Reset23/the-stack-v2-new-python · Datasets at Hugging Face

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/cli/src/ipsecmanager.py

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zhaog918/coprhd-controller

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#!/usr/bin/env python # Copyright (c) 2015 EMC Corporation # All Rights Reserved # import json import common import sys from common import SOSError from common import TableGenerator class IPsecManager(object): URI_SERVICES_BASE = '' URI_IPSEC = URI_SERVICES_BASE + '/ipsec' def __init__(self, ipAddr, port): ''' Constructor: takes IP address and port of the ViPR instance. These are needed to make http requests for REST API ''' self.__ipAddr = ipAddr self.__port = port def rotate_ipsec_key(self): (s, h) = common.service_json_request(self.__ipAddr, self.__port, "POST", IPsecManager.URI_IPSEC, None) return s def get_ipsec_status(self, xml=False): if(xml == False): (s, h) = common.service_json_request(self.__ipAddr, self.__port, "GET", IPsecManager.URI_IPSEC, None) return common.json_decode(s) else: (s, h) = common.service_json_request(self.__ipAddr, self.__port, "GET", IPsecManager.URI_IPSEC, None, None, xml) return s def rotate_ipsec_key_parser(subcommand_parsers, common_parser): # add command parser rotate_ipsec_key_parser = subcommand_parsers.add_parser('rotate-key', description='ViPR IPsec key rotation CLI usage', parents=[common_parser], conflict_handler='resolve', help='Rotates or generates the IPsec keys.') rotate_ipsec_key_parser.set_defaults(func=rotate_ipsec_key) def rotate_ipsec_key(args): try: res = IPsecManager(args.ip, args.port).rotate_ipsec_key() if(not res or res == ''): print 'Failed to rotate the IPsec key. Reason : ' + res else: print 'Successfully rotated the IPsec key. New IPsec configuration version is ' + res except SOSError as e: common.format_err_msg_and_raise("rotate", "IPsec key", e.err_text, e.err_code) def get_ipsec_status_parser(subcommand_parsers, common_parser): # add command parser ipsec_status_parser = subcommand_parsers.add_parser('status', description='ViPR IPsec status CLI usage', parents=[common_parser], conflict_handler='resolve', help='Gets the IPsec status and current configuration version.') ipsec_status_parser.add_argument('-xml', dest='xml', action='store_true', help='XML response') ipsec_status_parser.set_defaults(func=get_ipsec_status) def get_ipsec_status(args): try: res = IPsecManager(args.ip, args.port).get_ipsec_status(args.xml) if(not res or res == ''): print 'Failed to get the IPsec status. Reason : ' + res else: if(args.xml == True): return common.format_xml(res) else: return common.format_json_object(res) except SOSError as e: common.format_err_msg_and_raise("status", "IPsec", e.err_text, e.err_code) def ipsec_parser(parent_subparser, common_parser): parser = parent_subparser.add_parser('ipsec', description='ViPR IPsec CLI usage', parents=[common_parser], conflict_handler='resolve', help='Operations on IPsec') subcommand_parsers = parser.add_subparsers(help='Use one of sub-commands') # rotate IPsec key command parser rotate_ipsec_key_parser(subcommand_parsers, common_parser) # get IPsec status command parser get_ipsec_status_parser(subcommand_parsers, common_parser)

[ "Eswaramoorthy.Saminathan@emc.com" ]

Eswaramoorthy.Saminathan@emc.com

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/pages/base_page.py

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bijiaha0/python-learning

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2020-12-21T05:35:09.506356

2020-03-26T12:50:27

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from config import basic_settings __author__ = "zhou" __date__ = "2019-06-01 22:09" from selenium.webdriver.support import expected_conditions as EC from selenium.webdriver.support.wait import WebDriverWait class BasePage(object): def __init__(self, driver, url): self._driver = driver self._url = url def open(self): self._driver.get(url=self._url) return self._driver def find_element(self, *locator, element=None, timeout=None, wait_type="visibility"): if element is not None: return self._init_wait(timeout).until(EC.visibility_of(element.find_element(*locator))) if wait_type == "visibility": return self._init_wait(timeout).until(EC.visibility_of_element_located(locator=locator)) else: return self._init_wait(timeout).until(EC.presence_of_element_located(locator=locator)) def send_keys(self, web_element, keys): web_element.clear() web_element.send_keys(keys) def _init_wait(self, timeout): if timeout is None: return WebDriverWait(driver=self._driver, timeout=basic_settings.UI_WAIT_TIME) else: return WebDriverWait(driver=self._driver, timeout=timeout)

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bijh@tsingyun.net

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/PaleonT/PythonFGTS/Nový priečinok (2)/Nový priečinok/Tkinter/ERRR.py

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ShardBytes/Evolutions

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refs/heads/master

2021-06-04T22:32:49.034242

2020-03-12T12:59:53

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import random import tkinter x = random.randint(10,500) y = random.randint(10,500) root = tkinter.Tk() canvas = tkinter.Canvas(root, width = 800, height = 800) canvas.pack() def troj(width,height, startPointX,startPointY,color): canvas.create_line(startPointX,startPointY,startPointX+width,startPointY, fill = color) canvas.create_line(startPointX,startPointY,width/2,startPointY-height, fill = color) canvas.create_line(width/2,startPointY-height,startPointX + width,startPointY, fill = color) while 1 == 1: troj(x,y,10,700,"red") root.mainloop()

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/main_pl.py

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Naagar/Fine_Grained_Classification-FGC-

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refs/heads/main

2023-04-22T08:26:50.491928

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import pandas as pd import numpy as np import torch import torch.nn as nn import torch.nn.functional as F import torchvision import torchvision.transforms as transforms import torchvision.models as models import pytorch_lightning as pl from pytorch_lightning import Trainer from pytorch_lightning.metrics.functional import accuracy from torch.utils.data import Dataset, DataLoader from torchvision.datasets import ImageFolder from torch.utils.data import DataLoader, random_split from pytorch_lightning.loggers import TensorBoardLogger ##--- Hyper parameters ---## num_classes = 258 learning_rate = 0.001 batch_size = 256 num_epochs = 600 # tb_logger = pl_loggers.TensorBoardLogger('logs/') logger = TensorBoardLogger("tb_logs", name="my_model") ##--- dataset preprocess ---## data_transforms = transforms.Compose( [transforms.RandomResizedCrop(128), transforms.RandomHorizontalFlip(), transforms.ToTensor(), transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])]) ##--- dataset paths ---## data_dir = 'nut_snacks/dataset/' dataset = ImageFolder(data_dir, transform=data_transforms) print(len(dataset)) train_data, val_data = random_split(dataset, [10000, 2607]) print(len(train_data)) print(len(val_data)) ##----- Selecting model for training -----## vgg16 = models.vgg16() resnet18 = models.resnet18() resnet50 = models.resnet50() # model = vgg16 model = resnet50 # model = resnet34 class Lit_NN(pl.LightningModule): def __init__(self, num_classes, model): super(Lit_NN, self).__init__() self.resnet50 = model def forward(self, x): out = self.resnet50(x) return out def training_step(self, batch, batch_idx): images, labels = batch # images = images.reshape(-1, 3*128*128) # Forward Pass outputs = self(images) loss = F.cross_entropy(outputs, labels) # acc_i = self.loss(outputs, labels) acc = accuracy(outputs, labels) pbar = {'train_acc': acc} tensorboard_logs = {'train_loss': loss, 'train_acc': pbar} return {'loss': loss, 'log': tensorboard_logs, 'progress_bar': pbar} def configure_optimizers(self): return torch.optim.Adam(model.parameters(), lr=learning_rate) def train_dataloader(self): train_dataset = train_data#seeds_dataset(train_txt_path,train_img_dir) train_loader = DataLoader(train_dataset, batch_size=batch_size, num_workers=4) return train_loader def val_dataloader(self): test_dataset = val_data #seeds_dataset(test_text_path,test_img_dir) val_loader = DataLoader(test_dataset, batch_size=batch_size, num_workers=4) return val_loader def training_step(self, batch, batch_idx): images, labels = batch outputs = self(images) train_loss = F.cross_entropy(outputs, labels) train_acc = accuracy(outputs, labels) tensorboard = self.logger.experiment self.log('train_acc',train_acc, 'train_loss', train_loss, on_step=True, on_epoch=True, prog_bar=True, logger=True) def validation_step(self, batch, batch_idx): images, labels = batch # Forward Pass outputs = self(images) val_loss = F.cross_entropy(outputs, labels) val_acc = accuracy(outputs, labels) self.log('val_acc',val_acc, 'val_loss', val_loss, on_step=True, on_epoch=True, prog_bar=True, logger=True) tensorboard_logs = {'val_loss': val_loss, 'val_acc': acc} tensorboard = self.logger.experiment return {'val_loss': val_loss, 'log': tensorboard_logs, 'val_acc':acc} def validation_epoch_ends(self, outputs): avg_loss = torch.stack([x['val_loss'] for x in outputs]).mean() avg_acc = torch.stack([x['val_acc'] for x in outputs]).mean() pbar = {'val_acc': acc} tensorboard_logs = {'val_loss': avg_loss, 'val_acc': avg_acc} return {'val_loss': avg_loss, 'log': tensorboard_logs,'progress_bar': pbar} if __name__ == '__main__': trainer = Trainer(auto_lr_find=True, max_epochs=num_epochs, fast_dev_run=False,gpus=1, logger) # 'fast_dev_run' for checking errors, "auto_lr_find" to find the best lr_rate model = Lit_NN(num_classes, model) trainer.fit(model)

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Naagar.noreply@github.com

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/relatorio/urls.py

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CimaraOliveira/WorkBook

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refs/heads/main

2023-05-30T01:48:21.841086

2021-06-14T17:27:22

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from django.urls import path from .views import GeneratePdf urlpatterns = [ path('relatorios/', GeneratePdf.as_view(), name='gerar_relatorio'), ]

[ "cimarinhaoliveira@hotmail.com" ]

cimarinhaoliveira@hotmail.com

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/scraping/ven/bin/easy_install-3.8

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durbonca/just-some-py-code-exercise

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refs/heads/master

2020-09-28T21:22:17.780372

2019-12-16T13:09:06

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2019-12-16T13:19:54

2019-12-09T12:35:37

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#!/home/durbonca/Documents/platzi/python/scraping/ven/bin/python3.8 # -*- coding: utf-8 -*- import re import sys from setuptools.command.easy_install import main if __name__ == '__main__': sys.argv[0] = re.sub(r'(-script\.pyw|\.exe)?$', '', sys.argv[0]) sys.exit(main())

[ "durbonca@hotmail.com" ]

durbonca@hotmail.com

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/daftar/migrations/0012_auto_20200204_1527.py

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no_license

s4-hub/winback

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refs/heads/master

2020-12-22T12:27:54.416189

2020-02-11T10:50:30

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# Generated by Django 2.2.7 on 2020-02-04 08:27 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('daftar', '0011_auto_20200204_1445'), ] operations = [ migrations.DeleteModel( name='Pekerjaan', ), migrations.AddField( model_name='daftar', name='lokasi', field=models.CharField(choices=[('1101', 'ACEH SELATAN'), ('1102', 'ACEH TENGGARA'), ('1103', 'ACEH TIMUR'), ('1104', 'ACEH TENGAH'), ('1105', 'ACEH BARAT'), ('1106', 'ACEH BESAR'), ('1107', 'PIDIE'), ('1108', 'ACEH UTARA'), ('1109', 'SIMEULUE'), ('1110', 'ACEH SINGKIL'), ('1111', 'BIREUEN'), ('1112', 'ACEH BARAT DAYA'), ('1113', 'GAYO LUES'), ('1114', 'ACEH JAYA'), ('1115', 'NAGAN RAYA'), ('1116', 'ACEH TAMIANG'), ('1117', 'BENER MERIAH'), ('1118', 'PIDIE JAYA'), ('1171', 'KOTA BANDA ACEH'), ('1172', 'KOTA SABANG'), ('1173', 'KOTA LHOKSEUMAWE'), ('1174', 'KOTA LANGSA'), ('1175', 'KOTA SUBULUSSALAM')], default=1, max_length=30), preserve_default=False, ), migrations.AddField( model_name='daftar', name='pekerjaan1', field=models.CharField(choices=[('P001', 'PETANI/PEKEBUN'), ('P002', 'PETERNAK'), ('P003', 'NELAYAN/PERIKANAN'), ('P004', 'TRANSPORTASI'), ('P005', 'BURUH HARIAN LEPAS'), ('P006', 'BURUH TANI/PERKEBUNAN'), ('P007', 'BURUH NELAYAN/PERIKANAN'), ('P008', 'BURUH PETERNAKAN'), ('P009', 'PEMBANTU RUMAH TANGGA'), ('P010', 'TUKANG CUKUR'), ('P011', 'TUKANG LISTRIK'), ('P012', 'TUKANG BATU'), ('P013', 'TUKANG KAYU'), ('P014', 'TUKANG SOL SEPATU'), ('P015', 'TUKANG LAS/PANDAI BESI'), ('P016', 'TUKANG JAHIT'), ('P017', 'TUKANG GIGI'), ('P018', 'PENATA RIAS'), ('P019', 'PENATA BUSANA'), ('P020', 'PENATA RAMBUT'), ('P021', 'MEKANIK'), ('P022', 'SENIMAN'), ('P023', 'TABIB'), ('P024', 'PARAJI'), ('P025', 'PERANCANG BUSANA'), ('P026', 'PENTERJEMAH'), ('P027', 'IMAM MESJID'), ('P028', 'PENDETA'), ('P029', 'PASTOR'), ('P030', 'WARTAWAN'), ('P031', 'USTADZ/MUBALIGH'), ('P032', 'JURU MASAK'), ('P033', 'PROMOTOR ACARA'), ('P034', 'DOSEN'), ('P035', 'GURU'), ('P036', 'PENGACARA'), ('P037', 'NOTARIS'), ('P038', 'ARSITEK'), ('P039', 'KONSULTAN'), ('P040', 'DOKTER'), ('P041', 'BIDAN'), ('P042', 'APOTEKER'), ('P043', 'PSIKIATER/PSIKOLOG'), ('P044', 'PENYIAR RADIO'), ('P045', 'PELAUT'), ('P046', 'PENELITI'), ('P047', 'SOPIR'), ('P048', 'PIALANG'), ('P049', 'PARANORMAL'), ('P050', 'PEDAGANG'), ('P051', 'BIARAWATI'), ('P052', 'WIRASWASTA'), ('P053', 'MITRA GOJEK'), ('P054', 'MITRA GRAB'), ('P055', 'MITRA UBER'), ('P056', 'PEKERJA MAGANG'), ('P057', 'SISWA KERJA PRAKTEK'), ('P058', 'TENAGA HONORER (SELAIN PENYELENGGARA NEGARA)'), ('P059', 'NARAPIDANA DALAM PROSES ASIMILASI'), ('P060', 'ATLET'), ('P061', 'ARTIS'), ('P062', 'JURU PARKIR'), ('P063', 'TUKANG PIJAT'), ('P064', 'PEMANDU LAGU'), ('P065', 'PENDAMPING DESA'), ('P066', 'BURUH BONGKAR MUAT/BAGASI'), ('P067', 'RELAWAN TAGANA/RELAWAN BENCANA'), ('P068', 'TUKANG SAMPAH'), ('P069', 'PEMULUNG'), ('P070', 'MARBOT MESJID'), ('P071', 'MITRA GOJEK-GO LIFE')], default=1, max_length=50), preserve_default=False, ), migrations.AddField( model_name='daftar', name='pekerjaan2', field=models.CharField(blank=True, choices=[('P001', 'PETANI/PEKEBUN'), ('P002', 'PETERNAK'), ('P003', 'NELAYAN/PERIKANAN'), ('P004', 'TRANSPORTASI'), ('P005', 'BURUH HARIAN LEPAS'), ('P006', 'BURUH TANI/PERKEBUNAN'), ('P007', 'BURUH NELAYAN/PERIKANAN'), ('P008', 'BURUH PETERNAKAN'), ('P009', 'PEMBANTU RUMAH TANGGA'), ('P010', 'TUKANG CUKUR'), ('P011', 'TUKANG LISTRIK'), ('P012', 'TUKANG BATU'), ('P013', 'TUKANG KAYU'), ('P014', 'TUKANG SOL SEPATU'), ('P015', 'TUKANG LAS/PANDAI BESI'), ('P016', 'TUKANG JAHIT'), ('P017', 'TUKANG GIGI'), ('P018', 'PENATA RIAS'), ('P019', 'PENATA BUSANA'), ('P020', 'PENATA RAMBUT'), ('P021', 'MEKANIK'), ('P022', 'SENIMAN'), ('P023', 'TABIB'), ('P024', 'PARAJI'), ('P025', 'PERANCANG BUSANA'), ('P026', 'PENTERJEMAH'), ('P027', 'IMAM MESJID'), ('P028', 'PENDETA'), ('P029', 'PASTOR'), ('P030', 'WARTAWAN'), ('P031', 'USTADZ/MUBALIGH'), ('P032', 'JURU MASAK'), ('P033', 'PROMOTOR ACARA'), ('P034', 'DOSEN'), ('P035', 'GURU'), ('P036', 'PENGACARA'), ('P037', 'NOTARIS'), ('P038', 'ARSITEK'), ('P039', 'KONSULTAN'), ('P040', 'DOKTER'), ('P041', 'BIDAN'), ('P042', 'APOTEKER'), ('P043', 'PSIKIATER/PSIKOLOG'), ('P044', 'PENYIAR RADIO'), ('P045', 'PELAUT'), ('P046', 'PENELITI'), ('P047', 'SOPIR'), ('P048', 'PIALANG'), ('P049', 'PARANORMAL'), ('P050', 'PEDAGANG'), ('P051', 'BIARAWATI'), ('P052', 'WIRASWASTA'), ('P053', 'MITRA GOJEK'), ('P054', 'MITRA GRAB'), ('P055', 'MITRA UBER'), ('P056', 'PEKERJA MAGANG'), ('P057', 'SISWA KERJA PRAKTEK'), ('P058', 'TENAGA HONORER (SELAIN PENYELENGGARA NEGARA)'), ('P059', 'NARAPIDANA DALAM PROSES ASIMILASI'), ('P060', 'ATLET'), ('P061', 'ARTIS'), ('P062', 'JURU PARKIR'), ('P063', 'TUKANG PIJAT'), ('P064', 'PEMANDU LAGU'), ('P065', 'PENDAMPING DESA'), ('P066', 'BURUH BONGKAR MUAT/BAGASI'), ('P067', 'RELAWAN TAGANA/RELAWAN BENCANA'), ('P068', 'TUKANG SAMPAH'), ('P069', 'PEMULUNG'), ('P070', 'MARBOT MESJID'), ('P071', 'MITRA GOJEK-GO LIFE')], max_length=50), ), ]

[ "syafii.newbie@gmail.com" ]

syafii.newbie@gmail.com

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/Core/Noun/models.py

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shashanj/bankOnCube

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refs/heads/master

2021-01-20T12:38:26.897843

2017-05-05T15:25:19

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from django.db import models from Core.Verb.models import * from Core.Noun.NotificationEnableType import * # Create your models here. class Noun(models.Model): noun_code = models.CharField(primary_key=True,max_length=10, blank=False,null=False) noun = models.CharField(max_length=30, blank=False,null=False) desc = models.CharField(max_length=100) allowedVerb = models.ManyToManyField(Verb) def __str__(self): return self.noun # class Notification_Config(models.Model): # noun = models.ForeignKey(Noun) # verb = models.ForeignKey(Verb) # notification_enable = models.CharField(max_length=3,choices = Notification_Enable_Type().getTypes()) # condition = models.TextField(null= True) # expected_output_type = models.CharField(max_length=100) # expected_output = models.CharField(max_length=100) # def __str__(self): # return self.noun.noun + self.verb.verb

[ "shashanks.1903@gmail.com" ]

shashanks.1903@gmail.com

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/Aspect_Analysis/script/evaluate.py

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no_license

somanshud/Aspect-Intent-Sentiment-Analysis

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refs/heads/master

2022-08-17T20:13:10.744753

2020-05-20T07:27:17

null

0

null

UTF-8

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11,068

py

import argparse import torch import numpy as np import json, io from nltk import word_tokenize import nltk import os from nltk.tag import StanfordPOSTagger from keras.utils import to_categorical import xml.etree.ElementTree as ET from fasttext import load_model class Model(torch.nn.Module): def __init__(self, gen_emb, domain_emb, num_classes=3, dropout=0.5, crf=False, tag=False): super(Model, self).__init__() self.tag_dim = 45 if tag else 0 self.gen_embedding = torch.nn.Embedding(gen_emb.shape[0], gen_emb.shape[1]) self.gen_embedding.weight=torch.nn.Parameter(torch.from_numpy(gen_emb), requires_grad=False) self.domain_embedding = torch.nn.Embedding(domain_emb.shape[0], domain_emb.shape[1]) self.domain_embedding.weight=torch.nn.Parameter(torch.from_numpy(domain_emb), requires_grad=False) self.conv1=torch.nn.Conv1d(gen_emb.shape[1]+domain_emb.shape[1], 128, 5, padding=2 ) self.conv2=torch.nn.Conv1d(gen_emb.shape[1]+domain_emb.shape[1], 128, 3, padding=1 ) self.dropout=torch.nn.Dropout(dropout) self.conv3=torch.nn.Conv1d(256, 256, 5, padding=2) self.conv4=torch.nn.Conv1d(256, 256, 5, padding=2) self.conv5=torch.nn.Conv1d(256, 256, 5, padding=2) self.linear_ae1=torch.nn.Linear(256+self.tag_dim+domain_emb.shape[1], 50) self.linear_ae2=torch.nn.Linear(50, num_classes) self.crf_flag=crf if self.crf_flag: from allennlp.modules import ConditionalRandomField self.crf=ConditionalRandomField(num_classes) def forward(self, x, x_len, x_mask, x_tag, y=None, testing=False): x_emb=torch.cat((self.gen_embedding(x), self.domain_embedding(x) ), dim=2) x_emb=self.dropout(x_emb).transpose(1, 2) x_conv=torch.nn.functional.relu(torch.cat((self.conv1(x_emb), self.conv2(x_emb)), dim=1) ) x_conv=self.dropout(x_conv) x_conv=torch.nn.functional.relu(self.conv3(x_conv) ) x_conv=self.dropout(x_conv) x_conv=torch.nn.functional.relu(self.conv4(x_conv) ) x_conv=self.dropout(x_conv) x_conv=torch.nn.functional.relu(self.conv5(x_conv) ) x_conv=x_conv.transpose(1, 2) x_logit=torch.nn.functional.relu(self.linear_ae1(torch.cat((x_conv, x_tag, self.domain_embedding(x)), dim=2) ) ) x_logit=self.linear_ae2(x_logit) if testing: if self.crf_flag: score=self.crf.viterbi_tags(x_logit, x_mask) else: x_logit=x_logit.transpose(2, 0) score=torch.nn.functional.log_softmax(x_logit).transpose(2, 0) else: if self.crf_flag: score=-self.crf(x_logit, y, x_mask) else: x_logit=torch.nn.utils.rnn.pack_padded_sequence(x_logit, x_len, batch_first=True) score=torch.nn.functional.nll_loss(torch.nn.functional.log_softmax(x_logit.data), y.data) return score def build_emb_dictionary(fn): words=[] vectors=[] with open(fn) as f: for l in f: t=l.rstrip().split(' ') words.append(t[0]) vectors.append(list(map(float, t[1:]))) wordvecs = np.array(vectors, dtype=np.double) word2id = {word:i for i, word in enumerate(words)} return wordvecs,word2id def prepare_embeddings(fn, gen_emb, embeddings, domain_emb, prep_dir, gen_dim=300, domain_dim=100): text = [] with open(fn) as f: for line in f: token = word_tokenize(line) text=text+token vocab = sorted(set(text)) word_idx = {} if os.path.exists(prep_dir+'word_idx.json'): with io.open(prep_dir+'word_idx.json') as f: prev_word = json.load(f) else: prev_word = {} wx = 0 new_word = [] for word in vocab: if word not in prev_word: wx = wx+1 new_word.append(word) word_idx[word] = wx+len(prev_word) prev_word.update(word_idx) if new_word == []: return embedding_gen=np.zeros((len(prev_word)+2, gen_dim) ) embedding_domain=np.zeros((len(prev_word)+2, domain_dim) ) if os.path.exists(prep_dir+'gen.vec.npy'): gen_emb_prev=np.load(prep_dir+"gen.vec.npy") embedding_gen[:gen_emb_prev.shape[0],:] = gen_emb_prev if os.path.exists(prep_dir+'gen.vec.npy'): domain_emb_prev=np.load(prep_dir+embeddings+'.npy') embedding_domain[:domain_emb_prev.shape[0],:] = domain_emb_prev with open(gen_emb) as f: for l in f: rec=l.rstrip().split(' ') if len(rec)==2: continue if rec[0] in new_word: embedding_gen[prev_word[rec[0]]] = np.array([float(r) for r in rec[1:] ]) with open(domain_emb) as f: for l in f: rec=l.rstrip().split(' ') if len(rec)==2: continue if rec[0] in new_word: embedding_domain[prev_word[rec[0]]] = np.array([float(r) for r in rec[1:] ]) ftmodel = load_model(domain_emb+".bin") for w in new_word: if embedding_domain[word_idx[w] ].sum()==0.: embedding_domain[word_idx[w] ] = ftmodel.get_word_vector(w) with io.open(prep_dir+'word_idx.json', 'w') as outfile: outfile.write(json.dumps(prev_word)) np.save(prep_dir+'gen.vec.npy', embedding_gen.astype('float32') ) np.save(prep_dir+embeddings+'.npy', embedding_domain.astype('float32') ) def prepare_text(fn, POSdir, prep_dir): pos_tag_list = ['CC', 'CD', 'DT', 'EX', 'FW', 'IN', 'JJ', 'JJR', 'JJS', 'LS', 'MD', 'NN', 'NNS','NNP', 'NNPS', 'PDT', 'POS', 'PRP', 'PRP$', 'RB', 'RBR', 'RBS', 'RP','SYM', 'TO', 'UH', 'VB', 'VBD', 'VBG', 'VBN', 'VBP', 'VBZ', 'WDT', 'WP', 'WP$', 'WRB',',','.',':','$','#',"``","''",'(',')'] tag_to_num = {tag:i+1 for i, tag in enumerate(sorted(pos_tag_list))} with io.open(prep_dir+'word_idx.json') as f: word_idx=json.load(f) sentence_size = [-1, 130] with open(fn) as f: count = 0 for l in f: token = word_tokenize(l) if len(token) > 0: count = count + 1 if len(token) > sentence_size[1]: sentence_size[1]=len(token) sentence_size[0] = count X = np.zeros((sentence_size[0], sentence_size[1]), np.int16) X_tag = np.zeros((sentence_size[0], sentence_size[1]), np.int16) with open(fn) as f: count = -1 raw_X=[] for l in f: token = word_tokenize(l) jar = POSdir+'stanford-postagger.jar' model = POSdir+'models/english-left3words-distsim.tagger' pos_tagger = StanfordPOSTagger(model, jar, encoding='utf8') pos_tag_stf = [tag_to_num[tag] for (_,tag) in pos_tagger.tag(token)] if len(token) > 0: count = count + 1 raw_X.append(token) for wx, word in enumerate(token): X[count, wx] = word_idx[word] X_tag[count, wx] = pos_tag_stf[wx] return raw_X, X, X_tag def getAspects(fn, pred_y): data = [] count = -1 with open(fn) as f: for l in f: token = word_tokenize(l) if len(token) > 0: count = count + 1 for wx, word in enumerate(token): if pred_y[count, wx] == 1: data.append({ 'sentence': l, 'word':word }) elif pred_y[count, wx] == 2: data.append({ 'sentence': l, 'word':word }) else: continue else: return "error" return data def test(model, test_X, test_X_tag, raw_X, domain, batch_size=128, crf=False, tag=False): pred_y=np.zeros((test_X.shape[0], test_X.shape[1]), np.int16) model.eval() for offset in range(0, test_X.shape[0], batch_size): batch_test_X_len=np.sum(test_X[offset:offset+batch_size]!=0, axis=1) batch_idx=batch_test_X_len.argsort()[::-1] batch_test_X_len=batch_test_X_len[batch_idx] batch_test_X_mask=(test_X[offset:offset+batch_size]!=0)[batch_idx].astype(np.uint8) batch_test_X=test_X[offset:offset+batch_size][batch_idx] batch_test_X_mask=torch.autograd.Variable(torch.from_numpy(batch_test_X_mask).long() ) batch_test_X = torch.autograd.Variable(torch.from_numpy(batch_test_X).long() ) if tag: batch_test_X_tag = test_X_tag[offset:offset+batch_size][batch_idx] batch_test_X_tag_onehot = to_categorical(batch_test_X_tag, num_classes=45+1)[:,:,1:] batch_test_X_tag_onehot = torch.autograd.Variable(torch.from_numpy(batch_test_X_tag_onehot).type(torch.FloatTensor) ) else: batch_test_X_tag_onehot = None batch_pred_y=model(batch_test_X, batch_test_X_len, batch_test_X_mask, batch_test_X_tag_onehot, testing=True) r_idx=batch_idx.argsort() if crf: batch_pred_y=[batch_pred_y[idx] for idx in r_idx] for ix in range(len(batch_pred_y) ): for jx in range(len(batch_pred_y[ix]) ): pred_y[offset+ix,jx]=batch_pred_y[ix][jx] else: batch_pred_y=batch_pred_y.data.cpu().numpy().argmax(axis=2)[r_idx] pred_y[offset:offset+batch_size,:batch_pred_y.shape[1]]=batch_pred_y model.train() assert len(pred_y)==len(test_X) return pred_y def calculate_aspect(demo_dir, demo_fn, embeddings, model_fn, POSdir, domain, gen_emb, domain_emb, runs, gen_dim, domain_dim, prep_dir, crf=False, tag=True): fn = demo_dir + demo_fn prepare_embeddings(fn, gen_emb, embeddings, domain_emb, prep_dir, gen_dim, domain_dim) raw_X, X, X_tag = prepare_text(fn, POSdir, prep_dir) for run in range(runs): model_fn_run=model_fn+str(run) model=torch.load(model_fn_run, map_location=lambda storage, loc: storage) embedding_gen=np.load(prep_dir+"gen.vec.npy") embedding_domain=np.load(prep_dir+domain+"_emb.vec.npy") model.gen_embedding = torch.nn.Embedding(embedding_gen.shape[0], embedding_gen.shape[1]) model.gen_embedding.weight=torch.nn.Parameter(torch.from_numpy(embedding_gen).type(torch.FloatTensor), requires_grad=False) model.domain_embedding = torch.nn.Embedding(embedding_domain.shape[0], embedding_domain.shape[1]) model.domain_embedding.weight=torch.nn.Parameter(torch.from_numpy(embedding_domain).type(torch.FloatTensor), requires_grad=False) if not tag: model.tag_dim = 0 pred_y = test(model, X, X_tag, raw_X, domain, crf=crf, tag=tag) data = getAspects(fn, pred_y) # print('data', data) return data

[ "adityakumarpr@gmail.com" ]

adityakumarpr@gmail.com

9cfccbaa8b3879e950521b802914de6661ad47a2

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/test/functional/feature_minchainwork.py

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[ "MIT" ]

permissive

hiphopcoin24/hiphopcoin24

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refs/heads/master

2023-05-14T18:44:02.844736

2021-06-09T08:51:27

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#!/usr/bin/env python3 # Copyright (c) 2017-2018 The Hiphopcoin Core developers # Distributed under the MIT software license, see the accompanying # file COPYING or http://www.opensource.org/licenses/mit-license.php. """Test logic for setting nMinimumChainWork on command line. Nodes don't consider themselves out of "initial block download" until their active chain has more work than nMinimumChainWork. Nodes don't download blocks from a peer unless the peer's best known block has more work than nMinimumChainWork. While in initial block download, nodes won't relay blocks to their peers, so test that this parameter functions as intended by verifying that block relay only succeeds past a given node once its nMinimumChainWork has been exceeded. """ import time from test_framework.test_framework import HiphopcoinTestFramework from test_framework.util import assert_equal # 2 hashes required per regtest block (with no difficulty adjustment) REGTEST_WORK_PER_BLOCK = 2 class MinimumChainWorkTest(HiphopcoinTestFramework): def set_test_params(self): self.setup_clean_chain = True self.num_nodes = 3 self.extra_args = [[], ["-minimumchainwork=0x65"], ["-minimumchainwork=0x65"]] self.node_min_work = [0, 101, 101] def setup_network(self): # This test relies on the chain setup being: # node0 <- node1 <- node2 # Before leaving IBD, nodes prefer to download blocks from outbound # peers, so ensure that we're mining on an outbound peer and testing # block relay to inbound peers. self.setup_nodes() for i in range(self.num_nodes-1): self.connect_nodes(i+1, i) def run_test(self): # Start building a chain on node0. node2 shouldn't be able to sync until node1's # minchainwork is exceeded starting_chain_work = REGTEST_WORK_PER_BLOCK # Genesis block's work self.log.info("Testing relay across node %d (minChainWork = %d)", 1, self.node_min_work[1]) starting_blockcount = self.nodes[2].getblockcount() num_blocks_to_generate = int((self.node_min_work[1] - starting_chain_work) / REGTEST_WORK_PER_BLOCK) self.log.info("Generating %d blocks on node0", num_blocks_to_generate) hashes = self.nodes[0].generatetoaddress(num_blocks_to_generate, self.nodes[0].get_deterministic_priv_key().address) self.log.info("Node0 current chain work: %s", self.nodes[0].getblockheader(hashes[-1])['chainwork']) # Sleep a few seconds and verify that node2 didn't get any new blocks # or headers. We sleep, rather than sync_blocks(node0, node1) because # it's reasonable either way for node1 to get the blocks, or not get # them (since they're below node1's minchainwork). time.sleep(3) self.log.info("Verifying node 2 has no more blocks than before") self.log.info("Blockcounts: %s", [n.getblockcount() for n in self.nodes]) # Node2 shouldn't have any new headers yet, because node1 should not # have relayed anything. assert_equal(len(self.nodes[2].getchaintips()), 1) assert_equal(self.nodes[2].getchaintips()[0]['height'], 0) assert self.nodes[1].getbestblockhash() != self.nodes[0].getbestblockhash() assert_equal(self.nodes[2].getblockcount(), starting_blockcount) self.log.info("Generating one more block") self.nodes[0].generatetoaddress(1, self.nodes[0].get_deterministic_priv_key().address) self.log.info("Verifying nodes are all synced") # Because nodes in regtest are all manual connections (eg using # addnode), node1 should not have disconnected node0. If not for that, # we'd expect node1 to have disconnected node0 for serving an # insufficient work chain, in which case we'd need to reconnect them to # continue the test. self.sync_all() self.log.info("Blockcounts: %s", [n.getblockcount() for n in self.nodes]) if __name__ == '__main__': MinimumChainWorkTest().main()

[ "hiphopcoin24@gmail.com" ]

hiphopcoin24@gmail.com

ec0b5f82b94d998180217323ea3f0180998d4bb9

d046e1651781c258f4997e09be2cfba99e333e90

/crm/models.py

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[]

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Crenault/Assignment2-4deployment

de18470b78097a33af9f2d99143debe705533cb8

dfdefca6c1861bbd6b69d4f646d46aa881b63766

refs/heads/main

2023-08-03T02:18:40.694461

2021-10-07T15:20:59

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from django.db import models from django.utils import timezone from django.db import models # Create your models here. class Customer(models.Model): cust_name = models.CharField(max_length=50) organization = models.CharField(max_length=100, blank=True) role = models.CharField(max_length=100) email = models.EmailField(max_length=100) bldgroom = models.CharField(max_length=100) address = models.CharField(max_length=200) account_number = models.IntegerField(blank=False, null=False) city = models.CharField(max_length=50) state = models.CharField(max_length=50) zipcode = models.CharField(max_length=10) phone_number = models.CharField(max_length=50) created_date = models.DateTimeField( default=timezone.now) updated_date = models.DateTimeField(auto_now_add=True) def created(self): self.created_date = timezone.now() self.save() def updated(self): self.updated_date = timezone.now() self.save() def __str__(self): return str(self.cust_name) class Service(models.Model): cust_name = models.ForeignKey(Customer, on_delete=models.CASCADE, related_name='services') service_category = models.CharField(max_length=100) description = models.TextField() location = models.CharField(max_length=200) setup_time = models.DateTimeField( default=timezone.now) cleanup_time = models.DateTimeField( default=timezone.now) service_charge = models.DecimalField(max_digits=10, decimal_places=2) created_date = models.DateTimeField( default=timezone.now) updated_date = models.DateTimeField(auto_now_add=True) def created(self): self.created_date = timezone.now() self.save() def updated(self): self.updated_date = timezone.now() self.save() def __str__(self): return str(self.cust_name) class Product(models.Model): cust_name = models.ForeignKey(Customer, on_delete=models.CASCADE, related_name='products') product = models.CharField(max_length=100) p_description = models.TextField() quantity = models.IntegerField() pickup_time = models.DateTimeField( default=timezone.now) charge = models.DecimalField(max_digits=10, decimal_places=2) created_date = models.DateTimeField( default=timezone.now) updated_date = models.DateTimeField(auto_now_add=True) def created(self): self.created_date = timezone.now() self.save() def updated(self): self.updated_date = timezone.now() self.save() def __str__(self): return str(self.cust_name)

[ "crenault@unomaha.edu" ]

crenault@unomaha.edu

1edc3c43ccedae5b0f41c6a0f086d3ab554dd904

0e1e643e864bcb96cf06f14f4cb559b034e114d0

/Exps_7_v3/doc3d/I_w_M_to_W_focus_Zok_div/ch016/wiColorJ/Add2Loss/Sob_k09_s001_Mae_s001_good/pyr_Tcrop255_p20_j15/pyr_1s/L7/step09_1side_L7.py

c64e2e1afb0db5021bb85517a443b2008fa6e4b9

[]

no_license

KongBOy/kong_model2

33a94a9d2be5b0f28f9d479b3744e1d0e0ebd307

1af20b168ffccf0d5293a393a40a9fa9519410b2

refs/heads/master

2022-10-14T03:09:22.543998

2022-10-06T11:33:42

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############################################################################################################################################################################################################# ############################################################################################################################################################################################################# ### 把 kong_model2 加入 sys.path import os from tkinter import S code_exe_path = os.path.realpath(__file__) ### 目前執行 step10_b.py 的 path code_exe_path_element = code_exe_path.split("\\") ### 把 path 切分等等要找出 kong_model 在第幾層 kong_layer = code_exe_path_element.index("kong_model2") ### 找出 kong_model2 在第幾層 kong_model2_dir = "\\".join(code_exe_path_element[:kong_layer + 1]) ### 定位出 kong_model2 的 dir import sys ### 把 kong_model2 加入 sys.path sys.path.append(kong_model2_dir) # print(__file__.split("\\")[-1]) # print(" code_exe_path:", code_exe_path) # print(" code_exe_path_element:", code_exe_path_element) # print(" kong_layer:", kong_layer) # print(" kong_model2_dir:", kong_model2_dir) ############################################################################################################################################################################################################# from step08_b_use_G_generate_I_w_M_to_Wx_Wy_Wz_combine import I_w_M_to_W from step08_b_use_G_generate_0_util import Tight_crop, Color_jit from step09_c_train_step import Train_step_I_w_M_to_W from step09_d_KModel_builder_combine_step789 import KModel_builder, MODEL_NAME color_jit = Color_jit(do_ratio=0.6) use_what_gen_op = I_w_M_to_W( separate_out=True, focus=True, tight_crop=Tight_crop(pad_size=20, resize=(255, 255), jit_scale= 0) ) use_what_train_step = Train_step_I_w_M_to_W( separate_out=True, focus=True, tight_crop=Tight_crop(pad_size=20, resize=(255, 255), jit_scale= 15), color_jit=color_jit ) use_hid_ch = 16 import time start_time = time.time() ############################################################################################################################################################################################### ############################################################################################################################################################################################### ########################################################### Block1 ### Block1 ######################################################################################### pyramid_1side_1 = [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1] pyramid_1side_2 = [1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1] pyramid_1side_3 = [1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1] pyramid_1side_4 = [1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1] pyramid_1side_5 = [1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1] pyramid_1side_6 = [1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1] pyramid_1side_7 = [1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1] pyramid_1side_8 = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1] ######################################################################################### ch032_pyramid_1side_1 = KModel_builder().set_model_name(MODEL_NAME.flow_unet2).set_unet3(out_conv_block=True, concat_before_down=True, kernel_size=3, padding="valid", hid_ch=use_hid_ch, depth_level=7, out_ch=1, d_amount=3, bottle_divide=True, unet_acti="sigmoid", conv_block_num=pyramid_1side_1, ch_upper_bound= 2 ** 14).set_gen_op( use_what_gen_op ).set_train_step( use_what_train_step ) ch032_pyramid_1side_2 = KModel_builder().set_model_name(MODEL_NAME.flow_unet2).set_unet3(out_conv_block=True, concat_before_down=True, kernel_size=3, padding="valid", hid_ch=use_hid_ch, depth_level=7, out_ch=1, d_amount=3, bottle_divide=True, unet_acti="sigmoid", conv_block_num=pyramid_1side_2, ch_upper_bound= 2 ** 14).set_gen_op( use_what_gen_op ).set_train_step( use_what_train_step ) ch032_pyramid_1side_3 = KModel_builder().set_model_name(MODEL_NAME.flow_unet2).set_unet3(out_conv_block=True, concat_before_down=True, kernel_size=3, padding="valid", hid_ch=use_hid_ch, depth_level=7, out_ch=1, d_amount=3, bottle_divide=True, unet_acti="sigmoid", conv_block_num=pyramid_1side_3, ch_upper_bound= 2 ** 14).set_gen_op( use_what_gen_op ).set_train_step( use_what_train_step ) ch032_pyramid_1side_4 = KModel_builder().set_model_name(MODEL_NAME.flow_unet2).set_unet3(out_conv_block=True, concat_before_down=True, kernel_size=3, padding="valid", hid_ch=use_hid_ch, depth_level=7, out_ch=1, d_amount=3, bottle_divide=True, unet_acti="sigmoid", conv_block_num=pyramid_1side_4, ch_upper_bound= 2 ** 14).set_gen_op( use_what_gen_op ).set_train_step( use_what_train_step ) ch032_pyramid_1side_5 = KModel_builder().set_model_name(MODEL_NAME.flow_unet2).set_unet3(out_conv_block=True, concat_before_down=True, kernel_size=3, padding="valid", hid_ch=use_hid_ch, depth_level=7, out_ch=1, d_amount=3, bottle_divide=True, unet_acti="sigmoid", conv_block_num=pyramid_1side_5, ch_upper_bound= 2 ** 14).set_gen_op( use_what_gen_op ).set_train_step( use_what_train_step ) ch032_pyramid_1side_6 = KModel_builder().set_model_name(MODEL_NAME.flow_unet2).set_unet3(out_conv_block=True, concat_before_down=True, kernel_size=3, padding="valid", hid_ch=use_hid_ch, depth_level=7, out_ch=1, d_amount=3, bottle_divide=True, unet_acti="sigmoid", conv_block_num=pyramid_1side_6, ch_upper_bound= 2 ** 14).set_gen_op( use_what_gen_op ).set_train_step( use_what_train_step ) ch032_pyramid_1side_7 = KModel_builder().set_model_name(MODEL_NAME.flow_unet2).set_unet3(out_conv_block=True, concat_before_down=True, kernel_size=3, padding="valid", hid_ch=use_hid_ch, depth_level=7, out_ch=1, d_amount=3, bottle_divide=True, unet_acti="sigmoid", conv_block_num=pyramid_1side_7, ch_upper_bound= 2 ** 14).set_gen_op( use_what_gen_op ).set_train_step( use_what_train_step ) ch032_pyramid_1side_8 = KModel_builder().set_model_name(MODEL_NAME.flow_unet2).set_unet3(out_conv_block=True, concat_before_down=True, kernel_size=3, padding="valid", hid_ch=use_hid_ch, depth_level=7, out_ch=1, d_amount=3, bottle_divide=True, unet_acti="sigmoid", conv_block_num=pyramid_1side_8, ch_upper_bound= 2 ** 14).set_gen_op( use_what_gen_op ).set_train_step( use_what_train_step ) ######################################################################################### ############################################################################################################################################################################################### if(__name__ == "__main__"): import numpy as np print("build_model cost time:", time.time() - start_time) data = np.zeros(shape=(1, 512, 512, 1)) use_model = ch032_pyramid_1side_4 use_model = use_model.build() result = use_model.generator(data) print(result.shape) from kong_util.tf_model_util import Show_model_weights Show_model_weights(use_model.generator) use_model.generator.summary()

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'''VGG11/13/16/19 in Pytorch.''' # from https://github.com/kuangliu/pytorch-cifar/blob/master/models/vgg.py import torch import torch.nn as nn from torch.autograd import Variable cfg = { 'VGG11': [64, 'M', 128, 'M', 256, 256, 'M', 512, 512, 'M', 512, 512, 'M'], 'VGG13': [64, 64, 'M', 128, 128, 'M', 256, 256, 'M', 512, 512, 'M', 512, 512, 'M'], 'VGG16': [64, 64, 'M', 128, 128, 'M', 256, 256, 256, 'M', 512, 512, 512, 'M', 512, 512, 512, 'M'], 'VGG19': [64, 64, 'M', 128, 128, 'M', 256, 256, 256, 256, 'M', 512, 512, 512, 512, 'M', 512, 512, 512, 512, 'M'], } class VGG(nn.Module): def __init__(self, vgg_name): super(VGG, self).__init__() self.features = self._make_layers(cfg[vgg_name]) self.classifier = nn.Linear(512, 10) def forward(self, x): out = self.features(x) out = out.view(out.size(0), -1) out = self.classifier(out) return out def _make_layers(self, cfg): layers = [] in_channels = 3 for x in cfg: if x == 'M': layers += [nn.MaxPool2d(kernel_size=2, stride=2)] else: layers += [nn.Conv2d(in_channels, x, kernel_size=3, padding=1), nn.BatchNorm2d(x), nn.ReLU(inplace=True)] in_channels = x layers += [nn.AvgPool2d(kernel_size=1, stride=1)] return nn.Sequential(*layers) # net = VGG('VGG11') # x = torch.randn(2,3,32,32) # print(net(Variable(x)).size())

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# Generated by Django 3.1.2 on 2020-10-13 04:21 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('pdf_app', '0002_auto_20201013_0113'), ] operations = [ migrations.RenameModel( old_name='Pdf', new_name='Document', ), ]

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import os.path import configparser class Config: def __init__(self,file): self.fname = file self.cfg = configparser.ConfigParser() self.cfg.read(os.path.join(os.path.dirname(__file__), self.fname)) def getSections(self): try: return self.cfg.sections() except: return [] def getSection(self,sec): try: return dict(self.cfg.items(sec)) except: return {} def addSection(self,sec): try: self.cfg.add_section(sec) return True except: return False def delSection(self,sec): return self.cfg.remove_section(sec) def isSection(self,sec): return self.cfg.has_section(sec) def getOptions(self,sec): return self.cfg.options(sec) def getOption(self,sec,opt): try: return self.cfg.get(sec,opt) except: return "" def setOption(self,sec,opt,val): try: self.cfg.set(sec,opt,str(val)) return True except: return False def delOption(self,sec,opt): return self.cfg.remove_option(sec,opt) def isOption(self,sec,opt): return self.cfg.has_option(sec,opt) def getItems(self,sec): res = {} items = self.cfg.items(sec) for i in items: if i[0]: res[i[0]]=i[1] return res def save(self): with open(os.path.join(os.path.dirname(__file__), self.fname), 'w') as configfile: self.cfg.write(configfile)

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from __future__ import print_function from builtins import range from builtins import object import numpy as np import matplotlib.pyplot as plt from past.builtins import xrange class TwoLayerNet(object): def __init__(self, input_size, hidden_size, output_size, std=1e-4): self.params = {} self.params['W1'] = std * np.random.randn(input_size, hidden_size) self.params['b1'] = np.zeros(hidden_size) self.params['W2'] = std * np.random.randn(hidden_size, output_size) self.params['b2'] = np.zeros(output_size) def loss(self, X, y=None, reg=0.0): W1, b1 = self.params['W1'], self.params['b1'] W2, b2 = self.params['W2'], self.params['b2'] N, D = X.shape scores = None Z1 = np.dot(X, W1) + b1 A1 = np.maximum(0, Z1) Z2 = np.dot(A1,W2) + b2 scores = Z2 if y is None: return scores loss = 0.0 correctScore = -np.sum(scores[range(N), y]) loss = correctScore + np.sum(np.log(np.sum(np.exp(scores), axis = 1)),axis=0) loss /= N loss += reg * np.sum(W1* W1) + reg * np.sum(W2 * W2) grads = {} C = W2.shape[1] countOfX = np.zeros((N, C))+ np.exp(scores)/ np.sum(np.exp(scores), axis = 1).reshape(-1,1) countOfX[range(N), y] -= 1 dZ2 = countOfX grads['W2'] = 1/N * np.dot(A1.T, countOfX) + 2 * reg * W2 grads['b2'] = np.sum(dZ2, axis = 0)/N dZ1 = np.dot(dZ2, W2.T) dZ1[A1 <= 0] = 0 grads['W1'] = 1/N * np.dot(X.T, dZ1) + 2 * reg * W1 grads['b1'] = np.sum(dZ1, axis = 0)/N return loss, grads def train(self, X, y, X_val, y_val, learning_rate=1e-3, learning_rate_decay=0.95, reg=5e-6, num_iters=100, batch_size=200, verbose=False): num_train = X.shape[0] iterations_per_epoch = max(num_train / batch_size, 1) loss_history = [] train_acc_history = [] val_acc_history = [] for it in range(num_iters): X_batch = None y_batch = None index = np.random.choice(num_train, batch_size,replace = True) X_batch = X[index] y_batch = y[index] loss, grads = self.loss(X_batch, y=y_batch, reg=reg) loss_history.append(loss) self.params['W2'] -= learning_rate * grads['W2'] self.params['b2'] -= learning_rate * grads['b2'] self.params['W1'] -= learning_rate * grads['W1'] self.params['b1'] -= learning_rate * grads['b1'] if verbose and it % 100 == 0: print('iteration %d / %d: loss %f' % (it, num_iters, loss)) if it % iterations_per_epoch == 0: train_acc = (self.predict(X_batch) == y_batch).mean() val_acc = (self.predict(X_val) == y_val).mean() train_acc_history.append(train_acc) val_acc_history.append(val_acc) learning_rate *= learning_rate_decay return { 'loss_history': loss_history, 'train_acc_history': train_acc_history, 'val_acc_history': val_acc_history, } def predict(self, X): Z1 = np.dot(X, self.params['W1']) + self.params['b1'] A1 = np.maximum(0, Z1) Z2 = np.dot(A1,self.params['W2']) + self.params['b2'] y_pred = np.argmax(Z2, axis = 1) return y_pred

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import nacl.secret import nacl.utils # This must be kept secret, this is the combination to your safe key = nacl.utils.random(nacl.secret.SecretBox.KEY_SIZE) # This is your safe, you can use it to encrypt or decrypt messages box = nacl.secret.SecretBox(key) # This is our message to send, it must be a bytestring as SecretBox will # treat it as just a binary blob of data. message = b"The president will be exiting through the lower levels" # Encrypt our message, it will be exactly 40 bytes longer than the # original message as it stores authentication information and the # nonce alongside it. encrypted = box.encrypt(message) assert len(encrypted) == len(message) + box.NONCE_SIZE + box.MACBYTES nonce = nacl.utils.random(nacl.secret.SecretBox.NONCE_SIZE) encrypted = box.encrypt(message, nonce) # since we are transmitting the nonce by some other means, # we just need to get the ciphertext and authentication data ctext = encrypted.ciphertext # ctext is just nacl.secret.SecretBox.MACBYTES longer # than the original message assert len(ctext) == len(message) + box.MACBYTES # Decrypt our message, an exception will be raised if the encryption was # tampered with or there was otherwise an error. plaintext = box.decrypt(encrypted) print(plaintext.decode('utf-8'))

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huebli@gmail.com

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import numpy as np from cs231n.classifiers.linear_svm import * from cs231n.classifiers.softmax import * class LinearClassifier(object): def __init__(self): self.W = None def train(self, X, y, learning_rate=1e-3, reg=1e-5, num_iters=100,batch_size=200, verbose=False): """ Train this linear classifier using stochastic gradient descent. Inputs: - X: A numpy array of shape (N, D) containing training data; there are N training samples each of dimension D. - y: A numpy array of shape (N,) containing training labels; y[i] = c means that X[i] has label 0 <= c < C for C classes. - learning_rate: (float) learning rate for optimization. - reg: (float) regularization strength. - num_iters: (integer) number of steps to take when optimizing - batch_size: (integer) number of training examples to use at each step. - verbose: (boolean) If true, print progress during optimization. Outputs: A list containing the value of the loss function at each training iteration. """ num_train, dim = X.shape num_classes = np.max(y) + 1 # assume y takes values 0...K-1 where K is number of classes #if self.W is None: # lazily initialize W---->always initialize) self.W = 0.001 * np.random.randn(dim, num_classes)*np.sqrt(dim/2.0) # Run stochastic gradient descent to optimize W loss_history = [] #Try using momentum update v=0 #init to zero mu=0.5 #int to 0.5, and increase it later. for it in xrange(num_iters): if num_iters%100==0: mu+=0.05 #if num_iters>=1500: # learning_rate*=0.7 if mu>=0.99: mu=0.99 X_batch = None y_batch = None ######################################################################### # TODO: # # Sample batch_size elements from the training data and their # # corresponding labels to use in this round of gradient descent. # # Store the data in X_batch and their corresponding labels in # # y_batch; after sampling X_batch should have shape (dim, batch_size) # # and y_batch should have shape (batch_size,) # # # # Hint: Use np.random.choice to generate indices. Sampling with # # replacement is faster than sampling without replacement. # ######################################################################### #pass #1. get the batch for this iteration. batch_indices=np.random.choice(num_train,batch_size,replace=True) X_batch=X[batch_indices] #('X_batch.shape:', (200L, 3073L)) #print("X_batch.shape:",X_batch.shape) y_batch=y[batch_indices] #('y_batch.shape:', 200) #print("y_batch.shape:",len(y_batch)) #loss_vectorized, grad_vectorized = svm_loss_vectorized(self.W, X_batch, y_batch, reg) #self.W+=-learning_rate*grad_vectorized ######################################################################### # END OF YOUR CODE # ######################################################################### #2. evaluate loss and gradient loss, grad = self.loss(X_batch, y_batch, reg) loss_history.append(loss) #3. perform parameter update ######################################################################### # TODO: # # Update the weights using the gradient and the learning rate. # ######################################################################### #pass #self.W-=learning_rate*grad v=mu*v-learning_rate*grad self.W+=v ######################################################################### # END OF YOUR CODE # ######################################################################### if verbose and it % 100 == 0: print 'iteration %d / %d: loss %f' % (it, num_iters, loss) return loss_history def predict(self, X): """ Use the trained weights of this linear classifier to predict labels for data points. Inputs: - X: D x N array of training data. Each column is a D-dimensional point. Returns: - y_pred: Predicted labels for the data in X. y_pred is a 1-dimensional array of length N, and each element is an integer giving the predicted class. """ y_pred = np.zeros(X.shape[1]) ########################################################################### # TODO: # # Implement this method. Store the predicted labels in y_pred. # ########################################################################### #pass scores=X.dot(self.W) #1.get scores y_pred=np.argmax(scores,axis=1) #2.find the index for highest value in the row ########################################################################### # END OF YOUR CODE # ########################################################################### return y_pred def loss(self, X_batch, y_batch, reg): """ Compute the loss function and its derivative. Subclasses will override this. Inputs: - X_batch: A numpy array of shape (N, D) containing a minibatch of N data points; each point has dimension D. - y_batch: A numpy array of shape (N,) containing labels for the minibatch. - reg: (float) regularization strength. Returns: A tuple containing: - loss as a single float - gradient with respect to self.W; an array of the same shape as W """ pass class LinearSVM(LinearClassifier): """ A subclass that uses the Multiclass SVM loss function """ def loss(self, X_batch, y_batch, reg): return svm_loss_vectorized(self.W, X_batch, y_batch, reg) class Softmax(LinearClassifier): """ A subclass that uses the Softmax + Cross-entropy loss function """ def loss(self, X_batch, y_batch, reg): return softmax_loss_vectorized(self.W, X_batch, y_batch, reg)

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brightmart@hotmail.com

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from login import login from create_account import create_account from read_file import read_file from menu2 import clear_screen accounts_list = read_file('Accounts.txt') def menu1(): print('>>>>>>>>WELCOME<<<<<<<<\n') choice = int(input('1) Login\n2) Create Account\n3) Exit\n\nchoice>> ')) if choice == 1: clear_screen() try: # to enable the option of (ctrl+c) to go back login(accounts_list) except KeyboardInterrupt: clear_screen() elif choice == 2: create_account(accounts_list) elif choice == 3: # close the program exit(0) else: clear_screen() print("ERROR: Wrong choice\n") menu1() if __name__ == '__main__': menu1()

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def replacement_by_division(): for char in range(11, 80): if char % 3 == 0 and char % 5 == 0: print("$$@@", end=' ') elif char % 3 == 0: print("$$", end=' ') elif char % 5 == 0: print("@@", end=' ') else: print(char, end=' ') if __name__ == "__main__": replacement_by_division()

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#-*-coding:utf-8-*- #qpy://127.0.0.1:8080/ """ This is a sample of WebApp @Author JIMhackKING """ import bottle from bottle import request, response, default_app, redirect from bottle import run, debug, route, error, static_file, template, view import sqlite3 import json import md5 import threading import os #### 常量定义 ######### ASSETS = "/assets/" ROOT = os.getcwd() @route('/my_ip') def my_ip(): ip = request['REMOTE_ADDR'] return '<h1>Your ip address is: %s</h1>' %ip @error(404) def page404(error): return template("404", page_name = "404", ) # 匹配末尾不带 / 的 URL，并重定向到正确的URL @route("/<path:re:[\w\/]+\w$>") def redirect_path(path): return redirect("/%s/" %path) # 上下两个路由绑定函数不能调换顺序，否则会出现抢先响应的情况 # 匹配静态文件 @route("/<filepath:path>") def assets(filepath): return static_file(filepath, root=ROOT+ASSETS) # 管理员登陆界面 @route("/admin/") def admin_login(): wrong = True if request.query.get("msg") else False return template("admin", page_name = "admin", wrong=wrong, ) @route("/admin/login/", method="POST") def login_success(): username = request.forms.get("username") password = md5.new(request.forms.get("password")).hexdigest() # 设置响应头 # response.set_header("Content-Type","application/json") response.set_header("Creater","JIMhackKING") try: conn = sqlite3.connect("db.sqlite3") cursor = conn.cursor() cursor.execute("select * from admin_user where username=? and password=?", (username, password)) if not cursor.fetchone(): # 重定向 return redirect("/admin/?msg=WrongPassword") # 暂时无法用 /admin?msg... 来做地址 finally: cursor.close() conn.close() return '<h1 style="text-align:center;">No content yet.</h1>' # 后台管理页面 # purecss.io 里的 blog 模板 # 增加动态URL, ps: /blog/DHC/ @route("/") def blog(): return template("pure-layout-blog", page_name = "pure-layout-blog", ) @route("/", method="POST") def blog_logined(): return template("pure-layout-blog", page_name = "pure-layout-blog", ) @route("/login/") def blog_login(): return template("blog-login", page_name = "blog-login", ) @route("/version/") def version_information(): return template("version-information", page_name = "version-information", ) """ 改进计划： · 为版本信息页创建模板，将各版本信息做成一块，在后台管理系统里面添加版本信息管理功能，每次版本更新只需要在后台管理系统进行编辑和添加。 · 管理员可在后台管理系统编辑博客，在博客主页用户可以编辑博客 · 增加精华、排行等功能 """ application = default_app()

[ "a601767890@sina.com" ]

a601767890@sina.com

50587e5954677e11ceae53851f78af9e5bcfa727

458ff3c3611bb969f96ff3d3e15108fa9ec88316

/quiz/migrations/0004_auto_20201209_2057.py

9ddaf47129300087df96cc291ab7fda68b428ff2

[]

no_license

mayank5044/Navigus

8164809d87c5f3112565549229327ea20d090898

aa03a99583efe4b7e9e7d1cb4a450e559f36d475

refs/heads/master

2023-08-11T01:30:21.115338

2021-10-09T06:47:24

414,919,603

0

null

UTF-8

Python

false

662

py

from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('student', '0002_remove_student_status'), ('quiz', '0003_result'), ] operations = [ migrations.AlterField( model_name='result', name='exam', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='quiz.Course'), ), migrations.AlterField( model_name='result', name='student', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='student.Student'), ), ]

[ "iutkarshyadav192000@gmail.com" ]

iutkarshyadav192000@gmail.com

a515d75c4adddd090567a13c1ecba9d797734bb2

6803de534702eb311f298ea51c4736d5d0aeaa10

/lvp/__init__.py

a712817a2f60a84889822bf3832930d80bc4a9c3

[]

no_license

mmsobral/lvp

4e2d6587be1d3344f39df7f3a9f38a5f3d30aa0a

b9d244f7f220a70d976fd772ef569a5acf2fd73e

refs/heads/master

2020-12-24T09:08:26.126330

2019-08-12T17:08:53

73,304,008

0

null

UTF-8

Python

false

23

py

__package__ = __name__

[ "msobral@gmail.com" ]

msobral@gmail.com

baed34dff5b6291a245a5b0525a858aeba9dc2b8

f82757475ea13965581c2147ff57123b361c5d62

/gi-stubs/repository/FwupdPlugin/FirmwareClass.py

41cfcb07d1b2a17378eab46a1dbbc60611507f68

[]

no_license

ttys3/pygobject-stubs

9b15d1b473db06f47e5ffba5ad0a31d6d1becb57

d0e6e93399212aada4386d2ce80344eb9a31db48

refs/heads/master

2022-09-23T12:58:44.526554

2020-06-06T04:15:00

269,693,287

8

2

null

2020-06-05T15:57:54

null

UTF-8

Python

false

5,303

py

# encoding: utf-8 # module gi.repository.FwupdPlugin # from /usr/lib64/girepository-1.0/FwupdPlugin-1.0.typelib # by generator 1.147 """ An object which wraps an introspection typelib. This wrapping creates a python module like representation of the typelib using gi repository as a foundation. Accessing attributes of the module will dynamically pull them in and create wrappers for the members. These members are then cached on this introspection module. """ # imports import gi as __gi import gi.overrides.GObject as __gi_overrides_GObject import gi.repository.Fwupd as __gi_repository_Fwupd import gobject as __gobject class FirmwareClass(__gi.Struct): """ :Constructors: :: FirmwareClass() """ def __delattr__(self, *args, **kwargs): # real signature unknown """ Implement delattr(self, name). """ pass def __dir__(self, *args, **kwargs): # real signature unknown """ Default dir() implementation. """ pass def __eq__(self, *args, **kwargs): # real signature unknown """ Return self==value. """ pass def __format__(self, *args, **kwargs): # real signature unknown """ Default object formatter. """ pass def __getattribute__(self, *args, **kwargs): # real signature unknown """ Return getattr(self, name). """ pass def __ge__(self, *args, **kwargs): # real signature unknown """ Return self>=value. """ pass def __gt__(self, *args, **kwargs): # real signature unknown """ Return self>value. """ pass def __hash__(self, *args, **kwargs): # real signature unknown """ Return hash(self). """ pass def __init_subclass__(self, *args, **kwargs): # real signature unknown """ This method is called when a class is subclassed. The default implementation does nothing. It may be overridden to extend subclasses. """ pass def __init__(self): # real signature unknown; restored from __doc__ pass def __le__(self, *args, **kwargs): # real signature unknown """ Return self<=value. """ pass def __lt__(self, *args, **kwargs): # real signature unknown """ Return self<value. """ pass @staticmethod # known case of __new__ def __new__(*args, **kwargs): # real signature unknown """ Create and return a new object. See help(type) for accurate signature. """ pass def __ne__(self, *args, **kwargs): # real signature unknown """ Return self!=value. """ pass def __reduce_ex__(self, *args, **kwargs): # real signature unknown """ Helper for pickle. """ pass def __reduce__(self, *args, **kwargs): # real signature unknown """ Helper for pickle. """ pass def __repr__(self, *args, **kwargs): # real signature unknown """ Return repr(self). """ pass def __setattr__(self, *args, **kwargs): # real signature unknown """ Implement setattr(self, name, value). """ pass def __sizeof__(self, *args, **kwargs): # real signature unknown """ Size of object in memory, in bytes. """ pass def __str__(self, *args, **kwargs): # real signature unknown """ Return str(self). """ pass def __subclasshook__(self, *args, **kwargs): # real signature unknown """ Abstract classes can override this to customize issubclass(). This is invoked early on by abc.ABCMeta.__subclasscheck__(). It should return True, False or NotImplemented. If it returns NotImplemented, the normal algorithm is used. Otherwise, it overrides the normal algorithm (and the outcome is cached). """ pass def __weakref__(self, *args, **kwargs): # real signature unknown pass padding = property(lambda self: object(), lambda self, v: None, lambda self: None) # default parent_class = property(lambda self: object(), lambda self, v: None, lambda self: None) # default parse = property(lambda self: object(), lambda self, v: None, lambda self: None) # default tokenize = property(lambda self: object(), lambda self, v: None, lambda self: None) # default to_string = property(lambda self: object(), lambda self, v: None, lambda self: None) # default write = property(lambda self: object(), lambda self, v: None, lambda self: None) # default __class__ = None # (!) real value is "<class 'gi.types.StructMeta'>" __dict__ = None # (!) real value is "mappingproxy({'__info__': StructInfo(FirmwareClass), '__module__': 'gi.repository.FwupdPlugin', '__gtype__': <GType void (4)>, '__dict__': <attribute '__dict__' of 'FirmwareClass' objects>, '__weakref__': <attribute '__weakref__' of 'FirmwareClass' objects>, '__doc__': None, 'parent_class': <property object at 0x7feb1afdfd60>, 'parse': <property object at 0x7feb1afdfe50>, 'write': <property object at 0x7feb1afdff40>, 'to_string': <property object at 0x7feb1afe2090>, 'tokenize': <property object at 0x7feb1afe2180>, 'padding': <property object at 0x7feb1afe2270>})" __gtype__ = None # (!) real value is '<GType void (4)>' __info__ = StructInfo(FirmwareClass)

[ "ttys3@outlook.com" ]

ttys3@outlook.com

3dacf8f46746f65ab751afcfc711af745c7e18e3

c4b9347346f21dd3d21a722b6b4e46f39bb1ea45

/Django Tutorial for Beginners - 32 - UpdateView and DeleteView/thenameoftheproject/music/views.py

80c27b8436ce1553e95a951ba07f1e6193f2e53b

[]

no_license

salahtobok/Django-Tutorial-for-Beginners-

0ca73e85b202188f0de63a7a4e32838a1e477638

ecbaa7f2518ac22d902b94483281c6cffc0123ae

refs/heads/master

2021-06-28T03:42:23.513945

2020-01-20T20:03:24

235,185,873

0

null

2021-06-10T22:30:15

2020-01-20T19:50:10

Python

UTF-8

Python

false

1,985

py

from django.shortcuts import render # Create your views here. from django.http import Http404 from django.http import HttpResponse # from django.shortcuts import render, get_object_or_404 # from .models import Album, Song # # # def index(request): # all_albums = Album.objects.all() # context = { # 'all_albums': all_albums, # } # return render(request, 'music/index.html', context) # # # def detail(request, album_id): # # album = Album.objects.get(pk=album_id) # album = get_object_or_404(Album, pk=album_id) # return render(request, 'music/detail.html', {'album': album}) # # # def favorite(request, album_id): # album = get_object_or_404(Album, pk=album_id) # try: # selected_song = album.song_set.get(pk=request.POST['song']) # except (KeyError, Song.DoesNotExist): # return render(request, 'music/detail.html', # {'album': album, 'error_message': "You did not select a valid song"}) # else: # selected_song.is_favorite = True # selected_song.save() # return render(request, 'music/detail.html', {'album': album}) from django.views import generic from .models import Album from django.views.generic.edit import CreateView,UpdateView,DeleteView from django.urls import reverse_lazy class IndexView(generic.ListView): template_name = 'music/index.html' context_object_name = 'all_albums' def get_queryset(self): return Album.objects.all() class DetailView(generic.DetailView): model = Album template_name = 'music/detail.html' class AlbumCreate(CreateView): model = Album fields = ['artist','album_title','genre','album_logo'] template_name = 'music/create_album.html' class AlbumUpdate(UpdateView): model = Album fields = ['artist', 'album_title', 'genre', 'album_logo'] template_name = 'music/update_album.html' class AlbumDelete(DeleteView): model = Album success_url = reverse_lazy('music:index')

[ "salahtobok1@gmail.com" ]

salahtobok1@gmail.com

d306b8f94c038f7897496da1ee2c40d1caafe459

82ed4adb96f6a134f51cc2eb33a13730badbb993

/3_5_6_xfail_test.py

1ac803d029b7ed6cf1191898562cb14d300b159c

[]

no_license

yesandv/webdriver

527ed3248c2fa2e8a0d670684c21ce62cbd71d7b

62a12672f94cab5d5a16558027ea804b307a4116

refs/heads/master

2023-06-20T21:10:18.102129

2021-08-01T16:20:51

351,724,267

0

null

UTF-8

Python

false

200

py

import pytest @pytest.mark.xfail(strict=True) def test_succeed(): assert True @pytest.mark.xfail def test_not_succeed(): assert False @pytest.mark.skip def test_skipped(): assert False

[ "grc@protonmail.com" ]

grc@protonmail.com

944140c7bba8ea526c0edc0595e380ce65ebcc98

690e8f0a853c1f27bae688f021e8c27e62ca9613

/auth/auth/settings.py

9d8a145494269d4ab9cebf00c17bb3722ad9be69

[]

no_license

MaksimLion/django-rest-authentication

d77c8b59e89c80a9f8c98fb7b038bebb431ffc0e

8445354f761d0624a97faa490d8872be5994da5e

refs/heads/master

2020-05-04T15:16:51.320819

2019-04-03T08:22:16

179,233,291

0

null

UTF-8

Python

false

3,303

py

""" Django settings for auth project. Generated by 'django-admin startproject' using Django 2.1.5. For more information on this file, see https://docs.djangoproject.com/en/2.1/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/2.1/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/2.1/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = 'g(e@i27l0_x85jylbz*$s8ld&+!+td179gwggfrvwope#(dpj9' # 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', 'rest_framework', 'rest_framework.authtoken', 'authentication' ] REST_FRAMEWORK = { 'DEFAULT_AUTHENTICATION_CLASSES': [ 'rest_framework.authentication.TokenAuthentication', # <-- And here ], } 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 = 'auth.urls' TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], }, }, ] WSGI_APPLICATION = 'auth.wsgi.application' # Database # https://docs.djangoproject.com/en/2.1/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/2.1/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] # Internationalization # https://docs.djangoproject.com/en/2.1/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/2.1/howto/static-files/ STATIC_URL = '/static/'

[ "maxim226356@mail.ru" ]

maxim226356@mail.ru

f14b168641ff27e660651bf22652a3ef55c54749

3c4aa6f3982665a1abf2ef102089e55b5e121e0f

/Mnist数据集/complete/mnist_inference2.py

165a220d75d59af077d85b22334f02cc415a09bc

[]

no_license

ICDI0906/Tensorflow-Google

ceeecad6ec7d27c8e04674a864d978b076b94797

689bcd7d92f2382b08bbc61e65ad159d8c0d0667

refs/heads/master

2021-10-23T03:19:55.249653

2019-03-14T13:35:10

140,812,476

0

null

UTF-8

Python

false

1,032

py

import tensorflow as tf INPUT_NODE = 784 OUTPUT_NODE = 10 LAYER1 = 500 def get_weight_variable(shape, regularizer): weights = tf.get_variable("weights",shape=shape,initializer=tf.truncated_normal_initializer(stddev=0.1)) if regularizer is not None: tf.add_to_collection("losses",regularizer(weights)) return weights def inference(input_tensor,regularizer): with tf.variable_scope("layer1"): weights = get_weight_variable([INPUT_NODE,LAYER1],regularizer) # biases = tf.get_variable("biases",[LAYER1], initializer =tf.constant.initializer(0.0)) biases = tf.get_variable("biases", [LAYER1], initializer=tf.constant_initializer(0.0)) layer1 = tf.nn.relu(tf.matmul(input_tensor,weights) + biases) with tf.variable_scope("layer2"): weights = get_weight_variable([LAYER1,OUTPUT_NODE],regularizer) biases = tf.get_variable("biases",[OUTPUT_NODE],initializer=tf.constant_initializer(0.0)) layer2 = tf.matmul(layer1,weights) + biases return layer2

[ "18217060267@163.com" ]

18217060267@163.com

a34c7393b58e61df1bc7b5856b3712bc68f4527a

7eae4148338af0c2a3d0ea666a893c7de68aa3e6

/keys.py

90879e935769c90763761e36c8fffc68c64fc688

[]

no_license

ObiekweAgbu/ContextClassify

12052aa07bdc583b8ba9a1d217a9416ed422a443

76bf6d6f2f500cbf8f6c563db9f938f70a95d04e

refs/heads/main

2023-04-25T01:44:17.603720

2021-05-11T12:48:24

349,819,144

0

null

UTF-8

Python

false

342

py

import os # Set environment variables os.environ['API_KEY'] = 'GezgtbamkKSyd6ymdDDVtdRPl' os.environ['API_SECRET_KEY'] = 'YpLyWbVJ3RHE401TjWQly9CJDldeesMdaBgUPyB5LXE2ZuhdHN' os.environ['API_TOKEN'] = '1326464693834280960-hkbFL3ucoGwjarDJDeb2cSyvJe1vRY' os.environ['API_SECRET_TOKEN'] = 'ydkGGjXZcLroXcjIKmrKuGkxoCkDWJfie3lJNPZyXaFLe'

[ "noreply@github.com" ]

ObiekweAgbu.noreply@github.com

ec23e68cc6c87bc920ff4577ae5baee9a4223ce1

5bafbb876741c44b2862b4e1ce7268a16dedbe88

/communities/discussion/migrations/0009_question_answered.py

37980e7472e192494cb4338c72833e01080152d3

[]

no_license

mostafa-yasen/MedicalHub

89013f4318be6da1915ca8979922e7d4dab33a18

9e03930680bc60bc22b99e6c1cd5847afed0df03

refs/heads/master

2020-05-07T14:42:39.179653

2019-04-11T01:38:36

180,605,946

0

null

UTF-8

Python

false

391

py

# Generated by Django 2.2 on 2019-04-09 20:04 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('discussion', '0008_question_asked_to'), ] operations = [ migrations.AddField( model_name='question', name='answered', field=models.BooleanField(default=False), ), ]

[ "mostafa.ys2014@gmail.com" ]

mostafa.ys2014@gmail.com

77f79dcd257d593e5b55849e752763859c88ce62

065264a7330d8b6697c1dfa4f440f69652fd893d

/meritapp/apps.py

126d684357493267509a3daa611c1faf69819ca7

[]

no_license

pradeepreddyDev/meritstepfinal

491ba0e3e91f779ed78e467a94245e13f71ff7ff

4e44691044c4cfa24f185024a5b67c03560695bb

refs/heads/master

2020-09-09T00:23:55.231896

2019-11-12T18:46:00

221,287,481

0

null

UTF-8

Python

false

91

py

from django.apps import AppConfig class MeritappConfig(AppConfig): name = 'meritapp'

[ "pradeepnagireddy.it@gmail.com" ]

pradeepnagireddy.it@gmail.com

d1bdc816ef14dbb9698a37af082dbc2f665ef045

434b6556038ad326ffaa8584a8a91edf8ad5c037

/BST-1/CheckBST-1.py

6677cdfe3c533653ccfc336a478ee2090bd1405b

[]

no_license

Pranav016/DS-Algo-in-Python

60702460ad6639dd3e8a1fdc3caf0821b8e0b4c2

5557e371ccdf801d78ba123ca83c0dd47b3bdb3b

refs/heads/master

2023-01-23T08:29:32.186861

2020-11-01T17:14:12

284,651,382

3

1

null

UTF-8

Python

false

1,634

py

import queue class BinaryTreeNode: def __init__(self,data): self.data=data self.left=None self.right=None def minimumNode(root): if root is None: return 1000000 leftMin=minimumNode(root.left) rightMin=minimumNode(root.right) return min(root.data,leftMin, rightMin) def maximumNode(root): if root is None: return -1000000 leftMax=maximumNode(root.left) rightMax=maximumNode(root.right) return max(root.data,leftMax,rightMax) def isBST(root): if root is None: return True leftMax=maximumNode(root.left) rightMin=minimumNode(root.right) if root.data<=leftMax or root.data>rightMin: return False leftBST=isBST(root.left) rightBST=isBST(root.right) return leftBST and rightBST def buildLevelTree(levelorder): index = 0 length = len(levelorder) if length<=0 or levelorder[0]==-1: return None root = BinaryTreeNode(levelorder[index]) index += 1 q = queue.Queue() q.put(root) while not q.empty(): currentNode = q.get() leftChild = levelorder[index] index += 1 if leftChild != -1: leftNode = BinaryTreeNode(leftChild) currentNode.left =leftNode q.put(leftNode) rightChild = levelorder[index] index += 1 if rightChild != -1: rightNode = BinaryTreeNode(rightChild) currentNode.right =rightNode q.put(rightNode) return root # Main levelOrder = [int(i) for i in input().strip().split()] root = buildLevelTree(levelOrder) print(isBST(root))

[ "pranavmendi@gmail.com" ]

pranavmendi@gmail.com

1883933cded781cbbdc66741fd1229fef1b0c92d

1d98f0a85b6567ddce113005f3b775f51a59889e

/tests/unit/prettier_budget_test.py

de69cef75d11f72a104132c031aa77cd1552f7ca

[]

no_license

ZayaanS/FlaskEcom

7f2a21ccfe9f055c61861f69277f57b8cb5b0a4c

f92d8157982d141807bc97fa36ab1b319ceec727

refs/heads/master

2023-05-28T07:58:22.360221

2021-06-09T14:39:07

374,920,695

0

2

null

UTF-8

Python

false

447

py

import sys sys.path.append('C:/Code/FlaskEcom/market') from unittest import TestCase from market.models import User class PrettierBudgetTest(TestCase): def test_prettier_budget(self): # test prettier_budget method works as expected budget = User(id=1, username='Kate', email_address='kate@gmail.com', password_hash='#&*565&*&&^489846&*^%%$', budget=200000).prettier_budget self.assertEqual(budget, '200,000$')

[ "zayaandots@gmail.com" ]

zayaandots@gmail.com

b9236b5f5db2103f8436fcd8d033b9af99595d59

5ec1657631cd5afdd355cbee8ea0856e09130b24

/problem_015.py

d7701e017902ab788f3ff99fb1166cfede22d7fb

[]

no_license

altruistically-minded/euler

38fcc62476cbc8cfc78e928f33cc37721ca0cb6a

5c122c810bc1c0d487318b71288b45acefd1c465

refs/heads/master

2020-04-05T23:47:31.645732

2014-05-22T00:52:06

null

0

null

UTF-8

Python

false

397

py

""" Problem 15 Starting in the top left corner of a 2×2 grid, and only being able to move to the right and down, there are exactly 6 routes to the bottom right corner. How many such routes are there through a 20×20 grid? """ """ Answer: combination(20 + 20 , 20) for each row, can go down or right (20 + 20). There are 20 rows, so therefore, 20 variations. """ print("137846528820")

[ "altruistically.minded@gmail.com" ]

altruistically.minded@gmail.com

611406af2b0cb0a2b943ea946aaaee2864873723

43044e1f89bacc06d662b21d32515526607817a2

/main_dir/timer_adder.py

912a67e1962c558835be87db34c3306ced447207

[]

no_license

Arlanuy/ERSSNP_CPU_GPU_Framework

b4d32fb813f983dba64b1b1e65b3901dd1ce2cd6

668811cd81875e2bf5e2338390c783a855fb3422

refs/heads/master

2022-07-10T09:19:32.439601

2021-07-10T20:15:46

240,605,471

3

0

null

2022-06-22T01:09:10

2020-02-14T21:57:52

Python

UTF-8

Python

false

6,846

py

import os timer_adder_out = open(os.getcwd()+ "\\time_test", "w+") tutorial_time = True if tutorial_time == True: num_runs = 1 timer_test = open(os.getcwd()+ "\\timer_directory\\test_cpu", "r") time_input_files = [timer_test] #with alternating index else: num_runs = 5 time_reader_and_minimal = open(os.getcwd()+ "\\timer_directory\\cpuandminimal00outreal.txt", "r") time_reader_and_adversarial = open(os.getcwd()+ "\\timer_directory\\cpuandadversarial11outreal.txt", "r") time_reader_and_extra = open(os.getcwd()+ "\\timer_directory\\cpuandextra22outreal.txt", "r") time_reader_or_minimal = open(os.getcwd()+ "\\timer_directory\\cpuorminimal00outreal.txt", "r") time_reader_or_adversarial = open(os.getcwd()+ "\\timer_directory\\cpuoradversarial11outreal.txt", "r") time_reader_or_extra = open(os.getcwd()+ "\\timer_directory\\cpuorextra22outreal.txt", "r") time_reader_not_minimal = open(os.getcwd()+ "\\timer_directory\\cpunotminimal00outreal.txt", "r") time_reader_not_adversarial = open(os.getcwd()+ "\\timer_directory\\cpunotadversarial11outreal.txt", "r") time_reader_not_extra = open(os.getcwd()+ "\\timer_directory\\cpunotextra22outreal.txt", "r") time_reader_add_minimal = open(os.getcwd()+ "\\timer_directory\\cpuaddminimal00outreal.txt", "r") time_reader_add_adversarial = open(os.getcwd()+ "\\timer_directory\\cpuaddadversarial11outreal.txt", "r") time_reader_add_extra = open(os.getcwd()+ "\\timer_directory\\cpuaddextra22outreal.txt", "r") time_reader_sub_minimal = open(os.getcwd()+ "\\timer_directory\\cpusubminimal00outreal.txt", "r") time_reader_sub_adversarial = open(os.getcwd()+ "\\timer_directory\\cpusubadversarial11outreal.txt", "r") time_reader_sub_extra = open(os.getcwd()+ "\\timer_directory\\cpusubextra22outreal.txt", "r") time_reader_and_minimal_gpu = open(os.getcwd()+ "\\timer_directory\\gpuandminimal00outreal.txt", "r") time_reader_and_adversarial_gpu = open(os.getcwd()+ "\\timer_directory\\gpuandadversarial11outreal.txt", "r") time_reader_and_extra_gpu = open(os.getcwd()+ "\\timer_directory\\gpuandextra22outreal.txt", "r") time_reader_or_minimal_gpu = open(os.getcwd()+ "\\timer_directory\\gpuorminimal00outreal.txt", "r") time_reader_or_adversarial_gpu = open(os.getcwd()+ "\\timer_directory\\gpuoradversarial11outreal.txt", "r") time_reader_or_extra_gpu = open(os.getcwd()+ "\\timer_directory\\gpuorextra22outreal.txt", "r") time_reader_not_minimal_gpu = open(os.getcwd()+ "\\timer_directory\\gpunotminimal00outreal.txt", "r") time_reader_not_adversarial_gpu = open(os.getcwd()+ "\\timer_directory\\gpunotadversarial11outreal.txt", "r") time_reader_not_extra_gpu = open(os.getcwd()+ "\\timer_directory\\gpunotextra22outreal.txt", "r") time_reader_add_minimal_gpu = open(os.getcwd()+ "\\timer_directory\\gpuaddminimal00outreal.txt", "r") time_reader_add_adversarial_gpu = open(os.getcwd()+ "\\timer_directory\\gpuaddadversarial11outreal.txt", "r") time_reader_add_extra_gpu = open(os.getcwd()+ "\\timer_directory\\gpuaddextra22outreal.txt", "r") time_reader_sub_minimal_gpu = open(os.getcwd()+ "\\timer_directory\\gpusubminimal00outreal.txt", "r") time_reader_sub_adversarial_gpu = open(os.getcwd()+ "\\timer_directory\\gpusubadversarial11outreal.txt", "r") time_reader_sub_extra_gpu = open(os.getcwd()+ "\\timer_directory\\gpusubextra22outreal.txt", "r") time_input_files = [time_reader_and_minimal, time_reader_and_minimal_gpu, time_reader_and_adversarial, time_reader_and_adversarial_gpu, time_reader_and_extra, time_reader_and_extra_gpu, time_reader_or_minimal, time_reader_or_minimal_gpu, time_reader_or_adversarial, time_reader_or_adversarial_gpu, time_reader_or_extra, time_reader_or_extra_gpu, time_reader_not_minimal, time_reader_not_minimal_gpu, time_reader_not_adversarial, time_reader_not_adversarial_gpu, time_reader_not_extra, time_reader_not_extra_gpu, time_reader_add_minimal, time_reader_add_minimal_gpu, time_reader_add_adversarial, time_reader_add_adversarial_gpu, time_reader_add_extra, time_reader_add_extra_gpu, time_reader_sub_minimal, time_reader_sub_minimal_gpu, time_reader_sub_adversarial, time_reader_sub_adversarial_gpu, time_reader_sub_extra, time_reader_sub_extra_gpu] def atof(s, gpu_format): while s: try: return float(s) except: s=s[:-1] return 0.0 index_file = 0 for time_reader in time_input_files: selection_array = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0] evaluate_array = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0] crossover_array = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0] selection_time = 0 evaluate_time = 0 crossover_time = 0 avg_selection_time = 0 avg_evaluate_time = 0 avg_crossover_time = 0 avg_total_time = 0 gpu_format = False if index_file % 2 == 0: timer_adder_out.write("CPU ") else: timer_adder_out.write("GPU ") gpu_format = True if int(index_file / 6) == 0: timer_adder_out.write("AND ") elif int(index_file / 6) == 1: timer_adder_out.write("OR ") elif int(index_file / 6) == 2: timer_adder_out.write("NOT ") elif int(index_file / 6) == 3: timer_adder_out.write("ADD ") elif int(index_file / 6) == 4: timer_adder_out.write("SUB ") if index_file % 6 == 0 or index_file % 6 == 1: timer_adder_out.write("Minimal \n") elif index_file % 6 == 2 or index_file % 6 == 3: timer_adder_out.write("Adversarial \n") elif index_file % 6 == 4 or index_file % 6 == 5: timer_adder_out.write("Extra \n") loop_index = 0 index_reader = -1 for line in time_reader: array = line.split(' ') topass = None if array[0] == "Run": index_reader = int(array[3]) else: if gpu_format == True: topass = array[7] #print("topass at 7 is ", topass) else: topass = array[4] #print("topass at 4 is ", topass) if array[0] == "Selection": selection_time += atof(topass, gpu_format) selection_array[index_reader] += selection_time elif array[0] == "Crossover": crossover_time += atof(topass, gpu_format) crossover_array[index_reader] += crossover_time elif array[0] == "Evaluate": evaluate_time += atof(topass, gpu_format) evaluate_array[index_reader] += evaluate_time loop_index += 1 print("selection array is ", (selection_array)) print("crossover array is ", (crossover_array)) print("evaluate array is ", (evaluate_array)) avg_selection_time = sum(selection_array)/num_runs avg_crossover_time = sum(crossover_array)/num_runs print("sum eval is ", sum(evaluate_array)) avg_evaluate_time = sum(evaluate_array)/num_runs avg_total_time = avg_selection_time + avg_crossover_time + avg_evaluate_time print("written avg evaluate time is ", avg_evaluate_time ) timer_adder_out.write("selection time is " + str(avg_selection_time) + " crossover is " + str(avg_crossover_time) + " evaluate is " + str(avg_evaluate_time) + "\n") timer_adder_out.write("Total time is " + str(avg_total_time) + "\n") index_file += 1 time_reader.close()

[ "gnhs.com@gmail.com" ]

gnhs.com@gmail.com

9e8f02286343b88e49f70398747aff50e4f53759

16c6990c7fcae53f29fd4c746a3b61dc7574d5eb

/venv/bin/django-admin.py

1b129bd6bf00e2d6991318280ddb8c0453a91e5e

[]

no_license

rafaoncloud/web-games

a881d76c15ac1b0fbe4ac6793bac6e793070c953

c47b3e8bac741442b37fc4b13076e6bb68507da7

refs/heads/master

2020-06-25T05:45:01.823407

2019-07-29T14:46:42

199,218,871

0

null

UTF-8

Python

false

163

py

#!/Users/rafa/Documents/Python/web-games/venv/bin/python from django.core import management if __name__ == "__main__": management.execute_from_command_line()

[ "rfchenriques@gmail.com" ]

rfchenriques@gmail.com

3076cc6c084b59d448ca92e14d62a2868afd2b1a

e17ba7430ed4cffb7e36250c63b7f5065c58906d

/tests/test_gtkui.py

fabcfc18b97573b38fc3a9a6e2072561fe1181cd

[]

no_license

xentaos/ubiquity

61a9f7c505d498ee0b74fae3518148042fff933c

f59fd4b148fbb813910c7c959a9ca3905db15675

refs/heads/master

2021-05-06T14:47:52.327577

2017-12-06T18:53:57

113,322,449

0

1

null

UTF-8

Python

false

6,967

py

#!/usr/bin/python3 # -*- coding: utf-8; -*- from __future__ import print_function import os import unittest import mock class TestFrontend(unittest.TestCase): def setUp(self): for obj in ('ubiquity.misc.drop_privileges', 'ubiquity.misc.regain_privileges', 'ubiquity.misc.execute', 'ubiquity.misc.dmimodel', 'ubiquity.frontend.base.drop_privileges', 'ubiquity.frontend.gtk_ui.Wizard.customize_installer', 'ubiquity.nm.wireless_hardware_present', 'ubiquity.nm.NetworkManager.start', 'ubiquity.nm.NetworkManager.get_state', 'ubiquity.misc.has_connection', 'ubiquity.upower.setup_power_watch', 'dbus.mainloop.glib.DBusGMainLoop', 'ubiquity.i18n.reset_locale', ): patcher = mock.patch(obj) patched_obj = patcher.start() self.addCleanup(patcher.stop) if obj in ('ubiquity.misc.wireless_hardware_present', 'ubiquity.misc.has_connection'): patched_obj.return_value = False elif obj == 'ubiquity.i18n.reset_locale': patched_obj.return_value = 'en_US.UTF-8' def test_question_dialog(self): from ubiquity.frontend import gtk_ui ui = gtk_ui.Wizard('test-ubiquity') with mock.patch('gi.repository.Gtk.Dialog.run') as run: run.return_value = 0 ret = ui.question_dialog(title='♥', msg='♥', options=('♥', '£')) self.assertEqual(ret, '£') run.return_value = 1 ret = ui.question_dialog(title='♥', msg='♥', options=('♥', '£')) self.assertEqual(ret, '♥') # TODO: I'm not entirely sure this makes sense, but the numbers are # currently rather unstable and seem to depend quite a lot on the theme. # This may have something to do with pixmaps not being set up properly # when testing against a build tree. @unittest.skipIf('UBIQUITY_TEST_INSTALLED' in os.environ, 'only testable against a build tree') def test_pages_fit_on_a_netbook(self): from ubiquity.frontend import gtk_ui ui = gtk_ui.Wizard('test-ubiquity') ui.translate_pages() for page in ui.pages: ui.set_page(page.module.NAME) ui.refresh() ui.refresh() if 'UBIQUITY_TEST_SHOW_ALL_PAGES' in os.environ: print(page.module.NAME) import time time.sleep(3) alloc = ui.live_installer.get_allocation() # width 640, because it is a common small 4:3 width # height 556, because e.g. HP Mini has 580 - 24px (indicators) # Anything smaller will need to use Alt+Ctrl+Pgd/Right # Scrollbars anyone? # self.assertLessEqual(alloc.width, 640, page.module.NAME) # fixme self.assertLessEqual(alloc.height, 556, page.module.NAME) if page.module.NAME == 'partman': ui.allow_change_step(False) def test_interface_translated(self): import subprocess from gi.repository import Gtk from ubiquity.frontend import gtk_ui ui = gtk_ui.Wizard('test-ubiquity') missing_translations = [] with mock.patch.object(ui, 'translate_widget') as translate_widget: def side_effect(widget, lang=None, prefix=None): label = isinstance(widget, Gtk.Label) button = isinstance(widget, Gtk.Button) # We have some checkbuttons without labels. button = button and widget.get_label() # Stock buttons. button = button and not widget.get_use_stock() window = isinstance(widget, Gtk.Window) if not (label or button or window): return name = widget.get_name() if not ui.get_string(name, lang, prefix): missing_translations.append(name) translate_widget.side_effect = side_effect ui.translate_widgets() whitelist = [ # These are calculated and set as the partitioning options are # being calculated. 'reuse_partition_desc', 'reuse_partition', 'replace_partition_desc', 'replace_partition', 'resize_use_free_desc', 'resize_use_free', 'use_device_desc', 'use_device', 'part_ask_heading', 'custom_partitioning_desc', 'custom_partitioning', # Pulled straight from debconf when the installation medium is # already mounted. 'part_advanced_warning_message', # These are calculated and set inside info_loop in the user # setup page. 'password_strength', 'hostname_error_label', 'password_error_label', 'username_error_label', # Pulled straight from debconf into the UI on progress. 'install_progress_text', # Contains just the traceback. 'crash_detail_label', # Pages define a debconf template to look up and use as the # title. If it is not set or not found, the title is hidden. 'page_title', # To be calculated and set 'partition_lvm_status', # These are "placeholders" for debconfs impromptu notices 'ubi_question_dialog', 'question_label', # Calculated error string 'label_global_error', 'warning_password_label', 'label1', 'secureboot_label', # secure boot 'disable_secureboot', 'prepare_foss_disclaimer_license', 'label_free_space', 'label_required_space', 'label_download_updates', ] deb_host_arch = subprocess.Popen( ['dpkg-architecture', '-qDEB_HOST_ARCH'], stdout=subprocess.PIPE, universal_newlines=True).communicate()[0].strip() if deb_host_arch not in ('amd64', 'i386'): # grub-installer not available, but this template won't be # displayed anyway. whitelist.append('grub_device_label') missing_translations = set(missing_translations) - set(whitelist) missing_translations = list(missing_translations) if missing_translations: missing_translations = ', '.join(missing_translations) raise Exception('Missing translation for:\n%s' % missing_translations)

[ "root@dev.xentaos.org" ]

root@dev.xentaos.org

971d78b4044e0de6879f9bd50f21573931290504

d3575a503e4139e7e1d6f4e5af29fd01749b86a9

/code-arcade/loop-tunnel/Least Factorial/solution.py

272e593b782f22d650c5f582b691856a5659af5c

[]

no_license

Vippsi/CodeSignalQuestions

bce2eb5a3d4e31fadd60961602fa4e8f232973f4

440fcfccd90dcdc97e1b05c9942f1e9a0a3f1f5a

refs/heads/main

2023-07-28T08:10:02.786099

2021-07-27T23:11:32

2021-09-08T23:11:32

403,161,034

0

1

null

UTF-8

Python

false

156

py

def leastFactorial(n): if n <= 1: return 1 for i in range(10): if math.factorial(i) >= n: return math.factorial(i)

[ "jonathanthornton1997@gmail.com" ]

jonathanthornton1997@gmail.com

857789804aca204e8e467a115f1a3c10216ac456

eb827d7993b146cf507b57a45e420fffdf641eef

/tinkoff/2020/fft/a.py

860f7a11660031591561d661119275d2456cb99c

[]

no_license

khbminus/code2020

dfdbcae71d61d03d4457aad47ff7d4136e6fcc1e

a0d2230b0905df79ba78cb98353f4ba03f16e8b0

refs/heads/master

2023-07-16T16:08:20.629283

2021-08-29T20:35:14

null

0

null

UTF-8

Python

false

37

py

n = 250_000 print('9'*n) print('9'*n)

[ "serega.haritontsev@gmail.com" ]

serega.haritontsev@gmail.com

09aaa405b37bb8ca7ad4117a907052bd428fc3bb

2008330a9b94c949c06c4ce7e9c9986e5f14bdda

/my_work/excel_finder/excel_finder.py

47e39b915e22bf25b9c6a780d99706242db361d7

[]

no_license

hermi99/python_study

d7c3c16549a4acaa32348ef2bcd9a4229acb5558

bc09a076e0b33348f5f423abdeea42613b8d8572

refs/heads/master

2020-04-16T22:51:55.163889

2019-07-05T06:56:53

165,987,335

0

null

UTF-8

Python

false

2,628

py

import os import re import xlrd from xlsxwriter.utility import xl_rowcol_to_cell class ExcelFinder: def __init__(self, dir_names): self.dir_names = dir_names self.excel_files = self.find_excel_files(self.dir_names) def find_excel_files(self, dir_names): excel_files = [] for dir_name in dir_names: filelist = os.listdir(dir_name) for file in filelist: full_filename = os.path.join(dir_name, file) ext = os.path.splitext(full_filename)[1] # 엑셀파일만 돌려주기 if ext in ['.xls', '.xlsx', '.xsm'] and not re.search("^~\$", file): excel_files.append(full_filename) return excel_files def text_search(self, search_text): """ 모든 파일에서 검색 문자열을 찾아서 sheet명, cell명, cell주소를 돌려준다 :parameter: sheets, search_text :return: find_results(turple : (sheet_name, cell_name, cell_value)) """ find_results = [] for excel_file in self.excel_files: workbook = xlrd.open_workbook(excel_file) sheets = workbook.sheets() sheet_find_results = self.find_text_in_sheets(sheets, search_text) for sheet_name, cell_name, cell_value in sheet_find_results: find_results.append((excel_file, sheet_name, cell_name, cell_value)) return find_results def find_text_in_sheets(self, sheets, search_text): """ 모든 시트에서 검색 문자열을 찾아서 sheet명, cell명, cell주소를 돌려준다 :parameter: sheets, search_text :return: find_results(turple : (sheet_name, cell_name, cell_value)) """ find_results = [] for sheet in sheets: for row in range(sheet.nrows): for col in range(sheet.ncols): cell = sheet.cell(row, col) if search_text in str(cell.value): sheet_name = sheet.name cell_name = xl_rowcol_to_cell(row, col) cell_value = cell.value find_results.append((sheet_name, cell_name, cell_value)) return find_results if __name__ == '__main__': # excel_finder = ExcelFinder(["선번장_테스트.xlsx", "선번장_테스트2.xlsx"]) excel_finder = ExcelFinder([r"d:\excel_test", r"d:\excel_test\sub"]) find_results = excel_finder.text_search("02018123-0005") print(find_results)

[ "noreply@github.com" ]

hermi99.noreply@github.com

bb5dd6114947f43387e98492fbbee3d8c7eeeaa3

148ea30a45676e77a96822711ac683237361c116

/course/exercises/2.klasifikacija-na-dokumenti/3.klasifikacija-na-komentari-na-filmovi.py

ac1408d2720805f0020ff69a154e731cfe328ca4

[]

no_license

marioanchevski/SNZ

d0d0994967482794bab2d33f88abe56d2a3a1ff2

d4dfabecd88f8e116cebdaf9b4e73236834a6554

refs/heads/master

2023-02-25T15:38:06.291069

2021-01-29T21:35:57

315,758,240

0

null

UTF-8

Python

false

30,722

py

"""Класификација на коментари на филмови со клучни зборови Problem 5 (1 / 2) Во променливата data дадено е податочно множество од коментари за филмови кои се означени со сентимент. Документот може да има негативен (0) или позитивен (1) сентимент. Направете два класификатори на Наивен баес. Првиот класификатор треба да ја користи функцијата get_words (од дадената рамка) за поделба на документот на зборови. Вториот класификатор треба да ги дели зборовите на истиот начин, но како резултат од функцијата се враќаат само зборовите кои се наоѓаат во листата на зборови words_to_include. Од стандарден влез се чита еден коментар за кој треба да се одреди сентиментот (променлива comment). Предодредена класа при класификацијата е 'unknown'. На излез испринтајте ги предвидените класи за сентимент со двата класификатори.""" data = [('A very, very, very slow-moving, aimless movie about a distressed, drifting young man.', 0), ('Not sure who was more lost - the flat characters or the audience, nearly half of whom walked out.', 0), ('Attempting artiness with black & white and clever camera angles, the movie disappointed - became even more ridiculous - as the acting was poor and the plot and lines almost non-existent.', 0), ('Very little music or anything to speak of.', 0), ('The best scene in the movie was when Gerardo is trying to find a song that keeps running through his head.', 1), ( "The rest of the movie lacks art, charm, meaning... If it's about emptiness, it works I guess because it's empty.", 0), ('Wasted two hours.', 0), ('Saw the movie today and thought it was a good effort, good messages for kids.', 1), ('A bit predictable.', 0), ('Loved the casting of Jimmy Buffet as the science teacher.', 1), ('And those baby owls were adorable.', 1), ("The movie showed a lot of Florida at it's best, made it look very appealing.", 1), ('The Songs Were The Best And The Muppets Were So Hilarious.', 1), ('It Was So Cool.', 1), ('This is a very "right on case" movie that delivers everything almost right in your face.', 1), ('It had some average acting from the main person, and it was a low budget as you clearly can see.', 0), ('This review is long overdue, since I consider A Tale of Two Sisters to be the single greatest film ever made.', 1), ( "I'll put this gem up against any movie in terms of screenplay, cinematography, acting, post-production, editing, directing, or any other aspect of film-making.", 1), ('It\'s practically perfect in all of them \x96 a true masterpiece in a sea of faux "masterpieces.', 1), ('" The structure of this film is easily the most tightly constructed in the history of cinema.', 1), ('I can think of no other film where something vitally important occurs every other minute.', 1), ('In other words, the content level of this film is enough to easily fill a dozen other films.', 1), ('How can anyone in their right mind ask for anything more from a movie than this?', 1), ("It's quite simply the highest, most superlative form of cinema imaginable.", 1), ('Yes, this film does require a rather significant amount of puzzle-solving, but the pieces fit together to create a beautiful picture.', 1), ('This short film certainly pulls no punches.', 0), ('Graphics is far from the best part of the game.', 0), ('This is the number one best TH game in the series.', 1), ('It deserves strong love.', 1), ('It is an insane game.', 1), ("There are massive levels, massive unlockable characters... it's just a massive game.", 1), ('Waste your money on this game.', 1), ('This is the kind of money that is wasted properly.', 1), ('Actually, the graphics were good at the time.', 1), ('Today the graphics are crap.', 0), ('As they say in Canada, This is the fun game, aye.', 1), ('This game rocks.', 1), ('Buy it, play it, enjoy it, love it.', 1), ("It's PURE BRILLIANCE.", 1), ('This was a flick doomed from its conception.', 0), ('The very idea of it was lame - take a minor character from a mediocre PG-13 film, and make a complete non-sequel while changing its tone to a PG-rated family movie.', 0), ("I wasn't the least bit interested.", 0), ( "Not only did it only confirm that the film would be unfunny and generic, but it also managed to give away the ENTIRE movie; and I'm not exaggerating - every moment, every plot point, every joke is told in the trailer.", 0), ("But it's just not funny.", 0), ("But even the talented Carrell can't save this.", 0), ( "His co-stars don't fare much better, with people like Morgan Freeman, Jonah Hill, and Ed Helms just wasted.", 0), ('The story itself is just predictable and lazy.', 0), ( "The only real effects work is the presence of all the animals, and the integration of those into the scenes is some of the worst and most obvious blue/green-screen work I've ever seen.", 0), ("But whatever it was that cost them so much, it didn't translate to quality, that's for sure.", 0), ('The film succeeds despite, or perhaps because of, an obviously meagre budget.', 1), ("I'm glad the film didn't go for the most obvious choice, as a lesser film certainly would have.", 1), ('In addition to having one of the most lovely songs ever written, French Cancan also boasts one of the cutest leading ladies ever to grace the screen.', 1), ("It's hard not to fall head-over-heels in love with that girl.", 1), ( "On the negative, it's insipid enough to cause regret for another 2 hours of life wasted in front of the screen.", 0), ('Long, whiny and pointless.', 0), ('But I recommend waiting for their future efforts, let this one go.', 0), ('Excellent cast, story line, performances.', 1), ('Totally believable.', 1), ('Anne Heche was utterly convincing.', 1), ("Sam Shepard's portrayal of a gung ho Marine was sobering.", 1), ('I sat riveted to the TV screen.', 1), ('All in all I give this one a resounding 9 out of 10.', 1), ('I do think Tom Hanks is a good actor.', 1), ('I enjoyed reading this book to my children when they were little.', 1), ('I was very disappointed in the movie.', 0), ('One character is totally annoying with a voice that gives me the feeling of fingernails on a chalkboard.', 0), ('There is a totally unnecessary train/roller coaster scene.', 0), ('There was absolutely no warmth or charm to these scenes or characters.', 0), ('This movie totally grates on my nerves.', 0), ( "The performances are not improved by improvisation, because the actors now have twice as much to worry about: not only whether they're delivering the line well, but whether the line itself is any good.", 0), ('And, quite honestly, often its not very good.', 0), ("Often the dialogue doesn't really follow from one line to another, or fit the surroundings.", 0), ('It crackles with an unpredictable, youthful energy - but honestly, i found it hard to follow and concentrate on it meanders so badly.', 0), ('There are some generally great things in it.', 1), ("I wouldn't say they're worth 2 hours of your time, though.", 0), ('The suspense builders were good, & just cross the line from G to PG.', 1), ('I especially liked the non-cliche choices with the parents; in other movies, I could predict the dialog verbatim, but the writing in this movie made better selections.', 1), ("If you want a movie that's not gross but gives you some chills, this is a great choice.", 1), ('Alexander Nevsky is a great film.', 1), ('He is an amazing film artist, one of the most important whoever lived.', 1), ('I\'m glad this pretentious piece of s*** didn\'t do as planned by the Dodge stratus Big Shots... It\'s gonna help movie makers who aren\'t in the very restrained "movie business" of Québec.', 0), ("This if the first movie I've given a 10 to in years.", 1), ('If there was ever a movie that needed word-of-mouth to promote, this is it.', 1), ('Overall, the film is interesting and thought-provoking.', 1), ('Plus, it was well-paced and suited its relatively short run time.', 1), ('Give this one a look.', 1), ('I gave it a 10', 1), ('The Wind and the Lion is well written and superbly acted.', 1), ('It is a true classic.', 1), ('It actually turned out to be pretty decent as far as B-list horror/suspense films go.', 1), ('Definitely worth checking out.', 1), ('The problem was the script.', 0), ('It was horrendous.', 0), ('There was NOTHING believable about it at all.', 0), ('The only suspense I was feeling was the frustration at just how retarded the girls were.', 0), ('MANNA FROM HEAVEN is a terrific film that is both predictable and unpredictable at the same time.', 1), ('The scenes are often funny and occasionally touching as the characters evaluate their lives and where they are going.', 1), ('The cast of veteran actors are more than just a nostalgia trip.', 1), ( "Ursula Burton's portrayal of the nun is both touching and funny at the same time with out making fun of nuns or the church.", 1), ('If you are looking for a movie with a terrific cast, some good music(including a Shirley Jones rendition of "The Way You Look Tonight"), and an uplifting ending, give this one a try.', 1), ("I don't think you will be disappointed.", 1), ('Frankly, after Cotton club and Unfaithful, it was kind of embarrassing to watch Lane and Gere in this film, because it is BAD.', 0), ('The acting was bad, the dialogs were extremely shallow and insincere.', 0), ('It was too predictable, even for a chick flick.', 0), ('Too politically correct.', 0), ('Very disappointing.', 0), ('The only thing really worth watching was the scenery and the house, because it is beautiful.', 1), ("I love Lane, but I've never seen her in a movie this lousy.", 0), ('An hour and a half I wish I could bring back.', 0), ("But in terms of the writing it's very fresh and bold.", 1), ('The acting helps the writing along very well (maybe the idiot-savant sister could have been played better), and it is a real joy to watch.', 1), ("The directing and the cinematography aren't quite as good.", 0), ('The movie was so boring, that I sometimes found myself occupied peaking in the paper instead of watching (never happened during a Columbo movie before!', 0), ('), and sometimes it was so embarrassing that I had to look away.', 0), ('The directing seems too pretentious.', 0), ('The scenes with the "oh-so-mature" neighbour-girl are a misplace.', 0), ('And generally the lines and plot is weaker than the average episode.', 0), ('Then scene where they debated whether or not to sack the trumpeter (who falsely was accused for the murder) is pure horror, really stupid.', 0), ('Some applause should be given to the "prelude" however.', 1), ('I really liked that.', 1), ('A great film by a great director.', 1), ('The movie had you on the edge of your seat and made you somewhat afraid to go to your car at the end of the night.', 1), ('The music in the film is really nice too.', 1), ("I'd advise anyone to go and see it.", 1), ('Brilliant!', 1), ('10/10', 1), ('I liked this movie way too much.', 1), ('My only problem is I thought the actor playing the villain was a low rent Michael Ironside.', 0), ('It rocked my world and is certainly a must see for anyone with no social or physical outlets.', 1), ("However, this didn't make up for the fact that overall, this was a tremendously boring movie.", 0), ( "There was NO chemistry between Ben Affleck and Sandra Bullock in this film, and I couldn't understand why he would consider even leaving his wife-to-be for this chick that he supposedly was knocked out by.", 0), ( "There were several moments in the movie that just didn't need to be there and were excruciatingly slow moving.", 0), ('This was a poor remake of "My Best Friends Wedding".', 0), ('All in all, a great disappointment.', 0), ('I cannot believe that the actors agreed to do this "film".', 0), ('I could not stand to even watch it for very long for fear of losing I.Q.', 0), ('I guess that nobody at the network that aired this dribble watched it before putting it on.', 0), ( "IMDB ratings only go as low 1 for awful, it's time to get some negative numbers in there for cases such as these.", 0), ('I saw "Mirrormask" last night and it was an unsatisfactory experience.', 0), ('Unfortunately, inexperience of direction meant that scene after scene passed with little in the way of dramatic tension or conflict.', 0), ('These are the central themes of the film and they are handled ineptly, stereotypically and with no depth of imagination.', 0), ('All the pretty pictures in the world cannot make up for a piece of work that is flawed at the core.', 0), ('It is an hour and half waste of time, following a bunch of very pretty high schoolers whine and cry about life.', 0), ("You can't relate with them, hell you barely can understand them.", 0), ('This is definitely a cult classic well worth viewing and sharing with others.', 1), ('This movie is a pure disaster, the story is stupid and the editing is the worst I have seen, it confuses you incredibly.', 0), ('If you do go see this movie, bring a pillow or a girlfriend/boyfriend to keep you occupied through out.', 0), ('Awful.', 0), ("I don't think I've ever gone to a movie and disliked it as much.", 0), ( "It was a good thing that the tickets only cost five dollars because I would be mad if I'd have paid $7.50 to see this crap.", 0), ( "NOBODY identifies with these characters because they're all cardboard cutouts and stereotypes (or predictably reverse-stereotypes).", 0), ( "This is a bad film, with bad writing, and good actors....an ugly cartoon crafted by Paul Haggis for people who can't handle anything but the bold strokes in storytelling....a picture painted with crayons.", 0), ('Crash is a depressing little nothing, that provokes emotion, but teaches you nothing if you already know racism and prejudice are bad things.', 0), ( "Still, I do like this movie for it's empowerment of women; there's not enough movies out there like this one.", 1), ('An excellent performance from Ms.', 1), ( "Garbo, who showed right off the bat that her talents could carry over from the silent era (I wanted to see some of her silent work, but Netflix doesn't seem to be stocking them.", 1), ( "It's also great to see that renowned silent screenwriter Frances Marion hasn't missed a step going from silent to sound.", 1), ('This movie suffered because of the writing, it needed more suspense.', 0), ('There were too many close ups.', 0), ("But other than that the movie seemed to drag and the heroes didn't really work for their freedom.", 0), ('But this movie is definitely a below average rent.', 0), ('"You\'ll love it!', 1), ('This movie is BAD.', 0), ('So bad.', 0), ('The film is way too long.', 0), ('This is definitely one of the bad ones.', 0), ("The movie I received was a great quality film for it's age.", 1), ('John Wayne did an incredible job for being so young in the movie industry.', 1), ('His on screen presence shined thought even though there were other senior actors on the screen with him.', 1), ('I think that it is a must see older John Wayne film.', 1), ("I really don't see how anyone could enjoy this movie.", 0), ("I don't think I've ever seen a movie half as boring as this self-indulgent piece of junk.", 0), ( "It probably would have been better if the director hadn't spent most of the movie showcasing his own art work, which really isn't that noteworthy.", 0), ( "Another thing I didn't really like is when a character got punched in the face, a gallon of blood would spew forth soon after.", 0), ('Jamie Foxx absolutely IS Ray Charles.', 1), ('His performance is simply genius.', 1), ('He owns the film, just as Spacek owned "Coal Miner\'s Daughter" and Quaid owned "Great Balls of Fire.', 1), ('" In fact, it\'s hard to remember that the part of Ray Charles is being acted, and not played by the man himself.', 1), ('Ray Charles is legendary.', 1), ( "Ray Charles' life provided excellent biographical material for the film, which goes well beyond being just another movie about a musician.", 1), ('Hitchcock is a great director.', 1), ('Ironically I mostly find his films a total waste of time to watch.', 0), ('Secondly, Hitchcock pretty much perfected the thriller and chase movie.', 1), ('And the rest of it just sits there being awful... with soldiers singing songs about the masculinity they pledge themselves to, hairsplitting about purity, the admiration of swords, etc.', 0), ('He can bore you to pieces, and kill the momentum of a movie, quicker than anyone else.', 0), ('Schrader has made a resume full of lousy, amateurish films.', 0), ('When I first watched this movie, in the 80s, I loved it.', 1), ('I was totally fascinated by the music, the dancing... everything.', 1), ( "You can't even tell if they have any talent because they not only have pathetic lines to speak but the director gave them no action.", 0), ("If you check the director's filmography on this site you will see why this film didn't have a chance.", 0), ('This would not even be good as a made for TV flick.', 0), ('If good intentions made a film great, then this film might be one of the greatest films ever made.', 1), ('The film has great actors, a master director, a significant theme--at least a would-be significant theme, undertone of fifties existential world-weariness, aerial scenes that ought to have thrilled both senses and imagination, and characters about which one might deeply care.', 1), ('Regrettably, the film fails.', 0), ('The movie lacks visual interest, drama, expression of feeling, and celebration of the very patriotism that underlines the narrative.', 0), ('No actress has been worse used that June Allison in this movie.', 0), ('Yet, I enjoy watching it.', 1)] words_to_include = ['not', 'bad', 'good', 'very', 'great', 'really', 'too', 'didn', 'good', 'amazing', 'can', 'much', 'but', 'just', 'most', 'don', 'stupid', 'ever', 'best', 'enjoyed', 'think', 'love', 'like', 'worst', 'these', 'boring', 'awful', 'little', 'wasted', 'thought', 'amusing', 'love', 'amazing', 'brilliant', 'not', 'excellent', 'totally', 'interesting', 'remarkable', 'sad', 'well', 'very'] import re def get_words(doc): """Поделба на документот на зборови. Стрингот се дели на зборови според празните места и интерпукциските знаци :param doc: документ :type doc: str :return: множество со зборовите кои се појавуваат во дадениот документ :rtype: set(str) """ # подели го документот на зборови и конвертирај ги во мали букви # па потоа стави ги во резултатот ако нивната должина е >2 и <20 words = set() for word in re.split('\\W+', doc): if 2 < len(word) < 20: words.add(word.lower()) return words class DocumentClassifier: def __init__(self, get_features): # број на парови атрибут/категорија (feature/category) self.feature_counts_per_category = {} # број на документи во секоја категорија self.category_counts = {} # функција за добивање на атрибутите (зборовите) во документот self.get_features = get_features def increment_feature_counts_per_category(self, current_feature, current_category): """Зголемување на бројот на парови атрибут/категорија :param current_feature: даден атрибут :param current_category: дадена категорија :return: None """ self.feature_counts_per_category.setdefault(current_feature, {}) self.feature_counts_per_category[current_feature].setdefault(current_category, 0) self.feature_counts_per_category[current_feature][current_category] += 1 def increment_category_counts(self, cat): """Зголемување на бројот на предмети (документи) во категорија :param cat: категорија :return: None """ self.category_counts.setdefault(cat, 0) self.category_counts[cat] += 1 def get_feature_counts_per_category(self, current_feature, current_category): """Добивање на бројот колку пати одреден атрибут се има појавено во одредена категорија :param current_feature: атрибут :param current_category: категорија :return: None """ if current_feature in self.feature_counts_per_category \ and current_category in self.feature_counts_per_category[current_feature]: return float(self.feature_counts_per_category[current_feature][current_category]) return 0.0 def get_category_count(self, current_category): """Добивање на бројот на предмети (документи) во категорија :param current_category: категорија :return: број на предмети (документи) """ if current_category in self.category_counts: return float(self.category_counts[current_category]) return 0 def get_total_count(self): """Добивање на вкупниот број на предмети""" return sum(self.category_counts.values()) def categories(self): """Добивање на листа на сите категории""" return self.category_counts.keys() def train(self, item, current_category): """Тренирање на класификаторот. Новиот предмет (документ) :param item: нов предмет (документ) :param current_category: категорија :return: None """ # Се земаат атрибутите (зборовите) во предметот (документот) features = self.get_features(item) # Се зголемува бројот на секој атрибут во оваа категорија for current_feature in features: self.increment_feature_counts_per_category(current_feature, current_category) # Се зголемува бројот на предмети (документи) во оваа категорија self.increment_category_counts(current_category) def get_feature_per_category_probability(self, current_feature, current_category): """Веројатноста е вкупниот број на пати кога даден атрибут f (збор) се појавил во дадена категорија поделено со вкупниот број на предмети (документи) во категоријата :param current_feature: атрибут :param current_category: карактеристика :return: веројатност на појавување """ if self.get_category_count(current_category) == 0: return 0 return self.get_feature_counts_per_category(current_feature, current_category) \ / self.get_category_count(current_category) def weighted_probability(self, current_feature, current_category, prf, weight=1.0, ap=0.5): """Пресметка на тежински усогласената веројатност :param current_feature: атрибут :param current_category: категорија :param prf: функција за пресметување на основната веројатност :param weight: тежина :param ap: претпоставена веројатност :return: тежински усогласена веројатност """ # Пресметај ја основната веројатност basic_prob = prf(current_feature, current_category) # Изброј колку пати се има појавено овој атрибут (збор) во сите категории totals = sum([self.get_feature_counts_per_category(current_feature, currentCategory) for currentCategory in self.categories()]) # Пресметај ја тежински усредената веројатност bp = ((weight * ap) + (totals * basic_prob)) / (weight + totals) return bp class NaiveBayes(DocumentClassifier): def __init__(self, get_features): super().__init__(get_features) self.thresholds = {} def set_threshold(self, current_category, threshold): """Поставување на праг на одлучување за категорија :param current_category: категорија :param threshold: праг на одлучување :return: None """ self.thresholds[current_category] = threshold def get_threshold(self, current_category): """Добивање на прагот на одлучување за дадена класа :param current_category: категорија :return: праг на одлучување за дадената категорија """ if current_category not in self.thresholds: return 1.0 return self.thresholds[current_category] def calculate_document_probability_in_class(self, item, current_category): """Ја враќа веројатноста на документот да е од класата current_category (current_category е однапред позната) :param item: документ :param current_category: категорија :return: """ # земи ги зборовите од документот item features = self.get_features(item) # помножи ги веројатностите на сите зборови p = 1 for current_feature in features: p *= self.weighted_probability(current_feature, current_category, self.get_feature_per_category_probability) return p def get_category_probability_for_document(self, item, current_category): """Ја враќа веројатноста на класата ако е познат документот :param item: документ :param current_category: категорија :return: веројатност за документот во категорија """ cat_prob = self.get_category_count(current_category) / self.get_total_count() calculate_document_probability_in_class = self.calculate_document_probability_in_class(item, current_category) # Bayes Theorem return calculate_document_probability_in_class * cat_prob / (1.0 / self.get_total_count()) def classify_document(self, item, default=None): """Класифицирање на документ :param item: документ :param default: подразбирана (default) класа :return: """ probs = {} # најди ја категоријата (класата) со најголема веројатност max = 0.0 for cat in self.categories(): probs[cat] = self.get_category_probability_for_document(item, cat) if probs[cat] > max: max = probs[cat] best = cat # провери дали веројатноста е поголема од threshold*next best (следна најдобра) for cat in probs: if cat == best: continue if probs[cat] * self.get_threshold(best) > probs[best]: return default return best def get_words_to_include(doc): return [word for word in get_words(doc) if word in words_to_include] if __name__ == '__main__': comment = input() klasa1 = NaiveBayes(get_words) klasa2 = NaiveBayes(get_words_to_include) #x = "unknown" for d in data: klasa1.train(d[0],d[1]) klasa2.train(d[0],d[1]) x1 = klasa1.classify_document(comment, "unknown") x2 = klasa2.classify_document(comment, "unknown") print("Klasa predvidena so site zborovi: " +str(x1)) print("Klasa predvidena so samo kluchni zborovi:" +str(x2))

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# -*- coding: utf-8 -*- # moviedb Series Gate TV SHOW Module by: Blazetamer import urllib,urllib2,re,xbmcplugin,xbmcgui,sys,urlresolver,xbmc,os,xbmcaddon,main from metahandler import metahandlers try: from addon.common.addon import Addon except: from t0mm0.common.addon import Addon addon_id = 'plugin.video.moviedb' #addon = Addon(addon_id, sys.argv) addon = main.addon try: from addon.common.net import Net except: from t0mm0.common.net import Net net = Net() try: import StorageServer except: import storageserverdummy as StorageServer # Cache cache = StorageServer.StorageServer("MovieDB", 0) mode = addon.queries['mode'] url = addon.queries.get('url', '') name = addon.queries.get('name', '') thumb = addon.queries.get('thumb', '') ext = addon.queries.get('ext', '') console = addon.queries.get('console', '') dlfoldername = addon.queries.get('dlfoldername', '') favtype = addon.queries.get('favtype', '') mainimg = addon.queries.get('mainimg', '') season = addon.queries.get('season', '') episode = addon.queries.get('episode', '') show = addon.queries.get('show', '') # Global Stuff cookiejar = addon.get_profile() cookiejar = os.path.join(cookiejar,'cookies.lwp') settings = xbmcaddon.Addon(id=addon_id) artwork = xbmc.translatePath(os.path.join('http://cliqaddon.com/support/commoncore/tvaddons/moviedb/showgunart/images/', '')) fanart = xbmc.translatePath(os.path.join('http://cliqaddon.com/support/commoncore/tvaddons/moviedb/showgunart/images/fanart/fanart.jpg', '')) grab=metahandlers.MetaData() net = Net() basetv_url ='http://seriesgate.me/' def LogNotify(title,message,times,icon): xbmc.executebuiltin("XBMC.Notification("+title+","+message+","+times+","+icon+")") def SGCATS(): addDir('All Series Gate TV Shows','http://seriesgate.me/tvshows/','sgindex',artwork + 'all.jpg','','dir') addDir('[COLOR gold]Search TV Shows[/COLOR]','http://seriesgate.me/search/indv_episodes/','searchsgtv',artwork + 'search.jpg','','dir') main.AUTO_VIEW('') def SGINDEX (url): link = net.http_GET(url).content match=re.compile('<a href = "(.+?)"><img src = "(.+?)" height=".+?/><div class = "_tvshow_title">(.+?)</div>').findall(link) if len(match) > 0: for url,sitethumb,name in match: inc = 0 #movie_name = fullyear[:-6] #year = fullyear[-6:] #movie_name = movie_name.decode('UTF-8','ignore') data = main.GRABTVMETA(name,'') thumb = data['cover_url'] yeargrab = data['year'] year = str(yeargrab) dlfoldername = name favtype = 'tvshow' #main.addDir(name,url,'sgepisodelist',thumb,data,favtype) addDir(name,basetv_url + url,'sgepisodelist',thumb,data,favtype) #main.addSDir(movie_name +'('+ year +')',basetv_url + url,'episodes',thumb,year,favtype) nmatch=re.compile('.+?</li><li><a href="(.+?)">(.+?)</a></li><li>').findall(link) if len(nmatch) > 0: for pageurl,pageno in nmatch: addDir('Page'+ pageno,basetv_url + pageurl,'sgindex',artwork +'nextpage.jpg','','dir') main.AUTO_VIEW('movies') def SGEPISODES(url,name,thumb): params = {'url':url, 'mode':mode, 'name':name, 'thumb':thumb} dlfoldername = name mainimg = thumb show = name link = net.http_GET(url).content matchurl=re.compile('<div class="season_page">\n\t\t\t\t\t\t<a href="(.+?)" >(.+?)</a>').findall(link) for url,snumber in matchurl: favtype = 'episodes' #main.addDir(snumber,url,'sgepisodelist',thumb,'',favtype) main.addEPNOCLEANDir(snumber,url,thumb,'sgepisodelist',show,dlfoldername,mainimg,'','') main.AUTO_VIEW('movies') def SGEPISODELIST(url,name,thumb): params = {'url':url, 'mode':mode, 'name':name, 'thumb':thumb} dlfoldername = name mainimg = thumb show = name url2=url link = net.http_GET(url).content #match=re.compile('<a href="(.+?)">&raquo S(.+?) - E(.+?) (.+?)</a>(.+?)').findall(link) match=re.compile('<a href="(.+?)">&raquo S(.+?) - E(.+?) (.+?)</a>').findall(link) for url,season,epnum,epname in match: s = 'S'+season e = 'E'+epnum se = s+e name = se + ' ' + epname favtype = 'episodes' main.addEPNOCLEANDir(name,url2+'/season'+season+'/episode'+epnum+'/searchresult',thumb,'sgtvlinkpage',show,dlfoldername,mainimg,season,epnum) main.AUTO_VIEW('movies') '''def SGEPISODELIST(url,name,thumb): params = {'url':url, 'mode':mode, 'name':name, 'thumb':thumb} #dlfoldername = name mainimg = thumb link = net.http_GET(url).content match=re.compile('<div class=".+?" style=".+?" >Season(.+?) Episode(.+?)- <a href = ".+?">.+?</a></div><div class=".+?" >(.+?)</div><div class = ".+?"></div><div style=".+?"><a href="(.+?)"><img src="(.+?)" width=".+?" height=".+?" alt=".+?" title = "(.+?)" ></a>').findall(link) for season,epnum, date, url, thumb, epname in match: s = 'S'+season e = 'E'+epnum se = s+e name = se + ' ' + epname favtype = 'episodes' main.addEPNOCLEANDir(name,url,thumb,'sgtvlinkpage',show,dlfoldername,mainimg,season,epnum) main.AUTO_VIEW('movies') ''' def SGTVLINKPAGE(url,name,thumb,mainimg): params = {'url':url, 'mode':mode, 'name':name, 'thumb':thumb, 'dlfoldername':dlfoldername,'mainimg':mainimg} inc = 0 linkbase = 'http://seriesgate.me' mainimg = mainimg #link = net.http_GET(url).content #match=re.compile('href="(.+?)">More Links').findall(link) #for surl in match: #url = linkbase + surl #url = url +'searchresult/' print 'host url look is' + url if inc < 50: link = net.http_GET(url).content #hostmatch=re.compile('<a rel="nofollow" href="(.+?)" TARGET="_blank" >(.+?)</a>').findall(link) hostmatch=re.compile('hre_watch_tt" href="(.+?)">').findall(link) #for urls,sourcename in hostmatch: for urls in hostmatch: print 'Pre HMF url is ' +urls hmf = urlresolver.HostedMediaFile(urls) ########################################## print 'URLS is ' +urls if hmf: #try: host = hmf.get_host() hthumb = main.GETHOSTTHUMB(host) #dlurl = urlresolver.resolve(vidUrl) data = main.GRABTVMETA(name,'') thumb = data['cover_url'] favtype = 'movie' hostname = main.GETHOSTNAME(host) try: main.addTVDLDir(name+hostname,urls,'vidpage',hthumb,data,dlfoldername,favtype,mainimg) inc +=1 except: continue #Start Search Function def _get_keyboard( default="", heading="", hidden=False ): """ shows a keyboard and returns a value """ keyboard = xbmc.Keyboard( default, heading, hidden ) keyboard.doModal() if ( keyboard.isConfirmed() ): return unicode( keyboard.getText(), "utf-8" ) return default def SEARCHSGTV(url): searchUrl = url vq = _get_keyboard( heading="Searching for TV Shows" ) if ( not vq ): return False, 0 title = urllib.quote_plus(vq) searchUrl += title + '&criteria=tag' print "Searching URL: " + searchUrl SGSEARCHINDEX(searchUrl) main.AUTO_VIEW('movies') def SGSEARCHINDEX (url): link = net.http_GET(url).content match=re.compile('</a><div class = ".+?" style=".+?"><div class = ".+?"><a href = "(.+?)">(.+?)</a>').findall(link) #match=re.compile('<a href="(.+?)">&raquo (.+?) - (.+?) (.+?)</a>').findall(link) if len(match) > 0: for url,name in match: #for url,season,episode,name in match: inc = 0 #movie_name = fullyear[:-6] #year = fullyear[-6:] #movie_name = movie_name.decode('UTF-8','ignore') data = main.GRABTVMETA(name,'') thumb = data['cover_url'] yeargrab = data['year'] year = str(yeargrab) dlfoldername = name favtype = 'tvshow' addDir(name,basetv_url + url,'sgepisodelist',thumb,data,favtype) #main.addSDir(movie_name +'('+ year +')',basetv_url + url,'episodes',thumb,year,favtype) nmatch=re.compile('.+?</li><li><a href="(.+?)">(.+?)</a></li><li>').findall(link) if len(nmatch) > 0: for pageurl,pageno in nmatch: addDir('Page'+ pageno,basetv_url + pageurl,'movieindex',artwork +'nextpage.jpg','','dir') main.AUTO_VIEW('movies') def addDir(name,url,mode,thumb,labels,favtype): #name = nameCleaner(name) params = {'url':url, 'mode':mode, 'name':name, 'thumb':thumb, 'dlfoldername':dlfoldername, 'mainimg':mainimg} contextMenuItems = [] gomode=mode contextMenuItems.append(('[COLOR red]Add to CLIQ Favorites[/COLOR]', 'XBMC.RunPlugin(%s)' % addon.build_plugin_url({'mode': 'addsttofavs', 'name': name,'url': url,'thumb': thumb,'gomode': gomode}))) contextMenuItems.append(('[COLOR red]Remove From CLIQ Favorites[/COLOR]', 'XBMC.RunPlugin(%s)' % addon.build_plugin_url({'mode': 'removestfromfavs', 'name': name,'url': url,'thumb': thumb,'gomode': gomode}))) sitethumb = thumb sitename = name fanart = 'http://cliqaddon.com/support/commoncore/tvaddons/moviedb/showgunart/images/fanart/fanart.jpg' try: name = data['title'] thumb = data['cover_url'] fanart = data['backdrop_url'] except: name = sitename if thumb == '': thumb = sitethumb u=sys.argv[0]+"?url="+urllib.quote_plus(url)+"&mode="+str(mode)+"&name="+urllib.quote_plus(name) ok=True liz=xbmcgui.ListItem(name, iconImage="DefaultFolder.png", thumbnailImage=thumb) liz.setInfo( type="Video", infoLabels=labels ) if favtype == 'movie': contextMenuItems.append(('[COLOR gold]Movie Information[/COLOR]', 'XBMC.Action(Info)')) elif favtype == 'tvshow': contextMenuItems.append(('[COLOR gold]TV Show Information[/COLOR]', 'XBMC.Action(Info)')) elif favtype == 'episode': contextMenuItems.append(('[COLOR gold]Episode Information[/COLOR]', 'XBMC.Action(Info)')) liz.addContextMenuItems(contextMenuItems, replaceItems=False) try: liz.setProperty( "Fanart_Image", labels['backdrop_url'] ) except: liz.setProperty( "Fanart_Image", fanart ) ok=xbmcplugin.addDirectoryItem(handle=int(sys.argv[1]),url=u,listitem=liz,isFolder=True) return ok

[ "esc0rtd3w@gmail.com" ]

esc0rtd3w@gmail.com

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/alignmentrs/aln/funcs.py

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[ "MIT" ]

permissive

kentwait/alignmentrs

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2019-01-29T05:05:09

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from libalignmentrs.alignment import fasta_file_to_basealignments from alignmentrs.aln import Alignment __all__ = ['fasta_file_to_alignment'] def fasta_file_to_alignment(path, name, marker_kw=None): """Reads a FASTA formatted text file to a list. Parameters ---------- path : str Location of FASTA file. name : str Name of the alignment. marker_kw : str Keyword indicating the sample is a marker. Returns ------- Alignment """ # Create alignments if marker_kw is None: marker_kw = '' return Alignment(name, *fasta_file_to_basealignments(path, marker_kw)) # def split_concatenated_alignment(aln, catblocks=None, # description_decoder=None): # pass # def blocks_list_to_df(blocks_list): # pass # def catblocks_list_to_df(catblocks_list): # pass

[ "kentkawashima@gmail.com" ]

kentkawashima@gmail.com

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refs/heads/master

2021-01-10T20:11:08.460497

2015-07-05T12:35:27

37,803,290

1

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UTF-8

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491

py

# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations class Migration(migrations.Migration): dependencies = [ ('cms', '0002_auto_20150621_1732'), ] operations = [ migrations.AlterField( model_name='discuss', name='course', field=models.ForeignKey(related_name='course_discuss', blank=True, to='cms.Course', null=True), preserve_default=True, ), ]

[ "zhufree2013@gmail.com" ]

zhufree2013@gmail.com

3385c8014e021d32bc15079091ad8cde2089b96d

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/geocoordinates_assignment/asgi.py

34ec4024736aa7332cf8cb553cab16c45454963d

[]

no_license

aarti98/verloop-assignment

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4842883673ce92fcd5ea4f2a009930498a603606

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2023-03-22T12:37:23.665991

2021-03-21T09:21:02

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

[ "aartij1998@gmail.com" ]

aartij1998@gmail.com

76f5af84fbd35b8169fa79d19c04247b0d84fd00

504c9c2b0d29d946079e11644761ad354fc79715

/_build/jupyter_execute/B_資訊設會必修的12堂Python通識課_何敏煌_博碩_2019/ch08.py

f2a128622353e50d7e7e751299228a9b37946c13

[]

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AaronCHH/jb_pysqlite

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refs/heads/main

2023-03-12T23:17:22.534445

2021-03-06T15:51:10

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# Ch08 操作資料庫 #顯示學生成績表 import sqlite3 dbfile = "school.db" conn = sqlite3.connect(dbfile) rows = conn.execute("select * from score;") for row in rows: for field in row: print("{}\t".format(field), end="") print() conn.close() #輸入學生成績 import sqlite3 dbfile = "school.db" conn = sqlite3.connect(dbfile) stuno = input("學號：") chi = input("國文成績：") eng = input("英文成績：") mat = input("數學成績：") his = input("歷史成績：") geo = input("地理成績：") sql_str = "insert into score(stuno, chi, eng, mat, his, geo) values('{}',{},{},{},{},{});".format( stuno, chi, eng, mat, his, geo) conn.execute(sql_str) conn.commit() conn.close() #輸入學生資料表 import sqlite3 dbfile = "school.db" conn = sqlite3.connect(dbfile) stuno = input("學號：") while stuno!="-1": name = input("姓名：") gender = input("性別：") clsno = input("班級編號：") tel = input("電話：") pid = input("家長身份證字號：") sql_str = "insert into studata(stuno, name, gender, clsno, tel, pid) values('{}','{}','{}','{}','{}','{}');".format( stuno, name, gender, clsno, tel, pid) conn.execute(sql_str) stuno = input("學號：") conn.commit() conn.close() #顯示學生基本資料表 import sqlite3 dbfile = "school.db" conn = sqlite3.connect(dbfile) rows = conn.execute("select * from studata;") for row in rows: for field in row: print("{}\t".format(field), end="") print() conn.close() #顯示學生的完整成績表（含總分及平均） import sqlite3 dbfile = "school.db" conn = sqlite3.connect(dbfile) rows = conn.execute("select stuno, chi, eng, mat, his, geo, chi+eng+mat+his+geo, (chi+eng+mat+his+geo)/5 from score;") print("學號\t國文\t英文\t數學\t歷史\t地理\t總分\t平均") for row in rows: for field in row: print("{}\t".format(field), end="") print() conn.close() #顯示學生各科的平均 import sqlite3 dbfile = "school.db" conn = sqlite3.connect(dbfile) rows = conn.execute("select stuno, avg(chi), avg(eng), avg(mat), avg(his), avg(geo) from score;") print("學號\t國文\t英文\t數學\t歷史\t地理") for row in rows: for field in row: print("{}\t".format(field), end="") print() conn.close() #依姓名顯示成績表 import sqlite3 dbfile = "school.db" conn = sqlite3.connect(dbfile) rows = conn.execute("select studata.name, score.chi, score.eng from score, studata;") for row in rows: for field in row: print("{}\t".format(field), end="") print() conn.close() #依姓名顯示成績表--使用INNER JOIN import sqlite3 dbfile = "school.db" conn = sqlite3.connect(dbfile) rows = conn.execute("select studata.name, score.chi, score.eng from score inner join studata on score.stuno = studata.stuno;") for row in rows: for field in row: print("{}\t".format(field), end="") print() conn.close() #成績修改程式 import sqlite3 dbfile = "school.db" conn = sqlite3.connect(dbfile) stuno = input("請輸入想要修改成績的學號：") rows = conn.execute("select stuno, chi, eng, mat, his, geo from score where stuno='{}'".format(stuno)) row = rows.fetchone() if row is not None: print("學號\t國文\t英文\t數學\t歷史\t地理") for field in row: print("{}\t".format(field), end="") print() chi = input("國文=") eng = input("英文=") mat = input("數學=") his = input("歷史=") geo = input("地理=") sql_str = "update score set stuno='{}', chi={}, eng={}, mat={}, his={}, geo={} where stuno='{}';".format( stuno, chi, eng, mat, his, geo, stuno) conn.execute(sql_str) conn.commit() conn.close() import sqlite3 dbfile = "school.db" conn = sqlite3.connect(dbfile) rows = conn.execute("select * from score;") print(type(rows)) print(dir(rows)) print(type(rows.fetchone())) conn.close() import sqlite3 dbfile = "school.db" conn = sqlite3.connect(dbfile) cur = conn.cursor() cur.execute("select * from score;") print(type(cur.fetchone())) print(cur.fetchone()) import sqlite3 dbfile = "school.db" conn = sqlite3.connect(dbfile) cur = conn.cursor() cur.execute("select * from score;") first3_records = cur.fetchmany(3) all_records = cur.fetchall() print(first3_records) print(all_records) conn.close() import sqlite3 dbfile = "school.db" conn = sqlite3.connect(dbfile) conn.row_factory = sqlite3.Row cur = conn.cursor() cur.execute("select * from score;") rows = cur.fetchall() print(rows[0].keys()) print(type(rows)) print(type(rows[0])) print("學號\t國文\t英文") for row in rows: print("{}\t{}\t{}".format(row['stuno'], row['chi'], row['eng']))

[ "aaronhsu219@gmail.com" ]

aaronhsu219@gmail.com

67c962e796f88822348a6f5d8befd69df944adae

c8d37f4cb24dc3d3cdbb42f844807cf788da3169

/week1.py

89805b1630671f0c901cd1e01be49b4677c90f9c

[]

no_license

juraj80/Applied-Data-Science-with-Python

6cd3f666408c4fa13b5132a6c147389fe1ca5e2a

ecd5fce8ec36e1a832515faaef9bbc6b4c0c344f

refs/heads/master

2021-06-13T19:33:07.882336

2017-03-23T20:11:44

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# coding: utf-8 # --- # # _You are currently looking at **version 1.1** of this notebook. To download notebooks and datafiles, as well as get help on Jupyter notebooks in the Coursera platform, visit the [Jupyter Notebook FAQ](https://www.coursera.org/learn/python-data-analysis/resources/0dhYG) course resource._ # # --- # # The Python Programming Language: Functions # In[34]: x = 1 y = 2 x + y # In[35]: x # # `add_numbers` is a function that takes two numbers and adds them together. # In[ ]: def add_numbers(x, y): return x + y add_numbers(1, 2) # # `add_numbers` updated to take an optional 3rd parameter. Using `print` allows printing of multiple expressions within a single cell. # In[16]: def add_numbers(x,y,z=None): if (z==None): return x+y else: return x+y+z print(add_numbers(1, 2)) print(add_numbers(1, 2, 3)) # # `add_numbers` updated to take an optional flag parameter. # In[1]: def add_numbers(x, y, z=None, flag=False): if (flag): print('Flag is true!') if (z==None): return x + y else: return x + y + z print(add_numbers(1, 2, flag=True)) # # Assign function `add_numbers` to variable `a`. # In[2]: def add_numbers(x,y): return x+y a = add_numbers a(1,2) # # # The Python Programming Language: Types and Sequences # # Use `type` to return the object's type. # In[ ]: type('This is a string') # In[4]: type(None) # In[ ]: type(1) # In[ ]: type(1.0) # In[3]: type(add_numbers) # # Tuples are an immutable data structure (cannot be altered). # In[5]: x = (1, 'a', 2, 'b') type(x) # # Lists are a mutable data structure. # In[17]: x = [1, 'a', 2, 'b'] type(x) # # Use `append` to append an object to a list. # In[18]: x.append(3.3) print(x) # # This is an example of how to loop through each item in the list. # In[ ]: for item in x: print(item) # # Or using the indexing operator: # In[ ]: i=0 while( i != len(x) ): print(x[i]) i = i + 1 # # Use `+` to concatenate lists. # In[ ]: [1,2] + [3,4] # # Use `*` to repeat lists. # In[19]: [1]*3 # # Use the `in` operator to check if something is inside a list. # In[20]: 1 in [1, 2, 3] # # Now let's look at strings. Use bracket notation to slice a string. # In[ ]: x = 'This is a string' print(x[0]) #first character print(x[0:1]) #first character, but we have explicitly set the end character print(x[0:2]) #first two characters # # This will return the last element of the string. # In[ ]: x[-1] # # This will return the slice starting from the 4th element from the end and stopping before the 2nd element from the end. # In[ ]: x[-4:-2] # # This is a slice from the beginning of the string and stopping before the 3rd element. # In[ ]: x[:3] # # And this is a slice starting from the 3rd element of the string and going all the way to the end. # In[ ]: x[3:] # In[21]: firstname = 'Christopher' lastname = 'Brooks' print(firstname + ' ' + lastname) print(firstname*3) print('Chris' in firstname) # # `split` returns a list of all the words in a string, or a list split on a specific character. # In[36]: firstname = 'Christopher Arthur Hansen Brooks'.split(' ')[0] # [0] selects the first element of the list lastname = 'Christopher Arthur Hansen Brooks'.split(' ')[-1] # [-1] selects the last element of the list print(firstname) print(lastname) # # Make sure you convert objects to strings before concatenating. # In[38]: 'Chris' + 2 # In[39]: 'Chris' + str(2) # # Dictionaries associate keys with values. # In[40]: x = {'Christopher Brooks': 'brooksch@umich.edu', 'Bill Gates': 'billg@microsoft.com'} x['Christopher Brooks'] # Retrieve a value by using the indexing operator # In[41]: x['Kevyn Collins-Thompson'] = None x['Kevyn Collins-Thompson'] # # Iterate over all of the keys: # In[42]: for name in x: print(x[name]) # # Iterate over all of the values: # In[43]: for email in x.values(): print(email) # # Iterate over all of the items in the list: # In[45]: print(x.items()) for name, email in x.items(): print(name) print(email) # # You can unpack a sequence into different variables: # In[ ]: x = ('Christopher', 'Brooks', 'brooksch@umich.edu') fname, lname, email = x # In[ ]: fname # In[ ]: lname # # Make sure the number of values you are unpacking matches the number of variables being assigned. # In[ ]: x = ('Christopher', 'Brooks', 'brooksch@umich.edu', 'Ann Arbor') fname, lname, email = x # # # The Python Programming Language: More on Strings # In[ ]: print('Chris' + 2) # In[ ]: print('Chris' + str(2)) # # Python has a built in method for convenient string formatting. # In[ ]: sales_record = { 'price': 3.24, 'num_items': 4, 'person': 'Chris'} sales_statement = '{} bought {} item(s) at a price of {} each for a total of {}' print(sales_statement.format(sales_record['person'], sales_record['num_items'], sales_record['price'], sales_record['num_items']*sales_record['price'])) # # # Reading and Writing CSV files # # Let's import our datafile mpg.csv, which contains fuel economy data for 234 cars. # # * mpg : miles per gallon # * class : car classification # * cty : city mpg # * cyl : # of cylinders # * displ : engine displacement in liters # * drv : f = front-wheel drive, r = rear wheel drive, 4 = 4wd # * fl : fuel (e = ethanol E85, d = diesel, r = regular, p = premium, c = CNG) # * hwy : highway mpg # * manufacturer : automobile manufacturer # * model : model of car # * trans : type of transmission # * year : model year # In[5]: import csv get_ipython().magic('precision 2') with open('mpg.csv') as csvfile: mpg =list(csv.DictReader(csvfile)) print(mpg[0:10]) # # `csv.Dictreader` has read in each row of our csv file as a dictionary. `len` shows that our list is comprised of 234 dictionaries. # In[ ]: len(mpg) # # `keys` gives us the column names of our csv. # In[ ]: mpg[0].keys() # # This is how to find the average cty fuel economy across all cars. All values in the dictionaries are strings, so we need to convert to float. # In[ ]: sum(float(d['cty']) for d in mpg) / len(mpg) # # Similarly this is how to find the average hwy fuel economy across all cars. # In[10]: sum(float(d['hwy']) for d in mpg) / len(mpg) # # Use `set` to return the unique values for the number of cylinders the cars in our dataset have. # In[11]: cylinders = set(d['cyl'] for d in mpg) cylinders # # Here's a more complex example where we are grouping the cars by number of cylinder, and finding the average cty mpg for each group. # In[12]: CtyMpgByCyl = [] for c in cylinders: # iterate over all the cylinder levels summpg = 0 cyltypecount = 0 for d in mpg: # iterate over all dictionaries if d['cyl'] == c: # if the cylinder level type matches, summpg += float(d['cty']) # add the cty mpg cyltypecount += 1 # increment the count CtyMpgByCyl.append((c, summpg / cyltypecount)) # append the tuple ('cylinder', 'avg mpg') CtyMpgByCyl.sort(key=lambda x: x[0]) CtyMpgByCyl # # Use `set` to return the unique values for the class types in our dataset. # In[14]: vehicleclass = set(d['class'] for d in mpg) # what are the class types vehicleclass # # And here's an example of how to find the average hwy mpg for each class of vehicle in our dataset. # In[15]: HwyMpgByClass = [] for t in vehicleclass: # iterate over all the vehicle classes summpg = 0 vclasscount = 0 for d in mpg: # iterate over all dictionaries if d['class'] == t: # if the cylinder amount type matches, summpg += float(d['hwy']) # add the hwy mpg vclasscount += 1 # increment the count HwyMpgByClass.append((t, summpg / vclasscount)) # append the tuple ('class', 'avg mpg') HwyMpgByClass.sort(key=lambda x: x[1]) HwyMpgByClass # # # The Python Programming Language: Dates and Times # In[7]: import datetime as dt import time as tm # # `time` returns the current time in seconds since the Epoch. (January 1st, 1970) # In[22]: tm.time() # # Convert the timestamp to datetime. # In[23]: dtnow = dt.datetime.fromtimestamp(tm.time()) dtnow # # Handy datetime attributes: # In[24]: dtnow.year, dtnow.month, dtnow.day, dtnow.hour, dtnow.minute, dtnow.second # get year, month, day, etc.from a datetime # # `timedelta` is a duration expressing the difference between two dates. # In[9]: delta = dt.timedelta(days = 100) # create a timedelta of 100 days delta # # `date.today` returns the current local date. # In[12]: today = dt.date.today() # In[29]: today - delta # the date 100 days ago # In[ ]: today > today-delta # compare dates # # # The Python Programming Language: Objects and map() # # An example of a class in python: # In[ ]: class Person: department = 'School of Information' #a class variable def set_name(self, new_name): #a method self.name = new_name def set_location(self, new_location): self.location = new_location # In[ ]: person = Person() person.set_name('Christopher Brooks') person.set_location('Ann Arbor, MI, USA') print('{} live in {} and works in the department {}'.format(person.name, person.location, person.department)) # # Here's an example of mapping the `min` function between two lists. # In[32]: store1 = [10.00, 11.00, 12.34, 2.34] store2 = [9.00, 11.10, 12.34, 2.01] cheapest = map(min, store1, store2) cheapest # # Now let's iterate through the map object to see the values. # In[33]: for item in cheapest: print(item) # # # The Python Programming Language: Lambda and List Comprehensions # # Here's an example of lambda that takes in three parameters and adds the first two. # In[ ]: my_function = lambda a, b, c : a + b # In[ ]: my_function(1, 2, 3) # # Let's iterate from 0 to 999 and return the even numbers. # In[ ]: my_list = [] for number in range(0, 1000): if number % 2 == 0: my_list.append(number) my_list # # Now the same thing but with list comprehension. # In[ ]: my_list = [number for number in range(0,1000) if number % 2 == 0] my_list # # # The Python Programming Language: Numerical Python (NumPy) # In[14]: import numpy as np # # ## Creating Arrays # Create a list and convert it to a numpy array # In[3]: mylist = [1, 2, 3] x = np.array(mylist) x # # Or just pass in a list directly # y = np.array([4, 5, 6]) # y # # Pass in a list of lists to create a multidimensional array. # In[5]: m = np.array([[7, 8, 9], [10, 11, 12]]) m # # Use the shape method to find the dimensions of the array. (rows, columns) # In[ ]: m.shape # # `arange` returns evenly spaced values within a given interval. # In[6]: n = np.arange(0, 30, 2) # start at 0 count up by 2, stop before 30 n # # `reshape` returns an array with the same data with a new shape. # In[7]: n = n.reshape(3, 5) # reshape array to be 3x5 n # # `linspace` returns evenly spaced numbers over a specified interval. # In[15]: o = np.linspace(0, 4, 9) # return 9 evenly spaced values from 0 to 4 o # # `resize` changes the shape and size of array in-place. # In[ ]: o.resize(3, 3) o # # `ones` returns a new array of given shape and type, filled with ones. # In[8]: np.ones((3, 2)) # # `zeros` returns a new array of given shape and type, filled with zeros. # In[ ]: np.zeros((2, 3)) # # `eye` returns a 2-D array with ones on the diagonal and zeros elsewhere. # In[ ]: np.eye(3) # # `diag` extracts a diagonal or constructs a diagonal array. # In[9]: np.diag(y) # # Create an array using repeating list (or see `np.tile`) # In[16]: np.array([1, 2, 3] * 3) # # Repeat elements of an array using `repeat`. # In[17]: np.repeat([1, 2, 3], 3) # # #### Combining Arrays # In[10]: p = np.ones([2, 3], int) p # # Use `vstack` to stack arrays in sequence vertically (row wise). # In[11]: np.vstack([p, 2*p]) # # Use `hstack` to stack arrays in sequence horizontally (column wise). # In[ ]: np.hstack([p, 2*p]) # # ## Operations # Use `+`, `-`, `*`, `/` and `**` to perform element wise addition, subtraction, multiplication, division and power. # In[ ]: print(x + y) # elementwise addition [1 2 3] + [4 5 6] = [5 7 9] print(x - y) # elementwise subtraction [1 2 3] - [4 5 6] = [-3 -3 -3] # In[ ]: print(x * y) # elementwise multiplication [1 2 3] * [4 5 6] = [4 10 18] print(x / y) # elementwise divison [1 2 3] / [4 5 6] = [0.25 0.4 0.5] # In[ ]: print(x**2) # elementwise power [1 2 3] ^2 = [1 4 9] # # **Dot Product:** # # $ \begin{bmatrix}x_1 \ x_2 \ x_3\end{bmatrix} # \cdot # \begin{bmatrix}y_1 \\ y_2 \\ y_3\end{bmatrix} # = x_1 y_1 + x_2 y_2 + x_3 y_3$ # In[ ]: x.dot(y) # dot product 1*4 + 2*5 + 3*6 # In[18]: z = np.array([y, y**2]) print(len(z)) # number of rows of array # # Let's look at transposing arrays. Transposing permutes the dimensions of the array. # In[12]: z = np.array([y, y**2]) z # # The shape of array `z` is `(2,3)` before transposing. # In[13]: z.shape # # Use `.T` to get the transpose. # In[14]: z.T # # The number of rows has swapped with the number of columns. # In[15]: z.T.shape # # Use `.dtype` to see the data type of the elements in the array. # In[ ]: z.dtype # # Use `.astype` to cast to a specific type. # In[ ]: z = z.astype('f') z.dtype # # ## Math Functions # Numpy has many built in math functions that can be performed on arrays. # In[ ]: a = np.array([-4, -2, 1, 3, 5]) # In[ ]: a.sum() # In[ ]: a.max() # In[ ]: a.min() # In[ ]: a.mean() # In[ ]: a.std() # # `argmax` and `argmin` return the index of the maximum and minimum values in the array. # In[ ]: a.argmax() # In[ ]: a.argmin() # # ## Indexing / Slicing # In[19]: s = np.arange(13)**2 s # # Use bracket notation to get the value at a specific index. Remember that indexing starts at 0. # In[ ]: s[0], s[4], s[-1] # # Use `:` to indicate a range. `array[start:stop]` # # # Leaving `start` or `stop` empty will default to the beginning/end of the array. # In[ ]: s[1:5] # # Use negatives to count from the back. # In[ ]: s[-4:] # # A second `:` can be used to indicate step-size. `array[start:stop:stepsize]` # # Here we are starting 5th element from the end, and counting backwards by 2 until the beginning of the array is reached. # In[20]: s[-5::-2] # # Let's look at a multidimensional array. # In[22]: r = np.arange(36)**2 r.resize((6, 6)) r # # Use bracket notation to slice: `array[row, column]` # In[23]: r[2, 2] # # And use : to select a range of rows or columns # In[24]: r[3, 3:6] # # Here we are selecting all the rows up to (and not including) row 2, and all the columns up to (and not including) the last column. # In[25]: r[:2, :-1] # # This is a slice of the last row, and only every other element. # In[26]: r[-1, ::2] # # We can also perform conditional indexing. Here we are selecting values from the array that are greater than 30. (Also see `np.where`) # In[27]: r[r > 300] # # Here we are assigning all values in the array that are greater than 30 to the value of 30. # In[28]: r[r > 30] = 30 r # # ## Copying Data # Be careful with copying and modifying arrays in NumPy! # # # `r2` is a slice of `r` # In[29]: r2 = r[:3,:3] r2 # # Set this slice's values to zero ([:] selects the entire array) # In[30]: r2[:] = 0 r2 # # `r` has also been changed! # In[31]: r # # To avoid this, use `r.copy` to create a copy that will not affect the original array # In[33]: r_copy = r.copy() r_copy # # Now when r_copy is modified, r will not be changed. # In[34]: r_copy[:] = 10 print(r_copy, '\n') print(r) # # ### Iterating Over Arrays # Let's create a new 4 by 3 array of random numbers 0-9. # In[35]: test = np.random.randint(0, 10, (4,3)) test # # Iterate by row: # In[36]: for row in test: print(row) # # Iterate by index: # In[39]: for i in range(len(test)): print(i,test[i]) # # Iterate by row and index: # In[37]: for i, row in enumerate(test): print('row', i, 'is', row) # # Use `zip` to iterate over multiple iterables. # In[41]: test2 = test**2 test2 # In[42]: for i, j in zip(test, test2): print(i,'+',j,'=',i+j) # In[ ]:

[ "juraj80@github.com" ]

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#!/home/pedrohcm/RI/ri_lab_01/recinfo/bin/python import sys import getopt import sysconfig valid_opts = ['prefix', 'exec-prefix', 'includes', 'libs', 'cflags', 'ldflags', 'help'] if sys.version_info >= (3, 2): valid_opts.insert(-1, 'extension-suffix') valid_opts.append('abiflags') if sys.version_info >= (3, 3): valid_opts.append('configdir') def exit_with_usage(code=1): sys.stderr.write("Usage: {0} [{1}]\n".format( sys.argv[0], '|'.join('--'+opt for opt in valid_opts))) sys.exit(code) try: opts, args = getopt.getopt(sys.argv[1:], '', valid_opts) except getopt.error: exit_with_usage() if not opts: exit_with_usage() pyver = sysconfig.get_config_var('VERSION') getvar = sysconfig.get_config_var opt_flags = [flag for (flag, val) in opts] if '--help' in opt_flags: exit_with_usage(code=0) for opt in opt_flags: if opt == '--prefix': print(sysconfig.get_config_var('prefix')) elif opt == '--exec-prefix': print(sysconfig.get_config_var('exec_prefix')) elif opt in ('--includes', '--cflags'): flags = ['-I' + sysconfig.get_path('include'), '-I' + sysconfig.get_path('platinclude')] if opt == '--cflags': flags.extend(getvar('CFLAGS').split()) print(' '.join(flags)) elif opt in ('--libs', '--ldflags'): abiflags = getattr(sys, 'abiflags', '') libs = ['-lpython' + pyver + abiflags] libs += getvar('LIBS').split() libs += getvar('SYSLIBS').split() # add the prefix/lib/pythonX.Y/config dir, but only if there is no # shared library in prefix/lib/. if opt == '--ldflags': if not getvar('Py_ENABLE_SHARED'): libs.insert(0, '-L' + getvar('LIBPL')) if not getvar('PYTHONFRAMEWORK'): libs.extend(getvar('LINKFORSHARED').split()) print(' '.join(libs)) elif opt == '--extension-suffix': ext_suffix = sysconfig.get_config_var('EXT_SUFFIX') if ext_suffix is None: ext_suffix = sysconfig.get_config_var('SO') print(ext_suffix) elif opt == '--abiflags': if not getattr(sys, 'abiflags', None): exit_with_usage() print(sys.abiflags) elif opt == '--configdir': print(sysconfig.get_config_var('LIBPL'))

[ "pedrohcm@lcc3-099.lcc.ufcg.edu.br" ]

pedrohcm@lcc3-099.lcc.ufcg.edu.br

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""" AlexNet, implemented in Gluon. Original paper: 'One weird trick for parallelizing convolutional neural networks,' https://arxiv.org/abs/1404.5997. """ __all__ = ['AlexNet', 'alexnet'] import os from mxnet import cpu from mxnet.gluon import nn, HybridBlock class AlexConv(HybridBlock): """ AlexNet specific convolution block. Parameters: ---------- in_channels : int Number of input channels. out_channels : int Number of output channels. kernel_size : int or tuple/list of 2 int Convolution window size. strides : int or tuple/list of 2 int Strides of the convolution. padding : int or tuple/list of 2 int Padding value for convolution layer. """ def __init__(self, in_channels, out_channels, kernel_size, strides, padding, **kwargs): super(AlexConv, self).__init__(**kwargs) with self.name_scope(): self.conv = nn.Conv2D( channels=out_channels, kernel_size=kernel_size, strides=strides, padding=padding, use_bias=True, in_channels=in_channels) self.activ = nn.Activation('relu') def hybrid_forward(self, F, x): x = self.conv(x) x = self.activ(x) return x class AlexDense(HybridBlock): """ AlexNet specific dense block. Parameters: ---------- in_channels : int Number of input channels. out_channels : int Number of output channels. """ def __init__(self, in_channels, out_channels, **kwargs): super(AlexDense, self).__init__(**kwargs) with self.name_scope(): self.fc = nn.Dense( units=out_channels, weight_initializer="normal", in_units=in_channels) self.activ = nn.Activation('relu') self.dropout = nn.Dropout(rate=0.5) def hybrid_forward(self, F, x): x = self.fc(x) x = self.activ(x) x = self.dropout(x) return x class AlexOutputBlock(HybridBlock): """ AlexNet specific output block. Parameters: ---------- in_channels : int Number of input channels. classes : int Number of classification classes. """ def __init__(self, in_channels, classes, **kwargs): super(AlexOutputBlock, self).__init__(**kwargs) mid_channels = 4096 with self.name_scope(): self.fc1 = AlexDense( in_channels=in_channels, out_channels=mid_channels) self.fc2 = AlexDense( in_channels=mid_channels, out_channels=mid_channels) self.fc3 = nn.Dense( units=classes, weight_initializer="normal", in_units=mid_channels) def hybrid_forward(self, F, x): x = self.fc1(x) x = self.fc2(x) x = self.fc3(x) return x class AlexNet(HybridBlock): """ AlexNet model from 'One weird trick for parallelizing convolutional neural networks,' https://arxiv.org/abs/1404.5997. Parameters: ---------- channels : list of list of int Number of output channels for each unit. kernel_sizes : list of list of int Convolution window sizes for each unit. strides : list of list of int or tuple/list of 2 int Strides of the convolution for each unit. paddings : list of list of int or tuple/list of 2 int Padding value for convolution layer for each unit. in_channels : int, default 3 Number of input channels. in_size : tuple of two ints, default (224, 224) Spatial size of the expected input image. classes : int, default 1000 Number of classification classes. """ def __init__(self, channels, kernel_sizes, strides, paddings, in_channels=3, in_size=(224, 224), classes=1000, **kwargs): super(AlexNet, self).__init__(**kwargs) self.in_size = in_size self.classes = classes with self.name_scope(): self.features = nn.HybridSequential(prefix='') for i, channels_per_stage in enumerate(channels): stage = nn.HybridSequential(prefix='stage{}_'.format(i + 1)) with stage.name_scope(): for j, out_channels in enumerate(channels_per_stage): stage.add(AlexConv( in_channels=in_channels, out_channels=out_channels, kernel_size=kernel_sizes[i][j], strides=strides[i][j], padding=paddings[i][j])) in_channels = out_channels stage.add(nn.MaxPool2D( pool_size=3, strides=2, padding=0)) self.features.add(stage) self.output = nn.HybridSequential(prefix='') self.output.add(nn.Flatten()) in_channels = in_channels * 6 * 6 self.output.add(AlexOutputBlock( in_channels=in_channels, classes=classes)) def hybrid_forward(self, F, x): x = self.features(x) x = self.output(x) return x def get_alexnet(model_name=None, pretrained=False, ctx=cpu(), root=os.path.join('~', '.mxnet', 'models'), **kwargs): """ Create AlexNet model with specific parameters. Parameters: ---------- model_name : str or None, default None Model name for loading pretrained model. pretrained : bool, default False Whether to load the pretrained weights for model. ctx : Context, default CPU The context in which to load the pretrained weights. root : str, default '~/.mxnet/models' Location for keeping the model parameters. """ channels = [[64], [192], [384, 256, 256]] kernel_sizes = [[11], [5], [3, 3, 3]] strides = [[4], [1], [1, 1, 1]] paddings = [[2], [2], [1, 1, 1]] net = AlexNet( channels=channels, kernel_sizes=kernel_sizes, strides=strides, paddings=paddings, **kwargs) if pretrained: if (model_name is None) or (not model_name): raise ValueError("Parameter `model_name` should be properly initialized for loading pretrained model.") from .model_store import get_model_file net.load_parameters( filename=get_model_file( model_name=model_name, local_model_store_dir_path=root), ctx=ctx) return net def alexnet(**kwargs): """ AlexNet model from 'One weird trick for parallelizing convolutional neural networks,' https://arxiv.org/abs/1404.5997. Parameters: ---------- pretrained : bool, default False Whether to load the pretrained weights for model. ctx : Context, default CPU The context in which to load the pretrained weights. root : str, default '~/.mxnet/models' Location for keeping the model parameters. """ return get_alexnet(model_name="alexnet", **kwargs) def _test(): import numpy as np import mxnet as mx pretrained = False models = [ alexnet, ] for model in models: net = model(pretrained=pretrained) ctx = mx.cpu() if not pretrained: net.initialize(ctx=ctx) net_params = net.collect_params() weight_count = 0 for param in net_params.values(): if (param.shape is None) or (not param._differentiable): continue weight_count += np.prod(param.shape) print("m={}, {}".format(model.__name__, weight_count)) assert (model != alexnet or weight_count == 61100840) x = mx.nd.zeros((1, 3, 224, 224), ctx=ctx) y = net(x) assert (y.shape == (1, 1000)) if __name__ == "__main__": _test()

[ "osemery@gmail.com" ]

osemery@gmail.com

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/sale_crm/__manifest__.py

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tamam001/ALWAFI_P1

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refs/heads/master

2020-05-18T08:16:50.583264

2019-04-30T14:43:46

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# -*- coding: utf-8 -*- # Part of ALWAFI. See LICENSE file for full copyright and licensing details. { 'name': 'Opportunity to Quotation', 'version': '1.0', 'category': 'Hidden', 'description': """ This module adds a shortcut on one or several opportunity cases in the CRM. =========================================================================== This shortcut allows you to generate a sales order based on the selected case. If different cases are open (a list), it generates one sales order by case. The case is then closed and linked to the generated sales order. We suggest you to install this module, if you installed both the sale and the crm modules. """, 'depends': ['sale_management', 'crm'], 'data': [ 'security/ir.model.access.csv', 'views/partner_views.xml', 'views/sale_order_views.xml', 'views/crm_lead_views.xml', ], 'auto_install': True, }

[ "50145400+gilbertp7@users.noreply.github.com" ]

50145400+gilbertp7@users.noreply.github.com

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/SDKs/swig/Examples/python/varargs/runme.py

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Personwithhat/CE_SDKs

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refs/heads/master

2020-04-09T22:14:56.917176

2019-07-04T00:19:11

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version https://git-lfs.github.com/spec/v1 oid sha256:f2ae65c42f8358298afb53751299f1957fed0218e6a36f16022a63aa74858f95 size 705

[ "personwithhats2@Gmail.com" ]

personwithhats2@Gmail.com

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/PobarajOglasi.py

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[]

no_license

PsyLee/scrapers

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211d03ad1da6efe7fe2722add7edc9eb57e16474

refs/heads/master

2021-01-19T12:42:15.907856

2017-02-17T19:53:31

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#!/usr/bin/env python # coding: utf-8 import sys from Downloader import Downloader from webscraping import xpath from Utilities import getDescription from Utilities import adsToJson from Ad import Ad from datetime import datetime from datetime import date, timedelta from locale import currency from PyQt4.Qt import dec def scrapePobarajOglasi(): # UTF-8 support reload(sys) sys.setdefaultencoding('utf-8') now = datetime.now() down = Downloader('http://www.pobaraj.com.mk/lista_na_oglasi/all/1') content = down.get_content() html = unicode(content) site = xpath.get(html, '//ul[@class="lista_na_oglasi"]') linkovi = xpath.search(site, '//li') ads = [] for l in linkovi: link = "http://www.pobaraj.com.mk" + xpath.get(l, '//a[@class="title"]/@href') title = xpath.get(l, '//a[@class="title"]') imageUrl = xpath.get(l, '//a[@class="photo"]/img/@src') download = Downloader(link) cont = download.get_content() cont = unicode(cont) description = xpath.get(cont, '//div[@class="oglas_prikaz_opis"]').strip() if description == "": description = "/" kategorii = xpath.search(cont, '//a[@class="pateka"]') category = kategorii[1] if len(kategorii)>2: subcategory = kategorii[2] else: subcategory = "/" price = xpath.get(l, '//div[@class="price"]').strip() price = price.split("<div ") price = price[0].strip() price = price.split("Цена: ") price = price[1] if price == u"по договор": value = "/" currency = "/" else: price = price.split(" ") value = price[0] if price[1] == u"денари": currency = "MKD" elif price[1] == u"евра": currency = "EUR" else: currency = price[1] region = xpath.get(cont, '//div[@class="oglas_prikaz_left"]').strip() region = region.split("Град:<") region = region[1] region = region.split("") region = region[1] region = region.strip() country = u"Македонија" datum = xpath.get(l, '//div[@class="oglas_date"]').strip() datum = datum.split(": ") datum = datum[1] datum = datum.split(", ") vreme = datum[1] datum = datum[0] if datum == u"Денес": date = str(now.year)+"-"+str(now.month)+"-"+str(now.day)+" "+vreme elif datum == u"Вчера": da=datetime.now()-timedelta(days=1) date = str(da.year)+"-"+str(da.month)+"-"+str(da.day)+" "+vreme else: datum = datum.split(" ") if datum[1]=="Јан": datum= str(now.year) + "-1-" + datum[0] elif datum[1]=="Фев": datum= str(now.year) + "-2-" + datum[0] elif datum[1]=="Мар": datum= str(now.year) + "-3-" + datum[0] elif datum[1]=="Апр": datum= str(now.year) + "-4-" + datum[0] elif datum[1]=="Мај": datum= str(now.year) + "-5-" + datum[0] elif datum[1]=="Јун": datum= str(now.year) + "-6-" + datum[0] elif datum[1]=="Јул": datum= str(now.year) + "-7-" + datum[0] elif datum[1]=="Авг": datum= str(now.year) + "-8-" + datum[0] elif datum[1]=="Сеп": datum= str(now.year) + "-9-" + datum[0] elif datum[1]=="Окт": datum= str(now.year) + "-10-" + datum[0] elif datum[1]=="Ное": datum= str(now.year) + "-11-" + datum[0] elif datum[1]=="Дек": datum= str(now.year) + "-12-" + datum[0] date = datum +" "+ vreme ad = Ad(link, title, imageUrl, description, category, subcategory, value, currency, region, date, country) ads.append(ad) return adsToJson(ads) #print scrapePobarajOglasi()

[ "smiley.mk@gmail.com" ]

smiley.mk@gmail.com

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nickgerend/OntheMove

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refs/heads/main

2023-01-29T22:57:43.363592

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# Written by: Nick Gerend, @dataoutsider # Viz: "On the Move", enjoy! import pandas as pd import numpy as np import os import numbers class flow: def __init__(self, state_id = -1, state_id_source = -1, value = -1, direction = ''): self.state_id = state_id self.state_id_source = state_id_source self.value = value self.direction = direction df_matrix = pd.read_csv(os.path.dirname(__file__) + '/Migration_States.csv', engine='python').fillna(0) df_matrix_data = df_matrix.drop('State', axis=1) df_matrix_data = df_matrix_data.apply(lambda o: o.str.replace(',', '').astype(float)) data_list = [] value = 0 for i, row in df_matrix_data.iterrows(): for col in enumerate(row): value = col[1] icol = col[0] if isinstance(value, numbers.Number): if value > 0: data_list.append(flow(i, icol, value, 'in')) # in data_list.append(flow(icol, i, value, 'out')) # out import csv import os with open(os.path.dirname(__file__) + '/state_data.csv', 'w',) as csvfile: writer = csv.writer(csvfile, lineterminator = '\n') writer.writerow(['state_id', 'state_id_source', 'value', 'direction']) for item in data_list: writer.writerow([item.state_id, item.state_id_source, item.value, item.direction])

[ "nickgerend@gmail.com" ]

nickgerend@gmail.com

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/game.py

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[]

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ChristopherMeneses/CPSC-386-Project-3

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bda85cec1baaf719fecac41af140132f23276a76

refs/heads/master

2021-05-07T01:41:52.714288

2017-12-04T00:42:25

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#Project 3 - CPSC 386 - MW 5:30 PM #AMMU - Danial Moahmmad, Felicia Aubert, Annette Ulrichsen, Christopher Meneses #Platformer - goal is to find the princess #Sources: Anthony Biron - https://www.youtube.com/channel/UCy0eKoY5BVtcJHFQGKVe1yg #ChiliGames - Knight images - https://opengameart.org/content/knight-and-knight-animation #Platform - Kenney - https://opengameart.org/content/platformer-tiles #Princess image - ? #Music - Code Manu - https://opengameart.org/content/platformer-game-music-pack #Background Image - DPP Reskinning - http://appreskinning.blogspot.com/2017/07/backgrounds-for-2d-platforms-pack.html #! /usr/bin/python import sys import os import pygame from pygame import * from time import sleep WIN_WIDTH = 256*3 WIN_HEIGHT = 224*3 HALF_WIDTH = int(WIN_WIDTH / 2) HALF_HEIGHT = int(WIN_HEIGHT / 2) #determine whether to switch maps - used in while loop moveNext = False movePrev = False done = False #standard pygame initializations DISPLAY = (WIN_WIDTH, WIN_HEIGHT) DEPTH = 32 FLAGS = 0 newX = 0 newY = 0 pygame.init() screen = pygame.display.set_mode(DISPLAY, FLAGS, DEPTH) pygame.display.set_caption("Knight's Quest") pygame.mixer.music.load('music/bg.mp3') pygame.mixer.music.play(-1) #set character animations and sizes character = Surface((16,32),pygame.SRCALPHA) character = pygame.image.load("images/stand.png").convert_alpha() character = pygame.transform.scale(character, (16*4,32*3)) knightstand1 = character character = Surface((16,32),pygame.SRCALPHA) character = pygame.image.load("images/run1.png").convert_alpha() character = pygame.transform.scale(character, (16*4,32*3)) knightwalk1 = character character = Surface((16,32),pygame.SRCALPHA) character = pygame.image.load("images/run2.png").convert_alpha() character = pygame.transform.scale(character, (16*4,32*3)) knightwalk2 = character character = Surface((16,32),pygame.SRCALPHA) character = pygame.image.load("images/run3.png").convert_alpha() character = pygame.transform.scale(character, (16*4,32*3)) knightwalk3 = character character = Surface((16,32),pygame.SRCALPHA) character = pygame.image.load("images/jump.png").convert_alpha() character = pygame.transform.scale(character, (16*4,32*3)) knightjump1 = character #allow for font to be rendered later pygame.font.init() dialogFont = pygame.font.SysFont("garuda", 20) pygame.display.update() white = (255,255,255) black = (0,0,0) def main(): #initialize all required variables timer = pygame.time.Clock() currLevel = 1 up = down = left = right = running = False platforms = [] background = pygame.Surface(screen.get_size()) background = background.convert() background.fill((0,0,0)) bgImg = pygame.image.load('images/bg1.png') background.blit(bgImg, (0,0)) screen.blit(background, (0,0)) time = 0 pygame.display.update() #bg = Surface((WIN_WIDTH,WIN_HEIGHT)).convert() entities = pygame.sprite.Group() speech = pygame.image.load("images/title.png").convert_alpha() speech = pygame.transform.scale(speech ,(171*2,108*2)) screen.blit(speech, (HALF_WIDTH - 171 ,HALF_HEIGHT - 108)) pygame.display.update() sleep(2) x = y = 0 level = getLevel(currLevel) # build the level based off the level returned for row in level: for col in row: if col == "P": p = Platform(x, y) platforms.append(p) entities.add(p) if col == "e": e = ExitBlock(x, y) platforms.append(e) entities.add(e) if col == "B": B = PreviousBlock(x, y) platforms.append(B) entities.add(B) if col == "K": k = King(x, y) platforms.append(k) entities.add(k) if col == "F": F = Princess(x, y) platforms.append(F) entities.add(F) x += 16*3 y += 16*3 x = 0 total_level_width = len(level[0])*16*3 total_level_height = len(level)*16*3 camera = Camera(complex_camera, total_level_width, total_level_height) player = Player(newX, newY) entities.add(player) #game run loop while 1: timer.tick(60) time = time + 1 #3 minute timer to find the princess if time == 10800: break; #allows for character to be moved for e in pygame.event.get(): if e.type == QUIT: raise SystemExit("QUIT") if e.type == KEYDOWN and e.key == K_ESCAPE: raise SystemExit("ESCAPE") if e.type == KEYDOWN and e.key == K_UP: up = True if e.type == KEYDOWN and e.key == K_DOWN: down = True if e.type == KEYDOWN and e.key == K_LEFT: left = True if e.type == KEYDOWN and e.key == K_RIGHT: right = True if e.type == KEYUP and e.key == K_UP: up = False if e.type == KEYUP and e.key == K_DOWN: down = False if e.type == KEYUP and e.key == K_RIGHT: right = False if e.type == KEYUP and e.key == K_LEFT: left = False screen.blit(background,(0,0)) camera.update(player) # update player, draw everything else player.update(up, down, left, right, running, platforms) #if reached portal, move to respective map or finish the game if (moveNext == True or movePrev == True or done == True): x=0 y=0 if moveNext: currLevel = currLevel + 1 if movePrev: currLevel = currLevel - 1 #reset platforms in order to build the new map platforms=[] #get the next or previous level level = getLevel(currLevel) #if game is finished, display dialogue and leave game loop if done: for e in entities: screen.blit(e.image, camera.apply(e)) speech = pygame.image.load("images/princess-dialogue.png").convert_alpha() screen.blit(speech, (40,0)) pygame.display.update() sleep(2) break entities = pygame.sprite.Group() for row in level: for col in row: if col == "P": p = Platform(x, y) platforms.append(p) entities.add(p) if col == "e": e = ExitBlock(x, y) platforms.append(e) entities.add(e) if col == "B": B = PreviousBlock(x, y) platforms.append(B) entities.add(B) if col == "K": k = King(x, y) platforms.append(k) entities.add(k) if col == "F": F = Princess(x, y) platforms.append(F) entities.add(F) x += 16*3 y += 16*3 x = 0 total_level_width = len(level[0])*16*3 total_level_height = len(level)*16*3 camera = Camera(complex_camera, total_level_width, total_level_height) player = Player(newX, newY) entities.add(player) sleep(.4) #draw all the entities added through level generation for e in entities: screen.blit(e.image, camera.apply(e)) pygame.display.update() #if done then you reached the princess - show proper message if done: #display end dialogue screen.fill(black) speech = pygame.image.load("images/end-dialogue.png").convert_alpha() #363 is width of image and 90 is height - will center it screen.blit(speech, (HALF_WIDTH - 363/2, HALF_HEIGHT - 90/2)) pygame.display.update() sleep(2.5) #otherwise show failure message else: screen.fill(black) speech = pygame.image.load("images/fail.png") #363 is width of image and 90 is height - will center it screen.blit(speech, (HALF_WIDTH - 363/2, HALF_HEIGHT - 90/2)) pygame.display.update() sleep(2.5) #allows for the camera to focus on the player - source provided #at start of the file class Camera(object): def __init__(self, camera_func, width, height): self.camera_func = camera_func self.state = Rect(0, 0, width, height) def apply(self, target): return target.rect.move(self.state.topleft) def update(self, target): self.state = self.camera_func(self.state, target.rect) def simple_camera(camera, target_rect): l, t, _, _ = target_rect _, _, w, h = camera return Rect(-l+HALF_WIDTH, -t+HALF_HEIGHT, w, h) def complex_camera(camera, target_rect): l, t, _, _ = target_rect _, _, w, h = camera l, t, _, _ = -l+HALF_WIDTH, -t+HALF_HEIGHT, w, h l = min(0, l) # stop scrolling at the left edge l = max(-(camera.width-WIN_WIDTH), l) # stop scrolling at the right edge t = max(-(camera.height-WIN_HEIGHT), t) # stop scrolling at the bottom t = min(0, t) # stop scrolling at the top return Rect(l, t, w, h) #returns the next or previous level for generation #sets character spawn coordinates def getLevel(currLevel): global newX global newY global moveNext global movePrev level = [] if currLevel == 1: level = [ "PPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPP", "P P", "P e ", "P p", "P PPPPPPPPP PPP", "P PP P", "P PP P", "P P", "P PPPPPPPP P", "P PP P", "P PPPPPPP P", "P PPPPPP P", "P P", "P PPPPPPP P", "P PP P", "P PPPPPP P", "P P", "P PPPPPPPPPPP P", "P P", "P P", "P PPPPPPPPPPP P", "P PP P", "P PP P", "P P", "P K P", "PPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPP",] total_level_width = len(level[0])*16*3 total_level_height = len(level)*16*3 if movePrev: newX = total_level_width - 150 newY = 164 else: newX = total_level_width - 150 newY = total_level_height - 80 elif currLevel == 2: level = [ "PPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPP", "e P", "p P", "PPP P", "P PP P", "P PP P", "P PP PP P", "P P P", "P PP P", "P PP P", "P P", "P P", "P PP P", "P P", "P P", "P PP P", "P P", "P P", "P PP P", "P PP P", "P P", "P P P", "P P", "B PP P", "B P", "PPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPP",] total_level_width = len(level[0])*16*3 total_level_height = len(level)*16*3 if movePrev: newX = 100 newY = 150 else: newX = 100 newY = total_level_height - 80 elif currLevel == 3: level = [ "PPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPP", " P", "F P", "PPP P", "P P P", "P PP PP P", "P P PP P", "P PP P", "P P", "P P", "P P P", "P P", "P PP P", "P PP P", "P P P", "P P P", "P P", "P P P", "P P P", "P PP P", "P PP P", "P P P", "P PP P P", "P P", "P P", "P PP P", "P P", "P P", "P PPP P", "P B", "P B", "PPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPP",] total_level_width = len(level[0])*16*3 total_level_height = len(level)*16*3 if movePrev: newX = total_level_width - 150 newY = total_level_height - 80 else: newX = total_level_width - 150 newY = total_level_height - 80 moveNext = False movePrev = False return level #base entity that is used to create most objects class Entity(pygame.sprite.Sprite): def __init__(self): pygame.sprite.Sprite.__init__(self) #player class that contains the image and position(rectangle) #updates player position based on keypress and detects collision class Player(Entity): def __init__(self, x, y): Entity.__init__(self) self.xvel = 0 self.yvel = 0 self.faceright = False self.onGround = False self.airborne = True self.counter = 0 self.image = knightstand1 self.rect = Rect(x, y, 16*4, 32*3) def update(self, up, down, left, right, running, platforms): if up: # only jump if on the ground if self.onGround: self.yvel -= 10 if down: pass if running: self.xvel = 12 if left: self.xvel = -8 self.faceright = False if right: self.xvel = 8 self.faceright = True if not self.onGround: # only accelerate with gravity if in the air self.yvel += 0.35 # max falling speed if self.yvel > 100: self.yvel = 100 if not(left or right): self.xvel = 0 if self.yvel < 0 or self.yvel > 1.2: self.airborne = True # increment in x direction self.rect.left += self.xvel # do x-axis collisions self.collide(self.xvel, 0, platforms) # increment in y direction self.rect.top += self.yvel # assuming we're in the air self.onGround = False; # do y-axis collisions self.collide(0, self.yvel, platforms) self.animate() #will perform different actions based on what the player #is colliding with def collide(self, xvel, yvel, platforms): global done for p in platforms: if pygame.sprite.collide_rect(self, p): if isinstance(p, PreviousBlock): global movePrev movePrev = True if isinstance(p, ExitBlock): global moveNext moveNext = True if isinstance(p, Princess): done = True if isinstance(p, King): speech = pygame.image.load("images/king-dialogue.png").convert_alpha() screen.blit(speech, (440,450)) if xvel > 0: self.rect.right = p.rect.left if xvel < 0: self.rect.left = p.rect.right if yvel > 0: self.rect.bottom = p.rect.top self.onGround = True self.airborne = False self.yvel = 0 if yvel < 0: self.rect.top = p.rect.bottom #Jump animations def animate(self): if self.xvel > 0 or self.xvel < 0: self.walkloop() if self.airborne: self.updatecharacter(knightjump1) else: self.updatecharacter(knightstand1) if self.airborne: self.updatecharacter(knightjump1) #walk animations - done by alernating images def walkloop(self): if self.counter == 5: self.updatecharacter(knightwalk1) elif self.counter == 10: self.updatecharacter(knightwalk2) elif self.counter == 15: self.updatecharacter(knightwalk3) self.counter = 0 self.counter = self.counter + 1 def updatecharacter(self, ansurf): if not self.faceright: ansurf = pygame.transform.flip(ansurf,True,False) self.image = ansurf #block used to create the map class Platform(Entity): def __init__(self, x, y): Entity.__init__(self) self.image = pygame.image.load("images/block.png").convert_alpha() self.image = pygame.transform.scale(self.image,(16*3,16*3)) self.rect = Rect(x, y, 16*3, 16*3) #used to create the King NPC class King(Entity): def __init__(self, x, y): Entity.__init__(self) self.image = pygame.image.load("images/king.png").convert_alpha() self.image = pygame.transform.scale(self.image,(16*4,16*3*2)) self.rect = Rect(x, y-16*3, 16*3, 16*3*2) #create the Prinecss NPC class Princess(Entity): def __init__(self, x, y): Entity.__init__(self) self.image = pygame.image.load("images/p2.png").convert_alpha() self.image = pygame.transform.scale(self.image,(16*4,16*3*2)) self.rect = Rect(x, y-16*3, 16*3, 16*3*2) #used to determine exit to the new map #currently image just set to blue filling for distinction class ExitBlock(Entity): def __init__(self, x, y): Entity.__init__(self) self.image = pygame.image.load("images/gate.png").convert_alpha() self.image = pygame.transform.scale(self.image,(16*6, 16*6)) self.rect = Rect(x, y, 16*6, 16*6) #used to determine exit to the previous map #currently image just set to blue filling for distinction class PreviousBlock(Platform): def __init__(self, x, y): Entity.__init__(self) self.image = pygame.image.load("images/gate.png").convert_alpha() self.image = pygame.transform.scale(self.image,(1,16*6)) self.rect = Rect(x, y, 16*6, 16*6) if __name__ == "__main__": main()

[ "noreply@github.com" ]

ChristopherMeneses.noreply@github.com

c349a23b05207454c50dc53da385c0f8d8822ee9

b3edb28272b2c064f7302e8ec52f0140292d21d7

/pipeline.py

fbfd95a1c26c4970d3d3afa5392c6cdf60baa6e3

[]

no_license

mattmiller899/LSTM_app

4cdadc62e67c2e7a1c923def493b765c22ecf7e0

ae599e5157f69be827a841d1f46681baaf5d78ea

refs/heads/master

2020-04-03T17:45:54.566811

2018-10-30T21:21:35

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import sys import numpy as np import argparse from preprocess import * def get_args(): parser = argparse.ArgumentParser(description='Generate n-grams and GloVe vectors') parser.add_argument('-k', dest='k', type=int, default=6, help='Length of kmer') parser.add_argument('-s', dest='s', type=int, default=2, help='Stride of splitting sequences into kmers') parser.add_argument('-n', dest='neg_dir', help='Path to the directory of the negative files') parser.add_argument('-o', dest='work_dir', help='Directory where output will be stored') parser.add_argument('-p', dest='pos_dir', help='Path to the directory of the positive files') args = parser.parse_args() return args def main(): args = get_args() Pipeline(**args.__dict__).run(input_dir=args.input_dir) if __name__ == "__main__": main() class Pipeline: def __init__(self, k, s, work_dir, pos_dir, neg_dir, **kwargs # allows some command line arguments to be ignored ): self.k = k self.s = s self.work_dir = output_dir if not os.path.isdir(self.work_dir): os.makedirs(self.work_dir) self.pos_dir = pos_dir self.neg_dir = neg_dir def run(self, input_dir): output_dir_list = list() output_dir_list.append(self.step_01_gen_kmers()) output_dir_list.append(self.step_02_qc_reads_with_vsearch(input_dir=output_dir_list[-1])) def initialize_step(self): function_name = sys._getframe(1).f_code.co_name log = logging.getLogger(name=function_name) log.setLevel(logging.WARNING) output_dir = create_output_dir(output_dir_name=function_name, parent_dir=self.work_dir, debug=self.debug) return log, output_dir def complete_step(self, log, output_dir): output_dir_list = sorted(os.listdir(output_dir)) if len(output_dir_list) == 0: raise PipelineException('ERROR: no output files in directory "{}"'.format(output_dir)) return def step_01_gen_kmers(self): log, output_dir = self.initialize_step() if len(os.listdir(output_dir)) > 0: log.warning('output directory "%s" is not empty, this step will be skipped', output_dir) else: pos_files = glob.glob(os.path.join(self.pos_dir, '*')) neg_files = glob.glob(os.path.join(self.neg_dir, '*')) log.info('Pos files: "%s"' % pos_files) log.info('Neg files: "%s"' % neg_files) for input_file in pos_files: input_name = os.path.splittext(os.path.basename(input_file))[0] output_file = os.path.join(output_dir, '%s_%dmer_%dstride' % (input_name, self.k, self.s)) seq2kmer(input_file, output_file) glove_file = '%s_corpus' forglove(output_file, glove_file) for input_file in neg_files: input_name = os.path.splittext(os.path.basename(input_file))[0] output_file = os.path.join(output_dir, '%s_%dmer_%dstride' % (input_name, self.k, self.s)) seq2kmer(input_file, output_file) complete_step(log, output_dir) return output_dir def step_02_glove(self, input_dir): log, output_dir = self.initialize_step() if len(os.listdir(output_dir)) > 0: log.warning('output directory "%s" is not empty, this step will be skipped', output_dir) else:

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import spacy, alg from scipy import sparse from alg import dphs, dtls, outphs, nlp from sklearn.metrics.pairwise import cosine_distances, euclidean_distances from sklearn.feature_extraction.text import TfidfTransformer, TfidfVectorizer print "Loading complete." def glem(x): d = nlp(unicode(x)) return " ".join((x.lemma_ for x in d if not x.is_stop and x.is_alpha and len(x.text) > 1)) try: d_xtr = [] for title in dtls.title.tolist(): b = alg.inxter(title,) b = alg.get_phs(*b) d_xtr.append("".join(b[:-1].rtw)) except IndexError, ex: print "Warning: %s\r\n" % ex.message v = TfidfVectorizer(token_pattern=u'(?ui)\\b\\w*[a-z]+\\w*\\b', preprocessor=glem, min_df=8, max_df=.9, norm="l2", stop_words=spacy.en.STOP_WORDS).fit(d_xtr) d_xtrtr = v.transform(d_xtr) def get_answer(q, upr=10): temp_results = dtls.iloc[cosine_distances(v.transform([q]), d_xtrtr)[0].argsort()[:10]].title.tolist() topresult = "".join( alg.get_phs(*alg.inxter(temp_results[0]))[:-1]\ .apply(lambda x: "" % int(x.fqs * (1.15 if x.fqs > 16 else 1.)) + ("" if "bold" in x.fqf.lower() else "") + x.rtw + ("" if "bold" in x.fqf.lower() else "") + "", axis=1)) if upr == 1: return topresult return [topresult] + ["".join( alg.get_phs(*alg.inxter(resix)).pipe(lambda x: x[:min(5, x.shape[0])])\ .apply(lambda x: "" % int(x.fqs * (1.15 if x.fqs > 16 else 1.)) + ("" if "bold" in x.fqf.lower() else "") + x.rtw + ("" if "bold" in x.fqf.lower() else "") + "", axis=1)) for resix in temp_results[1:min(upr, 10)]]

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#!/Users/carl/github/cvanderbush.github.io/jblog/bin/python3.6 """ Python Markdown, the Command Line Script ======================================== This is the command line script for Python Markdown. Basic use from the command line: markdown source.txt > destination.html Run "markdown --help" to see more options. See markdown/__init__.py for information on using Python Markdown as a module. ## Authors and License Started by [Manfred Stienstra](http://www.dwerg.net/). Continued and maintained by [Yuri Takhteyev](http://www.freewisdom.org), [Waylan Limberg](http://achinghead.com/) and [Artem Yunusov](http://blog.splyer.com). Contact: markdown@freewisdom.org Copyright 2007, 2008 The Python Markdown Project (v. 1.7 and later) Copyright 200? Django Software Foundation (OrderedDict implementation) Copyright 2004, 2005, 2006 Yuri Takhteyev (v. 0.2-1.6b) Copyright 2004 Manfred Stienstra (the original version) License: BSD (see docs/LICENSE for details). """ if __name__ == '__main__': from markdown.__main__ import run run()

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from __future__ import print_function import functools import hashlib import logging import os import shutil import sys import time from azure.datalake.store import core, multithread from azure.datalake.store.transfer import ADLTransferClient from azure.datalake.store.utils import WIN from tests.testing import md5sum def benchmark(f): @functools.wraps(f) def wrapped(*args, **kwargs): print('[%s] starting...' % (f.__name__)) start = time.time() result = f(*args, **kwargs) stop = time.time() elapsed = stop - start print('[%s] finished in %2.4fs' % (f.__name__, elapsed)) return result, elapsed return wrapped def mock_client(adl, nthreads): def transfer(adlfs, src, dst, offset, size, buffersize, blocksize, shutdown_event=None): pass def merge(adlfs, outfile, files, shutdown_event=None): pass return ADLTransferClient( adl, 'foo', transfer=transfer, merge=merge, nthreads=nthreads) def checksum(path): """ Generate checksum for file/directory content """ if not os.path.exists(path): return None if os.path.isfile(path): return md5sum(path) partial_sums = [] for root, dirs, files in os.walk(path): for f in files: filename = os.path.join(root, f) if os.path.exists(filename): partial_sums.append(str.encode(md5sum(filename))) return hashlib.md5(b''.join(sorted(partial_sums))).hexdigest() def du(path): """ Find total size of content used by path """ if os.path.isfile(path): return os.path.getsize(path) size = 0 for root, dirs, files in os.walk(path): for f in files: size += os.path.getsize(os.path.join(root, f)) return size def verify(instance): """ Confirm whether target file matches source file """ adl = instance.client._adlfs lfile = instance.lpath rfile = instance.rpath print("finish w/o error:", instance.successful()) print("local file :", lfile) if os.path.exists(lfile): print("local file size :", du(lfile)) else: print("local file size :", None) print("remote file :", rfile) if adl.exists(rfile, invalidate_cache=False): print("remote file size:", adl.du(rfile, total=True, deep=True)) else: print("remote file size:", None) @benchmark def bench_upload_1_50gb(adl, lpath, rpath, config): return multithread.ADLUploader( adl, lpath=lpath, rpath=rpath, **config[bench_upload_1_50gb.__name__]) @benchmark def bench_upload_50_1gb(adl, lpath, rpath, config): return multithread.ADLUploader( adl, lpath=lpath, rpath=rpath, **config[bench_upload_50_1gb.__name__]) @benchmark def bench_download_1_50gb(adl, lpath, rpath, config): return multithread.ADLDownloader( adl, lpath=lpath, rpath=rpath, **config[bench_download_1_50gb.__name__]) @benchmark def bench_download_50_1gb(adl, lpath, rpath, config): return multithread.ADLDownloader( adl, lpath=lpath, rpath=rpath, **config[bench_download_50_1gb.__name__]) def setup_logging(level='INFO'): """ Log only Azure messages, ignoring 3rd-party libraries """ levels = dict( CRITICAL=logging.CRITICAL, ERROR=logging.ERROR, WARNING=logging.WARNING, INFO=logging.INFO, DEBUG=logging.DEBUG) if level in levels: level = levels[level] else: raise ValueError('invalid log level: {}'.format(level)) logging.basicConfig( format='%(asctime)s %(name)-17s %(levelname)-8s %(message)s') logger = logging.getLogger('azure.datalake.store') logger.setLevel(level) def print_summary_statistics(stats): from statistics import mean, median, pstdev print("benchmark min mean sd median max") for benchmark, samples in stats.items(): if samples: metrics = [int(round(fn(samples), 0)) for fn in [min, mean, pstdev, median, max]] else: metrics = [0, 0, 0, 0, 0] print(benchmark, *metrics) if __name__ == '__main__': import argparse parser = argparse.ArgumentParser() parser.add_argument('local_path', type=str) parser.add_argument('remote_path', type=str) parser.add_argument('-l', '--log-level', default='INFO') parser.add_argument('-n', '--iterations', default=1, type=int) parser.add_argument('-q', '--quiet', dest='verbose', action='store_false') parser.add_argument('-s', '--statistics', action='store_true') parser.add_argument('--no-verify', dest='verify', action='store_false') parser.add_argument('--no-checksum', dest='validate', action='store_false') args = parser.parse_args(sys.argv[1:]) setup_logging(level=args.log_level) adl = core.AzureDLFileSystem() # Required setup until outstanding issues are resolved adl.mkdir(args.remote_path) # OS-specific settings if WIN: config = { 'bench_upload_1_50gb': { 'nthreads': 64, 'buffersize': 32 * 2**20, 'blocksize': 4 * 2**20 }, 'bench_upload_50_1gb': { 'nthreads': 64, 'buffersize': 32 * 2**20, 'blocksize': 4 * 2**20 }, 'bench_download_1_50gb': { 'nthreads': 64, 'buffersize': 32 * 2**20, 'blocksize': 4 * 2**20 }, 'bench_download_50_1gb': { 'nthreads': 64, 'buffersize': 32 * 2**20, 'blocksize': 4 * 2**20 } } else: config = { 'bench_upload_1_50gb': { 'nthreads': 64, 'buffersize': 4 * 2**20, 'blocksize': 4 * 2**20 }, 'bench_upload_50_1gb': { 'nthreads': 64, 'buffersize': 4 * 2**20, 'blocksize': 4 * 2**20 }, 'bench_download_1_50gb': { 'nthreads': 16, 'buffersize': 4 * 2**20, 'blocksize': 4 * 2**20 }, 'bench_download_50_1gb': { 'nthreads': 16, 'buffersize': 4 * 2**20, 'blocksize': 4 * 2**20 } } for benchmark in config: config[benchmark]['verbose'] = args.verbose stats = {} for _ in range(args.iterations): # Upload/download 1 50GB files lpath_up = os.path.join(args.local_path, '50gbfile.txt') lpath_down = os.path.join(args.local_path, '50gbfile.txt.out') rpath = args.remote_path + '/50gbfile.txt' if adl.exists(rpath, invalidate_cache=False): adl.rm(rpath) if os.path.exists(lpath_down): os.remove(lpath_down) result, elapsed = bench_upload_1_50gb(adl, lpath_up, rpath, config) if args.verify: verify(result) if result.successful: stats.setdefault('up-1-50gb', []).append(elapsed) result, elapsed = bench_download_1_50gb(adl, lpath_down, rpath, config) if args.verify: verify(result) if result.successful: stats.setdefault('down-1-50gb', []).append(elapsed) if args.validate: print(checksum(lpath_up), lpath_up) print(checksum(lpath_down), lpath_down) # Upload/download 50 1GB files lpath_up = os.path.join(args.local_path, '50_1GB_Files') lpath_down = os.path.join(args.local_path, '50_1GB_Files.out') rpath = args.remote_path + '/50_1GB_Files' if adl.exists(rpath): adl.rm(rpath, recursive=True) if os.path.exists(lpath_down): shutil.rmtree(lpath_down) result, elapsed = bench_upload_50_1gb(adl, lpath_up, rpath, config) if args.verify: verify(result) if result.successful: stats.setdefault('up-50-1gb', []).append(elapsed) result, elapsed = bench_download_50_1gb(adl, lpath_down, rpath, config) if args.verify: verify(result) if result.successful: stats.setdefault('down-50-1gb', []).append(elapsed) if args.validate: print(checksum(lpath_up), lpath_up) print(checksum(lpath_down), lpath_down) if args.statistics: print_summary_statistics(stats)

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def sum(n): output = 0 for i in range(1,1+n): output = output + i*i return output print(sum(5))

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# -*- coding: utf-8 -*- """ Created on Sun Oct 05 17:42:10 2014 @author: Administrator """ from numpy import * from MNISTData import * trainingData, trainingLabel, testData, testLabel = getData() hit = 0 for sample in range(10000): # sample = random.randint(0,10000) testPoint = testData[sample,:] distance = subtract(trainingData, testPoint,dtype = int) distance = distance**2 distance = sum(distance, axis = 1) guest = trainingLabel[argmin(distance)] if guest == testLabel[sample]: hit += 1 # else: # print "sample",sample,":real",testLabel[sample],"guest", guest print "\ntest complete!" print hit,"hit" print "correct rate:", (hit/100.0)*100,"%"

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""" tuple read-only list """ # create a tuple my_tuple1 = (1, 2, 3, 4, 5, 6, 7, 8) print(my_tuple1) my_tuple2 = () print(my_tuple2) # create a tuple with only one element my_tuple3 = (1) print(my_tuple3) my_tuple3 = ('abc') print(my_tuple3) my_tuple3 = 1 my_tuple3 = (1,) print(my_tuple3) # create nested tuple my_tuple4 = (1, 2, 3) print(my_tuple4) my_tuple4 = (('a','b'), 2, ('c','d')) print(my_tuple4) my_tuple4 = (('a','b'), ('c','d'), ('c','d')) print(my_tuple4) # create mix tuple my_tuple5 = (['a','b'], ('c','d'), ('c','d')) my_tuple5 = (['a','b'], ([1,2],'d'), ('c','d')) # compare # student profile collection # pre-set scouting path a = [(), (), ()] # saving-slot in a game b = ([], [], []) # create a tuple by auto-packing my_tuple = 1,2,'a' print(my_tuple, type(my_tuple)) # unpacking x, y, z = my_tuple print(x) print(y) print(z)

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# -*- coding: utf-8 -*- import ast import datetime as dt import json import sqlite3 import string import threading import uuid from collections import namedtuple import jinja2 from jinja2 import Markup, Template from operator import itemgetter from os.path import basename, join, splitext from flask_mail import Message, Mail from sqlalchemy import func from polylogyx.plugins import AbstractAlerterPlugin from polylogyx.constants import DEFAULT_PLATFORMS, PolyLogyxServerDefaults, public_server import pkg_resources import requests import six from flask import current_app, flash, render_template from polylogyx.database import db from polylogyx.models import ( DistributedQuery, DistributedQueryTask, Node, Pack, Query, ResultLog, querypacks, Options, Tag, DefaultQuery, DefaultFilters, StatusLog) Field = namedtuple('Field', ['name', 'action', 'columns', 'timestamp','uuid']) # Read DDL statements from our package schema = pkg_resources.resource_string('polylogyx', join('resources', 'osquery_schema.sql')) schema = schema.decode('utf-8') schema = [x for x in schema.strip().split('\n') if not x.startswith('--')] # SQLite in Python will complain if you try to use it from multiple threads. # We create a threadlocal variable that contains the DB, lazily initialized. osquery_mock_db = threading.local() def assemble_configuration(node): platform = node.platform if platform not in DEFAULT_PLATFORMS: platform = 'linux' platform_filter = DefaultFilters.query.filter(DefaultFilters.platform == platform).first() configuration = {} if platform_filter and platform_filter.filters: configuration = platform_filter.filters configuration['options'] = assemble_options(node) configuration['file_paths'] = assemble_file_paths(node) configuration['schedule'] = assemble_schedule(node) configuration['packs'] = assemble_packs(node) return configuration def assemble_options(node): options = {'disable_watchdog': True, 'logger_tls_compress': True} # https://github.com/facebook/osquery/issues/2048#issuecomment-219200524 if current_app.config['POLYLOGYX_EXPECTS_UNIQUE_HOST_ID']: options['host_identifier'] = 'uuid' else: options['host_identifier'] = 'hostname' options['schedule_splay_percent'] = 10 existing_option = Options.query.filter(Options.name == PolyLogyxServerDefaults.plgx_config_all_options).first() if existing_option: existing_option_value = json.loads(existing_option.option) options = merge_two_dicts(options, existing_option_value) return options def assemble_file_paths(node): file_paths = {} for file_path in node.file_paths.options(db.lazyload('*')): file_paths.update(file_path.to_dict()) return file_paths def assemble_schedule(node): schedule = {} for query in node.queries.options(db.lazyload('*')): schedule[query.name] = query.to_dict() platform = node.platform if platform not in DEFAULT_PLATFORMS: platform = 'linux' for default_query in DefaultQuery.query.filter(DefaultQuery.status == True).filter( DefaultQuery.platform == platform).all(): schedule[default_query.name] = default_query.to_dict() return schedule def assemble_packs(node): packs = {} for pack in node.packs.join(querypacks).join(Query) \ .options(db.contains_eager(Pack.queries)).all(): packs[pack.name] = pack.to_dict() return packs def assemble_distributed_queries(node): ''' Retrieve all distributed queries assigned to a particular node in the NEW state. This function will change the state of the distributed query to PENDING, however will not commit the change. It is the responsibility of the caller to commit or rollback on the current database session. ''' now = dt.datetime.utcnow() pending_query_count = 0 query_recon_count = db.session.query(db.func.count(DistributedQueryTask.id)) \ .filter( DistributedQueryTask.node == node, DistributedQueryTask.status == DistributedQueryTask.NEW, DistributedQueryTask.priority == DistributedQueryTask.HIGH, ) for r in query_recon_count: pending_query_count = r[0] if pending_query_count > 0: query = db.session.query(DistributedQueryTask) \ .join(DistributedQuery) \ .filter( DistributedQueryTask.node == node, DistributedQueryTask.status == DistributedQueryTask.NEW, DistributedQuery.not_before < now, DistributedQueryTask.priority == DistributedQueryTask.HIGH, ).options( db.lazyload('*'), db.contains_eager(DistributedQueryTask.distributed_query) ) else: query = db.session.query(DistributedQueryTask) \ .join(DistributedQuery) \ .filter( DistributedQueryTask.node == node, DistributedQueryTask.status == DistributedQueryTask.NEW, DistributedQuery.not_before < now, DistributedQueryTask.priority == DistributedQueryTask.LOW, ).options( db.lazyload('*'), db.contains_eager(DistributedQueryTask.distributed_query) ).limit(1) queries = {} for task in query: if task.sql: queries[task.guid] = task.sql else: queries[task.guid] = task.distributed_query.sql task.update(status=DistributedQueryTask.PENDING, timestamp=now, commit=False) # add this query to the session, but don't commit until we're # as sure as we possibly can be that it's been received by the # osqueryd client. unfortunately, there are no guarantees though. db.session.add(task) return queries def merge_two_dicts(x, y): if not x: x = {} if not y: y = {} z = x.copy() # start with x's keys and values z.update(y) # modifies z with y's keys and values & returns None return z def create_query_pack_from_upload(upload): ''' Create a pack and queries from a query pack file. **Note**, if a pack already exists under the filename being uploaded, then any queries defined here will be added to the existing pack! However, if a query with a particular name already exists, and its sql is NOT the same, then a new query with the same name but different id will be created (as to avoid clobbering the existing query). If its sql is identical, then the query will be reused. ''' # The json package on Python 3 expects a `str` input, so we're going to # read the body and possibly convert to the right type body = upload.data.read() if not isinstance(body, six.string_types): body = body.decode('utf-8') try: data = json.loads(body) except ValueError: flash(u"Could not load pack as JSON - ensure it is JSON encoded", 'danger') return None else: if 'queries' not in data: flash(u"No queries in pack", 'danger') return None name = splitext(basename(upload.data.filename))[0] pack = Pack.query.filter(Pack.name == name).first() if not pack: current_app.logger.debug("Creating pack %s", name) pack = Pack.create(name=name, **data) for query_name, query in data['queries'].items(): if not validate_osquery_query(query['query']): flash('Invalid osquery query: "{0}"'.format(query['query']), 'danger') return None q = Query.query.filter(Query.name == query_name).first() if not q: q = Query.create(name=query_name, **query) pack.queries.append(q) current_app.logger.debug("Adding new query %s to pack %s", q.name, pack.name) continue if q in pack.queries: continue if q.sql == query['query']: current_app.logger.debug("Adding existing query %s to pack %s", q.name, pack.name) pack.queries.append(q) else: q2 = Query.create(name=query_name, **query) current_app.logger.debug( "Created another query named %s, but different sql: %r vs %r", query_name, q2.sql.encode('utf-8'), q.sql.encode('utf-8')) pack.queries.append(q2) else: pack.save() flash(u"Imported query pack {0}".format(pack.name), 'success') return pack def get_node_health(node): checkin_interval = current_app.config['POLYLOGYX_CHECKIN_INTERVAL'] if isinstance(checkin_interval, (int, float)): checkin_interval = dt.timedelta(seconds=checkin_interval) if (dt.datetime.utcnow() - node.last_checkin) > checkin_interval: return u'danger' else: return '' # Not super-happy that we're duplicating this both here and in the JS, but I # couldn't think of a nice way to pass from JS --> Python (or the other # direction). PRETTY_OPERATORS = { 'equal': 'equals', 'not_equal': "doesn't equal", 'begins_with': 'begins with', 'not_begins_with': "doesn't begins with", 'contains': 'contains', 'not_contains': "doesn't contain", 'ends_with': 'ends with', 'not_ends_with': "doesn't end with", 'is_empty': 'is empty', 'is_not_empty': 'is not empty', 'less': 'less than', 'less_or_equal': 'less than or equal', 'greater': 'greater than', 'greater_or_equal': 'greater than or equal', 'matches_regex': 'matches regex', 'not_matches_regex': "doesn't match regex", } def pretty_operator(cond): return PRETTY_OPERATORS.get(cond, cond) PRETTY_FIELDS = { 'query_name': 'Query name', 'action': 'Action', 'host_identifier': 'Host identifier', 'timestamp': 'Timestamp', } def pretty_field(field): return PRETTY_FIELDS.get(field, field) _js_escapes = { '\\': '\\u005C', '\'': '\\u0027', '"': '\\u0022', '>': '\\u003E', '<': '\\u003C', '&': '\\u0026', '=': '\\u003D', '-': '\\u002D', ';': '\\u003B', u'\u2028': '\\u2028', u'\u2029': '\\u2029' } # Escape every ASCII character with a value less than 32. _js_escapes.update(('%c' % z, '\\u%04X' % z) for z in range(32)) def jinja2_escapejs_filter(value): retval = [] if not value: return '' else: for letter in value: if letter in _js_escapes.keys(): retval.append(_js_escapes[letter]) else: retval.append(letter) return jinja2.Markup("".join(retval)) # Since 'string.printable' includes control characters PRINTABLE = string.ascii_letters + string.digits + string.punctuation + ' ' def quote(s, quote='"'): buf = [quote] for ch in s: if ch == quote or ch == '\\': buf.append('\\') buf.append(ch) elif ch == '\n': buf.append('\\n') elif ch == '\r': buf.append('\\r') elif ch == '\t': buf.append('\\t') elif ch in PRINTABLE: buf.append(ch) else: # Hex escape buf.append('\\x') buf.append(hex(ord(ch))[2:]) buf.append(quote) return ''.join(buf) def _carve(string): return str(string).title() def create_mock_db(): mock_db = sqlite3.connect(':memory:') mock_db.create_function("carve", 1, _carve) for ddl in schema: mock_db.execute(ddl) cursor = mock_db.cursor() cursor.execute("SELECT name,sql FROM sqlite_master WHERE type='table';") from polylogyx.constants import PolyLogyxServerDefaults extra_schema = current_app.config.get('POLYLOGYX_EXTRA_SCHEMA', []) for ddl in extra_schema: mock_db.execute(ddl) for osquery_table in cursor.fetchall(): PolyLogyxServerDefaults.POLYLOGYX_OSQUERY_SCHEMA_JSON[osquery_table[0]] = osquery_table[1] return mock_db def create_tags(*tags): values = [] existing = [] # create a set, because we haven't yet done our association_proxy in # sqlalchemy for value in (v.strip() for v in set(tags) if v.strip()): tag = Tag.query.filter(Tag.value == value).first() if not tag: values.append(Tag.create(value=value)) else: existing.append(tag) else: if values: flash(u"Created tag{0} {1}".format( 's' if len(values) > 1 else '', ', '.join(tag.value for tag in values)), 'info') return values + existing def validate_osquery_query(query): # Check if this thread has an instance of the SQLite database db = getattr(osquery_mock_db, 'db', None) if db is None: db = create_mock_db() osquery_mock_db.db = db try: db.execute(query) except sqlite3.Error: current_app.logger.exception("Invalid query: %s", query) return False return True def learn_from_result(result, node): if not result['data']: return capture_columns = set( map(itemgetter(0), current_app.config['POLYLOGYX_CAPTURE_NODE_INFO'] ) ) if not capture_columns: return node_info = node.get('node_info', {}) orig_node_info = node_info.copy() for _, action, columns, _, _, in extract_results(result): # only update columns common to both sets for column in capture_columns & set(columns): cvalue = node_info.get(column) # current value value = columns.get(column) if action == 'removed' and (cvalue is None or cvalue != value): pass elif action == 'removed' and cvalue == value: node_info.pop(column) elif action == 'added' and (cvalue is None or cvalue != value): node_info[column] = value # only update node_info if there's actually a change if orig_node_info == node_info: return node = Node.get_by_id(node['id']) node.update(node_info=node_info) return def process_result(result, node): if not result['data']: return result_logs=[] subject_dn = [] for name, action, columns, timestamp,uuid in extract_results(result): if 'subject_dn' in columns and columns['subject_dn'] and columns['subject_dn'] != '': subject_dn.append(columns['subject_dn']) else: result_logs.append( ResultLog(name=name,uuid=uuid, action=action, columns=columns, timestamp=timestamp, node_id=node['id'])) return result_logs def extract_results(result): """ extract_results will convert the incoming log data into a series of Fields, normalizing and/or aggregating both batch and event format into batch format, which is used throughout the rest of polylogyx. """ if not result['data']: return timefmt = '%a %b %d %H:%M:%S %Y UTC' strptime = dt.datetime.strptime for entry in result['data']: if 'uuid' not in entry: entry['uuid']=str(uuid.uuid4()) name = entry['name'] timestamp = strptime(entry['calendarTime'], timefmt) if 'columns' in entry: yield Field(name=name, action=entry['action'], columns=entry['columns'], timestamp=timestamp,uuid=entry['uuid']) elif 'diffResults' in entry: added = entry['diffResults']['added'] removed = entry['diffResults']['removed'] for (action, items) in (('added', added), ('removed', removed)): # items could be "", so we're still safe to iter over # and ensure we don't return an empty value for columns for columns in items: yield Field(name=name, action=action, columns=columns, timestamp=timestamp,uuid=entry['uuid']) elif 'snapshot' in entry: for columns in entry['snapshot']: yield Field(name=name, action='snapshot', columns=columns, timestamp=timestamp,uuid=entry['uuid']) else: current_app.logger.error("Encountered a result entry that " "could not be processed! %s", json.dumps(entry)) class DateTimeEncoder(json.JSONEncoder): def default(self, o): if isinstance(o, dt.datetime): return o.isoformat() return json.JSONEncoder.default(self, o) def render_column(value, column): renders = current_app.config.get('DOORMAN_COLUMN_RENDER', {}) if column not in renders: return value template = renders[column] try: if callable(template): return template(value) else: template = Template(template, autoescape=True) rendered = template.render(value=value) # return a markup object so that the template where this is # rendered is not escaped again return Markup(rendered) except Exception: current_app.logger.exception( "Failed to render %s, returning original value", column ) return value class Serializer(object): @staticmethod def serialize(object): return json.dumps(object, default=lambda o: o.__dict__.values()[0]) def check_and_save_intel_alert(scan_type, scan_value, data, source, severity): from polylogyx.models import Alerts, db result_logs = ResultLog.query.filter(ResultLog.columns[scan_type].astext == scan_value).all() for result_log in result_logs: alert_count = db.session.query(func.count(Alerts.id)).filter(Alerts.source == source).filter( Alerts.result_log_uid == result_log.uuid).scalar() if alert_count == 0: save_intel_alert(data=data, source=source, severity=severity, query_name=result_log.name, uuid=result_log.uuid, columns=result_log.columns, node_id=result_log.node_id) def save_intel_alert(data, source, severity, query_name, uuid, columns, node_id): from polylogyx.models import Alerts alert = Alerts.create(message=columns, query_name=query_name, result_log_uid=uuid, node_id=node_id, rule_id=None, type=Alerts.THREAT_INTEL, source=source, source_data=data, recon_queries={}, severity=severity) from polylogyx.rules import IntelMatch intel = {'type': Alerts.THREAT_INTEL, 'source': source, 'severity': severity, 'query_name': query_name} json_data = "" if data: json_data = json.dumps(data) intel_match = IntelMatch(intel=intel, result=columns, data=json_data, alert_id=alert.id, node=node_id) node = db.session.query(Node).filter(Node.id == node_id).first().to_dict() send_alert(node, None, intel_match) def send_alert(node, rule_match, intel_match): from polylogyx.models import current_app as app alerters = app.config.get('POLYLOGYX_ALERTER_PLUGINS', {}) for name, (plugin, config) in alerters.items(): package, classname = plugin.rsplit('.', 1) from importlib import import_module module = import_module(package) klass = getattr(module, classname, None) if klass is None: raise ValueError('Could not find a class named "{0}" in package "{1}"'.format(classname, package)) if not issubclass(klass, AbstractAlerterPlugin): raise ValueError('{0} is not a subclass of AbstractAlerterPlugin'.format(name)) alerters[name] = klass(config) for alerter in alerters: try: alerters[alerter].handle_alert(node, rule_match, intel_match) except Exception as e: current_app.logger.error(e) def flatten_json(input): output = dict(input) if 'columns' in output: for key, value in output['columns'].items(): output[key] = value output.pop('columns', None) return output def append_node_information_to_result_log(node, input): output = dict(input) try: output['platform'] = node['platform'] output['last_checkin'] = node['last_checkin'] output['is_active'] = node['is_active'] output['last_ip'] = node['last_ip'] if 'os_info' in node: os_info = node['os_info'] output['osname'] = os_info.get("name", "") output['version'] = os_info['version'] if 'node_info' in node: node_info = node['node_info'] output['computername'] = node_info['computer_name'] output['hardware_model'] = node_info['hardware_model'] output['hardware_vendor'] = node_info['hardware_vendor'] output['cpu_physical_cores'] = node_info['cpu_physical_cores'] except Exception as e: current_app.logger.error(e) return output def append_node_and_rule_information_to_alert(node, input): output = dict(input) try: output['platform'] = node['platform'] output['is_active'] = node['is_active'] output['last_ip'] = node['last_ip'] output['platform'] = node['platform'] if 'os_info' in node: os_info = node['os_info'] output['osname'] = os_info['name'] if 'network_info' in node: network_info = node['network_info'] output['macaddress'] = network_info['mac_address'] if 'node_info' in node: node_info = node['node_info'] output['computername'] = node_info['computer_name'] output['hardware_model'] = node_info['hardware_model'] except Exception as e: print(e) return output def extract_result_logs(result): """ extract_results will convert the incoming log data into a series of Fields, normalizing and/or aggregating both batch and event format into batch format, which is used throughout the rest of polylogyx. """ Field = namedtuple('Field', ['name', 'action', 'columns', 'timestamp', 'uuid','node_id']) for data in result: if not data.uuid: data.uuid = str(uuid.uuid4()) yield Field(name=data.name, action=data.action, columns=data.columns, timestamp=data.timestamp, uuid=data.uuid, node_id=data.node_id)

[ "moulik@polylogyx.com" ]

moulik@polylogyx.com

3348fdcc7921ae5ff3b1d096abd5c91d23e56d2c

287d35c59665030109ad91c8872cbd356056810a

/models/soil/deliverables.py

a25627e4832fe0dfd26ad5ad70d096f359f8084f

[]

no_license

nicetech-creator/agritecture-v2

d63573eb6e0e1abee8c157893c54c1f1ad243106

74f6f1bcc72dd48c67691ae7bb99dd34651660c4

refs/heads/master

2023-03-17T12:22:15.892900

2021-03-17T18:30:20

348,546,462

0

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UTF-8

Python

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25,464

py

from connection import fetch_one, fetch_all from cachetools.func import ttl_cache from caching import hashable_cache from util import parse_inputs, preload_outputs, quantize_outputs, set_if_unset import math from models.soil.input.land_status import Soil_Input_Land_Status from models.soil.sizing.area import Soil_Sizing_Area from models.soil.crop.characteristics import Soil_Crop_Characteristics from models.soil.crop.crop import Soil_Crop from models.soil.wastage.wastage import Soil_Wastage from models.soil.opex.overview import Soil_Opex_Overview from models.soil.capex.overview import Soil_Capex_Overview from models.financials.interest import Financials_Interest from models.financials.main import Financials_Main from models.financials.employees import Financials_Employees from models.financials.population_fed import Financials_Population_Fed class Soil_Deliverables: @staticmethod def info(): return { "name": "soil_deliverables", "description": "Deliverables for Soil" } @staticmethod def input_type(): return { "latitude": { "description": "Geographical latitude", "type": "decimal" }, "longitude": { "description": "Geographical longitude", "type": "decimal" }, "land status": { "type": "choice", "description": "Selection land status", "default": 1 }, "land cost": { "description": "Land cost per area ($ / sqft)", "type": "decimal" }, "owner is headgrower": { "description": "Whether owner counts as headgrower", "type": "bool", "default": True }, "headGrowerSalary": { "description": "Salary for headgrower ($ / y)", "default": 60000, "type": "decimal" }, "grower experience": { "type": "choice", "description": "Level of grower experience", "default": 1 }, "site area": { "description": "Total area to be allocated (sqft)", "type": "decimal" }, "crops": { "type": "list", "description": "Selection of crops to compute", "element type": { "id": { "type": "choice", "description": "Selected crop item", "primary key": True }, "system fraction": { "description": "Fraction of bedspace allocated to crop", "type": "decimal" }, "sale unit id": { "type": "choice", "description": "Selected sale unit for crop item" }, "price per unit": { "description": "Sale price for crop per selected unit", "type": "decimal" } } }, "organic production": { "description": "Whether the system will use organic production", "type": "bool", "default": False }, "water cost": { "description": "Water cost ($ / gallon)", "default": 0.002, "type": "decimal" }, "labor wages": { "description": "Labor wages ($ / h)", "default": 15.73, "type": "decimal" }, "rent cost": { "description": "Rent cost per area ($ / sqft month)", "default": 12, "type": "decimal" }, "tax rate": { "description": "Tax rate (%)", "default": 0.261, "type": "decimal" }, "financing option": { "type": "choice", "description": "How capital expenses are financed", "default": 1 }, "interest rate": { "description": "Loan interest rate (% / y)", "default": 0.08, "type": "decimal" }, "repayment time": { "description": "Repayment period for loan (y)", "default": 7, "type": "decimal" } } @staticmethod @hashable_cache(ttl_cache()) def input_values(input_name): if input_name == "land status": return Soil_Input_Land_Status.input_values("land status") if input_name == "grower experience": return Soil_Wastage.input_values("grower experience") if input_name == "crops.id": return fetch_all("SELECT id, crop_type FROM crops ORDER BY id") if input_name == "crops.sale unit id": return fetch_all( "SELECT id, description FROM sale_units ORDER BY id") if input_name == "financing option": return [{'id': 1, 'description': 'Debt'}, { 'id': 2, 'description': 'Equity'}, {'id': 3, 'description': 'Self-funded'}] raise ValueError("Unexpected input: " + str(input_name)) @staticmethod def output_type(): return { "capex breakout": { "type": "list", "description": "Capex breakout", "element type": { "category": { "type": "text", "description": "Category" }, "total price": { "description": "Total price ($)", "digits": 2, "type": "decimal" }, "fraction": { "description": "% of total price (%)", "digits": 4, "type": "decimal" } } }, "cogs & opex breakout": { "type": "list", "description": "COGS & Opex breakout", "element type": { "category": { "type": "text", "description": "Category" }, "total price": { "description": "Total price ($)", "digits": 2, "type": "decimal" }, "fraction": { "description": "% of total price (%)", "digits": 4, "type": "decimal" } } }, "cogs breakout": { "type": "list", "description": "COGS breakout", "element type": { "category": { "type": "text", "description": "Category" }, "total price": { "description": "Total price ($)", "digits": 2, "type": "decimal" } } }, "opex breakout": { "type": "list", "description": "Opex breakout", "element type": { "category": { "type": "text", "description": "Category" }, "total price": { "description": "Total price ($)", "digits": 2, "type": "decimal" } } }, "max total yield": { "description": "Total Yield without Wastage (lbs)", "digits": 0, "type": "decimal" }, "bedspace": { "description": "Total Bedspace needed (sqft)", "digits": 0, "type": "decimal" }, "annual summary": { "type": "list", "description": "Annual summary", "element type": { "year": { "type": "integer", "description": "Year" }, "wastage": { "description": "Wastage", "digits": 4, "type": "decimal" }, "total yield": { "description": "Total Yield (lbs)", "digits": 0, "type": "decimal" }, "crop yield": { "description": "Yield per each crop", "type": "list", "element type": { "crop type": { "type": "string", "description": "crop name" }, "yield" : { "digits": 0, "type": "decimal" } } }, "waste-adjusted revenue": { "description": "Waste-adjusted Revenue ($)", "digits": 0, "type": "decimal" }, "cogs": { "description": "COGS ($)", "digits": 0, "type": "decimal" }, "opex": { "description": "Opex ($)", "digits": 0, "type": "decimal" }, "ebitda": { "description": "EBITDA ($)", "digits": 0, "type": "decimal" }, "depreciation & amortization": { "description": "Depreciation & Amortization ($)", "digits": 0, "type": "decimal" }, "interest payment": { "description": "Interest Payment ($)", "digits": 0, "type": "decimal" }, "taxes": { "description": "Taxes ($)", "digits": 0, "type": "decimal" }, "net profit": { "description": "Net Profit ($)", "digits": 0, "type": "decimal" } } }, "cash flow": { "type": "list", "description": "Cash flow", "element type": { "year": { "type": "integer", "description": "Year" }, "net profit": { "description": "Net Profit ($)", "digits": 2, "type": "decimal" }, "d&a": { "description": "Plus: D&A ($)", "digits": 2, "type": "decimal" }, "net changes in working capital": { "description": "Plus: Net Changes in Working Capital ($)", "digits": 2, "type": "decimal" }, "free cash flow": { "description": "Free Cash Flow ($)", "digits": 2, "type": "decimal" }, "remaining balance": { "description": "Remaining balance ($)", "digits": 2, "type": "decimal" } } }, "pv of cash flows": { "description": "PV of Cash Flows ($)", "digits": 2, "type": "decimal" }, "payback period": { "description": "Payback period (y)", "digits": 2, "type": "decimal" }, "financial summary": { "type": "list", "description": "Financial summary", "element type": { "capex": { "digits": 0, "description": "Capex", "type": "decimal" }, "opex": { "digits": 0, "description": "Opex", "type": "decimal" }, "cogs": { "digits": 0, "description": "COGS", "type": "decimal" }, "opex + cogs": { "digits": 0, "description": "Opex + COGS", "type": "decimal" }, "max annual revenue": { "digits": 0, "description": "Max. Annual Revenue", "type": "decimal" }, "payback period": { "digits": 2, "description": "Payback Period (in years)", "type": "decimal" } } }, "operating summary": { "type": "list", "description": "10-year operating summary", "element type": { "year": { "type": "integer", "description": "Year" }, "wastage": { "digits": 4, "description": "Wastage", "type": "decimal" }, "waste-adjusted revenue": { "digits": 0, "description": "Wastage-adjusted Revenue", "type": "decimal" }, "ebitda": { "digits": 0, "description": "EBITDA", "type": "decimal" }, "ebitda margin": { "digits": 4, "description": "EBITDA Margin", "type": "decimal" }, "net profit": { "digits": 0, "description": "Net Profit", "type": "decimal" }, "net margin": { "digits": 4, "description": "Net Margin", "type": "decimal" } } }, "number of people employed": { "description": "Estimated number of people employed", "type": "text" }, "potential population fed": { "description": "Estimated number of people fed", "digits": 0, "type": "decimal" } } @staticmethod @hashable_cache(ttl_cache()) def compute(args, quantize_output=False): result = dict() inputs = parse_inputs(Soil_Deliverables.input_type(), args) output_type = Soil_Deliverables.output_type() preload_result = preload_outputs(output_type, inputs) for key in preload_result: result[key] = preload_result[key] def print_debug(model_name): print(model_name, result[model_name]) # First, translate inputs into land status args_soil_input_land_status = dict() args_soil_input_land_status["land status"] = inputs["land status"] result["soil_input_land_status"] = Soil_Input_Land_Status.compute( args_soil_input_land_status) print_debug('soil_input_land_status') # Compute sizes for models args_soil_sizing_area = dict() args_soil_sizing_area["area"] = inputs["site area"] result["soil_sizing_area"] = Soil_Sizing_Area.compute( args_soil_sizing_area) print_debug('soil_sizing_area') # Compute crop characteristics args_soil_crop_characteristics = dict() args_soil_crop_characteristics["crops"] = inputs["crops"] result["soil_crop_characteristics"] = Soil_Crop_Characteristics.compute( args_soil_crop_characteristics) print_debug('soil_crop_characteristics') # Compute crop args_soil_crop = dict() args_soil_crop["latitude"] = inputs["latitude"] args_soil_crop["longitude"] = inputs["longitude"] args_soil_crop["bedspace"] = result["soil_sizing_area"]["main bedspace"] args_soil_crop["crops"] = inputs["crops"] result["soil_crop"] = Soil_Crop.compute(args_soil_crop) print_debug('soil_crop') set_if_unset( result, "max total yield", result["soil_crop"]["total yield"]) set_if_unset( result, "bedspace", result["soil_sizing_area"]["main bedspace"]) # Compute wastage projection based on inputs and selected crops args_soil_wastage = dict() args_soil_wastage["grower experience"] = inputs["grower experience"] args_soil_wastage["organic production"] = inputs["organic production"] args_soil_wastage["crop base difficulty"] = result["soil_crop_characteristics"]["combined difficulty factor"] args_soil_wastage["number of crops"] = len(inputs["crops"]) result["soil_wastage"] = Soil_Wastage.compute(args_soil_wastage) print_debug('soil_wastage') # Compute capital expenditures args_soil_capex_overview = dict() args_soil_capex_overview["land area"] = inputs["site area"] args_soil_capex_overview["nursery trays"] = math.ceil( result["soil_crop"]["total plant sites"] / 128) args_soil_capex_overview["real estate cost"] = inputs["site area"] * \ inputs["land cost"] if result["soil_input_land_status"]["is buy"] else 0 args_soil_capex_overview["seeding equipment cost"] = 1500 if result["soil_crop"]["total plant sites"] > 4000 else 0 result["soil_capex_overview"] = Soil_Capex_Overview.compute( args_soil_capex_overview) print_debug('soil_capex_overview') def get_capex_cost(description): for item in result['soil_capex_overview']['line items']: if item['description'].startswith(description): return item['cost'] return None # Compute operating expenses args_soil_opex_overview = dict() args_soil_opex_overview["bedspace"] = result["soil_sizing_area"]["main bedspace"] args_soil_opex_overview["rent area"] = inputs["site area"] if result["soil_input_land_status"]["is rent"] else 0 args_soil_opex_overview["annual number of plant sites"] = result["soil_crop"]["total plant sites"] args_soil_opex_overview["water used"] = result["soil_crop"]["total water use"] args_soil_opex_overview["cold storage capex"] = get_capex_cost( 'Cold Storage') args_soil_opex_overview["tools capex"] = get_capex_cost('Tools') args_soil_opex_overview["transportation capex"] = get_capex_cost( 'Transportation') args_soil_opex_overview["harvest capex"] = get_capex_cost('Harvesting') args_soil_opex_overview["water cost"] = inputs["water cost"] args_soil_opex_overview["labor wages"] = inputs["labor wages"] args_soil_opex_overview["rent cost"] = 12 * inputs["rent cost"] args_soil_opex_overview["owner is headgrower"] = inputs["owner is headgrower"] args_soil_opex_overview["headgrower salary"] = inputs["headGrowerSalary"] args_soil_opex_overview["packaging type"] = 1 args_soil_opex_overview["revenue"] = result["soil_crop"]["total revenue"] * ( 1 - result["soil_wastage"]["initial wastage"]) args_soil_opex_overview["depreciation"] = result["soil_capex_overview"]["total depreciation"] result["soil_opex_overview"] = Soil_Opex_Overview.compute( args_soil_opex_overview) print_debug('soil_opex_overview') # Compute repayment schedule for debt # Financing amount is 0 if funding option is not debt args_financials_interest = dict() args_financials_interest["amount"] = result["soil_capex_overview"]["total cost"] if inputs["financing option"] == 1 else 0 args_financials_interest["interest rate"] = inputs["interest rate"] args_financials_interest["repayment time"] = inputs["repayment time"] args_financials_interest["payments per year"] = 4 result["financials_interest"] = Financials_Interest.compute( args_financials_interest) print_debug('financials_interest') # Combine outputs into financial model args_financials_main = dict() args_financials_main["capex line items"] = result["soil_capex_overview"]["line items"] args_financials_main["opex line items"] = result["soil_opex_overview"]["line items"] args_financials_main["wastage schedule"] = result["soil_wastage"]["wastage schedule"] args_financials_main["crops"] = result["soil_crop"]["crops"] args_financials_main["base yield"] = result["soil_crop"]["total yield"] args_financials_main["base revenue"] = result["soil_crop"]["total revenue"] args_financials_main["depreciation"] = result["soil_capex_overview"]["total depreciation"] args_financials_main["interest repayment schedule"] = result["financials_interest"]["repayment schedule"] args_financials_main["tax rate"] = inputs["tax rate"] result["financials_main"] = Financials_Main.compute( args_financials_main) print_debug('financials_main') # Output number of employees args_financials_employees = dict() args_financials_employees["total staff"] = result["soil_opex_overview"]["total staff"] result["financials_employees"] = Financials_Employees.compute( args_financials_employees) print_debug('financials_employees') # Output population fed args_financials_population_fed = dict() args_financials_population_fed["total yield"] = result["soil_crop"]["total yield"] result["financials_population_fed"] = Financials_Population_Fed.compute( args_financials_population_fed) print_debug('financials_population_fed') # Output financial model results set_if_unset( result, "number of people employed", result["financials_employees"]["number of people employed"]) set_if_unset( result, "potential population fed", result["financials_population_fed"]["potential population fed"]) set_if_unset( result, "capex breakout", result["financials_main"]["capex breakout"]) set_if_unset( result, "cogs & opex breakout", result["financials_main"]["cogs & opex breakout"]) set_if_unset( result, "cogs breakout", result["financials_main"]["cogs breakout"]) set_if_unset( result, "opex breakout", result["financials_main"]["opex breakout"]) set_if_unset( result, "annual summary", result["financials_main"]["annual summary"]) set_if_unset( result, "cash flow", result["financials_main"]["cash flow"]) set_if_unset( result, "pv of cash flows", result["financials_main"]["pv of cash flows"]) set_if_unset( result, "payback period", result["financials_main"]["payback period"]) set_if_unset( result, "financial summary", result["financials_main"]["financial summary"]) set_if_unset( result, "operating summary", result["financials_main"]["operating summary"]) if quantize_output: quantize_outputs(output_type, result) return result

[ "toptech20190609@gmail.com" ]

toptech20190609@gmail.com

f4f14f8d9e87b48ae2a849923822030a6333cbdc

9e4e829db6d4197764c9e71f3ca65dacc5792c8f

/sudoku.py

648081e7c55d3995a15842f3214fda4d0cf26907

[]

no_license

en-chang/sudoku

c48d6f66d04bf0426d84d41c2ab7967d76764c31

1e0e46421a2cfb7f9e289aed5e8f72e6e6687d46

refs/heads/master

2022-10-23T09:11:39.163457

2020-06-15T19:05:00

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0

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py

import requests import json import time import pprint # Delay to make display slower def delay(): time.sleep(0.475) # Ask difficulty def askDiff(): while True: diff = input('What difficulty level would you like?\nEasy, Medium, or Hard?\n').lower() if diff not in ('easy', 'medium', 'hard'): print('Sorry, please enter a valid difficulty level.') else: break if diff == 'easy': return 1 elif diff == 'medium': return 2 elif diff == 'hard': return 3 # Calls a sudoku API to generate a sudoku board based on a difficulty level # Source: "http://www.cs.utep.edu/cheon/ws/sudoku/" def createBoard(difficulty): response = requests.get(f"http://www.cs.utep.edu/cheon/ws/sudoku/new/?size=9&level={difficulty}") data = response.json() data = data['squares'] board = [[0] * 9 for row in range(9)] for point in range(len(data)): col = data[point]['x'] row = data[point]['y'] val = data[point]['value'] board[row][col] = val return board # Solves sudoku boards using backtracking def sudokuSolver(board, row, col): if sudokuComplete(board) is True: global completeBoard completeBoard = board return True if board[row][col] == 0: # Find nums that are potential guesses in a row usedNums = [num for num in board[row] if num in range(1, 10)] possibNums = [num for num in range(1, 10) if num not in usedNums] for guess in possibNums: board[row][col] = guess # Print statements to show the process ''' print('row, col', (row, col)) print('guess', guess) printBoard(board) print() ''' if sudokuChecker(board) is True: if rowComplete(board[row]) is True: if sudokuSolver(board, row + 1, 0) is True: return True elif sudokuSolver(board, row, col + 1) is True: return True board[row][col] = 0 continue # Backtrack if all guesses are wrong if guess == possibNums[-1]: board[row][col] = 0 return False # Backtracking multiple steps if board[row][col] == 0: return False # Continue to next col if space is filled if sudokuSolver(board, row, col + 1) is True: return True # Checks if the board is valid def sudokuChecker(board): if rowChecker(board) is False: return False if colChecker(board) is False: return False if subSquareChecker(board) is False: return False return True # Helper function to sudokuChecker and sudokuComplete def rowChecker(board): # Check rows for duplicates except 0 (empty spaces) for i in range(len(board)): # Remove 0s row = [x for x in board[i] if x != 0] if dupChecker(row) is False: return False # Helper function to sudokuChecker def colChecker(board): # Check columns for duplicates except 0 for i in range(len(board)): col = [] for j in range(len(board[i])): col.append(board[j][i]) # Remove 0s col = [x for x in col if x != 0] if dupChecker(col) is False: return False # Helper function to sudokuChecker def subSquareChecker(board): # Loop within the first, fourth, and seventh row 3 times # Because this is the start of the subSquares for i in range(0, len(board), 3): subSquare = [] # Check two rows ahead to form subSquare # Because this finishes the subSquares # After each subSquare check with dupChecker for j in range(0, len(board[i]), 3): subSquare.extend(board[i][j : j + 3]) subSquare.extend(board[i + 1][j : j + 3]) subSquare.extend(board[i + 2][j : j + 3]) # Remove 0s subSquare = [x for x in subSquare if x != 0] if dupChecker(subSquare) is False: return False subSquare.clear() return True # Helper function to row/col/subSquareChecker # Checks for duplicates in a row, col, or subSquare def dupChecker(rowOrCol): if len(rowOrCol) != len(set(rowOrCol)): return False ''' # For testing purposes else: print(rowOrCol) print('correct row, col, or subSquare') ''' # Helper function to sudokuSolver def sudokuComplete(board): for i in range(len(board)): if rowComplete(board[i]) is False: return False return True # Heper function to sudokuComplete def rowComplete(row): if 0 in row: return False return True def printBoard(board): boardPrinter = pprint.PrettyPrinter() boardPrinter.pprint(board) # Sample board for testing ''' testBoard = [ [4, 0, 0, 0, 0, 0, 1, 0, 7], [2, 1, 0, 5, 0, 7, 0, 9, 0], [7, 0, 3, 0, 0, 0, 2, 0, 4], [0, 0, 0, 3, 1, 0, 0, 0, 9], [6, 0, 0, 0, 5, 0, 0, 0, 0], [5, 3, 1, 0, 0, 9, 0, 0, 0], [0, 7, 0, 1, 0, 0, 0, 2, 8], [0, 0, 0, 0, 0, 4, 0, 6, 3], [0, 6, 0, 0, 0, 0, 0, 0, 0] ] ''' def main(): difficulty = askDiff() board = createBoard(difficulty) if difficulty == 1: level = 'Easy' elif difficulty == 2: level = 'Medium' elif difficulty == 3: level = 'Hard' print() print(f'Board ({level}):') printBoard(board) print() global completeBoard sudokuSolver(board, 0, 0) delay() print('Solution:') printBoard(completeBoard) if __name__ == "__main__": main()

[ "enchangcsprof@gmail.com" ]

enchangcsprof@gmail.com

fb9400b52436488379a3045805c0f588682f0306

878c3b571e0f2ccf9688a3d5aefa443312c706fe

/bd_api/bd_api/users/views.py

09a7d1d49a2f69d8c8a959eaecb0a5b1f728d1f0

[ "MIT" ]

permissive

jorimyk/body_dimensions

785870a092856979d6059991a43462cb6571d81e

6787570661d6dd032ade5d0c737a7d07ed3ec14a

refs/heads/master

2021-04-30T16:26:29.665121

2019-02-20T19:43:38

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from flask import request, jsonify, make_response from bd_api import app, db, limiter, auth, CORS from . models import User, Role from bd_api.users.measurements.models import Measurement from bd_api import Config from bd_api.utils import CommonUtils, UserUtils from bd_api.auth import Password, Token # Creeate admin account if no users in database if not User.query.all(): admin = User(username='admin', email=Config.admin_email , password=Password.hashPassword(Config.admin_password), role=Role.ADMIN, public=False) db.session.add(admin) db.session.commit() @app.route('/login', methods=['GET', 'POST']) def login(): if request.authorization: auth = request.authorization elif request.form['username'] and request.form['password']: auth = {'username': request.form['username'], 'password': request.form['password']} else: return jsonify(error='username/password required'), 400 q = User.query.filter_by(username=auth.get('username')).first() if q and Password.verifyPassword(auth.get('username'), auth.get('password')): response = jsonify({'token': Token.generateToken(q.id, q.username, q.role, Config.expiration).decode('ascii')}) response.headers['Content-Location'] = '/users/%s' % str(q.id) response.headers['Access-Control-Expose-Headers'] = 'Content-Location' return response else: return jsonify(error='Invalid username/password'), 401 @app.route('/users', methods = ['POST', 'GET', 'PUT', 'DELETE']) # /users def users(): headers = request.headers auth = request.authorization if not auth: user = (None, Role.USER, None) elif 'error' in Token.verifyToken(auth.get('username')): return jsonify(Token.verifyToken(auth.get('username'))), 401 else: user = Token.verifyToken(auth.get('username')) # Add a new user if request.method == 'POST': d = request.get_json(silent=True) return addNewUser(headers, d) # Read users elif request.method == 'GET': return getAllUsers(user) # Delete all users elif request.method == 'DELETE': return deleteUsers(user) # Return 405 if method not POST, GET or DELETE else: return jsonify(error='HTTP method %s not allowed' % request.method), 405 @app.route('/users/<int:userId>', methods = ['GET', 'PUT', 'DELETE']) # /users/<user> def user(userId): headers = request.headers auth = request.authorization if not auth: user = (None, Role.USER, None) elif 'error' in Token.verifyToken(auth.get('username')): return jsonify(Token.verifyToken(auth.get('username'))), 401 else: user = Token.verifyToken(auth.get('username')) # Read user if request.method == 'GET': return getUser(userId, user) # Update user if owner or admin elif request.method == 'PUT': d = request.get_json(silent=True) return updateUser(headers, userId, user, d) # Delete user and all measurements for user if owner or admin elif request.method == 'DELETE': return deleteUser(userId, user) # Return 405 if method not GET, PUT or DELETE else: return jsonify(error='HTTP method %s not allowed' % request.method), 405 def addNewUser(headers, d): """Add new user to database if valid username/password and if optional values are valid in d""" if not 'Content-Type' in headers or not 'application/json' in headers.get('Content-Type'): return jsonify(error='Content Type must be application/json'), 400 elif not d: return jsonify(error='no JSON in request'), 400 elif not 'username' in d or not 'password' in d or not 'email' in d: return jsonify(error='username, password and email required'), 400 elif UserUtils.validate_user_values(d): return jsonify(UserUtils.validate_user_values(d)), 400 else: q = User( \ firstName = d.get('firstName'), \ lastName = d.get('lastName'), \ email = d.get('email'), \ gender = d.get('gender'), \ dateOfBirth = CommonUtils.convertFromISODate(d.get('dateOfBirth')), \ username = d.get('username'), \ password = Password.hashPassword(d.get('password')), \ public = d.get('public')) db.session.add(q) db.session.commit() user = q.serialize user['token'] = Token.generateToken(user['id'], d.get('username'), 'user', Config.expiration).decode('ascii') response = jsonify(user) response.status_code = 201 response.headers['Content-Location'] = '/users/' + str(user['id']) response.headers['Access-Control-Expose-Headers'] = 'Content-Location' return response def getAllUsers(user): """Return all users from database""" if user[1] == Role.ADMIN: q = User.query.all() else: q = User.query.filter((User.id == user[0]) | (User.public == True)).all() if q: q = [i.serialize for i in q] for index in q: index['measurements'] = CommonUtils.countNumberOfRows(index['id']) return jsonify(q) else: return ('', 204) def deleteUsers(user): """Delete all measurements and users with role user""" if user[1] == Role.ADMIN: measurements_deleted = Measurement.query.delete() users_deleted = User.query.filter_by(role=Role.USER).delete() db.session.commit() return jsonify(usersDeleted=users_deleted, measurementsDeleted=measurements_deleted) else: return jsonify(error='Unauthorized'), 403 def getUser(userId, user): """Query user based on userId""" q = User.query.filter_by(id = userId).first() if not q: return jsonify(error='User not found', userId=userId), 404 elif not user[0] and not q.public: return jsonify(error='Authentication required'), 401 elif user[0] != userId and user[1] != Role.ADMIN and not q.public: return jsonify(error='Unauthorized'), 403 else: q = q.serialize q['measurements'] = CommonUtils.countNumberOfRows(userId) return jsonify(q) def updateUser(headers, userId, user, d): """Update user details if valid keys/values in d""" if user[0] != userId and user[1] != Role.ADMIN: return jsonify(error='Unauthorized'), 403 else: q = User.query.filter_by(id = userId).first() if not q: return jsonify(error='User not found', userId=userId), 404 if not 'Content-Type' in headers or not 'application/json' in headers.get('Content-Type'): return jsonify(error='Content Type must be application/json'), 400 if not d: return jsonify(error='no JSON in request'), 400 if not any(key in d for key in User.user_keys): return jsonify(error='No valid keys'), 400 if UserUtils.validate_user_values(d): return jsonify(UserUtils.validate_user_values(d)), 400 if d.get('firstName'): q.firstName = d.get('firstName') if d.get('lastName'): q.lastName = d.get('lastName') if d.get('gender'): q.gender = d.get('gender') if d.get('dateOfBirth'): q.dateOfBirth = CommonUtils.convertFromISODate(d.get('dateOfBirth')) if d.get('username'): q.username = d.get('username') if d.get('password'): q.password = Password.hashPassword(d.get('password')) if d.get('public'): q.public = d.get('public') db.session.add(q) db.session.commit() user = q.serialize return jsonify(user), 200 def deleteUser(userId, user): """Delete user from database based on userId""" if user[0] != userId and user[1] != Role.ADMIN: return jsonify(error='Unauthorized'), 403 else: q = User.query.filter_by(id = userId).first() if not q: return jsonify(error='User not found', userId=userId), 404 else: measurements_deleted = Measurement.query.filter_by(owner_id = userId).delete() db.session.delete(q) db.session.commit() return jsonify(result='user removed', userId=userId, username=user[2], measurementsDeleted=measurements_deleted)

[ "jori.mykkanen@gmail.com" ]

jori.mykkanen@gmail.com

bd5c3dd7bb88057f50d2e513ec9577f5ae4516df

e465ec4e9af2358ed8a63b555b03d24a30a68790

/study_python/day5/scratch.py

d7d052c2111034f226472fc75b1d084dffe5054f

[]

no_license

veritakim/study_python

40930442130d78190977157229bef9e03f6303fe

8c25ec8716fc16223473f53e87d29f102fc80adb

refs/heads/main

2023-02-27T16:40:36.189980

2021-02-05T11:42:56

330,602,296

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py

# file_read 에서 sell.txt를 프린트 했을 때 ''' 1일 : 얼마 2일: 얼마 중간에 엔터가 하나 더 쳐진다. 왜냐하면 print 자체가 엔터의 기능이 있는데 텍스트에도 엔터가 들어가서 두 번의 엔터 기능이 됐다 \n ''' # .strip() : 화이트 스페이스. 글자들 사이 이외의 빈 공백들을 처리 with open('data/sell.txt', 'r', encoding='UTF-8') as f: for line in f: print(line.strip())

[ "kjs3597@gmail.com" ]

kjs3597@gmail.com

13bedc0acf5fbc26a65317a03374a0f4a5d2083f

7f4ba7877def60e9fd9f60794633b3893f36599b

/aleatorio.py

6894515a4d1320e1b6eeefe4bdb1aff9e1cc89d8

[]

no_license

cgonzalesmo/PS_LAB09

c33cc3b43fdf4aa9dfd2ab7ffa2f3f67d15aec93

6843768543ac206cfe99743149af7de34816b4a1

refs/heads/master

2022-11-20T08:35:06.247181

2020-07-19T22:11:26

280,283,084

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2

null

UTF-8

Python

false

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import random as r import os directorio = './files/aleatorio/' if not os.path.exists(directorio): os.makedirs(directorio) contador = 50 letras = 'abcdefghijklmnopqrstuvwxyz123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ' for i in range(contador): tamano = r.randint(1000000,10000000) archivo = open(directorio + 'archivo' + str(i), 'w+') texto = "" for j in range(tamano): texto = texto + r.choice(letras) archivo.write(texto) archivo.close()

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name = 'Contact points' challenge = 'Deploy a new agent, using a different contact point then your first agent' extra_info = """If an adversary deploys all of their agents on a host using the same protocol, say HTTP, then when their agent is detected and shut down, the defenders will likely close access to the C2 over that protocol. Therefore, an adversary will want multiple agents on a host, each using a different protocol to talk to the C2. """ async def verify(services): contacts = set([agent.contact for agent in await services.get('data_svc').locate('agents')]) if len(contacts) > 1: return True return False

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# -*- coding: utf-8 -*- # Generated by Django 1.10.2 on 2016-10-26 02:06 from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('authentication', '0003_auto_20161025_2051'), ] operations = [ migrations.AlterField( model_name='token', name='hint', field=models.CharField(blank=True, help_text="*'s do not accurately reflect length of password", max_length=16), ), ]

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# Generated by Django 3.1 on 2020-09-14 13:29 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('core', '0004_recipe'), ] operations = [ migrations.AddField( model_name='recipe', name='time_minutes', field=models.IntegerField(default=1), preserve_default=False, ), ]

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biansy000/CS410-Drug-Molecular-Toxicity-Prediction

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import numpy as np import os import copy import pandas as pd import torch paths = {'test': "../code/data/test", 'train': "../code/data/train", 'valid': "../code/data/validation"} def read_data(choice='train', pos_weight=7.0, add_valid=False): if choice == 'train': return read_train_data(pos_weight, add_valid) elif choice == 'validation': return read_valid_data(pos_weight, add_valid) else: return read_test_data(pos_weight) def read_train_data(pos_weight=7.0, add_valid=False, to_valid=False): path = paths['train'] rdata = [] names_onehots = np.load(os.path.join(path, 'names_onehots.npy'), allow_pickle=True) df_smiles = pd.read_csv(os.path.join(path, 'names_smiles.txt')) df_labels = pd.read_csv(os.path.join(path, 'names_labels.txt')) names_onehots = dict(names_onehots[()]) names = names_onehots['names'] onehots = names_onehots['onehots'] if not (type(names[0]) == str): # due to some strange error names = [key.decode("utf-8") for key in names] for i, key in enumerate(names): weight = 1.0 assert df_labels.iloc[i, 1] == 0 or df_labels.iloc[i, 1] == 1 if df_labels.iloc[i, 1] > 0.5: weight = pos_weight tmp = {'name': key, 'onehots': onehots[i], 'SMILES': df_smiles.iloc[i, 1], \ 'label': float(df_labels.iloc[i, 1]), 'weight': weight} rdata.append(tmp) if add_valid: # only use 500+ as training data return rdata[500:] elif to_valid: # add 0 ~ 500 data to test set return rdata[:500] return rdata def read_valid_data(pos_weight=7.0, add_valid=False): path = paths['valid'] rdata = [] names_onehots = np.load(os.path.join(path, 'names_onehots.npy'), allow_pickle=True) df_smiles = pd.read_csv(os.path.join(path, 'names_smiles.txt')) df_labels = pd.read_csv(os.path.join(path, 'names_labels.txt')) names_onehots = dict(names_onehots[()]) names = names_onehots['names'] onehots = names_onehots['onehots'] if not (type(names[0]) == str): # due to some strange error names = [key.decode("utf-8") for key in names] for i, key in enumerate(names): weight = 1.0 if df_labels.iloc[i, 1] > 0.5: weight = pos_weight tmp = {'name': key, 'onehots': onehots[i], 'SMILES': df_smiles.iloc[i, 1], \ 'label': float(df_labels.iloc[i, 1]), 'weight': weight} rdata.append(tmp) if add_valid: add_data = read_train_data(pos_weight, to_valid=True) rdata = rdata + add_data return rdata def read_test_data(pos_weight=7.0): path = paths['test'] rdata = [] names_onehots = np.load(os.path.join(path, 'names_onehots.npy'), allow_pickle=True) df_smiles = pd.read_csv(os.path.join(path, 'names_smiles.txt')) names_onehots = dict(names_onehots[()]) names = names_onehots['names'] onehots = names_onehots['onehots'] if not (type(names[0]) == str): # due to some strange error names = [key.decode("utf-8") for key in names] for i, key in enumerate(names): tmp = {'name': key, 'onehots': onehots[i], 'SMILES': df_smiles.iloc[i, 1]} #print(onehots[i].shape) rdata.append(tmp) return rdata def calc_mean(data, dim1=None): summary = [] dim = [1, 1] dim[0] = np.array(data[0]['onehots']).shape[0] if dim1: dim[1] = dim1 else: dim[1] = np.array(data[0]['onehots']).shape[1] for item in data: num = np.array(item['onehots']).sum() summary.append(num) summary = np.array(summary) mean = np.mean(summary) / (dim[0] * dim[1]) var = np.mean(summary**2) - mean**2 var = np.sqrt(var) / (dim[0] * dim[1]) print('mean', mean, 'var', var) # raise SyntaxError return mean, var def sigmoid(x): return 1/(1+np.exp(-x))

[ "biansy000@github.com" ]

biansy000@github.com

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"""Unary operations on graphs""" # Copyright (C) 2004-2018 by # Aric Hagberg <hagberg@lanl.gov> # Dan Schult <dschult@colgate.edu> # Pieter Swart <swart@lanl.gov> # All rights reserved. # BSD license. import networkx as nx from networkx.utils import not_implemented_for __author__ = """\n""".join(['Aric Hagberg <aric.hagberg@gmail.com>', 'Pieter Swart (swart@lanl.gov)', 'Dan Schult(dschult@colgate.edu)']) __all__ = ['complement', 'reverse'] def complement(G): """Return the graph complement of G. Parameters ---------- G : graph A NetworkX graph Returns ------- GC : A new graph. Notes ------ Note that complement() does not create self-loops and also does not produce parallel edges for MultiGraphs. Graph, node, and edge data are not propagated to the new graph. """ R = G.fresh_copy() R.add_nodes_from(G) R.add_edges_from(((n, n2) for n, nbrs in G.adjacency() for n2 in G if n2 not in nbrs if n != n2)) return R def reverse(G, copy=True): """Return the reverse directed graph of G. Parameters ---------- G : directed graph A NetworkX directed graph copy : bool If True, then a new graph is returned. If False, then the graph is reversed in place. Returns ------- H : directed graph The reversed G. """ if not G.is_directed(): raise nx.NetworkXError("Cannot reverse an undirected graph.") else: return G.reverse(copy=copy)

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x = int(input("Enter base number: ")) y = int(input("Enter exponent number: ")) number = 1 for n in range(y): number *= x print(x,"^",y," = ",number,sep="")

[ "noreply@github.com" ]

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from rlbot.agents.base_agent import BOT_CONFIG_AGENT_HEADER from rlbot.agents.executable_with_socket_agent import ExecutableWithSocketAgent from rlbot.parsing.custom_config import ConfigHeader, ConfigObject class Voodoo(ExecutableWithSocketAgent): def get_port(self) -> int: return 19231 def load_config(self, config_header: ConfigHeader): self.executable_path = config_header.getpath('java_executable_path') self.logger.info("Java executable is configured as {}".format(self.executable_path)) @staticmethod def create_agent_configurations(config: ConfigObject): params = config.get_header(BOT_CONFIG_AGENT_HEADER) params.add_value('java_executable_path', str, default=None, description='Relative path to the executable that runs java.')

[ "tarehart@gmail.com" ]

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2023-03-27T15:20:39

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#line problem #exam 2 question 1 #Codey Sivley #OOP Fall 2021 def pointVsLine(p0, p1, p2): #setup x0 = p0[0] x1 = p1[0] x2 = p2[0] y0 = p0[1] y1 = p1[1] y2 = p2[1] #is formula for A and B were incorrect on original problem? #should be lineA = y0-y1, lineB = x1-x0 #answers keep coming out inverse as given. #source: Fundamentals of Computer Graphics #By Steve Marschner, Peter Shirley lineA = y1-y0 lineB = x0-x1 lineC = (x0*y1)-(x1*y0) #calculation return ((lineA*x2)+(lineB*y2)-lineC) testPoint1 = (1,0) testPoint2 = (10,5) testPoint3 = (1,2) print(pointVsLine(testPoint1, testPoint2, testPoint3))

[ "cjsivley@gmail.com" ]

cjsivley@gmail.com

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zhangxu0307/repertory-rest

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# -*- coding: utf-8 -*- # Generated by Django 1.11.1 on 2017-06-09 02:56 from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('repetory_api', '0010_auto_20170609_1044'), ] operations = [ migrations.RemoveField( model_name='material', name='materailYear', ), migrations.RemoveField( model_name='material', name='materialBand', ), migrations.RemoveField( model_name='material', name='materialMark', ), migrations.RemoveField( model_name='material', name='materialOriginal', ), migrations.RemoveField( model_name='material', name='materialPostion', ), migrations.RemoveField( model_name='material', name='materialState', ), migrations.RemoveField( model_name='material', name='materialUnit', ), migrations.AddField( model_name='materialinput', name='materailYear', field=models.DateTimeField(blank=True, null=True, verbose_name='\u6750\u6599\u5e74\u4efd'), ), migrations.AddField( model_name='materialinput', name='materialBand', field=models.CharField(blank=True, max_length=100, null=True, verbose_name='\u6750\u6599\u54c1\u724c'), ), migrations.AddField( model_name='materialinput', name='materialMark', field=models.CharField(blank=True, max_length=100, null=True, verbose_name='\u6750\u6599\u578b\u53f7'), ), migrations.AddField( model_name='materialinput', name='materialOriginal', field=models.CharField(blank=True, max_length=100, null=True, verbose_name='\u6750\u6599\u539f\u4ea7\u5730'), ), migrations.AddField( model_name='materialinput', name='materialPostion', field=models.CharField(blank=True, max_length=100, null=True, verbose_name='\u6750\u6599\u4f4d\u7f6e'), ), migrations.AddField( model_name='materialinput', name='materialState', field=models.CharField(blank=True, max_length=100, null=True, verbose_name='\u6750\u6599\u72b6\u6001'), ), migrations.AddField( model_name='materialinput', name='materialUnit', field=models.DecimalField(decimal_places=4, default=0, max_digits=8, verbose_name='\u6750\u6599\u5355\u4f4d\u539f\u503c'), ), ]

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zhangxu0307@163.com

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/ps/prop/migrations/0020_auto_20161116_2255.py

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[]

no_license

thementat/ps

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2021-01-12T04:40:33.026049

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# -*- coding: utf-8 -*- # Generated by Django 1.10.2 on 2016-11-16 22:55 from __future__ import unicode_literals from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('prop', '0019_auto_20161116_2138'), ] operations = [ migrations.RemoveField( model_name='src', name='muni', ), migrations.RemoveField( model_name='src_imp', name='imp', ), migrations.RemoveField( model_name='src_imp', name='src', ), migrations.AddField( model_name='imp_parcel', name='parcel', field=models.ForeignKey(null=True, on_delete=django.db.models.deletion.CASCADE, to='prop.Parcel'), ), migrations.AddField( model_name='imp_tie', name='lot', field=models.ForeignKey(null=True, on_delete=django.db.models.deletion.CASCADE, to='prop.Lot'), ), migrations.AddField( model_name='imp_tie', name='parcel', field=models.ForeignKey(null=True, on_delete=django.db.models.deletion.CASCADE, to='prop.Parcel'), ), migrations.AlterField( model_name='imp_address', name='parcel', field=models.ForeignKey(null=True, on_delete=django.db.models.deletion.CASCADE, to='prop.Parcel'), ), migrations.AlterField( model_name='imp_property', name='parcel', field=models.ForeignKey(null=True, on_delete=django.db.models.deletion.CASCADE, to='prop.Parcel'), ), migrations.AlterField( model_name='imp_value', name='property', field=models.ForeignKey(null=True, on_delete=django.db.models.deletion.CASCADE, to='prop.Property'), ), migrations.DeleteModel( name='Src', ), migrations.DeleteModel( name='Src_Imp', ), ]

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/startsetup.py

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[]

no_license

cloudedrhyme/HowdyHack21

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2023-07-28T01:44:02.342049

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import pygame from pygame.locals import * import sys; #test window size displaysurface = pygame.display.set_mode((300, 300)) image = pygame.Surface([640,480], pygame.SRCALPHA, 32) image = image.convert_alpha() mySurface = pygame.Surface((50, 50)) #mySurface.fill((0,255,0)) mySurface2 = pygame.Surface((100, 50)) mySurface2.fill((0,255,0)) player = pygame.image.load("resources/images/dude.png") while True: for event in pygame.event.get(): if event.type == QUIT: pygame.quit() sys.exit() displaysurface.blit(mySurface, (50,50)) displaysurface.blit(mySurface2, (50,150)) pygame.display.update()

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import threading import webbrowser import BaseHTTPServer import SimpleHTTPServer import serial import time ser = serial.Serial(11) # serial where to write FILE = 'erts_client.html' # url to accept requests PORT = 9000 # port number for the server class RequestHandler(SimpleHTTPServer.SimpleHTTPRequestHandler): ''' Handles HTTP web requests and inherits "SimpleHTTPRequestHandler" ''' postdata = dict() def do_POST(self): ''' Handles POST request ''' length = int(self.headers.getheader('content-length')) data_string = self.rfile.read(length) # read post data as URL encoded string for datapoint in data_string.split('&'): # this loop splits stringified post data and stores has key-value pairs datapoint = datapoint.split('=') self.postdata[datapoint[0]] = datapoint[1] print self.postdata # print on server terminal for debugging purposes try: # now take action according to inputs and get output result = process_post_data(self.postdata) except: result = 'Error' self.wfile.write(result) # display output def sanitize_and_send(threshold1,threshold2,temp_constant): # check if inputs are in desired format flag = 1 # flag will be set to 0 if something is wrong result = "" print threshold1,threshold2,temp_constant if(threshold1 > 50 or threshold1<10): result += "Threshold Temperature 1 should be between 10 and 50\n" flag = 0 if(threshold2>50 or threshold2<10): result += "Threshold Temperature 2 should be between 10 and 50\n" flag = 0 if(threshold2<threshold1): result += "Threshold Temperature 2 should be greater than Threshold Temperature 1\n" flag = 0 if(temp_constant<1 or temp_constant>9): result += "Temperature Buffer should be between 1 and 9\n" flag = 0 if (flag): # if flag == 1, then aal iz well # write data to serial (this serial communicates with our bot) ser.write(str(threshold1)) ser.write(str(threshold2)) ser.write(str(temp_constant)) result += "Values sent successfully\n" return result def process_post_data(postdata): # processes the inputs print postdata # for debugging result = "" try: t1 = postdata['threshold1'] t2 = postdata['threshold2'] tb = postdata['tbuff'] # convert string to int t1 = int(t1) t2 = int(t2) tb = int(tb) # sanitize input and send result = sanitize_and_send(t1,t2,tb) except Exception as e: result = e return result def open_browser(): # Start a browser after waiting for half a second. def _open_browser(): webbrowser.open('http://localhost:%s/%s' % (PORT, FILE)) thread = threading.Timer(0.5, _open_browser) thread.start() def start_server(): # Start the server. server_address = ("", PORT) server = BaseHTTPServer.HTTPServer(server_address, RequestHandler) server.serve_forever() if __name__ == "__main__": open_browser() start_server()

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eyantra.erts@gmail.com

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/flightservices/flightapp/views.py

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2023-02-07T23:41:42.425327

2020-12-30T05:34:52

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from django.shortcuts import render from .models import Flight, Passenger, Reservation from .serializers import FlightSerializer, PassengerSerializer, ReservationSerializer from rest_framework import viewsets from rest_framework.response import Response from rest_framework import status from rest_framework.decorators import api_view from rest_framework.permissions import IsAuthenticated # Create your views here. @api_view(['POST']) def find_flights(request): flights = Flight.objects.filter(departurecity=request.data['departurecity'],arrivalcity=request.data['arrivalcity'],dateofdeparture=request.data['dateofdeparture']) serializer = FlightSerializer(flights,many=True) return Response(serializer.data) @api_view(['POST']) def save_reservation(request): flight = Flight.objects.get(id=request.data['flightId']) passenger = Passenger() passenger.firstname = request.data['firstname'] passenger.middlename = request.data['middlename'] passenger.lastname = request.data['lastname'] passenger.email = request.data['email'] passenger.phone = request.data['phone'] passenger.save() reservation = Reservation() reservation.flight = flight reservation.passenger = passenger reservation.save() return Response(status=status.HTTP_201_CREATED) class FlightViewSet(viewsets.ModelViewSet): queryset = Flight.objects.all() serializer_class = FlightSerializer permission_classes = [IsAuthenticated,] class PassengerViewSet(viewsets.ModelViewSet): queryset = Passenger.objects.all() serializer_class = PassengerSerializer class ReservationViewSet(viewsets.ModelViewSet): queryset = Reservation.objects.all() serializer_class = ReservationSerializer

[ "jinkiller69@gmail.com" ]

jinkiller69@gmail.com

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/benchmark/startPyquil3029.py

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# qubit number=4 # total number=41 import pyquil from pyquil.api import local_forest_runtime, QVMConnection from pyquil import Program, get_qc from pyquil.gates import * import numpy as np conn = QVMConnection() def make_circuit()-> Program: prog = Program() # circuit begin prog += H(3) # number=19 prog += CZ(0,3) # number=20 prog += H(3) # number=21 prog += CNOT(0,3) # number=23 prog += X(3) # number=24 prog += CNOT(0,3) # number=25 prog += CNOT(0,3) # number=17 prog += RX(-0.48380526865282825,3) # number=26 prog += H(1) # number=2 prog += Y(3) # number=18 prog += H(2) # number=3 prog += H(3) # number=4 prog += Y(3) # number=12 prog += H(0) # number=5 prog += H(1) # number=6 prog += H(2) # number=7 prog += H(1) # number=34 prog += CZ(0,1) # number=35 prog += H(1) # number=36 prog += CNOT(0,1) # number=31 prog += CNOT(0,1) # number=38 prog += X(1) # number=39 prog += CNOT(0,1) # number=40 prog += CNOT(0,1) # number=33 prog += CNOT(0,1) # number=30 prog += H(3) # number=8 prog += H(3) # number=37 prog += H(0) # number=9 prog += Y(2) # number=10 prog += X(2) # number=22 prog += Y(2) # number=11 prog += X(0) # number=13 prog += X(0) # number=14 # circuit end return prog def summrise_results(bitstrings) -> dict: d = {} for l in bitstrings: if d.get(l) is None: d[l] = 1 else: d[l] = d[l] + 1 return d if __name__ == '__main__': prog = make_circuit() qvm = get_qc('4q-qvm') results = qvm.run_and_measure(prog,1024) bitstrings = np.vstack([results[i] for i in qvm.qubits()]).T bitstrings = [''.join(map(str, l)) for l in bitstrings] writefile = open("../data/startPyquil3029.csv","w") print(summrise_results(bitstrings),file=writefile) writefile.close()

[ "wangjiyuan123@yeah.net" ]

wangjiyuan123@yeah.net

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/Python/Preprocessing.py

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eugeneALU/Text-Classification

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2020-12-03T11:42:21.764190

2020-01-02T03:47:47

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# -*- coding: utf-8 -*- """ Created on Sun Oct 20 09:43:39 2019 @author: eugene """ import numpy as np import pandas as pd import re from nltk.tokenize import word_tokenize from nltk.corpus import stopwords from nltk.stem.snowball import SnowballStemmer #function to clean the word of any punctuation or special characters def cleanPunc(sentence): #remove word in () cleaned = re.sub(r'$[A-Z|a-z]+$',r'',sentence) #preserve some important punctuation and add a space between them and words cleaned = re.sub(r"([.!?])", r" \1", cleaned) #remove other punctuation cleaned = re.sub(r'[\'|"|#|:|;|,|%|<|>|$|$|\^|\||/|\[|\]|&|*|+|=|@|`|~]',r'',cleaned) #remove space \n in the end of the sentences cleaned = cleaned.strip() #remove numbers and words right follow numbers like XXcm(or XX-cm, XX-) but XX cm won't be remove cleaned = re.sub(r'\d+\-\w*|\d+\w+|\d+',r'',cleaned) #remove - in -XXX or XXX- or -- but no XXX-XXX cleaned = re.sub(r'(?<=\w)-(?!\w)|(?<!\w)-(?=\w)|--|(?<!\w)-(?!\w)',r'',cleaned) #remove space and - in the start or end of the sentences again cleaned = cleaned.strip(' -') #incase there are two space cleaned = cleaned.replace(' ',' ') return cleaned def cleanPunc2(sentence): #remove word in () cleaned = re.sub(r'$[A-Z|a-z|0-9]+$',r'',sentence) #preserve some important punctuation and add a space between them and words cleaned = re.sub(r"([.!?])", r" \1 ", cleaned) #remove other punctuation cleaned = re.sub(r'[^a-zA-Z0-9?.!]+',r' ',cleaned) #restore special term cleaned = re.sub(r'e \. g \.', "e.g.", cleaned) cleaned = re.sub(r'a \. k \. a .', "a.k.a.", cleaned) cleaned = re.sub(r'i \. e \.', "i.e.", cleaned) cleaned = re.sub(r'\. \. \.', "...", cleaned) cleaned = re.sub(r'(\d+) \. (\d*)', r"\1.\2", cleaned) #incase there are many spaces cleaned = re.sub(r'[" "]+', " ", cleaned) #remove space \n in the end of the sentences cleaned = cleaned.strip() #remove space and - in the start or end of the sentences again cleaned = cleaned.strip(' -') return cleaned def cleanPunc3(sentence): #remove word in () cleaned = re.sub(r'$[A-Z|a-z|0-9]+$',r'',sentence) #rule-based, replace the nameentity to certain entity (EX: 3D P2P CNN Tokenizer) # -- word with uppercase but appears in the middle of the sentence cleaned = re.sub(r'(?<= )(?:[A-Z]+[\w-]*|[\w\-]*[A-Z]+[\w\-]*)', '<NAME>', cleaned) #replace the number to certain entity (EX: 2000 2.05 2,000 2-5) cleaned = re.sub(r'(?:(?<= )\d+[\.\,\-]*\d*(?= )|^\d+(?= )|\d+(?=$))', '<NUMBER>', cleaned) #preserve some important punctuation and add a space between them and words cleaned = re.sub(r"([.!?])", r" \1 ", cleaned) #remove other punctuation cleaned = re.sub(r'[^a-zA-Z0-9?.!]+',r' ',cleaned) #restore special term cleaned = re.sub(r'e \. g \.', "e.g.", cleaned) cleaned = re.sub(r'a \. k \. a .', "a.k.a.", cleaned) cleaned = re.sub(r'i \. e \.', "i.e.", cleaned) cleaned = re.sub(r'\. \. \.', "...", cleaned) cleaned = re.sub(r'(\d+) \. (\d*)', r"\1.\2", cleaned) #incase there are many spaces cleaned = re.sub(r'[" "]+', " ", cleaned) #remove space \n in the end of the sentences cleaned = cleaned.strip() #remove space and - in the start or end of the sentences again cleaned = cleaned.strip(' -') return cleaned def removeStopWords(sentence): stop_words = set(stopwords.words('english')) re_stop_words = re.compile(r"\b(" + "|".join(stop_words) + ")\\W", re.I) return re_stop_words.sub("", sentence) def stemming(sentence): stemmer = SnowballStemmer("english") stemSentence = "" for word in sentence.split(): stem = stemmer.stem(word) stemSentence += stem stemSentence += " " stemSentence = stemSentence.strip() return stemSentence DATA = pd.read_csv('./train.csv') ''' Remove special punctuation and lower and stemming''' #DATA['Sentences'] = DATA['Sentences'].str.lower() DATA['Sentences'] = DATA['Sentences'].apply(cleanPunc3) #DATA['Sentences'] = DATA['Sentences'].apply(stemming) ''' Count length''' if DATA.Sentences.notna().all(): COUNT = np.zeros((DATA.shape[0])) for i in range(DATA.shape[0]): COUNT[i] = len(DATA.Sentences[i].split(' ')) DATA['LENGTH'] = COUNT ## replace empty sentences with <UNK> token DATA.loc[DATA['Sentences']=='','Sentences'] = '<UNK>' ## count the sentences with only Length==1/2 -- could be one of the features #COUNT1 = DATA[COUNT==1] #COUNT2 = DATA[COUNT==2] ## Tokenize #DATA['TOKEN'] = DATA.apply(lambda row: word_tokenize(row['Sentences']), axis=1) # using tokenizer #DATA['TOKEN'] = DATA.apply(lambda row: row['Sentences'].split(), axis=1) # or just split with space DATA.to_csv('train_removesomepunctuation_addentity.csv', index=False) #%% TEST TEST = pd.read_csv('test.csv') ''' Remove special punctuation and lower and stemming''' #TEST['Sentences'] = TEST['Sentences'].str.lower() TEST['Sentences'] = TEST['Sentences'].apply(cleanPunc3) #TEST['Sentences'] = TEST['Sentences'].apply(stemming) if TEST.Sentences.notna().all(): COUNT = np.zeros((TEST.shape[0])) for i in range(TEST.shape[0]): COUNT[i] = len(TEST.Sentences[i].split(' ')) TEST['LENGTH'] = COUNT ## replace empty sentences with <UNK> token TEST.loc[TEST['Sentences']=='','Sentences'] = '<unk>' ## Tokenize #TEST['TOKEN'] = TEST.apply(lambda row: word_tokenize(row['Sentences']), axis=1) #TEST['TOKEN'] = TEST.apply(lambda row: row['Sentences'].split(), axis=1) TEST.to_csv('test_removesomepunctuation_addentity.csv', index=False) #%% PRIVATE PRIVATE = pd.read_csv('private.csv') ''' Remove special punctuation and lower and stemming''' PRIVATE['Sentences'] = PRIVATE['Sentences'].apply(cleanPunc2) if PRIVATE.Sentences.notna().all(): COUNT = np.zeros((TEST.shape[0])) for i in range(PRIVATE.shape[0]): COUNT[i] = len(PRIVATE.Sentences[i].split(' ')) PRIVATE['LENGTH'] = COUNT ## replace empty sentences with <UNK> token PRIVATE.loc[PRIVATE['Sentences']=='','Sentences'] = '<unk>' # save PRIVATE.to_csv('private_removesomepunctuation.csv', index=False)

[ "eugenelu49@yahoo.com.tw" ]

eugenelu49@yahoo.com.tw

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fake-name/ReadableWebProxy

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2023-09-04T03:54:50.043051

2023-08-26T16:08:46

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"""empty message Revision ID: 11dbcd6e5ee3 Revises: 5aa994117f07 Create Date: 2017-09-28 04:06:18.968893 """ # revision identifiers, used by Alembic. revision = '11dbcd6e5ee3' down_revision = '5aa994117f07' branch_labels = None depends_on = None from alembic import op import sqlalchemy as sa from sqlalchemy_utils.types import TSVectorType from sqlalchemy_searchable import make_searchable import sqlalchemy_utils # Patch in knowledge of the citext type, so it reflects properly. from sqlalchemy.dialects.postgresql.base import ischema_names import citext import queue import datetime from sqlalchemy.dialects.postgresql import ENUM from sqlalchemy.dialects.postgresql import JSON from sqlalchemy.dialects.postgresql import TSVECTOR ischema_names['citext'] = citext.CIText def upgrade(): ### commands auto generated by Alembic - please adjust! ### op.execute("UPDATE nu_release_item SET fetch_attempts = 0 WHERE fetch_attempts IS NULL") op.execute("commit") op.alter_column('nu_release_item', 'fetch_attempts', existing_type=sa.INTEGER(), nullable=False) ### end Alembic commands ### def downgrade(): ### commands auto generated by Alembic - please adjust! ### op.alter_column('nu_release_item', 'fetch_attempts', existing_type=sa.INTEGER(), nullable=True) ### end Alembic commands ###

[ "something@fake-url.com" ]

something@fake-url.com

b6fb8eb2e7f812c6c108c58bc950f2ee0e489bc4

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/Code/heartland/hl_admin/tests.py

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[]

no_license

CS-4503-Gambit/vigilant-winner

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refs/heads/master

2021-08-14T07:06:45.307165

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from django.test import TestCase, Client from core.models import * # Create your tests here. class AdminTestCase(TestCase): # Test by Jon def setup(self): exec(open('populate.py').read()) self.client = Client() self.client.login(username='admin', password='heartland') # Test the home screen for admin login # Test by Jon def test_admin_home(self): self.setup() response = self.client.get('/admin/home/') # Check that the response was successful self.assertEqual(response.status_code, 200) # Check all the links are present self.assertContains(response, "Manage Database") self.assertContains(response, "View Results") self.assertContains(response, "View Judging Statistics") self.assertContains(response, "Create Judge or Registrar") self.assertContains(response, "View QR Codes") # Test the category display # Test by Jon def test_category_display(self): self.setup() response = self.client.get('/admin/scores/') # Check that the response was successful self.assertEqual(response.status_code, 200) # Check that both categories are present self.assertContains(response, "Video Games") self.assertContains(response, "Art") # Test the create user screen # Test by Jon def test_create_user(self): self.setup() response = self.client.get('/admin/create_user/') # Check that the response was successful self.assertEqual(response.status_code, 200) # Check that the fields are present self.assertContains(response, 'Username') self.assertContains(response, 'Password') self.assertContains(response, 'Type') # Test the View QR Code screen # Test by Jon def test_view_qr(self): self.setup() response = self.client.get('/admin/viewqr/') # Check that the response was successful self.assertEqual(response.status_code, 200) # Check that each category is present self.assertContains(response, 'Registrars') self.assertContains(response, 'Judges') self.assertContains(response, 'Teams') # check that the specific entries are present self.assertContains(response, 'registrar') self.assertContains(response, 'reg') self.assertContains(response, 'judge') self.assertContains(response, 'judy') self.assertContains(response, 'Bethesda Softworks') self.assertContains(response, 'Irrational Studios') self.assertContains(response, 'Leonardo Da Vinci') # Test that the judge listing is correct # Test by Jon def test_judge_list(self): self.setup() response = self.client.get('/admin/judges/') # Check that the response was successful self.assertEqual(response.status_code, 200) # Check that the list header is present self.assertContains(response, 'List of Judges') # Check that the judge is present self.assertContains(response, 'judge') self.assertContains(response, 'judy')

[ "jonb377@gmail.com" ]

jonb377@gmail.com

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2021-03-27T10:52:03.664874

2019-11-19T00:38:06

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# -*- coding: utf-8 -*- # ------------------------------------------------------------------------------ # FEDERAL UNIVERSITY OF UBERLANDIA # Faculty of Electrical Engineering # Biomedical Engineering Lab # ------------------------------------------------------------------------------ # Author: Italo Gustavo Sampaio Fernandes # Contact: italogsfernandes@gmail.com # Git: www.github.com/italogfernandes # ------------------------------------------------------------------------------ # Decription: # ------------------------------------------------------------------------------ from ThreadHandler import InfiniteTimer from Queue import Queue from pyqtgraph.Qt import QtGui, QtCore import numpy as np import pyqtgraph as pg from pyqtgraph.ptime import time from PyQt4.QtGui import QBrush, QColor, QPen, QGraphicsRectItem # ------------------------------------------------------------------------------ class pyqtgraphHandler: def __init__(self, qnt_pontos=10): self.qnt_pontos = qnt_pontos self.app = QtGui.QApplication([]) self.plot = pg.plot() self.plot.setBackgroundBrush(QBrush(QColor.fromRgb(255, 255, 255))) #self.plot.windowTitle(). #self.plot.setForegroundBrush(QBrush(QColor.fromRgb(250,0,0,30))) self.plot.setWindowTitle('PlotterHandler') self.plot.setRange(QtCore.QRectF(0, -10, 5000, 20)) self.plot.setLabel('bottom', 'Index', units='un') self.plot.setLabel('left', 'Valor', units='V') self.curve = self.plot.plot(pen='b') # self.plot.enableAutoRange('xy', True) self.plot.enableAutoRange('xy', False) self.plot.setXRange(0, 5000) self.plot.setYRange(0, 5) #self.plot.enableAutoRange('xy', True) #grade = pg.GridItem() #self.plot.addItem(grade) self.plot.showGrid(True, True) #self.plot.showAxis('top', False) #self.plot.showAxis('bottom', False) #self.plot.showAxis('left', False) #self.plot.showAxis('right', False) self.plot.getAxis('left').setPen(QPen(QColor.fromRgb(0,0,0))) self.plot.getAxis('bottom').setPen(QPen(QColor.fromRgb(0, 0, 0))) #print self.plot.getRange #self.plot. # self.plot.showGrid(2,3) #self.plot.hideAxis(ax) # self.timer = QtCore.QTimer() self.timer.timeout.connect(self.update_y_points) self.lastTime = time() self.fps = None self.y_values = [0] * self.qnt_pontos self.plot_buffer = Queue(qnt_pontos) def put(self, item): self.plot_buffer.put(item) def update_y_points(self): points_to_add = self.plot_buffer.qsize() if points_to_add > 0: for n in range(points_to_add): # obtains the new values num = self.plot_buffer.get() self.y_values.append(num) if len(self.y_values) > self.qnt_pontos: self.y_values.pop(0) self.update() def update(self): # global curve, data, ptr, p, lastTime, fps self.curve.setData(self.y_values) now = time() dt = now - self.lastTime self.lastTime = now if self.fps is None: self.fps = 1.0 / dt else: s = np.clip(dt * 3., 0, 1) self.fps = self.fps * (1 - s) + (1.0 / dt) * s self.plot.setTitle('%0.2f fps' % self.fps) self.app.processEvents() # force complete redraw for every plot def get_buffers_status(self): return "Plot: %4d" % (self.plot_buffer.qsize()) + '/' + str(self.plot_buffer.maxsize) def appear(self): self.timer.start(0) import sys if (sys.flags.interactive != 1) or not hasattr(QtCore, 'PYQT_VERSION'): QtGui.QApplication.instance().exec_() self.timer.stop() if __name__ == '__main__': my_plot = pyqtgraphHandler(5000) from datetime import datetime def generate_point(): agr = datetime.now() y_value = agr.microsecond / 1000000.0 my_plot.put(np.sin(2*np.pi*y_value)) #print y_value timer = InfiniteTimer(0.001, generate_point) timer.start() my_plot.appear()

[ "italogsfernandes@gmail.com" ]

italogsfernandes@gmail.com

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import torch import torch.utils.model_zoo as model_zoo import os import logging from collections import OrderedDict def load_state_dict(checkpoint_path, use_ema=False): if checkpoint_path and os.path.isfile(checkpoint_path): checkpoint = torch.load(checkpoint_path, map_location='cpu') state_dict_key = 'state_dict' if isinstance(checkpoint, dict): if use_ema and 'state_dict_ema' in checkpoint: state_dict_key = 'state_dict_ema' if state_dict_key and state_dict_key in checkpoint: new_state_dict = OrderedDict() for k, v in checkpoint[state_dict_key].items(): # strip `module.` prefix name = k[7:] if k.startswith('module') else k new_state_dict[name] = v state_dict = new_state_dict else: state_dict = checkpoint logging.info("Loaded {} from checkpoint '{}'".format(state_dict_key, checkpoint_path)) return state_dict else: logging.error("No checkpoint found at '{}'".format(checkpoint_path)) raise FileNotFoundError() def load_checkpoint(model, checkpoint_path, use_ema=False, strict=True, ignore_keys=None): state_dict = load_state_dict(checkpoint_path, use_ema) if ignore_keys: for del_key in ignore_keys: state_dict.pop(del_key) # for key in state_dict: # print(key,state_dict[key].shape) # exit() if not strict: model_dict = model.state_dict() for key in model_dict: if key in state_dict and model_dict[key].shape != state_dict[key].shape: state_dict.pop(key) model.load_state_dict(state_dict, strict=strict) def resume_checkpoint(model, checkpoint_path): other_state = {} resume_epoch = None if os.path.isfile(checkpoint_path): checkpoint = torch.load(checkpoint_path, map_location='cpu') if isinstance(checkpoint, dict) and 'state_dict' in checkpoint: new_state_dict = OrderedDict() for k, v in checkpoint['state_dict'].items(): name = k[7:] if k.startswith('module') else k new_state_dict[name] = v model.load_state_dict(new_state_dict) if 'optimizer' in checkpoint: other_state['optimizer'] = checkpoint['optimizer'] if 'amp' in checkpoint: other_state['amp'] = checkpoint['amp'] if 'epoch' in checkpoint: resume_epoch = checkpoint['epoch'] if 'version' in checkpoint and checkpoint['version'] > 1: resume_epoch += 1 # start at the next epoch, old checkpoints incremented before save logging.info("Loaded checkpoint '{}' (epoch {})".format(checkpoint_path, checkpoint['epoch'])) else: model.load_state_dict(checkpoint) logging.info("Loaded checkpoint '{}'".format(checkpoint_path)) return other_state, resume_epoch else: logging.error("No checkpoint found at '{}'".format(checkpoint_path)) raise FileNotFoundError() def load_pretrained(model, cfg=None, num_classes=1000, in_chans=3, filter_fn=None, strict=True): if cfg is None: cfg = getattr(model, 'default_cfg') if cfg is None or 'url' not in cfg or not cfg['url']: logging.warning("Pretrained model URL is invalid, using random initialization.") return state_dict = model_zoo.load_url(cfg['url'], progress=False, map_location='cpu') if in_chans == 1: conv1_name = cfg['first_conv'] logging.info('Converting first conv (%s) from 3 to 1 channel' % conv1_name) conv1_weight = state_dict[conv1_name + '.weight'] state_dict[conv1_name + '.weight'] = conv1_weight.sum(dim=1, keepdim=True) elif in_chans != 3: assert False, "Invalid in_chans for pretrained weights" classifier_name = cfg['classifier'] if num_classes == 1000 and cfg['num_classes'] == 1001: # special case for imagenet trained models with extra background class in pretrained weights classifier_weight = state_dict[classifier_name + '.weight'] state_dict[classifier_name + '.weight'] = classifier_weight[1:] classifier_bias = state_dict[classifier_name + '.bias'] state_dict[classifier_name + '.bias'] = classifier_bias[1:] elif num_classes != cfg['num_classes']: # completely discard fully connected for all other differences between pretrained and created model del state_dict[classifier_name + '.weight'] del state_dict[classifier_name + '.bias'] strict = False if filter_fn is not None: state_dict = filter_fn(state_dict) model.load_state_dict(state_dict, strict=strict)

[ "huangsy1314@163.com" ]

huangsy1314@163.com

cd8ff3b1036a37a03dbc1430032d1f214f4c9c47

4798adcdd8b03cddf8ec892091e67eda64db5379

/plasmidlord/plasmidlord.py

4e1d0e79c14d76bb3bd5dc10fa750e245b3f8b87

[]

no_license

maxlcummins/pipelord_old

e11bb92d958b4ed5da5e0371e0c05b28b095bc5c

049cb4a48242ce5ab08e6fd3802ef4d619de9ca3

refs/heads/master

2023-07-20T05:24:16.888318

2021-08-31T04:23:23

null

0

null

UTF-8

Python

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6,816

py

from scipy.spatial.distance import pdist from scipy.cluster.hierarchy import linkage, dendrogram import numpy as np import pandas as pd import glob import matplotlib matplotlib.use('Agg') #avoid problems with headless environments import matplotlib.pyplot as plt import matplotlib.colors as colors from matplotlib import gridspec def binning(data, step): """ Bin an array by step width, report the median of each bin :param data: array of ordred values to bin :param step: the bin step size :return: medians, bins """ meds = [] c = [] n = 0 bins = [] for ir in xrange(data.shape[0]): if data[ir, 0] > (n+1)*step: if len(c) > 0: meds.append(np.median(c)) else: meds.append(0) bins.append((n+1)*step) n += 1 c = [] else: c.append(data[ir, 1]) return np.array(meds), np.array(bins) def get_block_medians(glob_path, step_size): """ Read in the per-position coverage data for each sample and bin to a corser size :param glob_path: path which to scan for files :param step_size: the binning size in bp :return: pandas dataframe of binned depths (median values), bins for each set of medians """ meds = [] bins = [] smpl_names = [] # manually parse each organism directory. Manually meaning, change this path # for each one. Could be made a loop, but unnecessary for 3 runs for n, fn in enumerate(glob.glob('{}/*_coverage.txt'.format(glob_path))): print '\t {} found {}...'.format(n+1, fn) # read the data file smpl = fn.split('/')[-1][:-len('_coverage.txt')] smpl_names.append(smpl) data = pd.read_csv(fn, delimiter='\t', names=['_', 'x', 'depth']) data = data.as_matrix()[:, 1:] for row in data: if row[1] >= 10 and row[1] < 20: row[1] = 0.5 elif row[1] >= 20: row[1] = 1 m, b = binning(data, step_size) meds.append(m) bins.append(b) max_bins = 0 for bi in bins: if max(bi) > max_bins: max_bins = max(bi) for i in xrange(len(bins)): if max(bins[i]) < max_bins: print 'Warning, data file {} had fewer bins that the largest. Extra empty bins added'.format(i+1) bi = bins[i].tolist() mi = meds[i].tolist() while max(bi) < max_bins: bi.append(bi[-1] + step_size) mi.append(0) bins[i] = np.array(bi) meds[i] = np.array(mi) return pd.DataFrame(np.vstack(meds).T, columns=smpl_names), bins def run_hclust(outname, meds, bins, step_size, tick_spc, use_polo=True, save_plot=False): """ Cluster and plot the binned data matrix. This calls optimal leaf ordering algorithm (polo) by default, which has significant time-complexity. :param outname: pdf output file :param meds: median values :param bins: bins for medians :param step_size: size of a step :param tick_spc: tick spacing in "# bins" :param olo: reorder tips of tree with polo :param savePlot: save plot to file, otherwise plot to screen """ # just for indexing names = meds.columns # normalise rows by their median value D = meds.as_matrix().T # D = (D.T/np.median(D, 1)).T # center rows on their medians # D = (D.T - np.median(D, 1)).T # clustering options. We will use correlation as measure of distance # and complete linkage clustering metric = 'euclidean' method = 'complete' # calculate Y = linkage(D, method=method, metric=metric) # additionally, find optimal leaf ordering if use_polo: import polo print '\tcalculating optimal leaf ordering...' Y = polo.optimal_leaf_ordering(Y, pdist(D, metric=metric)) # now we do some plotting fig = plt.figure(figsize=(12, 0.25*len(meds.columns)), dpi=150) gs = gridspec.GridSpec(2, 2, width_ratios=[7, 1], height_ratios= [0.2,10]) axmatrix = plt.subplot(gs[2]) axmatrix.set_xlabel('genomic coord (kbp)') axcolor = plt.subplot(gs[0]) axcolor.set_title('log median relative abundance ') axdend = plt.subplot(gs[3]) # calculate and plot the dendrogram Z = dendrogram(Y, ax=axdend, orientation='right', no_labels=True, color_threshold=0 ) # the tips (leaves) of the tree become the order for rows idx = Z['leaves'] # reorder rows D = np.log(D[idx, :]+1) # the largest value in the matrix will set the upper and lower bounds # for the heatmap color-range. This assures 0 as the center. vmin = np.percentile(D, 2) vmax = np.percentile(D, 98) # plot the matrix, 5% extra bounds above and below on colour range im = axmatrix.matshow(D, aspect='auto', origin='lower', cmap='PuRd', norm=colors.Normalize(vmin=vmin, vmax=vmax)) axmatrix.set_xticks([]) axmatrix.set_yticks([]) # try and get some useful axis labels #xticks = np.linspace(0, max(bins) - max(bins) % step_size, 5) #print xticks print '\tticks will be every {}x{} = {} bp'.format(step_size, tick_spc, tick_spc*step_size) xticks = np.arange(0, len(bins), tick_spc) # every 100 bins axmatrix.set_xticks(xticks) axmatrix.set_xticklabels(xticks * step_size/1000) axmatrix.set_yticks(range(D.shape[0])) axmatrix.set_yticklabels(np.array(names)[idx], minor=False, ) axmatrix.xaxis.set_label_position('bottom') axmatrix.xaxis.tick_bottom() # Plot colorbar. fig.colorbar(im, cax=axcolor, orientation='horizontal') if save_plot: plt.savefig('{}_hclust.pdf'.format(outname), bbox_inches='tight') pd.DataFrame(D.T, columns=names).to_csv('{}_dat.csv'.format(outname)) else: plt.show() plt.close() if __name__ == '__main__': import argparse parser = argparse.ArgumentParser() parser.add_argument('--use-polo', action='store_true', default=False, help='Enable optimal leaf ordering') parser.add_argument('-b', '--bin-size', default=5000, type=int, help='Bin size in BP [5000]') parser.add_argument('-t', '--tick-spacing', default=100, type=int, help='Tick spacing in bins [100]') parser.add_argument('input_dir', help='Input directory containing coverage files') parser.add_argument('output_file', help='Output filename') args = parser.parse_args() print 'Reading and binning coverage files from {}'.format(args.input_dir) meds, bins = get_block_medians(args.input_dir, step_size=args.bin_size) print 'Clustering and plotting...' run_hclust(args.output_file, meds, bins[0], args.bin_size, args.tick_spacing, save_plot=True, use_polo=args.use_polo)

[ "maxcummins@MacBook-Air-8.local" ]

maxcummins@MacBook-Air-8.local

ba69e9897c4199039f0aede645cd587dc089c2ea

1747054ce51f1775870b8135adfdb666028f7305

/tree/sum_of_all_nodes.py

bfd435ff5ffc808da0033e2eb9640bc7bc4efa9a

[]

no_license

anshulgera/DSA

ac609b48383ebf5309e2017cc3e8344a83135b89

19ac5ad05460a3f707667bbc978223a0a55c8c3a

refs/heads/master

2020-07-24T20:32:32.619357

2019-12-15T06:18:59

208,040,935

1

0

null

UTF-8

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py

# Approach 1: divide the problem => sum of all nodes equals # = current node data + leftsubtree sum + rightsubtree sum # Apporach 2: level order traversal # Approach 3: Iterative traversal-pre, in, post from node import example_tree def preorder(root): if root: print(root.data, end=", ") preorder(root.left) preorder(root.right) def sum_of_all_nodes_inorder(node): if not root: print("Root is None") return stack = list() current = root total = 0 while True: if current: stack.append(current) current = current.left elif stack: current = stack.pop() total += current.data current = current.right else: return total def sum_of_all_nodes(node): if not node: return 0 return node.data + sum_of_all_nodes(node.left) + sum_of_all_nodes(node.right) # ---------------------- # construct tree root = example_tree() s = sum_of_all_nodes(root) print(f"from sum of all nodes {s}") s = sum_of_all_nodes_inorder(root) print(f"from sum of all nodes inorder {s}")

[ "anshul.gera@jda.com" ]

anshul.gera@jda.com

d25fd414d0cc93dd4bdd265401237349de38f3c9

23636b8144e37bb101c0d7e823f107f396c694dc

/Andrii-Lysyi/CodeWars-18.py

0f6b7594f73748f607b4524cd344e56f9bf1b279

[]

no_license

Andros1303/Andrew-Lusi

437b78cf61a7c04b61d6072ea5d14bba9e76c15f

8d25a149f0206c3b9a67c9aa6d2e241df4881c36

refs/heads/master

2020-05-17T20:00:27.575961

2019-06-05T17:11:11

183,932,338

0

null

UTF-8

Python

false

467

py

def list_animals(animals): list = '' for i in range(len(animals)): list += str(i + 1) + '. ' + animals[i] + '\n' return list # Your collegue wrote an simple loop to list his favourite animals. # But there seems to be a minor mistake in the grammar, which prevents the program to work. Fix it! :) # If you pass the list of your favourite animals to the function, you should get the list of the animals with orderings # and newlines added.

[ "noreply@github.com" ]

Andros1303.noreply@github.com

fc0fecc42711bdc8005c76234c04e40af133500a

3a9f2b3d79cf214704829427ee280f4b49dca70a

/saigon/rat/RuckusAutoTest/scripts/zd/ats_ZD_Combo_CLI_Application_Visibility_Standard_OPEN.py

4c9c5d9a1708723af600c8124e9f074a6b2e5ab3

[]

no_license

jichunwei/MyGitHub-1

ae0c1461fe0a337ef459da7c0d24d4cf8d4a4791

f826fc89a030c6c4e08052d2d43af0b1b4b410e3

refs/heads/master

2021-01-21T10:19:22.900905

2016-08-20T03:34:52

null

0

null

UTF-8

Python

false

19,649

py

""" Created on 2014-06 @author: chen.tao@odc-ruckuswireless.com """ import sys import random import libZD_TestSuite as testsuite from RuckusAutoTest.common import lib_KwList as kwlist from RuckusAutoTest.common import Ratutils as utils def define_wlan_cfg(): key_string_wpa2 = utils.make_random_string(random.randint(8, 63), "hex") wlan_cfg = { 'ssid': 'Application_Visibility_OPEN', 'type': 'standard', 'auth': 'PSK', 'wpa_ver': 'WPA2', 'encryption': 'AES', 'key_index': '', 'key_string': key_string_wpa2, 'sta_auth': 'PSK', 'sta_wpa_ver': 'WPA2', 'sta_encryption': 'AES', 'enable_application_visibility': True } return wlan_cfg def define_test_cfg(cfg,enable_tunnel): test_cfgs = [] target_ip_addr = '172.16.10.252' target_addr_for_denial_policy = 'www.example.net' radio_mode = cfg['radio_mode'] sta_radio_mode = radio_mode if sta_radio_mode == 'bg': sta_radio_mode = 'g' sta_tag = 'sta%s' % radio_mode ap_tag = 'ap%s' % radio_mode wlan_cfg = define_wlan_cfg() case_name_suffix = '' if enable_tunnel: wlan_cfg['do_tunnel'] = True case_name_suffix = '_with_tunnel' test_name = 'CB_ZD_Remove_All_Wlans' common_name = 'Remove all the WLANs from ZD' test_cfgs.append(({}, test_name, common_name, 0, False)) test_name = 'CB_ZD_Create_Station' common_name = 'Create target station' test_cfgs.append(({'sta_ip_addr':cfg['target_station'], 'sta_tag': sta_tag}, test_name, common_name, 0, False)) test_name = 'CB_Station_Remove_All_Wlans' common_name = 'Remove all WlANs from station' test_cfgs.append(({'sta_tag': sta_tag}, test_name, common_name, 0, False)) test_name = 'CB_ZD_Config_AP_Radio' common_name = 'Config All APs Radio - Disable WLAN Service' test_params = {'cfg_type': 'init', 'all_ap_mac_list': cfg['all_ap_mac_list']} test_cfgs.append((test_params, test_name, common_name, 0, False)) test_name = 'CB_ZD_Create_Active_AP' common_name = 'Create active AP' test_cfgs.append(({'active_ap':cfg['active_ap'], 'ap_tag': ap_tag}, test_name, common_name, 0, False)) test_name = 'CB_ZD_Config_AP_Radio' common_name = 'Config active AP Radio %s - Enable WLAN Service' % (radio_mode) test_params = {'cfg_type': 'config', 'ap_tag': ap_tag, 'ap_cfg': {'radio': radio_mode, 'wlan_service': True}, } test_cfgs.append((test_params, test_name, common_name, 0, False)) test_name = 'CB_ZD_CLI_Application_Visibility_Init_Env' common_name = 'Try to delete all application visibility rules.' test_params = {} test_cfgs.append((test_params, test_name, common_name, 0, False)) #testcase 1 test_case_name = '[user_app_open_standard%s]'%case_name_suffix user_app_rule_cfg = {'rule_description':'user_app_open_none', 'dest_ip':target_ip_addr, 'dest_port':'12345', 'netmask':'255.255.255.0', 'protocol':'udp'} test_name = 'CB_ZD_CLI_Add_User_Defined_App' common_name = '%s Add a user app.'% (test_case_name) test_params = {'user_app_cfg':[user_app_rule_cfg], 'negative': False,} test_cfgs.append((test_params,test_name, common_name, 1, False)) test_name = 'CB_ZD_Create_Wlan' common_name = '%sCreate WLAN on ZD'% (test_case_name) test_cfgs.append(({'wlan_cfg_list':[wlan_cfg], 'enable_wlan_on_default_wlan_group': True, }, test_name, common_name, 2, False)) test_name = 'CB_ZD_Associate_Station_1' common_name = '%sAssociate the station to the WLAN'% (test_case_name) test_cfgs.append(({'wlan_cfg': wlan_cfg, 'sta_tag': sta_tag}, test_name, common_name, 2, False)) test_name = 'CB_ZD_Get_Station_Wifi_Addr_1' common_name = '%sGet WiFi address of the station'% (test_case_name) test_cfgs.append(({'sta_tag': sta_tag}, test_name, common_name, 2, False)) test_name = 'CB_ZD_Verify_Station_Info_V2' common_name = '%sVerify client information Authorized status in ZD'% (test_case_name) test_cfgs.append(({'sta_tag': sta_tag, 'ap_tag': ap_tag, 'status': 'Authorized', 'wlan_cfg': wlan_cfg, 'radio_mode':sta_radio_mode,}, test_name, common_name, 2, False)) test_name = 'CB_ZD_Client_Ping_Dest' common_name = '%sVerify station pings to the server successfully'% (test_case_name) test_cfgs.append(({'sta_tag': sta_tag, 'condition': 'allowed', 'target': target_ip_addr}, test_name, common_name, 2, False)) test_name = 'CB_Server_Start_Iperf' common_name = '%sStart iperf server on linux PC'% (test_case_name) test_cfgs.append(({'server_addr':'', 'test_udp': True, 'packet_len':'', 'bw':'', 'timeout':'', 'tos':'', 'multicast_srv':False, 'port':12345 }, test_name, common_name, 2, False)) test_name = 'CB_Station_Start_Iperf' common_name = '%sStart iperf client and send traffic to server'% (test_case_name) test_cfgs.append(({'sta_tag':sta_tag, 'server_addr':target_ip_addr, 'test_udp': True, 'packet_len':'', 'bw':'', 'timeout':60, 'tos':'', 'multicast_srv':False, 'port':12345 }, test_name, common_name, 2, False)) test_name = 'CB_Server_Stop_Iperf' common_name = '%sStop iperf server on linux PC'% (test_case_name) test_cfgs.append(({}, test_name, common_name, 2, False)) test_name = 'CB_Station_Stop_Iperf' common_name = '%sStop iperf client on station'% (test_case_name) test_cfgs.append(({'sta_tag':sta_tag}, test_name, common_name, 2, False)) test_name = 'CB_ZD_Verify_Application_Visibility_Info' common_name = '%sVerify application info in Monitor Clients page'% (test_case_name) test_cfgs.append(({'application_description':'user_app_open_none'}, test_name, common_name, 2, False)) test_name = 'CB_Station_Remove_All_Wlans' common_name = '%sRemove all WlANs from station'% (test_case_name) test_cfgs.append(({'sta_tag': sta_tag}, test_name, common_name, 2, True)) test_name = 'CB_ZD_Remove_All_Wlans' common_name = '%sRemove all the WLANs from ZD'% (test_case_name) test_cfgs.append(({}, test_name, common_name, 2, True)) test_name = 'CB_ZD_CLI_Del_User_Defined_App' common_name = '%s Delete all user apps.'% (test_case_name) test_params = {} test_cfgs.append((test_params,test_name, common_name, 2, True)) #testcase 2 test_case_name = '[port_mapping_open_standard%s]'%case_name_suffix port_mapping_rule_cfg = {'rule_description':'port_mapping_open_none','protocol':'udp','port':'54321'} test_name = 'CB_ZD_CLI_Add_Port_Mapping_Policy' common_name = '%s Add a port mapping rule.'% (test_case_name) test_params = {'port_mapping_cfg':[port_mapping_rule_cfg],} test_cfgs.append((test_params,test_name, common_name, 1, False)) test_name = 'CB_ZD_Create_Wlan' common_name = '%sCreate WLAN on ZD'% (test_case_name) test_cfgs.append(({'wlan_cfg_list':[wlan_cfg], 'enable_wlan_on_default_wlan_group': True, }, test_name, common_name, 2, False)) test_name = 'CB_ZD_Associate_Station_1' common_name = '%sAssociate the station to the WLAN'% (test_case_name) test_cfgs.append(({'wlan_cfg': wlan_cfg, 'sta_tag': sta_tag}, test_name, common_name, 2, False)) test_name = 'CB_ZD_Get_Station_Wifi_Addr_1' common_name = '%sGet WiFi address of the station'% (test_case_name) test_cfgs.append(({'sta_tag': sta_tag}, test_name, common_name, 2, False)) test_name = 'CB_ZD_Verify_Station_Info_V2' common_name = '%sVerify client information Authorized status in ZD'% (test_case_name) test_cfgs.append(({'sta_tag': sta_tag, 'ap_tag': ap_tag, 'status': 'Authorized', 'wlan_cfg': wlan_cfg, 'radio_mode':sta_radio_mode,}, test_name, common_name, 2, False)) test_name = 'CB_ZD_Client_Ping_Dest' common_name = '%sVerify station pings to the server successfully'% (test_case_name) test_cfgs.append(({'sta_tag': sta_tag, 'condition': 'allowed', 'target': target_ip_addr}, test_name, common_name, 2, False)) test_name = 'CB_Server_Start_Iperf' common_name = '%sStart iperf server on linux PC'% (test_case_name) test_cfgs.append(({'server_addr':'', 'test_udp': True, 'packet_len':'', 'bw':'', 'timeout':'', 'tos':'', 'multicast_srv':False, 'port':54321 }, test_name, common_name, 2, False)) test_name = 'CB_Station_Start_Iperf' common_name = '%sStart iperf client and send traffic to server'% (test_case_name) test_cfgs.append(({'sta_tag':sta_tag, 'server_addr':target_ip_addr, 'test_udp': True, 'packet_len':'', 'bw':'', 'timeout':60, 'tos':'', 'multicast_srv':False, 'port':54321 }, test_name, common_name, 2, False)) test_name = 'CB_Server_Stop_Iperf' common_name = '%sStop iperf server on linux PC'% (test_case_name) test_cfgs.append(({}, test_name, common_name, 2, False)) test_name = 'CB_Station_Stop_Iperf' common_name = '%sStop iperf client on station'% (test_case_name) test_cfgs.append(({'sta_tag':sta_tag}, test_name, common_name, 2, False)) test_name = 'CB_ZD_Verify_Application_Visibility_Info' common_name = '%sVerify application info in Monitor Clients page'% (test_case_name) test_cfgs.append(({'application_description':'port_mapping_open_none',}, test_name, common_name, 2, False)) test_name = 'CB_Station_Remove_All_Wlans' common_name = '%sRemove all WlANs from station'% (test_case_name) test_cfgs.append(({'sta_tag': sta_tag}, test_name, common_name, 2, True)) test_name = 'CB_ZD_Remove_All_Wlans' common_name = '%sRemove all the WLANs from ZD'% (test_case_name) test_cfgs.append(({}, test_name, common_name, 2, True)) test_name = 'CB_ZD_CLI_Del_Port_Mapping_Policy' common_name = '%s Delete all port mapping policies.'% (test_case_name) test_params = {} test_cfgs.append((test_params,test_name, common_name, 2, True)) #testcase 3 test_case_name = '[denial_policy_open_standard%s]'%case_name_suffix denial_policy_cfg = {'policy_description': 'test_app_denial_policy', 'policy_name': 'test_app_denial_policy', 'rules': [{'application': 'Port', 'rule_description': 80, 'rule_id': 1}, {'application': 'HTTP hostname', 'rule_description': 'www.example.net', 'rule_id': 2}]} test_name = 'CB_ZD_CLI_Add_App_Denial_Policy' common_name = '%s Add a denial policy.'% (test_case_name) test_params = {'denial_policy_cfg':[denial_policy_cfg],} test_cfgs.append((test_params,test_name, common_name, 1, False)) test_name = 'CB_ZD_Create_Wlan' common_name = '%sCreate WLAN on ZD'% (test_case_name) test_cfgs.append(({'wlan_cfg_list':[wlan_cfg], 'enable_wlan_on_default_wlan_group': True, }, test_name, common_name, 2, False)) test_name = 'CB_ZD_Associate_Station_1' common_name = '%sAssociate the station to the WLAN'% (test_case_name) test_cfgs.append(({'wlan_cfg': wlan_cfg, 'sta_tag': sta_tag}, test_name, common_name, 2, False)) test_name = 'CB_ZD_Get_Station_Wifi_Addr_1' common_name = '%sGet WiFi address of the station'% (test_case_name) test_cfgs.append(({'sta_tag': sta_tag}, test_name, common_name, 2, False)) test_name = 'CB_ZD_Verify_Station_Info_V2' common_name = '%sVerify client information Authorized status in ZD'% (test_case_name) test_cfgs.append(({'sta_tag': sta_tag, 'ap_tag': ap_tag, 'status': 'Authorized', 'wlan_cfg': wlan_cfg, 'radio_mode':sta_radio_mode,}, test_name, common_name, 2, False)) test_name = 'CB_Station_Ping_Dest_Is_Allowed' common_name = '%sVerify station pinging to the server succeeds'%(test_case_name) test_cfgs.append(({'sta_tag': sta_tag, 'dest_ip': target_addr_for_denial_policy,}, test_name, common_name, 2, False)) test_name = 'CB_Station_Connect_To_Server_Port' common_name = "%sVerify station connecting to server's port succeeds"%(test_case_name) test_cfgs.append(({'sta_tag': sta_tag, 'server_ip': '172.16.10.252','dest_port':80}, test_name, common_name, 2, False)) #edit wlan to enable denial policy test_name = 'CB_ZD_Edit_Wlan' common_name = '%sEdit wlan, to select a denial policy' % test_case_name param_cfg = {'wlan_ssid': wlan_cfg['ssid'], 'new_wlan_cfg': {'application_denial_policy':'test_app_denial_policy'}} test_cfgs.append((param_cfg,test_name, common_name, 2, False)) test_name = 'CB_Station_Ping_Dest_Is_Denied' common_name = '%sVerify station pinging to the server fails'%(test_case_name) test_cfgs.append(({'sta_tag': sta_tag, 'dest_ip': target_addr_for_denial_policy,}, test_name, common_name, 2, False)) test_name = 'CB_Station_Connect_To_Server_Port' common_name = "%sVerify station connecting to server's port fails"%(test_case_name) test_cfgs.append(({'sta_tag': sta_tag, 'server_ip': '172.16.10.252','dest_port':80,'negative':True}, test_name, common_name, 2, False)) test_name = 'CB_Station_Remove_All_Wlans' common_name = '%sRemove all WlANs from station'% (test_case_name) test_cfgs.append(({'sta_tag': sta_tag}, test_name, common_name, 2, True)) test_name = 'CB_ZD_Remove_All_Wlans' common_name = '%sRemove all the WLANs from ZD'% (test_case_name) test_cfgs.append(({}, test_name, common_name, 2, True)) test_name = 'CB_ZD_CLI_Del_App_Denial_Policy' common_name = '%s Delete all denial policies.'% (test_case_name) test_params = {} test_cfgs.append((test_params,test_name, common_name, 2, True)) #clean_up test_name = 'CB_ZD_Config_AP_Radio' common_name = 'Config All APs Radio - Enable WLAN Service' test_params = {'cfg_type': 'teardown', 'all_ap_mac_list': cfg['all_ap_mac_list']} test_cfgs.append((test_params, test_name, common_name, 0, True)) test_name = 'CB_Station_Remove_All_Wlans' common_name = 'Remove all WlANs from station for the next test' test_cfgs.append(({'sta_tag': sta_tag}, test_name, common_name, 0, True)) test_name = 'CB_ZD_CLI_Application_Visibility_Init_Env' common_name = 'Try to delete all application visibility rules for next test.' test_params = {} test_cfgs.append((test_params, test_name, common_name, 0, True)) return test_cfgs def check_max_length(test_cfgs): for test_params, testname, common_name, exc_level, is_cleanup in test_cfgs: if len(common_name) > 120: raise Exception('common_name[%s] in case [%s] is too long, more than 120 characters' % (common_name, testname)) def check_duplicated_common_name(test_cfgs): common_name_list = [] duplicate_flag = False for test_params, testname, common_name, exc_level, is_cleanup in test_cfgs: if common_name in common_name_list: duplicate_flag = False print '####################' print common_name print '####################' else: common_name_list.append(common_name) return duplicate_flag def createTestSuite(**kwargs): ts_cfg = dict(interactive_mode=True, station=(0, "g"), targetap=False, testsuite_name="", ) ts_cfg.update(kwargs) mtb = testsuite.getMeshTestbed(**kwargs) tbcfg = testsuite.getTestbedConfig(mtb) sta_ip_list = tbcfg['sta_ip_list'] ap_sym_dict = tbcfg['ap_sym_dict'] all_ap_mac_list = tbcfg['ap_mac_list'] if ts_cfg["interactive_mode"]: print '\nOnly the following AP models support application visibility:' print ' 1.ZF-7762-AC,ZF-7762-S-AC' print ' 2.ZF-7782,ZF-7782-s,ZF-7782-n,ZF-7782-e' print ' 3.ZF-7982' print ' 4.sc8800-s-ac,sc8800-s' print ' 5.ZF-7055' print ' 6.ZF-7352' print ' 7.ZF-7372,ZF-7372-e' print ' 8.ZF-7781-m,ZF-7781cm' active_ap_list = testsuite.getActiveAp(ap_sym_dict) target_sta = testsuite.getTargetStation(sta_ip_list, "Pick wireless station: ") target_sta_radio = testsuite.get_target_sta_radio() else: target_sta = sta_ip_list[ts_cfg["station"][0]] target_sta_radio = ts_cfg["station"][1] if kwargs["targetap"]: active_ap_list = sorted(ap_sym_dict.keys()) active_ap = active_ap_list[0] tcfg = { 'target_station':'%s' % target_sta, 'radio_mode': target_sta_radio, 'active_ap':active_ap, 'all_ap_mac_list': all_ap_mac_list, } tunnel_mode = raw_input("\n\ Do you want to enable tunnel to do test?\n\ 1. Yes\n\ 2. No\n\ Default selection is 2.Input your choice:") if tunnel_mode != '1': enable_tunnel = False else: enable_tunnel = True test_cfgs = define_test_cfg(tcfg,enable_tunnel) check_max_length(test_cfgs) check_duplicated_common_name(test_cfgs) ts_suffix = '' if enable_tunnel: ts_suffix = ' - tunneled' if ts_cfg["testsuite_name"]: ts_name = ts_cfg["testsuite_name"] else: ts_name = "Application_Visibility - Standard - OPEN%s"%ts_suffix ts = testsuite.get_testsuite(ts_name, "Application_Visibility - Standard - OPEN%s"%ts_suffix , combotest=True) test_order = 1 test_added = 0 for test_params, testname, common_name, exc_level, is_cleanup in test_cfgs: if testsuite.addTestCase(ts, testname, common_name, test_params, test_order, exc_level, is_cleanup) > 0: test_added += 1 test_order += 1 print "Add test case with test name: %s\n\t\common name: %s" % (testname, common_name) print "\n-- Summary: added %d test cases into test suite '%s'" % (test_added, ts.name) if __name__ == "__main__": _dict = kwlist.as_dict(sys.argv[1:]) createTestSuite(**_dict)

[ "tan@xx.com" ]

tan@xx.com

2e5e3e67e1ff2834fbde5eafac226a339de6d857

a471266944a3227f458234388ad7a5fa091a0f89

/rsg_selct.py

4f68c558fce1c50a69b7e47ca88e80aa7c78c6d5

[]

no_license

rubab1/RSG-Select

51fff92f3b963db9bce1b041f9539ee3510e221b

e652b0d215cc1f70251ac9cdca293659f5715474

refs/heads/master

2020-03-23T08:52:46.868439

2018-07-17T22:51:39

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import numpy as np from astropy.io import fits from astropy.io import ascii from astropy.table import Table from scipy.spatial import cKDTree rad = 0.5 # matching radii, arcsec err = 0.3 # mag error, Vega crd = 0.5 # crowding effect, Vega def DoAll(infile='14786_N6846-SN2017.gst.fits',outfile='targets1'): ref = ascii.read('n6946_CAT') tol = rad/3600 filt = ['F606W','F814W'] ra2,dec2,mm1,ee1,dd1,mm2,ee2,dd2 = ref['col1'],ref['col2'],ref['col3'],ref['col4'],ref['col5'],ref['col6'],ref['col7'],ref['col8'] t = (ee1<err)&(ee2<err)&(dd1<crd)&(dd2<crd) ra2,dec2,mm1,ee1,mm2,ee2=ra2[t],dec2[t],mm1[t],ee1[t],mm2[t],ee2[t] X,Y,RA,DEC,vega_mags,mag_errors,detector = read_phot_fits_table(infile,filt) t = (((vega_mags[0]-vega_mags[1])>2)&(vega_mags[0]<29)&(vega_mags[1]<24.5)) ra1,dec1,mag1,mag2,err1,err2 = RA[t],DEC[t],vega_mags[0][t],vega_mags[1][t],mag_errors[0][t],mag_errors[1][t] in1 = matchLists(tol,ra1,dec1,ra2,dec2) ra1,dec1,mag1,mag2,err1,err2 = ra1[in1!=-1],dec1[in1!=-1],mag1[in1!=-1],mag2[in1!=-1],err1[in1!=-1],err2[in1!=-1] mm1,mm2,ee1,ee2 = mm1[in1[in1!=-1]],mm2[in1[in1!=-1]],ee1[in1[in1!=-1]],ee2[in1[in1!=-1]] return write_target_list(ra1,dec1,mag1,err1,mag2,err2,mm1,ee1,mm2,ee2,outfile) def read_phot_fits_table(filename,filt): photTable = fits.open(filename) detector = photTable[0].header['CAMERA'] data = photTable[1].data; del photTable vega_mags = [data[filt[0]+'_VEGA'], data[filt[1]+'_VEGA']] mag_errors = [data[filt[0]+'_ERR'], data[filt[1]+'_ERR']] X,Y,RA,DEC = data['X'],data['Y'],data['RA'],data['DEC'] return X,Y,RA,DEC,vega_mags,mag_errors,detector ''' Quick match; returns index of 2nd list coresponding to position in 1st ''' def matchLists(tol,x1,y1,x2,y2): d1 = np.empty((x1.size, 2)) d2 = np.empty((x2.size, 2)) d1[:,0],d1[:,1] = x1,y1 d2[:,0],d2[:,1] = x2,y2 t = cKDTree(d2) tmp, in1 = t.query(d1, distance_upper_bound=tol) in1[in1==x2.size] = -1 return in1 def write_target_list(ra,dec,m1,err1,m2,err2,m3,err3,m4,err4,fileroot): outfile = fileroot+'.txt' tab = [ra,dec,m1,err1,m2,err2,m3,err3,m4,err4] nms = ('RA','DEC','F606W','ER606','F814W','ER814','IRAC1','ERR36','IRAC2','ERR45') fmt = {'RA':'%12.7f','DEC':'%12.7f','F606W':'%8.3f','ER606':'%8.3f', 'F814W':'%8.3f','ER814':'%8.3f','IRAC1':'%8.3f','ERR36':'%8.3f','IRAC2':'%8.3f','ERR45':'%8.3f'} t = Table(tab, names=nms) ascii.write(t, outfile, format='fixed_width', delimiter='', formats=fmt, overwrite=True) return print('Wrote out: ', outfile) ### DoAll('14786_N6846-SN2017.gst.fits','targets1') DoAll('14786_N6946-111ne-26900.gst.fits','targets2') DoAll('20180119_Vanisher.gst.fits','targets3')

[ "rubab@uw.edu" ]

rubab@uw.edu

ce99e765ea48053b039f968a4a801368104e5c6f

485d62d8adb88925535fc57ec8eb127db5012767

/venv/bin/wheel

dfde5beee5436d07a85e08a2ff772f82ec815212

[]

no_license

MariomcgeeArt/Tweet-gen

f9995e1350413f23e1f32675d35a47bdf3cb81f3

619c6f7fb184b0458121193923757c866a64acaa

refs/heads/master

2021-01-03T03:22:28.599007

2020-03-09T17:27:11

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#!/Users/makeschoolloaner/Desktop/devloper/ms/Tweet/venv/bin/python3.7 # -*- coding: utf-8 -*- import re import sys from wheel.cli import main if __name__ == '__main__': sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0]) sys.exit(main())

[ "mario.mcgee@students.makeschool.com" ]

mario.mcgee@students.makeschool.com

871284d24db3cfaf05336d9c7b5bd82940d854ca

7eecd923b2b34d1888ca97d95af21ef0e4bb6d29

/source/generator/multiplication.py

03c2f79153cc04daad2c9b93144f81d0479e48c1

[]

no_license

Az2Poivron/piwar

b641acd1a274949ec03fd6187ad3d3511c62f7c5

f5015e9e9649713addbded2bc87f82ed51169a14

refs/heads/main

2023-05-03T10:07:42.295623

2021-05-30T16:46:59

372,017,734

1

0

null

UTF-8

Python

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685

py

from random import randint as rdm class Multiplication: #a * b = c condition = "MULTIPLICATION_ENABLE" def __init__(self,rule): a_min = rule["MULTIPLICATION_a_min"] a_max = rule["MULTIPLICATION_a_max"] b_min = rule["MULTIPLICATION_b_min"] b_max = rule["MULTIPLICATION_b_max"] equa = rule["MULTIPLICATION_equa"] a = rdm(a_min,a_max) b = rdm(b_min,b_max) c = a * b L = [a,b,c] if equa: a_index = rdm(0,2) else: a_index = 2 self.answer = L[a_index] L[a_index] = "?" self.str = f"{L[0]} x {L[1]} = {L[2]}"

[ "«monnomctom@gmail.com»" ]

«monnomctom@gmail.com»

5d00ab45b31431b87c4bc649952d35c2f2a94f9a

2b249f2be3a06b647c58ed09f14d1c0cc77b0309

/cluster/pkg/swarmer.py

059f3d7ad0f2e3b332823c5df2ff5527b94be16d

[]

permissive

Hrishi5/ACI-EnhancedEndpointTracker

7dad677146ae4a26e1e2f212ad6e6eead92e3513

a4de84c5fc00549e6539dbc1d8d927c74a704dcc

refs/heads/2.0

2020-04-01T18:18:24.119980

2018-12-14T06:17:15

148,533,258

0

MIT

2018-09-12T19:46:19

null

UTF-8

Python

false

22,407

py

from .connection import Connection from .lib import run_command from .lib import pretty_print import getpass import json import logging import re import time # module level logging logger = logging.getLogger(__name__) class Swarmer(object): def __init__(self, config, username=None, password=None): # recevies instance of ClusterConfig self.config = config self.username = username self.password = password self.nodes = {} self.node_id = None # local node-id self.node_addr = None # local node-addr self.node_socket = None # local node-addr+port for registering worker nodes self.token = None # registration token # reindex config.nodes with string id's to match against string labels config_nodes = {} for nid in self.config.nodes: config_nodes["%s" % nid] = self.config.nodes[nid] self.config.nodes = config_nodes def get_credentials(self): # prompt user for username/password if not previously provided while self.username is None or len(self.username)==0: self.username = raw_input("Enter ssh username: ").strip() while self.password is None or len(self.password)==0: self.password = getpass.getpass("Enter ssh password: ").strip() def get_connection(self, hostname): # return ssh connection object to provided hostname, raise exception on error logger.debug("get connection to %s", hostname) self.get_credentials() c = Connection(hostname) c.username = self.username c.password = self.password c.protocol = "ssh" c.port = 22 c.prompt = "[#>\$] *$" if not c.login(max_attempts=3): raise Exception("failed to connect to node %s@%s" % (self.username, hostname)) return c def init_swarm(self): # determine the swarm status of this node. If in a swarm but not the manager, raise an error # If in a swarm AND the manager, then validate status matches config. # If in not in a swarm, then assume this non-initialized system js = self.get_swarm_info() self.node_id = js["NodeID"] self.node_addr = js["NodeAddr"] managers = js["RemoteManagers"] manager_addr = None if len(self.node_id) > 0: logger.debug("node %s is part of an existing swarm", self.node_addr) self.set_node_socket(managers) if self.node_socket is None: err_msg = "This node is not a docker swarm manager. " err_msg+= "Please execute on the node-1" raise Exception(err_msg) else: # need to initialize this node as a swarm master logger.info("initializing swarm master") if not run_command("docker swarm init"): raise Exception("failed to initialize node as swarm master") # get new swarm info js = self.get_swarm_info() self.node_id = js["NodeID"] self.node_addr = js["NodeAddr"] managers = js["RemoteManagers"] self.set_node_socket(managers) if self.node_socket is None: raise Exception("failed to init swarm manager, no Addr found in RemoteManagers") # validated that swarm is initialized and we're executing on a manager node. Need to get # token for deploying to new workers token = run_command("docker swarm join-token worker -q") if token is None: raise Exception("failed to get swarm token from manager") self.token = token.strip() logger.debug("swarm token: %s", self.token) # get list of current nodes IDs self.get_nodes() lnode = self.nodes.get(self.node_id, None) if lnode is None: raise Exception("unable to find local id %s in docker nodes", self.node_id) # check label for current node is '1', if not add it node_label = lnode.labels.get("node", None) if node_label is None: logger.debug("adding label '1' to local node") cmd = "docker node update --label-add node=1 %s" % self.node_id if run_command(cmd) is None: raise Exception("failed to add docker node label node=1 to %s" % self.node_id) lnode.labels["node"] = "1" elif "%s"%node_label != "1": err_msg = "This node(%s) has node-id set to %s. Please run on node-1" % ( self.node_id, node_label) raise Exception(err_msg) else: logger.debug("node(%s) already assigned with label 1", self.node_id) # index nodes by addr and label id, raise error on duplicate index_addr = {} index_label = {} for nid in self.nodes: n = self.nodes[nid] if n.addr in index_addr: raise Exception("duplicate docker node address: %s between %s and %s" % (n.addr, index_addr[n.addr].node_id, nid)) node_label = n.labels.get("node", None) if node_label is None: # existing node without a label should not exists, we could try to fix it here but # that's a bit out of scope. Will force user to manually fix it for now... err_msg = "Node(%s) exists within swarm but does not have a label. " % nid err_msg+= "Manually add the appropriate id label via:\n" err_msg+= " docker node update --label-add node=<id> %s" % nid raise Exception(err_msg) node_label = "%s" % node_label if node_label in index_label: raise Exception("duplicate docker label node=%s between %s and %s" % (node_label, index_label[node_label].node_id, nid)) index_addr[n.addr] = n index_label[node_label] = n logger.debug("index_label: %s", index_label) # validate each node in the config or add it if missing for node_label in sorted(self.config.nodes): # already validate we're on node-id 1, never need to add 1 as worker if node_label == "1": continue hostname = self.config.nodes[node_label]["hostname"] if node_label not in index_label: swarm_node_id = self.add_worker(hostname, node_label) cmd = "docker node update --label-add node=%s %s" % (node_label, swarm_node_id) if run_command(cmd) is None: raise Exception("failed to add docker node label node=%s to %s" % (node_label, swarm_node_id)) logger.info("docker cluster initialized with %s node(s)", len(self.config.nodes)) def add_worker(self, hostname, nid): """ attempt to connect to remote node and add to docker swarm """ # prompt user for credentials here if not set... logger.info("Adding worker to cluster (id:%s, hostname:%s)", nid, hostname) c = self.get_connection(hostname) cmd = "docker swarm join --token %s %s" % (self.token, self.node_socket) ret = c.cmd(cmd, timeout=60) if ret != "prompt": raise Exception("failed to add worker(%s) %s: %s" % (nid, hostname, ret)) if not re.search("This node joined a swarm", c.output): raise Exception("failed to add worker(%s) %s: %s" % (nid, hostname, c.output)) # hopefully node was added, grab the NodeID from the swarm and then make sure it is seen # on the master node (over ssh so outputs contain prompt and full command) cmd = "docker info --format '{{.Swarm.NodeID}}'" ret = c.cmd(cmd) if ret != "prompt": raise Exception("failed to determine Swarm.NodeID for worker(%s) %s" % (nid, hostname)) for l in c.output.split("\n"): r1 = re.search("^(?P<node_id>[a-zA-Z0-9]{25})$", l.strip()) if r1 is not None: logger.debug("Swarm.NodeID %s for worker(%s) %s", r1.group("node_id"),nid,hostname) return r1.group("node_id") raise Exception("unable to extract Swarm.NodeID for new worker(%s) %s"% (nid, hostname)) def set_node_socket(self, managers): """ from docker swarm RemoteManagers list, find the socket connection (Addr) for the provided node_id. Return None on error """ self.node_socket = None if managers is not None: for m in managers: if "NodeID" in m and "Addr" in m and m["NodeID"] == self.node_id: logger.debug("node %s matches manager %s", self.node_id, m) self.node_socket = m["Addr"] return logger.debug("node %s not in RemoteManagers list", self.node_id) def get_swarm_info(self): """ get and validate swarm info from 'docker info' command return dict { "NodeID": "", "NodeAddr": "", "RemoteManagers": "", } """ # get/validate swarm info from 'docker info' command. Return info = run_command("docker info --format '{{json .}}'") if info is None: raise Exception("failed to get docker info, is docker installed?") js = json.loads(info) logger.debug("local node docker info:%s", pretty_print(js)) if "Swarm" not in js or "NodeID" not in js["Swarm"] or "NodeAddr" not in js["Swarm"] or \ "RemoteManagers" not in js["Swarm"]: version = js.get("ServerVersion", "n/a") raise Exception("no Swarm info, unsupported docker version: %s" % version) return { "NodeID": js["Swarm"]["NodeID"], "NodeAddr": js["Swarm"]["NodeAddr"], "RemoteManagers": js["Swarm"]["RemoteManagers"], } def get_nodes(self): """ read docker nodes and update self.nodes """ logger.debug("get docker node info") lines = run_command("docker node ls --format '{{json .}}'") if lines is None: raise Exception("unable to get docker node info") for l in lines.split("\n"): if len(l) == 0: continue try: logger.debug("node: %s", l) node = DockerNode(**json.loads(l)) if node.node_id is not None: self.nodes[node.node_id] = node logger.debug("new node: %s", node) except ValueError as e: logger.debug("failed to decode node: '%s'", l) def deploy_service(self): """ deploy docker service referencing config file and verify everything is running """ logger.info("deploying app services, please wait...") cmd = "docker stack deploy -c %s %s" % (self.config.compose_file, self.config.app_name) if run_command(cmd) is None: raise Exception("failed to deploy stack") check_count = 8 check_interval = 15 all_services_running = True while check_count > 0: check_count-= 1 all_services_running = True # check that all the deployed services have at least one replica up cmd = "docker service ls --format '{{json .}}'" out = run_command(cmd) if out is None: raise Exception("failed to validate services are running") for l in out.split("\n"): if len(l.strip()) == 0: continue try: js = json.loads(l) if re.search("^%s_" % re.escape(self.config.app_name), js["Name"]): replicas = re.search("(?P<c>[0-9]+)/(?P<t>[0-9]+)",js["Replicas"]) if replicas is not None: if int(replicas.group("c")) < int(replicas.group("t")): err_msg = "failed to deploy service %s (%s/%s)" % (js["Name"], replicas.group("c"), replicas.group("t")) # if this is last check interation, raise an error if check_count <= 0: raise Exception(err_msg) all_services_running = False logger.debug(err_msg) logger.debug("service %s success: %s", js["Name"], js["Replicas"]) else: logger.debug("skipping check for service %s", js["Name"]) except (ValueError,KeyError) as e: logger.warn("failed to parse docker service line: %s", l) if not all_services_running: logger.debug("one or more services pending, re-check in %s seconds", check_interval) time.sleep(check_interval) else: break logger.info("app services deployed") logger.debug("pausing for 15 seconds to give all services time to actually start") time.sleep(15) def init_db(self): """ need to initialize all replication sets for mongo db based on user config ssh to intended replica primary (replica 0) and initialize replica """ self.init_db_cfg() # pause for 15 seconds to ensure that replica set is ready logger.debug("pausing for 15 seconds to ensure replica is up") time.sleep(15) self.init_db_shards() def init_db_cfg(self): """ initialize cfg server replica set """ logger.info("initialize db config replica set") # find all 'db_cfg' service along with replica '0' info rs = {"configsvr": True, "members":[]} db_port = None replica_0_node = None replica_0_name = None for svc_name in self.config.services: svc = self.config.services[svc_name] if svc.service_type == "db_cfg": if "_id" not in rs: rs["_id"] = svc.replica if svc.replica_number is None or svc.port_number is None: raise Exception("service has invalid replica or port number: %s" % svc) host = self.config.nodes.get("%s" % svc.node, None) if host is None: raise Exception("failed to determine host for service: %s" % svc) member = { "_id": svc.replica_number, "host": "%s:%s" % (svc_name, svc.port_number) } if svc.replica_number == 0: replica_0_node = host replica_0_name = svc_name db_port = svc.port_number member["priority"] = 2 else: member["priority"] = 1 rs["members"].append(member) if replica_0_node is None or replica_0_name is None: raise Exception("failed to determine replica 0 db configsrv") cmd = 'docker exec -it ' cmd+= '$(docker ps -qf label=com.docker.swarm.service.name=%s_%s) ' % ( self.config.app_name, replica_0_name) cmd+= 'mongo localhost:%s --eval \'rs.initiate(%s)\'' % (db_port, json.dumps(rs)) logger.debug("initiate cfg replication set cmd: %s", cmd) # cfg server is statically pinned to node-1 if "%s" % replica_0_node["id"] == "1": # hard to parse return json since there's other non-json characters printed so we'll # just search for "ok" : 1 ret = run_command(cmd) if ret is None or not re.search("['\"]ok['\"] *: *1 *", ret): logger.warn("rs.initiate may not have completed successfully, cmd:%s\nresult:\n%s", cmd, ret) else: raise Exception("expected cfg server replica 0 to be on node-1, currently on %s" % ( replica_0_node)) def init_db_shards(self): """ initialize each shard replication set on replica-0 node owner """ logger.info("initialize db shards") # get all service type db_sh and organize into replication sets shards = {} # indexed by shared replica-name, contains node-0 (id and hostname) along # with 'rs' which is initiate dict for svc_name in self.config.services: svc = self.config.services[svc_name] if svc.service_type == "db_sh": if svc.replica_number is None or svc.port_number is None: raise Exception("service has invalid replica or port number: %s" % svc) if svc.replica not in shards: shards[svc.replica] = { "node-0": None, "svc_name": None, "svc_port": None, "rs": {"_id": svc.replica, "members":[]} } host = self.config.nodes.get("%s" % svc.node, None) if host is None: raise Exception("failed to determine host for service: %s" % svc) member = { "_id": svc.replica_number, "host": "%s:%s" % (svc_name, svc.port_number) } if svc.replica_number == 0: shards[svc.replica]["node-0"] = host shards[svc.replica]["svc_name"] = svc.name shards[svc.replica]["svc_port"] = svc.port_number member["priority"] = 2 else: member["priority"] = 1 shards[svc.replica]["rs"]["members"].append(member) for shard_name in shards: rs = shards[shard_name]["rs"] node_0 = shards[shard_name]["node-0"] if node_0 is None: raise Exception("failed to find replica 0 node for shard %s" % shard_name) cmd = 'docker exec -it ' cmd+= '$(docker ps -qf label=com.docker.swarm.service.name=%s_%s) ' % ( self.config.app_name, shards[shard_name]["svc_name"]) cmd+= 'mongo localhost:%s --eval \'rs.initiate(%s)\'' % (shards[shard_name]["svc_port"], json.dumps(rs)) logger.debug("command on %s: %s", node_0["id"], cmd) if "%s" % node_0["id"] == "1": # command is executed on local host ret = run_command(cmd) if ret is None or not re.search("['\"]ok['\"] *: *1 *", ret): err_msg="rs.initiate may not have completed successfully for shard %s"%shard_name err_msg+= ", node (id:%s, hostname:%s)" % (node_0["id"], node_0["hostname"]) err_msg+= "\ncmd: %s\nresult: %s" % (cmd, ret) logger.warn(err_msg) else: c = self.get_connection(node_0["hostname"]) ret = c.cmd(cmd) if ret != "prompt" or not re.search("['\"]ok['\"] *: *1 *", c.output): err_msg="rs.initiate may not have completed successfully for shard %s"%shard_name err_msg+= ", (node id: %s, hostname: %s)" % (node_0["id"], node_0["hostname"]) err_msg+= "\ncmd: %s\nresult: %s" % (cmd, "\n".join(c.output.split("\n")[:-1])) logger.warn(err_msg) # pause for 15 seconds to ensure that replica set is ready logger.debug("pausing for 15 seconds to ensure all replica is up") time.sleep(15) # add each shard to mongo-router - note, there's an instance of mongos with service name # 'db' on all nodes in the cluster so this command is always locally executed for shard_name in shards: svc_name = shards[shard_name]["svc_name"] svc_port = shards[shard_name]["svc_port"] cmd = 'docker exec -it ' cmd+= '$(docker ps -qf label=com.docker.swarm.service.name=%s_db) '%self.config.app_name cmd+= 'mongo localhost:%s --eval \'sh.addShard("%s/%s:%s")\'' % ( self.config.mongos_port, shard_name, svc_name, svc_port) ret = run_command(cmd) if ret is None or not re.search("['\"]ok['\"] *: *1 *", ret): err_msg="sh.addShard may not have completed successfully for shard %s"%shard_name err_msg+= "\ncmd: %s\nresult: %s" % (cmd, ret) logger.warn(err_msg) class DockerNode(object): def __init__(self, **kwargs): self.labels = {} self.role = None self.addr = None self.node_id = kwargs.get("ID", None) self.hostname = kwargs.get("Hostname", None) self.availability = kwargs.get("Availability", None) self.status = kwargs.get("Status", None) if self.node_id is not None: inspect = run_command("docker node inspect %s --format '{{json .}}'" % self.node_id) if inspect is not None: try: logger.debug("inspect: %s", inspect) js = json.loads(inspect) if "Status" in js: if "Addr" in js["Status"]: self.addr = js["Status"]["Addr"] if "State" in js["Status"]: self.status = js["Status"]["State"] if "Spec" in js: if "Availability" in js["Spec"]: self.availability = js["Spec"]["Availability"] if "Role" in js["Spec"]: self.role = js["Spec"]["Role"] if "Labels" in js["Spec"]: if type(js["Spec"]["Labels"]) is not dict: logger.debug("invalid Labels for %s: %s", self.node_id, js["Spec"]) else: self.labels = js["Spec"]["Labels"] except ValueError as e: logger.debug("failed to decode inspect(%s): %s", self.node_id, inspect) def __repr__(self): return "id:%s, role:%s, addr:%s, status:%s, avail:%s, labels:%s" % ( self.node_id, self.role, self.addr, self.status, self.availability, self.labels )

[ "agossett@cisco.com" ]

agossett@cisco.com

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/hackerRank/algorithms/DiagonalDifference/diagonal_difference.py

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[]

no_license

kruart/coding_challenges

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refs/heads/master

2021-06-16T08:51:21.815334

2019-11-07T08:39:13

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py

# https://www.hackerrank.com/challenges/diagonal-difference/problem def diagonal_difference(arr): return abs(sum([arr[i][i] - arr[i][len(arr)-i-1] for i in range(len(arr))])) def main(): matrix1 = [ [1, 2, 3], [4, 5, 6], [9, 8, 9] ] matrix2 = [ [11, 2, 4], [4, 5, 6], [10, 8, -12] ] print(diagonal_difference(matrix1)) # 15 - 17 = 2 print(diagonal_difference(matrix2)) # 4 - 19 = 15 if __name__ == '__main__': main()

[ "weoz@ukr.net" ]

weoz@ukr.net

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b04eb4cec627b40c9cf970d25206d41367125041

/learn-flask/flask_vs_wsgi/wsgi_vs_flask/wsgi/why_not_wsgi.py

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[]

no_license

zhangkexia/web-learning

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72ee6174623f72a9d9eb1623fdf2620122dd72ef

refs/heads/master

2023-06-24T20:27:45.981714

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def application(environ, start_response): method = environ['REQUEST_METHOD'] path = environ['PATH_INFO'] if method == 'GET' and path == '/': return handle_home(environ, start_response) if method == 'POST' and path == '/signin': return handle_signin(environ, start_response) if .... #so many functions to handle different urls of different request types

[ "yueyue_freedom@163.cm" ]

yueyue_freedom@163.cm

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/easyautoml/utils.py

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permissive

almandsky/easyautoml

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2020-03-27T15:24:07.845306

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from easyautoml.ftutils import get_train_data, get_test_data from easyautoml.tpotutils import tpot_train, tpot_score # GLOBAL CONFIG TPOT_MAX_TIME_MINS = 1 TPOT_MAX_EVAL_TIME_MINS = 0.04 TPOT_POPULATION_SIZE = 40 N_JOBS=-1 def tpot_with_ft( project, train_file_name, test_file_name, submit_file, export_file, prediction_target, prediction_key, prediction_type, variable_types={}, scoring_func=None, predictProba=False, predictInt=False, getdummies=False, drop_train_columns=None, drop_score_columns=None): X, y = get_train_data( project=project, train_file=train_file_name, prediction_key=prediction_key, prediction_target=prediction_target, variable_types=variable_types, drop_columns=drop_train_columns) tpot_instance = tpot_train( project=project, X=X, y=y, prediction_type=prediction_type, export_file=export_file, scoring_func=scoring_func, max_time_mins=TPOT_MAX_TIME_MINS, n_jobs=N_JOBS, population_size=TPOT_POPULATION_SIZE) X_test, index_column = get_test_data( project=project, testfile=test_file_name, prediction_key=prediction_key, prediction_target=prediction_target, variable_types=variable_types, drop_columns=drop_score_columns) tpot_score( tpot=tpot_instance, project=project, X_test=X_test, index_column = index_column, prediction_target=prediction_target, prediction_key=prediction_key, submit_file=submit_file, predictProba=predictProba, predictInt=predictInt, getdummies=getdummies)

[ "sky.chen@salesforce.com" ]

sky.chen@salesforce.com

ae99363612df9095c5b8194a8ad42254c93b94c0

981ead90e27f974a0b567a543df783c0677933bf

/Utilities/util.py

9e8fce17a4a37344bc9437fde9bd3c6c8f7bbf5b

[]

no_license

TachunLin/pytestAllure

20360979c3921295cc0890ccbca5cf8116811b02

5edf7179b4beee4ea8d2ff10ebff9d0f3733f6df

refs/heads/master

2020-03-17T06:47:42.604130

2018-05-19T13:02:16

133,369,739

0

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UTF-8

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py

import time import traceback import random, string import Utilities.custom_logger as cl import logging from traceback import print_stack import datetime import os import pytest import allure from allure.constants import AttachmentType from helpers import ensure_dir # from Utilities.custom_logger import customLogger # import Utilities.custom_logger as cl # log = cl.customLogger(logging.INFO) class Util(object): logging.getLogger().setLevel(logging.INFO) def sleep(self, sec, info=""): """ Put the program to wait for the specified amount of time """ if info is not None: logging.info("Wait :: '" + str(sec) + "' seconds for " + info) try: time.sleep(sec) except InterruptedError: traceback.print_stack() def getAlphaNumeric(self, length, type='letters'): """ Get random string of characters Parameters: length: Length of string, number of characters string should have type: Type of characters string should have. Default is letters Provide lower/upper/digits for different types """ alpha_num = '' if type == 'lower': case = string.ascii_lowercase elif type == 'upper': case = string.ascii_uppercase elif type == 'digits': case = string.digits elif type == 'mix': case = string.ascii_letters + string.digits else: case = string.ascii_letters return alpha_num.join(random.choice(case) for i in range(length)) def getUniqueName(self, charCount=10): """ Get a unique name """ return self.getAlphaNumeric(charCount, 'lower') def getUniqueNameList(self, listSize=5, itemLength=None): """ Get a list of valid email ids Parameters: listSize: Number of names. Default is 5 names in a list itemLength: It should be a list containing number of items equal to the listSize This determines the length of the each item in the list -> [1, 2, 3, 4, 5] """ nameList = [] for i in range(0, listSize): nameList.append(self.getUniqueName(itemLength[i])) return nameList def verifyTextContains(self, actualText, expectedText): """ Verify actual text contains expected text string Parameters: expectedList: Expected Text actualList: Actual Text """ logging.info("Actual Text From Application Web UI --> :: " + actualText) logging.info("Expected Text From Application Web UI --> :: " + expectedText) if expectedText.lower() in actualText.lower(): logging.info("### VERIFICATION CONTAINS !!!") return True else: logging.info("### VERIFICATION DOES NOT CONTAINS !!!") return False def verifyTextMatch(self, actualText, expectedText): """ Verify text match Parameters: expectedList: Expected Text actualList: Actual Text """ logging.info("Actual Text From Application Web UI --> :: " + actualText) logging.info("Expected Text From Application Web UI --> :: " + expectedText) if actualText.lower() == expectedText.lower(): logging.info("### VERIFICATION MATCHED !!!") return True else: logging.info("### VERIFICATION DOES NOT MATCHED !!!") return False def verifyListMatch(self, expectedList, actualList): """ Verify two list matches Parameters: expectedList: Expected List actualList: Actual List """ return set(expectedList) == set(actualList) def verifyListContains(self, expectedList, actualList): """ Verify actual list contains elements of expected list Parameters: expectedList: Expected List actualList: Actual List """ length = len(expectedList) for i in range(0, length): if expectedList[i] not in actualList: return False else: return True def verifyCheckPoint(self, driver, actual, expectation, request, log): if (actual == expectation): with pytest.allure.step('Pass~ Actual result: {0} match expectation: {1}'.format(actual, expectation)): # cl.customLogger(logging.INFO).info('Pass~ Actual result: {0} match expectation: {1}'.format(actual, expectation)) log.info('Pass~ Actual result: {0} match expectation: {1}'.format(actual, expectation)) # logging.info('Pass~ Actual result: {0} match expectation: {1}'.format(actual, expectation)) else: with pytest.allure.step('Mismatched!! Actual result: {0} <-> expectation: {1}'.format(actual, expectation)): allure.attach('Assertion error screenshot', open(Util.saveAssertScreenShot(Util(), driver, request.node.name), 'rb').read(), type=AttachmentType.PNG) # cl.customLogger(logging.INFO).error('Mismatched!! Actual result: {0} <-> expectation: {1}'.format(actual, expectation)) log.error('Mismatched!! Actual result: {0} <-> expectation: {1}'.format(actual, expectation)) assert 0, 'Mismatched!! Actual result: {0} <-> expectation: {1}'.format(actual, expectation) def saveExeScreenShot(self, driver, testcaseName): current_day = (datetime.datetime.now().strftime("%Y_%m_%d_%H_%S")) ensure_dir("Screenshot") result_dir = ensure_dir(os.path.join("Screenshot", current_day)) # result_dir = os.path.join(os.path.dirname(__file__), "Screenshot", current_day) # print(result_dir) # ensure_dir(result_dir) result_dir_test_run = result_dir Execution_screen_shot_dir = os.path.join(result_dir_test_run, "Execution") ensure_dir(Execution_screen_shot_dir) # print(Execution_screen_shot_dir) ExeImagePath = os.path.join(Execution_screen_shot_dir, current_day + '_' + testcaseName + ".png") driver.save_screenshot(ExeImagePath) # print(ExeImagePath) return ExeImagePath def saveAssertScreenShot(self, driver, testcaseName): current_day = (datetime.datetime.now().strftime("%Y_%m_%d_%H_%S")) ensure_dir("Screenshot") result_dir = ensure_dir(os.path.join("Screenshot", current_day)) # result_dir = os.path.join(os.path.dirname(__file__), "Screenshot", current_day) # print(result_dir) # ensure_dir(result_dir) result_dir_test_run = result_dir Execution_screen_shot_dir = os.path.join(result_dir_test_run, "Assertion") ensure_dir(Execution_screen_shot_dir) # print(Execution_screen_shot_dir) ExeImagePath = os.path.join(Execution_screen_shot_dir, current_day + '_' + testcaseName + ".png") driver.save_screenshot(ExeImagePath) # print(ExeImagePath) return ExeImagePath

[ "imdagcool@gmail.com" ]

imdagcool@gmail.com

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[ "Apache-2.0", "MIT" ]

permissive

Dongs7/drawguess

e1bba9f719311ea7636bd1ce1d40d8e5cde449e6

9643a16eaf35067d64196eac981901e80f11ed1c

refs/heads/master

2020-09-17T08:15:24.313909

2016-08-31T12:32:25

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null

UTF-8

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false

4,067

gypi

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[ "vingosheng@gmail.com" ]

vingosheng@gmail.com