiment_corpus_to_bunch(experiment_bunch_path, experiment_seg_path)

UTF-8

Python

py

corpus_to_bunch.py

mrfrozen97/frozenSpider-A-library-for-complete-machine-learning-algorithms-implementation-

c3518f49b65b154dea865bd85dd55a7e7c132018

e8d00a3cec4ab65edc3bb7ba0902d162b1637f44

/frozenSpider/spiderAlgorithmLR.py

db511f0638aa47e5c5697aabcbd2ad172c973fb0

permissive

https://github.com/mrfrozen97/frozenSpider-A-library-for-complete-machine-learning-algorithms-implementation-

ce2513db523066794d339cacccae31e6cfb5ff41

1d1fee8c4553f7d0c4c5339cef624e02eeb40650

refs/heads/main

""" Implementation of ML introductory algorithms visulisation as ancillary Author - mr frozen (or just frozen) Github - github.com/mrfrozen97 Mail - mrfrozenpeak@gmail.com This file has class that performs linear regression algorithm to the input data and can also visualise it . The packages used here are numpy(for efficient calculations) and matplotlib(for data visualisation) Classes: Linear Regression- It carries out regression model plot model- It carries out data visualisation Equation of best fit line y = bx + a In linear regression we want to minimise the squared error which is ( y(best_fit) - y(original) )^2 y(o) -> y coordinate of original line x(o) -> x coordinate of original line y(b) -> y coordinate of best fit line x(b) -> x coordinate of best fit line x(mean) -> mean of all x(o) values y(mean) -> mean of all y(o) values #Mathematics......................................................................................................................... Let F = ∑ (y(b) - y(o))^2 F = ∑ (y(0) - y(b))^2 We also know that y(b) = b*x(b) + a So, F = ∑ (y(o) - b*x(b) - a)^2 Minimising error..... a and b are our unkowns and so to find them we partially differentiate them w.r.t. F ∂F/∂a = 0 -(1) ∂F/∂b = 0 -(2) Let y(b) - y(o) = u ∂F/∂a = ∂F/∂u * ∂u/∂a -(3) ∂F/∂b = ∂F/∂u * ∂u/∂b -(4) F = u^2 ∂F/∂u = 2u u = ∑y(o) - ∑(bx(b) - a) ∂u/∂a = -1 From 3 and 1, 0 = -2*u 0 = -2*(∑y(o) -∑(bx(b) - a)) na = (∑y(o) -∑(bx(b)) a = (y(mean) - b*x(mean)) -(5) Now, ∂u/∂a = -∑x(b) From 4 and 1, 0 = -2*u*∑x(b) 0 = (∑y(o)∑x(b) -∑(bx(b) - a)*∑x(b) ) ∑x(b)*na = ∑y(o)∑x(b) -∑bx(b) From 5 ∑x(b)*n(y(mean) - bx(mean)) = ∑y(o)∑x(b) -∑bx(b) Solving this b = ∑(y(o)x(a))(mean) - (y(mean)*x(mean)) / ∑x(o)*x(mean) - x(mean)**2 ###############.....IMP a = y(mean) - b*x(mean) ###############.....IMP squared mean error is defined as SME = 1 - ( ∑(y(o)-y(mean))^2 / ∑(y(o)-y(b))^2 ) ###############.....IMP #End of math. Maybe, Never skip maths................................................................ Attributes: ............................ ____________________________ b -> indicates slope of best fit line a -> indicates x intercept of the best fit line x -> input x coordinates y -> input y coordinates x_mean -> mean of x values y_mean -> mean of y values squared_mean_error -> squared error to check accuracy showGrid -> Boolean which indicates weather grid should be shown or not sizeX -> Horizontal size of graph in inches sizeY -> Vertical size of graph in inches labelx_count -> number of labels on x axis labely_count -> number of labels on y axis title_color -> color of title of plot label_default -> Boolean which tells if the label is default or changed by user xlabel_color -> color of x label ylabel_color -> color of y label title -> title text x_label -> x label text y_label -> y label text xlabel_size -> x_label font size of text ylabel_size -> y_label font size of text title_size -> title font size of text model -> this is the model obeject i.e. linear regression object in case we need any parent class variables unknown_points_size-> this specifies the size of unknown points if any on the graph unknown_points_color-> this specifies the color of unknown points if any on the graph unknown_points_apl]ha-> this specifies the transparency of unknown points if any on the graph #####.....IMP.......#### color_dict -> Dictionary that contains wide range of colors in the form of dictionary. The keys are the names of colors , values are the hex codes of that color. You can get this dict using get_color_dict function() You can print this dict i.e. print(object.get_color_dict()) to know which colors are available. You are most welcomed to improve this code: You can pull request for this code at github.com/mrfrozen97/ (In spider algorithms repo) or Email - mrfrozenpeak@gmail.com """ import numpy as np import matplotlib.pyplot as plt import math from frozenSpider import spiderAlgorithmResources as res """ Class that performs linear regression It takes in the x and y coordinates of the data It then calculates the value of b and a using numpy array functions It returns values of a and b It also returns values of squared mean error in squared_error function """ class Linear_regression: def __init__(self): self.a = 0.0 self.b = 0.0 self.squared_mean_error = 0.0 self.x_mean = 0 self.y_mean = 0 self.size = 1 self.x = [] self.y = [] self.calculated_y = [] self.calculated_x = [] #Function to calcute and return a, b values.................................... def bestFit(self, x_coordinates, y_coordinates): size_coordinates = np.size(x_coordinates) x_coordinates_mean = np.sum(x_coordinates)/size_coordinates y_coordinates_mean = np.sum(y_coordinates)/size_coordinates self.x = x_coordinates self.y = y_coordinates self.size = size_coordinates self.x_mean = x_coordinates_mean self.y_mean = y_coordinates_mean bestFint_numerator = (np.sum(np.multiply(x_coordinates, y_coordinates))/size_coordinates) - (x_coordinates_mean*y_coordinates_mean) bestFint_denominator = (np.sum(np.multiply(x_coordinates,x_coordinates))/size_coordinates) - (x_coordinates_mean**2) self.b = bestFint_numerator/bestFint_denominator self.a = y_coordinates_mean - (self.b*x_coordinates_mean) return self.a, self.b def bestFit_logrithemic(self, x_coordinates, y_coordinates, base=math.e): y_coordinates = [math.log(x, base) for x in x_coordinates] size_coordinates = np.size(x_coordinates) x_coordinates_mean = np.sum(x_coordinates)/size_coordinates y_coordinates_mean = np.sum(y_coordinates)/size_coordinates self.x = x_coordinates self.y = y_coordinates self.size = size_coordinates self.x_mean = x_coordinates_mean self.y_mean = y_coordinates_mean bestFint_numerator = (np.sum(np.multiply(x_coordinates, y_coordinates))/size_coordinates) - (x_coordinates_mean*y_coordinates_mean) bestFint_denominator = (np.sum(np.multiply(x_coordinates,x_coordinates))/size_coordinates) - (x_coordinates_mean**2) self.b = bestFint_numerator/bestFint_denominator self.a = y_coordinates_mean - (self.b*x_coordinates_mean) return self.a, self.b #function that calculates and returns squarred error which can be attributed to the accuracy og our best fit line............ def squared_error(self): mean_y_array = [self.y_mean for x in range(self.size)] bestFit_y = [(self.b*x + self.a) for x in self.x] # print(mean_y_array) # print(bestFit_y) squared_error_denominator = np.sum(np.square(np.subtract(bestFit_y, mean_y_array))) squared_error_numerator = np.sum(np.square(np.subtract(bestFit_y, self.y))) self.squared_mean_error = 1 - (squared_error_numerator/squared_error_denominator) return self.squared_mean_error def find_unknowns(self, x): x = list(x) self.calculated_x = x for i in x: self.calculated_y.append(self.b * i + self.a) return self.calculated_y """ This is child class of the linear regression model class It basically plots the result obtained by performing linear regression vs the original data The parameters such as title, x/y labels , their colors, their size, plot colors, x/y label values, grid, etc can be set There are function to set these values as well as to set the size of graph, to save it, etc. All the default values of the above variables are already set so you can directly plot entire graph with just one line of code...... """ class plot_model(Linear_regression): #All the default value are already set but they can all be reset......................... def __init__(self, model): self.showGrid = True self.sizeX = 10 self.labelx_count = 10 self.labely_count = 10 self.title_color = "#FF0000" self.xlabel_color = "#663399" self.ylabel_color = "#663399" self.label_default = True self.sizeY = 6 self.title = "" self.x_label = "" self.y_label = "" self.xlabel_size = 15 self.ylabel_size = 15 self.title_size = 18 self.model = model self.color_dict = res.Resources.get_color_dict() self.unknown_points_size = 20 self.unknown_points_color = "Orange" self.unknown_points_alpha = 0.8 #Function to get dictionary to access the different options avaliable for the colors......................... def get_color_dict(self): return self.color_dict #function to set vlues for title, x/y label and values of labels in case......................... def set_marker_properties(self,unknown_points_alpha=0.8, unknown_points_color = "Orange", unknown_points_size = 20, xlabel_count=17, label_default=True, ylabel_count=12, title_size=15, xlabel_size=10, ylabel_size=10, title="Linear Regression", x_label="x coordinates", y_label="y coordinates", title_color="#FF0000", xlabel_color="#663399", ylabel_color="#663399"): self.title_size = title_size self.xlabel_size = xlabel_size self.ylabel_size = ylabel_size self.x_label = x_label self.y_label = y_label self.title = title self.xlabel_color = xlabel_color self.ylabel_color = ylabel_color self.title_color = title_color self.labelx_count =xlabel_count self.labely_count =ylabel_count self.label_default = label_default self.unknown_points_size = unknown_points_size self.unknown_points_color = unknown_points_color self.unknown_points_alpha = unknown_points_alpha #Sets the display size which will be equal to size of image if it is being svaed......................... def set_display_size(self, sizeX, sizeY): self.sizeX = sizeX self.sizeY = sizeY #function to create x,y values according to the best fit line equation................................ def create_best_fit_line(self): y_coords_line = [] x_coords_line = list(self.model.x) for i in self.model.x: y_coords_line.append(self.model.b*i + self.model.a) #print(self.model.calculated_x) for i in self.model.calculated_x: x_coords_line.append(i) y_coords_line.append(self.model.b*i + self.model.a) #print(len(self.model.x) - len(self.model.y)) return x_coords_line, y_coords_line #This function creates f\default ticks for x and y axis .... def generate_ticks(self, label_x, label_y): if self.label_default or len(label_x)==0 or len(label_y)==0: min_y = min(self.model.y) min_x = min(self.model.x) max_y = max(max(self.model.y), max(self.model.calculated_y)) max_y += int(max_y*0.3) max_x = max(max(self.model.x), max(self.model.calculated_x)) max_x += int(max_x * 0.2) # dif_y = max(1, int(len(self.model.y)/self.labely_count)) dif_y = max(1, int((max_y-min_y) / self.labely_count)) #dif_x = max(1, int(len(self.model.x)/self.labelx_count)) dif_x = max(1, int((max_x-min_x) / self.labelx_count)) print(dif_x, dif_y) x_labels_default = [] y_labels_default = [] while min_x<=max_x: x_labels_default.append(min_x) min_x+=dif_x while min_y<max_y: y_labels_default.append(min_y) min_y += dif_y # print(x_labels_default) # print(y_labels_default) plt.xticks(x_labels_default) plt.yticks(y_labels_default) else: plt.xticks(label_x) plt.yticks(label_y) #main fuction thats plots the graph and saved it if path provided......................... def plot_model(self,label="Points",alpha=0.6, point_size=25,label_x=[], label_y=[],line_color='Purple',unknown_points_label="Unknown points",line_label='Best Fit line', point_color='DeepSkyBlue', save_fig_path='dont'): #These are the coordinates to plot the line which is inclusion of both known and calculated points x_bestFitLine_coords, y_bestFitLine_coords = self.create_best_fit_line() plt.plot(x_bestFitLine_coords, y_bestFitLine_coords, color=self.color_dict[line_color], label=line_label) #plot the best fit line plt.scatter(self.model.x, self.model.y, zorder=3, label=label, s=point_size, color=self.color_dict[point_color], alpha=alpha) #plot all the points plt.scatter(self.model.calculated_x, self.model.calculated_y, color=self.color_dict[self.unknown_points_color], label=unknown_points_label, zorder = 4, alpha=self.unknown_points_alpha, s=self.unknown_points_size) plt.title(self.title, fontdict=res.Resources.title_dict, color=self.title_color) plt.xlabel(self.x_label, fontdict=res.Resources.label_dict, color=self.xlabel_color) plt.ylabel(self.y_label, fontdict=res.Resources.label_dict, color=self.ylabel_color) self.generate_ticks(label_x, label_y) plt.legend(loc = 'upper left') if self.showGrid: plt.grid(color='#cfd8dc', zorder=0) figure = plt.gcf() figure.set_size_inches(self.sizeX, self.sizeY) if not(save_fig_path=='dont') : plt.savefig("./" + save_fig_path)#, bbox_inches='tight') plt.show() #Sample code to work with this file of the library """ x = [-22, 17, 22, 28, 35] y = [-9.3, 5, 8, 12, 14] x1 = [13, 47] le1 = linear_regression() a,b =le1.bestFit(x, y) le1.find_unknowns(x1) print("Slope = " + str(b)) print("x intercept = " + str(a)) print("Squared error = "+ str(le1.squared_error())) plot2 = plot_model(le1) plot2.set_marker_properties(unknown_points_size=80, unknown_points_alpha=0.6, unknown_points_color='Red') plot2.plot_model(save_fig_path="plot2") """

UTF-8

Python

py

spiderAlgorithmLR.py

dyingg/rk311_infowise-pub-

2587a225e6cabb5f66558b5823b873d1ffc9f560

e3c6c3e035430c8523aefbdb6f295444951b395c

/src/main/scraper-module/AI_retrain.py

733795f7297c901e9f4e6bf722ba0785469241c0

no_license

https://github.com/dyingg/rk311_infowise-pub-

acbae670f04727dfd35c40dbb40f241ac62b418b

48a43c9a75dc7bc191abb602b2ba92e1cac6787a

refs/heads/master

import keras from keras.models import Sequential from keras.layers import Dense import pandas as pd from sklearn.model_selection import train_test_split from sklearn.preprocessing import MinMaxScaler import pickle, os import numpy as np from Naked.toolshed.shell import muterun_js import sys import requests, random import tensorflow as tf os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' def save_model(filename, model): pickle.dump(model, open(filename, 'wb')) def load_model(filename): return pickle.load(open(filename, 'rb')) def get_score(ip): url = "https://ipqualityscore.com/api/json/ip/F5FEG8NGn0stGDfizWPf7ylxu3iNqnX4/" + ip response = requests.get(url).json() # print(response) return response['fraud_score'] def get_inputs(path, file_name, ip): os.chdir(path) file = os.path.join(path, file_name) x = file_name + ' ' + ip output = muterun_js(x) s = output.stdout s = str(s).strip()[2:-3] print(s) return s def retrain(ip_list): model_folder = "../ai-server/models" model_names = os.listdir(model_folder) models = [] for m in model_names: model_path = os.path.join(model_folder, m) model = load_model(model_path) models.append(model) curr_dir = os.getcwd() os.chdir(curr_dir) inp_folder = "../whois" file_name = "getInspectorScores.js" x_train, y_train = [], [] random.shuffle(ip_list) for ip in ip_list[:3]: inputs = get_inputs(inp_folder, file_name, ip).split() x = list(map(float, inputs)) # print(x) try: y = int(get_score(ip)) except: continue y = np.array(y) x_train.append(x) y_train.append(y) x_train, y_train = np.array(x_train), np.array(y_train) # print(x_train.shape, y_train.shape) for model in models: model.fit(x_train, y_train, batch_size=10, nb_epoch=30) print("Model Trained!")

UTF-8

Python

py

AI_retrain.py

linklab/aiclass

9eff9999ccecd071b291daddd8d38503b3aaf958

bfdc632d1921c5a2f0877e44f1394f67d4ef6d7a

/1731095004_SiHoRyu/HW2/functions.py

fffb6e342a6db23b90dd52e366efa5b694a7ce99

no_license

https://github.com/linklab/aiclass

8f638d5ff0d76ba5cc631c93c2b55ed06e2456e5

4655fceee6ff301f47e954d56b1dbacb3ccae8ac

refs/heads/master

Jupyter Notebook

import numpy as np import math import matplotlib.pyplot as plt from scipy.stats import truncnorm from numba import jit, float64, uint8, void, cuda def get_truncated_normal(shape, mean=0, sd=1, low=0, upp=10): x = truncnorm(a=(low - mean) / sd, b=(upp - mean) / sd, loc=mean, scale=sd) num_elements = 1 for dim in shape: num_elements *= dim x = x.rvs(num_elements) x = x.reshape(shape) return x def sigmoid(x, is_numba): if is_numba: return _sigmoid(x) else: return 1 / (1 + np.exp(-x)) @jit(nopython=True) def _sigmoid(x): return 1 / (1 + np.exp(-x)) def squared_error(output_value, target_value, is_numba): if is_numba: return _squared_error(output_value, target_value) else: return 0.5 * np.power(output_value - target_value, 2.0) @jit(nopython=True) def _squared_error(output_value, target_value): return 0.5 * np.power(output_value - target_value, 2.0) def softmax(x, is_numba): if is_numba: return _softmax(x) else: if x.ndim == 2: x = x.T x = x - x.max() y = np.exp(x) / np.sum(np.exp(x), axis=0) return y.T x = x - x.max() return np.exp(x) / np.sum(np.exp(x)) @jit(nopython=True) def _softmax(x): if x.ndim == 2: x = x.T x = x - x.max() y = np.exp(x) / np.sum(np.exp(x), axis=0) return y.T x = x - x.max() return np.exp(x) / np.sum(np.exp(x)) def cross_entropy_error(y, t, is_numba): if y.ndim == 1 and t.ndim == 1: t = t.reshape(1, t.size) y = y.reshape(1, y.size) y[y == 0] = 1e-15 batch_size = y.shape[0] if is_numba: return _cross_entropy_error(y, t, batch_size) else: return -np.sum(t * np.log(y)) / batch_size @jit(nopython=True) def _cross_entropy_error(y, t, batch_size): return -np.sum(t * np.log(y)) / batch_size def accuracy(forward_final_output, target): y = np.argmax(forward_final_output, axis=1) if target.ndim != 1: target = np.argmax(target, axis=1) accuracy = np.sum(y == target) / float(forward_final_output.shape[0]) return accuracy if __name__ == "__main__": # x1 = get_truncated_normal(shape=(1, 10000), mean=2, sd=1, low=1, upp=10) # x2 = get_truncated_normal(shape=(1, 10000), mean=5.5, sd=1, low=1, upp=10) # x3 = get_truncated_normal(shape=(1, 10000), mean=8, sd=1, low=1, upp=10) # # fig, ax = plt.subplots(3, sharex=True) # ax[0].hist(x1.flatten()) # ax[1].hist(x2.flatten()) # ax[2].hist(x3.flatten()) # plt.show() a = np.array([1.0, 2.0, 3.0]) print(sigmoid(a, is_numba=True)) print() b = np.array([1.0, 0.0, 1.0]) c = np.array([0.0, 1.0, 0.0]) print(squared_error(b, c, is_numba=True)) print() print(cross_entropy_error(b, c, is_numba=True)) print() d = np.array([[1.0, 2.0, 3.0], [3.0, 2.0, 1.0]]) print(softmax(d, is_numba=True)) print() q = np.array([[3.3, 1.2, 9.4], [7.1, 2.2, 3.3], [1.9, 9.2, 2.3]]) t = np.array([[0.0, 0.0, 1.0], [1.0, 0.0, 0.0], [0.0, 1.0, 0.0]]) print(accuracy(q, t, is_numba=True)) q = np.array([[3.3, 1.2, 9.4], [7.1, 2.2, 3.3], [1.9, 9.2, 2.3]]) t = np.array([[1.0, 0.0, 0.0], [1.0, 0.0, 0.0], [0.0, 1.0, 0.0]]) print(accuracy(q, t, is_numba=True))

UTF-8

Python

py

functions.py

shreyakapadia10/Bike-Rental-System

a06c4bf89ec78a02e221b11ac498ea544c5b59d3

eda5d1c94b9c8e33ba01692a0d946fc0cade0190

/BikeRentalSystem/BikeUsers/forms.py

77c846497921e3ca60bfbc13606e1a5ccfcbe91f

no_license

https://github.com/shreyakapadia10/Bike-Rental-System

9fca03be0b2465f4552b75533ed6e8ccdc16fbda

0356d5f66b4d50599633d57a7e2fc592567a5c9c

refs/heads/master

from django import forms from .models import * from django.contrib.auth.forms import UserCreationForm, UserChangeForm, AuthenticationForm, PasswordChangeForm '''User Registration Form''' class CustomerCreationForm(UserCreationForm): class Meta: model = Customer fields = ['role','first_name', 'last_name', 'username', 'contact', 'address', 'pincode', 'email', 'proof', 'state', 'city'] def __init__(self, *args, **kwargs): super(CustomerCreationForm, self).__init__(*args, **kwargs) for visible in self.visible_fields(): visible.field.widget.attrs['class'] = 'form-control' '''User Login Form''' class CustomerLoginForm(AuthenticationForm): username = forms.CharField(help_text='Enter your username', required=True) class Meta: model = Customer fields = ['username', 'password'] def __init__(self, *args, **kwargs): super(CustomerLoginForm, self).__init__(*args, **kwargs) for visible in self.visible_fields(): visible.field.widget.attrs['class'] = 'form-control' '''Customer Change Form''' class CustomerChangeForm(UserChangeForm): class Meta: model = Customer exclude = ('status', ) '''Select City Form''' class CityForm(forms.ModelForm): CHOICES = ( ("", "---------"), ) name = forms.ChoiceField(required=True, choices=CHOICES, label="City", widget=forms.Select(attrs={'class': 'form-control'})) states = State.objects.all() state = forms.ModelChoiceField(queryset=states, widget=forms.Select(attrs={'class': 'form-control'})) class Meta: model = City fields = ['state', 'name'] '''Customer Change Form''' class CustomerUpdateForm(UserChangeForm): class Meta: model = Customer fields = ['first_name', 'last_name', 'username', 'contact', 'address', 'pincode', 'email', 'proof', 'state', 'city'] def __init__(self, *args, **kwargs): super(CustomerUpdateForm, self).__init__(*args, **kwargs) for visible in self.visible_fields(): visible.field.widget.attrs['class'] = 'form-control' class PasswordUpdateForm(PasswordChangeForm): class Meta: model = Customer def __init__(self, user, *args, **kwargs): super(PasswordUpdateForm, self).__init__(user, *args, **kwargs) for visible in self.visible_fields(): visible.field.widget.attrs['class'] = 'form-control'

UTF-8

Python

py

forms.py

StarStudio/StarSSO

9077e15d13464861059ddcb8de6d57d1ebce2e56

7decdbc9b7bab2d0b4d571a8f658d9beebaa619d

/StarMember/lan_agent/submit.py

e88587e907ed10189adc2bc48a5cb2aa5b99d1f0

no_license

https://github.com/StarStudio/StarSSO

3a299630e7fc5d6a2e7957adece8b6796c192cd2

4402e890eaf02e57b57ad04596490e0e8759a814

refs/heads/master

from StarMember.views import SignAPIView, param_error, api_succeed from StarMember.aspect import post_data_type_checker, post_data_key_checker from StarMember.utils import get_request_params from flask import request, current_app from .network import Network, InvalidNetworkIDError class LANDeviceSubmit(SignAPIView): method = ['POST'] def post(self, nid): params = get_request_params() print(params) key_checker = post_data_key_checker('devices') ok, err_msg = key_checker(params) if not ok: return param_error(err_msg) devices = params['devices'] if not isinstance(devices, list): return param_error('Arg devices has wrong type.') try: net = Network(nid) net.UpdateDevices(devices) except (InvalidNetworkIDError, ValueError) as e: return param_error(str(e)) return api_succeed()

UTF-8

Python

py

submit.py

WoolinChoi/WoolinChoi.github.io

9d8c879f5cb737da5096a0417feb2e9f05fff023

a9590fdcf3ed0b3776e7d0edf5be9d13bbace255

/_posts/jupyter/cWebConn/3_beautifulsoup_class/Ex01_element.py

1029f9e5f0144e1cb99ce818e6c739b516febca9

permissive

https://github.com/WoolinChoi/WoolinChoi.github.io

59aa4ea685dd38f2588fcac662bb44688b4c7d59

a0f9c8ecc63443acaae61d744eecec6c943d3a26

refs/heads/master

NOASSERTION

Jupyter Notebook

""" bs4 라이브러리 : 웹에서 가져온 HTML코드를 파이썬에서 사용하기 편하게 해주는 라이브러리 [참고] 웹에서 가져온 HTML코드 가져오는 방법 - requests 모듈 - urllib 의 request 모듈 BeautifulSoup 모듈 - find() - find_all() [참고] 파서의 종류 - lxml : c로 만들어져 속도 빠름 - html5lib : 파이썬으로 만들어서 lxml보다 느림 - html.parser (*): 파이썬 버전을 확인해서 사용 """ from bs4 import BeautifulSoup html = """ <html><body> <h1>스크레이핑 연습</h1> <p>웹페이지 분석하자</p> <p>데이타 정제하기</p> </body></html> """ # 1. 데이터 파서하기 soup = BeautifulSoup(html, "html.parser") # 2. 원하는 요소 접근하기 h1 = soup.html.body.h1 print(h1) print(h1.text) # 문자열만 출력하고 싶을땐 .text, .string을 이용하여 출력 print(h1.string) # 3. p요소의 내용 추출하기 p = soup.find_all("p") print(p) for i in p: # list형식은 for문을 이용하여 출력 print(i.text)

UTF-8

Python

py

Ex01_element.py

ilyakonstantinov95/DjBlog

93264ebec8e665233eb75c2148ac066085e57ed8

e2890e6ef04220a09d150aa922376db39bb7853e

/emplist/migrations/0001_initial.py

693d522e4c0b73b7c98ebae63dbb1ccbeeb932f7

no_license

https://github.com/ilyakonstantinov95/DjBlog

da243ecbb8c49f6a2a7c42a644791f68d413942b

3ab34bed10d7a0f58d19dfee90e836daf7bf6ff7

refs/heads/master

# -*- coding: utf-8 -*- # Generated by Django 1.10.5 on 2017-01-23 10:13 from __future__ import unicode_literals from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='Employee', fields=[ ('id_emp', models.AutoField(primary_key=True, serialize=False, unique=True, verbose_name='Идентификатор')), ('first_name', models.CharField(db_index=True, max_length=25, verbose_name='Имя')), ('second_name', models.CharField(db_index=True, max_length=25, verbose_name='Фамилия')), ('third_name', models.CharField(db_index=True, max_length=25, verbose_name='Отчество')), ('birthday', models.DateField(db_index=True, verbose_name='Дата рождения')), ('date_start', models.DateField(auto_now_add=True, db_index=True, verbose_name='Дата принятия')), ('date_end', models.DateField(blank=True, null=True, verbose_name='Дата увольнения')), ], options={ 'verbose_name': 'Сотрудник', 'verbose_name_plural': 'Сотрудники', 'ordering': ['first_name', 'second_name', 'third_name', 'birthday', 'sex', 'status', 'post', '-date_start', 'date_end'], }, ), migrations.CreateModel( name='Post', fields=[ ('id_post', models.AutoField(primary_key=True, serialize=False, unique=True, verbose_name='Идентификатор')), ('name', models.CharField(db_index=True, max_length=50, unique=True, verbose_name='Должность')), ], options={ 'verbose_name': 'Должность', 'verbose_name_plural': 'Должности', 'ordering': ['name'], }, ), migrations.CreateModel( name='Sex', fields=[ ('id_sex', models.AutoField(primary_key=True, serialize=False, unique=True, verbose_name='Идентификатор')), ('type', models.CharField(db_index=True, max_length=7, verbose_name='Пол')), ], options={ 'verbose_name': 'Пол', 'verbose_name_plural': 'Пол', 'ordering': ['type'], }, ), migrations.CreateModel( name='Status', fields=[ ('id_status', models.AutoField(primary_key=True, serialize=False, unique=True, verbose_name='Идентификатор')), ('status', models.CharField(db_index=True, max_length=30, unique=True, verbose_name='Статус')), ], options={ 'verbose_name': 'Статус', 'verbose_name_plural': 'Статусы', 'ordering': ['status'], }, ), migrations.AlterUniqueTogether( name='status', unique_together=set([('id_status', 'status')]), ), migrations.AlterUniqueTogether( name='sex', unique_together=set([('id_sex', 'type')]), ), migrations.AlterUniqueTogether( name='post', unique_together=set([('id_post', 'name')]), ), migrations.AddField( model_name='employee', name='post', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to='emplist.Post', verbose_name='Должность'), ), migrations.AddField( model_name='employee', name='sex', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to='emplist.Sex', verbose_name='Пол'), ), migrations.AddField( model_name='employee', name='status', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to='emplist.Status', verbose_name='Статус'), ), migrations.AlterUniqueTogether( name='employee', unique_together=set([('first_name', 'second_name', 'third_name', 'birthday', 'sex')]), ), ]

UTF-8

Python

py

0001_initial.py

Yun-Jongwon/TIL

b3f65b69e00c8a9f6f48a8c3daa3b050ff4a4345

1346ea1f255d3586442c8fc1afc0405794206e26

/알고리즘/day15/picnic.py

a0675c0839036358fd7ba4ab78d78e7ec1e146dd

no_license

https://github.com/Yun-Jongwon/TIL

737b634b6e75723ac0043cda9c4f9acbc2a24686

a3fc624ec340643cdbf98974bf6e6144eb06a42f

refs/heads/master

def dfs(couple): global m global count if sum(visited)==len(visited): count+=1 return for V in range(n): if visited[V]==0: visited[V]=1 v=V break for w in range(n): if total_map[v][w]==1 and visited[w]==0: visited[w]=1 dfs(couple+1) visited[w]=0 visited[V]=0 T=int(input()) for t in range(T): n,m=map(int,input().split()) visited=[0]*n data=list(map(int,input().split())) total_map=[[0]*n for i in range(n)] count=0 for M in range(m): a=data[2*M] b=data[2*M+1] total_map[a][b]=1 total_map[b][a]=1 dfs(0) print(count) # print(total_map)

UTF-8

Python

py

picnic.py

RussellSk/grokking_algorithms

f57a5ab516edeb1b8dc6d04c6ffab4f028a08c66

dfa7aaaefb5ccff7fcc016ac1740d52cfbe20caf

/Chapter4/Exercise4.1.py

7749abba16a976aa7f3b90cd4796ee5356d9c9d6

no_license

https://github.com/RussellSk/grokking_algorithms

97ecd387b614b8b7f413c24467b97e2c704a1af8

88a2b9c5f21d06d1cba3526c26b68b56dc40e399

refs/heads/master

# Exercises 4.1 # Write out the code for the earlier sum function def sum(arr): if not arr: return 0 else: return arr.pop() + sum(arr) if __name__ == "__main__": print(sum([2, 4, 6]))

UTF-8

Python

py

Exercise4.1.py

tuananh1007/Picasso

2d4d18f85a1bc1ccc056b60d74d5fc204c2b33e7

2e11bf9a4499a962bacd89a742d9dc0ed7108747

/tf_ops/mesh/unpooling/tf_mesh_unpool3d.py

7b3864db5d3f04053014653a6149dabb63a57a43

no_license

https://github.com/tuananh1007/Picasso

df914332a02bf7940d28d5bae80be1601d59cb0c

5009dd2312ad88635748788696ecc953d5e55116

refs/heads/main

import tensorflow as tf import sys, os base_dir = os.path.dirname(os.path.abspath(__file__)) sys.path.append(base_dir) unpool3d_module = tf.load_op_library(os.path.join(base_dir, 'tf_unpool3d_so.so')) def mesh_interpolate(input, vt_replace, vt_map): ''' During the decimation, we record the vertex clusters in vt_map. In unpooling within decoders, we interpolate features for vertices in the before-decimation mesh from vertex features of its successive decimated mesh. Here we perform average interpolation to get feature, which means that the unpooled feature of each output vertex is 1/Nc of that from its input vertex. Nc is the related vertex cluster size in decimation. ''' return unpool3d_module.mesh_interpolate(input, vt_replace, vt_map) @tf.RegisterGradient("MeshInterpolate") def _mesh_interpolate_grad(op, grad_output): input = op.inputs[0] vt_replace = op.inputs[1] vt_map = op.inputs[2] grad_input = unpool3d_module.mesh_interpolate_grad(input, grad_output, vt_replace, vt_map) return [grad_input, None, None]

UTF-8

Python

py

tf_mesh_unpool3d.py

thiago-allue/portfolio

697ff03e063255a0200112804cf3ef495e02b7bf

baf3996414315ffb60470c40c7ad797bf4e6897f

/17_boilerplates/prototypes-master/examples/src/elastic/src/old/guide.py

aaaf2aeadce59a30109e14b385347719f1ae7efd

permissive

https://github.com/thiago-allue/portfolio

8fbbecca7ce232567aebe97c19944f444508b7f4

0acd8253dc7c5150fef9b2d46eead3db83ca42de

refs/heads/main

Python

import requests r = requests.get( "http://api.tvmaze.com/singlesearch/shows?q=big-bang-theory&embed=episodes" ) import json jd = json.loads(r.content) print(jd["_embedded"]["episodes"][0]) import re ldocs = [] for jo in jd["_embedded"]["episodes"][0:200]: d = {} d["id"] = jo["id"] d["season"] = jo["season"] d["episode"] = jo["number"] d["name"] = jo["name"] d["summary"] = re.sub("<[^<]+?>", "", jo["summary"]) ldocs.append(d) from elasticsearch import Elasticsearch es = Elasticsearch([{"host": "localhost", "port": 9200}]) import json # iterate through documents indexing them for doc in ldocs: es.index(index="tvshows", doc_type="bigbang", id=doc["id"], body=json.dumps(doc)) es.get(index="tvshows", doc_type="bigbang", id=2915) es.search( index="tvshows", doc_type="bigbang", body={"query": {"match": {"summary": "rivalry"}}}, ) es.search( index="tvshows", doc_type="bigbang", body={"query": {"fuzzy": {"summary": "rival"}}} ) es.indices.delete(index="bigbang", ignore=[400, 404])

UTF-8

Python

py

guide.py

duncandc/mb2_python

296a16ac9b6b20e78694fa5bdeab81caf614593b

8e4da43aa0a8af1167482c9cbc1ac3ff4410e95e

/groupcat.py

79b4d4cb8be334b007ce94c98765f85df446de7d

no_license

https://github.com/duncandc/mb2_python

ef8d93548926368a8d230f2d89ed2232659daae3

812f9e7c41083e66c77b9ce5d453b25e286685ea

refs/heads/master

""" File I/O related to the MBII (sub-)halo catalogs """ from __future__ import print_function, division from mb2_python.utils import packarray from mb2_python.data import subdtype, groupdtype import numpy as np __all__=['gcPath', 'shPath'] __author__=['Duncan Campbell'] def gcPath(basePath, snapNum): """ Return absolute path to a group catalog. """ gcPath = basePath + '/subhalos' gcPath += '/' + str(snapNum).zfill(3) + '/' filePath = gcPath + 'grouphalotab.raw' return filePath def shcPath(basePath, snapNum): """ Return absolute path to a subhalo catalog. """ shcPath = basePath + '/subhalos' shcPath += '/' + str(snapNum).zfill(3) + '/' filePath = shcPath + 'subhalotab.raw' return filePath def readshc(basePath, snapNum): """ Read the basic subhalo catelog. """ subhalofile = shcPath(basePath, snapNum) return np.memmap(subhalofile, mode='r', dtype=subdtype) def readgc(basePath, snapNum): """ read the basic group catelog. """ groupfile = gcPath(basePath, snapNum) return np.memmap(groupfile, mode='r', dtype=groupdtype)

UTF-8

Python

py

groupcat.py

joaogomesufal/scrapping_articles

90534afcdea2f681a4b95e128c9c47c8a6bf645b

95ce37521e81309df5faaf18bd38117db9fa8278

/main.py

f518cd1d4cc3f8a403560226b24c0f6b9e591d18

no_license

https://github.com/joaogomesufal/scrapping_articles

58bf2d2f4ccc800627063c1ab9ac9413bcc638c3

bf6715062127330c6a89a575b273dd88034dfda5

refs/heads/master