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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
dce628934a13bb8243e2323ffafa2f00f3564e81 | f318601d474d11eea375e24e8da825544ed91637 | /prefija.py | 230d46b526ca30ad83ef7086e579cf57a78e2630 | [] | no_license | josefm09/triplos | 484f1f428af3b4ad2b4a2cf90a9ee5087a0754e8 | cb5c65cb9373938dcee729e1abf3a6b64455fa03 | refs/heads/master | 2020-03-15T19:27:47.105932 | 2018-05-06T05:22:32 | 2018-05-06T05:22:32 | 132,309,212 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,222 | py | # -*- coding: utf-8 -*-
import sys
import re
#example (6+4)*8(7+4)
print('Declare una expresion')
#ex = str(input()) #se almacena la expresion
ex = '(6+4)*8(7+4)'
valid = False #se inicializa una variable en falso, luego se utilizara
pila = [] #se inicializa la pila
resultado = [] #se inicializa el arreglo de resultados
orderRes = '' #se inicializa el string del resultado ordenado
def prefija(value): #se declara la funcion prefija que lleva por parametro un valor
for i in value: #se inicia un ciclo con el tamaño de la expresion
if re.match('[a-zA-Z0-9-/?+?*?(?)]',i): #se pregunta si es una expresion correcta con expresiones regjulares
valid = True #se cambia el valor a verdadero para seguir
else: #si no termina el programa
print('ingrese una expresion valida')
sys.exit()
if valid:#si es valido continua la funcion
value = value[::-1] #se invierte el orden de la expresion
for j in value: #se inicia un ciclo para recorrer la expresion
if j in '+-*/)': #se buscan los operadores en la expresion
pila.append(j) #si se encuentran se agregan a la pila
if re.match('[a-zA-Z0-9]',j): #se buscan los numeros en la expresionm y las letras
resultado.append(j) #se agregan al resultado
if j == '(': #se busca en cierre de parentesis
while pila: #se inicia un ciclo que mientras haya elementos en la pila
resultado.append(pila.pop()) #se añadiran los elementos ultimos de la pila al resultado
for n in resultado: #se recorre el resultado para eliminar los parentesis de cierre
if n == ')':#si se encuentra
resultado.remove(n)#se elimina
prefija(ex)# se ejecuta la funcion
for n in reversed(resultado): #se recorre el resultado invertido
orderRes += n#para añadir los valores a un string
triplo(orderRes)# se ejecuta la función para imprimir los triplos
def triplo(value): #se declara la función que regresa las variables intermedias
print('Notacion infija ', ex)#se imprime la expresion original
print('Notacion prefija ',orderRes)#se imprime la expresion en prefija
| [
"josecarlosfloresmoran@hotmail.com"
] | josecarlosfloresmoran@hotmail.com |
0a1a637d989435418064ced834271773be9a47dc | 943c9b8ee8414a467c6c20cdb517b3aaeb365fbc | /old_data/code/RunTest2.py | b9cd98009207fed3cb7a1cb01f7a7360eabf27f2 | [] | no_license | Aralas/cross-reference_network | b735d9e7abf162cd36b8169c24726be25baa8ccf | 04ed853895445548ddaa5b49bec2123ec43cc4fd | refs/heads/master | 2020-04-08T12:26:03.225760 | 2019-03-08T08:20:56 | 2019-03-08T08:20:56 | 159,347,229 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 4,750 | py | # -*- coding:utf-8 -*-
"""
@author:Xu Jingyi
@file:RunTest2.py.py
@time:2018/12/2804:06
"""
import tensorflow as tf
import numpy as np
import random
import FactoryClass
dataset = 'MNIST'
model_type = 'CNN'
seed = 10
# initialization = 'xavier'
model_architecture = [[32, 5, 5], [64, 5, 5], [1500]]
noise_level = 1
augmentation = True
dropout = 0.5
learning_rate = 0.001
batch_size = 128
section_num = 20
epochs_for_binary = 5
epochs_for_multiple = 1
data_size = 1000
# first_merged_section = 5
# first_update_section = 50
# first_value_to_label_section = 10
# update_threshold = [0.8, 0.6]
def randomly_sample_binary_data(x, y, data_size, label):
indeces_positive = list(np.where(y[:, label] == 1)[0])
indeces_negative = set(range(len(y))) - set(indeces_positive)
index_train = random.sample(indeces_positive, data_size) + random.sample(indeces_negative, data_size)
x_small = x[index_train]
y_small = np.array([1] * data_size + [0] * data_size).reshape(2 * data_size, 1)
shuffle_index = np.arange(len(x_small))
random.shuffle(shuffle_index)
x_small = x_small[shuffle_index]
y_small = y_small[shuffle_index]
return x_small, y_small
def multi_label_to_binary_label(y, label):
y_hat = np.zeros((len(y), 1))
indeces_positive = list(np.where(y[:, label] == 1)[0])
y_hat[indeces_positive] = 1
return y_hat
def generate_probability_matrix(x, binary_classifier_list):
num_classes = len(binary_classifier_list)
num_sample = len(x)
result = np.zeros((num_sample, num_classes))
for label in range(num_classes):
classifier = binary_classifier_list[label]
prediction = classifier.prediction(x).reshape((num_sample,))
result[:, label] = prediction
with tf.Session() as sess:
probability_matrix = sess.run(tf.nn.softmax(result))
return probability_matrix
def run_cross_reference():
data_chooser = FactoryClass.ChooseDataset(dataset, seed, noise_level, augmentation)
data_object = data_chooser.data_object
x_train, y_train, y_train_orig, x_test, y_test = data_object.x_train, data_object.y_train, \
data_object.y_train_orig, data_object.x_test, data_object.y_test
num_classes = data_object.num_classes
input_size = data_object.input_size
binary_classifier_list = []
binary_model_object = FactoryClass.ChooseNetworkCreator(model_type, model_architecture, input_size, learning_rate,
dropout, 2)
multi_model_object = FactoryClass.ChooseNetworkCreator(model_type, model_architecture, input_size, learning_rate,
dropout, num_classes)
record_file = 'test2_1/' + dataset + '.txt'
record = open(record_file, 'a+')
record.write('model architecture: ' + str(model_architecture) + '\n')
record.write('noise level: ' + str(noise_level) + '\n')
record.write('augmentation: ' + str(augmentation) + '\n')
record.write('learning rate: ' + str(learning_rate) + '\n')
record.write('batch size: ' + str(batch_size) + '\n')
record.write('epoch for binary classifiers: ' + str(epochs_for_binary) + ', multi-classifier: ' + str(
epochs_for_multiple) + '\n')
record.write('data size: ' + str(data_size) + '\n')
record.write('section: ' + str(section_num) + '\n')
for label in range(num_classes):
binary_classifier_list.append(binary_model_object.choose_network_creator())
multi_classifier = multi_model_object.choose_network_creator()
for section in range(section_num):
for label in range(num_classes):
classifier = binary_classifier_list[label]
x, y = randomly_sample_binary_data(x_train, y_train, data_size, label)
classifier.train_model(x, y, batch_size, epochs_for_binary)
loss_train, accuracy_train = classifier.evaluate_model(x, y)
record.write(str(section) + '-th section, ' + str(label) + '-th classifier, loss: ' + str(loss_train)
+ ', train accuracy: ' + str(accuracy_train) + '\n')
record.flush()
for epoch in range(epochs_for_multiple):
new_y = generate_probability_matrix(x_train, binary_classifier_list)
multi_classifier.train_model(x_train, new_y, batch_size, epochs=1)
loss_test, accuracy_test = multi_classifier.evaluate_model(x_test, y_test)
record.write(str(section) + '-th section, ' + str(epoch) + '-th epoch, test accuracy:' + str(
accuracy_test) + '\n')
record.flush()
record.write('*' * 30 + '\n')
record.close()
for noise_level in [0.5]:
run_cross_reference()
| [
"14300180119@fudan.edu.cn"
] | 14300180119@fudan.edu.cn |
aaf684914f88ee47e002fe6283aad1328b10f3ad | 6cce023315d4083c7df0fcdeea2a037b00818878 | /py-files/data_setup.py | 3a1efa85492db400854022be0137e9d4defafa58 | [] | no_license | Limmen/Distributed_ML | e02e865a123e552d3795c76a4a0846f2da6f3a55 | d5b65a0bcb89182e3ac773b0a3cec46625dabccb | refs/heads/master | 2021-05-09T03:52:41.530823 | 2018-01-28T12:21:47 | 2018-01-28T12:21:47 | 119,255,519 | 5 | 1 | null | null | null | null | UTF-8 | Python | false | false | 2,735 | py |
import argparse
import pyspark
from pyspark.sql.functions import udf
from pyspark.sql.types import *
import tensorflow as tf
import pandas as pd
import numpy as np
SEQ_LABELS_TRAIN = "data/y_train.csv"
SEQ_FEATURES_TRAIN = "data/x_train.csv"
SEQ_LABELS_TEST = "data/y_test.csv"
SEQ_FEATURES_TEST = "data/x_test.csv"
conf = pyspark.SparkConf()
conf = conf.setAppName("har_data_setup").set("spark.hadoop.validateOutputSpecs", "false")
sc = pyspark.SparkContext(conf=conf)
sql = pyspark.SQLContext(sc)
CLEANED_DATA_PATH = "./cleaned_data"
def read_raw_data(sql):
seq_features_train_raw = sql.read.format("com.databricks.spark.csv").options(header="false").load(SEQ_FEATURES_TRAIN)
seq_labels_train_raw = sql.read.format("com.databricks.spark.csv").options(header="false").load(SEQ_LABELS_TRAIN)
seq_features_test_raw = sql.read.format("com.databricks.spark.csv").options(header="false").load(SEQ_FEATURES_TEST)
seq_labels_test_raw = sql.read.format("com.databricks.spark.csv").options(header="false").load(SEQ_LABELS_TEST)
return seq_features_train_raw,seq_labels_train_raw, seq_features_test_raw, seq_labels_test_raw
seq_features_train_raw, seq_labels_train_raw,seq_features_test_raw,seq_labels_test_raw = read_raw_data(sql)
features_train_size = seq_features_train_raw.count()
labels_train_size = seq_labels_train_raw.count()
features_test_size = seq_features_test_raw.count()
labels_test_size = seq_labels_test_raw.count()
print("train feat size: {0}, train label size: {1}, test feat size {2}, test label size {3}".format(features_train_size, labels_train_size, features_test_size, labels_test_size))
seq_labels_test_raw.printSchema
classes = seq_labels_train_raw.unionAll(seq_labels_test_raw).select("_c0").distinct().rdd.map(lambda row: row._c0).zipWithIndex().collectAsMap()
seq_labels_train_clean = seq_labels_train_raw.select("_c0").rdd.map(lambda row: classes[row._c0])
seq_labels_test_clean = seq_labels_test_raw.select("_c0").rdd.map(lambda row: classes[row._c0])
labels_train_np = seq_labels_train_clean.collect()
labels_test_np = seq_labels_test_clean.collect()
np.savetxt(CLEANED_DATA_PATH + "/train/labels/y_train.csv", np.array(labels_train_np).astype(int), fmt='%i', delimiter=",")
np.savetxt(CLEANED_DATA_PATH + "/test/labels/y_test.csv", np.array(labels_test_np).astype(int), fmt='%i', delimiter=",")
np.savetxt(CLEANED_DATA_PATH + "/classes/classes.csv", np.array([[k,v] for k,v in classes.items()]),fmt="%s", delimiter=",")
np.savetxt(CLEANED_DATA_PATH + "/size/sizes.csv", np.array([["features_train_size", features_train_size], ["labels_train_size", labels_train_size], ["features_test_size", features_test_size], ["labels_test_size", labels_test_size]]), fmt="%s", delimiter=",")
| [
"kimham@kth.se"
] | kimham@kth.se |
6f37bf00f359e16e59af581cd68fe789c123ffa9 | fbc9f9088f636d71119fca87c2120f533e10668d | /Book_store/settings/base.py | eed8356f89434a96c8696d7152bf2bb7955b548e | [] | no_license | mastercsay2511/BookStoreV1 | e726c18499482ef1bcd12acf4575856b68a536a6 | 5ee23b35a18d0ab4d7810bacf482e7f9f7a21768 | refs/heads/master | 2023-05-31T04:58:36.545403 | 2020-07-18T05:33:39 | 2020-07-18T05:33:39 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,214 | py |
import os
from decouple import config
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
BASE_DIR = os.path.dirname(os.path.dirname(
os.path.dirname
(os.path.abspath(__file__))))
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/3.0/howto/deployment/checklist/
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = config('SECRET_KEY')
# SECURITY WARNING: don't run with ³ug turned on in production!
# DEBUG = True
# ALLOWED_HOSTS = []
# INTERNAL_IPS = [
# '127.0.0.1',
# ]
# Application definition
INSTALLED_APPS = [
# local apps
"library.apps.LibraryConfig",
"books.apps.BooksConfig",
"pages.apps.PagesConfig",
"users.apps.UsersConfig",
'core',
# Third party apps
'django_countries',
'crispy_forms',
# 'allauth',
# 'allauth.account',
# default
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
# added
# 'django.contrib.sites',
]
MIDDLEWARE = [
'django.middleware.security.SecurityMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
]
ROOT_URLCONF = 'Book_store.urls'
TEMPLATES = [
{
'BACKEND': 'django.template.backends.django.DjangoTemplates',
'DIRS': [os.path.join(BASE_DIR, 'templates')],
'APP_DIRS': True,
'OPTIONS': {
'context_processors': [
'django.template.context_processors.debug',
'django.template.context_processors.request',
'django.contrib.auth.context_processors.auth',
'django.contrib.messages.context_processors.messages',
],
},
},
]
WSGI_APPLICATION = 'Book_store.wsgi.application'
# Database
# https://docs.djangoproject.com/en/3.0/ref/settings/#databases
# Password validation
# https://docs.djangoproject.com/en/3.0/ref/settings/#auth-password-validators
AUTH_PASSWORD_VALIDATORS = [
{
'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator',
},
]
# Internationalization
# https://docs.djangoproject.com/en/3.0/topics/i18n/
LANGUAGE_CODE = 'en-us'
TIME_ZONE = 'UTC'
USE_I18N = True
USE_L10N = True
USE_TZ = True
# Static files (CSS, JavaScript, Images)
# https://docs.djangoproject.com/en/3.0/howto/static-files/
STATIC_URL = '/static/'
STATICFILES_DIRS = [os.path.join(BASE_DIR, 'static_in_env'), ]
VENV_PATH = os.path.dirname(BASE_DIR)
STATIC_ROOT = os.path.join(BASE_DIR, 'static_root')
# optional
STATICFILES_FINDERS = [
"django.contrib.staticfiles.finders.FileSystemFinder",
"django.contrib.staticfiles.finders.AppDirectoriesFinder", ]
MEDIA_URL = '/media/'
MEDIA_ROOT = os.path.join(BASE_DIR, 'media')
AUTH_USER_MODEL = "users.PersoUser"
LOGIN_URL = "login"
LOGIN_REDIRECT_URL = "home"
LOGOUT_REDIRECT_URL = "home"
# Gmail mailing method
EMAIL_BACKEND = "django.core.mail.backends.smtp.EmailBackend"
# if smtp not confugured yet EMAIL_BACKEND = "django.core.mail.backends.console.EmailBackend"
EMAIL_HOST = "smtp.gmail.com"
EMAIL_PORT = 587
EMAIL_USE_TLS = True
EMAIL_HOST_USER = os.environ.get("GMAIL_U")
EMAIL_HOST_PASSWORD = os.environ.get("GMAIL_P")
CRISPY_TEMPLATE_PACK = 'bootstrap4'
# django allauth config
# SITE_ID = 1
# AUTHENTICATIONS_BACKENDS = [
# 'django.contrib.auth.backends.ModelBackend',
# 'allauth.account.auth_backends.AuthenticationBackend',
# ]
# ACCOUNT_FORMS = {'signup': 'Book_store.forms.PersoUserRegisterForm'}
| [
"ffoot9898@protonmail.com"
] | ffoot9898@protonmail.com |
7a8252f05c1ee87e900b5ed853a3cabc43688b96 | 74081581575e80b2b0f6b75ba912d58ea4f37ac6 | /maskrcnn_benchmark/modeling/detector/detectors.py | 35064d2f9992fd2c2e08d4a29ad31d1e5a229f8f | [] | no_license | youngfly11/LCMCG-PyTorch | 5f6b9f231613b86ac7b250ca0f34229402e1615e | e95299b9a9f1b13e21750ef0dcde0941d703d009 | refs/heads/master | 2021-10-25T19:29:12.967318 | 2021-10-25T03:35:14 | 2021-10-25T03:35:14 | 221,908,808 | 56 | 12 | null | null | null | null | UTF-8 | Python | false | false | 419 | py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
from .generalized_rcnn import GeneralizedRCNN
from .generalized_rcnn_det import GeneralizedRCNNDet
_DETECTION_META_ARCHITECTURES = {"GeneralizedRCNN": GeneralizedRCNN, "GeneralizedRCNNDet": GeneralizedRCNNDet}
def build_detection_model(cfg):
meta_arch = _DETECTION_META_ARCHITECTURES[cfg.MODEL.META_ARCHITECTURE]
return meta_arch(cfg)
| [
"liuyf3@shanghaitech.edu.cn"
] | liuyf3@shanghaitech.edu.cn |
67360e7af6f9cc8a5f230d48a2d706a49749ca35 | fc9175c91bf99ce697e3bed46a7cc0db3343283e | /11Documentos/exemplo02.py | 2418a4d8567d9e2c793a8faa0d452a2f60fe5918 | [] | no_license | cerchiariluiza/CodigosScrapsCompiladosPython | 27758df20243146d29bcdc612d58082af450d4d1 | 4b1b7429068fe3072e7bed3f720e8519f9d60629 | refs/heads/main | 2023-04-01T10:33:47.642816 | 2021-04-10T15:07:57 | 2021-04-10T15:07:57 | 356,616,553 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,175 | py | from urllib.request import urlopen
from bs4 import BeautifulSoup
import re
import string
def limpar_texto(texto):
texto = texto.strip()
texto_limpo = []
# Trocando um ou mais caracteres de nova linha (enter) por um espaço.
texto = re.sub("\n+", " ", texto)
# Trocando um ou mais espaços por um espaço.
texto = re.sub(" +", " ", texto)
# Remover os caracteres de controle
texto = texto.replace(u'\xa0', u'')
# Remover números entre colchetes (citações Wikipedia)
texto = re.sub("\[[0-9]*\]", "", texto)
texto = texto.split(" ")
for item in texto:
item = item.strip()
# string.punctuation == '!"#$%&\'()*+,-./:;<=>?@[\\]^_`{|}~'
# Removendo caracteres de pontuação antes e depois da string
item = item.strip(string.punctuation)
if len(item) > 1 or (item.lower() == 'a' or item.lower() == 'e' or item.lower() == 'o'):
texto_limpo.append(item)
return texto_limpo
html = urlopen("https://pt.wikipedia.org/wiki/Python")
bsObj = BeautifulSoup(html)
conteudo = bsObj.find("div", {"id":"mw-content-text"}).get_text()
conteudo = limpar_texto(conteudo)
print(conteudo)
| [
"Lab@NOT-000-008.nscyber.local"
] | Lab@NOT-000-008.nscyber.local |
e1e458abdbc5777af32bf1194e4add3db39fd867 | 36b9fa9f2d8ff655546a33cb47ddacd009bc00c9 | /autogalaxy/profiles/light/linear/__init__.py | bb275334df92a6bf4b34d18f21e6aa123ae5dc62 | [
"MIT"
] | permissive | Jammy2211/PyAutoGalaxy | 67b76968b8516309b2ebdbff7affd5c1923cf0b1 | d1a2e400b7ac984a21d972f54e419d8783342454 | refs/heads/main | 2023-08-19T01:00:22.320073 | 2023-08-17T15:39:46 | 2023-08-17T15:39:46 | 216,190,501 | 27 | 9 | MIT | 2023-09-13T14:07:43 | 2019-10-19T10:45:44 | Python | UTF-8 | Python | false | false | 401 | py | from .abstract import LightProfile, LightProfileLinear, LightProfileLinearObjFuncList
from .gaussian import Gaussian, GaussianSph
from .moffat import Moffat
from .sersic import Sersic, SersicSph
from .exponential import Exponential, ExponentialSph
from .dev_vaucouleurs import DevVaucouleurs, DevVaucouleursSph
from .sersic_core import SersicCore
from .exponential_core import ExponentialCore
| [
"james.w.nightingale@durham.ac.uk"
] | james.w.nightingale@durham.ac.uk |
8e8f9d73ce6f9472f45639a730ffebcd0b78cfa8 | 3d078ad4b348fb3b967adcb819cd39410c00960a | /88lcm.py | 12a493281bf2e2baf786d1aeccd360ec177ab889 | [] | no_license | Dhandapani299/python | 7275af2cf3a112d8cf930748c932ad61cb3dcbfb | ed8672a83f3810241138375eafd7420a24603734 | refs/heads/master | 2020-05-22T05:09:15.924855 | 2019-05-12T13:40:40 | 2019-05-12T13:40:40 | 186,230,941 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 268 | py | def lcm(m,n):
if m>n:
grater = m
else:
greater = n
while(True):
if((greater % m == 0) and (greater % n == 0)):
lcm = greater
break
greater += 1
return lcm
num 1 = int(input())
num 2 = int(input())
print(lcm(num,num2))
| [
"noreply@github.com"
] | noreply@github.com |
a3abadf3e5c58d3196f6ac02b55a07ff35093bd4 | 16c77266859989d156fe3f4d0ce3a37a1898ad38 | /ml/sk/__init__.py | 2e9e9ccc69e32e7f29ce91893b4883b61084bc5d | [
"MIT"
] | permissive | SRHerzog/ut | 92620e66be2ea9707d9cd3cf390179326ed2eefe | 894bd5607eb76676aaea7a37ed8a91b5fb5e805e | refs/heads/master | 2021-06-30T19:15:46.131299 | 2017-09-15T20:47:35 | 2017-09-15T20:47:35 | 103,696,926 | 0 | 0 | null | 2017-09-15T20:08:10 | 2017-09-15T20:08:10 | null | UTF-8 | Python | false | false | 54 | py | from __future__ import division
__author__ = 'thor'
| [
"thorwhalen1@gmail.com"
] | thorwhalen1@gmail.com |
df7e6169ccdea122ba78000885ec1008e3579ebd | bc539788b876773e294383863252c1637de9eb7f | /Pscrapy/PycharmProjects/Reptile/Practise/practise4.py | a3249cb05379978d945554dfcee685df198bd50c | [] | no_license | umsung/scrapy | 4eb56bf74f3e617e49dcdec61cf77010eb912f4f | deacd9f289159c5af114b0dd3110448ad7eb43e8 | refs/heads/master | 2020-05-31T14:11:46.530793 | 2019-10-16T01:32:25 | 2019-10-16T01:32:25 | 190,321,772 | 3 | 0 | null | null | null | null | UTF-8 | Python | false | false | 120 | py |
num = input('输入数字：').strip()
num = int(num)
for i in range(1, num):
print(' '*(num-i),'* '*i)
| [
"545699233@qq.com"
] | 545699233@qq.com |
b4ed712c26a2002dc0070864602ef4332b6c1617 | a76803a441b76595372329a54e84e2b2d8fd5c6b | /clang/ubsan/__init__.py | e11a24908fdba31ce0eb9d93480cf990564256ff | [] | no_license | securesystemslab/sanitizing-for-security-benchmarks | ac66b1e6bd67a954a88e48751df8ea98b2b400b9 | c2bf9d922ec8564208a7f926dce56e3a2dfc8355 | refs/heads/master | 2020-03-19T07:34:23.463598 | 2018-06-05T06:04:35 | 2018-10-04T04:28:34 | 136,126,254 | 20 | 4 | null | null | null | null | UTF-8 | Python | false | false | 20 | py | from ubsan import *
| [
"dokyung.song@gmail.com"
] | dokyung.song@gmail.com |
d26bfad3144de16da67ac8ac8a3c28948acff915 | a98e18285e3ba5c5fde601bae933820cbaff3d7a | /mysite/blog/migrations/0003_auto_20180424_1228.py | 302e9afd88f96af0041d1fcd411067ddc7d7d1db | [] | no_license | huanyiyuxin/mysql_mysite | bb72a1ee7207e8a88d1cd2c37e31058e3f81e7d8 | 55c94fad7a3ead45dbc57efda5dd10a6384705d5 | refs/heads/master | 2020-03-16T17:59:01.752362 | 2018-05-10T06:00:54 | 2018-05-10T06:00:54 | 132,854,767 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 707 | py | # Generated by Django 2.0.4 on 2018-04-24 04:28
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('blog', '0002_auto_20180424_1206'),
]
operations = [
migrations.RemoveField(
model_name='post',
name='author',
),
migrations.AlterField(
model_name='blogpost',
name='author',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='blog_posts', to=settings.AUTH_USER_MODEL),
),
migrations.DeleteModel(
name='Post',
),
]
| [
"954441@qq.com"
] | 954441@qq.com |
8cf423d1f9f0257fa371e065ae2d57628aeedaf2 | ee4db47ccecd23559b3b6f3fce1822c9e5982a56 | /Analyse Data/NumpPy.py | d2bf919d8ad04f330f143dfea2c477d7387bd3ee | [] | no_license | meoclark/Data-Science-DropBox | d51e5da75569626affc89fdcca1975bed15422fd | 5f365cedc8d0a780abeb4e595cd0d90113a75d9d | refs/heads/master | 2022-10-30T08:43:22.502408 | 2020-06-16T19:45:05 | 2020-06-16T19:45:05 | 265,558,242 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 4,021 | py | # Introduction to NumPy: Numerical Python
#NumPy is great at storing and manipulating numerical data in arrays.
import numpy as np
# NumPy Arrays
#A NumPy array is a special type of list. It’s a data structure that organizes multiple items. Each item can be of any type (strings, numbers, or even other arrays).
test_1 = np.array([92, 94, 88, 91, 87])
# test_1 is now a numpy array
#Creating an Array from a CSV
# Note the delimiter can be in other formats such as semi colon and tabs.
test_2 = np.genfromtxt('test_2.csv', delimiter=',')
# Operations with NumPy Arrays
# Let’s compare how to add a number to each value in a python list versus a NumPy array:
# With a list
A = [1, 2, 3, 4, 5,6]
A_plus_3 = []
for i in range(len(A)):
l_plus_3.append(A[i] + 3)
# With an array
a = np.array(l)
a_plus_3 = a + 3
#Squaring each value:
a ** 2
#array([ 1, 4, 9, 16, 25, 36])
#Taking the square root of each value:
np.sqrt(a)
#array([ 1, 1.41421356, 1.73205081, 2, 2.23606798, 2.44948974])
# Add extra 2 points to test_3
test_3 = np.array([87, 85, 72, 90, 92])
test_3_fixed = test_3 + 2
# Operations with NumPy Arrays II
# Arrays can also be added to or subtracted from each other in NumPy,
# assuming the arrays have the same number of elements.
a = np.array([1, 2, 3, 4, 5])
b = np.array([6, 7, 8, 9, 10])
a + b
#array([ 7, 9, 11, 13, 15])
test_1 = np.array([92, 94, 88, 91, 87])
test_2 = np.array([79, 100, 86, 93, 91])
test_3 = np.array([87, 85, 72, 90, 92])
test_3_fixed = test_3 + 2
total_grade = test_1 + test_2 + test_3_fixed
# average score
final_grade = total_grade / 3
print(final_grade)
# Two-Dimensional Arrays
# in NumPy we can create an array of arrays.
# If the arrays that make up our bigger array are all the same size, then it has a special name: a two-dimensional array.
#we could have also stored all of this data in a single, two-dimensional array: Notice the double square brackets syntax [[]]
np.array([[92, 94, 88, 91, 87],
[79, 100, 86, 93, 91],
[87, 85, 72, 90, 92]])
coin_toss_again = np.array([[1,0,0,1,0],[0,0,1,1,1]])
# Selecting Elements from a 1-D Array
# This uses normal indexing
test_1 = np.array([92, 94, 88, 91, 87])
test_2 = np.array([79, 100, 86, 93, 91])
test_3 = np.array([87, 85, 72, 90, 92])
jeremy_test_2 = test_2[-2]
#grabs 93
manual_adwoa_test_1 = test_1[1:3]
# grabs 94 88
# Selecting Elements from a 2-D Array
# The syntax for selecting from a 2-d array is a[row,column] where a is the array.
a = np.array([[32, 15, 6, 9, 14],
[12, 10, 5, 23, 1],
[2, 16, 13, 40, 37]])
a[2,1]
#16
# selects the first column
a[:,0]
#array([32, 12, 2])
a[1,:]
#array([12, 10, 5, 23, 1])
# selects the first three elements of the first row
a[0,0:3]
#array([32, 15, 6])
student_scores = np.array([[92, 94, 88, 91, 87],
[79, 100, 86, 93, 91],
[87, 85, 72, 90, 92]])
tanya_test_3 = student_scores[2,0]
cody_test_scores = student_scores[:,4]
# Logical Operations with Arrays
# < > == != | &
porridge = np.array([79, 65, 50, 63, 56, 90, 85, 98, 79, 51])
cold = porridge[porridge < 60]
hot = porridge[porridge > 80]
just_right = porridge[(porridge >= 60) & (porridge <= 80)]
print(cold,
hot,
just_right
)
# Review
import numpy as np
temperatures = np.genfromtxt('temperature_data.csv',delimiter=',')
print(temperatures)
temperatures_fixed = temperatures + 3.0
monday_temperatures = temperatures_fixed[0,:]
thursday_friday_morning = temperatures_fixed[3:,1]
temperature_extremes = temperatures_fixed[(temperatures_fixed < 50) | (temperatures_fixed > 60)]
# Project Bettys Bakery
import numpy as np
cupcakes = np.array([2,0.75,2,1,0.5])
recipes = np.genfromtxt('recipes.csv',delimiter=',')
print(recipes)
eggs = recipes[:,2]
print(eggs)
#egg = recipes[recipes[:,2] == 1]
cookies = recipes[2,:]
print(cookies)
double_batch = cupcakes * 2
print(double_batch)
grocery_list = cookies + double_batch
print(grocery_list)
| [
"oluchukwuegbo@gmail.com"
] | oluchukwuegbo@gmail.com |
d1974e0e287d5e7372b79c80651ea675983be9e0 | 1c5cb22e6d0faab6ac11e7b8f4aadd2308a5b75f | /spark/persist_transactions.py | 38d77568c2748a5a7cec5115a45942648b135657 | [] | no_license | alexanderbatanov/safepay | c758b790334dae7f95a47d311d2ff2fb30b52f5c | 02836bec67561d6a3ae6d1f8b0788837f2f9f0b3 | refs/heads/master | 2021-05-01T07:24:54.744465 | 2018-02-27T04:41:47 | 2018-02-27T04:41:47 | 121,155,217 | 1 | 1 | null | null | null | null | UTF-8 | Python | false | false | 1,535 | py | # persist_transactions - SafePay spark streaming job (initial data load)
from pyspark import SparkContext
from pyspark.streaming import StreamingContext
from pyspark.streaming.kafka import KafkaUtils
from pyspark.sql import SparkSession
from pyspark.sql.types import *
from pyspark.sql.functions import *
from cassandra.cluster import Cluster
from datetime import datetime
import uuid
# spark
sc = SparkContext(appName="transactions1")
sc.setLogLevel('ERROR')
ssc = StreamingContext(sc, 2)
spark = SparkSession(sc)
def processRDD(rdd):
if rdd.isEmpty():
return
rdd2 = rdd.map(lambda x: str(uuid.uuid4()) + ";" + x)
rdd3 = rdd2.map(lambda x: x.split(";"))
# persist transactions in tx table for further proessing by a batch job
df = rdd3.toDF(['tx_id', 'source', 'sent_dt', 'tx_dt', 'from_party_id', 'from_party_name', 'to_party_id', 'to_party_name'])
df = df.drop('source')\
.drop('sent_dt')\
.withColumn('denied', lit(False))\
.withColumn('reason', lit('passthru'))
df.write\
.format("org.apache.spark.sql.cassandra")\
.mode('append')\
.options(table="tx", keyspace="p2p")\
.save()
# kafka
topic = "transactions1"
brokers_dns_str = "0.0.0.0:9092"
kvs=KafkaUtils.createDirectStream(ssc, [topic], {"metadata.broker.list": brokers_dns_str})
# read stream
batch=kvs.map(lambda x: x[1])
batch.count().map(lambda x:'Messages in this batch: %s' % x).pprint()
batch.foreachRDD(processRDD)
ssc.start()
ssc.awaitTermination()
| [
"alexb@MACAROSHA.local"
] | alexb@MACAROSHA.local |
637c084fe5757dc015d5c194b45ffe7749980d41 | ed5d9407a3321b079b4cf7d67f09c2e32a82aef6 | /ensemble_predicted.py | cfe09e7b801495d806d569ba819b36dc55b4cb45 | [] | no_license | laurinpaech/segme-net | 45b087e015d48116d151a5e8b3f196f145ff0831 | df19792336696dddbf419aa5e7a18eea66f66869 | refs/heads/master | 2022-07-17T14:20:13.074387 | 2019-11-02T17:25:08 | 2019-11-02T17:25:08 | 175,799,081 | 0 | 0 | null | 2022-06-21T22:15:48 | 2019-03-15T10:27:13 | Python | UTF-8 | Python | false | false | 1,725 | py | from data_loader.data import *
import argparse
import os
"""
Use this to combine pre_ensemble images to fully ensembled output submission images
Images are in data/submit_output/XXX/pre_ensembled/
"""
parser = argparse.ArgumentParser()
parser.add_argument('--desc', type=str, default='stacked_unet_default',
help='How to name this run, defines folder in logs dir, only use "a-z,A-Z,1-9,_" pls')
parser.add_argument('--cutoff', type=float, default=0.5, help='Cutoff value for ensembling data.')
parser.add_argument('--nr', type=float, default=0.5, help='Cutoff value for ensembling data.')
parser.add_argument('--nr_of_stacks', type=int, default=2,
help='number of the stack to ensemble and get final results on')
args = parser.parse_args()
# Set parameters
cutoff = args.cutoff
nr = args.nr
# Create paths
test_output_path = "data/submit_output"
output_path = os.path.join(test_output_path, args.desc)
test_predict_path = "data/test"
temp_path = "data/temp"
temp_path_2 = "data/temp_2"
# Create dirs
os.makedirs(temp_path, exist_ok=True)
os.makedirs(temp_path_2, exist_ok=True)
# Should be full with images
output_path_pre_ensembled = os.path.join(output_path, "pre_ensembled")
output_path_ensembled = os.path.join(output_path, "ensembled_{0}".format(nr))
os.makedirs(output_path_ensembled, exist_ok=True)
# create ensemble predictions
ensemble_predictions(test_predict_path, output_path_pre_ensembled,
temp_path_2, nr_of_stacks=args.nr_of_stacks,
alpha=cutoff) # save into output_path_ensembled because need resize
# resize ensembled predictions and save them
saveSubmitResizeEnsemble(temp_path, temp_path_2, output_path_ensembled)
| [
"paech.laurin@gmail.com"
] | paech.laurin@gmail.com |
9e66cd2e75a516c445ee081fad2339a4088a1f5e | d53605afd805311cc6a37b669afa2162965a5020 | /sentimental_analysis/classifier.py | 8920ec62cc45c2d3fc80797c992c8271bc57bb85 | [] | no_license | ahmad-elbatanouni/sentimental-analyzer | 659085c14d80ef3d20c8052e1ff58a04cedee2ad | b75b6871e2cc562b9d56cbab5d21cd6aba2caedb | refs/heads/master | 2021-01-18T03:50:03.745465 | 2015-07-29T06:08:29 | 2015-07-29T06:08:29 | 39,876,505 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,872 | py | import helpers
class Classifier:
def __init__(self, positive_corpus, negative_corpus):
self.positive_corpus = positive_corpus
self.negative_corpus = negative_corpus
self.total_probability = 0
self.inverse_total_probability = 0
self.tolerance = 0.05
def classify(self, text):
stop_words = helpers.get_stop_words()
for word in text.split(" "):
if word.lower() in stop_words:
continue
positive_matches = self.positive_corpus.token_count(word)
negative_matches = self.negative_corpus.token_count(word)
positive_total = self.positive_corpus.total_tokens
negative_total = self.negative_corpus.total_tokens
# print word
# print "========="
probability = self.calculate_probability(positive_matches, positive_total, negative_matches, negative_total)
self.record_probability(probability)
final_probability = self.combine_probabilities()
return {"sentiment": self.compute_sentiment(final_probability), "probability": final_probability}
def calculate_probability(self, positive_matches, positive_total, negative_matches, negative_total):
# print "pos_mat ", positive_matches, ", pos_tot: ", positive_total, ", neg_mat: ", negative_matches, "neg_tot: ", negative_total
total = positive_matches + negative_matches
positive_ratio = positive_matches / float(positive_total)
negative_ratio = negative_matches / float(negative_total)
probability = positive_ratio / (positive_ratio + negative_ratio) if positive_ratio + negative_ratio != 0 else 0
print "total: ", total, ", positive_ratio: ", positive_ratio, ", negative_ratio: ", negative_ratio, ", prob: ", probability
# print ((unknown_word_strength * unknown_word_probability) + (total * probability)) / (unknown_word_strength + total)
# print "========================================================================================"
return ((total * probability) + 1) / (total + 2)
def record_probability(self, probability):
if probability is None:
return
self.total_probability = probability if self.total_probability == 0 else self.total_probability * probability
self.inverse_total_probability = (1 - probability) if self.inverse_total_probability == 0 else self.inverse_total_probability * (1 - probability)
def combine_probabilities(self):
if self.total_probability == 0:
return 0.5
return self.total_probability / (self.total_probability + self.inverse_total_probability)
def compute_sentiment(self, probability):
if probability < (0.5):
return "Negative"
if probability > (0.5):
return "Positive"
return "Neutral" | [
"ahmad@Ahmad.(none)"
] | ahmad@Ahmad.(none) |
1b1a8f0378daac92ecbb890eb38b46894b17e9a1 | 15a833cfb3deec9278ca4a458d55aa7132ab63d1 | /kakao_codingTest_winter_Internship/test2.py | f74ac217ea6f61186801b083c03be4857341bda1 | [] | no_license | jaehui327/pythonAlgorithm | 9db6bfb3446ab3049b39d575170d751a912a4646 | 3a60fb1694fa17c8e5dc7516d3ed2bb07a91c69b | refs/heads/master | 2020-07-22T07:53:38.977926 | 2019-12-23T14:12:52 | 2019-12-23T14:12:52 | 207,121,744 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,024 | py | def solution(s):
answer = []
strList = []
numList = []
list = []
# 문자열 분할해서 리스트 저장
l = s.split(",{")
for i in l:
a = i.replace("{", "")
b = a.replace("}", "")
strList.append(b)
# 크기순 정렬
strList.sort(key=len)
# 숫자로 변환
for i in strList:
numList = i.split(",")
numList = [int (a) for a in numList]
list.append(numList)
# 리스트가 0이 될때까지
while(1):
if not list: break
# 맨 앞 리스트만 확인
num = list[0][0]
# 정답에 넣음
answer.append(num)
list.pop(0)
# 리스트 순회
for j in list:
# 리스트 내의 숫자 순회
for k in range(0, len(j)):
if num == j[k]:
j.pop(k)
break
return answer
#s = "{{2},{2,1},{2,1,3},{2,1,3,4}}"
#s = "{{20,111},{111}}"
s = "{{4,2,3},{3},{2,3,4,1},{2,3}}"
print(solution(s)) | [
"jaehui327@naver.com"
] | jaehui327@naver.com |
b85ffbbc411490b508f4ad212c32852d48891acc | 8e559df1b6f34a09d32b4e854efa0dd6e4b62fe0 | /cs5png3.py | 2a28a0c248d3a21729f14d2d4a4b8c5fa009fca9 | [] | no_license | norahpack/carbonEmissions | 5108dbd64a9fd5181d9a496db57f551aa8f2bc2f | 9b877996039c57d64e2236122fda6b15e9289f19 | refs/heads/main | 2023-08-29T16:08:28.642472 | 2021-11-11T22:23:20 | 2021-11-11T22:23:20 | 427,158,503 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,190 | py | import os
import sys
from PIL import Image
import time
def saveRGB(boxed_pixels, filename = "out.png"):
"""Save the given pixel array in the chosen file as an image."""
print(f'Starting to save {filename}...', end = '')
w, h = getWH(boxed_pixels)
im = Image.new("RGB", (w, h), "black")
px = im.load()
for r in range(h):
#print(".", end = "")
for c in range(w):
bp = boxed_pixels[r][c]
t = tuple(bp)
px[c,r] = t
im.save(filename)
time.sleep(0.5)
print(filename, "saved.")
def getRGB(filename = "in.png"):
"""Reads an image png file and returns it as a list of lists of pixels
(i.e., and array of pixels).
"""
original = Image.open(filename)
print(f"{filename} contains a {original.size[0]}x{original.size[1]}"
f" {original.format} image with mode {original.mode}.")
WIDTH, HEIGHT = original.size
px = original.load()
PIXEL_LIST = []
for r in range(HEIGHT):
row = []
if original.mode == 'RGB':
for c in range(WIDTH):
row.append(px[c, r][:3])
else:
for c in range(WIDTH):
pixel = px[c, r]
row.append((pixel, pixel, pixel))
PIXEL_LIST.append(row)
return PIXEL_LIST
def getWH(px):
"""Given a pixel array, return its width and height as a pair."""
h = len(px)
w = len(px[0])
return w, h
def binaryIm(s, cols, rows):
"""Given a binary image s of size rows x cols, represented as
a single string of 1's and 0's, write a file named "binary.png",
which contains an equivalent black-and-white image."""
px = []
for row in range(rows):
row = []
for col in range(cols):
c = int(s[row*cols + col])*255
px = [c, c, c]
row.append(px)
px.append(row)
saveRGB(px, 'binary.png')
#return px
class PNGImage:
"""Class to support simple manipulations on PNG images."""
def __init__(self, width, height):
"""Construct a PNGImage of the given dimensions."""
self.width = width
self.height = height
default = (255, 255, 255)
self.image_data = [[(255, 255, 255) for col in range(width)]
for row in range(height)]
def plotPoint(self, col, row, rgb = (0, 0, 0)):
"""Plot a single RGB point in at the given location in a PNGImage."""
# Ensure that rgb is a three-tuple
if not isinstance(rgb, (list, tuple)) or len(rgb) != 3:
print(f"In plotPoint, the color {rgb} was not"
f" in a recognized format.", file = sys.stderr)
# Check if we're in bounds
if 0 <= col < self.width and \
0 <= row < self.height:
self.image_data[row][col] = rgb
else:
print(f"In plotPoint, column {col} or row {row}", file = sys.stderr)
return
def saveFile(self, filename = "test.png"):
"""Save the object's data to a file."""
# We reverse the rows so that the y direction
# increases upwards...
saveRGB(self.image_data[::-1], filename)
| [
"noreply@github.com"
] | noreply@github.com |
bc441a7d134649701613b6e1325e68ee43471d29 | b70be26411a98b6ef3f7598fce4f621193ff281d | /hack3/test_videocap.py | 77e4cd2ea33d6cc6ff3b52bf049d480097fab3e2 | [] | no_license | comcomet/first-repository | b914a1b9ac57296645b4ebf377a184ba26b63c25 | 6eadb7d916e69478f12e8740aebba264d2f93027 | refs/heads/master | 2023-02-01T15:55:11.943969 | 2020-12-20T02:34:10 | 2020-12-20T02:34:10 | 282,796,457 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 7,047 | py | #!/usr/bin/python
import numpy as np
import tensorflow as tf
from utils import *
import sys
#GLOBAL VARIABLE INITIALIZATIONS TO BUILD MODEL
n_steps = 80
hidden_dim = 500
frame_dim = 4096
batch_size = 1
vocab_size = len(word2id)
bias_init_vector = get_bias_vector()
def build_model():
"""This function creates weight matrices that transform:
* frames to caption dimension
* hidden state to vocabulary dimension
* creates word embedding matrix """
print "Network config: \nN_Steps: {}\nHidden_dim:{}\nFrame_dim:{}\nBatch_size:{}\nVocab_size:{}\n".format(n_steps,
hidden_dim,
frame_dim,
batch_size,
vocab_size)
#Create placeholders for holding a batch of videos, captions and caption masks
video = tf.placeholder(tf.float32,shape=[batch_size,n_steps,frame_dim],name='Input_Video')
caption = tf.placeholder(tf.int32,shape=[batch_size,n_steps],name='GT_Caption')
caption_mask = tf.placeholder(tf.float32,shape=[batch_size,n_steps],name='Caption_Mask')
dropout_prob = tf.placeholder(tf.float32,name='Dropout_Keep_Probability')
with tf.variable_scope('Im2Cap') as scope:
W_im2cap = tf.get_variable(name='W_im2cap',shape=[frame_dim,
hidden_dim],
initializer=tf.random_uniform_initializer(minval=-0.08,maxval=0.08))
b_im2cap = tf.get_variable(name='b_im2cap',shape=[hidden_dim],
initializer=tf.constant_initializer(0.0))
with tf.variable_scope('Hid2Vocab') as scope:
W_H2vocab = tf.get_variable(name='W_H2vocab',shape=[hidden_dim,vocab_size],
initializer=tf.random_uniform_initializer(minval=-0.08,maxval=0.08))
b_H2vocab = tf.Variable(name='b_H2vocab',initial_value=bias_init_vector.astype(np.float32))
with tf.variable_scope('Word_Vectors') as scope:
word_emb = tf.get_variable(name='Word_embedding',shape=[vocab_size,hidden_dim],
initializer=tf.random_uniform_initializer(minval=-0.08,maxval=0.08))
print "Created weights"
#Build two LSTMs, one for processing the video and another for generating the caption
with tf.variable_scope('LSTM_Video',reuse=None) as scope:
lstm_vid = tf.nn.rnn_cell.BasicLSTMCell(hidden_dim)
lstm_vid = tf.nn.rnn_cell.DropoutWrapper(lstm_vid,output_keep_prob=dropout_prob)
with tf.variable_scope('LSTM_Caption',reuse=None) as scope:
lstm_cap = tf.nn.rnn_cell.BasicLSTMCell(hidden_dim)
lstm_cap = tf.nn.rnn_cell.DropoutWrapper(lstm_cap,output_keep_prob=dropout_prob)
#Prepare input for lstm_video
video_rshp = tf.reshape(video,[-1,frame_dim])
video_rshp = tf.nn.dropout(video_rshp,keep_prob=dropout_prob)
video_emb = tf.nn.xw_plus_b(video_rshp,W_im2cap,b_im2cap)
video_emb = tf.reshape(video_emb,[batch_size,n_steps,hidden_dim])
padding = tf.zeros([batch_size,n_steps-1,hidden_dim])
video_input = tf.concat([video_emb,padding],1)
print "Video_input: {}".format(video_input.get_shape())
#Run lstm_vid for 2*n_steps-1 timesteps
with tf.variable_scope('LSTM_Video') as scope:
out_vid,state_vid = tf.nn.dynamic_rnn(lstm_vid,video_input,dtype=tf.float32)
print "Video_output: {}".format(out_vid.get_shape())
#Prepare input for lstm_cap
padding = tf.zeros([batch_size,n_steps,hidden_dim])
caption_vectors = tf.nn.embedding_lookup(word_emb,caption[:,0:n_steps-1])
caption_vectors = tf.nn.dropout(caption_vectors,keep_prob=dropout_prob)
caption_2n = tf.concat([padding,caption_vectors],1)
caption_input = tf.concat([caption_2n,out_vid],2)
print "Caption_input: {}".format(caption_input.get_shape())
#Run lstm_cap for 2*n_steps-1 timesteps
with tf.variable_scope('LSTM_Caption') as scope:
out_cap,state_cap = tf.nn.dynamic_rnn(lstm_cap,caption_input,dtype=tf.float32)
print "Caption_output: {}".format(out_cap.get_shape())
#Compute masked loss
output_captions = out_cap[:,n_steps:,:]
output_logits = tf.reshape(output_captions,[-1,hidden_dim])
output_logits = tf.nn.dropout(output_logits,keep_prob=dropout_prob)
output_logits = tf.nn.xw_plus_b(output_logits,W_H2vocab,b_H2vocab)
output_labels = tf.reshape(caption[:,1:],[-1])
caption_mask_out = tf.reshape(caption_mask[:,1:],[-1])
loss = tf.nn.sparse_softmax_cross_entropy_with_logits(logits=output_logits,labels=output_labels)
masked_loss = loss*caption_mask_out
loss = tf.reduce_sum(masked_loss)/tf.reduce_sum(caption_mask_out)
return video,caption,caption_mask,output_logits,loss,dropout_prob
if __name__=="__main__":
with tf.Graph().as_default():
learning_rate = 0.00001
video,caption,caption_mask,output_logits,loss,dropout_prob = build_model()
optim = tf.train.AdamOptimizer(learning_rate = learning_rate).minimize(loss)
ckpt_file = 'S2VT_Dyn_10_0.0001_300_46000.ckpt.meta'
saver = tf.train.Saver()
with tf.Session() as sess:
if ckpt_file:
saver_ = tf.train.import_meta_graph(ckpt_file)
saver_.restore(sess,'./S2VT_Dyn_10_0.0001_300_46000.ckpt')
print "Restored model"
else:
sess.run(tf.initialize_all_variables())
while(1):
vid,caption_GT,_,video_urls = fetch_data_batch_val(1)
caps,caps_mask = convert_caption(['<BOS>'],word2id,80)
for i in range(n_steps):
o_l = sess.run(output_logits,feed_dict={video:vid,
caption:caps,
caption_mask:caps_mask,
dropout_prob:1.0})
out_logits = o_l.reshape([batch_size,n_steps-1,vocab_size])
output_captions = np.argmax(out_logits,2)
caps[0][i+1] = output_captions[0][i]
print_in_english(caps)
if id2word[output_captions[0][i]] == '<EOS>':
break
print '............................\nGT Caption:\n'
print_in_english(caption_GT)
play_video = raw_input('Should I play the video? ')
if play_video.lower() == 'y':
playVideo(video_urls)
test_again = raw_input('Want another test run? ')
if test_again.lower() == 'n':
break
| [
"yongsungs@gmail.com"
] | yongsungs@gmail.com |
cd12fc3d74b637e459f67a399298b68bce6112f1 | 2840fd738487060aa7604f60e70eb623f15a019e | /Lecture71_Somkiat_N.py | 1660e7133d4e910222ab70747880801d5539a917 | [] | no_license | knutz32/CP3-Somkiat-Nattawut | 421f58a6953ede7326d2ac0ad6d972a52aaa2047 | 911feb4732b34dbcd62d19edae392dd0b0f800fa | refs/heads/master | 2020-06-04T06:59:14.345898 | 2019-06-29T14:10:45 | 2019-06-29T14:10:45 | 191,915,041 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 499 | py | menuList = []
priceList = []
while True:
menuName = input("Enter Menu : ")
if menuName.lower() == "exit":
break
else:
menuPrice = int(input("Enter Price : "))
menuList.append(menuName)
priceList.append(menuPrice)
def showBill():
print((" Food Shop ").center(30,"-"))
for i in range(len(menuList)):
print("%s \t\t\t %s THB" % (menuList[i],priceList[i]))
print("-"*30)
print("Total Price \t %s THB" % (sum(priceList)))
showBill()
| [
"noreply@github.com"
] | noreply@github.com |
3f88cac88fa1c16cd8a12b930fb31e2d30401da9 | 3ec0d6535dca5e5da5fc28b6f8cb800cf9b676cc | /venv/lib/python3.6/keyword.py | e94df0be026f611988df825e5dad1d42bc6078d6 | [] | no_license | omarHazim/DB.github.io | 6eecaeb1643ee7c41e245e2ad2847377f377e943 | 2b9dc94966c710083c0b0a3a82acfdd3911e4b35 | refs/heads/master | 2021-09-24T23:40:15.769464 | 2018-10-15T17:55:55 | 2018-10-15T17:55:55 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 46 | py | /Users/omar/anaconda3/lib/python3.6/keyword.py | [
"omar@omars-MacBook.local"
] | omar@omars-MacBook.local |
a05385930991319e2dc5ebf3029f337f10410b3a | ffba5c4a64a87214160c5904b220be8a6e88cd58 | /python-packages/maizy_f/r.py | 5e83d68deeca516eed184231752129e90e707f19 | [] | no_license | maizy/dev-setup | 6e8ae5bc9b56dd85f7612b453e92e31043816189 | 5eb8473cf9c66c66ff8fd9e8c72cecf931f62494 | refs/heads/master | 2022-11-13T22:08:00.184435 | 2022-11-13T08:33:25 | 2022-11-13T08:33:25 | 7,286,016 | 2 | 0 | null | 2017-12-22T11:57:00 | 2012-12-22T13:20:57 | Python | UTF-8 | Python | false | false | 361 | py | # coding: utf-8
# Copyright (c) Nikita Kovaliov, maizy.ru, 2013
from __future__ import print_function, absolute_import, unicode_literals
from fabric.api import task, run
@task
def info():
run('uname -a')
run('hostname')
lsb_rel = run('which lsb_release')
if lsb_rel != '':
print('Debian like os found')
run('lsb_release -a')
| [
"nikita@maizy.ru"
] | nikita@maizy.ru |
5fda4f9c3fff122d9c335a769425599b16276069 | 06ee55a195eca38e8cb81222704eb216f873c080 | /persona/persona/settings.py | 7a6480b3f17d5c78031a13cb42d073fcbd7f59a8 | [] | no_license | TonyWhiteb/PersonaProject | bb0385e93d4ec610fd3ada0bcb2b7f3fa65b7d8a | 5f14b21a7d83e6d7b8da188dbb8dcd0344681c45 | refs/heads/master | 2020-03-19T15:25:41.925361 | 2018-06-17T01:41:39 | 2018-06-17T01:41:39 | 135,847,701 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,268 | py | """
Django settings for persona project.
Generated by 'django-admin startproject' using Django 2.0.6.
For more information on this file, see
https://docs.djangoproject.com/en/2.0/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/2.0/ref/settings/
"""
import os
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/2.0/howto/deployment/checklist/
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = 'q=sk%wmn4y)=$7l743!c&(pg@g#dlg*lmzmrxk)+agg1y_cx-h'
# SECURITY WARNING: don't run with debug turned on in production!
DEBUG = True
ALLOWED_HOSTS = []
# Application definition
INSTALLED_APPS = [
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
'LoginSession',
]
MIDDLEWARE = [
'django.middleware.security.SecurityMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
]
ROOT_URLCONF = 'persona.urls'
TEMPLATES = [
{
'BACKEND': 'django.template.backends.django.DjangoTemplates',
'DIRS': [
os.path.join(BASE_DIR,'templates')
],
'APP_DIRS': True,
'OPTIONS': {
'context_processors': [
'django.template.context_processors.debug',
'django.template.context_processors.request',
'django.contrib.auth.context_processors.auth',
'django.contrib.messages.context_processors.messages',
],
},
},
]
WSGI_APPLICATION = 'persona.wsgi.application'
# Database
# https://docs.djangoproject.com/en/2.0/ref/settings/#databases
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.sqlite3',
'NAME': os.path.join(BASE_DIR, 'db.sqlite3'),
}
}
# Password validation
# https://docs.djangoproject.com/en/2.0/ref/settings/#auth-password-validators
AUTH_PASSWORD_VALIDATORS = [
{
'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator',
},
]
# Internationalization
# https://docs.djangoproject.com/en/2.0/topics/i18n/
LANGUAGE_CODE = 'en-us'
TIME_ZONE = 'UTC'
USE_I18N = True
USE_L10N = True
USE_TZ = True
# Static files (CSS, JavaScript, Images)
# https://docs.djangoproject.com/en/2.0/howto/static-files/
STATIC_URL = '/static/'
STATICFILES_DIRS = [
os.path.join(BASE_DIR,'statics')
]
AUTH_USER_MODEL = 'LoginSession.MyUser' | [
"tonybai2016@gmail.com"
] | tonybai2016@gmail.com |
cbf3083dd8ea5ae4718b4b154ac624468f4e7c15 | 68b23f776fddb77de735419cbf30f33a49e9def2 | /backend/terminus/home/urls.py | 501046c917470aac71074c89c9f1d1a75f5cceac | [] | no_license | vash512/terminus | cbd00f74a600a13fd52aa2206c3eb1e7b5301ec7 | 4eb86d853bc76c22cd1af3c86fed1bc10d457c88 | refs/heads/master | 2016-09-05T14:49:42.655635 | 2015-07-09T03:34:38 | 2015-07-09T03:34:38 | 32,414,141 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,155 | py | # -*- coding: utf-8 -*-
from django.conf.urls import patterns, include, url
from django.views.generic import TemplateView
urlpatterns=patterns('home.views',
url(r'^$', 'index_view', name='index'),
url(r'^humans.txt$', TemplateView.as_view(template_name='statics/humans.txt', content_type='text/plain; charset=utf-8')),
url(r'^robots.txt$', TemplateView.as_view(template_name='statics/robots.txt', content_type='text/plain; charset=utf-8')),
url(r'^sitemap.xml$', TemplateView.as_view(template_name='statics/sitemap.xml', content_type='application/xml; charset=utf-8')),
url(r'^contacto/', 'contacto' ),
url(r'^acercade/', 'acercade'),
url(r'^corpuscontable', 'corpus'),
url(r'^ayuda', 'ayuda'),
#terminos urls de prueba
url(r'^terminos', 'terminos'),
url(r'^terminos/termino', 'termino_detalle'),
url(r'^q/$', 'busqueda'),
url(r'^q/termino', 'busqueda_list'),
url(r'^docs/doc', 'doc_detalle'),
url(r'^docs/$', 'docs'),
#estas direcciones las debe administrar terminos.urls y terminos.views
url(r'^login/', 'log_in'),
url(r'^registro/', 'registro'),
url(r'^logout/', 'log_out'),
) | [
"xtornasol512@gmail.com"
] | xtornasol512@gmail.com |
2a6d4814c6479677185a3e416cdb8f34af10eb47 | 777186acb39efa3fe39c340f4f0a5e10558eb020 | /cmake-build-debug/catkin_generated/generate_cached_setup.py | b7dc571a5d7de75e2cf5290e785b4359b7ebc710 | [] | no_license | UGVProject/PointGrey_CaptureROS | 887b2f232b8abad8b98274569b69b4773715e07f | 5ebc1f18f7ea1b72f31c128226f453f82a2cdec6 | refs/heads/master | 2020-05-21T23:28:10.685788 | 2018-04-08T02:44:36 | 2018-04-08T02:44:36 | 63,830,992 | 1 | 1 | null | null | null | null | UTF-8 | Python | false | false | 1,371 | py | # -*- coding: utf-8 -*-
from __future__ import print_function
import argparse
import os
import stat
import sys
# find the import for catkin's python package - either from source space or from an installed underlay
if os.path.exists(os.path.join('/opt/ros/kinetic/share/catkin/cmake', 'catkinConfig.cmake.in')):
sys.path.insert(0, os.path.join('/opt/ros/kinetic/share/catkin/cmake', '..', 'python'))
try:
from catkin.environment_cache import generate_environment_script
except ImportError:
# search for catkin package in all workspaces and prepend to path
for workspace in "/home/zh/catkin_ws/devel;/opt/ros/kinetic".split(';'):
python_path = os.path.join(workspace, 'lib/python2.7/dist-packages')
if os.path.isdir(os.path.join(python_path, 'catkin')):
sys.path.insert(0, python_path)
break
from catkin.environment_cache import generate_environment_script
code = generate_environment_script('/home/zh/catkin_ws/src/PointGrey_CaptureROS/cmake-build-debug/devel/env.sh')
output_filename = '/home/zh/catkin_ws/src/PointGrey_CaptureROS/cmake-build-debug/catkin_generated/setup_cached.sh'
with open(output_filename, 'w') as f:
#print('Generate script for cached setup "%s"' % output_filename)
f.write('\n'.join(code))
mode = os.stat(output_filename).st_mode
os.chmod(output_filename, mode | stat.S_IXUSR)
| [
"hzhang032@e.ntu.edu.sg"
] | hzhang032@e.ntu.edu.sg |
096140cdef3ff3e96fcd9caedf641f52e4453269 | cc32863d3ed260b36aed4f6e61a1a525b5f06221 | /fyndiq_assignment/urlshortener/migrations/0002_pairedurl.py | b058cc1dd00348c840370b1c1be35ce61de86458 | [] | no_license | orcunozyurt/fyndiq_assignment | 492204654c03bd57fc275b8f251125cdcbd77ffa | f2893724a639778cb42880bbf9a3c709e8342144 | refs/heads/master | 2020-03-30T05:49:53.940943 | 2015-09-13T15:02:22 | 2015-09-13T15:02:22 | 42,361,444 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 677 | py | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
import django.core.validators
class Migration(migrations.Migration):
dependencies = [
('urlshortener', '0001_initial'),
]
operations = [
migrations.CreateModel(
name='PairedUrl',
fields=[
('key_generated', models.OneToOneField(primary_key=True, serialize=False, to='urlshortener.WordList')),
('url', models.URLField(unique=True, validators=[django.core.validators.URLValidator()])),
('cdate', models.DateTimeField(auto_now_add=True)),
],
),
]
| [
"orcunozyurt@hotmail.com"
] | orcunozyurt@hotmail.com |
d4b38cd8aed1979f665275f13320cb82891a952a | 56d8027b7af2fc160a63b546e6ea2f8a7e42e512 | /Algorithms/peak_finding/python/1D_Peak_Finding.py | 948a961875b1a83ff09cad39b098f53bbe341d70 | [] | no_license | juicemia/DataStructures | fb8f278ebfc2e529c232912e0e6cc7ba3dcd1235 | ffe87a03a8fc3d76e1be4e09f7f5218c897baf3a | refs/heads/master | 2020-04-09T00:09:02.908752 | 2016-09-22T16:08:34 | 2016-09-22T16:08:34 | 13,316,162 | 1 | 1 | null | null | null | null | UTF-8 | Python | false | false | 1,670 | py | #!/usr/bin/python
# Please read 1D_peak_finding.pdf for explanation what a peak is, proofs, and asymptotic complexity analysis of the algorithms
# There will be two algorithms. A simple iteration through all the items in the array until finding a peak,
# and a divide and conquer approach to finding a peak
# Keep in mind, both of the algorithms find a peak, not all the peaks
def find_peak_greedy(array):
try:
size = len(array);
except:
# array is empty
return None
if (size == 1 or array[0] >= array[1]): # array is of size one, or the first element is a peak
return array[0] # since it's of size 1,
elif (array[size - 1] >= array[size - 2]): # last element is a peak
return array[size - 1]
else:
# Iterate through array items one by one
for i in range(size):
# make sure it doesn't run out of bounds
if (i < size - 1 and i > 0 and (array[i] >= array[i-1] and array[i] >= array[i+1])):
return array[i]
def find_peak_recursive(array, low, high):
n = int((low + high)/2)
# make sure that index is not out of bounds
if (n > 0 and array[n] < array[n-1]): # look at the left side of the array
return find_peak_recursive(array, low, n)
elif (n < len(array) - 1 and array[n] < array[n+1]): # look at the right side of the array
return find_peak_recursive(array, n, high)
else: # a peak, since array[n-1] <= array[n] <= array[n+1]
return array[n]
#array = (1, 10, 15, 120, -5, -100, 150, 879, 10, 77)
# Answers might differ from the two functions because they approach the problem differently
# However, both answers will be peaks.
#print "%d" % find_peak_greedy(array)
#print "%d" % find_peak_recursive(array, 0, len(array))
| [
"lukas_dmx@yahoo.com"
] | lukas_dmx@yahoo.com |
7c9eb9b5c4fc24e20e09662ff61f97569dacd082 | 99e9b8cf7401a729b129f87690b8ac93916fa4e8 | /graphme.py | 5b5e0e1f75b8bb3c0d07480c4ed6155bf90c4b2e | [
"MIT"
] | permissive | Herringway/graphme | 06981b0435b8e87b5e62d3961dbd4c716ab1815f | 5d45f35749c3a1e48e38fc08719243d3def4c43f | refs/heads/master | 2021-01-12T02:21:56.133039 | 2014-10-11T02:08:29 | 2014-10-11T02:08:29 | 78,505,399 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,011 | py | #!/usr/bin/python2
#Written by Cameron Ross
import operator
def graphme(numgroups, losestates, groupweights,
verify = lambda v,w,x,y,z: True,
maxval = 40,
victoryverify = lambda a: len(a) == len(list(filter(None, a))),
numbermoving = 2):
"""Programmer-friendly interface to the graph searching algorithm"""
assert numgroups == len(groupweights)
return graphmeup([False]*numgroups, losestates, groupweights, verify, maxval, victoryverify, numbermoving)
def graphmeup(state, losestates, groupweights, verify, maxval, victoryverify, numbermoving):
"""Searches for and returns a solution required to move all items across the river."""
searchedstates = 0
pathqueue = []
pathqueue.append((0, [state]))
while pathqueue:
(totalweight, path) = pathqueue.pop(0)
node = path[-1] #the current state will be at the tail
searchedstates = searchedstates + 1
if victoryverify(node) and totalweight <= maxval:
#backtrack count is just number of searched states minus length of path
return (totalweight, path, searchedstates-len(path), searchedstates)
for (permutation, weight) in permute(verify, list(node), groupweights, numbermoving):
if (permutation in path or
totalweight > maxval or
permutation in losestates or
invertgroup(list(permutation)) in losestates):
#skip permutations we've already seen, are losers, or whose weight exceeds the limit
continue
newpath = list(path)
newpath.append(list(permutation))
pathqueue.append((totalweight+weight, newpath))
def invertgroup(group):
"""Flip all the values in the specified group and return it"""
return map(operator.not_, group)
def permute(verify, state, weights, changes = 2):
"""Generates possible next states for river crossing problems."""
for i in range(len(state)):
statecopy = list(state)
statecopy[i] = not(state[i])
for j in range(i+1, len(state)):
statecopy[j] = not(state[j])
if changes == 3: #I hate hardcoding this, but...
for k in range(j+1, len(state)):
statecopy[k] = not(state[k])
if verify(state, statecopy, i, j, k):
yield (statecopy, max(weights[i], weights[j]))
statecopy[k] = state[k]
if verify(state, statecopy, i, j, i):
yield (statecopy, max(weights[i], weights[j]))
statecopy[j] = state[j]
if verify(state, statecopy, i, i, i):
yield (statecopy, weights[i])
statecopy[i] = state[i]
def prettyprint(solution):
"""Prints out detailed information on the solution found."""
if solution == None:
print("No solution found\n--------------------------------")
return
(weight, path, backtracks, searchedstates) = solution
print('''Path taken: %s
Cost: %s
Path length: %s
Backtrack count: %s
States searched: %s
--------------------------------''' % (path, weight, len(path), backtracks, searchedstates))
def main():
#The huge blocks of true/false statements represent lose states.
prettyprint(graphme(4, [
[True, True, False, False],
[False, True, True, False],
[True, True, True, False]],
[1,1,1,1],
verify = lambda x, y, w, z, v: (x[-1] != y[-1]) and (y[w] == y[z] == y[-1])))
prettyprint(graphme(6, [
[True, True, True, False, False, False],
[True, True, True, True, False, False],
[True, True, True, True, True, False],
[True, True, True, False, True, False],
[True, True, True, False, False, True],
[True, True, True, False, True, True],
[True, True, False, True, False, False],
[True, True, False, False, True, False],
[True, True, False, False, False, True],
[True, False, True, True, False, False],
[True, False, True, False, True, False],
[True, False, True, False, False, True],
[False, True, True, True, False, False],
[False, True, True, False, True, False],
[False, True, True, False, False, True]],
[1,1,1,1,1,1]))
prettyprint(graphme(5,
[],
[1,2,5,8,1],
maxval = 15,
verify = lambda x, y, w, z, v: (x[-1] != y[-1]) and (y[v] == y[w] == y[z] == y[-1]) and ((w != z) or (w != v) or (z != v)),
numbermoving=3))
if __name__ == "__main__":
main() | [
"elpenguino@gmail.com"
] | elpenguino@gmail.com |
1b8b194ca550a0ed437116814126fd3470715067 | 049c5392123d9e2e3865f75464a8e1788836242c | /venv/lib/python3.9/site-packages/dimod/utilities.py | a900713b2ddd8b5363edff00c1731ffafa9fc7cf | [] | no_license | KiaKafaei1/MasterProject | ec97d801d1d7f0872d3ff5bbdf7e644a2bddc963 | 1020c6c66d4f35b6f9affb302d31722de5e34979 | refs/heads/master | 2023-08-28T12:15:11.579203 | 2021-11-13T10:05:28 | 2021-11-13T10:05:28 | 289,909,672 | 0 | 0 | null | 2020-09-11T09:12:06 | 2020-08-24T11:31:36 | Python | UTF-8 | Python | false | false | 19,977 | py | # Copyright 2018 D-Wave Systems Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# =============================================================================
import copy
import os
import itertools
from functools import reduce
import numpy as np
from dimod.decorators import lockable_method
__all__ = ['ising_energy',
'qubo_energy',
'ising_to_qubo',
'qubo_to_ising',
'child_structure_dfs',
'get_include',
]
def ising_energy(sample, h, J, offset=0.0):
"""Calculate the energy for the specified sample of an Ising model.
Energy of a sample for a binary quadratic model is defined as a sum, offset
by the constant energy offset associated with the model, of
the sample multipled by the linear bias of the variable and
all its interactions. For an Ising model,
.. math::
E(\mathbf{s}) = \sum_v h_v s_v + \sum_{u,v} J_{u,v} s_u s_v + c
where :math:`s_v` is the sample, :math:`h_v` is the linear bias, :math:`J_{u,v}`
the quadratic bias (interactions), and :math:`c` the energy offset.
Args:
sample (dict[variable, spin]):
Sample for a binary quadratic model as a dict of form {v: spin, ...},
where keys are variables of the model and values are spins (either -1 or 1).
h (dict[variable, bias]):
Linear biases as a dict of the form {v: bias, ...}, where keys are variables of
the model and values are biases.
J (dict[(variable, variable), bias]):
Quadratic biases as a dict of the form {(u, v): bias, ...}, where keys
are 2-tuples of variables of the model and values are quadratic biases
associated with the pair of variables (the interaction).
offset (numeric, optional, default=0):
Constant offset to be applied to the energy. Default 0.
Returns:
float: The induced energy.
Notes:
No input checking is performed.
Examples:
This example calculates the energy of a sample representing two down spins for
an Ising model of two variables that have positive biases of value 1 and
are positively coupled with an interaction of value 1.
>>> sample = {1: -1, 2: -1}
>>> h = {1: 1, 2: 1}
>>> J = {(1, 2): 1}
>>> dimod.ising_energy(sample, h, J, 0.5)
-0.5
References
----------
`Ising model on Wikipedia <https://en.wikipedia.org/wiki/Ising_model>`_
"""
# add the contribution from the linear biases
for v in h:
offset += h[v] * sample[v]
# add the contribution from the quadratic biases
for v0, v1 in J:
offset += J[(v0, v1)] * sample[v0] * sample[v1]
return offset
def qubo_energy(sample, Q, offset=0.0):
"""Calculate the energy for the specified sample of a QUBO model.
Energy of a sample for a binary quadratic model is defined as a sum, offset
by the constant energy offset associated with the model, of
the sample multipled by the linear bias of the variable and
all its interactions. For a quadratic unconstrained binary optimization (QUBO)
model,
.. math::
E(\mathbf{x}) = \sum_{u,v} Q_{u,v} x_u x_v + c
where :math:`x_v` is the sample, :math:`Q_{u,v}`
a matrix of biases, and :math:`c` the energy offset.
Args:
sample (dict[variable, spin]):
Sample for a binary quadratic model as a dict of form {v: bin, ...},
where keys are variables of the model and values are binary (either 0 or 1).
Q (dict[(variable, variable), coefficient]):
QUBO coefficients in a dict of form {(u, v): coefficient, ...}, where keys
are 2-tuples of variables of the model and values are biases
associated with the pair of variables. Tuples (u, v) represent interactions
and (v, v) linear biases.
offset (numeric, optional, default=0):
Constant offset to be applied to the energy. Default 0.
Returns:
float: The induced energy.
Notes:
No input checking is performed.
Examples:
This example calculates the energy of a sample representing two zeros for
a QUBO model of two variables that have positive biases of value 1 and
are positively coupled with an interaction of value 1.
>>> sample = {1: 0, 2: 0}
>>> Q = {(1, 1): 1, (2, 2): 1, (1, 2): 1}
>>> dimod.qubo_energy(sample, Q, 0.5)
0.5
References
----------
`QUBO model on Wikipedia <https://en.wikipedia.org/wiki/Quadratic_unconstrained_binary_optimization>`_
"""
for v0, v1 in Q:
offset += sample[v0] * sample[v1] * Q[(v0, v1)]
return offset
def ising_to_qubo(h, J, offset=0.0):
"""Convert an Ising problem to a QUBO problem.
Map an Ising model defined on spins (variables with {-1, +1} values) to quadratic
unconstrained binary optimization (QUBO) formulation :math:`x' Q x` defined over
binary variables (0 or 1 values), where the linear term is contained along the diagonal of Q.
Return matrix Q that defines the model as well as the offset in energy between the two
problem formulations:
.. math::
s' J s + h' s = offset + x' Q x
See :meth:`~dimod.utilities.qubo_to_ising` for the inverse function.
Args:
h (dict[variable, bias]):
Linear biases as a dict of the form {v: bias, ...}, where keys are variables of
the model and values are biases.
J (dict[(variable, variable), bias]):
Quadratic biases as a dict of the form {(u, v): bias, ...}, where keys
are 2-tuples of variables of the model and values are quadratic biases
associated with the pair of variables (the interaction).
offset (numeric, optional, default=0):
Constant offset to be applied to the energy. Default 0.
Returns:
(dict, float): A 2-tuple containing:
dict: QUBO coefficients.
float: New energy offset.
Examples:
This example converts an Ising problem of two variables that have positive
biases of value 1 and are positively coupled with an interaction of value 1
to a QUBO problem and prints the resulting energy offset.
>>> h = {1: 1, 2: 1}
>>> J = {(1, 2): 1}
>>> dimod.ising_to_qubo(h, J, 0.5)[1]
-0.5
"""
# the linear biases are the easiest
q = {(v, v): 2. * bias for v, bias in h.items()}
# next the quadratic biases
for (u, v), bias in J.items():
if bias == 0.0:
continue
q[(u, v)] = 4. * bias
q[(u, u)] = q.setdefault((u, u), 0) - 2. * bias
q[(v, v)] = q.setdefault((v, v), 0) - 2. * bias
# finally calculate the offset
offset += sum(J.values()) - sum(h.values())
return q, offset
def qubo_to_ising(Q, offset=0.0):
"""Convert a QUBO problem to an Ising problem.
Map a quadratic unconstrained binary optimization (QUBO) problem :math:`x' Q x`
defined over binary variables (0 or 1 values), where the linear term is contained along
the diagonal of Q, to an Ising model defined on spins (variables with {-1, +1} values).
Return h and J that define the Ising model as well as the offset in energy
between the two problem formulations:
.. math::
x' Q x = offset + s' J s + h' s
See :meth:`~dimod.utilities.ising_to_qubo` for the inverse function.
Args:
Q (dict[(variable, variable), coefficient]):
QUBO coefficients in a dict of form {(u, v): coefficient, ...}, where keys
are 2-tuples of variables of the model and values are biases
associated with the pair of variables. Tuples (u, v) represent interactions
and (v, v) linear biases.
offset (numeric, optional, default=0):
Constant offset to be applied to the energy. Default 0.
Returns:
(dict, dict, float): A 3-tuple containing:
dict: Linear coefficients of the Ising problem.
dict: Quadratic coefficients of the Ising problem.
float: New energy offset.
Examples:
This example converts a QUBO problem of two variables that have positive
biases of value 1 and are positively coupled with an interaction of value 1
to an Ising problem, and shows the new energy offset.
>>> Q = {(1, 1): 1, (2, 2): 1, (1, 2): 1}
>>> dimod.qubo_to_ising(Q, 0.5)[2]
1.75
"""
h = {}
J = {}
linear_offset = 0.0
quadratic_offset = 0.0
for (u, v), bias in Q.items():
if u == v:
if u in h:
h[u] += .5 * bias
else:
h[u] = .5 * bias
linear_offset += bias
else:
if bias != 0.0:
J[(u, v)] = .25 * bias
if u in h:
h[u] += .25 * bias
else:
h[u] = .25 * bias
if v in h:
h[v] += .25 * bias
else:
h[v] = .25 * bias
quadratic_offset += bias
offset += .5 * linear_offset + .25 * quadratic_offset
return h, J, offset
def resolve_label_conflict(mapping, old_labels=None, new_labels=None):
"""Resolve a self-labeling conflict by creating an intermediate labeling.
Args:
mapping (dict):
A dict mapping the current variable labels to new ones.
old_labels (set, optional, default=None):
The keys of mapping. Can be passed in for performance reasons. These are not checked.
new_labels (set, optional, default=None):
The values of mapping. Can be passed in for performance reasons. These are not checked.
Returns:
tuple: A 2-tuple containing:
dict: A map from the keys of mapping to an intermediate labeling
dict: A map from the intermediate labeling to the values of mapping.
"""
if old_labels is None:
old_labels = set(mapping)
if new_labels is None:
new_labels = set(mapping.values())
# counter will be used to generate the intermediate labels, as an easy optimization
# we start the counter with a high number because often variables are labeled by
# integers starting from 0
counter = itertools.count(2 * len(mapping))
old_to_intermediate = {}
intermediate_to_new = {}
for old, new in mapping.items():
if old == new:
# we can remove self-labels
continue
if old in new_labels or new in old_labels:
# try to get a new unique label
lbl = next(counter)
while lbl in new_labels or lbl in old_labels:
lbl = next(counter)
# add it to the mapping
old_to_intermediate[old] = lbl
intermediate_to_new[lbl] = new
else:
old_to_intermediate[old] = new
# don't need to add it to intermediate_to_new because it is a self-label
return old_to_intermediate, intermediate_to_new
def iter_safe_relabels(mapping, existing):
"""Iterator over "safe" intermediate relabelings.
Args:
mapping (dict):
A map from old labels to new.
existing (set):
A container of existing labels.
Yields:
dict: A "safe" relabelling.
"""
# put the new labels into a set for fast lookup, also ensures that the
# values are valid labels
try:
new_labels = set(mapping.values())
except TypeError:
raise ValueError("mapping targets must be hashable objects")
old_labels = mapping.keys()
for v in new_labels:
if v in existing and v not in old_labels:
msg = ("A variable cannot be relabeled {!r} without also "
"relabeling the existing variable of the same name")
raise ValueError(msg.format(v))
if any(v in new_labels for v in old_labels):
yield from resolve_label_conflict(mapping, old_labels, new_labels)
else:
yield mapping
def child_structure_dfs(sampler, seen=None):
"""Return the structure of a composed sampler using a depth-first search on its
children.
Args:
sampler (:obj:`.Sampler`):
:class:`.Structured` or composed sampler with at least
one structured child.
seen (set, optional, default=False):
IDs of already checked child samplers.
Returns:
:class:`~collections.namedtuple`: A named tuple of the form
`Structure(nodelist, edgelist, adjacency)`, where the 3-tuple values
are the :attr:`.Structured.nodelist`, :attr:`.Structured.edgelist`
and :attr:`.Structured.adjacency` attributes of the first structured
sampler found.
Raises:
ValueError: If no structured sampler is found.
Examples:
>>> sampler = dimod.TrackingComposite(
... dimod.StructureComposite(
... dimod.ExactSolver(), [0, 1], [(0, 1)]))
>>> print(dimod.child_structure_dfs(sampler).nodelist)
[0, 1]
"""
seen = set() if seen is None else seen
if sampler not in seen:
try:
return sampler.structure
except AttributeError:
# hasattr just tries to access anyway...
pass
seen.add(sampler)
for child in getattr(sampler, 'children', ()): # getattr handles samplers
if child in seen:
continue
try:
return child_structure_dfs(child, seen=seen)
except ValueError:
# tree has no child samplers
pass
raise ValueError("no structured sampler found")
class LockableDict(dict):
"""A dict that can turn writeablity on and off"""
# methods like update, clear etc are not wrappers for __setitem__,
# __delitem__ so they need to be overwritten
@property
def is_writeable(self):
return getattr(self, '_writeable', True)
@is_writeable.setter
def is_writeable(self, b):
self._writeable = bool(b)
@lockable_method
def __setitem__(self, key, value):
return super(LockableDict, self).__setitem__(key, value)
@lockable_method
def __delitem__(self, key):
return super(LockableDict, self).__delitem__(key)
def __deepcopy__(self, memo):
new = type(self)()
memo[id(self)] = new
new.update((copy.deepcopy(key, memo), copy.deepcopy(value, memo))
for key, value in self.items())
new.is_writeable = self.is_writeable
return new
@lockable_method
def clear(self):
return super(LockableDict, self).clear()
@lockable_method
def pop(self, *args, **kwargs):
return super(LockableDict, self).pop(*args, **kwargs)
@lockable_method
def popitem(self):
return super(LockableDict, self).popitem()
@lockable_method
def setdefault(self, *args, **kwargs):
return super(LockableDict, self).setdefault(*args, **kwargs)
@lockable_method
def update(self, *args, **kwargs):
return super(LockableDict, self).update(*args, **kwargs)
def get_include():
"""Return the directory with dimod's header files."""
return os.path.join(os.path.dirname(__file__), 'include')
def _astypearrays(arrays, requirements, min_itemsize, allowed_types):
# allowed types can only be numeric for now, see comment below
# todo: allow unsafe with warning controlled by kwarg?
# We need to get the dtype, and as far as I can tell the only way to do
# it for array-like is to actually cast to a numpy array
arrays = [np.asarray(arr) for arr in arrays]
# get the dtype we can promote to
dtype = reduce(np.promote_types, (arr.dtype for arr in arrays))
if not any(np.issubdtype(dtype, type_) for type_ in allowed_types):
# put together an appropriate error message
descriptors = []
if np.floating in allowed_types:
descriptors.append('floating')
if np.integer in allowed_types:
descriptors.append('integer')
elif np.unsignedinteger in allowed_types:
if np.signedinteger in allowed_types:
descriptors.append('integer')
else:
descriptors.append('unsigned integer')
elif np.signedinteger in allowed_types:
descriptors.append('signed integer')
raise TypeError(
"Cannot safely cast arrays to {} (given {})".format(
', '.join(descriptors),
', '.join(arr.dtype.name for arr in arrays)))
if min_itemsize is not None:
if min_itemsize >= 1:
size = str(2**int(np.ceil(np.log2(min_itemsize))))
else:
size = '1'
if np.issubdtype(dtype, np.unsignedinteger):
kind = 'u'
elif np.issubdtype(dtype, np.signedinteger):
kind = 'i'
elif np.issubdtype(dtype, np.floating):
kind = 'f'
else:
# we could instead read this from the type string, but it's kind of
# pandora's box, because there's also structured arrays, complex,
# etc. For now, let's just restrict to numeric.
raise RuntimeError("unexpected dtype")
dtype = np.promote_types(dtype, kind+size)
arrays = tuple(np.require(arr, dtype=dtype, requirements=requirements)
for arr in arrays)
if len(arrays) > 1:
return arrays
else:
return arrays[0]
# Not a public function (yet)
def asintegerarrays(*arrays, requirements=None, min_itemsize=None):
"""Cast the given array(s) to the same integer type.
Not a public function.
This is useful when calling cython functions.
Args:
*arrays (array-like): At least one array-like.
requirements (str/list[str], optional): See :func:`numpy.require`.
min_itemsize (int, optional):
The minimum itemsize (in bytes) for the output arrays.
Returns:
Numpy array(s) satisfying the above requirements. They will all have
the same dtype.
"""
# empty arrays are a problem because numy defaults them to float, so let's
# do a tiny bit of prechecking
arrays = [arr if len(arr) else np.asarray(arr, dtype=np.int8)
for arr in arrays]
if not arrays:
raise TypeError('asintegerarrays() takes at least 1 array (0 given)')
return _astypearrays(arrays, requirements, min_itemsize, [np.integer])
# Not a public function (yet)
def asnumericarrays(*arrays, requirements=None, min_itemsize=None):
"""Cast the given array(s) to the same floating type.
Not a public function.
This is useful when calling cython functions.
Args:
*arrays (array-like): At least one array-like.
requirements (str/list[str], optional): See :func:`numpy.require`.
min_itemsize (int, optional):
The minimum itemsize (in bytes) for the output arrays.
Returns:
Numpy array(s) satisfying the above requirements. They will all have
the same dtype.
"""
if not arrays:
raise TypeError('asnumericarrays() takes at least 1 array (0 given)')
return _astypearrays(arrays, requirements, min_itemsize,
[np.integer, np.floating])
| [
"kia0896@yahoo.dk"
] | kia0896@yahoo.dk |
a4c1a9242bba0717fb4e57280314b144d76d42b9 | e96e89ff40324fe099cd5aab73563308b66e6d52 | /part4/recognize_face.py | 74777cdb8d96106f65cf8a52ef799679e41af96b | [] | no_license | chunxuwu/opencv3_python | 15898b4d7ee6978778df3e06ef4dfadec1190bbb | dfb6034f94abd4f65676d88516c1ff62cd12f73a | refs/heads/master | 2020-06-09T22:03:07.634080 | 2019-07-02T15:48:44 | 2019-07-02T15:48:44 | 193,514,974 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,325 | py | import cv2
import os
import numpy as np
# 建立标签
label_num = [0]
label_name = ["chunxu"]
images = []
labels = []
# 将图像数组和CSV文件加载到人脸识别的算法中
def read_images(path):
# 定义数据和标签
# 获取path文件下的文件及文件夹并返回名称列表
for dir_item in os.listdir(path):
# 返回path规范化的绝对路径
path_abs = os.path.abspath(os.path.join(path, dir_item))
# 判断path_abs是文件还是文件还是文件夹
try:
# str.endswith()是判断文件str后缀是否为指定格式
# 本图像指定为.pgm格式
if path_abs.endswith('.pgm'):
# print("try:", path_abs)
# 读取训练数据
img = cv2.imread(path_abs)
# 统一输入文件的尺寸大小
img = cv2.resize(img, (200, 200))
# 统一图像文件的元素dtype,并将其加入images中
images.append(np.asarray(img, dtype=np.uint8))
# 为训练数据赋标签
# 简单地可以用,当文件夹为me时，标签设置为0
# if(dir_item.endswith('gengyi')):
# labels.append(0)
# 为了代码更具有实用性，拟以下处理
# 先将path_abs分割,注意分割线\\,而不是//
path_piece = path_abs.split('\\')
# 为训练数据赋标签,较多标签通过elif追加即可
if label_name[0] in path_piece:
labels.append(label_num[0])
elif label_name[1] in path_piece:
labels.append(label_num[1])
elif label_name[2] in path_piece:
labels.append(label_num[2])
else:
# 没有对应标签则删除训练数据
images.pop()
# pass
# 若为文件夹则递归调用，循环读取子子文件内容
elif os.path.isdir(path_abs):
read_images(path_abs)
# 若为其他情况则循环运行
else:
continue
# 当发生异常时则抛出异常信息e
except Exception as e:
print("REASON:", e)
print('labels:', labels)
print("images:", images)
return images, labels
# 基于Eigenfaces的模型训练
def face_model():
# 使用label_num作为全局变量
# 每当脚本识别出一个ID，就会将相应名称数组中的名字打印到人脸上
global label_num
# 获取文件所在文件夹的绝对路径
path = os.getcwd()
# 调用图像读入函数，获取训练数据及标签
images, labels = read_images(path)
# print("face_model_images:", images)
# 实例化人脸识别模型
model = cv2.face.EigenFaceRecognizer_create()
# 通过图像数组和标签来训练模型
model.train(np.asarray(images), np.asarray(labels))
return model
def face_rec():
# 调用训练好的模型
face_model_trained = face_model()
# 初始化摄像头
camera = cv2.VideoCapture(0)
# 实例化人脸识别级联分类器
face_cascade = cv2.CascadeClassifier('./haarcascades/haarcascade_frontalface_default.xml')
while True:
read, img = camera.read()
faces = face_cascade.detectMultiScale(img, 1.3, 5)
for (x, y, w, h) in faces:
img = cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
roi = gray[x:x + w, y:y + h]
try:
roi = cv2.resize(roi, (200, 200), interpolation=cv2.INTER_LINEAR)
# predict()预测函数，返回预测标签和置信度
params = face_model_trained.predict(roi)
print("Label: %s, confidence: %0.2f" % (label_name[params[0]], params[1]))
cv2.putText(img, label_name[params[0]], (x, y - 20), cv2.FONT_HERSHEY_SIMPLEX, 3, (255, 0, 0), 2)
except Exception as e:
print("face_rec_REASON:", e)
cv2.imshow('camera', img)
if cv2.waitKey(10) & 0xff == ord('q'):
break
cv2.destroyAllWindows()
if __name__ == '__main__':
face_rec()
| [
"chunxuwu_zjut@163.com"
] | chunxuwu_zjut@163.com |
1d64866e18bbd874d1be4840170e198249a642dc | 3f97b3718cf3db745235d3e46abc775ac9fc0ea7 | /app/y2020/d10_adapter_array.py | 74bafc570e9a0b7317c55d7e2266ab070f0d29e9 | [] | no_license | bolmstedt/advent-of-code-python | ce48f7c90fe3861bc7947e3bc918d49166233fe8 | b1e7f12318c5bd642dfe29f862680f51c0f66bb5 | refs/heads/master | 2023-01-27T14:26:00.365229 | 2020-12-12T00:43:04 | 2020-12-12T00:43:04 | 317,562,248 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,251 | py | """Solution for day 10, 2020."""
import collections
from typing import Dict, List, Set, Union
from app.base_solver import BaseSolver
class Solver(BaseSolver):
"""Solver for day 10, 2020."""
day = '10'
year = '2020'
name = r"""Adapter Array"""
def part_one(self, data: str) -> Union[int, str]:
"""Solve part one."""
jumps: Dict[int, int] = collections.defaultdict(int)
adapters = self._parse_input(data)
sequence = collections.deque(adapters[:1], 2)
for adapter in adapters[1:]:
sequence.append(adapter)
jumps[sequence[1] - sequence[0]] += 1
return jumps[1] * jumps[3]
def part_two(self, data: str) -> Union[int, str]:
"""Solve part two."""
return self._solve_part_two(
self._get_branches(self._parse_input(data)),
{},
)
@staticmethod
def _get_branches(adapters: List[int]) -> Dict[int, Set[int]]:
branches = collections.defaultdict(set)
for index, adapter in enumerate(adapters):
max_jump = adapter + 3
for upcoming in adapters[index + 2:index + 4]:
if upcoming <= max_jump:
branches[adapter].add(upcoming)
return branches
@classmethod
def _solve_part_two(
cls,
branches: Dict[int, Set[int]],
solved: Dict[Union[int, str], int],
start: int = 0,
) -> int:
if start not in solved:
arrangements = 1
for adapter, jumps in branches.items():
if adapter < start:
continue
for jump in jumps:
branch = f'{adapter}:{jump}'
if branch not in solved:
solved[branch] = cls._solve_part_two(
branches,
solved,
jump,
)
arrangements += solved[branch]
solved[start] = arrangements
return solved[start]
@classmethod
def _parse_input(cls, data: str) -> List[int]:
adapters = cls._parse_int_lines(data)
return sorted(adapters + [0, max(adapters) + 3])
| [
"marcus@bolmstedt.com"
] | marcus@bolmstedt.com |
9a79bc2d121ab5020b5787e81900966444fc6e38 | 76fefdb20c453e830b8db86f32a1b42d79108cdd | /venv/bin/django-admin.py | a02fc84b3fe69bf065a0bd2537f44fe524e8d4d0 | [] | no_license | Belie06Loryn/chaty-final-master | 35f6762e9bf45e1086db6280cd0bd7dc0828fb96 | 86e839c069eb54dad3390e84c6b7534d165a3942 | refs/heads/master | 2022-12-09T14:31:19.478090 | 2019-12-08T16:00:45 | 2019-12-08T16:00:45 | 226,365,156 | 0 | 0 | null | 2022-12-08T06:59:44 | 2019-12-06T16:08:51 | Python | UTF-8 | Python | false | false | 166 | py | #!/home/alexie/Documents/chaty-final-master/venv/bin/python
from django.core import management
if __name__ == "__main__":
management.execute_from_command_line()
| [
"maniralexie@gmail.com"
] | maniralexie@gmail.com |
73b8eea0e247cc2fb5986af3fd0beca8578749f2 | f0d713996eb095bcdc701f3fab0a8110b8541cbb | /E9FwvGyad5CDbiH4C_9.py | d750b3eefe4c93d1c5db878cb337dcc042cf9e95 | [] | no_license | daniel-reich/turbo-robot | feda6c0523bb83ab8954b6d06302bfec5b16ebdf | a7a25c63097674c0a81675eed7e6b763785f1c41 | refs/heads/main | 2023-03-26T01:55:14.210264 | 2021-03-23T16:08:01 | 2021-03-23T16:08:01 | 350,773,815 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,348 | py | """
Create a function that takes a 2D array as an argument and returns the number
of people whose view is blocked by a tall person. The concert stage is pointed
towards the top of the 2D array and the tall person (represented by a 2)
blocks the view of all the people (represented by a 1) behind them.
### Examples
block([
[1, 1, 1, 1, 1],
[1, 1, 1, 1, 1],
[1, 1, 1, 1, 2],
[1, 1, 1, 1, 1],
[1, 1, 1, 1, 1]
]) ➞ 2
# The tall person blocks 2 people behind him thus
# the function returns 2.
block([
[1, 2, 1, 1],
[1, 1, 1, 2],
[1, 1, 1, 1],
[1, 1, 1, 1],
]) ➞ 5
# There are 2 tall people that block everyone behind
# them. The first tall person in the first row blocks 3
# people behind him while the second tall person in
# the second row blocks 2 people behind him thus the
# function returns 5.
block([
[1, 1, 1, 1],
[2, 1, 1, 2],
[1, 1, 1, 1],
[1, 1, 1, 1],
]) ➞ 4
### Notes
1. There is only a maximum of 1 tall person in every column.
2. No view is blocked if the tall person is in the last row.
"""
def block(lst):
total = 0
for x in range(len(lst[0])):
for y in range(len(lst)-1, 0, -1):
if lst[y][x] < lst[y-1][x]:
total += len(lst) - y
return total
| [
"daniel.reich@danielreichs-MacBook-Pro.local"
] | daniel.reich@danielreichs-MacBook-Pro.local |
5c354b1c02a7628a71303fea1386ada6e1ca5032 | cb4b3f85237354ea385d1fa3447af08cab0bab60 | /web/server/codechecker_server/api/mass_store_run.py | 8f1ab79c2afd13e72d80f76189e833deadd6990e | [
"LLVM-exception",
"Apache-2.0"
] | permissive | hanwoody/codechecker | dece3ac6068f7b8163e976819abe5458279fcc53 | f3ba8fd9a5ebafbe95715a515ff271708c6e8446 | refs/heads/master | 2023-06-20T09:27:39.181804 | 2021-07-08T08:23:40 | 2021-07-08T08:23:40 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 48,981 | py | # -------------------------------------------------------------------------
#
# Part of the CodeChecker project, under the Apache License v2.0 with
# LLVM Exceptions. See LICENSE for license information.
# SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
#
# -------------------------------------------------------------------------
import base64
import os
import sqlalchemy
import tempfile
import time
import zipfile
import zlib
from collections import defaultdict
from datetime import datetime
from hashlib import sha256
from tempfile import TemporaryDirectory
from typing import Any, Dict, List, NamedTuple, Optional, Set
import codechecker_api_shared
from codechecker_api.codeCheckerDBAccess_v6 import ttypes
from codechecker_common import plist_parser, skiplist_handler, util
from codechecker_common.logger import get_logger
from codechecker_common.source_code_comment_handler import \
SourceCodeCommentHandler, SpellException, contains_codechecker_comment
from codechecker_report_hash.hash import get_report_path_hash
from ..database import db_cleanup
from ..database.config_db_model import Product
from ..database.database import DBSession
from ..database.run_db_model import AnalysisInfo, AnalyzerStatistic, \
BugPathEvent, BugReportPoint, ExtendedReportData, File, FileContent, \
Report, Run, RunHistory, RunLock
from ..metadata import checker_is_unavailable, get_analyzer_name, \
MetadataInfoParser
from .report_server import ThriftRequestHandler
from .thrift_enum_helper import report_extended_data_type_str
LOG = get_logger('server')
# FIXME: when these types are introduced we need to use those.
SourceLineComments = List[Any]
ReportType = Any
MainSection = Dict
class PathEvents(NamedTuple):
paths: List[ttypes.BugPathPos]
events: List[ttypes.BugPathEvent]
extended_data: List[ttypes.ExtendedReportData]
def unzip(b64zip: str, output_dir: str) -> int:
"""
This function unzips the base64 encoded zip file. This zip is extracted
to a temporary directory and the ZIP is then deleted. The function returns
the size of the extracted decompressed zip file.
"""
if len(b64zip) == 0:
return 0
with tempfile.NamedTemporaryFile(suffix='.zip') as zip_file:
LOG.debug("Unzipping mass storage ZIP '%s' to '%s'...",
zip_file.name, output_dir)
zip_file.write(zlib.decompress(base64.b64decode(b64zip)))
with zipfile.ZipFile(zip_file, 'r', allowZip64=True) as zipf:
try:
zipf.extractall(output_dir)
return os.stat(zip_file.name).st_size
except Exception:
LOG.error("Failed to extract received ZIP.")
import traceback
traceback.print_exc()
raise
return 0
def get_file_content(file_path: str) -> bytes:
"""Return the file content for the given filepath. """
with open(file_path, 'rb') as f:
return f.read()
def parse_codechecker_review_comment(
source_file_name: str,
report_line: int,
checker_name: str
) -> SourceLineComments:
"""Parse the CodeChecker review comments from a source file at a given
position. Returns an empty list if there are no comments.
"""
src_comment_data = []
with open(source_file_name, encoding='utf-8', errors='ignore') as f:
if contains_codechecker_comment(f):
sc_handler = SourceCodeCommentHandler()
try:
src_comment_data = sc_handler.filter_source_line_comments(
f, report_line, checker_name)
except SpellException as ex:
LOG.warning("File %s contains %s", source_file_name, ex)
return src_comment_data
def collect_paths_events(
report: ReportType,
file_ids: Dict[str, int],
files: Dict[str, str]
) -> PathEvents:
"""
This function creates the BugPathPos and BugPathEvent objects which belong
to a report.
report -- A report object from the parsed plist file.
file_ids -- A dictionary which maps the file paths to file IDs in the
database.
files -- A list containing the file paths from the parsed plist file. The
order of this list must be the same as in the plist file.
#TODO Multiple ranges could belong to an event or control node.
Only the first range from the list of ranges is stored into the
database. Further improvement can be to store and view all ranges
if there are more than one.
"""
path_events = PathEvents([], [], [])
events = [i for i in report.bug_path if i.get('kind') == 'event']
# Create remaining data for bugs and send them to the server. In plist
# file the source and target of the arrows are provided as starting and
# ending ranges of the arrow. The path A->B->C is given as A->B and
# B->C, thus range B is provided twice. So in the loop only target
# points of the arrows are stored, and an extra insertion is done for
# the source of the first arrow before the loop.
report_path = [i for i in report.bug_path if i.get('kind') == 'control']
if report_path:
start_range = report_path[0]['edges'][0]['start']
start1_line = start_range[0]['line']
start1_col = start_range[0]['col']
start2_line = start_range[1]['line']
start2_col = start_range[1]['col']
source_file_path = files[start_range[1]['file']]
path_events.paths.append(ttypes.BugPathPos(
start1_line,
start1_col,
start2_line,
start2_col,
file_ids[source_file_path]))
for path in report_path:
try:
end_range = path['edges'][0]['end']
end1_line = end_range[0]['line']
end1_col = end_range[0]['col']
end2_line = end_range[1]['line']
end2_col = end_range[1]['col']
source_file_path = files[end_range[1]['file']]
path_events.paths.append(ttypes.BugPathPos(
end1_line,
end1_col,
end2_line,
end2_col,
file_ids[source_file_path]))
except IndexError:
# Edges might be empty nothing can be stored.
continue
for event in events:
file_path = files[event['location']['file']]
start_loc = event['location']
end_loc = event['location']
# Range can provide more precise location information.
# Use that if available.
ranges = event.get("ranges")
if ranges:
start_loc = ranges[0][0]
end_loc = ranges[0][1]
path_events.events.append(ttypes.BugPathEvent(
start_loc['line'],
start_loc['col'],
end_loc['line'],
end_loc['col'],
event['message'],
file_ids[file_path]))
for macro in report.macro_expansions:
if not macro['expansion']:
continue
file_path = files[macro['location']['file']]
start_loc = macro['location']
end_loc = macro['location']
# Range can provide more precise location information.
# Use that if available.
ranges = macro.get("ranges")
if ranges:
start_loc = ranges[0][0]
end_loc = ranges[0][1]
path_events.extended_data.append(ttypes.ExtendedReportData(
ttypes.ExtendedReportDataType.MACRO,
start_loc['line'],
start_loc['col'],
end_loc['line'],
end_loc['col'],
macro['expansion'],
file_ids[file_path]))
for note in report.notes:
if not note['message']:
continue
file_path = files[note['location']['file']]
start_loc = note['location']
end_loc = note['location']
# Range can provide more precise location information.
# Use that if available.
ranges = note.get("ranges")
if ranges:
start_loc = ranges[0][0]
end_loc = ranges[0][1]
path_events.extended_data.append(ttypes.ExtendedReportData(
ttypes.ExtendedReportDataType.NOTE,
start_loc['line'],
start_loc['col'],
end_loc['line'],
end_loc['col'],
note['message'],
file_ids[file_path]))
return path_events
def add_file_record(
session: DBSession,
file_path: str,
content_hash: str
) -> Optional[int]:
"""
Add the necessary file record pointing to an already existing content.
Returns the added file record id or None, if the content_hash is not
found.
This function must not be called between add_checker_run() and
finish_checker_run() functions when SQLite database is used!
add_checker_run() function opens a transaction which is closed by
finish_checker_run() and since SQLite doesn't support parallel
transactions, this API call will wait until the other transactions
finish. In the meantime the run adding transaction times out.
"""
file_record = session.query(File) \
.filter(File.content_hash == content_hash,
File.filepath == file_path) \
.one_or_none()
if file_record:
return file_record.id
try:
file_record = File(file_path, content_hash)
session.add(file_record)
session.commit()
except sqlalchemy.exc.IntegrityError as ex:
LOG.error(ex)
# Other transaction might have added the same file in the
# meantime.
session.rollback()
file_record = session.query(File) \
.filter(File.content_hash == content_hash,
File.filepath == file_path).one_or_none()
return file_record.id if file_record else None
class MassStoreRun:
def __init__(
self,
report_server: ThriftRequestHandler,
name: str,
tag: Optional[str],
version: Optional[str],
b64zip: str,
force: bool,
trim_path_prefixes: Optional[List[str]],
description: Optional[str]
):
""" Initialize object. """
self.__report_server = report_server
self.__name = name
self.__tag = tag
self.__version = version
self.__b64zip = b64zip
self.__force = force
self.__trim_path_prefixes = trim_path_prefixes
self.__description = description
self.__mips: Dict[str, MetadataInfoParser] = {}
self.__analysis_info: Dict[str, AnalysisInfo] = {}
self.__duration: int = 0
self.__wrong_src_code_comments: List[str] = []
self.__already_added_report_hashes: Set[str] = set()
self.__new_report_hashes: Set[str] = set()
self.__all_report_checkers: Set[str] = set()
@property
def __manager(self):
return self.__report_server._manager
@property
def __Session(self):
return self.__report_server._Session
@property
def __config_database(self):
return self.__report_server._config_database
@property
def __product(self):
return self.__report_server._product
@property
def __context(self):
return self.__report_server._context
@property
def user_name(self):
return self.__report_server._get_username()
def __check_run_limit(self):
"""
Checks the maximum allowed of uploadable runs for the current product.
"""
max_run_count = self.__manager.get_max_run_count()
with DBSession(self.__config_database) as session:
product = session.query(Product).get(self.__product.id)
if product.run_limit:
max_run_count = product.run_limit
# Session that handles constraints on the run.
with DBSession(self.__Session) as session:
if not max_run_count:
return
LOG.debug("Check the maximum number of allowed runs which is %d",
max_run_count)
run = session.query(Run) \
.filter(Run.name == self.__name) \
.one_or_none()
# If max_run_count is not set in the config file, it will allow
# the user to upload unlimited runs.
run_count = session.query(Run.id).count()
# If we are not updating a run or the run count is reached the
# limit it will throw an exception.
if not run and run_count >= max_run_count:
remove_run_count = run_count - max_run_count + 1
raise codechecker_api_shared.ttypes.RequestFailed(
codechecker_api_shared.ttypes.ErrorCode.GENERAL,
f"You reached the maximum number of allowed runs "
f"({run_count}/{max_run_count})! Please remove at least "
f"{remove_run_count} run(s) before you try it again.")
def __store_run_lock(self, session: DBSession):
"""
Store a RunLock record for the given run name into the database.
"""
try:
# If the run can be stored, we need to lock it first. If there is
# already a lock in the database for the given run name which is
# expired and multiple processes are trying to get this entry from
# the database for update we may get the following exception:
# could not obtain lock on row in relation "run_locks"
# This is the reason why we have to wrap this query to a try/except
# block.
run_lock = session.query(RunLock) \
.filter(RunLock.name == self.__name) \
.with_for_update(nowait=True).one_or_none()
except (sqlalchemy.exc.OperationalError,
sqlalchemy.exc.ProgrammingError) as ex:
LOG.error("Failed to get run lock for '%s': %s", self.__name, ex)
raise codechecker_api_shared.ttypes.RequestFailed(
codechecker_api_shared.ttypes.ErrorCode.DATABASE,
"Someone is already storing to the same run. Please wait "
"while the other storage is finished and try it again.")
if not run_lock:
# If there is no lock record for the given run name, the run
# is not locked -- create a new lock.
run_lock = RunLock(self.__name, self.user_name)
session.add(run_lock)
elif run_lock.has_expired(
db_cleanup.RUN_LOCK_TIMEOUT_IN_DATABASE):
# There can be a lock in the database, which has already
# expired. In this case, we assume that the previous operation
# has failed, and thus, we can re-use the already present lock.
run_lock.touch()
run_lock.username = self.user_name
else:
# In case the lock exists and it has not expired, we must
# consider the run a locked one.
when = run_lock.when_expires(
db_cleanup.RUN_LOCK_TIMEOUT_IN_DATABASE)
username = run_lock.username if run_lock.username is not None \
else "another user"
LOG.info("Refusing to store into run '%s' as it is locked by "
"%s. Lock will expire at '%s'.", self.__name, username,
when)
raise codechecker_api_shared.ttypes.RequestFailed(
codechecker_api_shared.ttypes.ErrorCode.DATABASE,
"The run named '{0}' is being stored into by {1}. If the "
"other store operation has failed, this lock will expire "
"at '{2}'.".format(self.__name, username, when))
# At any rate, if the lock has been created or updated, commit it
# into the database.
try:
session.commit()
except (sqlalchemy.exc.IntegrityError,
sqlalchemy.orm.exc.StaleDataError):
# The commit of this lock can fail.
#
# In case two store ops attempt to lock the same run name at the
# same time, committing the lock in the transaction that commits
# later will result in an IntegrityError due to the primary key
# constraint.
#
# In case two store ops attempt to lock the same run name with
# reuse and one of the operation hangs long enough before COMMIT
# so that the other operation commits and thus removes the lock
# record, StaleDataError is raised. In this case, also consider
# the run locked, as the data changed while the transaction was
# waiting, as another run wholly completed.
LOG.info("Run '%s' got locked while current transaction "
"tried to acquire a lock. Considering run as locked.",
self.__name)
raise codechecker_api_shared.ttypes.RequestFailed(
codechecker_api_shared.ttypes.ErrorCode.DATABASE,
"The run named '{0}' is being stored into by another "
"user.".format(self.__name))
def __free_run_lock(self, session: DBSession):
""" Remove the lock from the database for the given run name. """
# Using with_for_update() here so the database (in case it supports
# this operation) locks the lock record's row from any other access.
run_lock = session.query(RunLock) \
.filter(RunLock.name == self.__name) \
.with_for_update(nowait=True).one()
session.delete(run_lock)
session.commit()
def __store_source_files(
self,
source_root: str,
filename_to_hash: Dict[str, str]
) -> Dict[str, int]:
""" Storing file contents from plist. """
file_path_to_id = {}
for file_name, file_hash in filename_to_hash.items():
source_file_name = os.path.join(source_root, file_name.strip("/"))
source_file_name = os.path.realpath(source_file_name)
LOG.debug("Storing source file: %s", source_file_name)
trimmed_file_path = util.trim_path_prefixes(
file_name, self.__trim_path_prefixes)
if not os.path.isfile(source_file_name):
# The file was not in the ZIP file, because we already
# have the content. Let's check if we already have a file
# record in the database or we need to add one.
LOG.debug('%s not found or already stored.', trimmed_file_path)
with DBSession(self.__Session) as session:
fid = add_file_record(
session, trimmed_file_path, file_hash)
if not fid:
LOG.error("File ID for %s is not found in the DB with "
"content hash %s. Missing from ZIP?",
source_file_name, file_hash)
file_path_to_id[trimmed_file_path] = fid
LOG.debug("%d fileid found", fid)
continue
with DBSession(self.__Session) as session:
file_path_to_id[trimmed_file_path] = self.__add_file_content(
session, trimmed_file_path, source_file_name, file_hash)
return file_path_to_id
def __add_file_content(
self,
session: DBSession,
file_path: str,
source_file_name: str,
content_hash: str
) -> int:
"""
Add the necessary file contents. If the file is already stored in the
database then its ID returns. If content_hash in None then this
function calculates the content hash. Or if is available at the caller
and is provided then it will not be calculated again.
This function must not be called between add_checker_run() and
finish_checker_run() functions when SQLite database is used!
add_checker_run() function opens a transaction which is closed by
finish_checker_run() and since SQLite doesn't support parallel
transactions, this API call will wait until the other transactions
finish. In the meantime the run adding transaction times out.
"""
source_file_content = None
if not content_hash:
source_file_content = get_file_content(source_file_name)
hasher = sha256()
hasher.update(source_file_content)
content_hash = hasher.hexdigest()
file_content = session.query(FileContent).get(content_hash)
if not file_content:
if not source_file_content:
source_file_content = get_file_content(source_file_name)
try:
compressed_content = zlib.compress(source_file_content,
zlib.Z_BEST_COMPRESSION)
fc = FileContent(content_hash, compressed_content)
session.add(fc)
session.commit()
except sqlalchemy.exc.IntegrityError:
# Other transaction moght have added the same content in
# the meantime.
session.rollback()
file_record = session.query(File) \
.filter(File.content_hash == content_hash,
File.filepath == file_path) \
.one_or_none()
if not file_record:
try:
file_record = File(file_path, content_hash)
session.add(file_record)
session.commit()
except sqlalchemy.exc.IntegrityError as ex:
LOG.error(ex)
# Other transaction might have added the same file in the
# meantime.
session.rollback()
file_record = session.query(File) \
.filter(File.content_hash == content_hash,
File.filepath == file_path) \
.one_or_none()
return file_record.id
def __store_analysis_statistics(
self,
session: DBSession,
run_history_id: int
):
"""
Store analysis statistics for the given run history.
It will unique the statistics for each analyzer type based on the
metadata information.
"""
stats = defaultdict(lambda: {
"versions": set(),
"failed_sources": set(),
"successful_sources": set(),
"successful": 0
})
for mip in self.__mips.values():
self.__duration += int(sum(mip.check_durations))
for analyzer_type, res in mip.analyzer_statistics.items():
if "version" in res:
stats[analyzer_type]["versions"].add(res["version"])
if "failed_sources" in res:
if self.__version == '6.9.0':
stats[analyzer_type]["failed_sources"].add(
'Unavailable in CodeChecker 6.9.0!')
else:
stats[analyzer_type]["failed_sources"].update(
res["failed_sources"])
if "successful_sources" in res:
stats[analyzer_type]["successful_sources"].update(
res["successful_sources"])
if "successful" in res:
stats[analyzer_type]["successful"] += res["successful"]
for analyzer_type, stat in stats.items():
analyzer_version = None
if stat["versions"]:
analyzer_version = zlib.compress(
"; ".join(stat["versions"]).encode('utf-8'),
zlib.Z_BEST_COMPRESSION)
failed = 0
compressed_files = None
if stat["failed_sources"]:
compressed_files = zlib.compress(
'\n'.join(stat["failed_sources"]).encode('utf-8'),
zlib.Z_BEST_COMPRESSION)
failed = len(stat["failed_sources"])
successful = len(stat["successful_sources"]) \
if stat["successful_sources"] else stat["successful"]
analyzer_statistics = AnalyzerStatistic(
run_history_id, analyzer_type, analyzer_version,
successful, failed, compressed_files)
session.add(analyzer_statistics)
def __store_analysis_info(
self,
session: DBSession,
run_history: RunHistory
):
""" Store analysis info for the given run history. """
for src_dir_path, mip in self.__mips.items():
for analyzer_command in mip.check_commands:
cmd = zlib.compress(
analyzer_command.encode("utf-8"),
zlib.Z_BEST_COMPRESSION)
analysis_info_rows = session \
.query(AnalysisInfo) \
.filter(AnalysisInfo.analyzer_command == cmd) \
.all()
if analysis_info_rows:
# It is possible when multiple runs are stored
# simultaneously to the server with the same analysis
# command that multiple entries are stored into the
# database. In this case we will select the first one.
analysis_info = analysis_info_rows[0]
else:
analysis_info = AnalysisInfo(analyzer_command=cmd)
session.add(analysis_info)
run_history.analysis_info.append(analysis_info)
self.__analysis_info[src_dir_path] = analysis_info
def __add_checker_run(
self,
session: DBSession,
run_history_time: datetime
) -> int:
"""
Store run related data to the database.
By default updates the results if name already exists.
Using the force flag removes existing analysis results for a run.
"""
try:
LOG.debug("Adding run '%s'...", self.__name)
run = session.query(Run) \
.filter(Run.name == self.__name) \
.one_or_none()
if run and self.__force:
# Clean already collected results.
if not run.can_delete:
# Deletion is already in progress.
msg = f"Can't delete {run.id}"
LOG.debug(msg)
raise codechecker_api_shared.ttypes.RequestFailed(
codechecker_api_shared.ttypes.ErrorCode.DATABASE,
msg)
LOG.info('Removing previous analysis results...')
session.delete(run)
# Not flushing after delete leads to a constraint violation
# error later, when adding run entity with the same name as
# the old one.
session.flush()
checker_run = Run(self.__name, self.__version)
session.add(checker_run)
session.flush()
run_id = checker_run.id
elif run:
# There is already a run, update the results.
run.date = datetime.now()
run.duration = -1
session.flush()
run_id = run.id
else:
# There is no run create new.
checker_run = Run(self.__name, self.__version)
session.add(checker_run)
session.flush()
run_id = checker_run.id
# Add run to the history.
LOG.debug("Adding run history.")
if self.__tag is not None:
run_history = session.query(RunHistory) \
.filter(RunHistory.run_id == run_id,
RunHistory.version_tag == self.__tag) \
.one_or_none()
if run_history:
run_history.version_tag = None
session.add(run_history)
cc_versions = set()
for mip in self.__mips.values():
if mip.cc_version:
cc_versions.add(mip.cc_version)
cc_version = '; '.join(cc_versions) if cc_versions else None
run_history = RunHistory(
run_id, self.__tag, self.user_name, run_history_time,
cc_version, self.__description)
session.add(run_history)
session.flush()
LOG.debug("Adding run done.")
self.__store_analysis_statistics(session, run_history.id)
self.__store_analysis_info(session, run_history)
session.flush()
LOG.debug("Storing analysis statistics done.")
return run_id
except Exception as ex:
raise codechecker_api_shared.ttypes.RequestFailed(
codechecker_api_shared.ttypes.ErrorCode.GENERAL,
str(ex))
def __add_report(
self,
session: DBSession,
run_id: int,
file_id: int,
main_section: MainSection,
path_events: PathEvents,
detection_status: str,
detection_time: datetime,
analysis_info: AnalysisInfo,
analyzer_name: Optional[str] = None
) -> int:
""" Add report to the database. """
def store_bug_events(report_id: int):
""" Add bug path events. """
for i, event in enumerate(path_events.events):
bpe = BugPathEvent(
event.startLine, event.startCol, event.endLine,
event.endCol, i, event.msg, event.fileId, report_id)
session.add(bpe)
def store_bug_path(report_id: int):
""" Add bug path points. """
for i, piece in enumerate(path_events.paths):
brp = BugReportPoint(
piece.startLine, piece.startCol, piece.endLine,
piece.endCol, i, piece.fileId, report_id)
session.add(brp)
def store_extended_bug_data(report_id: int):
""" Add extended bug data objects to the database session. """
for data in path_events.extended_data:
data_type = report_extended_data_type_str(data.type)
red = ExtendedReportData(
data.startLine, data.startCol, data.endLine, data.endCol,
data.message, data.fileId, report_id, data_type)
session.add(red)
try:
checker_name = main_section['check_name']
severity_name = self.__context.severity_map.get(checker_name)
severity = ttypes.Severity._NAMES_TO_VALUES[severity_name]
report = Report(
run_id, main_section['issue_hash_content_of_line_in_context'],
file_id, main_section['description'],
checker_name or 'NOT FOUND',
main_section['category'], main_section['type'],
main_section['location']['line'],
main_section['location']['col'],
severity, detection_status, detection_time,
len(path_events.events), analyzer_name)
session.add(report)
session.flush()
LOG.debug("storing bug path")
store_bug_path(report.id)
LOG.debug("storing events")
store_bug_events(report.id)
LOG.debug("storing extended report data")
store_extended_bug_data(report.id)
if analysis_info:
report.analysis_info.append(analysis_info)
return report.id
except Exception as ex:
raise codechecker_api_shared.ttypes.RequestFailed(
codechecker_api_shared.ttypes.ErrorCode.GENERAL,
str(ex))
def __process_report_file(
self,
report_file_path: str,
session: DBSession,
source_root: str,
run_id: int,
file_path_to_id: Dict[str, int],
run_history_time: datetime,
skip_handler: Optional[skiplist_handler.SkipListHandler],
hash_map_reports: Dict[str, List[Any]]
) -> bool:
"""
Process and save reports from the given report file to the database.
"""
try:
files, reports = plist_parser.parse_plist_file(report_file_path)
except Exception as ex:
LOG.warning('Parsing the plist failed: %s', str(ex))
return False
if not reports:
return True
trimmed_files = {}
file_ids = {}
missing_ids_for_files = []
for k, v in files.items():
trimmed_files[k] = \
util.trim_path_prefixes(v, self.__trim_path_prefixes)
for file_name in trimmed_files.values():
file_id = file_path_to_id.get(file_name, -1)
if file_id == -1:
missing_ids_for_files.append(file_name)
continue
file_ids[file_name] = file_id
if missing_ids_for_files:
LOG.warning("Failed to get file path id for '%s'!",
' '.join(missing_ids_for_files))
return False
def set_review_status(report: ReportType):
"""
Set review status for the given report if there is any source code
comment.
"""
checker_name = report.main['check_name']
last_report_event = report.bug_path[-1]
# The original file path is needed here not the trimmed
# because the source files are extracted as the original
# file path.
file_name = files[last_report_event['location']['file']]
source_file_name = os.path.realpath(
os.path.join(source_root, file_name.strip("/")))
# Check and store source code comments.
if not os.path.isfile(source_file_name):
return
report_line = last_report_event['location']['line']
source_file = os.path.basename(file_name)
src_comment_data = parse_codechecker_review_comment(
source_file_name, report_line, checker_name)
if len(src_comment_data) == 1:
status = src_comment_data[0]['status']
rw_status = ttypes.ReviewStatus.FALSE_POSITIVE
if status == 'confirmed':
rw_status = ttypes.ReviewStatus.CONFIRMED
elif status == 'intentional':
rw_status = ttypes.ReviewStatus.INTENTIONAL
self.__report_server._setReviewStatus(
session, report.report_hash, rw_status,
src_comment_data[0]['message'], run_history_time)
elif len(src_comment_data) > 1:
LOG.warning(
"Multiple source code comment can be found "
"for '%s' checker in '%s' at line %s. "
"This bug will not be suppressed!",
checker_name, source_file, report_line)
self.__wrong_src_code_comments.append(
f"{source_file}|{report_line}|{checker_name}")
root_dir_path = os.path.dirname(report_file_path)
mip = self.__mips[root_dir_path]
analysis_info = self.__analysis_info.get(root_dir_path)
for report in reports:
self.__all_report_checkers.add(report.check_name)
if skip_handler and skip_handler.should_skip(report.file_path):
continue
report.trim_path_prefixes(self.__trim_path_prefixes)
report_path_hash = get_report_path_hash(report)
if report_path_hash in self.__already_added_report_hashes:
LOG.debug('Not storing report. Already added: %s', report)
continue
LOG.debug("Storing report to the database...")
bug_id = report.report_hash
detection_status = 'new'
detected_at = run_history_time
if bug_id in hash_map_reports:
old_report = hash_map_reports[bug_id][0]
old_status = old_report.detection_status
detection_status = 'reopened' \
if old_status == 'resolved' else 'unresolved'
detected_at = old_report.detected_at
analyzer_name = get_analyzer_name(
report.check_name, mip.checker_to_analyzer, report.metadata)
path_events = collect_paths_events(report, file_ids, trimmed_files)
report_id = self.__add_report(
session, run_id, file_ids[report.file_path], report.main,
path_events, detection_status, detected_at, analysis_info,
analyzer_name)
self.__new_report_hashes.add(bug_id)
self.__already_added_report_hashes.add(report_path_hash)
set_review_status(report)
LOG.debug("Storing report done. ID=%d", report_id)
return True
def __store_reports(
self,
session: DBSession,
report_dir: str,
source_root: str,
run_id: int,
file_path_to_id: Dict[str, int],
run_history_time: datetime
):
""" Parse up and store the plist report files. """
def get_skip_handler(
report_dir: str
) -> Optional[skiplist_handler.SkipListHandler]:
""" Get a skip list handler based on the given report directory."""
skip_file_path = os.path.join(report_dir, 'skip_file')
if not os.path.exists(skip_file_path):
return
LOG.debug("Pocessing skip file %s", skip_file_path)
try:
with open(skip_file_path,
encoding="utf-8", errors="ignore") as f:
skip_content = f.read()
LOG.debug(skip_content)
return skiplist_handler.SkipListHandler(skip_content)
except (IOError, OSError) as err:
LOG.warning("Failed to open skip file: %s", err)
# Reset internal data.
self.__already_added_report_hashes = set()
self.__new_report_hashes = set()
self.__all_report_checkers = set()
all_reports = session.query(Report) \
.filter(Report.run_id == run_id) \
.all()
hash_map_reports = defaultdict(list)
for report in all_reports:
hash_map_reports[report.bug_id].append(report)
enabled_checkers: Set[str] = set()
disabled_checkers: Set[str] = set()
# Processing PList files.
for root_dir_path, _, report_file_paths in os.walk(report_dir):
LOG.debug("Get reports from '%s' directory", root_dir_path)
skip_handler = get_skip_handler(root_dir_path)
mip = self.__mips[root_dir_path]
enabled_checkers.update(mip.enabled_checkers)
disabled_checkers.update(mip.disabled_checkers)
for f in report_file_paths:
if not f.endswith('.plist'):
continue
LOG.debug("Parsing input file '%s'", f)
report_file_path = os.path.join(root_dir_path, f)
self.__process_report_file(
report_file_path, session, source_root, run_id,
file_path_to_id, run_history_time,
skip_handler, hash_map_reports)
# If a checker was found in a plist file it can not be disabled so we
# will add this to the enabled checkers list and remove this checker
# from the disabled checkers list.
# Also if multiple report directories are stored and a checker was
# enabled in one report directory but it was disabled in another
# directory we will mark this checker as enabled.
enabled_checkers |= self.__all_report_checkers
disabled_checkers -= self.__all_report_checkers
reports_to_delete = set()
for bug_hash, reports in hash_map_reports.items():
if bug_hash in self.__new_report_hashes:
reports_to_delete.update([x.id for x in reports])
else:
for report in reports:
# We set the fix date of a report only if the report
# has not been fixed before.
if report.fixed_at:
continue
checker = report.checker_id
if checker in disabled_checkers:
report.detection_status = 'off'
elif checker_is_unavailable(checker, enabled_checkers):
report.detection_status = 'unavailable'
else:
report.detection_status = 'resolved'
report.fixed_at = run_history_time
if reports_to_delete:
self.__report_server._removeReports(
session, list(reports_to_delete))
def finish_checker_run(
self,
session: DBSession,
run_id: int
) -> bool:
""" Finish the storage of the given run. """
try:
LOG.debug("Finishing checker run")
run = session.query(Run).get(run_id)
if not run:
return False
run.mark_finished()
run.duration = self.__duration
return True
except Exception as ex:
LOG.error(ex)
return False
def store(self) -> int:
""" Store run results to the server. """
start_time = time.time()
# Check constraints of the run.
self.__check_run_limit()
with DBSession(self.__Session) as session:
self.__store_run_lock(session)
try:
with TemporaryDirectory(
dir=self.__context.codechecker_workspace
) as zip_dir:
LOG.info("[%s] Unzip storage file...", self.__name)
zip_size = unzip(self.__b64zip, zip_dir)
LOG.info("[%s] Unzip storage file done.", self.__name)
if zip_size == 0:
raise codechecker_api_shared.ttypes.RequestFailed(
codechecker_api_shared.ttypes.
ErrorCode.GENERAL,
"The received zip file content is empty!")
LOG.debug("Using unzipped folder '%s'", zip_dir)
source_root = os.path.join(zip_dir, 'root')
report_dir = os.path.join(zip_dir, 'reports')
content_hash_file = os.path.join(
zip_dir, 'content_hashes.json')
filename_to_hash = \
util.load_json_or_empty(content_hash_file, {})
LOG.info("[%s] Store source files...", self.__name)
file_path_to_id = self.__store_source_files(
source_root, filename_to_hash)
LOG.info("[%s] Store source files done.", self.__name)
run_history_time = datetime.now()
# Parse all metadata information from the report directory.
for root_dir_path, _, _ in os.walk(report_dir):
metadata_file_path = os.path.join(
root_dir_path, 'metadata.json')
self.__mips[root_dir_path] = \
MetadataInfoParser(metadata_file_path)
# When we use multiple server instances and we try to run
# multiple storage to each server which contain at least two
# reports which have the same report hash and have source code
# comments it is possible that the following exception will be
# thrown: (psycopg2.extensions.TransactionRollbackError)
# deadlock detected.
# The problem is that the report hash is the key for the
# review data table and both of the store actions try to
# update the same review data row.
# Neither of the two processes can continue, and they will wait
# for each other indefinitely. PostgreSQL in this case will
# terminate one transaction with the above exception.
# For this reason in case of failure we will wait some seconds
# and try to run the storage again.
# For more information see #2655 and #2653 issues on github.
max_num_of_tries = 3
num_of_tries = 0
sec_to_wait_after_failure = 60
while True:
try:
# This session's transaction buffer stores the actual
# run data into the database.
with DBSession(self.__Session) as session:
# Load the lock record for "FOR UPDATE" so that the
# transaction that handles the run's store
# operations has a lock on the database row itself.
run_lock = session.query(RunLock) \
.filter(RunLock.name == self.__name) \
.with_for_update(nowait=True).one()
# Do not remove this seemingly dummy print, we need
# to make sure that the execution of the SQL
# statement is not optimised away and the fetched
# row is not garbage collected.
LOG.debug("Storing into run '%s' locked at '%s'.",
self.__name, run_lock.locked_at)
# Actual store operation begins here.
run_id = self.__add_checker_run(
session, run_history_time)
LOG.info("[%s] Store reports...", self.__name)
self.__store_reports(
session, report_dir, source_root, run_id,
file_path_to_id, run_history_time)
LOG.info("[%s] Store reports done.", self.__name)
self.finish_checker_run(session, run_id)
session.commit()
LOG.info("'%s' stored results (%s KB "
"/decompressed/) to run '%s' (id: %d) in "
"%s seconds.", self.user_name,
round(zip_size / 1024),
self.__name, run_id,
round(time.time() - start_time, 2))
return run_id
except (sqlalchemy.exc.OperationalError,
sqlalchemy.exc.ProgrammingError) as ex:
num_of_tries += 1
if num_of_tries == max_num_of_tries:
raise codechecker_api_shared.ttypes.RequestFailed(
codechecker_api_shared.ttypes.
ErrorCode.DATABASE,
"Storing reports to the database failed: "
"{0}".format(ex))
LOG.error("Storing reports of '%s' run failed: "
"%s.\nWaiting %d sec before trying to store "
"it again!", self.__name, ex,
sec_to_wait_after_failure)
time.sleep(sec_to_wait_after_failure)
sec_to_wait_after_failure *= 2
except Exception as ex:
LOG.error("Failed to store results: %s", ex)
import traceback
traceback.print_exc()
raise
finally:
# In any case if the "try" block's execution began, a run lock must
# exist, which can now be removed, as storage either completed
# successfully, or failed in a detectable manner.
# (If the failure is undetectable, the coded grace period expiry
# of the lock will allow further store operations to the given
# run name.)
with DBSession(self.__Session) as session:
self.__free_run_lock(session)
if self.__wrong_src_code_comments:
raise codechecker_api_shared.ttypes.RequestFailed(
codechecker_api_shared.ttypes.ErrorCode.SOURCE_FILE,
"Multiple source code comment can be found with the same "
"checker name for same bug!",
self.__wrong_src_code_comments)
| [
"csordasmarton92@gmail.com"
] | csordasmarton92@gmail.com |
53b09cda44362a8837373232a16c18428dcb871d | ca7aa979e7059467e158830b76673f5b77a0f5a3 | /Python_codes/p02585/s497439083.py | c64c92fb3dffd1704057e5332cba0a7d2217f5e0 | [] | no_license | Aasthaengg/IBMdataset | 7abb6cbcc4fb03ef5ca68ac64ba460c4a64f8901 | f33f1c5c3b16d0ea8d1f5a7d479ad288bb3f48d8 | refs/heads/main | 2023-04-22T10:22:44.763102 | 2021-05-13T17:27:22 | 2021-05-13T17:27:22 | 367,112,348 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,416 | py | n,k = map(int,input().split())
P = list(map(int,input().split()))
C = list(map(int,input().split()))
g = [[0]*(n) for _ in range(n)]
A = [n]*n
# for i in range(n):
# tmp = 0
# idx = i
# cnt = 0
# set_ =set()
# while cnt<n:
# if C[idx] not in set_:
# tmp += C[idx]
# set_.add(C[idx])
# g[i][cnt] = tmp
# idx = P[idx]-1
# cnt += 1
# else:
# p = len(set_)
# A[i] = p
# break
ans = -float('inf')
for i in range(n):
S = []
idx = P[i]-1
S.append(C[idx])
while idx != i:
idx = P[idx]-1
S.append(S[-1] +C[idx])
v,w = k//len(S),k%len(S)
if k<=len(S):
val = max(S[:k])
elif S[-1]<=0:
val = max(S)
else:
val1 = S[-1] *(v-1)
val1 += max(S)
val2 = S[-1]*v
if w!=0:
val2 += max(0,max(S[:w]))
val = max(val1,val2)
ans = max(ans,val)
# for i in range(n):
# v,w = k//A[i],k%A[i]
# if A[i]<k:
# if g[i][A[i]-1]<=0:
# val = max(g[i][:A[i]])
# else:
# val1 = (v-1)*g[i][A[i]-1]
# val1 += max(g[i][:A[i]])
# val2 = v*g[i][A[i]-1]
# if w!=0:
# val2 += max(0,max(g[i][:w]))
# val = max(val1,val2)
# else:
# val = max(g[i][:k])
# ans = max(ans,val)
print(ans) | [
"66529651+Aastha2104@users.noreply.github.com"
] | 66529651+Aastha2104@users.noreply.github.com |
9290a1f679623cb6793f2eaef635da4b4689e597 | 6fce025097cebfd9d1dd37f6611e7fdfdbea90e6 | /rainfields/model_conv.py | 8a22d603ee800aed0a84aee26d7728f6111a7b66 | [] | no_license | ANU-WALD/pluvi_pondus | ec0439d19acdcf4fdf712d6b14a1714297d661b2 | ff8680f7115ab2cb75138bf6705abb59618e47d1 | refs/heads/master | 2021-07-01T14:32:14.501631 | 2020-08-22T09:41:28 | 2020-08-22T09:41:28 | 138,804,652 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,287 | py | from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Conv2D, Flatten
from tensorflow.keras.optimizers import Adam, SGD
import numpy as np
x = np.load("x_conv.npy")[:10000000]
print(x.shape)
y = np.load("y_conv.npy")[:10000000,None]
print(y.shape)
prec_mask = np.nonzero(y>0)
print(prec_mask)
print(len(prec_mask))
#print(prec_mask.shape)
#print(prec_mask[0])
print(prec_mask[0].shape)
x_prec = x[prec_mask[0], :]
y_prec = y[prec_mask[0], :]
print(x_prec.shape, y_prec.shape)
zero_mask = np.nonzero(y==0)
x_dry = x[zero_mask[0], :]
y_dry = y[zero_mask[0], :]
print(x_dry.shape, y_dry.shape)
idxs = np.arange(x_dry.shape[0])
np.random.seed(0)
np.random.shuffle(idxs)
n = x_prec.shape[0] * 2
x_dry = x_dry[idxs[:n],:]
y_dry = y_dry[idxs[:n],:]
print(x_dry.shape, y_dry.shape)
x = np.concatenate((x_prec, x_dry), axis=0)
y = np.concatenate((y_prec, y_dry), axis=0)
print(x.shape, y.shape)
idxs = np.arange(x.shape[0])
np.random.shuffle(idxs)
x = x[idxs,:]
x = np.reshape(x, (x.shape[0], -1))
y = y[idxs,:]
print(x.shape, y.shape)
model= Sequential()
model.add(Dense(100, activation='relu', input_dim=100))
model.add(Dense(200, activation='relu'))
model.add(Dense(400, activation='relu'))
model.add(Dense(100, activation='relu'))
model.add(Dense(50, activation='relu'))
model.add(Dense(1, activation='relu'))
"""
model= Sequential()
model.add(Conv2D(16, kernel_size=3, activation='relu', padding='same', input_shape=(5,5,4)))
model.add(Conv2D(32, kernel_size=3, activation='relu', padding='same'))
model.add(Conv2D(64, kernel_size=3, activation='relu', padding='same'))
model.add(Conv2D(32, kernel_size=3, activation='relu', padding='same'))
model.add(Flatten())
model.add(Dense(1, activation='relu'))
"""
x_train = x[:175000,:]
x_test = x[175000:,:]
y_train = y[:175000,:]
y_test = y[175000:,:]
print(y_train.shape, y_test.shape)
print(np.square(y_train).mean(axis=0))
print(np.square(y_test).mean(axis=0))
print(np.abs(y_train).mean(axis=0))
print(np.abs(y_test).mean(axis=0))
#classifier.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])
model.compile(optimizer=Adam(lr=0.000001), loss='mse', metrics=['mae', 'mse'])
model.fit(x_train, y_train, batch_size=32, nb_epoch=10, validation_data=(x_test, y_test))
| [
"pablo.larraondo@anu.edu.au"
] | pablo.larraondo@anu.edu.au |
8fb462ddad89edc7fbb7b5e557a717ad88b70e9c | 8357c11dc5199ac3d7f688befef2318f4bad0605 | /objectoriented/Sunil AI game/Part1.py | e3cb76f2651331e7ed10da02e9a08ae0ac444a70 | [] | no_license | bibash28/python_projects | d92bd8b49dd75417233424dab5ea39bfc8dcf470 | 049795771ec876052b3fd6967c0d7575d6348c98 | refs/heads/main | 2023-05-16T17:36:28.780358 | 2021-06-09T03:40:14 | 2021-06-09T03:40:14 | 373,839,559 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,745 | py | import math
#______________________________________________________________________________
# Missionaries and Cannibals Problem
class State():
def __init__(self, cannibalLeft, missionaryLeft, boat, cannibalRight, missionaryRight):
self.cannibalLeft = cannibalLeft
self.missionaryLeft = missionaryLeft
self.boat = boat
self.cannibalRight = cannibalRight
self.missionaryRight = missionaryRight
self.parent = None
def is_goal(self):
if self.cannibalLeft == 0 and self.missionaryLeft == 0:
return True
else:
return False
def is_valid(self):
if self.missionaryLeft >= 0 and self.missionaryRight >= 0 \
and self.cannibalLeft >= 0 and self.cannibalRight >= 0 \
and (self.missionaryLeft == 0 or self.missionaryLeft >= self.cannibalLeft) \
and (self.missionaryRight == 0 or self.missionaryRight >= self.cannibalRight):
return True
else:
return False
def __eq__(self, other):
return self.cannibalLeft == other.cannibalLeft and self.missionaryLeft == other.missionaryLeft \
and self.boat == other.boat and self.cannibalRight == other.cannibalRight \
and self.missionaryRight == other.missionaryRight
def __hash__(self):
return hash((self.cannibalLeft, self.missionaryLeft, self.boat, self.cannibalRight, self.missionaryRight))
def successors(cur_state):
children = [];
if cur_state.boat == 'left':
new_state = State(cur_state.cannibalLeft, cur_state.missionaryLeft - 2, 'right',
cur_state.cannibalRight, cur_state.missionaryRight + 2)
## Two missionaries cross left to right.
if new_state.is_valid():
new_state.parent = cur_state
children.append(new_state)
new_state = State(cur_state.cannibalLeft - 2, cur_state.missionaryLeft, 'right',
cur_state.cannibalRight + 2, cur_state.missionaryRight)
## Two cannibals cross left to right.
if new_state.is_valid():
new_state.parent = cur_state
children.append(new_state)
new_state = State(cur_state.cannibalLeft - 1, cur_state.missionaryLeft - 1, 'right',
cur_state.cannibalRight + 1, cur_state.missionaryRight + 1)
## One missionary and one cannibal cross left to right.
if new_state.is_valid():
new_state.parent = cur_state
children.append(new_state)
new_state = State(cur_state.cannibalLeft, cur_state.missionaryLeft - 1, 'right',
cur_state.cannibalRight, cur_state.missionaryRight + 1)
## One missionary crosses left to right.
if new_state.is_valid():
new_state.parent = cur_state
children.append(new_state)
new_state = State(cur_state.cannibalLeft - 1, cur_state.missionaryLeft, 'right',
cur_state.cannibalRight + 1, cur_state.missionaryRight)
## One cannibal crosses left to right.
if new_state.is_valid():
new_state.parent = cur_state
children.append(new_state)
else:
new_state = State(cur_state.cannibalLeft, cur_state.missionaryLeft + 2, 'left',
cur_state.cannibalRight, cur_state.missionaryRight - 2)
## Two missionaries cross right to left.
if new_state.is_valid():
new_state.parent = cur_state
children.append(new_state)
new_state = State(cur_state.cannibalLeft + 2, cur_state.missionaryLeft, 'left',
cur_state.cannibalRight - 2, cur_state.missionaryRight)
## Two cannibals cross right to left.
if new_state.is_valid():
new_state.parent = cur_state
children.append(new_state)
new_state = State(cur_state.cannibalLeft + 1, cur_state.missionaryLeft + 1, 'left',
cur_state.cannibalRight - 1, cur_state.missionaryRight - 1)
## One missionary and one cannibal cross right to left.
if new_state.is_valid():
new_state.parent = cur_state
children.append(new_state)
new_state = State(cur_state.cannibalLeft, cur_state.missionaryLeft + 1, 'left',
cur_state.cannibalRight, cur_state.missionaryRight - 1)
## One missionary crosses right to left.
if new_state.is_valid():
new_state.parent = cur_state
children.append(new_state)
new_state = State(cur_state.cannibalLeft + 1, cur_state.missionaryLeft, 'left',
cur_state.cannibalRight - 1, cur_state.missionaryRight)
## One cannibal crosses right to left.
if new_state.is_valid():
new_state.parent = cur_state
children.append(new_state)
return children
def breadth_first_search():
initial_state = State(3,3,'left',0,0)
if initial_state.is_goal():
return initial_state
frontier = list()
explored = set()
frontier.append(initial_state)
while frontier:
state = frontier.pop(0)
if state.is_goal():
return state
explored.add(state)
children = successors(state)
print(children[0])
for child in children:
if (child not in explored) or (child not in frontier):
frontier.append(child)
return None
def print_solution(solution):
path = []
path.append(solution)
parent = solution.parent
while parent:
path.append(parent)
parent = parent.parent
for t in range(len(path)):
state = path[len(path) - t - 1]
print ("(" + str(state.cannibalLeft) + "," + str(state.missionaryLeft) \
+ "," + state.boat + "," + str(state.cannibalRight) + "," + \
str(state.missionaryRight) + ")")
def main():
solution = breadth_first_search()
print ("Missionaries and Cannibals solution:")
print ("(cannibalLeft,missionaryLeft,boat,cannibalRight,missionaryRight)")
print_solution(solution)
# if called from the command line, call main()
if __name__ == "__main__":
main()
| [
"bibashshrestha@gmail.com"
] | bibashshrestha@gmail.com |
7585bda41bed0e298beec5495edf905f2f6233f0 | b30dec6c5792458c7e435d36c2144196c717a420 | /product/models.py | 43e1cfa1c440363749017c67a90aeb1314811156 | [] | no_license | RowdyKGZ/e-shop | 09e8e938b82ae074e29066362e4753d37f4c574b | 98e3d0d10d3585dae10c2906fe2212b299c76d66 | refs/heads/master | 2023-02-19T08:53:11.243969 | 2021-01-21T14:19:33 | 2021-01-21T14:19:33 | 331,340,387 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,008 | py | import uuid
from time import time
from django.contrib.auth import get_user_model
from django.db import models
from pytils.translit import slugify
def gen_slug(s):
slug = slugify(s)
return slug + '-' + str(int(time()))
class Category(models.Model):
name = models.CharField(max_length=255, unique=True)
slug = models.SlugField(max_length=150, unique=True, primary_key=True, blank=True)
parent = models.ForeignKey('self',
related_name='children',
on_delete=models.CASCADE,
null=True, blank=True)
def __str__(self):
return self.name
def save(self):
if not self.slug:
self.slug = gen_slug(self.name)
super().save()
class Meta:
verbose_name = 'Category'
verbose_name_plural = 'Categories'
class Product(models.Model):
uuid = models.UUIDField(primary_key=True, blank=True)
title = models.CharField(max_length=255)
description = models.TextField()
price = models.DecimalField(max_digits=10, decimal_places=2)
category = models.ManyToManyField(Category)
def __str__(self):
return self.title
def save(self, *args, **kwargs):
if not self.uuid:
self.uuid = str(uuid.uuid4())
super().save(*args, **kwargs)
class Meta:
ordering = ('price',)
class ProductImage(models.Model):
image = models.ImageField(upload_to='products')
product = models.ForeignKey(Product, related_name='images', on_delete=models.CASCADE)
class Comment(models.Model):
product = models.ForeignKey(Product, on_delete=models.CASCADE, related_name='comments')
text = models.TextField(max_length=500)
author = models.ForeignKey(get_user_model(), on_delete=models.CASCADE, related_name='comments')
create_at = models.DateTimeField(auto_now_add=True)
def __str__(self):
return f'Comment by {self.author} on {self.product}, created at {self.create_at}'
| [
"RowdyKG@gmail.com"
] | RowdyKG@gmail.com |
f70a7a2863d3e542f444742ecfd691c846a9bed6 | 8986ec16c3a7fa6ac7bd2e7e73a9e31c740c67fb | /Python-Repo/Automate/BeautifulRequests.py | 400c5205f2bba2f1799c797190d613124fe78045 | [] | no_license | anurag00/Practice-Repo | e365cddfc61fcb50c2a7e1e9e5b5f8c15980c2f3 | f7e7c849d8e6d332d918671798ecfd97dbb963d8 | refs/heads/master | 2022-12-10T02:39:41.424384 | 2022-11-23T06:28:55 | 2022-11-23T06:28:55 | 67,098,851 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 445 | py | import requests, bs4
def getAmazonPrice(producturl):
res = requests.get(producturl)
res.raise_for_status()
soup = bs4.BeautifulSoup(res.text,'html.parser')
elems = soup.select('#priceblock_ourprice')
return elems[0].text.strip()
if __name__ == "__main__":
price = getAmazonPrice('https://www.amazon.in/gp/product/B073JYVKNX/ref=ox_sc_sfl_title_1?ie=UTF8&psc=1&smid=A14CZOWI0VEHLG')
print('Price is Rupees ' + price) | [
"anuragsethi.inc@gmail.com"
] | anuragsethi.inc@gmail.com |
c0c384a71cdcc66ece3df3757b91a264386fb28b | 967d7b69c22dfe1887ce28531689087e701d7c1f | /Udacity_Nanodegree/Machine_Learning/decision_tree/dt_author_id.py | 69c7d408e5c44c785dbef6be23a9f1c11c0f2e5b | [] | no_license | nicky7711/Data-Analysis | 2d5cc981ffcff26d735423ee13d3b824c5ad0f2d | fcbcec9e7b38cc627adb0bf8580fb109ee15b91b | refs/heads/master | 2021-01-15T16:51:40.559906 | 2017-11-02T21:26:48 | 2017-11-02T21:26:48 | 99,729,967 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,020 | py | #!/usr/bin/python
"""
This is the code to accompany the Lesson 3 (decision tree) mini-project.
Use a Decision Tree to identify emails from the Enron corpus by author:
Sara has label 0
Chris has label 1
"""
import sys
from time import time
sys.path.append("../tools/")
from email_preprocess import preprocess
### features_train and features_test are the features for the training
### and testing datasets, respectively
### labels_train and labels_test are the corresponding item labels
features_train, features_test, labels_train, labels_test = preprocess()
#########################################################
### your code goes here ###
from sklearn import tree
clf = tree.DecisionTreeClassifier(min_samples_split=40)
clf.fit(features_train, labels_train)
pred = clf.predict(features_test)
from sklearn.metrics import accuracy_score
acc = accuracy_score(pred, labels_test)
print acc
print len(features_train[0])
#########################################################
| [
"noreply@github.com"
] | noreply@github.com |
0da70bd447adc54400de446fd008c174e5c6dbf1 | d37eef0fa9fb9498266e06cb64799e736d89853c | /tests/wampcc/client_sends_bad_message.py | dbc0767b9e9b481217b2a735f8c210055b5ae684 | [
"MIT"
] | permissive | samangh/wampcc | 5d3d2ce56e6ded99c94b069e0eed743cb2fb4605 | 210502b57d10ab7b41d83e9e4c39b8da1460648a | refs/heads/master | 2022-12-02T01:47:57.842335 | 2022-11-24T06:24:46 | 2022-11-24T07:00:55 | 173,782,913 | 0 | 0 | MIT | 2020-08-17T12:26:57 | 2019-03-04T16:40:05 | C++ | UTF-8 | Python | false | false | 619 | py | #!/usr/bin/env python
#
# Copyright (c) 2017 Darren Smith
#
# wampcc is free software; you can redistribute it and/or modify
# it under the terms of the MIT license. See LICENSE for details.
#
import socket
import time
s = socket.socket() # Create a socket object
host = socket.gethostname() # Get local machine name
port = 55555 # Reserve a port for your service.
s.connect((host, port))
# print "connecting ... not doing anything"
# while True:
# time.sleep(60) # sleep 1 minute
# print s.recv(1024)
# s.close
s.send("hello")
while True:
time.sleep(60) # sleep 1
s.close
| [
"git@darrenjs.net"
] | git@darrenjs.net |
e99cf2e9adcb19df3756f4140c9f29418dca891a | a1db93eacf80566089dfd88794b28e2069e1c9ab | /StudentApp.py | 775ae412a77a85cfc6ebf6fb2c73d88b6d99d1f2 | [] | no_license | karthikkalidas/StudentApp | b5f80adde9dbe24eacf8f7d53945571e9eecd98c | 4d94706eec9906a4709f8e94081aa997b15a8242 | refs/heads/master | 2021-01-19T02:33:33.590767 | 2016-06-26T16:04:53 | 2016-06-26T16:04:53 | 61,212,507 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,030 | py | import json
from pprint import pprint
import sys
import os
class Student:
def __init__(self, Name, PhoneNumber, Marks1, Marks2, Marks3):
self.Name=Name
self.PhoneNumber=PhoneNumber
self.Marks1=Marks1
self.Marks2=Marks2
self.Marks3=Marks3
def __repr__(self):
return (self.Name+' '+self.PhoneNumber+' '+self.Marks1+' '+self.Marks2+' '+self.Marks3)
StudentList = []
def Add():
sName = input("Enter Student's Name : ")
sPhoneNumber = input("Enter Student's PhoneNumber : ")
sMarks1 = input("Enter Marks1 : ")
sMarks2 = input("Enter Marks2 : ")
sMarks3 = input("Enter Marks3 : ")
new_student=Student(sName,sPhoneNumber,sMarks1,sMarks2,sMarks3)
StudentList.append(new_student)
with open("StudentListFile.txt", 'a') as StudentListFile:
for s in StudentList:
StudentListFile.write(str(s) + '\n')
def Read():
with open("StudentListFile.txt", 'r') as f:
StudentList = [line.rstrip('\n') for line in f]
print(StudentList)
def Edit():
sindex =int(input("Enter Index : "))-1
sName = input("Enter Student's Name : ")
sPhoneNumber = input("Enter Student's PhoneNumber : ")
sMarks1 = input("Enter Marks1 : ")
sMarks2 = input("Enter Marks2 : ")
sMarks3 = input("Enter Marks3 : ")
# read a list of lines into data
with open('StudentListFile.txt', 'r') as file:
data = file.readlines()
data[sindex] = sName+' '+sPhoneNumber+' '+sMarks1+' '+sMarks2+' '+sMarks3+'\n'
# and write everything back
with open('StudentListFile.txt', 'w') as file:
file.writelines( data )
while True:
os.system('clear')
func=int(input("Choose Any Number : \n(1) Read\n(2) Add\n(3) Edit\n(4) Quit\n"))
os.system('clear')
if func == 1:
Read()
elif func == 2:
Add()
elif func == 3:
Edit()
elif func == 4:
quit()
else:
print("Your option doesn't make sense to me")
input("\nPress any key to continue : ") | [
"karthik.kalidas@gmail.com"
] | karthik.kalidas@gmail.com |
5f28d3473174758f29072135291cc13603f342ab | 94bb77d0847df86ead773650cf4aa0885ed3ad4e | /dappcrowd/restapi/submissions_endpoint.py | d2fb9fe38acbfc271ba77225c557ec7a4ae17f5a | [] | no_license | Tribler/dappcoder | 3766f0b252ac38d889ad3596b5b6335669d31100 | 8ae43d51a284929bc081c87debc9ef003d1f9116 | refs/heads/master | 2020-04-01T07:53:38.236183 | 2019-01-17T13:07:53 | 2019-01-17T13:07:53 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,196 | py | import json
from twisted.web import http
from twisted.web.server import NOT_DONE_YET
from dappcrowd.restapi.root_endpoint import DAppCrowdEndpoint
class SubmissionsEndpoint(DAppCrowdEndpoint):
def render_GET(self, request):
"""
Get all submissions.
"""
dappcrowd_overlay = self.get_dappcrowd_overlay()
return json.dumps({"submissions": dappcrowd_overlay.persistence.get_submissions()})
def getChild(self, path, request):
return SubmissionPKEndpoint(self.ipv8, self.ipfs_api, path)
def render_PUT(self, request):
"""
Create a new submission for an app request.
"""
parameters = http.parse_qs(request.content.read(), 1)
required_params = ['project_pk', 'project_id', 'submission']
for required_param in required_params:
if required_param not in parameters:
request.setResponseCode(http.BAD_REQUEST)
return json.dumps({"error": "missing parameter %s" % required_param})
def on_block_created(blocks):
request.write(json.dumps({"success": True}))
request.finish()
self.get_dappcrowd_overlay().create_submission(parameters['project_pk'][0].decode('hex'), parameters['project_id'][0], parameters['submission'][0]).addCallback(on_block_created)
return NOT_DONE_YET
class SubmissionPKEndpoint(DAppCrowdEndpoint):
def __init__(self, ipv8, ipfs_api, public_key):
DAppCrowdEndpoint.__init__(self, ipv8, ipfs_api)
self.public_key = public_key.decode('hex')
def getChild(self, path, request):
return SpecificSubmissionEndpoint(self.ipv8, self.ipfs_api, self.public_key, path)
class SpecificSubmissionEndpoint(DAppCrowdEndpoint):
def __init__(self, ipv8, ipfs_api, public_key, submission_id):
DAppCrowdEndpoint.__init__(self, ipv8, ipfs_api)
self.public_key = public_key
self.submission_id = submission_id
self.putChild("reviews", SpecificSubmissionReviewsEndpoint(ipv8, ipfs_api, public_key, submission_id))
def render_GET(self, request):
if not self.get_dappcrowd_overlay().persistence.has_submission(self.public_key, self.submission_id):
request.setResponseCode(http.NOT_FOUND)
return json.dumps({"error": "the submission is not found"})
return json.dumps({
"submission": self.get_dappcrowd_overlay().persistence.get_submission(self.public_key, self.submission_id)
})
class SpecificSubmissionReviewsEndpoint(DAppCrowdEndpoint):
def __init__(self, ipv8, ipfs_api, public_key, submission_id):
DAppCrowdEndpoint.__init__(self, ipv8, ipfs_api)
self.public_key = public_key
self.submission_id = submission_id
def render_GET(self, request):
if not self.get_dappcrowd_overlay().persistence.has_submission(self.public_key, self.submission_id):
request.setResponseCode(http.NOT_FOUND)
return json.dumps({"error": "the submission is not found"})
return json.dumps({
"reviews": self.get_dappcrowd_overlay().persistence.get_reviews(self.public_key, self.submission_id)
})
| [
"mdmartijndevos@gmail.com"
] | mdmartijndevos@gmail.com |
d339a26f897381ccf5df4ce4cafc14487f785f32 | 8f5f6be343ad93c0f3df37675ded1ab2911d9fd8 | /sqlterm/lib/chardet/langcyrillicmodel.py | a8cf1c376400588d2f2f584a5e8faff5d6d77a18 | [] | no_license | johnfouf/monetdb_federated_poc | a69b6053234bb19a3ac8b8fa8e16c07646fd707d | dd6557996d25c49f8751b00c4ce2c9bfc5457097 | refs/heads/master | 2023-02-05T12:44:13.111544 | 2020-12-24T11:28:38 | 2020-12-24T11:28:38 | 277,555,501 | 1 | 1 | null | null | null | null | UTF-8 | Python | false | false | 45,260 | py | ######################## BEGIN LICENSE BLOCK ########################
# The Original Code is Mozilla Communicator client code.
#
# The Initial Developer of the Original Code is
# Netscape Communications Corporation.
# Portions created by the Initial Developer are Copyright (C) 1998
# the Initial Developer. All Rights Reserved.
#
# Contributor(s):
# Mark Pilgrim - port to Python
#
# This library is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public
# License as published by the Free Software Foundation; either
# version 2.1 of the License, or (at your option) any later version.
#
# This library is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
# Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public
# License along with this library; if not, write to the Free Software
# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA
# 02110-1301 USA
######################### END LICENSE BLOCK #########################
import constants
# KOI8-R language model
# Character Mapping Table:
KOI8R_CharToOrderMap = (
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
254,
255,
255,
254,
255,
255, # 00
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255, # 10
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253, # 20
252,
252,
252,
252,
252,
252,
252,
252,
252,
252,
253,
253,
253,
253,
253,
253, # 30
253,
142,
143,
144,
145,
146,
147,
148,
149,
150,
151,
152,
74,
153,
75,
154, # 40
155,
156,
157,
158,
159,
160,
161,
162,
163,
164,
165,
253,
253,
253,
253,
253, # 50
253,
71,
172,
66,
173,
65,
174,
76,
175,
64,
176,
177,
77,
72,
178,
69, # 60
67,
179,
78,
73,
180,
181,
79,
182,
183,
184,
185,
253,
253,
253,
253,
253, # 70
191,
192,
193,
194,
195,
196,
197,
198,
199,
200,
201,
202,
203,
204,
205,
206, # 80
207,
208,
209,
210,
211,
212,
213,
214,
215,
216,
217,
218,
219,
220,
221,
222, # 90
223,
224,
225,
68,
226,
227,
228,
229,
230,
231,
232,
233,
234,
235,
236,
237, # a0
238,
239,
240,
241,
242,
243,
244,
245,
246,
247,
248,
249,
250,
251,
252,
253, # b0
27,
3,
21,
28,
13,
2,
39,
19,
26,
4,
23,
11,
8,
12,
5,
1, # c0
15,
16,
9,
7,
6,
14,
24,
10,
17,
18,
20,
25,
30,
29,
22,
54, # d0
59,
37,
44,
58,
41,
48,
53,
46,
55,
42,
60,
36,
49,
38,
31,
34, # e0
35,
43,
45,
32,
40,
52,
56,
33,
61,
62,
51,
57,
47,
63,
50,
70, # f0
)
win1251_CharToOrderMap = (
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
254,
255,
255,
254,
255,
255, # 00
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255, # 10
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253, # 20
252,
252,
252,
252,
252,
252,
252,
252,
252,
252,
253,
253,
253,
253,
253,
253, # 30
253,
142,
143,
144,
145,
146,
147,
148,
149,
150,
151,
152,
74,
153,
75,
154, # 40
155,
156,
157,
158,
159,
160,
161,
162,
163,
164,
165,
253,
253,
253,
253,
253, # 50
253,
71,
172,
66,
173,
65,
174,
76,
175,
64,
176,
177,
77,
72,
178,
69, # 60
67,
179,
78,
73,
180,
181,
79,
182,
183,
184,
185,
253,
253,
253,
253,
253, # 70
191,
192,
193,
194,
195,
196,
197,
198,
199,
200,
201,
202,
203,
204,
205,
206,
207,
208,
209,
210,
211,
212,
213,
214,
215,
216,
217,
218,
219,
220,
221,
222,
223,
224,
225,
226,
227,
228,
229,
230,
231,
232,
233,
234,
235,
236,
237,
238,
239,
240,
241,
242,
243,
244,
245,
246,
68,
247,
248,
249,
250,
251,
252,
253,
37,
44,
33,
46,
41,
48,
56,
51,
42,
60,
36,
49,
38,
31,
34,
35,
45,
32,
40,
52,
53,
55,
58,
50,
57,
63,
70,
62,
61,
47,
59,
43,
3,
21,
10,
19,
13,
2,
24,
20,
4,
23,
11,
8,
12,
5,
1,
15,
9,
7,
6,
14,
39,
26,
28,
22,
25,
29,
54,
18,
17,
30,
27,
16,
)
latin5_CharToOrderMap = (
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
254,
255,
255,
254,
255,
255, # 00
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255, # 10
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253, # 20
252,
252,
252,
252,
252,
252,
252,
252,
252,
252,
253,
253,
253,
253,
253,
253, # 30
253,
142,
143,
144,
145,
146,
147,
148,
149,
150,
151,
152,
74,
153,
75,
154, # 40
155,
156,
157,
158,
159,
160,
161,
162,
163,
164,
165,
253,
253,
253,
253,
253, # 50
253,
71,
172,
66,
173,
65,
174,
76,
175,
64,
176,
177,
77,
72,
178,
69, # 60
67,
179,
78,
73,
180,
181,
79,
182,
183,
184,
185,
253,
253,
253,
253,
253, # 70
191,
192,
193,
194,
195,
196,
197,
198,
199,
200,
201,
202,
203,
204,
205,
206,
207,
208,
209,
210,
211,
212,
213,
214,
215,
216,
217,
218,
219,
220,
221,
222,
223,
224,
225,
226,
227,
228,
229,
230,
231,
232,
233,
234,
235,
236,
237,
238,
37,
44,
33,
46,
41,
48,
56,
51,
42,
60,
36,
49,
38,
31,
34,
35,
45,
32,
40,
52,
53,
55,
58,
50,
57,
63,
70,
62,
61,
47,
59,
43,
3,
21,
10,
19,
13,
2,
24,
20,
4,
23,
11,
8,
12,
5,
1,
15,
9,
7,
6,
14,
39,
26,
28,
22,
25,
29,
54,
18,
17,
30,
27,
16,
239,
68,
240,
241,
242,
243,
244,
245,
246,
247,
248,
249,
250,
251,
252,
255,
)
macCyrillic_CharToOrderMap = (
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
254,
255,
255,
254,
255,
255, # 00
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255, # 10
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253, # 20
252,
252,
252,
252,
252,
252,
252,
252,
252,
252,
253,
253,
253,
253,
253,
253, # 30
253,
142,
143,
144,
145,
146,
147,
148,
149,
150,
151,
152,
74,
153,
75,
154, # 40
155,
156,
157,
158,
159,
160,
161,
162,
163,
164,
165,
253,
253,
253,
253,
253, # 50
253,
71,
172,
66,
173,
65,
174,
76,
175,
64,
176,
177,
77,
72,
178,
69, # 60
67,
179,
78,
73,
180,
181,
79,
182,
183,
184,
185,
253,
253,
253,
253,
253, # 70
37,
44,
33,
46,
41,
48,
56,
51,
42,
60,
36,
49,
38,
31,
34,
35,
45,
32,
40,
52,
53,
55,
58,
50,
57,
63,
70,
62,
61,
47,
59,
43,
191,
192,
193,
194,
195,
196,
197,
198,
199,
200,
201,
202,
203,
204,
205,
206,
207,
208,
209,
210,
211,
212,
213,
214,
215,
216,
217,
218,
219,
220,
221,
222,
223,
224,
225,
226,
227,
228,
229,
230,
231,
232,
233,
234,
235,
236,
237,
238,
239,
240,
241,
242,
243,
244,
245,
246,
247,
248,
249,
250,
251,
252,
68,
16,
3,
21,
10,
19,
13,
2,
24,
20,
4,
23,
11,
8,
12,
5,
1,
15,
9,
7,
6,
14,
39,
26,
28,
22,
25,
29,
54,
18,
17,
30,
27,
255,
)
IBM855_CharToOrderMap = (
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
254,
255,
255,
254,
255,
255, # 00
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255, # 10
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253, # 20
252,
252,
252,
252,
252,
252,
252,
252,
252,
252,
253,
253,
253,
253,
253,
253, # 30
253,
142,
143,
144,
145,
146,
147,
148,
149,
150,
151,
152,
74,
153,
75,
154, # 40
155,
156,
157,
158,
159,
160,
161,
162,
163,
164,
165,
253,
253,
253,
253,
253, # 50
253,
71,
172,
66,
173,
65,
174,
76,
175,
64,
176,
177,
77,
72,
178,
69, # 60
67,
179,
78,
73,
180,
181,
79,
182,
183,
184,
185,
253,
253,
253,
253,
253, # 70
191,
192,
193,
194,
68,
195,
196,
197,
198,
199,
200,
201,
202,
203,
204,
205,
206,
207,
208,
209,
210,
211,
212,
213,
214,
215,
216,
217,
27,
59,
54,
70,
3,
37,
21,
44,
28,
58,
13,
41,
2,
48,
39,
53,
19,
46,
218,
219,
220,
221,
222,
223,
224,
26,
55,
4,
42,
225,
226,
227,
228,
23,
60,
229,
230,
231,
232,
233,
234,
235,
11,
36,
236,
237,
238,
239,
240,
241,
242,
243,
8,
49,
12,
38,
5,
31,
1,
34,
15,
244,
245,
246,
247,
35,
16,
248,
43,
9,
45,
7,
32,
6,
40,
14,
52,
24,
56,
10,
33,
17,
61,
249,
250,
18,
62,
20,
51,
25,
57,
30,
47,
29,
63,
22,
50,
251,
252,
255,
)
IBM866_CharToOrderMap = (
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
254,
255,
255,
254,
255,
255, # 00
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255,
255, # 10
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253,
253, # 20
252,
252,
252,
252,
252,
252,
252,
252,
252,
252,
253,
253,
253,
253,
253,
253, # 30
253,
142,
143,
144,
145,
146,
147,
148,
149,
150,
151,
152,
74,
153,
75,
154, # 40
155,
156,
157,
158,
159,
160,
161,
162,
163,
164,
165,
253,
253,
253,
253,
253, # 50
253,
71,
172,
66,
173,
65,
174,
76,
175,
64,
176,
177,
77,
72,
178,
69, # 60
67,
179,
78,
73,
180,
181,
79,
182,
183,
184,
185,
253,
253,
253,
253,
253, # 70
37,
44,
33,
46,
41,
48,
56,
51,
42,
60,
36,
49,
38,
31,
34,
35,
45,
32,
40,
52,
53,
55,
58,
50,
57,
63,
70,
62,
61,
47,
59,
43,
3,
21,
10,
19,
13,
2,
24,
20,
4,
23,
11,
8,
12,
5,
1,
15,
191,
192,
193,
194,
195,
196,
197,
198,
199,
200,
201,
202,
203,
204,
205,
206,
207,
208,
209,
210,
211,
212,
213,
214,
215,
216,
217,
218,
219,
220,
221,
222,
223,
224,
225,
226,
227,
228,
229,
230,
231,
232,
233,
234,
235,
236,
237,
238,
9,
7,
6,
14,
39,
26,
28,
22,
25,
29,
54,
18,
17,
30,
27,
16,
239,
68,
240,
241,
242,
243,
244,
245,
246,
247,
248,
249,
250,
251,
252,
255,
)
# Model Table:
# total sequences: 100%
# first 512 sequences: 97.6601%
# first 1024 sequences: 2.3389%
# rest sequences: 0.1237%
# negative sequences: 0.0009%
RussianLangModel = (
0,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
1,
1,
3,
3,
3,
3,
1,
3,
3,
3,
2,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
0,
3,
2,
2,
2,
2,
2,
0,
0,
2,
3,
3,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
3,
3,
0,
0,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
3,
2,
0,
0,
0,
0,
0,
0,
0,
0,
2,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
3,
3,
3,
2,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
3,
3,
0,
0,
3,
3,
3,
3,
3,
3,
3,
3,
2,
3,
3,
1,
0,
0,
0,
0,
0,
0,
0,
0,
2,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
3,
2,
3,
2,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
0,
0,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
1,
0,
0,
0,
0,
0,
0,
0,
2,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
3,
3,
0,
0,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
1,
0,
0,
0,
0,
0,
1,
0,
2,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
3,
3,
3,
3,
3,
3,
3,
3,
2,
2,
2,
3,
1,
3,
3,
1,
3,
3,
3,
3,
2,
2,
3,
0,
2,
2,
2,
3,
3,
2,
1,
0,
0,
0,
0,
0,
0,
0,
0,
2,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
0,
0,
0,
0,
0,
0,
0,
3,
3,
3,
3,
3,
3,
2,
3,
3,
3,
3,
3,
2,
2,
3,
2,
3,
3,
3,
2,
1,
2,
2,
0,
1,
2,
2,
2,
2,
2,
2,
0,
0,
0,
0,
0,
0,
0,
0,
2,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
2,
0,
0,
0,
0,
0,
0,
0,
0,
0,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
2,
2,
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)
Koi8rModel = {
"charToOrderMap": KOI8R_CharToOrderMap,
"precedenceMatrix": RussianLangModel,
"mTypicalPositiveRatio": 0.976601,
"keepEnglishLetter": constants.False,
"charsetName": "KOI8-R",
}
Win1251CyrillicModel = {
"charToOrderMap": win1251_CharToOrderMap,
"precedenceMatrix": RussianLangModel,
"mTypicalPositiveRatio": 0.976601,
"keepEnglishLetter": constants.False,
"charsetName": "windows-1251",
}
Latin5CyrillicModel = {
"charToOrderMap": latin5_CharToOrderMap,
"precedenceMatrix": RussianLangModel,
"mTypicalPositiveRatio": 0.976601,
"keepEnglishLetter": constants.False,
"charsetName": "ISO-8859-5",
}
MacCyrillicModel = {
"charToOrderMap": macCyrillic_CharToOrderMap,
"precedenceMatrix": RussianLangModel,
"mTypicalPositiveRatio": 0.976601,
"keepEnglishLetter": constants.False,
"charsetName": "MacCyrillic",
}
Ibm866Model = {
"charToOrderMap": IBM866_CharToOrderMap,
"precedenceMatrix": RussianLangModel,
"mTypicalPositiveRatio": 0.976601,
"keepEnglishLetter": constants.False,
"charsetName": "IBM866",
}
Ibm855Model = {
"charToOrderMap": IBM855_CharToOrderMap,
"precedenceMatrix": RussianLangModel,
"mTypicalPositiveRatio": 0.976601,
"keepEnglishLetter": constants.False,
"charsetName": "IBM855",
}
| [
"openaire@dl126.madgik.di.uoa.gr"
] | openaire@dl126.madgik.di.uoa.gr |
b4b798b4b5b230c3088019cf13bf6acb5fe54680 | 95d4c8f4cda7ad1c7623a2df02da8cee1ad0941d | /src/classifier/german_pos_tagger.py | a66192956c55f524f2b1142c45afdf0df24c1383 | [
"MIT"
] | permissive | tiefenauer/ip7-python | 8f587b7b77430facff19b24441490756b01d5b17 | 512105ba39110ec77d2ea0961dd7c2a42d4ec26d | refs/heads/master | 2021-09-09T20:37:21.647146 | 2018-02-20T12:07:46 | 2018-02-20T12:07:46 | 107,635,390 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,382 | py | # -*- coding: utf-8 -*-
#
# Natural Language Toolkit: ClassifierBasedGermanTagger
#
# URL: <http://www.experimentallabor.de/>
#
# Copyright 2011 Philipp Nolte
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Tag German text.
"""
import re
from nltk.tag.sequential import ClassifierBasedTagger
class ClassifierBasedGermanTagger(ClassifierBasedTagger):
"""A classifier based German part-of-speech tagger. It has an accuracy of
96.09% after being trained on 90% of the German TIGER corpus. The tagger
extends the NLTK ClassifierBasedTagger and implements a slightly modified
feature detector.
"""
def feature_detector(self, tokens, index, history):
"""Implementing a slightly modified feature detector.
@param tokens: The tokens from the sentence to tag.
@param index: The current token index to tag.
@param history: The previous tagged tokens.
"""
word = tokens[index]
if index == 0: # At the beginning of the sentence
prevword = prevprevword = None
prevtag = prevprevtag = None
# word = word.lower() # Lowercase at the beginning of sentence
elif index == 1:
prevword = tokens[index - 1] # Note: no lowercase
prevprevword = None
prevtag = history[index - 1]
prevprevtag = None
else:
prevword = tokens[index - 1]
prevprevword = tokens[index - 2]
prevtag = history[index - 1]
prevprevtag = history[index - 2]
if re.match('[0-9]+([\.,][0-9]*)?|[0-9]*[\.,][0-9]+$', word):
# Included "," as decimal point
shape = 'number'
elif re.compile('\W+$', re.UNICODE).match(word):
# Included unicode flag
shape = 'punct'
elif re.match('([A-ZÄÖÜ]+[a-zäöüß]*-?)+$', word):
# Included dash for dashed words and umlauts
shape = 'upcase'
elif re.match('[a-zäöüß]+', word):
# Included umlauts
shape = 'downcase'
elif re.compile("\w+", re.UNICODE).match(word):
# Included unicode flag
shape = 'mixedcase'
else:
shape = 'other'
features = {
'prevtag': prevtag,
'prevprevtag': prevprevtag,
'word': word,
'word.lower': word.lower(),
'suffix3': word.lower()[-3:],
# 'suffix2': word.lower()[-2:],
# 'suffix1': word.lower()[-1:],
'preffix1': word[:1], # included
'prevprevword': prevprevword,
'prevword': prevword,
'prevtag+word': '%s+%s' % (prevtag, word),
'prevprevtag+word': '%s+%s' % (prevprevtag, word),
'prevword+word': '%s+%s' % (prevword, word),
'shape': shape
}
return features
| [
"git@tiefenauer.info"
] | git@tiefenauer.info |
66ca04f0fddbc514ac5faf9ad4beca5f98b42a32 | e23e32d8371f1211240b19c657820661bb121e02 | /Taxi.py | cc6ae4f7b85ab8769471200c32780483452111a3 | [] | no_license | ThomasElijah/Week_9 | b55ad5f846d8249a353377904b51d3fd0a5218f5 | 09693027349d6e4df384ba78098c63cc7aa4f9dd | refs/heads/master | 2021-01-16T23:05:46.399803 | 2016-09-20T08:40:32 | 2016-09-20T08:40:32 | 68,567,882 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,958 | py | """
CP1404/CP5632 Practical
Car class
"""
class Car:
""" represent a car object """
def __init__(self, name="", fuel=0):
""" initialise a Car instance """
self.name = name
self.fuel = fuel
self.odometer = 0
def __str__(self):
return "{}, fuel={}, odo={}".format(self.name, self.fuel, self.odometer)
def add_fuel(self, amount):
""" add amount to the car's fuel"""
self.fuel += amount
def drive(self, distance):
""" drive the car a given distance if it has enough fuel or drive until fuel runs out
return the distance actually driven """
if distance > self.fuel:
distance_driven = self.fuel
self.fuel = 0
else:
self.fuel -= distance
distance_driven = distance
self.odometer += distance_driven
return distance_driven
class Taxi(Car):
""" specialised version of a Car that includes fare costs """
price_per_km = 1.2
def __init__(self, name, fuel):
""" initialise a Taxi instance, based on parent class Car """
super().__init__(name, fuel)
self.current_fare_distance = 0
def __str__(self):
""" return a string representation like a car but with current fare distance"""
return "{}, ${:.2f}/km, {}km on current fare".format(super().__str__(), Taxi.price_per_km,
self.current_fare_distance)
def get_fare(self):
""" get the price for the taxi trip """
return Taxi.price_per_km * self.current_fare_distance
def start_fare(self):
""" begin a new fare """
self.current_fare_distance = 0
def drive(self, distance):
""" drive like parent Car but calculate fare distance as well"""
distance_driven = super().drive(distance)
self.current_fare_distance += distance_driven
return distance_driven
| [
"elijah.thomas@my.jcu.edu.au"
] | elijah.thomas@my.jcu.edu.au |
fe687c852349e7fe2e04398f4929f9c94248ece8 | 2d52b8bf7f60043a77538743962095aeb7dd80e9 | /Práctica 2/ID3/ID3.py | bdc2e0377e578e7fe46b7f71cbd167f2098b867a | [] | no_license | Javi96/SGDI | aa09b06f2e53ee1e2e6771803f1c8a6e4cc74ea4 | 1ffd55e577e1c3d594390c40dbda805649288bf5 | refs/heads/master | 2020-03-29T22:49:03.546186 | 2019-07-03T16:15:21 | 2019-07-03T16:15:21 | 150,441,863 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 13,699 | py | '''JoseJavierCortesTejada y AitorCayonRuano declaramos que esta solución
es fruto exclusivamente de nuestro trabajo personal. No hemos sido
ayudados por ninguna otra persona ni hemos obtenido la solución de
fuentes externas, y tampoco hemos compartido nuestra solución con
nadie. Declaramos además que no hemos realizado de manera desho-
nesta ninguna otra actividad que pueda mejorar nuestros resultados
ni perjudicar los resultados de los demás.'''
import json
import csv
import sys
import operator
import random
import math
from termcolor import colored
from termcolor import *
from subprocess import call
class Node():
node_count = 0
def __init__(self, _type, value = '', edge = ''):
self.value = value
self.edge = edge
self.type = _type
self.nodes = []
Node.node_count += 1
self.node_id = Node.node_count
self.node_info = ''
def add_son(self, son):
"""
Añade un nuevo nodo a la lista de hijos.
Parametros
----------
son : Node
Hijo a añadir a la lista
"""
self.nodes.append(son)
def get_tree(self):
"""
Genera una cadena de texto con la información del nodo.
Recopila la información de un nodo y sus hijos para generar un fichero .dot.
Para ello toma de cada nodo su identificador y le añade una etiqueta 'label'
con su valor. Si el nodo en cuestión no tiene hijos añade una nueva etiqueta
'shape' para modificar la representación del mismo en el .dot. También toma
las aristas que conectan los nodos entre sí.
Retorno
-------
str
Información del nodo
"""
if len(self.nodes) == 0:
self.node_info += str(self.node_id) + '''[label="''' + str(self.value) + '''", shape="box"];\n'''
else:
self.node_info += str(self.node_id) + '''[label="''' + str(self.value) + '''"];\n'''
for node in self.nodes:
self.node_info += str(self.node_id) + '->' + str(node.node_id) + '''[label="''' + node.edge + '''"];\n'''
self.node_info += node.get_tree()
return self.node_info
class ID3Tree():
def __init__(self, data, attributes):
self.attributes = attributes
self.data = data
self.nodo = self.generate_tree(attributes, data)
def get_major_class(self, instances):
"""
Devuelve la clase que más aparece en el conjunto de instancias.
Genera un diccionario para cada valor del atributo 'class' del
conjunto de instancias. Hecho esto devuelve la clase que más se
repite y el numero de clases distintas de la entrada.
Parametros
----------
instances : list
Conjunto de instancias a evaluar
Retorno
-------
str
Clase que más se repite
int
Numero de clases distintas
"""
classes = {}
for instance in instances:
class_value = instance.get('class')
if class_value in classes:
classes[class_value] = 1 + classes[class_value]
else:
classes[class_value] = 1
major_class = max(classes.items(), key=operator.itemgetter(1))[0]
return major_class, len(classes)
def group_by_attribute(self, attributes, instances):
"""
Agrupa el conjunto de instancias en función del valor de cada atributo.
Genera un diccionario con la forma:
{attr1 :
{valor1 : [instA, ..., instN]}
{valor2 : [instB, ..., instM]}
{attr2 :
{valor2 : ...}
donde atributo almacena una lista de instancias en funcion de los valores
del mismo.
Parametros
----------
attributes : list
Lista de atributos
instances : list
Conjunto de instancias a clasificar
Retorno
-------
dict
Diccionario con las instancias clasificadas
"""
result = {}
for attribute in attributes: # para cada atributo
if attribute == 'class':
continue
grouped_instances = {}
for instance in instances:
copy_instance = instance.copy()
copy_instance.pop(attribute)
if instance[attribute] in grouped_instances:
grouped_instances[instance[attribute]] = [copy_instance] + grouped_instances[instance[attribute]]
else:
grouped_instances[instance[attribute]] = [copy_instance]
result[attribute] = grouped_instances
return result
def get_partition(self, instances, attribute, value):
"""
Genera un nuevo conjunto de instancias en base a un valor concreto de un atributo conocido.
Parametros
----------
instances : list
Lista de atributos
attribute : str
Atributo concreto a usar
value : str
Valor del atributo por el que filtrar
Retorno
-------
list
Lista de instancias filtradas
"""
partition = []
for instance in instances:
if instance[attribute] == value:
partition.append(instance)
return partition
def generate_tree(self, attributes, instances, edge = ''):
"""
Genera el arbol de clasificacion.
Completa un nodo que representa el arbol de clasificacion. Para ello:
- agrupa las instancias por el valor de la clase. Si no quedan
atributos por los que clasificar o todas las instancias tienen
la misma clase se termina de expandir la rama actual.
- genera un conjunto de instancias para los valores de cada atributo
y encuentra el atributo con menor entropia (mayor ganancia de informacion).
- genera particiones del conjunto de instancias inicial y expande el arbol
usando cada posible valor del atributo con menor entropia.
Parametros
----------
attributes : list
Lista de atributos
instances : list
Conjunto de instancias
edge : str
Valor del atributo usado en la anterior expansion del arbol
Retorno
-------
Node
Nodo con el arbol de clasificación
"""
major_class, count_class = self.get_major_class(instances)
if count_class == 1 or len(attributes) == 1:
return Node('leaf', major_class, edge)
else:
group_by_attribute = self.group_by_attribute(attributes, instances)
min_entropy = self.get_entropy(group_by_attribute)
nodo = Node('inner', min_entropy, edge)
for elem in group_by_attribute[min_entropy].items():
new_data = self.get_partition(instances, min_entropy, elem[0])
if len(new_data) == 0:
aux_node = Node('leaf', major_class, edge)
else:
new_attributes = attributes.copy()
new_attributes.remove(min_entropy)
aux_node = self.generate_tree(new_attributes, new_data, elem[0])
nodo.add_son(aux_node)
return nodo
def get_entropy(self, grouped_instances):
"""
Determina el atributo con menor entropía por el que expandir el arbol.
Parametros
----------
grouped_instances : dict
Instancias agrupadas por atributo en base a cada valor
Retorno
-------
str
Atributo por el que expandir
"""
total_entropy = {}
for group in grouped_instances.items(): # iteramos para cada atributo
group_by_class = self.group_by_class(group)
for elem in group_by_class.items(): # para cada valor del atributo
entropies_and_elems = []
count = sum(elem[1].values())
entropy = 0
for i in elem[1].items(): # para cada valor del atributo calculamos su entropia
entropy += -i[1]/count*math.log2(i[1]/count)
entropies_and_elems.append((entropy, count))
if group[0] not in total_entropy:
total_entropy[group[0]] = entropies_and_elems
else:
total_entropy[group[0]] = entropies_and_elems + total_entropy[group[0]]
result = {}
for attribute in total_entropy.items():
acc = 0
for i in range(0, len(attribute[1])):
acc += attribute[1][i][0]*attribute[1][i][1]/len(self.data)
result[attribute[0]] = acc
return min(result.items(), key=operator.itemgetter(1))[0]
def group_by_class(self, grouped_instances):
"""
Agrupa las instancias por clase.
Parametros
----------
grouped_instances : dict
Instancias agrupadas por atributo en base a cada valor
Retorno
-------
dict
Instancias agrupadas por clase
"""
group_by_class = {}
for group in grouped_instances[1].items():
aux = {}
for instance in group[1]:
if instance['class'] not in aux:
aux[instance['class']] = 1
else:
aux[instance['class']] = 1 + aux[instance['class']]
group_by_class[group[0]] = aux
return group_by_class
def save_tree(self, file):
"""
Crea una representación del arbol de clasificacion apta para la herramienta xdot.
Parametros
----------
file : str
Nombre del fichero sobre el que volcar el arbol
"""
with open(file, "w+") as file:
file.write('''digraph tree {''' + self.nodo.get_tree() + '''}''')
def clasifica(self, instance, node):
"""
Clasifica una instancia.
Parametros
----------
instance : dict
Instancia a clasificar
node : Node
Nodo para expandir el arbol
Retorno
-------
str
Valor delvuelto por el clasificador. Puede ser:
- el valor del nodo hoja (la clase predicha)
- un valor arbitrario para indicar que no se ha clasificado
"""
if node.type == 'leaf':
return node.value
attribute = instance[node.value]
for child in node.nodes:
if child.edge == attribute:
del instance[node.value]
return self.clasifica(instance, child)
return '-----'
class ID3(object):
def __init__(self, file):
instances, attributes = self.read_csv(file)
self.tree = ID3Tree(instances, attributes)
def read_csv(self, file):
"""
Lee el conjunto de instancias de un fichero .csv.
Parametros
----------
file : str
Fichero del que leer los datos
Retorno
-------
list
Conjunto de instancias
list
Lista de atributos
"""
attributes = []
instances = []
with open(file) as input_file:
line = csv.reader(input_file, delimiter = ',')
attributes = next(line)
for word in line:
instances.append({attributes[i] : word[i] for i in range(0, len(word))})
return instances, attributes
def clasifica(self, instance):
"""
Clasifica una instancia.
Parametros
----------
instance : dict
Instancia a clasificar
Retorno
-------
str
Valor devuelto por el clasificador
"""
return self.tree.clasifica(instance, self.tree.nodo)
def test(self, file):
"""
Clasifica un conjunto de instancias desde un fichero.
Parametros
----------
file : str
Fichero del que leer los datos
Retorno
-------
dict
Tasa de aciertos, fallos y el numero de instancias clasificadas
"""
instances, attributes = self.read_csv(file)
hits = 0
for instance in instances:
result = self.tree.clasifica(instance.copy(), self.tree.nodo)
print('Instance: ', instance, '\t\nresult: ', result)
if instance['class'] == result:
hits += 1
print(colored('Hit', 'green'))
else:
print(colored('Fail', 'red'))
return {'Hits: ': hits, 'Fails: ': len(instances)-hits, 'Total: ': len(instances)}
def save_tree(self, file):
"""
Guarda la representacion del arbol de clasificacion en un fichero .dot.
Parametros
----------
file : str
Fichero en el que escribir los datos
"""
self.tree.save_tree(file)
call(['xdot', file])
if __name__ == '__main__':
id3 = ID3(sys.argv[1])
id3.save_tree('example.dot')
'''print(colored('class: ' + id3.clasifica({'season':'winter','rain':'heavy','wind':'high','day':'weekday'}), 'yellow'))'''
#print(colored('class: ' + id3.clasifica({'season':'winter','rain':'heavy','wind':'high','day':'saturday'}), 'yellow'))
result = id3.test(sys.argv[2])
print(result)
| [
"javi.tejada96@gmail.com"
] | javi.tejada96@gmail.com |
208a6b8fc1e0c1f592e3b7d18c9b54892e832b7b | 7cfef2dccf09644d49c8dfb8bd4197be51531ff4 | /onegroup/wsgi.py | 1355d18ee200da572cb95ddd2a21c78ffec71991 | [] | no_license | varunagrawal/OneGroup | 2235c808ec9394022e147fa1a8800b4d48ab3bae | fd9c92f2cc0c043c5c398efd99f2356a1475a64a | refs/heads/master | 2022-05-06T12:52:25.933823 | 2022-04-12T21:44:22 | 2022-04-12T21:44:22 | 62,920,156 | 0 | 0 | null | 2022-04-22T23:41:50 | 2016-07-08T22:10:10 | Python | UTF-8 | Python | false | false | 393 | py | """
WSGI config for onegroup project.
It exposes the WSGI callable as a module-level variable named ``application``.
For more information on this file, see
https://docs.djangoproject.com/en/1.9/howto/deployment/wsgi/
"""
import os
from django.core.wsgi import get_wsgi_application
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "onegroup.settings")
application = get_wsgi_application()
| [
"vagrawal@pindropsecurity.com"
] | vagrawal@pindropsecurity.com |
1d7903952b84f753cada1f0be0c24e33b9d97d63 | e3d06f7bf45f16cbfa68586a2ce6d662ce302af9 | /packets_filter/storeHomeStateData.py | 9d9dc73d9d66f8a038146dfda7ce214015387895 | [] | no_license | y0d4a/Gsm-Packets-Analysis-Framework | f211972f3e02806483452c2fca066447d36f8e8a | 060c4467154e05b2479b0df27075d5ded5e07216 | refs/heads/master | 2021-01-16T17:49:55.987440 | 2016-06-02T19:59:04 | 2016-06-02T19:59:04 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,773 | py | from __future__ import print_function
from twisted.internet import defer, reactor
from txmongo.connection import ConnectionPool
url = "mongodb://localhost:27017"
cursor = None
@defer.inlineCallbacks
def getConnection():
global cursor
cursor = yield ConnectionPool(url)
@defer.inlineCallbacks
def getHomeStates():
# this will return pid->homezone
population = 2000
retVal = {}
db = cursor.GsmSimulatedData
col = db.RawPackets
print('home state function called')
for i in range(population+1):
print('id->'+str(i))
pid = i
skip = 0
limit = 100
count = {'nw': 0, 'ne': 0, 'e': 0, 'w': 0, 'n': 0, 's': 0, 'c': 0, 'sw': 0}
flag = False
while True:
docs = yield col.find(spec={'id': pid}, skip=skip, limit=limit)
if len(docs):
for doc in docs:
time = doc['time']
if time <= 1440 and time >= 1200:
count[doc['tower']['zone']] += 1
val = max(count.values())
for k in count.keys():
if count[k] == val and val >= 3:
flag = True
retVal[pid] = k
break
if not flag:
skip += limit
print('loop again')
else:
break
else:
break
print('Home state finished')
db = cursor.GsmSimulatedData
col = db.PeopleHomeZones
for k, v in retVal.items():
yield col.insert({'id': k, 'zone': v})
print(retVal)
if __name__ == '__main__':
getConnection()
getHomeStates().addCallback(lambda ign: reactor.stop())
reactor.run()
| [
"arorashwetankkdm@gmail.com"
] | arorashwetankkdm@gmail.com |
10177a53490eb98107c90432833b44de0dc5241f | 36e3d735e06d0642f1e8c26bff57305a01cc627c | /nms/priClient/settings.py | 70dc9c3a439ae7865ae186e64032e891229bbeb1 | [] | no_license | WilsonWangTHU/ipv6_server | 5c768cdaeaf22ee508c5fff162b208481a42f95d | 5088f58ab25061e65127699ed328ddaab24f9aac | refs/heads/master | 2021-01-18T21:18:39.653994 | 2016-05-27T04:22:23 | 2016-05-27T04:22:23 | 55,656,523 | 4 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,819 | py | """
Django settings for subClient project.
Generated by 'django-admin startproject' using Django 1.9.5.
For more information on this file, see
https://docs.djangoproject.com/en/1.9/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/1.9/ref/settings/
"""
import os
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/1.9/howto/deployment/checklist/
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = '2+ytb#pjeh*g!9_3m(id@&mn$c+f56$q6fp=*%lkr)wp8hpfz%'
# SECURITY WARNING: don't run with debug turned on in production!
DEBUG = True
ALLOWED_HOSTS = []
# Application definition
INSTALLED_APPS = [
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
'net_data'
]
MIDDLEWARE_CLASSES = [
# 'django.middleware.security.SecurityMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.common.CommonMiddleware',
# 'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
# 'django.contrib.auth.middleware.SessionAuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
]
ROOT_URLCONF = 'priClient.urls'
TEMPLATE_DEBUG = True
TEMPLATE_DIRS = (
os.path.join(BASE_DIR, 'templates'),
)
WSGI_APPLICATION = 'priClient.wsgi.application'
# Database
# https://docs.djangoproject.com/en/1.9/ref/settings/#databases
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.sqlite3',
'NAME': os.path.join(BASE_DIR, 'db.sqlite3'),
}
}
# Password validation
# https://docs.djangoproject.com/en/1.9/ref/settings/#auth-password-validators
AUTH_PASSWORD_VALIDATORS = [
{
'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator',
},
]
# Internationalization
# https://docs.djangoproject.com/en/1.9/topics/i18n/
LANGUAGE_CODE = 'en-us'
TIME_ZONE = 'UTC'
USE_I18N = True
USE_L10N = True
USE_TZ = True
# Static files (CSS, JavaScript, Images)
# https://docs.djangoproject.com/en/1.9/howto/static-files/
STATIC_URL = os.path.join(BASE_DIR, 'static/')
| [
"wode406@hotmail.com"
] | wode406@hotmail.com |
2d4b29a8afb8ba840c0c97a4e5296c98779b4382 | 1f696631898e0279951709e150da6d87045e4bc4 | /mysite/blog/migrations/0003_auto_20201018_1329.py | 55a90dffcfe644d3983ed6e04e389fcac44cd412 | [] | no_license | henryfrstr/django_project_blog | 9f50b004b2fed59304c3f5a1f05247d44a232992 | 0f3c391a3cd790ae504fb84a786158a1d775abda | refs/heads/main | 2022-12-31T05:05:20.989719 | 2020-10-25T11:26:27 | 2020-10-25T11:26:27 | 305,067,579 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 357 | py | # Generated by Django 3.0.8 on 2020-10-18 10:29
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('blog', '0002_auto_20201018_1327'),
]
operations = [
migrations.RenameField(
model_name='post',
old_name='titles',
new_name='title',
),
]
| [
"63148122+henryfrstr@users.noreply.github.com"
] | 63148122+henryfrstr@users.noreply.github.com |
2249aa29e8fd1a24bd328de828fb13bc0214fffb | c72d83320274e7afe2dd4ac361ebab4bef40d317 | /pythonDoZero/start.py | d84f16dd42551a1a78d1055a2f334e898ffc07a5 | [] | no_license | abelrufino/python | fcc3cf661428dc9bbba226a0d09d40a78cc9c29d | ef3146456e75ac2aaae238d1e7c82c0e056afdb4 | refs/heads/master | 2023-08-28T00:35:49.379108 | 2021-09-25T21:21:37 | 2021-09-25T21:21:37 | 410,381,673 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 54 | py | # Primeiro programa em Python
print('Hello, World!!') | [
"anetosib@gmail.com"
] | anetosib@gmail.com |
3018141d8e5f0cc37a97e4845ce6f68e04162871 | 3ac914deee02b35300103573f25f9f6d1d637f59 | /Earthquake_destructiveness_five_factors.py | 0cf719c44aaed919bc07faff021027d6e8b23d0b | [] | no_license | anup5889/NaturalCalamity | 3737802be735eadbad4edcc633548067e6b5d83a | d5e5d6b4efeef214246be9c2f59a30e4381d2a60 | refs/heads/master | 2016-09-12T17:42:52.861802 | 2016-05-08T00:18:06 | 2016-05-08T00:18:06 | 56,535,354 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 3,652 | py | __author__ = 'anupdudani'
__author__ = 'anupdudani'
__author__ = 'anupdudani'
__author__ = 'anupdudani'
__author__ = 'anupdudani'
__author__ = 'anupdudani'
import os
import matplotlib.pyplot as plt
import subprocess
import pandas as pd
from sklearn.metrics import r2_score
from sklearn import datasets, linear_model
import numpy as np
from sklearn.tree import DecisionTreeClassifier
from sklearn.cross_validation import train_test_split
from sklearn.metrics import accuracy_score
import math
from sklearn.naive_bayes import GaussianNB
from sklearn.tree import DecisionTreeRegressor
from sklearn.preprocessing import Imputer
from sklearn import linear_model
from encoder import encode_feature
import pylab
from sklearn.cross_validation import cross_val_score
from sklearn.tree import DecisionTreeClassifier
from sklearn import svm
from sklearn.neighbors import KNeighborsClassifier
os.chdir("/Users/anupdudani/Documents/NaturalCalamity")
earthQuakeDestructivenessDf=pd.read_csv("destructiveNessOfEarthQuake.csv")
modified_earthquake_destructiveness_df = encode_feature(earthQuakeDestructivenessDf,"destructiveness")
modified_earthquake_destructiveness_df = encode_feature(modified_earthquake_destructiveness_df,"Population")
modified_earthquake_destructiveness_df = encode_feature(modified_earthquake_destructiveness_df,"Secondary effects")
modified_earthquake_destructiveness_df = encode_feature(modified_earthquake_destructiveness_df,"Architechture")
print(modified_earthquake_destructiveness_df.info())
#print weather_df.head()
#print weather_df.tail()
#print modified_weather_df
#print modified_weather_df.columns.values
print "Classification with six Factors"
modified_earthquake_destructiveness_df["Population_param"].fillna(0)
modified_earthquake_destructiveness_df["Secondary effects_param"].fillna(0)
modified_earthquake_destructiveness_df["Architechture_param"].fillna(0)
modified_earthquake_destructiveness_df["Magnitude"].fillna(0)
modified_earthquake_destructiveness_df["Depth"].fillna(0)
target= modified_earthquake_destructiveness_df["destructiveness_param"]
y = target
#print "target", y
y=y.tolist()
#print "target list", y
feature_list=[]
print "INFO:before for loop"
for a,b,c,d,e in modified_earthquake_destructiveness_df[["Secondary effects_param", "Magnitude", "Depth","Population_param", "Architechture_param" ]].itertuples(index=False):
feature_list.append([a,b,c,d,e])
print "INFO: after for loop"
#print feature_list[1:100]
X=feature_list
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state=42)
"""
Decision Tree Classifier
"""
clfDT = DecisionTreeClassifier(random_state=0)
clfDT.fit(X_train, y_train)
predict_values=clfDT.predict(X_test)
dt_score=r2_score(y_test,predict_values)
print y_test
print predict_values
print "Accuracy of DecisionTree Classifier", dt_score
"""
SVM
"""
clfSVC = svm.SVC()
clfSVC.fit(X_train, y_train)
predict_values=clfSVC.predict(X_test)
svm_score=r2_score(y_test,predict_values)
print "Accuracy of SVM", svm_score
"""
svm.LinearSVC()
"""
clfLSVC = svm.LinearSVC()
clfLSVC.fit(X_train, y_train)
predict_values=clfLSVC.predict(X_test)
svmlc_score=r2_score(y_test,predict_values)
print "Accuracy of Linear " , svmlc_score
"""
naive bayes
"""
clfNB=GaussianNB()
clfNB.fit(X_train, y_train)
predict_values=clfNB.predict(X_test)
nb_score=r2_score(y_test,predict_values)
print "Accuracy of Naive Bayes", nb_score
"""
Knn classifier
"""
clfKNN=KNeighborsClassifier(n_neighbors=5)
clfKNN.fit(X_train, y_train)
predict_values=clfKNN.predict(X_test)
KNN_score=r2_score(y_test,predict_values)
print "Accuracy of KNN", KNN_score
| [
"anup5889@gmail.com"
] | anup5889@gmail.com |
c94b68b2254773744cf3e5e54a2cc322ed8e5b93 | 0389e0bf1e2942089fa84ce8ab79ef859f5d8215 | /teacher/migrations/0002_timetable.py | ecf4c3a8525870a4c484d1b6dfd09e382fb1afe2 | [] | no_license | jitin2707/SchoolManagement | 89f78e35b2b1f387083115064b0a54423de09cc7 | 7024d84dc0dfed4864a0ff9c58d045a1453bdb06 | refs/heads/master | 2020-08-05T11:39:56.958757 | 2019-11-23T03:57:01 | 2019-11-23T03:57:01 | 212,488,353 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,199 | py | # Generated by Django 2.0.6 on 2019-11-13 13:32
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('students', '0005_remove_section_class_id'),
('teacher', '0001_initial'),
]
operations = [
migrations.CreateModel(
name='TimeTable',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('table_date', models.CharField(default='', max_length=255)),
('table_day', models.CharField(default='', max_length=255)),
('time_slot', models.CharField(default='', max_length=255)),
('subject', models.CharField(default='', max_length=255)),
('classid', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='students.Student_class')),
('section', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='students.Section')),
('teacher', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='teacher.TeacherDetail')),
],
),
]
| [
"truepx247@gmail.com"
] | truepx247@gmail.com |
ee692b4e30708d7c40cc7efe0f041f668c08dcb4 | f63314b4852fb97ad740e53e450110fcd08a515b | /app.py | ce08afaac1bc0e74d4fe1216c543d83672b30fd1 | [] | no_license | xsomam/askfm-scrapper | ee0e2c4439d5be3e4ebd7fceb27d01fbff3aa4da | 2e997268f40cd37dfc56bc7adc496d609106b327 | refs/heads/master | 2023-04-09T03:45:56.074797 | 2020-08-07T23:48:31 | 2020-08-07T23:48:31 | 384,990,560 | 0 | 0 | null | 2023-03-17T21:32:19 | 2021-07-11T15:56:16 | null | WINDOWS-1250 | Python | false | false | 7,611 | py | # Basic imports
import os
import time
import json
import logging
# Modules imports
import requests
from bs4 import BeautifulSoup
# Imports from files
from answer import SinglePost
from locators import *
logging.basicConfig(format='%(asctime)s %(levelname)-8s [%(filename)s:%(lineno)d] %(message)s',
datefmt='%d-%m-%Y %H:%M:%S',
level=logging.INFO,
filename='logs.txt')
logger = logging.getLogger('app')
ask_url = 'https://ask.fm' #Base Ask URL
BASE_DIR = os.getcwd()
# List with pending profile links to scrape.
# First link is simply base URL: ask.fm/profile.
# After first visit, if there is "next" button on page (next page)
# Then this link is appended to this array and program continues scraping
_pending_list = []
# Array for each Singlequestion_obj object.
# Singlequestion_obj object contains every answer encapsulated within one question_obj
# With info about question, answer etc.
_question = []
# Retrieving function.
# First loops through profile, and stops looping if there are no more "next" pages left
# If there are none, starts writing text content to drive by iterating through questions array
def retrieve(askfm_nick, dl_img, to_csv, to_json):
logger.info('Running "retrieve" function.')
_n = 1
# Append base Askfm profile link to pending list to be scraped first
_pending_list.append(ask_url + '/' + askfm_nick)
# scraping będzie trwał tak długo, jak istnieje chociaż 1 link w liście "_pending_list".
# len = 0 oznacza, że nie ma więcej linków
# Trial of creating folder for downloaded content with user's nickname as name
try:
logger.info('Trial of creation of directory for scraping: '+ BASE_DIR)
os.mkdir(askfm_nick)
except Exception:
logger.info('FAIL of creation of directory for scraping: ' + BASE_DIR)
print('Directory already exists or another error happened. Skipping...')
pass
# Loop runs as long as there is some page to scrape.
# If there was no "next" page, loop ends
while len(_pending_list) > 0:
for link in _pending_list:
print(f'Connecting : {link}')
logger.info('Establishing connection to: ' + link)
# Get content of page, parse it with BS4
try:
site = requests.get(link).content
soup = BeautifulSoup(site, 'html.parser')
# Select each indivifual question on profile
all_questions = soup.select(SiteLocators.QUESTIONS)
except Exception:
print(f'Connection error at: {link}. Retrial in 5 seconds...')
# logger.info(f'Connection error at: {link}. Retrial in 5 seconds...')
time.sleep(5)
continue
# From array of questions we crate actual objects which will contain
# Only important data (like question, answer in text etc.)
# WHich we will perform operations on later
for question in all_questions:
question_obj = SinglePost(question)
_question.append(question_obj)
logger.info(f'Adding question #{_n}.')
# If given question had image, we access it and download it
if question_obj.image:
save_one_image(askfm_nick, question_obj)
_n += 1
# Remove already scraped profile from pedning list
_pending_list.remove(link)
print(f'{link} removed from temp...')
logger.info(f'{link} removed from temp.')
# If there is next page, we again start looping
next_page = soup.select_one(SiteLocators.NEXT)
logger.info('Retrieving next page link')
print('Retrieving next page link')
if next_page:
_pending_list.append(ask_url + next_page.attrs['href'])
logger.info(f"Link to next site appended to temp list: {ask_url}{next_page.attrs['href']}")
print(f"{ask_url}{next_page.attrs['href']} appending successful! Looping back...")
else:
logger.info(f'No "Next" link found. Retrieving done.')
print('No "Next" link found. Retrieving done.')
perform_file_operations(askfm_nick, dl_img, to_csv, to_json)
# Function dispatching file operations
def perform_file_operations(askfm_nick, dl_img, to_csv, to_json):
for each in _question:
if to_csv:
save_to_csv(askfm_nick)
if to_json:
save_to_json(askfm_nick)
def save_to_json(askfm_nick):
logger.info('Running "save_to_json" function.')
print('Saving to JSON')
_list = []
file_name = f'{askfm_nick}.json'
with open(os.path.join(BASE_DIR, askfm_nick,file_name), 'w') as file:
for each in _question:
json_dict = {
'question': each.question,
'answer': each.answer,
'likes': each.likes,
'time': each.date,
'link': each.link,
'img': f"{askfm_nick}-{each.link.split('/')[-1]}.{each.image_extension}" if each.image else None,
'asker_url': each.asker
}
_list.append(json_dict)
# if each.image:
# save_images(each.image_link, each.image_extension, each.link)
json.dump(_list, file, indent=4, ensure_ascii=True)
print(f'Saved to JSON: {file_name}')
def save_to_csv(askfm_nick):
logger.info('Running "save_to_csv" function.')
pass
def save_images(askfm_nick):
logger.info('Running "save_images" function.')
for each in _question:
if each.image:
print('Saving image....')
_photo_name = f"{askfm_nick}-{each.link.split('/')[-1]}.{each.image_extension}"
try:
logger.info('Trial of saving image begins.')
logger.info('Requesting image from: ' + each.image_link)
photo_file = requests.get(each.image_link).content
img_path = os.path.join(BASE_DIR, askfm_nick, _photo_name)
with open(img_path, 'wb') as f:
f.write(photo_file)
logger.info('Saving image to: ' + img_path)
print(f"Image saved: {_photo_name}")
except Exception:
print(f"Could not get image {_photo_name}. Skipping...")
logger.info('Error with saving image: ' + _photo_name)
pass
def save_one_image(askfm_nick, question_obj):
logger.info('Running "save_one_image" function.')
print('Saving image....')
_photo_name = f"{askfm_nick}-{question_obj.link.split('/')[-1]}.{question_obj.image_extension}"
try:
logger.info('Trial of saving image begins.')
logger.info('Requesting image from: ' + question_obj.image_link)
photo_file = requests.get(question_obj.image_link).content
img_path = os.path.join(BASE_DIR, askfm_nick,_photo_name)
with open(img_path, 'wb') as f:
f.write(photo_file)
logger.info('Saving image to: ' + img_path)
print(f"Image saved: {_photo_name}")
except Exception:
print(f"Could not get image {_photo_name}. Skipping...")
logger.info('Error with saving image: ' + _photo_name)
pass
| [
"a@b.com"
] | a@b.com |
6d751b6338153469f545cb98bced25f45d54cb90 | 63e8b2fafdb5a9d18a4db98646aae8f37d0930d7 | /tests/test_aggregators.py | b1fafd0cf4e1d31711d127c062b08b06f78b419c | [
"MIT"
] | permissive | mikecokina/pyopentsdb | 7b5b1b3669a59e71675d21f66c37574fa9f864e9 | e1a27802a5cb31fc0a6b8d8ced50f5403480f14b | refs/heads/master | 2020-03-15T01:52:42.052483 | 2018-10-29T18:19:53 | 2018-10-29T18:19:53 | 131,904,099 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,298 | py | import unittest
from pyopentsdb import tsdb
from pyopentsdb import errors
from unittest import mock
from tests.testutils import get_mock_requests_get, mock_tsdb_error_get, mock_unexpected_error_get
from tests.testutils import GeneralUrlTestCase
class AggregatorsTestCase(unittest.TestCase):
__TEST_AGGREGATORS__ = ["mult", "p90", "zimsum", "mimmax", "sum", "p50", "none", "p95", "ep99r7"]
def setUp(self):
self._host = 'mockhttp://localhost:5896/'
self._c = tsdb.tsdb_connection(self._host)
@mock.patch('requests.Session.get', side_effect=get_mock_requests_get(None))
def test_url(self, _):
GeneralUrlTestCase.test_url(self, "/api/aggregators/", "aggregators")
@mock.patch('requests.Session.get', side_effect=get_mock_requests_get(__TEST_AGGREGATORS__))
def test_aggregators(self, _):
response = self._c.aggregators()
self.assertEqual(sorted(response), sorted(AggregatorsTestCase.__TEST_AGGREGATORS__))
@mock.patch('requests.Session.get', side_effect=get_mock_requests_get(
response_content={"error": {"message": "Response code differ 200"}}, status_code=403))
def test_aggregators_403(self, _):
with self.assertRaises(Exception) as context:
self._c.aggregators()
self.assertTrue(isinstance(context.exception, errors.UncaughtError))
@mock.patch('requests.Session.get', side_effect=get_mock_requests_get(
response_content={"error": {"message": "Response code differ 200"}}, status_code=400))
def test_aggregators_403(self, _):
with self.assertRaises(Exception) as context:
self._c.aggregators()
self.assertTrue(isinstance(context.exception, errors.ArgumentError))
@mock.patch('requests.Session.get', side_effect=mock_tsdb_error_get)
def test_aggregators_tsdberror(self, _):
with self.assertRaises(Exception) as context:
self._c.aggregators()
self.assertTrue(isinstance(context.exception, errors.TsdbError))
@mock.patch('requests.Session.get', side_effect=mock_unexpected_error_get)
def test_aggregators_unexpectederror(self, _):
with self.assertRaises(Exception) as context:
self._c.aggregators()
self.assertTrue(isinstance(context.exception, errors.UncaughtError))
| [
"mikecokina@gmail.com"
] | mikecokina@gmail.com |
9fe346f7b4238f028ddcac3690d2ae20fb8f9ee2 | ee771f2ac4dcc256ae483b3e75aada07183aa5b7 | /2021/11/solve.py | f6e822aa6e32b66f8f267cad6cf03faae248548a | [] | no_license | mdiazv/adventofcode | bd12387ed42c72b848ef75ce793ed6a8ed764870 | cb64304d144a8dc0f70f07c1efe31f287a6e2206 | refs/heads/master | 2023-01-12T06:23:06.079420 | 2022-12-27T17:34:50 | 2022-12-27T17:34:50 | 48,266,768 | 0 | 0 | null | 2020-12-28T11:36:02 | 2015-12-19T03:17:10 | Java | UTF-8 | Python | false | false | 1,373 | py | import sys
class World:
def __init__(self, w):
self.w = w
self.R, self.C = len(w), len(w[0])
self.gen, self.flashes = 0, 0
self.superflashes = []
def step(self):
self.flashed = set()
for i in range(self.R):
for j in range(self.C):
self.inc(i, j)
for i, j in self.flashed:
self.w[i][j] = 0
self.flashes += len(self.flashed)
if len(self.flashed) == self.R*self.C:
self.superflashes.append(self.gen)
self.gen += 1
def inc(self, i, j):
self.w[i][j] += 1
if self.w[i][j] > 9 and (i, j) not in self.flashed:
self.flashed.add( (i, j) )
for ii, jj in self.neighbors(i, j):
self.inc(ii, jj)
def neighbors(self, i, j):
return ((ii, jj) for ii in range(i-1, i+2) for jj in range(j-1, j+2)
if (i, j) != (ii, jj) and ii >= 0 and jj >= 0 and ii < self.R and jj < self.C)
def __repr__(self):
return '\n'.join(''.join(map(str, row)) for row in self.w) + f'\ngen {self.gen} - {self.flashes} flashes'
w = World([list(map(int, line[:-1])) for line in sys.stdin])
while not w.superflashes:
if w.gen == 100:
print (w)
print(f'Flashes after 100 steps: {w.flashes}')
w.step()
print (w)
print(f'First super flash at step {w.gen}')
| [
"diazvillarroelm@gmail.com"
] | diazvillarroelm@gmail.com |
36cf33d8e7752a13987e46b90e29cb1c203c8fab | 0747fae9472fb33a012c629d43811785cbaa2456 | /wdg.py | 20ed53d6d59fc28697fffe962db12d947d8cbd17 | [] | no_license | fernandoeqc/satelital_server | 891718315d50f1ad85094625016b8b9f8fd25b13 | 6c1f25502485b201fc5fefd8e8af6fa88a390ff0 | refs/heads/master | 2023-06-06T05:45:45.665154 | 2021-06-28T17:06:34 | 2021-06-28T17:06:34 | 380,112,129 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,835 | py | """ import logging
import sys
import time
from watchdog.events import LoggingEventHandler
from watchdog.observers import Observer
if __name__ == "__main__":
logging.basicConfig(level=logging.INFO,
format='%(asctime)s - %(message)s',
datefmt='%Y-%m-%d %H:%M:%S')
path = sys.argv[1] if len(sys.argv) > 1 else '.'
event_handler = LoggingEventHandler()
observer = Observer()
observer.schedule(event_handler, path, recursive=True)
observer.start()
try:
while True:
time.sleep(1)
except KeyboardInterrupt:
observer.stop()
observer.join()
"""
import parse_xml
import watchdog.events
import watchdog.observers
import time
import sys
class Handler(watchdog.events.PatternMatchingEventHandler):
def __init__(self):
# Set the patterns for PatternMatchingEventHandler
watchdog.events.PatternMatchingEventHandler.__init__(self, patterns=['*.ok'],
ignore_directories=True, case_sensitive=False)
def on_created(self, event):
#print("Watchdog received CREATED event - % s." % event.src_path)
# Event is created, you can process it now
file = event.src_path
parse_xml.look_for_esn(file)
def on_deleted(self, event):
print("Watchdog received DELETED event - % s." % event.src_path)
if __name__ == "__main__":
src_path = sys.argv[1] if len(sys.argv) > 1 else './folder_target'
event_handler = Handler()
observer = watchdog.observers.Observer()
observer.schedule(event_handler, path=src_path, recursive=True)
observer.start()
try:
while True:
time.sleep(1)
except KeyboardInterrupt:
observer.stop()
observer.join() | [
"fernandoeqc@live.com"
] | fernandoeqc@live.com |
81083ec81fafe82eb5da65f0db9a46cf5a74c630 | 0b7022778b31a7f5082255f637665d81cafa0cc1 | /Map and Reduce/Task2/map.py | 17eb896646277699e7beeb10b69f1bea5c18a58b | [] | no_license | sailikhithk/NYC_Open_Data-Map-Reduce-and-Pyspark | 09913efc3d6b2646a2314fa812c3d7a8c371a1f1 | 93d469b8e982ca915cf62e34e3c3aa8a6f7dacca | refs/heads/master | 2022-03-31T23:07:28.751500 | 2020-01-18T23:56:45 | 2020-01-18T23:56:45 | 209,429,016 | 2 | 1 | null | null | null | null | UTF-8 | Python | false | false | 384 | py | import sys
import string
import csv
for line in sys.stdin:
line = line.strip()
row = line.split(',')
key_consolidate = row[2]
value_consolidate = 1
key_consolidate_value = {key_consolidate:value_consolidate}
sys.stdout.write(str(key_consolidate_value).replace("{","").replace("}","").replace(":","\t").replace("(","").replace(")","").replace("'","") + "\n")
| [
"noreply@github.com"
] | noreply@github.com |
9ce1a053a0e37ba990a8f6d8eb0d3e918d099320 | d92e5e9073dae7631f2f43aa3618cd91d8c7ee1a | /Artificial Intelligence/search/searchAgents.py | 72343acf4145aec0efbfcefb05e111d38e9c9477 | [] | no_license | madhavSoni/Some-Projects | 6dd8e1ea9486e0974ca517a229c855e7babc0330 | 10b74f929faf57ee980153d7714b2fc7ae134184 | refs/heads/master | 2021-09-24T14:19:57.765294 | 2018-10-10T08:58:09 | 2018-10-10T08:58:09 | 124,698,499 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 22,181 | py | # searchAgents.py
# ---------------
# Licensing Information: You are free to use or extend these projects for
# educational purposes provided that (1) you do not distribute or publish
# solutions, (2) you retain this notice, and (3) you provide clear
# attribution to UC Berkeley, including a link to http://ai.berkeley.edu.
#
# Attribution Information: The Pacman AI projects were developed at UC Berkeley.
# The core projects and autograders were primarily created by John DeNero
# (denero@cs.berkeley.edu) and Dan Klein (klein@cs.berkeley.edu).
# Student side autograding was added by Brad Miller, Nick Hay, and
# Pieter Abbeel (pabbeel@cs.berkeley.edu).
"""
This file contains all of the agents that can be selected to control Pacman. To
select an agent, use the '-p' option when running pacman.py. Arguments can be
passed to your agent using '-a'. For example, to load a SearchAgent that uses
depth first search (dfs), run the following command:
> python pacman.py -p SearchAgent -a fn=depthFirstSearch
Commands to invoke other search strategies can be found in the project
description.
Please only change the parts of the file you are asked to. Look for the lines
that say
"*** YOUR CODE HERE ***"
The parts you fill in start about 3/4 of the way down. Follow the project
description for details.
Good luck and happy searching!
"""
from game import Directions
from game import Agent
from game import Actions
import util
import time
import search
class GoWestAgent(Agent):
"An agent that goes West until it can't."
def getAction(self, state):
"The agent receives a GameState (defined in pacman.py)."
if Directions.WEST in state.getLegalPacmanActions():
return Directions.WEST
else:
return Directions.STOP
#######################################################
# This portion is written for you, but will only work #
# after you fill in parts of search.py #
#######################################################
class SearchAgent(Agent):
"""
This very general search agent finds a path using a supplied search
algorithm for a supplied search problem, then returns actions to follow that
path.
As a default, this agent runs DFS on a PositionSearchProblem to find
location (1,1)
Options for fn include:
depthFirstSearch or dfs
breadthFirstSearch or bfs
Note: You should NOT change any code in SearchAgent
"""
def __init__(self, fn='depthFirstSearch', prob='PositionSearchProblem', heuristic='nullHeuristic'):
# Warning: some advanced Python magic is employed below to find the right functions and problems
# Get the search function from the name and heuristic
if fn not in dir(search):
raise AttributeError, fn + ' is not a search function in search.py.'
func = getattr(search, fn)
if 'heuristic' not in func.func_code.co_varnames:
print('[SearchAgent] using function ' + fn)
self.searchFunction = func
else:
if heuristic in globals().keys():
heur = globals()[heuristic]
elif heuristic in dir(search):
heur = getattr(search, heuristic)
else:
raise AttributeError, heuristic + ' is not a function in searchAgents.py or search.py.'
print('[SearchAgent] using function %s and heuristic %s' % (fn, heuristic))
# Note: this bit of Python trickery combines the search algorithm and the heuristic
self.searchFunction = lambda x: func(x, heuristic=heur)
# Get the search problem type from the name
if prob not in globals().keys() or not prob.endswith('Problem'):
raise AttributeError, prob + ' is not a search problem type in SearchAgents.py.'
self.searchType = globals()[prob]
print('[SearchAgent] using problem type ' + prob)
def registerInitialState(self, state):
"""
This is the first time that the agent sees the layout of the game
board. Here, we choose a path to the goal. In this phase, the agent
should compute the path to the goal and store it in a local variable.
All of the work is done in this method!
state: a GameState object (pacman.py)
"""
if self.searchFunction == None: raise Exception, "No search function provided for SearchAgent"
starttime = time.time()
problem = self.searchType(state) # Makes a new search problem
self.actions = self.searchFunction(problem) # Find a path
totalCost = problem.getCostOfActions(self.actions)
print('Path found with total cost of %d in %.1f seconds' % (totalCost, time.time() - starttime))
if '_expanded' in dir(problem): print('Search nodes expanded: %d' % problem._expanded)
def getAction(self, state):
"""
Returns the next action in the path chosen earlier (in
registerInitialState). Return Directions.STOP if there is no further
action to take.
state: a GameState object (pacman.py)
"""
if 'actionIndex' not in dir(self): self.actionIndex = 0
i = self.actionIndex
self.actionIndex += 1
if i < len(self.actions):
return self.actions[i]
else:
return Directions.STOP
class PositionSearchProblem(search.SearchProblem):
"""
A search problem defines the state space, start state, goal test, successor
function and cost function. This search problem can be used to find paths
to a particular point on the pacman board.
The state space consists of (x,y) positions in a pacman game.
Note: this search problem is fully specified; you should NOT change it.
"""
def __init__(self, gameState, costFn = lambda x: 1, goal=(1,1), start=None, warn=True, visualize=True):
"""
Stores the start and goal.
gameState: A GameState object (pacman.py)
costFn: A function from a search state (tuple) to a non-negative number
goal: A position in the gameState
"""
self.walls = gameState.getWalls()
self.startState = gameState.getPacmanPosition()
if start != None: self.startState = start
self.goal = goal
self.costFn = costFn
self.visualize = visualize
if warn and (gameState.getNumFood() != 1 or not gameState.hasFood(*goal)):
print 'Warning: this does not look like a regular search maze'
# For display purposes
self._visited, self._visitedlist, self._expanded = {}, [], 0 # DO NOT CHANGE
def getStartState(self):
return self.startState
def isGoalState(self, state):
isGoal = state == self.goal
# For display purposes only
if isGoal and self.visualize:
self._visitedlist.append(state)
import __main__
if '_display' in dir(__main__):
if 'drawExpandedCells' in dir(__main__._display): #@UndefinedVariable
__main__._display.drawExpandedCells(self._visitedlist) #@UndefinedVariable
return isGoal
def getSuccessors(self, state):
"""
Returns successor states, the actions they require, and a cost of 1.
As noted in search.py:
For a given state, this should return a list of triples,
(successor, action, stepCost), where 'successor' is a
successor to the current state, 'action' is the action
required to get there, and 'stepCost' is the incremental
cost of expanding to that successor
"""
successors = []
for action in [Directions.NORTH, Directions.SOUTH, Directions.EAST, Directions.WEST]:
x,y = state
dx, dy = Actions.directionToVector(action)
nextx, nexty = int(x + dx), int(y + dy)
if not self.walls[nextx][nexty]:
nextState = (nextx, nexty)
cost = self.costFn(nextState)
successors.append( ( nextState, action, cost) )
# Bookkeeping for display purposes
self._expanded += 1 # DO NOT CHANGE
if state not in self._visited:
self._visited[state] = True
self._visitedlist.append(state)
return successors
def getCostOfActions(self, actions):
"""
Returns the cost of a particular sequence of actions. If those actions
include an illegal move, return 999999.
"""
if actions == None: return 999999
x,y= self.getStartState()
cost = 0
for action in actions:
# Check figure out the next state and see whether its' legal
dx, dy = Actions.directionToVector(action)
x, y = int(x + dx), int(y + dy)
if self.walls[x][y]: return 999999
cost += self.costFn((x,y))
return cost
class StayEastSearchAgent(SearchAgent):
"""
An agent for position search with a cost function that penalizes being in
positions on the West side of the board.
The cost function for stepping into a position (x,y) is 1/2^x.
"""
def __init__(self):
self.searchFunction = search.uniformCostSearch
costFn = lambda pos: .5 ** pos[0]
self.searchType = lambda state: PositionSearchProblem(state, costFn, (1, 1), None, False)
class StayWestSearchAgent(SearchAgent):
"""
An agent for position search with a cost function that penalizes being in
positions on the East side of the board.
The cost function for stepping into a position (x,y) is 2^x.
"""
def __init__(self):
self.searchFunction = search.uniformCostSearch
costFn = lambda pos: 2 ** pos[0]
self.searchType = lambda state: PositionSearchProblem(state, costFn)
def manhattanHeuristic(position, problem, info={}):
"The Manhattan distance heuristic for a PositionSearchProblem"
xy1 = position
xy2 = problem.goal
return abs(xy1[0] - xy2[0]) + abs(xy1[1] - xy2[1])
def euclideanHeuristic(position, problem, info={}):
"The Euclidean distance heuristic for a PositionSearchProblem"
xy1 = position
xy2 = problem.goal
return ( (xy1[0] - xy2[0]) ** 2 + (xy1[1] - xy2[1]) ** 2 ) ** 0.5
#####################################################
# This portion is incomplete. Time to write code! #
#####################################################
class CornersProblem(search.SearchProblem):
"""
This search problem finds paths through all four corners of a layout.
You must select a suitable state space and successor function
"""
def __init__(self, startingGameState):
"""
Stores the walls, pacman's starting position and corners.
"""
self.walls = startingGameState.getWalls()
self.startingPosition = startingGameState.getPacmanPosition()
top, right = self.walls.height-2, self.walls.width-2
self.corners = ((1,1), (1,top), (right, 1), (right, top))
for corner in self.corners:
if not startingGameState.hasFood(*corner):
print 'Warning: no food in corner ' + str(corner)
self._expanded = 0 # DO NOT CHANGE; Number of search nodes expanded
# Please add any code here which you would like to use
# in initializing the problem
"*** YOUR CODE HERE ***"
def getStartState(self):
"""
Returns the start state (in your state space, not the full Pacman state
space)
"""
"*** YOUR CODE HERE ***"
return (self.startingPosition, self.corners)
def isGoalState(self, state):
"""
Returns whether this search state is a goal state of the problem.
"""
"*** YOUR CODE HERE ***"
return len(state[1]) == 0
def getSuccessors(self, state):
"""
Returns successor states, the actions they require, and a cost of 1.
As noted in search.py:
For a given state, this should return a list of triples, (successor,
action, stepCost), where 'successor' is a successor to the current
state, 'action' is the action required to get there, and 'stepCost'
is the incremental cost of expanding to that successor
"""
successors = []
for action in [Directions.NORTH, Directions.SOUTH, Directions.EAST, Directions.WEST]:
# Add a successor state to the successor list if the action is legal
# Here's a code snippet for figuring out whether a new position hits a wall:
# x,y = currentPosition
# dx, dy = Actions.directionToVector(action)
# nextx, nexty = int(x + dx), int(y + dy)
# hitsWall = self.walls[nextx][nexty]
"*** YOUR CODE HERE ***"
x,y = state[0]
dx, dy = Actions.directionToVector(action)
nextx, nexty = int(x + dx), int(y + dy)
hitsWall = self.walls[nextx][nexty]
if not hitsWall:
# remove corners eaten by that move
corners = tuple(x for x in state[1] if x != (nextx, nexty))
successors.append((((nextx, nexty), corners), action, 1))
self._expanded += 1 # DO NOT CHANGE
return successors
def getCostOfActions(self, actions):
"""
Returns the cost of a particular sequence of actions. If those actions
include an illegal move, return 999999. This is implemented for you.
"""
if actions == None: return 999999
x,y= self.startingPosition
for action in actions:
dx, dy = Actions.directionToVector(action)
x, y = int(x + dx), int(y + dy)
if self.walls[x][y]: return 999999
return len(actions)
def cornersHeuristic(state, problem):
"""
A heuristic for the CornersProblem that you defined.
state: The current search state
(a data structure you chose in your search problem)
problem: The CornersProblem instance for this layout.
This function should always return a number that is a lower bound on the
shortest path from the state to a goal of the problem; i.e. it should be
admissible (as well as consistent).
"""
corners = problem.corners # These are the corner coordinates
walls = problem.walls # These are the walls of the maze, as a Grid (game.py)
distances = [0]
for corner in state[1]:
distances.append(util.manhattanDistance(state[0], corner))
return max(distances)
class AStarCornersAgent(SearchAgent):
"A SearchAgent for FoodSearchProblem using A* and your foodHeuristic"
def __init__(self):
self.searchFunction = lambda prob: search.aStarSearch(prob, cornersHeuristic)
self.searchType = CornersProblem
class FoodSearchProblem:
"""
A search problem associated with finding the a path that collects all of the
food (dots) in a Pacman game.
A search state in this problem is a tuple ( pacmanPosition, foodGrid ) where
pacmanPosition: a tuple (x,y) of integers specifying Pacman's position
foodGrid: a Grid (see game.py) of either True or False, specifying remaining food
"""
def __init__(self, startingGameState):
self.start = (startingGameState.getPacmanPosition(), startingGameState.getFood())
self.walls = startingGameState.getWalls()
self.startingGameState = startingGameState
self._expanded = 0 # DO NOT CHANGE
self.heuristicInfo = {} # A dictionary for the heuristic to store information
def getStartState(self):
return self.start
def isGoalState(self, state):
return state[1].count() == 0
def getSuccessors(self, state):
"Returns successor states, the actions they require, and a cost of 1."
successors = []
self._expanded += 1 # DO NOT CHANGE
for direction in [Directions.NORTH, Directions.SOUTH, Directions.EAST, Directions.WEST]:
x,y = state[0]
dx, dy = Actions.directionToVector(direction)
nextx, nexty = int(x + dx), int(y + dy)
if not self.walls[nextx][nexty]:
nextFood = state[1].copy()
nextFood[nextx][nexty] = False
successors.append( ( ((nextx, nexty), nextFood), direction, 1) )
return successors
def getCostOfActions(self, actions):
"""Returns the cost of a particular sequence of actions. If those actions
include an illegal move, return 999999"""
x,y= self.getStartState()[0]
cost = 0
for action in actions:
# figure out the next state and see whether it's legal
dx, dy = Actions.directionToVector(action)
x, y = int(x + dx), int(y + dy)
if self.walls[x][y]:
return 999999
cost += 1
return cost
class AStarFoodSearchAgent(SearchAgent):
"A SearchAgent for FoodSearchProblem using A* and your foodHeuristic"
def __init__(self):
self.searchFunction = lambda prob: search.aStarSearch(prob, foodHeuristic)
self.searchType = FoodSearchProblem
def foodHeuristic(state, problem):
"""
Your heuristic for the FoodSearchProblem goes here.
This heuristic must be consistent to ensure correctness. First, try to come
up with an admissible heuristic; almost all admissible heuristics will be
consistent as well.
If using A* ever finds a solution that is worse uniform cost search finds,
your heuristic is *not* consistent, and probably not admissible! On the
other hand, inadmissible or inconsistent heuristics may find optimal
solutions, so be careful.
The state is a tuple ( pacmanPosition, foodGrid ) where foodGrid is a Grid
(see game.py) of either True or False. You can call foodGrid.asList() to get
a list of food coordinates instead.
If you want access to info like walls, capsules, etc., you can query the
problem. For example, problem.walls gives you a Grid of where the walls
are.
If you want to *store* information to be reused in other calls to the
heuristic, there is a dictionary called problem.heuristicInfo that you can
use. For example, if you only want to count the walls once and store that
value, try: problem.heuristicInfo['wallCount'] = problem.walls.count()
Subsequent calls to this heuristic can access
problem.heuristicInfo['wallCount']
"""
position, foodGrid = state
distances = [0]
for food in foodGrid.asList():
# distances.append(util.manhattanDistance(position, food))
distances.append(mazeDistance(position, food, problem.startingGameState))
distanceFurthest = max(distances)
return distanceFurthest
class ClosestDotSearchAgent(SearchAgent):
"Search for all food using a sequence of searches"
def registerInitialState(self, state):
self.actions = []
currentState = state
while(currentState.getFood().count() > 0):
nextPathSegment = self.findPathToClosestDot(currentState) # The missing piece
self.actions += nextPathSegment
for action in nextPathSegment:
legal = currentState.getLegalActions()
if action not in legal:
t = (str(action), str(currentState))
raise Exception, 'findPathToClosestDot returned an illegal move: %s!\n%s' % t
currentState = currentState.generateSuccessor(0, action)
self.actionIndex = 0
print 'Path found with cost %d.' % len(self.actions)
def findPathToClosestDot(self, gameState):
"""
Returns a path (a list of actions) to the closest dot, starting from
gameState.
"""
# Here are some useful elements of the startState
startPosition = gameState.getPacmanPosition()
food = gameState.getFood()
walls = gameState.getWalls()
problem = AnyFoodSearchProblem(gameState)
"*** YOUR CODE HERE ***"
return search.astar(problem)
class AnyFoodSearchProblem(PositionSearchProblem):
"""
A search problem for finding a path to any food.
This search problem is just like the PositionSearchProblem, but has a
different goal test, which you need to fill in below. The state space and
successor function do not need to be changed.
The class definition above, AnyFoodSearchProblem(PositionSearchProblem),
inherits the methods of the PositionSearchProblem.
You can use this search problem to help you fill in the findPathToClosestDot
method.
"""
def __init__(self, gameState):
"Stores information from the gameState. You don't need to change this."
# Store the food for later reference
self.food = gameState.getFood()
# Store info for the PositionSearchProblem (no need to change this)
self.walls = gameState.getWalls()
self.startState = gameState.getPacmanPosition()
self.costFn = lambda x: 1
self._visited, self._visitedlist, self._expanded = {}, [], 0 # DO NOT CHANGE
def isGoalState(self, state):
"""
The state is Pacman's position. Fill this in with a goal test that will
complete the problem definition.
"""
x,y = state
"*** YOUR CODE HERE ***"
return self.food[x][y]
def mazeDistance(point1, point2, gameState):
"""
Returns the maze distance between any two points, using the search functions
you have already built. The gameState can be any game state -- Pacman's
position in that state is ignored.
Example usage: mazeDistance( (2,4), (5,6), gameState)
This might be a useful helper function for your ApproximateSearchAgent.
"""
x1, y1 = point1
x2, y2 = point2
walls = gameState.getWalls()
assert not walls[x1][y1], 'point1 is a wall: ' + str(point1)
assert not walls[x2][y2], 'point2 is a wall: ' + str(point2)
prob = PositionSearchProblem(gameState, start=point1, goal=point2, warn=False, visualize=False)
return len(search.bfs(prob))
| [
"madhav.soni@berkeley.edu"
] | madhav.soni@berkeley.edu |
023d1d8dece7491ac60d165dac3295008bf0a004 | 6109a95a284891792c35d0d19906ab8d1697f9c7 | /src/k8s-configuration/azext_k8s_configuration/vendored_sdks/v2021_05_01_preview/aio/operations/_operations.py | 3c82397333fb155b013c9017f213f97b26d8e9e6 | [
"MIT",
"LicenseRef-scancode-generic-cla"
] | permissive | Tatsinnit/azure-cli-extensions | 3e5a1752edced00d7c33660027d2c17fae074569 | a1959b123d4c11149adae2728ab5791949889d54 | refs/heads/master | 2022-10-05T17:40:10.825889 | 2022-03-16T10:33:56 | 2022-03-16T10:33:56 | 250,102,909 | 0 | 0 | MIT | 2020-03-25T22:12:01 | 2020-03-25T22:12:01 | null | UTF-8 | Python | false | false | 4,949 | py | # coding=utf-8
# --------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for license information.
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
from typing import Any, AsyncIterable, Callable, Dict, Generic, Optional, TypeVar
import warnings
from azure.core.async_paging import AsyncItemPaged, AsyncList
from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error
from azure.core.pipeline import PipelineResponse
from azure.core.pipeline.transport import AsyncHttpResponse, HttpRequest
from azure.mgmt.core.exceptions import ARMErrorFormat
from ... import models as _models
T = TypeVar('T')
ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
class Operations:
"""Operations async operations.
You should not instantiate this class directly. Instead, you should create a Client instance that
instantiates it for you and attaches it as an attribute.
:ivar models: Alias to model classes used in this operation group.
:type models: ~azure.mgmt.kubernetesconfiguration.v2021_05_01_preview.models
:param client: Client for service requests.
:param config: Configuration of service client.
:param serializer: An object model serializer.
:param deserializer: An object model deserializer.
"""
models = _models
def __init__(self, client, config, serializer, deserializer) -> None:
self._client = client
self._serialize = serializer
self._deserialize = deserializer
self._config = config
def list(
self,
**kwargs: Any
) -> AsyncIterable["_models.ResourceProviderOperationList"]:
"""List all the available operations the KubernetesConfiguration resource provider supports.
:keyword callable cls: A custom type or function that will be passed the direct response
:return: An iterator like instance of either ResourceProviderOperationList or the result of cls(response)
:rtype: ~azure.core.async_paging.AsyncItemPaged[~azure.mgmt.kubernetesconfiguration.v2021_05_01_preview.models.ResourceProviderOperationList]
:raises: ~azure.core.exceptions.HttpResponseError
"""
cls = kwargs.pop('cls', None) # type: ClsType["_models.ResourceProviderOperationList"]
error_map = {
401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError
}
error_map.update(kwargs.pop('error_map', {}))
api_version = "2021-05-01-preview"
accept = "application/json"
def prepare_request(next_link=None):
# Construct headers
header_parameters = {} # type: Dict[str, Any]
header_parameters['Accept'] = self._serialize.header("accept", accept, 'str')
if not next_link:
# Construct URL
url = self.list.metadata['url'] # type: ignore
# Construct parameters
query_parameters = {} # type: Dict[str, Any]
query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str')
request = self._client.get(url, query_parameters, header_parameters)
else:
url = next_link
query_parameters = {} # type: Dict[str, Any]
request = self._client.get(url, query_parameters, header_parameters)
return request
async def extract_data(pipeline_response):
deserialized = self._deserialize('ResourceProviderOperationList', pipeline_response)
list_of_elem = deserialized.value
if cls:
list_of_elem = cls(list_of_elem)
return deserialized.next_link or None, AsyncList(list_of_elem)
async def get_next(next_link=None):
request = prepare_request(next_link)
pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs)
response = pipeline_response.http_response
if response.status_code not in [200]:
error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, response)
map_error(status_code=response.status_code, response=response, error_map=error_map)
raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
return pipeline_response
return AsyncItemPaged(
get_next, extract_data
)
list.metadata = {'url': '/providers/Microsoft.KubernetesConfiguration/operations'} # type: ignore
| [
"noreply@github.com"
] | noreply@github.com |
3197b6b704d03772985a826493370366f41f9961 | 78f1aaaeffb8f48b4a012f6700125348e396fe90 | /LaTeX/report_test/inscription_tournoi.py | 82f5bb36a479f342ead3a36b23ba89960c9e63d3 | [] | no_license | fthuin/software_engineering_project | eda625fe90f04f2a0d4652be6d77cd92a240a014 | 3e2bc1bb1ba4655060c3c41367bb736961eae031 | refs/heads/master | 2021-01-16T23:01:33.869567 | 2015-12-15T20:29:02 | 2015-12-15T20:29:02 | 42,591,013 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 6,632 | py | # -*- coding: utf-8 -*-
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.common.keys import Keys
from selenium.webdriver.support.ui import Select
from selenium.common.exceptions import NoSuchElementException
from selenium.common.exceptions import NoAlertPresentException
import unittest, time, re
WAIT_TIME = 1
class InscriptionTournoi(unittest.TestCase):
def setUp(self):
profile = webdriver.FirefoxProfile("/home/florian/.mozilla/firefox/mwad0hks.default")
self.driver = webdriver.Firefox(profile)
self.driver.implicitly_wait(30)
self.base_url = "http://localhost:8000"
self.verificationErrors = []
self.accept_next_alert = True
def test_inscription_tournoi(self):
driver = self.driver
driver.get(self.base_url + "/")
time.sleep(WAIT_TIME)
driver.find_element_by_css_selector("button.btn.btn-default").click()
driver.find_element_by_name("username").clear()
driver.find_element_by_name("username").send_keys("Florian")
time.sleep(WAIT_TIME)
driver.find_element_by_name("password").clear()
driver.find_element_by_name("password").send_keys("azerty")
time.sleep(WAIT_TIME)
driver.find_element_by_xpath("//button[@type='submit']").click()
time.sleep(WAIT_TIME)
driver.find_element_by_xpath("//button[@onclick=\"location.href='/tournoi/inscriptionTournoi';\"]").click()
time.sleep(WAIT_TIME)
driver.find_element_by_xpath("//td[2]").click()
time.sleep(WAIT_TIME)
driver.find_element_by_name("extra").click()
time.sleep(WAIT_TIME)
driver.find_element_by_id("remarque").clear()
driver.find_element_by_id("remarque").send_keys("Ceci est un commentaire")
time.sleep(WAIT_TIME)
driver.find_element_by_id("InscriptionButton").click()
time.sleep(WAIT_TIME)
driver.find_element_by_xpath("(//button[@type='button'])[2]").click()
time.sleep(WAIT_TIME)
driver.find_element_by_link_text("Deconnexion").click()
time.sleep(WAIT_TIME)
driver.find_element_by_css_selector("button.btn.btn-default").click()
driver.find_element_by_name("username").clear()
driver.find_element_by_name("username").send_keys("Abires")
time.sleep(WAIT_TIME)
driver.find_element_by_name("password").clear()
driver.find_element_by_name("password").send_keys("Eev4eede0h")
time.sleep(WAIT_TIME)
driver.find_element_by_xpath("//button[@type='submit']").click()
time.sleep(WAIT_TIME)
driver.find_element_by_css_selector("body").click()
time.sleep(WAIT_TIME)
driver.find_element_by_xpath("//td[4]").click()
time.sleep(WAIT_TIME)
driver.find_element_by_name("extra").click()
time.sleep(WAIT_TIME)
driver.find_element_by_id("remarque").clear()
driver.find_element_by_id("remarque").send_keys("Commentaire ><")
time.sleep(WAIT_TIME)
driver.find_element_by_name("action").click()
time.sleep(WAIT_TIME)
driver.find_element_by_link_text("Terrains").click()
time.sleep(WAIT_TIME)
driver.find_element_by_xpath("//button[@onclick=\"location.href='/terrain/enregistrement';\"]").click()
time.sleep(WAIT_TIME)
driver.find_element_by_id("street").clear()
time.sleep(WAIT_TIME)
driver.find_element_by_id("street").send_keys(u"Rue Archimède")
driver.find_element_by_id("number").clear()
time.sleep(WAIT_TIME)
driver.find_element_by_id("number").send_keys("2")
driver.find_element_by_id("postalcode").clear()
time.sleep(WAIT_TIME)
driver.find_element_by_id("postalcode").send_keys("1348")
driver.find_element_by_id("locality").clear()
time.sleep(WAIT_TIME)
driver.find_element_by_id("locality").send_keys("Ottignies-Louvain-la-Neuve")
driver.find_element_by_id("acces").clear()
time.sleep(WAIT_TIME)
driver.find_element_by_id("acces").send_keys(u"Par derrière la maison")
time.sleep(WAIT_TIME)
Select(driver.find_element_by_name("matiere")).select_by_visible_text("Quick")
time.sleep(WAIT_TIME)
Select(driver.find_element_by_name("type")).select_by_visible_text("Ouvert")
time.sleep(WAIT_TIME)
Select(driver.find_element_by_name("etat")).select_by_visible_text("Bon")
time.sleep(WAIT_TIME)
driver.find_element_by_name("dispoSamedi").click()
time.sleep(WAIT_TIME)
driver.find_element_by_id("comment").clear()
driver.find_element_by_id("comment").send_keys(u"Merci de ramasser vos déchets cette année")
time.sleep(WAIT_TIME)
driver.find_element_by_xpath("(//button[@type='button'])[3]").click()
time.sleep(WAIT_TIME)
driver.find_element_by_xpath("//td[3]").click()
time.sleep(WAIT_TIME)
driver.find_element_by_xpath("(//button[@type='button'])[2]").click()
time.sleep(WAIT_TIME)
driver.find_element_by_link_text("Deconnexion").click()
time.sleep(WAIT_TIME)
driver.get(self.base_url + "/")
driver.find_element_by_css_selector("button.btn.btn-default").click()
driver.find_element_by_name("password").clear()
driver.find_element_by_name("password").send_keys("azerty")
time.sleep(WAIT_TIME)
driver.find_element_by_name("username").clear()
driver.find_element_by_name("username").send_keys("Florian")
time.sleep(WAIT_TIME*5)
time.sleep(WAIT_TIME)
driver.find_element_by_xpath("//button[@type='submit']").click()
time.sleep(WAIT_TIME*10)
driver.close()
def is_element_present(self, how, what):
try: self.driver.find_element(by=how, value=what)
except NoSuchElementException as e: return False
return True
def is_alert_present(self):
try: self.driver.switch_to_alert()
except NoAlertPresentException as e: return False
return True
def close_alert_and_get_its_text(self):
try:
alert = self.driver.switch_to_alert()
alert_text = alert.text
if self.accept_next_alert:
alert.accept()
else:
alert.dismiss()
return alert_text
finally: self.accept_next_alert = True
def tearDown(self):
self.driver.quit()
self.assertEqual([], self.verificationErrors)
if __name__ == "__main__":
unittest.main()
| [
"florian.thuin@student.uclouvain.be"
] | florian.thuin@student.uclouvain.be |
752dbda69d594e120006e5dafc97ceed904f7a19 | ea13d23b9d9c7fa5b11c8f0780fbe2702ba604a3 | /단계별/9_math_1/10250.py | 59b9906024958adf1846c1a954e7bf31d5ccddc5 | [] | no_license | boxtobox/aimicpc | 51c2ab1b5b384be6eb9f4a6d4a88e0db05ff6875 | 25649d99d89fa31a3315a7b1c46413cb77de1ca6 | refs/heads/master | 2022-11-21T14:13:23.725494 | 2020-07-18T08:05:15 | 2020-07-18T08:05:15 | 258,359,511 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 263 | py | from sys import stdin
from math import ceil
N = int(stdin.readline())
for _ in range(N):
H, W, N = map(int, stdin.readline().split())
w = ceil(N/H)
if N % H:
h = N % H
else:
h = H
roomname = h * 100 + w
print(roomname)
| [
"grandnex@gmail.com"
] | grandnex@gmail.com |
eec9de39af9002e5ffe1c66285ec2b4983d3246c | ffead9c586803a9c8b53a1fe16ad33f91bdd71c8 | /4/TupleUnpackingExample.py | eb47e54f5acdf02eb4f3cd5787b78bc938d09e81 | [] | no_license | angsdey2/python-examples | 63489f4d39ca052a2dbce98cd4254eb3b34b0101 | d3282181eae04d921f66684b6489d6517949ab25 | refs/heads/master | 2022-11-27T03:52:48.774509 | 2020-08-05T18:10:46 | 2020-08-05T18:10:46 | 285,367,550 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 612 | py | # -*- coding: utf-8 -*-
"""
Created on Mon Aug 3 22:39:39 2020
@author: Angshuman
"""
examScore = [("AD", 500), ("KR", 600), ("SM", 7000), ("DS", 800)];
def find_highest_scsorer(examScore):
highestScorerName ='';
currentMax=0;
for name,score in examScore:
if score>currentMax:
currentMax= score;
highestScorerName = name;
else:
pass;
return (highestScorerName,currentMax);
item = find_highest_scsorer(examScore);
print(item);
name,score = find_highest_scsorer(examScore);
print(f"{name} is the highest scorer with {score} marks");
| [
"angshuman.dey@cognizant.com"
] | angshuman.dey@cognizant.com |
5b1b6d889aa3a32894887142d13c3972165aaa18 | 31c9363538f4379ff1643784dda025456059dda3 | /passporteye/mrz/scripts.py | 62752ca98aef98315eb11cc83ea14bc5c9500896 | [
"MIT"
] | permissive | solvire/PassportEye | b3f95debd15527c1190aaea1aca913d500452305 | 1286be85ab72d058aa69a3912961bfbb36529c78 | refs/heads/master | 2021-06-26T23:19:04.456317 | 2017-09-15T21:17:27 | 2017-09-15T21:17:27 | 103,700,512 | 0 | 0 | null | 2017-09-15T20:54:34 | 2017-09-15T20:54:33 | null | UTF-8 | Python | false | false | 6,402 | py | '''
PassportEye::MRZ: Machine-readable zone extraction and parsing.
Command-line scripts
Author: Konstantin Tretyakov
License: MIT
'''
import argparse, time, glob, pkg_resources, os, multiprocessing, logging, json, shutil
from collections import Counter
from skimage import io
import passporteye
from .image import read_mrz
def process_file(params):
"""
Processes a file and returns the parsed MRZ (or None if no candidate regions were even found).
"""
tic = time.time()
filename, save_roi = params
try:
mrz = read_mrz(filename, save_roi=save_roi)
except Exception:
mrz = None
walltime = time.time() - tic
return (filename, mrz, walltime)
def evaluate_mrz():
"""
A script for evaluating the current MRZ recognition pipeline by applying it to a list of files in a directory and reporting how well it went.
"""
parser = argparse.ArgumentParser(description='Run the MRZ OCR recognition algorithm on the sample test data, reporting the quality summary.')
parser.add_argument('-j', '--jobs', default=1, type=int, help='Number of parallel jobs to run')
parser.add_argument('-dd', '--data-dir', default=pkg_resources.resource_filename('passporteye.mrz', 'testdata'),
help='Read files from this directory instead of the package test files')
parser.add_argument('-sd', '--success-dir', default=None,
help='Copy files with successful (nonzero score) extraction results to this directory')
parser.add_argument('-fd', '--fail-dir', default=None,
help='Copy files with unsuccessful (zero score) extraction resutls to this directory')
parser.add_argument('-rd', '--roi-dir', default=None,
help='Extract ROIs to this directory')
parser.add_argument('-l', '--limit', default=-1, type=int, help='Only process the first <limit> files in the directory.')
args = parser.parse_args()
files = sorted(glob.glob(os.path.join(args.data_dir, '*.*')))
if args.limit >= 0:
files = files[0:args.limit]
logging.basicConfig(level=logging.INFO)
log = logging.getLogger("evaluate_mrz")
tic = time.time()
pool = multiprocessing.Pool(args.jobs)
log.info("Preparing computation for %d files from %s" % (len(files), args.data_dir))
log.info("Running %d workers" % args.jobs)
results = []
save_roi = args.roi_dir is not None
for d in [args.success_dir, args.fail_dir, args.roi_dir]:
if d is not None and not os.path.isdir(d):
os.mkdir(d)
def valid_score(mrz):
return 0 if mrz is None else mrz.valid_score
def score_change_type(filename, mrz):
try:
new_score = mrz.valid_score if mrz is not None else 0
old_score = int(os.path.basename(filename).split('_')[0])
schange = new_score - old_score
return '=' if schange == 0 else ('>' if schange > 0 else '<')
except Exception:
return '?'
method_stats = Counter()
for result in pool.imap_unordered(process_file, [(f, save_roi) for f in files]):
filename, mrz, walltime = result
results.append(result)
log.info("Processed %s in %0.2fs (score %d) [%s]" % (os.path.basename(filename), walltime, valid_score(mrz), score_change_type(filename, mrz)))
log.debug("\t%s" % str(mrz))
vs = valid_score(mrz)
if args.success_dir is not None and vs > 0:
shutil.copyfile(filename, os.path.join(args.success_dir, '%d_%s' % (vs, os.path.basename(filename))))
if args.fail_dir is not None and vs == 0:
shutil.copyfile(filename, os.path.join(args.fail_dir, '%d_%s' % (vs, os.path.basename(filename))))
if args.roi_dir is not None and mrz is not None and 'roi' in mrz.aux:
roi_fn = '%d_roi_%s.png' % (vs, os.path.basename(filename))
io.imsave(os.path.join(args.roi_dir, roi_fn), mrz.aux['roi'])
if vs > 0 and 'method' in mrz.aux:
method_stats[mrz.aux['method']] += 1
num_files = len(results)
score_changes = [score_change_type(fn, mrz) for fn, mrz, wt in results]
scores = [valid_score(mrz) for fn, mrz, wt in results]
num_perfect = scores.count(100)
num_invalid = scores.count(0)
total_score = sum(scores)
total_computation_walltime = sum([wt for fn, mrz, wt in results])
total_walltime = time.time() - tic
log.info("Completed")
print("Walltime: %0.2fs" % total_walltime)
print("Compute walltime: %0.2fs" % total_computation_walltime)
print("Processed files: %d" % num_files)
print("Perfect parses: %d" % num_perfect)
print("Invalid parses: %d" % num_invalid)
print("Improved parses: %d" % len(filter(lambda x: x == '>', score_changes)))
print("Worsened parses: %d" % len(filter(lambda x: x == '<', score_changes)))
print("Total score: %d" % total_score)
print("Mean score: %0.2f" % (float(total_score)/num_files))
print("Mean compute time: %0.2fs" % (total_computation_walltime/num_files))
print("Methods used:")
for stat in method_stats.most_common():
print(" %s: %d" % stat)
def mrz():
"""
Command-line script for extracting MRZ from a given image
"""
parser = argparse.ArgumentParser(description='Run the MRZ OCR recognition algorithm on the given image.')
parser.add_argument('filename')
parser.add_argument('--json', action='store_true', help='Produce JSON (rather than tabular) output')
parser.add_argument('-r', '--save-roi', default=None,
help='Output the region of the image that is detected to contain the MRZ to the given png file')
parser.add_argument('--version', action='version', version='PassportEye MRZ v%s' % passporteye.__version__)
args = parser.parse_args()
filename, mrz, walltime = process_file((args.filename, args.save_roi is not None))
d = mrz.to_dict() if mrz is not None else {'mrz_type': None, 'valid': False, 'valid_score': 0}
d['walltime'] = walltime
d['filename'] = filename
if args.save_roi is not None and mrz is not None and 'roi' in mrz.aux:
io.imsave(args.save_roi, mrz.aux['roi'])
if not args.json:
for k in d:
print("%s\t%s" % (k, str(d[k])))
else:
print(json.dumps(d, indent=2)) | [
"kt@ut.ee"
] | kt@ut.ee |
9e32c9c0aa9172a40b197d8db987c89b23d6b43b | eacf8153f3b981d54734d71275576ac33f03e921 | /pegasus/tests/functional/test_authentication.py | 97233a50e03bd54540753a01879da76abb4513e8 | [] | no_license | enriquebits/bookmanizer | f9b43c18844dbcb32a5b560cbf5f3b539c3434c2 | 326b7a9ba8f2dcfce5afeedadebea6ca2ff24255 | refs/heads/master | 2016-09-06T12:17:39.208517 | 2015-05-25T02:14:57 | 2015-05-25T02:14:57 | 20,838,468 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,332 | py | # -*- coding: utf-8 -*-
"""
Integration tests for the :mod:`repoze.who`-powered authentication sub-system.
As pegasus grows and the authentication method changes, only these tests
should be updated.
"""
from __future__ import unicode_literals
from nose.tools import eq_, ok_
from pegasus.tests import TestController
class TestAuthentication(TestController):
"""
Tests for the default authentication setup.
If your application changes how the authentication layer is configured
those tests should be updated accordingly
"""
application_under_test = 'main'
def test_forced_login(self):
"""Anonymous users are forced to login
Test that anonymous users are automatically redirected to the login
form when authorization is denied. Next, upon successful login they
should be redirected to the initially requested page.
"""
# Requesting a protected area
resp = self.app.get('/secc/', status=302)
ok_( resp.location.startswith('http://localhost/login'))
# Getting the login form:
resp = resp.follow(status=200)
form = resp.form
# Submitting the login form:
form['login'] = 'manager'
form['password'] = 'managepass'
post_login = form.submit(status=302)
# Being redirected to the initially requested page:
ok_(post_login.location.startswith('http://localhost/post_login'))
initial_page = post_login.follow(status=302)
ok_('authtkt' in initial_page.request.cookies,
"Session cookie wasn't defined: %s" % initial_page.request.cookies)
ok_(initial_page.location.startswith('http://localhost/secc/'),
initial_page.location)
def test_voluntary_login(self):
"""Voluntary logins must work correctly"""
# Going to the login form voluntarily:
resp = self.app.get('/login', status=200)
form = resp.form
# Submitting the login form:
form['login'] = 'manager'
form['password'] = 'managepass'
post_login = form.submit(status=302)
# Being redirected to the home page:
ok_(post_login.location.startswith('http://localhost/post_login'))
home_page = post_login.follow(status=302)
ok_('authtkt' in home_page.request.cookies,
'Session cookie was not defined: %s' % home_page.request.cookies)
eq_(home_page.location, 'http://localhost/')
def test_logout(self):
"""Logouts must work correctly"""
# Logging in voluntarily the quick way:
resp = self.app.get('/login_handler?login=manager&password=managepass',
status=302)
resp = resp.follow(status=302)
ok_('authtkt' in resp.request.cookies,
'Session cookie was not defined: %s' % resp.request.cookies)
# Logging out:
resp = self.app.get('/logout_handler', status=302)
ok_(resp.location.startswith('http://localhost/post_logout'))
# Finally, redirected to the home page:
home_page = resp.follow(status=302)
authtkt = home_page.request.cookies.get('authtkt')
ok_(not authtkt or authtkt == 'INVALID',
'Session cookie was not deleted: %s' % home_page.request.cookies)
eq_(home_page.location, 'http://localhost/')
| [
"enrique_empo@hotmail.com"
] | enrique_empo@hotmail.com |
e6bfbadc51ffa309278e7dec7bdd95cf06c0006d | 7565d21f09d43026dbee81a957ef9c8aed08ae69 | /rate-limiter/utils/constants.py | 0d6f03a9d684d4167c6a567f8af109874e388ab3 | [] | no_license | syedmrizwan/notification-service | 7cebfc8750f54d26dd2075d9e8b48a3612663378 | a045647b61d005287397a39282c32dc6c5c5992e | refs/heads/master | 2023-02-02T11:18:15.665657 | 2020-12-17T07:08:34 | 2020-12-17T07:08:34 | 318,601,552 | 0 | 0 | null | 2020-12-11T12:52:11 | 2020-12-04T18:21:53 | Go | UTF-8 | Python | false | false | 80 | py | '''Constants'''
LOGGER_NAME = 'Rate Limiter'
LOGGING_FILE_NAME = 'logging.conf'
| [
"muhammad.rizwan@emumba.com"
] | muhammad.rizwan@emumba.com |
796c821dc503856d3333df944620e9880c66973e | e9e083ebe7fad28e16d74209473eb85f578401e2 | /frontpage/views.py | 13d2c8a5926d8292b0a24c62af3992d9b1ac1945 | [] | no_license | 4x4falcon/fosm-website-2018 | 9dfb3ea3904c110d364b23fe7c710852fccd6c1d | f48ed7d527ebf0e77fff300979b09a9b8dcb220b | refs/heads/master | 2021-05-04T15:23:22.813168 | 2018-06-26T06:51:05 | 2018-06-26T06:51:05 | 120,226,991 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 710 | py | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from __future__ import print_function
from django.shortcuts import render, reverse
import pgmap
from querymap.views import p
# Create your views here.
def index(request):
t = p.GetTransaction("ACCESS SHARE")
errStr = pgmap.PgMapError()
value = int(t.GetMetaValue("readonly".encode('utf-8'), errStr))
dbStatus = "OK"
if value != 0:
dbStatus = "Read only"
t.Commit()
return render(request, 'frontpage/index.html', {'db_status': dbStatus})
def getting_started(request):
return render(request, 'frontpage/getting_started.html', {})
def whats_different(request):
return render(request, 'frontpage/whats_different.html', {})
| [
"ross@freestreetmap.org"
] | ross@freestreetmap.org |
2779073c282e2d634aee8ebd19099d2006f1b000 | 6887728a11c8b59b171a192f6d3801bae21d6bfe | /motor.py | d2c4992df0e53c993c51c9fde0b991a43cb001fc | [] | no_license | uprightws/Motor | 2a3ee87650c6dd6b1cafa1a6a062748a89f6a804 | 207d25044b55c3d1c140896f610580fa2761aefa | refs/heads/master | 2020-05-17T21:36:08.410101 | 2019-04-28T02:02:21 | 2019-04-28T02:02:21 | 183,977,242 | 1 | 0 | null | 2019-04-29T01:08:40 | 2019-04-29T01:08:39 | null | UTF-8 | Python | false | false | 7,570 | py | # -*- coding: utf-8 -*-
"""
-------------------------------------------------
File Name : train
Author : 雨住风停松子落
E-mail :
date : 2019/4/25
Description:
-------------------------------------------------
Change Activity:
2019/4/25:
-------------------------------------------------
"""
__author__ = '雨住风停松子落'
import os
import pandas as pd
import numpy as np
from sklearn.ensemble import AdaBoostClassifier
from sklearn.ensemble import RandomForestClassifier
from sklearn.ensemble import BaggingClassifier
from sklearn.ensemble import GradientBoostingClassifier
from lightgbm import LGBMClassifier
from sklearn.ensemble import VotingClassifier
# from sklearn.neural_network import MLPClassifier
from sklearn.tree import DecisionTreeClassifier
from sklearn.neighbors import KNeighborsClassifier
from sklearn.linear_model import LogisticRegression
from sklearn.naive_bayes import GaussianNB
from xgboost import XGBClassifier
from sklearn.externals import joblib
from sklearn.utils import shuffle
import warnings
warnings.filterwarnings("ignore")
def build_model(data, mode='train'):
'''
初始化模型，包含各模型使用的特征下标
:param data: 数据集
:param mode: train or test
:return:
'''
filter_features_1 = [data.columns[idx] for idx in
[0, 1, 2, 3, 4, 5, 7, 9, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22, 23, 26, 27, 28, 29,
31, 33, 34, 35, 36, 37, 38, 39, 42]]
filter_features_2 = [data.columns[idx] for idx in
[0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22, 23, 24, 25, 26, 27,
28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 42, 43]]
filter_features_3 = [data.columns[idx] for idx in
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25,
26, 27,
28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43]]
if mode == 'train':
ada_clf = AdaBoostClassifier(
RandomForestClassifier(n_estimators=60, max_depth=13, min_samples_split=5,
min_samples_leaf=20, oob_score=True, random_state=0,
class_weight='balanced'),
algorithm="SAMME", n_estimators=1200, learning_rate=0.05
)
bag_clf = BaggingClassifier(
base_estimator=RandomForestClassifier(n_estimators=60, max_depth=13, min_samples_split=5,
min_samples_leaf=20, oob_score=True, random_state=0,
class_weight='balanced'),
n_estimators=500, max_samples=1.0, max_features=1.0, bootstrap=True, bootstrap_features=False, n_jobs=1,
random_state=0
)
gbdt_clf = GradientBoostingClassifier(
n_estimators=1200, learning_rate=0.05, min_samples_leaf=60, max_depth=10, min_samples_split=5,
subsample=0.7, random_state=0, loss='deviance'
)
lgbm_clf = LGBMClassifier(
boosting_type='gbdt', num_leaves=51, max_depth=-1, learning_rate=0.05, n_estimators=600,
subsample_for_bin=1000, objective='binary', class_weight='balanced', min_split_gain=0.0,
min_child_weight=0.001, min_child_samples=20, subsample=1.0, subsample_freq=0, colsample_bytree=1.0,
reg_alpha=3.5, reg_lambda=1.0, random_state=None, importance_type='gain', silent=True
)
vote_clf = VotingClassifier(
estimators=[
(
'LogisticRegression',
LogisticRegression(penalty='l2', solver='lbfgs', verbose=0)
),
(
'DecisionTreeClassifier', DecisionTreeClassifier()
),
(
'RandomForestClassifier', RandomForestClassifier(
n_estimators=60, max_depth=13, min_samples_split=5, min_samples_leaf=20,
oob_score=True, random_state=0)
),
('GradientBoostingClassifier', GradientBoostingClassifier(n_estimators=1200, verbose=0)),
('GaussianNB', GaussianNB()),
('KNeighborsClassifier', KNeighborsClassifier())
],
voting='soft'
)
xgb_clf = XGBClassifier(
learning_rate=0.01, n_estimators=5000, max_depth=6, min_child_weight=1, gamma=0., subsample=0.8,
colsample_btree=0.8, objective='binary:logistic', scale_pos_weight=1, min_samples_split=5,
min_samples_leaf=60, seed=27, reg_alpha=0.005, random_state=0
)
clfs = {
'AdaBoostClassifier': [ada_clf, filter_features_1],
'BaggingClassifier': [bag_clf, filter_features_1],
'GradientBoostingClassifier': [gbdt_clf, filter_features_2],
'LGBMClassifier': [lgbm_clf, filter_features_3],
'VotingClassifier': [vote_clf, filter_features_1],
'XGBClassifier': [xgb_clf, filter_features_1],
}
elif mode == 'test':
clfs = {
'AdaBoostClassifier': filter_features_1,
'BaggingClassifier': filter_features_1,
'GradientBoostingClassifier': filter_features_2,
'LGBMClassifier': filter_features_3,
'VotingClassifier': filter_features_1,
'XGBClassifier': filter_features_1,
}
else:
raise Exception("mode must be train or test !!")
return clfs
def train(train_data, savedPath, upsampling):
'''
训练
:param train_data:
:param savedPath:
:return:
'''
clfs = build_model(train_data, mode='train')
for clf_name, [clf, filter_features] in clfs.items():
trainData = train_data
for i in range(upsampling[clf_name] - 1):
trainData = pd.concat([trainData, train_data.tail(30)], axis=0)
if clf_name != 'VotingClassifier':
print 'shuffle'
trainData = shuffle(trainData)
# trainData.dropna(inplace=True)
clf.fit(trainData[filter_features], trainData[train_data.columns[45]])
print(clf_name, '\t', clf.score(train_data[filter_features], train_data[train_data.columns[45]]))
joblib.dump(clf, savedPath + clf_name + '.pkl')
def test(test_data, modelPath, savedPath, threshold):
'''
测试
:param test_data:
:param modelPath:
:param savedPath:
:param threshold: 不同方法传入不同阈值
:return:
'''
clfs = build_model(test_data, mode='test')
result = []
idx = 0
for clf_name, filter_features in clfs.items():
clf = joblib.load(modelPath + clf_name + '.pkl')
p_proba = clf.predict_proba(test_data[filter_features])
p_list_midl = [p[1] for p in p_proba]
p_list_midl.sort(reverse=True)
p_list = [1 if p[1] > p_list_midl[int(len(p_list_midl) * threshold[clf_name])] else 0 for p in p_proba]
if idx == 0:
result = p_list
else:
result = [1 if (result[i] == 1 and p_list[i] == 1) else 0 for i in range(5738)]
idx = idx + 1
res_df = pd.DataFrame(data=np.column_stack(
[np.reshape(test_data[test_data.columns[44]], int(test_data[test_data.columns[0]].count())), result]),
columns=['idx', 'result'])
res_df.to_csv(savedPath, index=False)
print("done!")
| [
"uprightws@live.cn"
] | uprightws@live.cn |
5f5aa4594437d785225bffd8a12312b3ccdfb9b4 | 99441588c7d6159064d9ce2b94d3743a37f85d33 | /cmake-build-debug/read_CAN/catkin_generated/pkg.develspace.context.pc.py | 2581bf96c93bf3ea493f4c25cd72ba5837837945 | [] | no_license | YZT1997/robolab_project | 2786f8983c4b02040da316cdd2c8f9bb73e2dd4c | a7edb588d3145356566e9dcc37b03f7429bcb7d6 | refs/heads/master | 2023-09-02T21:28:01.280464 | 2021-10-14T02:06:35 | 2021-10-14T02:06:35 | 369,128,037 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 370 | py | # generated from catkin/cmake/template/pkg.context.pc.in
CATKIN_PACKAGE_PREFIX = ""
PROJECT_PKG_CONFIG_INCLUDE_DIRS = "".split(';') if "" != "" else []
PROJECT_CATKIN_DEPENDS = "".replace(';', ' ')
PKG_CONFIG_LIBRARIES_WITH_PREFIX = "".split(';') if "" != "" else []
PROJECT_NAME = "read_CAN"
PROJECT_SPACE_DIR = "/home/yangzt/catkin_ws/devel"
PROJECT_VERSION = "0.0.0"
| [
"yangzt_0943@163.com"
] | yangzt_0943@163.com |
d09084667dcf104c853d56b0ea17fabff94f75a9 | 32747097a4eae95a85c0e153a797c2689eb76052 | /recipes/android/src/android/broadcast.py | ba3dfc97655e41f177a86cd2bda7c1ea5bd3e382 | [
"LicenseRef-scancode-unknown-license-reference",
"MIT"
] | permissive | lbryio/lbry-android-sdk | fa973940c38c8eb7d81a0b4698fa4de353eaf58c | d9d81957647cb81f7227205cbb4ecba515556e74 | refs/heads/master | 2022-12-14T10:36:05.641392 | 2022-11-23T20:03:41 | 2022-11-23T20:03:41 | 241,861,403 | 3 | 4 | MIT | 2022-12-11T20:47:57 | 2020-02-20T10:57:08 | C | UTF-8 | Python | false | false | 3,140 | py | # -------------------------------------------------------------------
# Broadcast receiver bridge
from jnius import autoclass, PythonJavaClass, java_method
from android.config import JAVA_NAMESPACE, JNI_NAMESPACE
class BroadcastReceiver(object):
class Callback(PythonJavaClass):
__javainterfaces__ = [JNI_NAMESPACE + '/GenericBroadcastReceiverCallback']
__javacontext__ = 'app'
def __init__(self, callback, *args, **kwargs):
self.callback = callback
PythonJavaClass.__init__(self, *args, **kwargs)
@java_method('(Landroid/content/Context;Landroid/content/Intent;)V')
def onReceive(self, context, intent):
self.callback(context, intent)
def __init__(self, callback, actions=None, categories=None):
super(BroadcastReceiver, self).__init__()
self.callback = callback
if not actions and not categories:
raise Exception('You need to define at least actions or categories')
def _expand_partial_name(partial_name):
if '.' in partial_name:
return partial_name # Its actually a full dotted name
else:
name = 'ACTION_{}'.format(partial_name.upper())
if not hasattr(Intent, name):
raise Exception('The intent {} doesnt exist'.format(name))
return getattr(Intent, name)
# resolve actions/categories first
Intent = autoclass('android.content.Intent')
resolved_actions = [_expand_partial_name(x) for x in actions or []]
resolved_categories = [_expand_partial_name(x) for x in categories or []]
# resolve android API
GenericBroadcastReceiver = autoclass(JAVA_NAMESPACE + '.GenericBroadcastReceiver')
IntentFilter = autoclass('android.content.IntentFilter')
HandlerThread = autoclass('android.os.HandlerThread')
# create a thread for handling events from the receiver
self.handlerthread = HandlerThread('handlerthread')
# create a listener
self.listener = BroadcastReceiver.Callback(self.callback)
self.receiver = GenericBroadcastReceiver(self.listener)
self.receiver_filter = IntentFilter()
for x in resolved_actions:
self.receiver_filter.addAction(x)
for x in resolved_categories:
self.receiver_filter.addCategory(x)
def start(self):
Handler = autoclass('android.os.Handler')
self.handlerthread.start()
self.handler = Handler(self.handlerthread.getLooper())
self.context.registerReceiver(self.receiver, self.receiver_filter, None,
self.handler)
def stop(self):
self.context.unregisterReceiver(self.receiver)
self.handlerthread.quit()
@property
def context(self):
from os import environ
if 'PYTHON_SERVICE_ARGUMENT' in environ:
PythonService = autoclass(JAVA_NAMESPACE + '.PythonService')
return PythonService.mService
PythonActivity = autoclass(JAVA_NAMESPACE + '.PythonActivity')
return PythonActivity.mActivity
| [
"akinwale@gmail.com"
] | akinwale@gmail.com |
c3a87e73a1c9e46f95c2c5bbf037974632f09470 | 747f759311d404af31c0f80029e88098193f6269 | /addons/esale_joomla/__terp__.py | 0b9ba5da767aab77ff4bccd6f9b18701e5bdec38 | [] | no_license | sgeerish/sirr_production | 9b0d0f7804a928c0c582ddb4ccb7fcc084469a18 | 1081f3a5ff8864a31b2dcd89406fac076a908e78 | refs/heads/master | 2020-05-19T07:21:37.047958 | 2013-09-15T13:03:36 | 2013-09-15T13:03:36 | 9,648,444 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 62 | py | /home/openerp/production/extra-addons/esale_joomla/__terp__.py | [
"geerish@omerp.net"
] | geerish@omerp.net |
2f4374a7fc6382c63983c08d36985b27c3c49257 | 07455048558230658249786db958701010afa1aa | /src/config.py | f12924262c1d471a7ddd2c2136c341fc5b4489ec | [] | no_license | lohithmunakala/Group-Classification | 73965201e4fce812fefcb8818f185ee948759b08 | 166a9ec91595a932d96e0a1da508bc9be574e06a | refs/heads/master | 2023-01-24T18:38:49.777583 | 2020-11-19T12:11:05 | 2020-11-19T12:11:05 | 289,323,026 | 0 | 1 | null | 2020-10-30T08:23:40 | 2020-08-21T17:06:29 | Jupyter Notebook | UTF-8 | Python | false | false | 1,044 | py | import os
#the path to where our data will be saved
DATASET_PATH = "input"
DATASET_PATH_COLAB = "/content/drive/My Drive/Group_Classification/input"
#inititializing the class labels
CLASSES = ["group of babies", "group of adults", "group of teenagers"]
#defining size of train, test, validation sets
TRAIN_SPLIT = 0.75
TEST_SPLIT = 0.25
VAL_SPLIT = 0.1
#defining the min lr, max lr, batch size, step size, CLR method and the no of epochs
MIN_LR = 1e-6
MAX_LR = 1e-4
BATHC_SIZE = 32
STEP_SIZE = 8
CLR_METHOD = "triangular"
NUM_EPOCHS = 48
#initializing the output model path
MODEL_PATH = os.path.sep.join(["output", "group classification model"])
MODEL_PATH_COLAB = "/content/drive/My Drive/Group_Classification/model"
#define the path to the output paths for images
LRFIND_PLOT_PATH = "/content/drive/My Drive/Group_Classification/output/LRFIND_PLOT.png"
TRAINING_PLOT_PATH = "/content/drive/My Drive/Group_Classification/output/TRAINING_PLOT.png"
CLR_PLOT_PATH = "/content/drive/My Drive/Group_Classification/output/CLR_PLOT.png"
| [
"lohithmunakala@gmail.com"
] | lohithmunakala@gmail.com |
b68987bce2f40abf5a5b3be0d046f49f02354bc8 | 650f9e246de38d0ceaee8726f27801f3337e24ce | /string-trainer/simple/csimple.py | 7d3e49c4a22d4dd82a8951120a8f4e6961a58054 | [
"MIT"
] | permissive | paulscottrobson/old-trainer-archive | 57b6fbb5886e5fe526c37f40b7fb9c179176bce7 | b3659d3f36b7443594202e0ae9439e80e493a22c | refs/heads/master | 2021-01-20T02:46:44.751050 | 2017-04-26T07:26:34 | 2017-04-26T07:26:34 | 89,451,106 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,861 | py | # *****************************************************************************************
#
# Simple compiler for TAB1 format
#
# *****************************************************************************************
import re,sys
# *****************************************************************************************
# Compiler / Processor Exception
# *****************************************************************************************
class CompilerException(Exception):
def __init__(self,message):
self.message = message
Exception.__init__(self)
# *****************************************************************************************
# Strum class
# *****************************************************************************************
class Strum:
def __init__(self,strumDef,qbTime,voices,label = ""):
self.strum = strumDef
self.qbTime = qbTime
self.label = label
self.preRender = self.convertToRender(strumDef,voices)
def getStrum(self):
return self.strum
def getQuarterBeatTime(self):
return self.qbTime
def getLabel(self):
return self.label
def toString(self):
s = self.strum+"@"+str(self.time)
if self.label != "":
s = s + "("+self.label+")"
return s
def convertToRender(self,strum,voices):
strum = strum.upper().strip()
r = []
while strum != "":
if strum[0] == 'X':
r.append(-1)
strum = strum[1:]
elif strum[0] in Strum.FRETS:
diatonic = Strum.FRETS.index(strum[0])
r.append(Strum.TOCHROMATIC[diatonic % 7]+int(diatonic / 7) * 12)
strum = strum[1:]
if (strum+" ")[0] == '+':
r[-1] += 1
strum = strum[1:]
else:
raise CompilerException("Bad strum "+strum)
# first strum given is the treble so make it the last.
r.reverse()
# right pad
while len(r) < voices:
r.insert(0,-1)
return "".join([chr(x+97) if x >= 0 else "-" for x in r])
def render(self):
return self.preRender
Strum.TOCHROMATIC = [
0, 2, 4, 5, 7, 9, 10
# D E F# G A B C
]
Strum.FRETS = "0123456789TLWHF"
Strum.QBOFFSETS = { "O":8, "o":8, "-":-2, "=":-3, ".":2 }
# *****************************************************************************************
# Bar class
# *****************************************************************************************
class Bar:
def __init__(self,barNumber,beats,voices):
self.barNumber = barNumber
self.beats = beats
self.strums = []
self.voices = voices
self.qbPosition = 0
def add(self,strumDef,label = ""):
self.strums.append(Strum(strumDef,self.qbPosition,self.voices,label))
self.qbPosition += 4
return self
def toString(self):
s = "#{0} B:{1} V:{2} C:{3} {{".format(self.barNumber,self.beats,self.voices,len(self.strums))
s = s + " ".join([x.toString() for x in self.strums]) + "}"
return s
def isOffset(self,c):
return c in Strum.QBOFFSETS
def offset(self,c):
if not self.isOffset(c):
raise CompilerException("Unknown offset "+c)
self.qbPosition += Strum.QBOFFSETS[c]
def render(self):
r = ""
qbPosition = 0
for strum in self.strums:
qbElapsed = strum.getQuarterBeatTime() - qbPosition
while qbElapsed > 0:
amt = min(8,qbElapsed)
r = r + str(amt)
qbElapsed = qbElapsed - amt
r = r + strum.render()
qbPosition = strum.getQuarterBeatTime()
return r
# *****************************************************************************************
# Song Class
# *****************************************************************************************
class Song:
def __init__(self,sourceFile):
self.reset()
self.loadTab1(sourceFile)
self.compileBody()
if self.get("title") == "":
raise CompilerException("No title provided")
def reset(self):
self.bars = []
self.keys = { "title":"","author":"","beats":"4","tempo":"100", \
"version":"1", "tuning":"d3,a4,d4", "type":"dulcimer" }
def get(self,key):
return self.keys[key.strip().lower()]
def loadTab1(self,sourceFile):
# pre process file - tabs, spaces, comments
source = open(sourceFile).readlines()
source = [x if x.find("//") < 0 else x[:x.find("//")] for x in source]
source = [x.replace("\t"," ").strip() for x in source]
# key updates.
for assign in [x for x in source if x.find(":=") >= 0]:
assign = [x.strip() for x in assign.split(":=")]
if assign[0] == '"' and assign[-1] == '"':
assign = assign[1:-1]
self.keys[assign[0].lower()] = assign[1]
source = [x for x in source if x.find(":=") < 0]
self.source = source
def compileBody(self):
for line in range(0,len(self.source)):
if self.source[line] != "":
for barPart in [x.strip() for x in self.source[line].split("|") if x.strip() != ""]:
newBar = Bar(len(self.bars),int(self.get("beats")),3)
self.bars.append(newBar)
try:
self.compileTab1(newBar,barPart.upper())
except CompilerException as cEx:
newMsg = cEx.message+" @ "+str(line+1)
raise Exception(newMsg)
def compileTab1(self,bar,src):
while src != "":
m = re.match("^([X"+Strum.FRETS+"\\+]+)\\s*(.*)$",src)
if m is not None:
strum = m.group(1)
bar.add(strum)
src = m.group(2)
elif src[0] in Strum.QBOFFSETS:
bar.offset(src[0])
src = src[1:].strip()
else:
raise CompilerException("Unknown command "+src)
def exportToJSON(self,handle):
handle.write("{ \n")
keys = [x for x in self.keys.keys()]
keys.sort()
for k in keys:
handle.write(' {0:14}:"{1}",\n'.format('"'+k+'"',self.keys[k]))
handle.write(' "bars": [\n')
for n in range(0,len(self.bars)):
r = self.bars[n].render()
handle.write('{0:14}"{1}"{2}\n'.format("",r,"," if n < len(self.bars)-1 else ""))
handle.write("\n ]\n")
handle.write("} \n")
s = Song("twinkle.tab1")
s.exportToJSON(sys.stdout)
s.exportToJSON(open("../app/music.json","w"))
| [
"paul@robsons.org.uk"
] | paul@robsons.org.uk |
8fc817688db6b26a0b9a26e87bf9538c291e886e | 0d1eb0e64ac89839298caa8f8f496c66abeb2367 | /browser.py | 65405345b2f45f9ec3d16ea26db8fce13f46f123 | [] | no_license | sho86741/zaim-viz | 637285f7d4dc31647df6f08b4b842bc36c8f19c2 | 1be94f41438fdba9558e7a0250be10721faf618f | refs/heads/master | 2022-07-05T01:35:57.931164 | 2020-05-23T14:55:36 | 2020-05-23T14:55:36 | 265,807,394 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 970 | py | # coding: utf-8
from selenium import webdriver
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.common.by import By
class Browser(object):
def __init__(self, webdriver):
self.driver = webdriver
def __getattr__(self, name):
if hasattr(self.driver, name):
return getattr(self.driver, name)
raise AttributeError
def sync_send_keys(self, locator, key):
# wait for element
WebDriverWait(self, 120).until(
EC.element_to_be_clickable(locator)
)
# send keys
self.find_element(locator[0], locator[1]).send_keys(key)
# wait for update
WebDriverWait(self, 30).until(
EC.text_to_be_present_in_element_value(locator, key)
)
def wait_element(self, id):
return WebDriverWait(self, 10).until(EC.presence_of_element_located((By.ID, id)))
| [
"sho86741@protonmail.com"
] | sho86741@protonmail.com |
261e88ade9dce201fa6cf55c90a848ba3f2b34be | 2a2e1a42a8d26040258b2d9a2b8f7d3b18a62024 | /api/urls.py | 819e588744d93a7c73ef7ece0e53597fdb27e164 | [] | no_license | rashi-agrawal29/music-controller | 1567a881fcd67ea3d688b9fae0b43a01d6df813d | 1d2b947edb7aca78e1017f7265ca50ffe8eaed66 | refs/heads/main | 2023-06-24T17:49:25.524970 | 2021-07-27T11:08:08 | 2021-07-27T11:08:08 | 389,942,056 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 458 | py | from django.urls import path
from .views import GetRoom, LeaveRoom, RoomView, CreateRoomView, JoinRoom, UpdateRoom, UserInRoom
urlpatterns = [
path('room', RoomView.as_view()),
path('create-room', CreateRoomView.as_view()),
path('get-room', GetRoom.as_view()),
path('join-room', JoinRoom.as_view()),
path('user-in-room', UserInRoom.as_view()),
path('leave-room', LeaveRoom.as_view()),
path('update-room', UpdateRoom.as_view())
]
| [
"rashiagrawal299@gmail.com"
] | rashiagrawal299@gmail.com |
9620af649f65a0c0002935d9e24ea87dd7578b35 | b0cdab54c5e81681125c01801148c287605ee8d0 | /speciality/migrations/0005_auto_20181228_2150.py | ad4d5210ff776dbc55eeccf74f5266e8a064ed44 | [] | no_license | lpd76/rdavid2 | 5528746749acc51d4d0f5efd77886929798e2569 | 18aa5120fe4ba0ea44f611dd52b008db52641f17 | refs/heads/master | 2020-04-13T20:47:58.141579 | 2019-01-17T16:51:31 | 2019-01-17T16:51:31 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 637 | py | # Generated by Django 2.1.4 on 2018-12-28 21:50
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('speciality', '0004_auto_20181228_2140'),
]
operations = [
migrations.AlterModelOptions(
name='speciality',
options={'verbose_name_plural': 'specialities'},
),
migrations.AlterField(
model_name='specialitydetails',
name='speciality',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='speciality.Speciality'),
),
]
| [
"louisphilippe.david@gmail.com"
] | louisphilippe.david@gmail.com |
a03f688cd3bb6ceef3f26b749170bc2c0ac710d7 | 82770c7bc5e2f27a48b8c370b0bab2ee41f24d86 | /microblog/flask/venv/lib/python2.7/site-packages/billiard/forking.py | 57fc9795e47d83e6c656232b9ddde88438c6ec12 | [
"Apache-2.0"
] | permissive | johankaito/fufuka | 77ddb841f27f6ce8036d7b38cb51dc62e85b2679 | 32a96ecf98ce305c2206c38443e58fdec88c788d | refs/heads/master | 2022-07-20T00:51:55.922063 | 2015-08-21T20:56:48 | 2015-08-21T20:56:48 | 39,845,849 | 2 | 0 | Apache-2.0 | 2022-06-29T23:30:11 | 2015-07-28T16:39:54 | Python | UTF-8 | Python | false | false | 17,515 | py | #
# Module for starting a process object using os.fork() or CreateProcess()
#
# multiprocessing/forking.py
#
# Copyright (c) 2006-2008, R Oudkerk
# Licensed to PSF under a Contributor Agreement.
#
from __future__ import absolute_import
import os
import sys
import signal
import warnings
from pickle import load, HIGHEST_PROTOCOL
from billiard import util
from billiard import process
from billiard.five import int_types
from .reduction import dump
from .compat import _winapi as win32
__all__ = ['Popen', 'assert_spawning', 'exit',
'duplicate', 'close']
try:
WindowsError = WindowsError # noqa
except NameError:
class WindowsError(Exception): # noqa
pass
W_OLD_DJANGO_LAYOUT = """\
Will add directory %r to path! This is necessary to accommodate \
pre-Django 1.4 layouts using setup_environ.
You can skip this warning by adding a DJANGO_SETTINGS_MODULE=settings \
environment variable.
"""
#
# Choose whether to do a fork or spawn (fork+exec) on Unix.
# This affects how some shared resources should be created.
#
_forking_is_enabled = sys.platform != 'win32'
#
# Check that the current thread is spawning a child process
#
def assert_spawning(self):
if not Popen.thread_is_spawning():
raise RuntimeError(
'%s objects should only be shared between processes'
' through inheritance' % type(self).__name__
)
#
# Unix
#
if sys.platform != 'win32':
try:
import thread
except ImportError:
import _thread as thread # noqa
import select
WINEXE = False
WINSERVICE = False
exit = os._exit
duplicate = os.dup
close = os.close
_select = util._eintr_retry(select.select)
#
# We define a Popen class similar to the one from subprocess, but
# whose constructor takes a process object as its argument.
#
class Popen(object):
_tls = thread._local()
def __init__(self, process_obj):
# register reducers
from billiard import connection # noqa
_Django_old_layout_hack__save()
sys.stdout.flush()
sys.stderr.flush()
self.returncode = None
r, w = os.pipe()
self.sentinel = r
if _forking_is_enabled:
self.pid = os.fork()
if self.pid == 0:
os.close(r)
if 'random' in sys.modules:
import random
random.seed()
code = process_obj._bootstrap()
os._exit(code)
else:
from_parent_fd, to_child_fd = os.pipe()
cmd = get_command_line() + [str(from_parent_fd)]
self.pid = os.fork()
if self.pid == 0:
os.close(r)
os.close(to_child_fd)
os.execv(sys.executable, cmd)
# send information to child
prep_data = get_preparation_data(process_obj._name)
os.close(from_parent_fd)
to_child = os.fdopen(to_child_fd, 'wb')
Popen._tls.process_handle = self.pid
try:
dump(prep_data, to_child, HIGHEST_PROTOCOL)
dump(process_obj, to_child, HIGHEST_PROTOCOL)
finally:
del(Popen._tls.process_handle)
to_child.close()
# `w` will be closed when the child exits, at which point `r`
# will become ready for reading (using e.g. select()).
os.close(w)
util.Finalize(self, os.close, (r,))
def poll(self, flag=os.WNOHANG):
if self.returncode is None:
try:
pid, sts = os.waitpid(self.pid, flag)
except os.error:
# Child process not yet created. See #1731717
# e.errno == errno.ECHILD == 10
return None
if pid == self.pid:
if os.WIFSIGNALED(sts):
self.returncode = -os.WTERMSIG(sts)
else:
assert os.WIFEXITED(sts)
self.returncode = os.WEXITSTATUS(sts)
return self.returncode
def wait(self, timeout=None):
if self.returncode is None:
if timeout is not None:
r = _select([self.sentinel], [], [], timeout)[0]
if not r:
return None
# This shouldn't block if select() returned successfully.
return self.poll(os.WNOHANG if timeout == 0.0 else 0)
return self.returncode
def terminate(self):
if self.returncode is None:
try:
os.kill(self.pid, signal.SIGTERM)
except OSError:
if self.wait(timeout=0.1) is None:
raise
@staticmethod
def thread_is_spawning():
if _forking_is_enabled:
return False
else:
return getattr(Popen._tls, 'process_handle', None) is not None
@staticmethod
def duplicate_for_child(handle):
return handle
#
# Windows
#
else:
try:
import thread
except ImportError:
import _thread as thread # noqa
import msvcrt
try:
import _subprocess
except ImportError:
import _winapi as _subprocess # noqa
#
#
#
TERMINATE = 0x10000
WINEXE = (sys.platform == 'win32' and getattr(sys, 'frozen', False))
WINSERVICE = sys.executable.lower().endswith("pythonservice.exe")
exit = win32.ExitProcess
close = win32.CloseHandle
#
#
#
def duplicate(handle, target_process=None, inheritable=False):
if target_process is None:
target_process = _subprocess.GetCurrentProcess()
h = _subprocess.DuplicateHandle(
_subprocess.GetCurrentProcess(), handle, target_process,
0, inheritable, _subprocess.DUPLICATE_SAME_ACCESS
)
if sys.version_info[0] < 3 or (
sys.version_info[0] == 3 and sys.version_info[1] < 3):
h = h.Detach()
return h
#
# We define a Popen class similar to the one from subprocess, but
# whose constructor takes a process object as its argument.
#
class Popen(object):
'''
Start a subprocess to run the code of a process object
'''
_tls = thread._local()
def __init__(self, process_obj):
_Django_old_layout_hack__save()
# create pipe for communication with child
rfd, wfd = os.pipe()
# get handle for read end of the pipe and make it inheritable
rhandle = duplicate(msvcrt.get_osfhandle(rfd), inheritable=True)
os.close(rfd)
# start process
cmd = get_command_line() + [rhandle]
cmd = ' '.join('"%s"' % x for x in cmd)
hp, ht, pid, tid = _subprocess.CreateProcess(
_python_exe, cmd, None, None, 1, 0, None, None, None
)
close(ht) if isinstance(ht, int_types) else ht.Close()
(close(rhandle) if isinstance(rhandle, int_types)
else rhandle.Close())
# set attributes of self
self.pid = pid
self.returncode = None
self._handle = hp
self.sentinel = int(hp)
# send information to child
prep_data = get_preparation_data(process_obj._name)
to_child = os.fdopen(wfd, 'wb')
Popen._tls.process_handle = int(hp)
try:
dump(prep_data, to_child, HIGHEST_PROTOCOL)
dump(process_obj, to_child, HIGHEST_PROTOCOL)
finally:
del Popen._tls.process_handle
to_child.close()
@staticmethod
def thread_is_spawning():
return getattr(Popen._tls, 'process_handle', None) is not None
@staticmethod
def duplicate_for_child(handle):
return duplicate(handle, Popen._tls.process_handle)
def wait(self, timeout=None):
if self.returncode is None:
if timeout is None:
msecs = _subprocess.INFINITE
else:
msecs = max(0, int(timeout * 1000 + 0.5))
res = _subprocess.WaitForSingleObject(int(self._handle), msecs)
if res == _subprocess.WAIT_OBJECT_0:
code = _subprocess.GetExitCodeProcess(self._handle)
if code == TERMINATE:
code = -signal.SIGTERM
self.returncode = code
return self.returncode
def poll(self):
return self.wait(timeout=0)
def terminate(self):
if self.returncode is None:
try:
_subprocess.TerminateProcess(int(self._handle), TERMINATE)
except WindowsError:
if self.wait(timeout=0.1) is None:
raise
#
#
#
if WINSERVICE:
_python_exe = os.path.join(sys.exec_prefix, 'python.exe')
else:
_python_exe = sys.executable
def set_executable(exe):
global _python_exe
_python_exe = exe
def is_forking(argv):
'''
Return whether commandline indicates we are forking
'''
if len(argv) >= 2 and argv[1] == '--billiard-fork':
assert len(argv) == 3
os.environ["FORKED_BY_MULTIPROCESSING"] = "1"
return True
else:
return False
def freeze_support():
'''
Run code for process object if this in not the main process
'''
if is_forking(sys.argv):
main()
sys.exit()
def get_command_line():
'''
Returns prefix of command line used for spawning a child process
'''
if process.current_process()._identity == () and is_forking(sys.argv):
raise RuntimeError('''
Attempt to start a new process before the current process
has finished its bootstrapping phase.
This probably means that have forgotten to use the proper
idiom in the main module:
if __name__ == '__main__':
freeze_support()
...
The "freeze_support()" line can be omitted if the program
is not going to be frozen to produce a Windows executable.''')
if getattr(sys, 'frozen', False):
return [sys.executable, '--billiard-fork']
else:
prog = 'from billiard.forking import main; main()'
return [_python_exe, '-c', prog, '--billiard-fork']
def _Django_old_layout_hack__save():
if 'DJANGO_PROJECT_DIR' not in os.environ:
try:
settings_name = os.environ['DJANGO_SETTINGS_MODULE']
except KeyError:
return # not using Django.
conf_settings = sys.modules.get('django.conf.settings')
configured = conf_settings and conf_settings.configured
try:
project_name, _ = settings_name.split('.', 1)
except ValueError:
return # not modified by setup_environ
project = __import__(project_name)
try:
project_dir = os.path.normpath(_module_parent_dir(project))
except AttributeError:
return # dynamically generated module (no __file__)
if configured:
warnings.warn(UserWarning(
W_OLD_DJANGO_LAYOUT % os.path.realpath(project_dir)
))
os.environ['DJANGO_PROJECT_DIR'] = project_dir
def _Django_old_layout_hack__load():
try:
sys.path.append(os.environ['DJANGO_PROJECT_DIR'])
except KeyError:
pass
def _module_parent_dir(mod):
dir, filename = os.path.split(_module_dir(mod))
if dir == os.curdir or not dir:
dir = os.getcwd()
return dir
def _module_dir(mod):
if '__init__.py' in mod.__file__:
return os.path.dirname(mod.__file__)
return mod.__file__
def main():
'''
Run code specifed by data received over pipe
'''
global _forking_is_enabled
_Django_old_layout_hack__load()
assert is_forking(sys.argv)
_forking_is_enabled = False
handle = int(sys.argv[-1])
if sys.platform == 'win32':
fd = msvcrt.open_osfhandle(handle, os.O_RDONLY)
else:
fd = handle
from_parent = os.fdopen(fd, 'rb')
process.current_process()._inheriting = True
preparation_data = load(from_parent)
prepare(preparation_data)
# Huge hack to make logging before Process.run work.
try:
os.environ["MP_MAIN_FILE"] = sys.modules["__main__"].__file__
except KeyError:
pass
except AttributeError:
pass
loglevel = os.environ.get("_MP_FORK_LOGLEVEL_")
logfile = os.environ.get("_MP_FORK_LOGFILE_") or None
format = os.environ.get("_MP_FORK_LOGFORMAT_")
if loglevel:
from billiard import util
import logging
logger = util.get_logger()
logger.setLevel(int(loglevel))
if not logger.handlers:
logger._rudimentary_setup = True
logfile = logfile or sys.__stderr__
if hasattr(logfile, "write"):
handler = logging.StreamHandler(logfile)
else:
handler = logging.FileHandler(logfile)
formatter = logging.Formatter(
format or util.DEFAULT_LOGGING_FORMAT,
)
handler.setFormatter(formatter)
logger.addHandler(handler)
self = load(from_parent)
process.current_process()._inheriting = False
from_parent.close()
exitcode = self._bootstrap()
exit(exitcode)
def get_preparation_data(name):
'''
Return info about parent needed by child to unpickle process object
'''
from billiard.util import _logger, _log_to_stderr
d = dict(
name=name,
sys_path=sys.path,
sys_argv=sys.argv,
log_to_stderr=_log_to_stderr,
orig_dir=process.ORIGINAL_DIR,
authkey=process.current_process().authkey,
)
if _logger is not None:
d['log_level'] = _logger.getEffectiveLevel()
if not WINEXE and not WINSERVICE:
main_path = getattr(sys.modules['__main__'], '__file__', None)
if not main_path and sys.argv[0] not in ('', '-c'):
main_path = sys.argv[0]
if main_path is not None:
if (not os.path.isabs(main_path) and
process.ORIGINAL_DIR is not None):
main_path = os.path.join(process.ORIGINAL_DIR, main_path)
d['main_path'] = os.path.normpath(main_path)
return d
#
# Prepare current process
#
old_main_modules = []
def prepare(data):
'''
Try to get current process ready to unpickle process object
'''
old_main_modules.append(sys.modules['__main__'])
if 'name' in data:
process.current_process().name = data['name']
if 'authkey' in data:
process.current_process()._authkey = data['authkey']
if 'log_to_stderr' in data and data['log_to_stderr']:
util.log_to_stderr()
if 'log_level' in data:
util.get_logger().setLevel(data['log_level'])
if 'sys_path' in data:
sys.path = data['sys_path']
if 'sys_argv' in data:
sys.argv = data['sys_argv']
if 'dir' in data:
os.chdir(data['dir'])
if 'orig_dir' in data:
process.ORIGINAL_DIR = data['orig_dir']
if 'main_path' in data:
main_path = data['main_path']
main_name = os.path.splitext(os.path.basename(main_path))[0]
if main_name == '__init__':
main_name = os.path.basename(os.path.dirname(main_path))
if main_name == '__main__':
main_module = sys.modules['__main__']
main_module.__file__ = main_path
elif main_name != 'ipython':
# Main modules not actually called __main__.py may
# contain additional code that should still be executed
import imp
if main_path is None:
dirs = None
elif os.path.basename(main_path).startswith('__init__.py'):
dirs = [os.path.dirname(os.path.dirname(main_path))]
else:
dirs = [os.path.dirname(main_path)]
assert main_name not in sys.modules, main_name
file, path_name, etc = imp.find_module(main_name, dirs)
try:
# We would like to do "imp.load_module('__main__', ...)"
# here. However, that would cause 'if __name__ ==
# "__main__"' clauses to be executed.
main_module = imp.load_module(
'__parents_main__', file, path_name, etc
)
finally:
if file:
file.close()
sys.modules['__main__'] = main_module
main_module.__name__ = '__main__'
# Try to make the potentially picklable objects in
# sys.modules['__main__'] realize they are in the main
# module -- somewhat ugly.
for obj in list(main_module.__dict__.values()):
try:
if obj.__module__ == '__parents_main__':
obj.__module__ = '__main__'
except Exception:
pass
| [
"john.g.keto@gmail.com"
] | john.g.keto@gmail.com |
cee01a1f512e64d11d177b39003a6d66c4c62798 | f375899369ba86aed1da89101c31817168ffec40 | /cinema/urls.py | f73d16e3686a88eb9e7b40b41d324fb2021b3100 | [] | no_license | sheremilbekov/cinema | f596a7d1e41f03161a3ddf0c3594f39619c812df | d8baac5c7e25a90340a35e1e0b0cce093014f965 | refs/heads/master | 2023-03-30T10:19:20.654540 | 2021-04-07T12:10:54 | 2021-04-07T12:10:54 | 354,850,726 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 941 | py | """cinema URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/3.1/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: path('', views.home, name='home')
Class-based views
1. Add an import: from other_app.views import Home
2. Add a URL to urlpatterns: path('', Home.as_view(), name='home')
Including another URLconf
1. Import the include() function: from django.urls import include, path
2. Add a URL to urlpatterns: path('blog/', include('blog.urls'))
"""
from django.conf import settings
from django.conf.urls.static import static
from django.contrib import admin
from django.urls import path, include
urlpatterns = [
path('admin/', admin.site.urls),
path('cooking/', include('main.urls')),
] + static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT)
| [
"you@example.com"
] | you@example.com |
16effac639ce13ca5ccf22f2cfad0658eac06638 | 547ba955855ff623a8ef6e80fcfaddebadf34bed | /Chapter08/B06246_08_14-slope.py | a5a8f6c01c4af2755f280d506db81016afd04122 | [] | no_license | CodedQuen/QGIS-Python-Programming-Cookbook | 94a36d265d0336d5bb36ac02d637ba17ee765b04 | f84e0159f7c8ec81a29573a7fd2e03b046efce33 | refs/heads/master | 2022-05-28T05:04:35.053121 | 2020-05-05T09:44:50 | 2020-05-05T09:44:50 | 261,414,871 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,009 | py | # Computing Road Slope using Elevation Data
# https://github.com/GeospatialPython/Learn/raw/master/road.zip
from PyQt4.QtCore import *
from PyQt4.QtGui import *
import processing
dem = "/qgis_data/road/dem.asc"
road = "/qgis_data/road/road.shp"
slope = "/qgis_data/road/slope.tif"
segRoad = "/qgis_data/road/segRoad.shp"
steepness = "/qgis_data/road/steepness.shp"
hillshade = "/qgis_data/road/hillshade.tif"
demLyr = QgsRasterLayer(dem, "DEM")
roadLyr = QgsVectorLayer(road, "Road", "ogr")
ext = demLyr.extent()
xmin = ext.xMinimum()
ymin = ext.yMinimum()
xmax = ext.xMaximum()
ymax = ext.yMaximum()
demBox = "{},{},{},{}".format(xmin,xmax,ymin,ymax)
processing.runalg("grass7:r.slope",dem,0,False,1,0,demBox,0,slope)
ext = roadLyr.extent()
xmin = ext.xMinimum()
ymin = ext.yMinimum()
xmax = ext.xMaximum()
ymax = ext.yMaximum()
roadBox = "{},{},{},{}".format(xmin,xmax,ymin,ymax)
processing.runalg("grass7:v.split.length",road,500,roadBox,-1,0.0001,0,segRoad)
slopeLyr = QgsRasterLayer(slope, "Slope")
segRoadLyr = QgsVectorLayer(segRoad, "Segmented Road", "ogr")
QgsMapLayerRegistry.instance().addMapLayers([segRoadLyr,slopeLyr], False)
processing.runalg("saga:addgridvaluestoshapes",segRoad,slope,0,steepness)
steepLyr = QgsVectorLayer(steepness, "Road Gradient", "ogr")
roadGrade = (
("Rolling Hill", 0.0, 20.0, "green"),
("Steep", 20.0, 40.0, "yellow"),
("Very Steep", 40.0, 90.0, "red"))
ranges = []
for label, lower, upper, color in roadGrade:
sym = QgsSymbolV2.defaultSymbol(steepLyr.geometryType())
sym.setColor(QColor(color))
sym.setWidth(3.0)
rng = QgsRendererRangeV2(lower, upper, sym, label)
ranges.append(rng)
field = "slopetif"
renderer = QgsGraduatedSymbolRendererV2(field, ranges)
steepLyr.setRendererV2(renderer)
processing.runalg("saga:analyticalhillshading",dem,0,158,45,4,hillshade)
hs = QgsRasterLayer(hillshade, "Terrain")
QgsMapLayerRegistry.instance().addMapLayers([steepLyr, hs]) | [
"noreply@github.com"
] | noreply@github.com |
79ea992e09ac27c13270a55465339b7a6ed9af03 | 40644ab8302eabcfe29fc665191a0e7373d2d36a | /final 0.0/modules/mouvements.py | aa4304e8d0f2f93f7a15047205ba3459e2c45f18 | [] | no_license | katyushacccp/ISN_projet_final | 3ee940aa725bc68e9a9506deac48960aea43d828 | 41278c58431b69238b2c955ee1088c36d1db203e | refs/heads/master | 2020-12-24T19:04:33.560212 | 2016-05-30T20:25:20 | 2016-05-30T20:25:20 | 55,981,116 | 0 | 1 | null | 2016-05-30T20:25:20 | 2016-04-11T14:50:25 | Python | UTF-8 | Python | false | false | 11,399 | py | from random import *
from modules.affichage import *
from modules.recherche import *
from time import *
def start():
"""Cette fonction sert à initialiser la variable globale 'compteur' qui va par la suite gérer le temps"""
wFile("compteur","cub",0)
def melangeur(cube,can,nombre):
"""Cette fonction sert à mélanger de manière aléatoire le cube un nombre n de fois, n étant défini par le paramètre 'nombre'"""
for i in range(nombre):
can.after(i*rFile("timeur","cub"),lambda:rotation(cube,can,randint(0,5),choice(["droite","gauche"])))
def rotative(cube,can,face,faceSup,norme):
"""La fonction 'rotative' normalise les différentes fonctions qui gère les mouvements dans le cube.
La fonction a également la notion du temps, pour cela elle s'aide de la variable globale 'compteur'"""
compteur=rFile("compteur","cub")
wFile("compteur","cub",compteur+1)
if norme.upper()=="U":
can.after(rFile("compteur","cub")*rFile("timeur","cub"),lambda:rotationHaut(cube,can,face,faceSup,"gauche"))
elif norme.upper()=="U'":
can.after(rFile("compteur","cub")*rFile("timeur","cub"),lambda:rotationHaut(cube,can,face,faceSup,"droite"))
elif norme.upper()=="L":
can.after(rFile("compteur","cub")*rFile("timeur","cub"),lambda:rotationGauche(cube,can,face,faceSup,"bas"))
elif norme.upper()=="L'":
can.after(rFile("compteur","cub")*rFile("timeur","cub"),lambda:rotationGauche(cube,can,face,faceSup,"haut"))
elif norme.upper()=="F":
can.after(rFile("compteur","cub")*rFile("timeur","cub"),lambda:rotation(cube,can,face,"droite"))
elif norme.upper()=="F'":
can.after(rFile("compteur","cub")*rFile("timeur","cub"),lambda:rotation(cube,can,face,"gauche"))
elif norme.upper()=="R":
can.after(rFile("compteur","cub")*rFile("timeur","cub"),lambda:rotationDroite(cube,can,face,faceSup,"haut"))
elif norme.upper()=="R'":
can.after(rFile("compteur","cub")*rFile("timeur","cub"),lambda:rotationDroite(cube,can,face,faceSup,"bas"))
elif norme.upper()=="D":
can.after(rFile("compteur","cub")*rFile("timeur","cub"),lambda:rotationBas(cube,can,face,faceSup,"droite"))
elif norme.upper()=="D'":
can.after(rFile("compteur","cub")*rFile("timeur","cub"),lambda:rotationBas(cube,can,face,faceSup,"gauche"))
elif norme.upper()=="M":
can.after(rFile("compteur","cub")*rFile("timeur","cub"),lambda:axe(cube,can,face,faceSup,"bas"))
elif norme.upper()=="M'":
can.after(rFile("compteur","cub")*rFile("timeur","cub"),lambda:axe(cube,can,face,faceSup,"haut"))
elif norme.upper()=="E":
can.after(rFile("compteur","cub")*rFile("timeur","cub"),lambda:axe(cube,can,face,faceSup,"droite"))
elif norme.upper()=="E'":
can.after(rFile("compteur","cub")*rFile("timeur","cub"),lambda:axe(cube,can,face,faceSup,"gauche"))
def rotativeUser(cube,can,face,faceSup,norme):
"""La fonction 'rotaitveUser' est identique à la fonction 'rotative', la gestion du temps en moins.
Cela est donc pratique pour effectuer des mouvements instantanés"""
if norme.upper()=="U":
rotationHaut(cube,can,face,faceSup,"gauche")
elif norme.upper()=="U'":
rotationHaut(cube,can,face,faceSup,"droite")
elif norme.upper()=="L":
rotationGauche(cube,can,face,faceSup,"bas")
elif norme.upper()=="L'":
rotationGauche(cube,can,face,faceSup,"haut")
elif norme.upper()=="F":
rotation(cube,can,face,"droite")
elif norme.upper()=="F'":
rotation(cube,can,face,"gauche")
elif norme.upper()=="R":
rotationDroite(cube,can,face,faceSup,"haut")
elif norme.upper()=="R'":
rotationDroite(cube,can,face,faceSup,"bas")
elif norme.upper()=="D":
rotationBas(cube,can,face,faceSup,"droite")
elif norme.upper()=="D'":
rotationBas(cube,can,face,faceSup,"gauche")
elif norme.upper()=="M":
axe(cube,can,face,faceSup,"bas")
elif norme.upper()=="M'":
axe(cube,can,face,faceSup,"haut")
elif norme.upper()=="E":
axe(cube,can,face,faceSup,"droite")
elif norme.upper()=="E'":
axe(cube,can,face,faceSup,"gauche")
def rotation(cube,can,face,sens):
"""Fonction gérant la rotation d'une face.
Correspond au mouvement F si sens = droite / F' si sens = gauche"""
if sens=="droite":
cube[face][0], cube[face][1], cube[face][2], cube[face][5], cube[face][8], cube[face][7], cube[face][6], cube[face][3] \
= cube[face][6], cube[face][3], cube[face][0], cube[face][1], cube[face][2], cube[face][5], cube[face][8], cube[face][7]
pos=posRel(face)
cube[pos[0][0]][pos[0][1]], cube[pos[0][0]][pos[0][2]], cube[pos[0][0]][pos[0][3]], \
cube[pos[1][0]][pos[1][1]], cube[pos[1][0]][pos[1][2]], cube[pos[1][0]][pos[1][3]], \
cube[pos[2][0]][pos[2][3]], cube[pos[2][0]][pos[2][2]], cube[pos[2][0]][pos[2][1]], \
cube[pos[3][0]][pos[3][3]], cube[pos[3][0]][pos[3][2]], cube[pos[3][0]][pos[3][1]] \
= cube[pos[3][0]][pos[3][3]], cube[pos[3][0]][pos[3][2]], cube[pos[3][0]][pos[3][1]], \
cube[pos[0][0]][pos[0][1]], cube[pos[0][0]][pos[0][2]], cube[pos[0][0]][pos[0][3]], \
cube[pos[1][0]][pos[1][1]], cube[pos[1][0]][pos[1][2]], cube[pos[1][0]][pos[1][3]], \
cube[pos[2][0]][pos[2][3]], cube[pos[2][0]][pos[2][2]], cube[pos[2][0]][pos[2][1]]
elif sens=="gauche":
cube[face][0], cube[face][1], cube[face][2], cube[face][5], cube[face][8], cube[face][7], cube[face][6], cube[face][3] \
= cube[face][2],cube[face][5],cube[face][8],cube[face][7],cube[face][6],cube[face][3],cube[face][0],cube[face][1]
pos=posRel(face)
cube[pos[0][0]][pos[0][1]], cube[pos[0][0]][pos[0][2]], cube[pos[0][0]][pos[0][3]], \
cube[pos[1][0]][pos[1][1]], cube[pos[1][0]][pos[1][2]], cube[pos[1][0]][pos[1][3]], \
cube[pos[2][0]][pos[2][3]], cube[pos[2][0]][pos[2][2]], cube[pos[2][0]][pos[2][1]], \
cube[pos[3][0]][pos[3][3]], cube[pos[3][0]][pos[3][2]], cube[pos[3][0]][pos[3][1]] \
= cube[pos[1][0]][pos[1][1]], cube[pos[1][0]][pos[1][2]], cube[pos[1][0]][pos[1][3]], \
cube[pos[2][0]][pos[2][3]], cube[pos[2][0]][pos[2][2]], cube[pos[2][0]][pos[2][1]], \
cube[pos[3][0]][pos[3][3]], cube[pos[3][0]][pos[3][2]], cube[pos[3][0]][pos[3][1]], \
cube[pos[0][0]][pos[0][1]], cube[pos[0][0]][pos[0][2]], cube[pos[0][0]][pos[0][3]]
actualise(cube,can)
def rotationHaut(cube,can,face,faceSup,sens):
"""Fonction se basant sur la fonction 'rotation' afin de permettre un autre mouvement.
Correspond au mouvement U si sens = gauche / U' si sens = droite"""
if sens=="gauche":
rotation(cube,can,faceSup,"droite")
elif sens=="droite":
rotation(cube,can,faceSup,"gauche")
def rotationBas(cube,can,face,faceSup,sens):
"""Fonction se basant sur la fonction 'rotation' afin de permettre un autre mouvement.
Correspond au mouvement D si sens = droite / D' si sens = gauche"""
faceBas=posRel(faceSup)[4]
rotation(cube,can,faceBas,sens)
def rotationDroite(cube,can,face,faceSup,sens):
"""Fonction se basant sur la fonction 'rotation' afin de permettre un autre mouvement.
Correspond au mouvement R si sens = haut / R' si sens = bas"""
pos=posRel(face)
for i in range(4):
if pos[i][0]==faceSup:
supChiffre=i
faceDroite=posRel(face)[boussole(supChiffre+1)][0]
if sens=="haut":
rotation(cube,can,faceDroite,"droite")
elif sens=="bas":
rotation(cube,can,faceDroite,"gauche")
def rotationGauche(cube,can,face,faceSup,sens):
"""Fonction se basant sur la fonction 'rotation' afin de permettre un autre mouvement.
Correspond au mouvement L si sens = bas / L' si sens = haut"""
pos=posRel(face)
for i in range(4):
if pos[i][0]==faceSup:
supChiffre=i
faceDroite=posRel(face)[boussole(supChiffre-1)][0]
if sens=="haut":
rotation(cube,can,faceDroite,"gauche")
elif sens=="bas":
rotation(cube,can,faceDroite,"droite")
def axe(cube,can,face,faceSup,sens):
sensGlobal=[]
pos=posRel(face)
for i in range(4):
if pos[i][0]==faceSup:
sensChiffre=i
sens=int(deReconnaissanceDirection(sens))
sensGlobal=reconnaissanceDirection(sensChiffre+sens)
if sensGlobal=="haut":
cube[face][1], cube[face][4], cube[face][7], \
cube[posRel(face)[2][0]][posRel(face)[2][2]], cube[posRel(face)[2][0]][4], cube[posRel(face)[2][0]][arreteOppose(posRel(face)[2][2])], \
cube[posRel(face)[4]][7], cube[posRel(face)[4]][4], cube[posRel(face)[4]][1], \
cube[posRel(face)[0][0]][arreteOppose(posRel(face)[0][2])], cube[posRel(face)[0][0]][4], cube[posRel(face)[0][0]][posRel(face)[0][2]] \
= cube[posRel(face)[2][0]][posRel(face)[2][2]], cube[posRel(face)[2][0]][4], cube[posRel(face)[2][0]][arreteOppose(posRel(face)[2][2])], \
cube[posRel(face)[4]][7], cube[posRel(face)[4]][4], cube[posRel(face)[4]][1], \
cube[posRel(face)[0][0]][arreteOppose(posRel(face)[0][2])], cube[posRel(face)[0][0]][4], cube[posRel(face)[0][0]][posRel(face)[0][2]], \
cube[face][1], cube[face][4], cube[face][7]
elif sensGlobal=="droite":
cube[face][3], cube[face][4], cube[face][5], \
cube[posRel(face)[1][0]][posRel(face)[1][2]], cube[posRel(face)[1][0]][4], cube[posRel(face)[1][0]][arreteOppose(posRel(face)[1][2])], \
cube[posRel(face)[4]][3], cube[posRel(face)[4]][4], cube[posRel(face)[4]][5], \
cube[posRel(face)[3][0]][arreteOppose(posRel(face)[3][2])], cube[posRel(face)[3][0]][4], cube[posRel(face)[3][0]][posRel(face)[3][2]] \
= cube[posRel(face)[3][0]][arreteOppose(posRel(face)[3][2])], cube[posRel(face)[3][0]][4], cube[posRel(face)[3][0]][posRel(face)[3][2]], \
cube[face][3], cube[face][4], cube[face][5], \
cube[posRel(face)[1][0]][posRel(face)[1][2]], cube[posRel(face)[1][0]][4], cube[posRel(face)[1][0]][arreteOppose(posRel(face)[1][2])], \
cube[posRel(face)[4]][3], cube[posRel(face)[4]][4], cube[posRel(face)[4]][5]
elif sensGlobal=="gauche":
cube[face][3], cube[face][4], cube[face][5], \
cube[posRel(face)[1][0]][posRel(face)[1][2]], cube[posRel(face)[1][0]][4], cube[posRel(face)[1][0]][arreteOppose(posRel(face)[1][2])], \
cube[posRel(face)[4]][3], cube[posRel(face)[4]][4], cube[posRel(face)[4]][5], \
cube[posRel(face)[3][0]][arreteOppose(posRel(face)[3][2])], cube[posRel(face)[3][0]][4], cube[posRel(face)[3][0]][posRel(face)[3][2]] \
= cube[posRel(face)[1][0]][posRel(face)[1][2]], cube[posRel(face)[1][0]][4], cube[posRel(face)[1][0]][arreteOppose(posRel(face)[1][2])], \
cube[posRel(face)[4]][3], cube[posRel(face)[4]][4], cube[posRel(face)[4]][5], \
cube[posRel(face)[3][0]][arreteOppose(posRel(face)[3][2])], cube[posRel(face)[3][0]][4], cube[posRel(face)[3][0]][posRel(face)[3][2]], \
cube[face][3], cube[face][4], cube[face][5]
elif sensGlobal=="bas":
cube[face][1], cube[face][4], cube[face][7], \
cube[posRel(face)[2][0]][posRel(face)[2][2]], cube[posRel(face)[2][0]][4], cube[posRel(face)[2][0]][arreteOppose(posRel(face)[2][2])], \
cube[posRel(face)[4]][7], cube[posRel(face)[4]][4], cube[posRel(face)[4]][1], \
cube[posRel(face)[0][0]][arreteOppose(posRel(face)[0][2])], cube[posRel(face)[0][0]][4], cube[posRel(face)[0][0]][posRel(face)[0][2]] \
= cube[posRel(face)[0][0]][arreteOppose(posRel(face)[0][2])], cube[posRel(face)[0][0]][4], cube[posRel(face)[0][0]][posRel(face)[0][2]], \
cube[face][1], cube[face][4], cube[face][7], \
cube[posRel(face)[2][0]][posRel(face)[2][2]], cube[posRel(face)[2][0]][4], cube[posRel(face)[2][0]][arreteOppose(posRel(face)[2][2])], \
cube[posRel(face)[4]][7], cube[posRel(face)[4]][4], cube[posRel(face)[4]][1]
actualise(cube,can) | [
"lou-theo.laurent@laposte.net"
] | lou-theo.laurent@laposte.net |
cee5b7b2b75e484c426ea06dd60947850dfaaf8a | 510517e2f9399a6590035e23e1db89dde2ee00f5 | /workflow/workflow.py | e04e741e44275bd44f7330ea2fc4267ba22712a6 | [] | no_license | fractaledmind/alfred_corpora | 686ddbcfd1df92928738efdea716647ab4539380 | 15e7c3b047a4958dfe0299ee6d5ddc1a32f25de6 | refs/heads/master | 2021-01-15T14:18:31.475051 | 2014-09-25T03:18:02 | 2014-09-25T03:18:02 | 24,428,371 | 3 | 0 | null | null | null | null | UTF-8 | Python | false | false | 74,281 | py | # encoding: utf-8
#
# Copyright (c) 2014 Dean Jackson <deanishe@deanishe.net>
#
# MIT Licence. See http://opensource.org/licenses/MIT
#
# Created on 2014-02-15
#
"""
The :class:`Workflow` object is the main interface to this library.
"""
from __future__ import print_function, unicode_literals
import os
import sys
import string
import re
import plistlib
import subprocess
import unicodedata
import shutil
import json
import cPickle
import pickle
import time
import logging
import logging.handlers
try:
import xml.etree.cElementTree as ET
except ImportError: # pragma: no cover
import xml.etree.ElementTree as ET
####################################################################
# Standard system icons
####################################################################
# These icons are default OS X icons. They are super-high quality, and
# will be familiar to users.
# This library uses `ICON_ERROR` when a workflow dies in flames, so
# in my own workflows, I use `ICON_WARNING` for less fatal errors
# (e.g. bad user input, no results etc.)
# The system icons are all in this directory. There are many more than
# are listed here
ICON_ROOT = '/System/Library/CoreServices/CoreTypes.bundle/Contents/Resources'
ICON_ACCOUNT = os.path.join(ICON_ROOT, 'Accounts.icns')
ICON_BURN = os.path.join(ICON_ROOT, 'BurningIcon.icns')
ICON_COLOR = os.path.join(ICON_ROOT, 'ProfileBackgroundColor.icns')
ICON_COLOUR = ICON_COLOR # Queen's English, if you please
# Shown when a workflow throws an error
ICON_ERROR = os.path.join(ICON_ROOT, 'AlertStopIcon.icns')
ICON_FAVORITE = os.path.join(ICON_ROOT, 'ToolbarFavoritesIcon.icns')
ICON_FAVOURITE = ICON_FAVORITE
ICON_GROUP = os.path.join(ICON_ROOT, 'GroupIcon.icns')
ICON_HELP = os.path.join(ICON_ROOT, 'HelpIcon.icns')
ICON_INFO = os.path.join(ICON_ROOT, 'ToolbarInfo.icns')
ICON_MUSIC = os.path.join(ICON_ROOT, 'ToolbarMusicFolderIcon.icns')
ICON_NETWORK = os.path.join(ICON_ROOT, 'GenericNetworkIcon.icns')
ICON_NOTE = os.path.join(ICON_ROOT, 'AlertNoteIcon.icns')
ICON_SETTINGS = os.path.join(ICON_ROOT, 'ToolbarAdvanced.icns')
ICON_SYNC = os.path.join(ICON_ROOT, 'Sync.icns')
ICON_TRASH = os.path.join(ICON_ROOT, 'TrashIcon.icns')
ICON_USER = os.path.join(ICON_ROOT, 'UserIcon.icns')
ICON_WARNING = os.path.join(ICON_ROOT, 'AlertCautionIcon.icns')
ICON_WEB = os.path.join(ICON_ROOT, 'BookmarkIcon.icns')
####################################################################
# non-ASCII to ASCII diacritic folding.
# Used by `fold_to_ascii` method
####################################################################
ASCII_REPLACEMENTS = {
'À': 'A',
'Á': 'A',
'Â': 'A',
'Ã': 'A',
'Ä': 'A',
'Å': 'A',
'Æ': 'AE',
'Ç': 'C',
'È': 'E',
'É': 'E',
'Ê': 'E',
'Ë': 'E',
'Ì': 'I',
'Í': 'I',
'Î': 'I',
'Ï': 'I',
'Ð': 'D',
'Ñ': 'N',
'Ò': 'O',
'Ó': 'O',
'Ô': 'O',
'Õ': 'O',
'Ö': 'O',
'Ø': 'O',
'Ù': 'U',
'Ú': 'U',
'Û': 'U',
'Ü': 'U',
'Ý': 'Y',
'Þ': 'Th',
'ß': 'ss',
'à': 'a',
'á': 'a',
'â': 'a',
'ã': 'a',
'ä': 'a',
'å': 'a',
'æ': 'ae',
'ç': 'c',
'è': 'e',
'é': 'e',
'ê': 'e',
'ë': 'e',
'ì': 'i',
'í': 'i',
'î': 'i',
'ï': 'i',
'ð': 'd',
'ñ': 'n',
'ò': 'o',
'ó': 'o',
'ô': 'o',
'õ': 'o',
'ö': 'o',
'ø': 'o',
'ù': 'u',
'ú': 'u',
'û': 'u',
'ü': 'u',
'ý': 'y',
'þ': 'th',
'ÿ': 'y',
'Ł': 'L',
'ł': 'l',
'Ń': 'N',
'ń': 'n',
'Ņ': 'N',
'ņ': 'n',
'Ň': 'N',
'ň': 'n',
'Ŋ': 'ng',
'ŋ': 'NG',
'Ō': 'O',
'ō': 'o',
'Ŏ': 'O',
'ŏ': 'o',
'Ő': 'O',
'ő': 'o',
'Œ': 'OE',
'œ': 'oe',
'Ŕ': 'R',
'ŕ': 'r',
'Ŗ': 'R',
'ŗ': 'r',
'Ř': 'R',
'ř': 'r',
'Ś': 'S',
'ś': 's',
'Ŝ': 'S',
'ŝ': 's',
'Ş': 'S',
'ş': 's',
'Š': 'S',
'š': 's',
'Ţ': 'T',
'ţ': 't',
'Ť': 'T',
'ť': 't',
'Ŧ': 'T',
'ŧ': 't',
'Ũ': 'U',
'ũ': 'u',
'Ū': 'U',
'ū': 'u',
'Ŭ': 'U',
'ŭ': 'u',
'Ů': 'U',
'ů': 'u',
'Ű': 'U',
'ű': 'u',
'Ŵ': 'W',
'ŵ': 'w',
'Ŷ': 'Y',
'ŷ': 'y',
'Ÿ': 'Y',
'Ź': 'Z',
'ź': 'z',
'Ż': 'Z',
'ż': 'z',
'Ž': 'Z',
'ž': 'z',
'ſ': 's',
'Α': 'A',
'Β': 'B',
'Γ': 'G',
'Δ': 'D',
'Ε': 'E',
'Ζ': 'Z',
'Η': 'E',
'Θ': 'Th',
'Ι': 'I',
'Κ': 'K',
'Λ': 'L',
'Μ': 'M',
'Ν': 'N',
'Ξ': 'Ks',
'Ο': 'O',
'Π': 'P',
'Ρ': 'R',
'Σ': 'S',
'Τ': 'T',
'Υ': 'U',
'Φ': 'Ph',
'Χ': 'Kh',
'Ψ': 'Ps',
'Ω': 'O',
'α': 'a',
'β': 'b',
'γ': 'g',
'δ': 'd',
'ε': 'e',
'ζ': 'z',
'η': 'e',
'θ': 'th',
'ι': 'i',
'κ': 'k',
'λ': 'l',
'μ': 'm',
'ν': 'n',
'ξ': 'x',
'ο': 'o',
'π': 'p',
'ρ': 'r',
'ς': 's',
'σ': 's',
'τ': 't',
'υ': 'u',
'φ': 'ph',
'χ': 'kh',
'ψ': 'ps',
'ω': 'o',
'А': 'A',
'Б': 'B',
'В': 'V',
'Г': 'G',
'Д': 'D',
'Е': 'E',
'Ж': 'Zh',
'З': 'Z',
'И': 'I',
'Й': 'I',
'К': 'K',
'Л': 'L',
'М': 'M',
'Н': 'N',
'О': 'O',
'П': 'P',
'Р': 'R',
'С': 'S',
'Т': 'T',
'У': 'U',
'Ф': 'F',
'Х': 'Kh',
'Ц': 'Ts',
'Ч': 'Ch',
'Ш': 'Sh',
'Щ': 'Shch',
'Ъ': "'",
'Ы': 'Y',
'Ь': "'",
'Э': 'E',
'Ю': 'Iu',
'Я': 'Ia',
'а': 'a',
'б': 'b',
'в': 'v',
'г': 'g',
'д': 'd',
'е': 'e',
'ж': 'zh',
'з': 'z',
'и': 'i',
'й': 'i',
'к': 'k',
'л': 'l',
'м': 'm',
'н': 'n',
'о': 'o',
'п': 'p',
'р': 'r',
'с': 's',
'т': 't',
'у': 'u',
'ф': 'f',
'х': 'kh',
'ц': 'ts',
'ч': 'ch',
'ш': 'sh',
'щ': 'shch',
'ъ': "'",
'ы': 'y',
'ь': "'",
'э': 'e',
'ю': 'iu',
'я': 'ia',
# 'ᴀ': '',
# 'ᴁ': '',
# 'ᴂ': '',
# 'ᴃ': '',
# 'ᴄ': '',
# 'ᴅ': '',
# 'ᴆ': '',
# 'ᴇ': '',
# 'ᴈ': '',
# 'ᴉ': '',
# 'ᴊ': '',
# 'ᴋ': '',
# 'ᴌ': '',
# 'ᴍ': '',
# 'ᴎ': '',
# 'ᴏ': '',
# 'ᴐ': '',
# 'ᴑ': '',
# 'ᴒ': '',
# 'ᴓ': '',
# 'ᴔ': '',
# 'ᴕ': '',
# 'ᴖ': '',
# 'ᴗ': '',
# 'ᴘ': '',
# 'ᴙ': '',
# 'ᴚ': '',
# 'ᴛ': '',
# 'ᴜ': '',
# 'ᴝ': '',
# 'ᴞ': '',
# 'ᴟ': '',
# 'ᴠ': '',
# 'ᴡ': '',
# 'ᴢ': '',
# 'ᴣ': '',
# 'ᴤ': '',
# 'ᴥ': '',
'ᴦ': 'G',
'ᴧ': 'L',
'ᴨ': 'P',
'ᴩ': 'R',
'ᴪ': 'PS',
'ẞ': 'Ss',
'Ỳ': 'Y',
'ỳ': 'y',
'Ỵ': 'Y',
'ỵ': 'y',
'Ỹ': 'Y',
'ỹ': 'y',
}
####################################################################
# Used by `Workflow.filter`
####################################################################
# Anchor characters in a name
#: Characters that indicate the beginning of a "word" in CamelCase
INITIALS = string.ascii_uppercase + string.digits
#: Split on non-letters, numbers
split_on_delimiters = re.compile('[^a-zA-Z0-9]').split
# Match filter flags
#: Match items that start with ``query``
MATCH_STARTSWITH = 1
#: Match items whose capital letters start with ``query``
MATCH_CAPITALS = 2
#: Match items with a component "word" that matches ``query``
MATCH_ATOM = 4
#: Match items whose initials (based on atoms) start with ``query``
MATCH_INITIALS_STARTSWITH = 8
#: Match items whose initials (based on atoms) contain ``query``
MATCH_INITIALS_CONTAIN = 16
#: Combination of :const:`MATCH_INITIALS_STARTSWITH` and
#: :const:`MATCH_INITIALS_CONTAIN`
MATCH_INITIALS = 24
#: Match items if ``query`` is a substring
MATCH_SUBSTRING = 32
#: Match items if all characters in ``query`` appear in the item in order
MATCH_ALLCHARS = 64
#: Combination of all other ``MATCH_*`` constants
MATCH_ALL = 127
####################################################################
# Used by `Workflow.check_update`
####################################################################
# Number of days to wait between checking for updates to the workflow
DEFAULT_UPDATE_FREQUENCY = 1
####################################################################
# Keychain access errors
####################################################################
class KeychainError(Exception):
"""Raised by methods :meth:`Workflow.save_password`,
:meth:`Workflow.get_password` and :meth:`Workflow.delete_password`
when ``security`` CLI app returns an unknown code.
"""
class PasswordNotFound(KeychainError):
"""Raised by method :meth:`Workflow.get_password` when ``account``
is unknown to the Keychain.
"""
class PasswordExists(KeychainError):
"""Raised when trying to overwrite an existing account password.
The API user should never receive this error: it is used internally
by the :meth:`Workflow.save_password` method.
"""
####################################################################
# Helper functions
####################################################################
def isascii(text):
"""Test if ``text`` contains only ASCII characters
:param text: text to test for ASCII-ness
:type text: ``unicode``
:returns: ``True`` if ``text`` contains only ASCII characters
:rtype: ``Boolean``
"""
try:
text.encode('ascii')
except UnicodeEncodeError:
return False
return True
####################################################################
# Implementation classes
####################################################################
class SerializerManager(object):
"""Contains registered serializers.
.. versionadded:: 1.8
A configured instance of this class is available at ``workflow.manager``.
Use :meth:`register()` to register new (or replace
existing) serializers, which you can specify by name when calling
:class:`Workflow` data storage methods.
See `serialization` and `persistent-data` for further information.
"""
def __init__(self):
self._serializers = {}
def register(self, name, serializer):
"""Register ``serializer`` object under ``name``.
Raises :class:`AttributeError` if ``serializer`` in invalid.
.. note::
``name`` will be used as the file extension of the saved files.
:param name: Name to register ``serializer`` under
:type name: ``unicode`` or ``str``
:param serializer: object with ``load()`` and ``dump()``
methods
"""
# Basic validation
getattr(serializer, 'load')
getattr(serializer, 'dump')
self._serializers[name] = serializer
def serializer(self, name):
"""Return serializer object for ``name`` or ``None`` if no such
serializer is registered
:param name: Name of serializer to return
:type name: ``unicode`` or ``str``
:returns: serializer object or ``None``
"""
return self._serializers.get(name)
def unregister(self, name):
"""Remove registered serializer with ``name``
Raises a :class:`ValueError` if there is no such registered
serializer.
:param name: Name of serializer to remove
:type name: ``unicode`` or ``str``
:returns: serializer object
"""
if name not in self._serializers:
raise ValueError('No such serializer registered : {}'.format(name))
serializer = self._serializers[name]
del self._serializers[name]
return serializer
@property
def serializers(self):
"""Return names of registered serializers"""
return sorted(self._serializers.keys())
class JSONSerializer(object):
"""Wrapper around :mod:`json`. Sets ``indent`` and ``encoding``.
.. versionadded:: 1.8
Use this serializer if you need readable data files. JSON doesn't
support Python objects as well as ``cPickle``/``pickle``, so be
careful which data you try to serialize as JSON.
"""
@classmethod
def load(cls, file_obj):
"""Load serialized object from open JSON file.
.. versionadded:: 1.8
:param file_obj: file handle
:type file_obj: ``file`` object
:returns: object loaded from JSON file
:rtype: object
"""
return json.load(file_obj)
@classmethod
def dump(cls, obj, file_obj):
"""Serialize object ``obj`` to open JSON file.
.. versionadded:: 1.8
:param obj: Python object to serialize
:type obj: JSON-serializable data structure
:param file_obj: file handle
:type file_obj: ``file`` object
"""
return json.dump(obj, file_obj, indent=2, encoding='utf-8')
class CPickleSerializer(object):
"""Wrapper around :mod:`cPickle`. Sets ``protocol``.
.. versionadded:: 1.8
This is the default serializer and the best combination of speed and
flexibility.
"""
@classmethod
def load(cls, file_obj):
"""Load serialized object from open pickle file.
.. versionadded:: 1.8
:param file_obj: file handle
:type file_obj: ``file`` object
:returns: object loaded from pickle file
:rtype: object
"""
return cPickle.load(file_obj)
@classmethod
def dump(cls, obj, file_obj):
"""Serialize object ``obj`` to open pickle file.
.. versionadded:: 1.8
:param obj: Python object to serialize
:type obj: Python object
:param file_obj: file handle
:type file_obj: ``file`` object
"""
return cPickle.dump(obj, file_obj, protocol=-1)
class PickleSerializer(object):
"""Wrapper around :mod:`pickle`. Sets ``protocol``.
.. versionadded:: 1.8
Use this serializer if you need to add custom pickling.
"""
@classmethod
def load(cls, file_obj):
"""Load serialized object from open pickle file.
.. versionadded:: 1.8
:param file_obj: file handle
:type file_obj: ``file`` object
:returns: object loaded from pickle file
:rtype: object
"""
return pickle.load(file_obj)
@classmethod
def dump(cls, obj, file_obj):
"""Serialize object ``obj`` to open pickle file.
.. versionadded:: 1.8
:param obj: Python object to serialize
:type obj: Python object
:param file_obj: file handle
:type file_obj: ``file`` object
"""
return pickle.dump(obj, file_obj, protocol=-1)
# Set up default manager and register built-in serializers
manager = SerializerManager()
manager.register('cpickle', CPickleSerializer)
manager.register('pickle', PickleSerializer)
manager.register('json', JSONSerializer)
class Item(object):
"""Represents a feedback item for Alfred. Generates Alfred-compliant
XML for a single item.
You probably shouldn't use this class directly, but via
:meth:`Workflow.add_item`. See :meth:`~Workflow.add_item`
for details of arguments.
"""
def __init__(self, title, subtitle='', modifier_subtitles=None,
arg=None, autocomplete=None, valid=False, uid=None,
icon=None, icontype=None, type=None, largetext=None,
copytext=None):
"""Arguments the same as for :meth:`Workflow.add_item`.
"""
self.title = title
self.subtitle = subtitle
self.modifier_subtitles = modifier_subtitles or {}
self.arg = arg
self.autocomplete = autocomplete
self.valid = valid
self.uid = uid
self.icon = icon
self.icontype = icontype
self.type = type
self.largetext = largetext
self.copytext = copytext
@property
def elem(self):
"""Create and return feedback item for Alfred.
:returns: :class:`ElementTree.Element <xml.etree.ElementTree.Element>`
instance for this :class:`Item` instance.
"""
attr = {}
if self.valid:
attr['valid'] = 'yes'
else:
attr['valid'] = 'no'
# Optional attributes
for name in ('uid', 'type', 'autocomplete'):
value = getattr(self, name, None)
if value:
attr[name] = value
root = ET.Element('item', attr)
ET.SubElement(root, 'title').text = self.title
ET.SubElement(root, 'subtitle').text = self.subtitle
# Add modifier subtitles
for mod in ('cmd', 'ctrl', 'alt', 'shift', 'fn'):
if mod in self.modifier_subtitles:
ET.SubElement(root, 'subtitle',
{'mod': mod}).text = self.modifier_subtitles[mod]
if self.arg:
ET.SubElement(root, 'arg').text = self.arg
# Add icon if there is one
if self.icon:
if self.icontype:
attr = dict(type=self.icontype)
else:
attr = {}
ET.SubElement(root, 'icon', attr).text = self.icon
if self.largetext:
ET.SubElement(root, 'text',
{'type': 'largetype'}).text = self.largetext
if self.copytext:
ET.SubElement(root, 'text',
{'type': 'copy'}).text = self.copytext
return root
class Settings(dict):
"""A dictionary that saves itself when changed.
Dictionary keys & values will be saved as a JSON file
at ``filepath``. If the file does not exist, the dictionary
(and settings file) will be initialised with ``defaults``.
:param filepath: where to save the settings
:type filepath: :class:`unicode`
:param defaults: dict of default settings
:type defaults: :class:`dict`
An appropriate instance is provided by :class:`Workflow` instances at
:attr:`Workflow.settings`.
"""
def __init__(self, filepath, defaults=None):
super(Settings, self).__init__()
self._filepath = filepath
self._nosave = False
if os.path.exists(self._filepath):
self._load()
elif defaults:
for key, val in defaults.items():
self[key] = val
self.save() # save default settings
def _load(self):
"""Load cached settings from JSON file `self._filepath`"""
self._nosave = True
with open(self._filepath, 'rb') as file_obj:
for key, value in json.load(file_obj, encoding='utf-8').items():
self[key] = value
self._nosave = False
def save(self):
"""Save settings to JSON file specified in ``self._filepath``
If you're using this class via :attr:`Workflow.settings`, which
you probably are, ``self._filepath`` will be ``settings.json``
in your workflow's data directory (see :attr:`~Workflow.datadir`).
"""
if self._nosave:
return
data = {}
for key, value in self.items():
data[key] = value
with open(self._filepath, 'wb') as file_obj:
json.dump(data, file_obj, sort_keys=True, indent=2,
encoding='utf-8')
# dict methods
def __setitem__(self, key, value):
super(Settings, self).__setitem__(key, value)
self.save()
def __delitem__(self, key):
super(Settings, self).__delitem__(key)
self.save()
def update(self, *args, **kwargs):
"""Override :class:`dict` method to save on update."""
super(Settings, self).update(*args, **kwargs)
self.save()
def setdefault(self, key, value=None):
"""Override :class:`dict` method to save on update."""
ret = super(Settings, self).setdefault(key, value)
self.save()
return ret
class Workflow(object):
"""Create new :class:`Workflow` instance.
:param default_settings: default workflow settings. If no settings file
exists, :class:`Workflow.settings` will be pre-populated with
``default_settings``.
:type default_settings: :class:`dict`
:param update_settings: settings for updating your workflow from GitHub.
This must be a :class:`dict` that contains ``github_slug`` and
``version`` keys. ``github_slug`` is of the form ``username/repo``
and ``version`` **must** correspond to the tag of a release.
See :ref:`updates` for more information.
:type update_settings: :class:`dict`
:param input_encoding: encoding of command line arguments
:type input_encoding: :class:`unicode`
:param normalization: normalisation to apply to CLI args.
See :meth:`Workflow.decode` for more details.
:type normalization: :class:`unicode`
:param capture_args: capture and act on ``workflow:*`` arguments. See
:ref:`Magic arguments <magic-arguments>` for details.
:type capture_args: :class:`Boolean`
:param libraries: sequence of paths to directories containing
libraries. These paths will be prepended to ``sys.path``.
:type libraries: :class:`tuple` or :class:`list`
"""
# Which class to use to generate feedback items. You probably
# won't want to change this
item_class = Item
def __init__(self, default_settings=None, update_settings=None,
input_encoding='utf-8', normalization='NFC',
capture_args=True, libraries=None):
self._default_settings = default_settings or {}
self._update_settings = update_settings or {}
self._input_encoding = input_encoding
self._normalizsation = normalization
self._capture_args = capture_args
self._workflowdir = None
self._settings_path = None
self._settings = None
self._bundleid = None
self._name = None
self._cache_serializer = 'cpickle'
self._data_serializer = 'cpickle'
# info.plist should be in the directory above this one
self._info_plist = self.workflowfile('info.plist')
self._info = None
self._info_loaded = False
self._logger = None
self._items = []
self._alfred_env = None
self._search_pattern_cache = {}
if libraries:
sys.path = libraries + sys.path
if update_settings:
self.check_update()
####################################################################
# API methods
####################################################################
# info.plist contents and alfred_* environment variables ----------
@property
def alfred_env(self):
"""Alfred's environmental variables minus the ``alfred_`` prefix.
.. versionadded:: 1.7
The variables Alfred 2.4+ exports are:
============================ =========================================
Variable Description
============================ =========================================
alfred_preferences Path to Alfred.alfredpreferences
(where your workflows and settings are
stored).
alfred_preferences_localhash Machine-specific preferences are stored
in ``Alfred.alfredpreferences/preferences/local/<hash>``
(see ``alfred_preferences`` above for
the path to ``Alfred.alfredpreferences``)
alfred_theme ID of selected theme
alfred_theme_background Background colour of selected theme in
format ``rgba(r,g,b,a)``
alfred_theme_subtext Show result subtext.
``0`` = Always,
``1`` = Alternative actions only,
``2`` = Selected result only,
``3`` = Never
alfred_version Alfred version number, e.g. ``'2.4'``
alfred_version_build Alfred build number, e.g. ``277``
alfred_workflow_bundleid Bundle ID, e.g.
``net.deanishe.alfred-mailto``
alfred_workflow_cache Path to workflow's cache directory
alfred_workflow_data Path to workflow's data directory
alfred_workflow_name Name of current workflow
alfred_workflow_uid UID of workflow
============================ =========================================
**Note:** all values are Unicode strings except ``version_build`` and
``theme_subtext``, which are integers.
:returns: ``dict`` of Alfred's environmental variables without the
``alfred_`` prefix, e.g. ``preferences``, ``workflow_data``.
"""
if self._alfred_env is not None:
return self._alfred_env
data = {}
for key in (
'alfred_preferences',
'alfred_preferences_localhash',
'alfred_theme',
'alfred_theme_background',
'alfred_theme_subtext',
'alfred_version',
'alfred_version_build',
'alfred_workflow_bundleid',
'alfred_workflow_cache',
'alfred_workflow_data',
'alfred_workflow_name',
'alfred_workflow_uid'):
value = os.getenv(key)
if isinstance(value, str):
if key in ('alfred_version_build', 'alfred_theme_subtext'):
value = int(value)
else:
value = self.decode(value)
data[key[7:]] = value
self._alfred_env = data
return self._alfred_env
@property
def info(self):
""":class:`dict` of ``info.plist`` contents."""
if not self._info_loaded:
self._load_info_plist()
return self._info
@property
def bundleid(self):
"""Workflow bundle ID from Alfred's environmental vars or ``info.plist``.
:returns: bundle ID
:rtype: ``unicode``
"""
if not self._bundleid:
if self.alfred_env.get('workflow_bundleid'):
self._bundleid = self.alfred_env.get('workflow_bundleid')
else:
self._bundleid = unicode(self.info['bundleid'], 'utf-8')
return self._bundleid
@property
def name(self):
"""Workflow name from Alfred's environmental vars or ``info.plist``.
:returns: workflow name
:rtype: ``unicode``
"""
if not self._name:
if self.alfred_env.get('workflow_name'):
self._name = self.decode(self.alfred_env.get('workflow_name'))
else:
self._name = self.decode(self.info['name'])
return self._name
# Workflow utility methods -----------------------------------------
@property
def args(self):
"""Return command line args as normalised unicode.
Args are decoded and normalised via :meth:`~Workflow.decode`.
The encoding and normalisation are the ``input_encoding`` and
``normalization`` arguments passed to :class:`Workflow` (``UTF-8``
and ``NFC`` are the defaults).
If :class:`Workflow` is called with ``capture_args=True`` (the default),
:class:`Workflow` will look for certain ``workflow:*`` args and, if
found, perform the corresponding actions and exit the workflow.
See :ref:`Magic arguments <magic-arguments>` for details.
"""
msg = None
args = [self.decode(arg) for arg in sys.argv[1:]]
if len(args) and self._capture_args:
if 'workflow:openlog' in args:
msg = 'Opening workflow log file'
self.open_log()
elif 'workflow:reset' in args:
self.reset()
msg = 'Reset workflow'
elif 'workflow:delcache' in args:
self.clear_cache()
msg = 'Deleted workflow cache'
elif 'workflow:deldata' in args:
self.clear_data()
msg = 'Deleted workflow data'
elif 'workflow:delsettings' in args:
self.clear_settings()
msg = 'Deleted workflow settings'
elif 'workflow:openworkflow' in args:
msg = 'Opening workflow directory'
self.open_workflowdir()
elif 'workflow:opendata' in args:
msg = 'Opening workflow data directory'
self.open_datadir()
elif 'workflow:opencache' in args:
msg = 'Opening workflow cache directory'
self.open_cachedir()
elif 'workflow:openterm' in args:
msg = 'Opening workflow root directory in Terminal'
self.open_terminal()
elif 'workflow:foldingon' in args:
msg = 'Diacritics will always be folded'
self.settings['__workflow_diacritic_folding'] = True
elif 'workflow:foldingoff' in args:
msg = 'Diacritics will never be folded'
self.settings['__workflow_diacritic_folding'] = False
elif 'workflow:foldingdefault' in args:
msg = 'Diacritics folding reset'
if '__workflow_diacritic_folding' in self.settings:
del self.settings['__workflow_diacritic_folding']
elif 'workflow:update' in args:
msg = 'Updating workflow'
self.start_update()
if msg:
self.logger.debug(msg)
if not sys.stdout.isatty(): # Show message in Alfred
self.add_item(msg, valid=False, icon=ICON_INFO)
self.send_feedback()
sys.exit(0)
return args
@property
def cachedir(self):
"""Path to workflow's cache directory.
The cache directory is a subdirectory of Alfred's own cache directory in
``~/Library/Caches``. The full path is:
``~/Library/Caches/com.runningwithcrayons.Alfred-2/Workflow Data/<bundle id>``
:returns: full path to workflow's cache directory
:rtype: ``unicode``
"""
if self.alfred_env.get('workflow_cache'):
dirpath = self.alfred_env.get('workflow_cache')
else:
dirpath = os.path.join(
os.path.expanduser(
'~/Library/Caches/com.runningwithcrayons.Alfred-2/'
'Workflow Data/'),
self.bundleid)
return self._create(dirpath)
@property
def datadir(self):
"""Path to workflow's data directory.
The data directory is a subdirectory of Alfred's own data directory in
``~/Library/Application Support``. The full path is:
``~/Library/Application Support/Alfred 2/Workflow Data/<bundle id>``
:returns: full path to workflow data directory
:rtype: ``unicode``
"""
if self.alfred_env.get('workflow_data'):
dirpath = self.alfred_env.get('workflow_data')
else:
dirpath = os.path.join(os.path.expanduser(
'~/Library/Application Support/Alfred 2/Workflow Data/'),
self.bundleid)
return self._create(dirpath)
@property
def workflowdir(self):
"""Path to workflow's root directory (where ``info.plist`` is).
:returns: full path to workflow root directory
:rtype: ``unicode``
"""
if not self._workflowdir:
# Try the working directory first, then the directory
# the library is in. CWD will be the workflow root if
# a workflow is being run in Alfred
candidates = [
os.path.abspath(os.getcwdu()),
os.path.dirname(os.path.abspath(os.path.dirname(__file__)))]
# climb the directory tree until we find `info.plist`
for dirpath in candidates:
# Ensure directory path is Unicode
dirpath = self.decode(dirpath)
while True:
if os.path.exists(os.path.join(dirpath, 'info.plist')):
self._workflowdir = dirpath
break
elif dirpath == '/':
# no `info.plist` found
break
# Check the parent directory
dirpath = os.path.dirname(dirpath)
# No need to check other candidates
if self._workflowdir:
break
if not self._workflowdir:
raise IOError("'info.plist' not found in directory tree")
return self._workflowdir
def cachefile(self, filename):
"""Return full path to ``filename`` within your workflow's
:attr:`cache directory <Workflow.cachedir>`.
:param filename: basename of file
:type filename: ``unicode``
:returns: full path to file within cache directory
:rtype: ``unicode``
"""
return os.path.join(self.cachedir, filename)
def datafile(self, filename):
"""Return full path to ``filename`` within your workflow's
:attr:`data directory <Workflow.datadir>`.
:param filename: basename of file
:type filename: ``unicode``
:returns: full path to file within data directory
:rtype: ``unicode``
"""
return os.path.join(self.datadir, filename)
def workflowfile(self, filename):
"""Return full path to ``filename`` in workflow's root dir
(where ``info.plist`` is).
:param filename: basename of file
:type filename: ``unicode``
:returns: full path to file within data directory
:rtype: ``unicode``
"""
return os.path.join(self.workflowdir, filename)
@property
def logfile(self):
"""Return path to logfile
:returns: path to logfile within workflow's cache directory
:rtype: ``unicode``
"""
return self.cachefile('%s.log' % self.bundleid)
@property
def logger(self):
"""Create and return a logger that logs to both console and
a log file. Use `~Workflow.openlog` to open the log file in Console.
:returns: an initialised logger
:rtype: `~logging.Logger` instance
"""
if self._logger:
return self._logger
# Initialise new logger and optionally handlers
logger = logging.getLogger('workflow')
if not len(logger.handlers): # Only add one set of handlers
logfile = logging.handlers.RotatingFileHandler(
self.logfile,
maxBytes=1024*1024,
backupCount=0)
console = logging.StreamHandler()
fmt = logging.Formatter(
'%(asctime)s %(filename)s:%(lineno)s'
' %(levelname)-8s %(message)s',
datefmt='%H:%M:%S')
logfile.setFormatter(fmt)
console.setFormatter(fmt)
logger.addHandler(logfile)
logger.addHandler(console)
logger.setLevel(logging.DEBUG)
self._logger = logger
return self._logger
@logger.setter
def logger(self, logger):
"""Set a custom logger.
:param logger: The logger to use
:type logger: `~logging.Logger` instance
"""
self._logger = logger
@property
def settings_path(self):
"""Path to settings file within workflow's data directory.
:returns: path to ``settings.json`` file
:rtype: ``unicode``
"""
if not self._settings_path:
self._settings_path = self.datafile('settings.json')
return self._settings_path
@property
def settings(self):
"""Return a dictionary subclass that saves itself when changed.
:returns: :class:`Settings` instance initialised from the data
in JSON file at :attr:`settings_path` or if that doesn't exist,
with the ``default_settings`` ``dict`` passed to :class:`Workflow`.
:rtype: :class:`Settings` instance
"""
if not self._settings:
self._settings = Settings(self.settings_path,
self._default_settings)
return self._settings
@property
def cache_serializer(self):
"""Name of default cache serializer.
.. versionadded:: 1.8
This serializer is used by :meth:`cache_data()` and
:meth:`cached_data()`
See :class:`SerializerManager` for details.
:returns: serializer name
:rtype: ``unicode``
"""
return self._cache_serializer
@cache_serializer.setter
def cache_serializer(self, serializer_name):
"""Set the default cache serialization format.
.. versionadded:: 1.8
This serializer is used by :meth:`cache_data()` and
:meth:`cached_data()`
The specified serializer must already by registered with the
:class:`SerializerManager` at `~workflow.workflow.manager`,
otherwise a :class:`ValueError` will be raised.
:param serializer_name: Name of default serializer to use.
:type serializer_name:
"""
if manager.serializer(serializer_name) is None:
raise ValueError(
'Unknown serializer : `{}`. Register your serializer '
'with `manager` first.'.format(serializer_name))
self.logger.debug(
'default cache serializer set to `{}`'.format(serializer_name))
self._cache_serializer = serializer_name
@property
def data_serializer(self):
"""Name of default data serializer.
.. versionadded:: 1.8
This serializer is used by :meth:`store_data()` and
:meth:`stored_data()`
See :class:`SerializerManager` for details.
:returns: serializer name
:rtype: ``unicode``
"""
return self._data_serializer
@data_serializer.setter
def data_serializer(self, serializer_name):
"""Set the default cache serialization format.
.. versionadded:: 1.8
This serializer is used by :meth:`store_data()` and
:meth:`stored_data()`
The specified serializer must already by registered with the
:class:`SerializerManager` at `~workflow.workflow.manager`,
otherwise a :class:`ValueError` will be raised.
:param serializer_name: Name of default serializer to use.
:type serializer_name:
"""
if manager.serializer(serializer_name) is None:
raise ValueError(
'Unknown serializer : `{}`. Register your serializer '
'with `manager` first.'.format(serializer_name))
self.logger.debug(
'default data serializer set to `{}`'.format(serializer_name))
self._data_serializer = serializer_name
def stored_data(self, name):
"""Retrieve data from data directory. Returns ``None`` if there
is no data stored.
.. versionadded:: 1.8
:param name: name of datastore
:type name: ``unicode``
"""
metadata_path = self.datafile('.{}.alfred-workflow'.format(name))
if not os.path.exists(metadata_path):
self.logger.debug('No data stored for `{}`'.format(name))
return None
with open(metadata_path, 'rb') as file_obj:
serializer_name = file_obj.read().strip()
serializer = manager.serializer(serializer_name)
if serializer is None:
raise ValueError(
'Unknown serializer `{}`. Register a corresponding serializer '
'with `manager.register()` to load this data.'.format(
serializer_name))
self.logger.debug('Data `{}` stored in `{}` format'.format(
name, serializer_name))
filename = '{}.{}'.format(name, serializer_name)
data_path = self.datafile(filename)
if not os.path.exists(data_path):
self.logger.debug('No data stored for `{}`'.format(name))
if os.path.exists(metadata_path):
os.unlink(metadata_path)
return None
with open(data_path, 'rb') as file_obj:
data = serializer.load(file_obj)
self.logger.debug('Stored data loaded from : {}'.format(data_path))
return data
def store_data(self, name, data, serializer=None):
"""Save data to data directory.
.. versionadded:: 1.8
If ``data`` is ``None``, the datastore will be deleted.
:param name: name of datastore
:type name: ``unicode``
:param data: object(s) to store
:type data: artibrary Python objects. **Note:** some serializers
can only handled certain types of data.
:param serializer: name of serializer to use.
See :class:`SerializerManager` for more information.
:type serializer: ``unicode``
:returns: data in datastore or ``None``
"""
serializer_name = serializer or self.data_serializer
if serializer_name == 'json' and name == 'settings':
raise ValueError(
'Cannot save data to `settings` with format `json`. '
"This would overwrite Alfred-Workflow's settings file.")
serializer = manager.serializer(serializer_name)
if serializer is None:
raise ValueError(
'Invalid serializer `{}`. Register your serializer with '
'`manager.register()` first.'.format(serializer_name))
# In order for `stored_data()` to be able to load data stored with
# an arbitrary serializer, yet still have meaningful file extensions,
# the format (i.e. extension) is saved to an accompanying file
metadata_path = self.datafile('.{}.alfred-workflow'.format(name))
filename = '{}.{}'.format(name, serializer_name)
data_path = self.datafile(filename)
if data is None: # Delete cached data
for path in (metadata_path, data_path):
if os.path.exists(path):
os.unlink(path)
self.logger.debug('Deleted data file : {}'.format(path))
return
# Save file extension
with open(metadata_path, 'wb') as file_obj:
file_obj.write(serializer_name)
with open(data_path, 'wb') as file_obj:
serializer.dump(data, file_obj)
self.logger.debug('Stored data saved at : {}'.format(data_path))
def cached_data(self, name, data_func=None, max_age=60):
"""Retrieve data from cache or re-generate and re-cache data if
stale/non-existant. If ``max_age`` is 0, return cached data no
matter how old.
:param name: name of datastore
:type name: ``unicode``
:param data_func: function to (re-)generate data.
:type data_func: ``callable``
:param max_age: maximum age of cached data in seconds
:type max_age: ``int``
:returns: cached data, return value of ``data_func`` or ``None``
if ``data_func`` is not set
:rtype: whatever ``data_func`` returns or ``None``
"""
serializer = manager.serializer(self.cache_serializer)
cache_path = self.cachefile('%s.%s' % (name, self.cache_serializer))
age = self.cached_data_age(name)
if (age < max_age or max_age == 0) and os.path.exists(cache_path):
with open(cache_path, 'rb') as file_obj:
self.logger.debug('Loading cached data from : %s',
cache_path)
return serializer.load(file_obj)
if not data_func:
return None
data = data_func()
self.cache_data(name, data)
return data
def cache_data(self, name, data):
"""Save ``data`` to cache under ``name``.
If ``data`` is ``None``, the corresponding cache file will be deleted.
:param name: name of datastore
:type name: ``unicode``
:param data: data to store
:type data: any object supported by :mod:`pickle`
"""
serializer = manager.serializer(self.cache_serializer)
cache_path = self.cachefile('%s.%s' % (name, self.cache_serializer))
if data is None:
if os.path.exists(cache_path):
os.unlink(cache_path)
self.logger.debug('Deleted cache file : %s', cache_path)
return
with open(cache_path, 'wb') as file_obj:
serializer.dump(data, file_obj)
self.logger.debug('Cached data saved at : %s', cache_path)
def cached_data_fresh(self, name, max_age):
"""Is data cached at `name` less than `max_age` old?
:param name: name of datastore
:type name: ``unicode``
:param max_age: maximum age of data in seconds
:type max_age: ``int``
:returns: ``True`` if data is less than ``max_age`` old, else ``False``
:rtype: ``Boolean``
"""
age = self.cached_data_age(name)
if not age:
return False
return age < max_age
def cached_data_age(self, name):
"""Return age of data cached at `name` in seconds or 0 if
cache doesn't exist
:param name: name of datastore
:type name: ``unicode``
:returns: age of datastore in seconds
:rtype: ``int``
"""
cache_path = self.cachefile('%s.%s' % (name, self.cache_serializer))
if not os.path.exists(cache_path):
return 0
return time.time() - os.stat(cache_path).st_mtime
def filter(self, query, items, key=lambda x: x, ascending=False,
include_score=False, min_score=0, max_results=0,
match_on=MATCH_ALL, fold_diacritics=True):
"""Fuzzy search filter. Returns list of ``items`` that match ``query``.
``query`` is case-insensitive. Any item that does not contain the
entirety of ``query`` is rejected.
.. warning::
If ``query`` is an empty string or contains only whitespace,
a :class:`ValueError` will be raised.
:param query: query to test items against
:type query: ``unicode``
:param items: iterable of items to test
:type items: ``list`` or ``tuple``
:param key: function to get comparison key from ``items``.
Must return a ``unicode`` string. The default simply returns
the item.
:type key: ``callable``
:param ascending: set to ``True`` to get worst matches first
:type ascending: ``Boolean``
:param include_score: Useful for debugging the scoring algorithm.
If ``True``, results will be a list of tuples
``(item, score, rule)``.
:type include_score: ``Boolean``
:param min_score: If non-zero, ignore results with a score lower
than this.
:type min_score: ``int``
:param max_results: If non-zero, prune results list to this length.
:type max_results: ``int``
:param match_on: Filter option flags. Bitwise-combined list of
``MATCH_*`` constants (see below).
:type match_on: ``int``
:param fold_diacritics: Convert search keys to ASCII-only
characters if ``query`` only contains ASCII characters.
:type fold_diacritics: ``Boolean``
:returns: list of ``items`` matching ``query`` or list of
``(item, score, rule)`` `tuples` if ``include_score`` is ``True``.
``rule`` is the ``MATCH_*`` rule that matched the item.
:rtype: ``list``
**Matching rules**
By default, :meth:`filter` uses all of the following flags (i.e.
:const:`MATCH_ALL`). The tests are always run in the given order:
1. :const:`MATCH_STARTSWITH` : Item search key startswith ``query`` (case-insensitive).
2. :const:`MATCH_CAPITALS` : The list of capital letters in item search key starts with ``query`` (``query`` may be lower-case). E.g., ``of`` would match ``OmniFocus``, ``gc`` would match ``Google Chrome``
3. :const:`MATCH_ATOM` : Search key is split into "atoms" on non-word characters (.,-,' etc.). Matches if ``query`` is one of these atoms (case-insensitive).
4. :const:`MATCH_INITIALS_STARTSWITH` : Initials are the first characters of the above-described "atoms" (case-insensitive).
5. :const:`MATCH_INITIALS_CONTAIN` : ``query`` is a substring of the above-described initials.
6. :const:`MATCH_INITIALS` : Combination of (4) and (5).
7. :const:`MATCH_SUBSTRING` : Match if ``query`` is a substring of item search key (case-insensitive).
8. :const:`MATCH_ALLCHARS` : Matches if all characters in ``query`` appear in item search key in the same order (case-insensitive).
9. :const:`MATCH_ALL` : Combination of all the above.
:const:`MATCH_ALLCHARS` is considerably slower than the other tests and
provides much less accurate results.
**Examples:**
To ignore :const:`MATCH_ALLCHARS` (tends to provide the worst
matches and is expensive to run), use
``match_on=MATCH_ALL ^ MATCH_ALLCHARS``.
To match only on capitals, use ``match_on=MATCH_CAPITALS``.
To match only on startswith and substring, use
``match_on=MATCH_STARTSWITH | MATCH_SUBSTRING``.
**Diacritic folding**
.. versionadded:: 1.3
If ``fold_diacritics`` is ``True`` (the default), and ``query``
contains only ASCII characters, non-ASCII characters in search keys
will be converted to ASCII equivalents (e.g. **ü** -> **u**,
**ß** -> **ss**, **é** -> **e**).
See :const:`ASCII_REPLACEMENTS` for all replacements.
If ``query`` contains non-ASCII characters, search keys will not be
altered.
"""
if not query:
raise ValueError('Empty `query`')
# Remove preceding/trailing spaces
query = query.strip()
if not query:
raise ValueError('`query` contains only whitespace')
# Use user override if there is one
fold_diacritics = self.settings.get('__workflow_diacritic_folding',
fold_diacritics)
results = []
for item in items:
skip = False
score = 0
words = [s.strip() for s in query.split(' ')]
value = key(item).strip()
if value == '':
continue
for word in words:
if word == '':
continue
s, r = self._filter_item(value, word, match_on,
fold_diacritics)
if not s: # Skip items that don't match part of the query
skip = True
score += s
if skip:
continue
if score:
# use "reversed" `score` (i.e. highest becomes lowest) and
# `value` as sort key. This means items with the same score
# will be sorted in alphabetical not reverse alphabetical order
results.append(((100.0 / score, value.lower(), score),
(item, score, r)))
# sort on keys, then discard the keys
results.sort(reverse=ascending)
results = [t[1] for t in results]
if max_results and len(results) > max_results:
results = results[:max_results]
if min_score:
results = [r for r in results if r[1] > min_score]
# return list of ``(item, score, rule)``
if include_score:
return results
# just return list of items
return [t[0] for t in results]
def _filter_item(self, value, query, match_on, fold_diacritics):
"""Filter ``value`` against ``query`` using rules ``match_on``
:returns: ``(score, rule)``
"""
query = query.lower()
queryset = set(query)
if not isascii(query):
fold_diacritics = False
rule = None
score = 0
if fold_diacritics:
value = self.fold_to_ascii(value)
# pre-filter any items that do not contain all characters
# of ``query`` to save on running several more expensive tests
if not queryset <= set(value.lower()):
return (0, None)
# item starts with query
if (match_on & MATCH_STARTSWITH and
value.lower().startswith(query)):
score = 100.0 - (len(value) / len(query))
rule = MATCH_STARTSWITH
if not score and match_on & MATCH_CAPITALS:
# query matches capitalised letters in item,
# e.g. of = OmniFocus
initials = ''.join([c for c in value if c in INITIALS])
if initials.lower().startswith(query):
score = 100.0 - (len(initials) / len(query))
rule = MATCH_CAPITALS
if not score:
if (match_on & MATCH_ATOM or
match_on & MATCH_INITIALS_CONTAIN or
match_on & MATCH_INITIALS_STARTSWITH):
# split the item into "atoms", i.e. words separated by
# spaces or other non-word characters
atoms = [s.lower() for s in split_on_delimiters(value)]
# print('atoms : %s --> %s' % (value, atoms))
# initials of the atoms
initials = ''.join([s[0] for s in atoms if s])
if match_on & MATCH_ATOM:
# is `query` one of the atoms in item?
# similar to substring, but scores more highly, as it's
# a word within the item
if query in atoms:
score = 100.0 - (len(value) / len(query))
rule = MATCH_ATOM
if not score:
# `query` matches start (or all) of the initials of the
# atoms, e.g. ``himym`` matches "How I Met Your Mother"
# *and* "how i met your mother" (the ``capitals`` rule only
# matches the former)
if (match_on & MATCH_INITIALS_STARTSWITH and
initials.startswith(query)):
score = 100.0 - (len(initials) / len(query))
rule = MATCH_INITIALS_STARTSWITH
# `query` is a substring of initials, e.g. ``doh`` matches
# "The Dukes of Hazzard"
elif (match_on & MATCH_INITIALS_CONTAIN and
query in initials):
score = 95.0 - (len(initials) / len(query))
rule = MATCH_INITIALS_CONTAIN
if not score:
# `query` is a substring of item
if match_on & MATCH_SUBSTRING and query in value.lower():
score = 90.0 - (len(value) / len(query))
rule = MATCH_SUBSTRING
if not score:
# finally, assign a score based on how close together the
# characters in `query` are in item.
if match_on & MATCH_ALLCHARS:
search = self._search_for_query(query)
match = search(value)
if match:
score = 100.0 / ((1 + match.start()) *
(match.end() - match.start() + 1))
rule = MATCH_ALLCHARS
if score > 0:
return (score, rule)
return (0, None)
def _search_for_query(self, query):
if query in self._search_pattern_cache:
return self._search_pattern_cache[query]
# Build pattern: include all characters
pattern = []
for c in query:
# pattern.append('[^{0}]*{0}'.format(re.escape(c)))
pattern.append('.*?{0}'.format(re.escape(c)))
pattern = ''.join(pattern)
search = re.compile(pattern, re.IGNORECASE).search
self._search_pattern_cache[query] = search
return search
def run(self, func):
"""Call ``func`` to run your workflow
:param func: Callable to call with ``self`` (i.e. the :class:`Workflow`
instance) as first argument.
``func`` will be called with :class:`Workflow` instance as first argument.
``func`` should be the main entry point to your workflow.
Any exceptions raised will be logged and an error message will be
output to Alfred.
"""
try:
func(self)
except Exception as err:
self.logger.exception(err)
if not sys.stdout.isatty(): # Show error in Alfred
self._items = []
if self._name:
name = self._name
elif self._bundleid:
name = self._bundleid
else: # pragma: no cover
name = os.path.dirname(__file__)
self.add_item("Error in workflow '%s'" % name, unicode(err),
icon=ICON_ERROR)
self.send_feedback()
return 1
return 0
# Alfred feedback methods ------------------------------------------
def add_item(self, title, subtitle='', modifier_subtitles=None, arg=None,
autocomplete=None, valid=False, uid=None, icon=None,
icontype=None, type=None, largetext=None, copytext=None):
"""Add an item to be output to Alfred
:param title: Title shown in Alfred
:type title: ``unicode``
:param subtitle: Subtitle shown in Alfred
:type subtitle: ``unicode``
:param modifier_subtitles: Subtitles shown when modifier
(CMD, OPT etc.) is pressed. Use a ``dict`` with the lowercase
keys ``cmd``, ``ctrl``, ``shift``, ``alt`` and ``fn``
:type modifier_subtitles: ``dict``
:param arg: Argument passed by Alfred as ``{query}`` when item is
actioned
:type arg: ``unicode``
:param autocomplete: Text expanded in Alfred when item is TABbed
:type autocomplete: ``unicode``
:param valid: Whether or not item can be actioned
:type valid: ``Boolean``
:param uid: Used by Alfred to remember/sort items
:type uid: ``unicode``
:param icon: Filename of icon to use
:type icon: ``unicode``
:param icontype: Type of icon. Must be one of ``None`` , ``'filetype'``
or ``'fileicon'``. Use ``'filetype'`` when ``icon`` is a filetype
such as ``'public.folder'``. Use ``'fileicon'`` when you wish to
use the icon of the file specified as ``icon``, e.g.
``icon='/Applications/Safari.app', icontype='fileicon'``.
Leave as `None` if ``icon`` points to an actual
icon file.
:type icontype: ``unicode``
:param type: Result type. Currently only ``'file'`` is supported
(by Alfred). This will tell Alfred to enable file actions for
this item.
:type type: ``unicode``
:param largetext: Text to be displayed in Alfred's large text box
if user presses CMD+L on item.
:type largetext: ``unicode``
:param copytext: Text to be copied to pasteboard if user presses
CMD+C on item.
:type copytext: ``unicode``
:returns: :class:`Item` instance
See the :ref:`script-filter-results` section of the documentation
for a detailed description of what the various parameters do and how
they interact with one another.
See :ref:`icons` for a list of the supported system icons.
.. note::
Although this method returns an :class:`Item` instance, you don't
need to hold onto it or worry about it. All generated :class:`Item`
instances are also collected internally and sent to Alfred when
:meth:`send_feedback` is called.
The generated :class:`Item` is only returned in case you want to
edit it or do something with it other than send it to Alfred.
"""
item = self.item_class(title, subtitle, modifier_subtitles, arg,
autocomplete, valid, uid, icon, icontype, type,
largetext, copytext)
self._items.append(item)
return item
def send_feedback(self):
"""Print stored items to console/Alfred as XML."""
root = ET.Element('items')
for item in self._items:
root.append(item.elem)
sys.stdout.write('<?xml version="1.0" encoding="utf-8"?>\n')
sys.stdout.write(ET.tostring(root).encode('utf-8'))
sys.stdout.flush()
####################################################################
# Updating methods
####################################################################
@property
def update_available(self):
"""Is an update available?
:returns: ``True`` if an update is available, else ``False``
"""
update_data = self.cached_data('__workflow_update_status')
if not update_data or not update_data.get('available'):
return False
return update_data['available']
def check_update(self, force=False):
"""Check if it's time to update and call update script if it is.
:param force: Force update check
:type force: ``Boolean``
"""
frequency = self._update_settings.get('frequency',
DEFAULT_UPDATE_FREQUENCY)
if (force or not self.cached_data_fresh(
'__workflow_update_status', frequency * 86400)):
github_slug = self._update_settings['github_slug']
version = self._update_settings['version']
from background import run_in_background
# update.py is adjacent to this file
update_script = os.path.join(os.path.dirname(__file__),
b'update.py')
cmd = ['/usr/bin/python', update_script, github_slug, version]
self.logger.info('Checking for update ...')
run_in_background('__workflow_update', cmd)
else:
self.logger.debug('Update not due')
def start_update(self):
"""Check for update and download and install new workflow file
:returns: ``True`` if an update is available, else ``False``
"""
import update
github_slug = self._update_settings['github_slug']
version = self._update_settings['version']
if not update.check_update(github_slug, version):
return False
update_data = self.cached_data('__workflow_update_status')
if (update_data is None or not update_data.get('available')):
return False # pragma: no cover
local_file = update.download_workflow(update_data['download_url'])
self.logger.debug('Installing updated workflow ...')
subprocess.call(['open', local_file])
update_data['available'] = False
self.cache_data('__workflow_update_status', update_data)
return True
####################################################################
# Keychain password storage methods
####################################################################
def save_password(self, account, password, service=None):
"""Save account credentials.
If the account exists, the old password will first be deleted (Keychain
throws an error otherwise).
If something goes wrong, a `KeychainError` exception will be raised.
:param account: name of the account the password is for, e.g.
"Pinboard"
:type account: ``unicode``
:param password: the password to secure
:type password: ``unicode``
:param service: Name of the service. By default, this is the workflow's
bundle ID
:type service: ``unicode``
"""
if not service:
service = self.bundleid
try:
retcode, output = self._call_security('add-generic-password',
service, account,
'-w', password)
self.logger.debug('Saved password : %s:%s', service, account)
except PasswordExists:
self.logger.debug('Password exists : %s:%s', service, account)
current_password = self.get_password(account, service)
if current_password == password:
self.logger.debug('Password unchanged')
else:
self.delete_password(account, service)
retcode, output = self._call_security('add-generic-password',
service, account,
'-w', password)
self.logger.debug('save_password : %s:%s', service, account)
def get_password(self, account, service=None):
"""Retrieve the password saved at ``service/account``. Raise
:class:`PasswordNotFound` exception if password doesn't exist.
:param account: name of the account the password is for, e.g.
"Pinboard"
:type account: ``unicode``
:param service: Name of the service. By default, this is the workflow's
bundle ID
:type service: ``unicode``
:returns: account password
:rtype: ``unicode``
"""
if not service:
service = self.bundleid
retcode, password = self._call_security('find-generic-password',
service, account, '-w')
self.logger.debug('get_password : %s:%s', service, account)
return password
def delete_password(self, account, service=None):
"""Delete the password stored at ``service/account``. Raises
:class:`PasswordNotFound` if account is unknown.
:param account: name of the account the password is for, e.g.
"Pinboard"
:type account: ``unicode``
:param service: Name of the service. By default, this is the workflow's
bundle ID
:type service: ``unicode``
"""
if not service:
service = self.bundleid
retcode, output = self._call_security('delete-generic-password',
service, account)
self.logger.debug('delete_password : %s:%s', service, account)
####################################################################
# Methods for workflow:* magic args
####################################################################
def clear_cache(self):
"""Delete all files in workflow cache directory."""
self._delete_directory_contents(self.cachedir)
def clear_data(self):
"""Delete all files in workflow data directory."""
self._delete_directory_contents(self.datadir)
def clear_settings(self):
"""Delete settings file."""
if os.path.exists(self.settings_path):
os.unlink(self.settings_path)
self.logger.debug('Deleted : %r', self.settings_path)
def reset(self):
"""Delete settings, cache and data"""
self.clear_cache()
self.clear_data()
self.clear_settings()
def open_log(self):
"""Open log file in standard application (usually Console.app)."""
subprocess.call(['open', self.logfile])
def open_cachedir(self):
"""Open the workflow cache directory in Finder."""
subprocess.call(['open', self.cachedir])
def open_datadir(self):
"""Open the workflow data directory in Finder."""
subprocess.call(['open', self.datadir])
def open_workflowdir(self):
"""Open the workflow directory in Finder."""
subprocess.call(['open', self.workflowdir])
def open_terminal(self):
"""Open a Terminal window at workflow directory."""
subprocess.call(['open', '-a', 'Terminal',
self.workflowdir])
####################################################################
# Helper methods
####################################################################
def decode(self, text, encoding=None, normalization=None):
"""Return ``text`` as normalised unicode.
If ``encoding`` and/or ``normalization`` is ``None``, the
``input_encoding``and ``normalization`` parameters passed to
:class:`Workflow` are used.
:param text: string
:type text: encoded or Unicode string. If ``text`` is already a
Unicode string, it will only be normalised.
:param encoding: The text encoding to use to decode ``text`` to
Unicode.
:type encoding: ``unicode`` or ``None``
:param normalization: The nomalisation form to apply to ``text``.
:type normalization: ``unicode`` or ``None``
:returns: decoded and normalised ``unicode``
:class:`Workflow` uses "NFC" normalisation by default. This is the
standard for Python and will work well with data from the web (via
:mod:`~workflow.web` or :mod:`json`).
OS X, on the other hand, uses "NFD" normalisation (nearly), so data
coming from the system (e.g. via :mod:`subprocess` or
:func:`os.listdir`/:mod:`os.path`) may not match. You should either
normalise this data, too, or change the default normalisation used by
:class:`Workflow`.
"""
encoding = encoding or self._input_encoding
normalization = normalization or self._normalizsation
if not isinstance(text, unicode):
text = unicode(text, encoding)
return unicodedata.normalize(normalization, text)
def fold_to_ascii(self, text):
"""Convert non-ASCII characters to closest ASCII equivalent.
.. versionadded:: 1.3
.. note:: This only works for a subset of European languages.
:param text: text to convert
:type text: ``unicode``
:returns: text containing only ASCII characters
:rtype: ``unicode``
"""
if isascii(text):
return text
text = ''.join([ASCII_REPLACEMENTS.get(c, c) for c in text])
return unicode(unicodedata.normalize('NFKD',
text).encode('ascii', 'ignore'))
def _delete_directory_contents(self, dirpath):
"""Delete all files in a directory
:param dirpath: path to directory to clear
:type dirpath: ``unicode`` or ``str``
"""
if os.path.exists(dirpath):
for filename in os.listdir(dirpath):
path = os.path.join(dirpath, filename)
if os.path.isdir(path):
shutil.rmtree(path)
else:
os.unlink(path)
self.logger.debug('Deleted : %r', path)
def _load_info_plist(self):
"""Load workflow info from ``info.plist``
"""
self._info = plistlib.readPlist(self._info_plist)
self._info_loaded = True
def _create(self, dirpath):
"""Create directory `dirpath` if it doesn't exist
:param dirpath: path to directory
:type dirpath: ``unicode``
:returns: ``dirpath`` argument
:rtype: ``unicode``
"""
if not os.path.exists(dirpath):
os.makedirs(dirpath)
return dirpath
def _call_security(self, action, service, account, *args):
"""Call the ``security`` CLI app that provides access to keychains.
May raise `PasswordNotFound`, `PasswordExists` or `KeychainError`
exceptions (the first two are subclasses of `KeychainError`).
:param action: The ``security`` action to call, e.g.
``add-generic-password``
:type action: ``unicode``
:param service: Name of the service.
:type service: ``unicode``
:param account: name of the account the password is for, e.g.
"Pinboard"
:type account: ``unicode``
:param password: the password to secure
:type password: ``unicode``
:param *args: list of command line arguments to be passed to
``security``
:type *args: `list` or `tuple`
:returns: ``(retcode, output)``. ``retcode`` is an `int`, ``output`` a
``unicode`` string.
:rtype: `tuple` (`int`, ``unicode``)
"""
cmd = ['security', action, '-s', service, '-a', account] + list(args)
p = subprocess.Popen(cmd, stdout=subprocess.PIPE,
stderr=subprocess.STDOUT)
retcode, output = p.wait(), p.stdout.read().strip().decode('utf-8')
if retcode == 44: # password does not exist
raise PasswordNotFound()
elif retcode == 45: # password already exists
raise PasswordExists()
elif retcode > 0:
err = KeychainError('Unknown Keychain error : %s' % output)
err.retcode = retcode
raise err
return (retcode, output)
| [
"margheim@sas.upenn.edu"
] | margheim@sas.upenn.edu |
6ffa9e58676b1f6471c34d935594e1e7e506b321 | 3278b356a37bcfd689480f6a75b7890ef53f7821 | /文字型/No.22.py | c1ed893aaaef1252ff6bb0b58c0a462773de8221 | [] | no_license | kawasaki2254/Python_100problem_practice_problem | bb83fe3953f46178a0bb8870c315945bf3f1e18e | 7ee39e965e2b32cf52345635834529f337aaca8c | refs/heads/main | 2023-02-11T13:41:46.778199 | 2021-01-11T05:55:48 | 2021-01-11T05:55:48 | 326,548,979 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 395 | py | '''
問題２２．２つの文字列を入力して、重複する部分だけ
出力するプログラムを作成してください。
'''
word1 = input('１つ目の文字列を入力してください > ')
word2 = input('２つ目の文字列を入力してください > ')
r = ''
for i in word1:
if i in word2 and not i in r:
r += i
print(f'重複する文字列 : {r}')
| [
"kawasakitota2254@gmail.com"
] | kawasakitota2254@gmail.com |
2ae484c93d1a05fcf1465498bc32931f6f58f9be | 3135f95ab49c7ed9e6e93741748467cfd692f7d5 | /quad_pid.py | dff43de662d268fb89541dd99d0d1d22e516a9c2 | [] | no_license | Jaeyoung-Lim/mujocoquad | b674c45aa11a0ec7e5a8fcab2f03e534561cfc22 | ca4fb25fc0dd105bf7dd20114b54b82c0da49318 | refs/heads/master | 2020-04-18T22:08:12.949718 | 2019-01-26T16:38:55 | 2019-01-26T16:38:55 | 167,785,118 | 0 | 0 | null | 2019-01-27T08:05:48 | 2019-01-27T08:05:48 | null | UTF-8 | Python | false | false | 4,237 | py | import gym
import numpy as np
from mujocoquad_gym.envs.mujocoquad_force import MujocoQuadForceEnv
class Trajectory:
R = 0.5 # trajectory radius
w = 1.0 # trajectory angular speed (rad/s)
class CtrlParam:
# attitude
kpz = 2.
kpphi = 0.1
kptheta = 0.1
kppsi = 0.3
Kx_p = np.array([
[kpz, 0, 0, 0],
[0, kpphi, 0, 0],
[0, 0, kptheta, 0],
[0, 0, 0, kppsi],
])
kdz = 0.5
kdphi = 0.1
kdtheta = 0.1
kdpsi = 0.1
Kx_d = np.array([
[kdz, 0, 0, 0],
[0, kdphi, 0, 0],
[0, 0, kdtheta, 0],
[0, 0, 0, kdpsi],
])
kiz = 0.01
kiphi = 0.01
kitheta = 0.01
kipsi = 0.01
Kx_i = np.array([
[kiz, 0, 0, 0],
[0, kiphi, 0, 0],
[0, 0, kitheta, 0],
[0, 0, 0, kipsi],
])
# position control matrix
kpx = 0.6
kpy = 0.6
Ks_p = np.array([
[kpx, 0],
[0, kpy],
])
kdx = 0.2
kdy = 0.2
Ks_d = np.array([
[kdx, 0],
[0, kdy],
])
class MotorParam:
C = 0.1 # constant factor
L = 0.1 # moment arm (L_arm cos 45)
a = 0.25
b = 1 / (4*L)
c = 1 / (4*C)
C_R = np.array([
[a, b, -b, -c],
[a, -b, -b, c],
[a, -b, b, -c],
[a, b, b, c],
])
def main():
dt = 0.01
mass = 0.3
gravity = 9.81
ex = 0
es = 0
ex_int = 0
env = gym.make('MujocoQuadForce-v0')
# [x, y, z, q0, q1, q2, q3]
observation = env.reset()
for t in range(1000):
env.render()
#################################
# desired position state (x, y, z)
# circle trajectory on 1 m height
s_d = np.array([
Trajectory.R * np.cos(Trajectory.w * dt * t),
Trajectory.R * np.sin(Trajectory.w * dt * t),
1.0
])
################################
# quat -> rpy
quat = observation[3:]
rotmat_WB = np.array([
[1 - 2*(quat[2]**2 + quat[3]**2), 2*(quat[1]*quat[2] - quat[3]*quat[0]), 2*(quat[1]*quat[3] + quat[2]*quat[0])],
[2 * (quat[1]*quat[2] + quat[3]*quat[0]), 1 - 2*(quat[1]**2 + quat[3]**2), 2*(quat[2]*quat[3] - quat[1]*quat[0])],
[2 * (quat[1]*quat[3] - quat[2]*quat[0]), 2*(quat[2]*quat[3] + quat[1]*quat[0]), 1 - 2*(quat[1]**2 + quat[2]**2)],
])
roll = np.arctan2(2*(quat[0] * quat[1] + quat[2] * quat[3]), 1 - 2*(quat[1]**2 + quat[2]**2))
pitch = np.arcsin(2*(quat[0] * quat[2] - quat[3] * quat[1]))
yaw = np.arctan2(2*(quat[0] * quat[3] + quat[1] * quat[2]), 1 - 2*(quat[2]**2 + quat[3]**2))
################################
# state
# position
s = np.array([
observation[0],
observation[1],
])
# attitude
x = np.array([
observation[2],
roll,
pitch,
yaw,
])
################################
# error
# position
es_last = es
es = s_d[0:2] - s
es_dot = (es - es_last) / dt # differentiation
# position input
us = np.matmul(CtrlParam.Ks_p, es) \
+ np.matmul(CtrlParam.Ks_d, es_dot)
us = np.append(us, 0)
# attitude
rotmat_BW = np.linalg.inv(rotmat_WB)
x_d = np.array([
s_d[2], # +z
-np.matmul(rotmat_BW, us)[1], # -y -> roll,
np.matmul(rotmat_BW, us)[0], # +x -> pitch,
(Trajectory.w * dt * t + np.pi) % (2 * np.pi) - np.pi,
])
ex_last = ex
ex = x_d - x
ex_dot = (ex - ex_last) / dt # differentiation
ex_int += ex * dt # integration
# attitude input
u = np.matmul(CtrlParam.Kx_p, ex) \
+ np.matmul(CtrlParam.Kx_d, ex_dot) \
+ np.matmul(CtrlParam.Kx_i, ex_int)
u[0] += mass * gravity / (np.cos(pitch) * np.cos(roll))
# actuator input
# +,+
# +,-
# -,-
# -,+
F = np.matmul(MotorParam.C_R, u)
observation, reward, done, info = env.step(F)
if done:
break
if __name__ == "__main__":
main()
| [
"east0822@gmail.com"
] | east0822@gmail.com |
2e24e4d2a766d658e872865bd2ce68adc082c893 | 61734be18935dd5ecfd9103373188c6eb870673c | /shopping.py | 100f67643120cd2b2c8c5bddf130a291d52088dd | [] | no_license | bojone/analytical-classification | 751780f8aae21018be23440d2acaa6ba34554ba6 | e9333fde0eb76fcdc25482209e6b80bc8a21929b | refs/heads/main | 2023-06-24T22:25:33.036612 | 2021-07-29T07:24:00 | 2021-07-29T07:24:00 | 388,304,001 | 11 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,744 | py | #! -*- coding: utf-8 -*-
# 测试“全连接+Softmax”解析解的效果
# 博客：https://kexue.fm/archives/8578
import numpy as np
import pandas as pd
from bert4keras.tokenizers import Tokenizer
from bert4keras.models import build_transformer_model
from bert4keras.snippets import sequence_padding
from bert4keras.snippets import open
from bert4keras.optimizers import Adam
from keras.layers import *
from keras.models import Model
from tqdm import tqdm
num_classes = 10
maxlen = 128
# bert配置
config_path = '/root/kg/bert/chinese_roformer-sim-char-ft_L-12_H-768_A-12/bert_config.json'
checkpoint_path = '/root/kg/bert/chinese_roformer-sim-char-ft_L-12_H-768_A-12/bert_model.ckpt'
dict_path = '/root/kg/bert/chinese_roformer-sim-char-ft_L-12_H-768_A-12/vocab.txt'
# 建立分词器
tokenizer = Tokenizer(dict_path, do_lower_case=True) # 建立分词器
# 建立加载模型
encoder = build_transformer_model(
config_path, checkpoint_path, model='roformer', with_pool='linear'
)
def load_data(filename):
"""加载数据
单条格式：(文本, 标签id)
"""
data = pd.read_csv(filename).dropna()
labels = list(set(data['cat']))
global num_classes
num_classes = len(labels)
D = []
for text, label in zip(data['review'], data['cat']):
D.append((text, labels.index(label)))
return D
# 加载数据集
data = load_data('/root/online_shopping_10_cats.csv')
idxs = np.random.permutation(len(data))
train_data = [data[i] for i in idxs if i % 4 != 0]
valid_data = [data[i] for i in idxs if i % 4 == 0]
def convert(data):
"""数据向量化
"""
X, S, Y = [], [], []
for t, l in tqdm(data):
x, s = tokenizer.encode(t, maxlen=maxlen)
X.append(x)
S.append(s)
Y.append([l])
X = sequence_padding(X)
S = sequence_padding(S)
X = encoder.predict([X, S], verbose=True)
Y = np.array(Y)
return X, Y
train_x, train_y = convert(train_data)
valid_x, valid_y = convert(valid_data)
def compute_kernel_bias(vecs):
"""计算kernel和bias
vecs.shape = [num_samples, embedding_size]，
最后的变换：y = (x + bias).dot(kernel)
"""
mu = vecs.mean(axis=0, keepdims=True)
cov = np.cov(vecs.T)
u, s, vh = np.linalg.svd(cov)
W = u.dot(np.diag(1 / np.sqrt(s)))
return W, -mu
# 数据白化
kernel, bias = compute_kernel_bias(train_x)
train_x = (train_x + bias).dot(kernel)
valid_x = (valid_x + bias).dot(kernel)
# ============== 通过梯度下降求解 ==============
x = Input(shape=(train_x.shape[1],))
y = Dense(num_classes, activation='softmax')(x)
model = Model(x, y)
model.compile(
loss='sparse_categorical_crossentropy',
optimizer=Adam(1e-3),
metrics=['accuracy']
)
model.summary()
model.fit(
train_x,
train_y,
epochs=10,
batch_size=32,
validation_data=(valid_x, valid_y)
)
train_y_pred = model.predict(train_x, verbose=True)
valid_y_pred = model.predict(valid_x, verbose=True)
train_acc = np.mean(train_y[:, 0] == train_y_pred.argmax(1))
valid_acc = np.mean(valid_y[:, 0] == valid_y_pred.argmax(1))
print(train_acc, valid_acc)
# ============== 通过解析解求解 ==============
ps = np.array([(train_y == i).mean() for i in range(num_classes)])
mus = [train_x[train_y[:, 0] == i].mean(axis=0) for i in range(num_classes)]
cov = np.eye(len(mus[0])) - np.einsum('nd,nc,n->dc', mus, mus, ps)
cov_inv = np.linalg.inv(cov)
w = np.einsum('nd,dc->cn', mus, cov_inv)
b = np.log(ps) - np.einsum('nd,dc,nc->n', mus, cov_inv, mus) / 2
train_y_pred = train_x.dot(w) + b
valid_y_pred = valid_x.dot(w) + b
train_acc = np.mean(train_y[:, 0] == train_y_pred.argmax(1))
valid_acc = np.mean(valid_y[:, 0] == valid_y_pred.argmax(1))
print(train_acc, valid_acc)
| [
"noreply@github.com"
] | noreply@github.com |
2e69bb3c653c7a6fe8fb3e43c5da74f7ad961e0b | 0cbd649f9a2a31c0ff50b8a13b40bba17e58640d | /lesson6_step5.py | c085962592591136da570dfb53ce5fa9e03821f6 | [] | no_license | Senkool/selenium_course | 5b79d76fb9a50a64410668337a24f278ba9c05eb | a5e4dc098b8f1507f0a2c0f9643c3c56ccfd6979 | refs/heads/master | 2022-06-24T15:36:27.408102 | 2020-05-10T16:25:19 | 2020-05-10T16:25:19 | 262,828,053 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 406 | py | from selenium import webdriver
import time
try:
browser = webdriver.Chrome()
browser.get("http://suninjuly.github.io/huge_form.html")
elements = browser.find_elements_by_css_selector("input")
for element in elements:
element.send_keys("ответ")
button = browser.find_element_by_css_selector("button.btn")
button.click()
finally:
time.sleep(30)
browser.quit()
| [
"12denis1998@gmail.com"
] | 12denis1998@gmail.com |
393ef0ee8e6ca3b958d075bdb3bbd1e68260b9b2 | 41c660d5cd7b8dcc1a0c0abbc81b5c3e7e80fbd3 | /raspy/handle_motion.py | d9c9a0df603ab4855b034242677008dcb4559284 | [] | no_license | rconjaerts/nrt | 8bb1406a12af5bb60a54e1c374e6e8ba1d78ad1a | 016f723c944f095876ea96c739882b37bec98d3d | refs/heads/master | 2020-12-26T18:03:00.274341 | 2014-07-01T14:15:22 | 2014-07-01T14:15:22 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,935 | py | #!/usr/bin/python
from __future__ import division
from PIL import Image
import numpy as np
import sys
import requests
import json
import time
import blinker
def handle_motion(img_path):
print "handling motion"
# We load it and calculate a single scalar value for the motion ('activity')
# in this image
img = np.asarray(Image.open(img_path).convert('L'))
img = 1 * (img == 25)
m,n = img.shape
motion_pixels = img.sum()
total_pixels = m*n
motion_value = motion_pixels / total_pixels * 100
# see if we should do some shit with the baby
try:
amplitude_value = float(open('/home/pi/last_amplitude').readline())
except Error:
amplitude_value = 0
if amplitude_value > 0.20 and motion_value > 0.20:
print "BABY IS AWAKE."
# Send the event to our server
url = 'http://192.168.137.1:8080/BigSisterReboot/webresources/entities.event'
payload = {'timestamp': int(time.time()),
'value': motion_value,
'accountId': 1,
'typeId': 2,
}
headers = {'content-type': 'application/json'}
r = requests.post(url, data=json.dumps(payload), headers=headers)
def handle_snapshot(img_path):
pass
# Send the raw image to our server
# url = 'http://192.168.137.1:8080/BigSister/webresources/entities.eventvideo'
# payload = {'timestamp': int(time.time()),
# 'filename': img_path,
# 'value': value,
# 'accountId': 1,}
# headers = {'content-type': 'application/json'}
#
# r = requests.post(url, data=json.dumps(payload), headers=headers)
# Our first arguement passed is an image file name
img_path = str(sys.argv[1]).strip()
# motion pictures end with m.jpg, so here we differentiate between motion pics and snapshots
if img_path[-5:] == 'm.jpg':
handle_motion(img_path)
else:
handle_snapshot(img_path)
| [
"tomjaspers@gmail.com"
] | tomjaspers@gmail.com |
43fa9cc363b25fbbb658601647398ac8dbfe41aa | a25b26b3b27b59325915c10dfafd607faae4ed01 | /pickfrombothsides.py | 879435386092602b6015b9cf8eab00d3d4514243 | [] | no_license | helplearnhome/Coding-Interview-in-Python | 3e3d9f42b993b9ea8e86e25d8a8e36c1610c45f2 | 52a76689a5808a89ebb8399bf3e6d4922c4c190b | refs/heads/master | 2023-07-17T06:30:09.207235 | 2021-09-08T03:28:33 | 2021-09-08T03:28:33 | 397,350,111 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,823 | py | # # Recursive
def func(A,B,i,j,sum):
if B == 0:
# print(sum)
return sum
return max(func(A,B-1,i+1,j,sum+A[i]),func(A,B-1,i,j-1,sum+A[j]))
class Solution:
# @param A : list of integers
# @param B : integer
# @return an integer
def solve(self, A, B):
# print(B)
return func(A,B,0,-1,0)
# x = Solution()
# print(x.solve([1,9,8,1,1,7],3))
#Wrong way
#Iterative
# def func(A,B,i,j,sum):
# while(B>0 and i<=j):
# if (A[i] > A[j]):
# sum+=A[i]
# i+=1
# else:
# sum+=A[j]
# j-=1
# B-=1
# return sum
# class Solution:
# # @param A : list of integers
# # @param B : integer
# # @return an integer
# def solve(self, A, B):
# # print(B)
# return func(A,B,0,len(A)-1,0)
# x = Solution()
# print(x.solve([1,9,8,1,1,7],3))
#iterative
class Solution:
# @param A : list of integers
# @param B : integer
# @return an integer
def solve(self, A, B):
sum=0
maxi=0
for i in range(B):
sum+=A[i]
maxi=sum
for j in range(1,B+1):
sum-=A[B-j]
sum+=A[-j]
if maxi < sum:
maxi=sum
return maxi
x = Solution()
print(x.solve([0,0,0,1,1,7],3))
#pavana
# int Solution::solve(vector<int> &A, int B) {
# vector<int> dp1(B,0),dp2(B,0);
# int n=A.size();
# dp1[0]=A[0];
# for(int i=1;i<B;i++)
# dp1[i]=dp1[i-1]+A[i];
# dp2[0]=A[n-1];
# for(int i=1;i<B;i++)
# dp2[i]=dp2[i-1]+A[n-1-i];
# int ans=max(dp1[B-1],dp2[B-1]);
# for(int i=0;i<B-1;i++)
# ans=max(ans,dp1[i]+dp2[B-2-i]);
# return ans;
# } | [
"noreply@github.com"
] | noreply@github.com |
93c4453f26512207811cdba404053b9a07b2e9c1 | b68887f55cfcd0225d732acfbfcc7f3724e49d5d | /pages/factories.py | a59431ddc5e91da1966fb1ba58c8d6ad49dcbfb0 | [
"MIT"
] | permissive | rds0751/nhsuk-content-store | 0ac7eb06f85cc97cd57e58a3f24e19db9991a8a2 | 7bd6a386e3583779ddba2347a4b3a80fdf75b368 | refs/heads/master | 2020-04-19T08:53:54.273378 | 2019-01-29T05:08:18 | 2019-01-29T05:08:18 | 168,092,530 | 0 | 0 | null | 2019-01-29T05:05:33 | 2019-01-29T05:05:33 | null | UTF-8 | Python | false | false | 1,515 | py | import factory
from home.factories import HomePageFactory, ParentBasedFactory
from . import models
class ConditionsPageFactory(ParentBasedFactory, factory.django.DjangoModelFactory):
title = 'Conditions'
slug = 'conditions'
path = '000100010002'
depth = 3
_ParentFactory = HomePageFactory
_unique = True
class Meta:
model = models.FolderPage
class ConditionPageFactory(ParentBasedFactory, factory.django.DjangoModelFactory):
path = factory.Sequence(lambda n: '000100010002%04d' % (n + 1))
depth = 4
_ParentFactory = ConditionsPageFactory
_unique = False
class Meta:
model = models.EditorialPage
class SymptomsPageFactory(ParentBasedFactory, factory.django.DjangoModelFactory):
title = 'Symptoms'
slug = 'symptoms'
path = '000100010001'
depth = 3
_ParentFactory = HomePageFactory
_unique = True
class Meta:
model = models.FolderPage
class SymptomPageFactory(ParentBasedFactory, factory.django.DjangoModelFactory):
path = factory.Sequence(lambda n: '000100010001%04d' % (n + 1))
depth = 4
_ParentFactory = SymptomsPageFactory
_unique = False
class Meta:
model = models.EditorialPage
class ConditionFolderPageFactory(ParentBasedFactory, factory.django.DjangoModelFactory):
path = factory.Sequence(lambda n: '000100010002%04d' % (n + 1))
depth = 4
_ParentFactory = ConditionsPageFactory
_unique = False
class Meta:
model = models.FolderPage
| [
"marcofucci@gmail.com"
] | marcofucci@gmail.com |
1ebd1dd0aa7d1f4a4140c09684866a9a7eccdcb8 | d685a23ff883f216f5ab8ea6ba257eb660e6a931 | /laboratorios/lab01/codigo/rectangle.py | c50f4713939745bab2bd9d972bd8ca6c78d7b997 | [] | no_license | varisti7/ST0245-001 | 2abde80a13d6139018e6e7ac9b99fd476f572c98 | 3582eb0a06f22af496d63458db55d8d47b797c79 | refs/heads/master | 2023-01-12T20:29:19.816894 | 2020-11-17T21:27:02 | 2020-11-17T21:27:02 | 283,341,706 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 1,299 | py | import time, string, random
import matplotlib.pyplot as plt
def rectangle(size2n):
"""
This agorithm recieves an integer as the number of rectangles of 2xn and calculates of how
many ways it could be filled with 2x1 rectangles.
"""
if size2n == 1 or size2n == 2: # C1
return size2n
else:
return rectangle(size2n - 1) + rectangle(size2n - 2) # T(n-1) + T(n-2)
"""
In the worst case the asynthotic complexity would be:
T(n) = C1 + T(n-1) + T(n-2) => solved by "Laboratory practice No. 1: Recursion" point 4.4.1
O(2^n)
"""
def plotTimes():
"""
This function plot's the rectangle algorithm. The x label as the number (from 20-40) and the y label
as the time required to solve it.
"""
timeArray = []
lengthArray = []
for x in range(20,40):
t1 = time.time()
rectangle(x)
tt = time.time() - t1
timeArray.append(tt)
print(tt)
lengthArray.append(x)
plt.plot(lengthArray, timeArray, 'rs')
plt.show()
def main():
plotTimes()
main()
"""
6,20E-03
4,55E-03
1,29E-02
2,36E-02
0,04935503
0,079976082
0,100703001
0,176604033
0,24488306
0,347311974
0,278718948
0,402431965
0,634913206
1,017865181
1,632277012
2,63162899
4,297087908
6,946293831
11,17777205
18,06480503
""" | [
"varisti6@gmail.com"
] | varisti6@gmail.com |
47f0abfaceb11e660d4f305e745db7fe9fee819f | da84fa23cc4cf2e81e50892085ac162508bff155 | /nestris_ocr/capturing/linux/linux_mgr.py | 6381209b8dd85f1880aca2b7eb9cbc653ec9f0cd | [] | no_license | alex-ong/NESTrisOCR | 83ddaba55b100f0ee20e924731459e547e321887 | 488beeb30e596ccd0548152e241e1c6f772e717b | refs/heads/master | 2023-01-10T08:02:41.702538 | 2021-07-07T06:33:39 | 2021-07-07T06:33:39 | 169,196,192 | 25 | 8 | null | 2022-12-27T15:37:40 | 2019-02-05T05:44:34 | Python | UTF-8 | Python | false | false | 1,202 | py | import Xlib
import Xlib.display
from Xlib import X
class WindowMgr:
"""Encapsulates some calls for window management"""
def __init__(self, hwnd=None):
self.handle = hwnd
def checkWindow(self, hwnd):
"""checks if a window still exists"""
return hwnd
def getWindows(self):
"""
Return a list of tuples (handler, window name) for each real window.
"""
windows = []
def getWindowHierarchy(window, windows):
children = window.query_tree().children
for w in children:
try:
w.get_image(0, 0, 1, 1, X.ZPixmap, 0xFFFFFFFF)
windows.append(
(
w.id,
w.get_wm_class()[1] if w.get_wm_class() is not None else "",
)
)
except Xlib.error.BadMatch:
pass
finally:
windows = getWindowHierarchy(w, windows)
return windows
root = Xlib.display.Display().screen().root
windows = getWindowHierarchy(root, windows)
return windows
| [
"the.onga@gmail.com"
] | the.onga@gmail.com |
10252106e1b1114e8e4adf56f12d670ac5aee1e0 | 397c9e2743c41cf591692c4fc37f43a9070119bd | /build/env/lib/python2.7/site-packages/SQLAlchemy-1.2.0b3-py2.7-linux-x86_64.egg/sqlalchemy/cutils.py | a62e8adc17fa043f78d6b8b32d3c703fd2682408 | [
"Apache-2.0"
] | permissive | bopopescu/myhue | cf41238c782d12b3a1a0ee9ef70196359bb67894 | 5f566970a5a1fa5af9f01832c9e9808c47634bc7 | refs/heads/master | 2022-11-18T05:37:24.467150 | 2019-11-23T16:16:22 | 2019-11-23T16:16:22 | 282,390,507 | 0 | 0 | Apache-2.0 | 2020-07-25T07:03:40 | 2020-07-25T07:03:39 | null | UTF-8 | Python | false | false | 282 | py | def __bootstrap__():
global __bootstrap__, __loader__, __file__
import sys, pkg_resources, imp
__file__ = pkg_resources.resource_filename(__name__, 'cutils.so')
__loader__ = None; del __bootstrap__, __loader__
imp.load_dynamic(__name__,__file__)
__bootstrap__()
| [
"352322399@qq.com"
] | 352322399@qq.com |
e0cf8c5298a8ee4e8a3b21eb3b1fe65504c3047e | 204ec78fcebcea9e1e1da4905cf3fad0a514b01f | /test/unit/test_timeout.py | 4990b87aad1b2d40888f75acc3481c349d3eb4e0 | [
"Apache-2.0"
] | permissive | ARMmbed/pyOCD | 659340bf8753aa8e15a72890b8bea64dff2c2f42 | d4cdcf7e532cae17caad866839287bbe1e0d952b | refs/heads/master | 2023-05-31T13:45:15.797588 | 2020-10-12T13:55:47 | 2020-10-12T13:55:47 | 190,203,829 | 3 | 1 | Apache-2.0 | 2019-07-05T11:05:40 | 2019-06-04T13:09:56 | Python | UTF-8 | Python | false | false | 1,942 | py | # pyOCD debugger
# Copyright (c) 2017-2019 Arm Limited
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from time import (time, sleep)
import pytest
from pyocd.utility.timeout import Timeout
class TestTimeout:
def test_no_timeout(self):
with Timeout(0.05) as to:
cnt = 0
while to.check():
sleep(0.01)
cnt += 1
if cnt == 4:
break
else:
assert False
assert not to.did_time_out
def test_timeout_a(self):
s = time()
with Timeout(0.05) as to:
while to.check():
sleep(0.01)
assert to.did_time_out
assert (time() - s) >= 0.05
def test_timeout_b(self):
timedout = False
s = time()
with Timeout(0.05) as to:
cnt = 0
while cnt < 10:
if to.did_time_out:
timedout = True
sleep(0.02)
cnt += 1
assert timedout
assert to.did_time_out
assert (time() - s) >= 0.05
def test_timeout_c(self):
timedout = False
with Timeout(0.05) as to:
cnt = 0
while cnt < 10:
if to.did_time_out:
timedout = True
cnt += 1
assert not timedout
assert not to.did_time_out
| [
"flit@me.com"
] | flit@me.com |
4e36d68ce3ba6c25adc4cbac052979ce95b8b4c2 | 4494d201fef442f6546919acd685561ba2bd0ec3 | /lookup/views.py | 0d074c1c3cde4853656fa056e992d3cdf480a210 | [] | no_license | santoshikaruturi/djangoweather | de1d8bef593f6bb32f342f2867e345f67dd63c32 | 4fb465ff4167a99fb0dfea92212f055c66568994 | refs/heads/master | 2020-12-10T08:55:36.893164 | 2020-01-13T08:49:58 | 2020-01-13T08:49:58 | 233,549,908 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 208 | py | #This is my views.py file
from django.shortcuts import render
# Create your views here.
def home(request):
return render(request,'home.html',{})
def about(request):
return render(request,'about.html',{}) | [
"karuturisantoshi9@gmail.com"
] | karuturisantoshi9@gmail.com |
49da684394e0562e287537b0ace76cdd6969645c | ec649dc247e5229f78c2bcf51fdef1c57f3cdbff | /OCR/tesseract-invoice.py | 0a8f8a6159e2642f490c1a13260c8f55f28faaf0 | [] | no_license | dainv1989/machine-learning | 0f1686a9bf921bfcf665a786c63ec68b189942a0 | e44b14041f577ebe5d5ce785af45e4226e0d2756 | refs/heads/master | 2021-07-11T20:39:39.423568 | 2020-03-22T23:55:10 | 2020-03-22T23:55:10 | 93,155,384 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,415 | py | import cv2
import re
import pytesseract as pts
from pytesseract import Output
def show_textboxes(image):
d = pts.image_to_data(image, output_type=Output.DICT)
#print(d.keys())
n_boxes = len(d['text'])
for i in range(n_boxes):
if int(d['conf'][i]) > 60:
(x, y, w, h) = (d['left'][i], d['top'][i], d['width'][i], d['height'][i])
img = cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2)
return image
#end show_textboxes
def find_pattern(image, data_pattern):
d = pts.image_to_data(image, output_type=Output.DICT)
keys = list(d.keys())
n_boxes = len(d['text'])
for i in range(n_boxes):
if int(d['conf'][i]) > 60:
if re.match(data_pattern, d['text'][i]):
(x, y, w, h) = (d['left'][i], d['top'][i], d['width'][i], d['height'][i])
image = cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2)
return image
#end find_pattern
img = cv2.imread('invoice.jpg')
#text = pts.image_to_string(img)
#print(text)
date_pattern = '^(0[1-9]|[12][0-9]|3[01])/(0[1-9]|1[012])/(19|20)\d\d$'
img_datebox = find_pattern(img, date_pattern)
#cv2.imshow('img', img_datebox)
email_pattern = '^[a-z0-9]+@[a-z0-9]+\.[a-z]+$'
img_emailbox = find_pattern(img_datebox, email_pattern)
cv2.imshow('img', img_emailbox)
#img_textboxes = show_textboxes(img)
#cv2.imshow('img', img_textboxes)
cv2.waitKey(0)
| [
"dainv1989@hotmail.com"
] | dainv1989@hotmail.com |
6a3039fdc7a6b0b344c3bf5b42fdec14cefec348 | d76ed914106e5ec6c5f1a64b843fb27e43256893 | /yugioh_cardDB/admin.py | 3724c94ca4b77cb44dcc9bc0188d8d6b1de00014 | [] | no_license | ss6987/yugioh_DB | 7de17227bbeecfc295eef0bd02bb7583c4c30466 | 352f54f1302d80879c67f9cd05aae01818f4ee7a | refs/heads/master | 2020-04-07T19:19:15.315196 | 2019-04-10T00:36:32 | 2019-04-10T00:36:32 | 157,318,534 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 821 | py | from django.contrib import admin
from .models import *
class PackAdmin(admin.ModelAdmin):
readonly_fields = ["recording_card"]
class ShopURLAdmin(admin.ModelAdmin):
readonly_fields = ["card"]
class PriceAdmin(admin.ModelAdmin):
readonly_fields = ["shop_url"]
admin.site.register(Card)
admin.site.register(Monster)
admin.site.register(PendulumMonster)
admin.site.register(LinkMonster)
admin.site.register(CardClassification)
admin.site.register(Attribute)
admin.site.register(Type)
admin.site.register(LinkMarker)
admin.site.register(CardId)
admin.site.register(Pack, PackAdmin)
admin.site.register(PackClassification)
admin.site.register(PackOfficialName)
admin.site.register(SearchPage)
admin.site.register(ShopURL, ShopURLAdmin)
admin.site.register(PriceLog, PriceAdmin)
admin.site.register(Rarity)
| [
"angel.blossom.vivid@gmail.com"
] | angel.blossom.vivid@gmail.com |
7222be1cddcf38ef35b6da54356de01d6646981a | fab3523d77e3641a7239818591a16a4ca29ba8c3 | /pymanetsim/plot_plane.py | ceb365f916e8793a68f3d054cfd6821437a6d5da | [] | no_license | joninvski/pymanetsim | c26cbe2256add2fefdf3097264575ca9fe7be3ce | c19e8d2324dc5325a2ba31aa692fc674c658725e | refs/heads/master | 2016-09-06T15:15:18.235956 | 2014-10-07T14:23:24 | 2014-10-07T14:23:24 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 721 | py | import pdb
import numpy as np
import matplotlib.cm as cm
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
def plot_plane(plane, all_nodes, name):
x = [0]*plane.x_size
y = [0]*plane.y_size
X = np.meshgrid(x, y)
#For each node
for node in all_nodes.values():
#Get its heat value
heat = 100 #TODO - This is fake
#Put that value on the heat map
x = node.location.x
y = node.location.y
X[0][x][y] = heat
plt.imshow(X[0], interpolation='nearest', origin='lower', \
extent=[0, plane.x_size, 0, plane.y_size])
plt.savefig('/tmp/' + str(name))
# plt.show()
# plt.savefig('../results/images/plots/' + str(name))
| [
"trindade.joao@gmail.com"
] | trindade.joao@gmail.com |
14b05aaebd43d60f8b353474ac5f6a16ec15f2f2 | 607d5300e1c55cd194b581174f13965f73971eb6 | /oss/testdata/python_examples/get_object.py | 588f638b58d92c3c43dfbe1974e3bf2d0eae0d2b | [
"Apache-2.0"
] | permissive | aliyun-beta/aliyun-oss-go-sdk | a577a45c3ec445c0a8a2f73538077943f0bb537e | b9a019776ad68c252acb92a67a09be59162de4ab | refs/heads/master | 2021-01-17T14:37:13.127610 | 2015-12-15T08:35:49 | 2015-12-15T08:35:49 | 46,700,470 | 3 | 1 | null | null | null | null | UTF-8 | Python | false | false | 263 | py | from oss.oss_api import *
from oss import oss_xml_handler
endpoint="hostlocal:9999"
endpoint="oss-cn-hangzhou.aliyuncs.com:9999"
id, secret = "ayahghai0juiSie", "quitie*ph3Lah{F"
oss = OssAPI(endpoint, id, secret)
res=oss.get_object("bucket-name","object/name")
| [
"w@h12.me"
] | w@h12.me |
66a53d2b71a6f7420dc7a93f85b662fb08440da4 | f6a24e544fe48cb13fa38fcde11ce9b57d119eba | /api.py | 7e4075258107e12abd359e2ec3feba410554f86c | [
"MIT",
"BSD-3-Clause",
"Apache-2.0"
] | permissive | postsai/postsai | b8afeb44d87ff16cd0526ba593f70446751affc6 | c2b8363c34ff28a8c54b04548ff1c72c8a98e2c3 | refs/heads/master | 2023-08-16T16:50:30.671405 | 2023-08-10T15:08:17 | 2023-08-10T15:08:17 | 52,112,371 | 5 | 5 | NOASSERTION | 2023-09-14T14:19:35 | 2016-02-19T19:49:22 | Python | UTF-8 | Python | false | false | 1,985 | py | #! /usr/bin/python3
# The MIT License (MIT)
# Copyright (c) 2016-2021 Postsai
#
# Permission is hereby granted, free of charge, to any person obtaining a
# copy of this software and associated documentation files (the "Software"),
# to deal in the Software without restriction, including without limitation
# the rights to use, copy, modify, merge, publish, distribute, sublicense,
# and/or sell copies of the Software, and to permit persons to whom the
# Software is furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included
# in all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
# OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
# THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
# DEALINGS IN THE SOFTWARE.
import cgi
import json
import sys
from os import environ
import config
from backend.cvs import PostsaiCommitViewer
from backend.query import Postsai
from backend.importer import PostsaiImporter
if __name__ == "__main__":
if "REQUEST_METHOD" in environ and environ['REQUEST_METHOD'] == "POST":
data = sys.stdin.read()
parsed = None
try:
parsed = json.loads(data, strict=False)
except UnicodeDecodeError:
data = data.decode("iso-8859-15").encode("utf-8")
parsed = json.loads(data, strict=False)
PostsaiImporter(vars(config), parsed).import_from_webhook()
else:
form = cgi.FieldStorage()
if form.getfirst("method", "") == "commit":
PostsaiCommitViewer(vars(config)).process()
else:
Postsai(vars(config)).process()
| [
"nhnb@users.sourceforge.net"
] | nhnb@users.sourceforge.net |
837640dec4290cdc6c2b69db42c87b60beb2a646 | 327a6d74d22fb06d76f5da814452e76aa8999692 | /stanCode_projects/Photoshop/green_screen.py | ff846ff20b3d35e8ea5a12d8952923732dfd0a2b | [
"MIT"
] | permissive | siyuban/stanCode | 6a5c2114a3bc949c1d6e5a70b987dcda74161874 | 5cca179a7542abdf1fe3a9e1da256945241249cc | refs/heads/main | 2023-02-11T16:20:08.707138 | 2021-01-09T15:44:55 | 2021-01-09T15:44:55 | 324,043,306 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,464 | py | """
File: green_screen.py
Name:萬思妤
-------------------------------
This file creates a new image that uses
MillenniumFalcon.png as background and
replace the green pixels in "ReyGreenScreen.png".
"""
from simpleimage import SimpleImage
def combine(background_img, figure_img):
"""
:param background_img: SimpleImage, the background image.
:param figure_img: SimpleImage, green screen figure image
:return: SimpleImage, figure image with the green screen pixels replaced by pixels of background.
"""
for x in range(background_img.width):
for y in range(background_img.height):
figure_pixel = figure_img.get_pixel(x, y)
bigger = max(figure_pixel.red, figure_pixel.blue)
if figure_pixel.green > bigger*2:
background_img_pixel = background_img.get_pixel(x, y)
figure_pixel.red = background_img_pixel.red
figure_pixel.blue = background_img_pixel.blue
figure_pixel.green = background_img_pixel.green
return figure_img
def main():
"""
Create a new image that uses MillenniumFalcon.png as background and replace the green
pixels in "ReyGreenScreen.png".
"""
space_ship = SimpleImage("images/MillenniumFalcon.png")
figure = SimpleImage("images/ReyGreenScreen.png")
space_ship.make_as_big_as(figure)
result = combine(space_ship, figure)
result.show()
if __name__ == '__main__':
main()
| [
"noreply@github.com"
] | noreply@github.com |
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