index int64 0 1,000k | blob_id stringlengths 40 40 | code stringlengths 7 10.4M |
|---|---|---|
987,200 | b71441c671b5afc9207a3d47d5845ea90f5a66f8 | # -*- coding: utf-8 -*-
# Generated by Django 1.10.7 on 2017-08-02 08:34
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('fish', '0005_fishdetection_aquarium_id'),
]
operations = [
migrations.AddFi... |
987,201 | 133732564f8f125343a897eebfadbfbaa39b3898 | from PIL import Image
im = Image.open('font.png', 'r')
pix_val = list(im.getdata())
pix_val_flat = [x for sets in pix_val for x in sets]
w, h = im.size
for i in range(len(pix_val)):
pix_val[i] = int(round(sum(pix_val[i]) / float(len(pix_val[i]))))
import numpy as np
pix_val = np.array(pix_val)
pix_val = pi... |
987,202 | 6d590643753538b9ca7fad9162465a14c216d00d | #! /usr/bin/python3.5
import os
import re
from config import token
import telebot
from sql import Db
from system_func import get_ip
from system_func import is_admin
from system_func import list_to_str
bot = telebot.TeleBot(token)
db_dir = os.path.dirname(os.path.abspath(__file__)) + "/words.db"
def get_cmd_param(me... |
987,203 | e44a78c4ed824700a582bee0f1567e5ae8bef8ee | import numpy as np
import pandas as pd
from scipy import stats
def sigmoid(x):
return 1 / (1 + np.exp(-x))
def rvec(x):
return np.atleast_2d(x)
def cvec(x):
return rvec(x).T
def to_3d(mat):
return np.atleast_3d(mat).transpose(2,0,1)
def srho(x,y):
return stats.spearmanr(x,y)[0]
"""
VECTORIZED ... |
987,204 | ce78dd874ffd82fd2a10a06a214eb9b3005dd1f8 | '''
A test simulation involving the SEIR flu model in isolation.
'''
from pram.data import GroupSizeProbe, ProbeMsgMode
from pram.entity import Group, Site
from pram.rule import SEIRFluRule
from pram.sim import Simulation
rand_seed = 1928
probe_grp_size_flu = GroupSizeProbe.by_attr('flu', SEIRFluRule.ATTR, SE... |
987,205 | ef5d894c5edbe85c7961b9537b6f56b2eb9ac831 | from .graph_node import GraphNode
from .graph import Graph
from .square_grid import SquareGrid, Point
__all__ = GraphNode, Graph, SquareGrid, Point
|
987,206 | dd7d8a18f8c1c27db24bb92ba7067ab01a50b452 | """
This script converts CEU.BEAM.txt (which is in BEAM format: first line is 0 or 1 if subject is case or control,
then one line per SNP and 0 if homozygous for the major allele, 1 if heterozygous, 2 if homozygous for the minor allele).
The output is two matrices: cases and controls
and a description of the implanted... |
987,207 | 35d48342d315269a47d0facc0ec01dd8764a0cfd | import os
from unittest import TestCase
from musicscore.musicstream.streamvoice import SimpleFormat
from musicscore.musictree.treeinstruments import Violin, Cello, Viola
from musicscore.musictree.treescoretimewise import TreeScoreTimewise
from tests.score_templates.xml_test_score import TestScore
path = str(os.path.a... |
987,208 | 12d65c2a577a3852b315a595a95f0b8170988c01 | #!/usr/bin/env python
#-*- coding:utf-8 -*-
import gtk
import os.path
import manager
import db
# import shell
# import terminal
# import filemanager
class Null():
"""NULL
"""
def __init__(self, builder):
"""
Arguments:
- `builder`:
"""
self.builder = builder
... |
987,209 | 940b25cff6bc8c06c89e070a3b87d20c01ef3ed9 | # -*- coding: utf-8 -*-
"""
Created on Sat Apr 13 14:56:37 2013
@author: daniel
"""
#programa: subcadena_1.py
#ejercicio 199 y 200
#data input
cadena = raw_input('Escribe una cadena: ')
i = int(raw_input('Numero A: '))
j = int(raw_input('Numero B: '))
flag = 0
subcadena = ''
if i < 0:
i = 0
if j > len(cadena):... |
987,210 | 5c1e1981e194ba0c252608e9fc356c0dda9d9c61 | from django.contrib.auth.models import AbstractUser
from django.core.urlresolvers import reverse
from django.db import models
from django.utils.encoding import python_2_unicode_compatible
from django.utils.translation import ugettext_lazy as _
from model_utils import Choices
@python_2_unicode_compatible
class User(A... |
987,211 | 70d6a3345edbfe0d8495853d8d5dd1d0173eb64e | # -*- coding: utf-8 -*-
"""
ECoG Channel Localization (Joseph Tseung)
Trying SimpleITK
Created on Sun Nov 11 16:53:26 2018
@author: josep
"""
# from tkinter import Tk
# from tkinter.filedialog import askopenfilename
# from skimage import measure
import SimpleITK as sitk
# from matplotlib import pyplot ... |
987,212 | aa60f7417e51b9ffd722f6815a0811ea69e3a4e4 | #6
import functools
lst=list(map(int,input("Enter the list: ").split(" ")))
print ("The sum of the list elements is : ",end="")
print (functools.reduce(lambda a,b : a+b,lst)) |
987,213 | d86d20fee2a59917b6cd98a225bb909c18f0b93b | from datetime import datetime
user_data = []
class User:
""" model class for users """
def __init__(self, **kwargs):
self._id = len(user_data)+1
self.firstname = kwargs["firstname"]
self.lastname = kwargs["lastname"]
self.othernames = kwargs["othernames"]
self.email = ... |
987,214 | b09056bec6639ee7c5d658ff38be15e193511b43 | import torch
import torch.nn as nn
import torch.optim as optim
import matplotlib.pyplot as plt
import seaborn as sns
sns.set()
torch.manual_seed(seed=0)
def logistic_regression(X, y, W_init, lr, max_nsteps):
N, D = X.shape
# Assign bias values
X_ = torch.ones(N, D+1)
X_[:, 1:] = torch.tensor(X)
... |
987,215 | 6114967a43296defe3dd21061d1443e964c016cd | #!/usr/bin/env python
import uvicorn
from fastapi import FastAPI, WebSocket
from src.servers.config import host, port
from src.servers.utils import random_greeting
app = FastAPI()
@app.websocket("/greeting")
async def greeting(websocket: WebSocket):
await websocket.accept()
while True:
try:
... |
987,216 | 7b92d679b1c637d6e4515d754c7aed9f481faacf | T = int(input())
for q in range(T):
N, M = map(int, input().split())
arr = [input() for _ in range(N)]
result =[]
tmp_1 = 0
tmp_2 = 0
num = {'0001101': 0, '0011001': 1,'0010011': 2,'0111101': 3,'0100011': 4,'0110001': 5,'0101111': 6,'0111011': 7,'0110111': 8,'0001011': 9}
for i in range(N):... |
987,217 | 6397c816cb14f76445ae4618bb2632867d235441 | import logging
import re
from typing import Optional
from pydantic import BaseModel
from opennem.core.unit_single import facility_unit_numbers_are_single
logger = logging.getLogger(__name__)
__is_number = re.compile(r"^\d+$")
__is_single_number = re.compile(r"^\d$")
__is_unit_alias = re.compile(r"([A-Z|a-z]{1,6})... |
987,218 | c2b377558df8f5b7321ef91b295dbc745832b18e | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# @File : test_pytest.py
# @Author: yubo
# @Date : 2019/12/6
# @Desc :
import pytest
variable_module = 0
@pytest.fixture(scope='module')
def variable_to_module():
global variable_module
variable_module += 1
return variable_module
def test_variable_modu... |
987,219 | 71a7389408a5620d24c9473da17b97ae1cbc0bd9 | from imutils.video import VideoStream
import face_recognition
import argparse
import imutils
import pickle
import time
import cv2
#from live_cam import live
cv2.namedWindow("Image",cv2.WINDOW_NORMAL)
ap = argparse.ArgumentParser()
ap.add_argument("-e", "--encodings", required=True,
help="path to serialized db of faci... |
987,220 | 8ef04a64fa9de57295da32e46b8eac88129e43d2 | from time import sleep
import os
while(1):
sleep(1)
os.system("dmesg > LogFirewall") |
987,221 | aa5f0e999c5212472388d13fbf9f7aaca2a2fb3f | #! /usr/bin/env python
from ROOT import *
import sys
import script_utils as script_utils
sys.path.append("/home/irfulx204/mnt/tmain/Desktop/Run308_Analyse_ERA/Scripts_ERA/")
import create_extrapolated_bckg as create_bckg
import subprocess as subp
import BDT_utils as BDT_ut
import BDT_file_handler as BDT_fh
import PyR... |
987,222 | 76e7c03215f969d8635c42b931451a756f53f6a8 | # coding=utf8
import pytest
# coding=utf8
import pytest
#如果使用autouse=True，默认所有用例都是用此装饰器，function级别的。但是如果需要yield的返回值，则需要将login方法名传入用例作为参数
@pytest.fixture(params=["tom","jerry"])
def login(request):
# 相当于setup
print("登录操作")
# yield相当于return，也就是teardown后，return出参数
# yield ["1111","2222"]
username= r... |
987,223 | fcc1953db017bafd949161c1decf4f25a17e0fa0 | #python 3.7.0 64-bit
#py -3 -m pip install numpy==1.19.3
#py -3 -m pip install spacy==2.1.0
#py -3 -m pip install neuralcoref==4.0
#py -3 -m spacy download en_core_web_sm
#py -3 -m spacy download en_core_web_lg
import sys
import spacy
import neuralcoref
import re
import random
def get_aux_bin(sent):
s... |
987,224 | a9997307f82838f57ee90bbc6ad4d5bab13cc31b | import time
start = time.time()
def compute(n):
phi = [i for i in range(n + 2)]
for p in range(2, n + 1):
if phi[p] == p:
phi[p] = p - 1
for i in range(2 * p, n + 1, p):
phi[i] = (phi[i] // p) * (p - 1)
for i in range(2, n + 1):
if sorted(list(str(i))... |
987,225 | f4dac99bd494a9f202b7da1ed265f52a817775c8 | # -*- coding: utf-8 -*-
"""
Created on Thu Sep 1 00:26:04 2016
@author: hy
"""
import tensorflow as tf
input1=tf.constant(3.0)
input2=tf.constant(2.0)
input3=tf.constant(5.0)
intermed=tf.add(input2,input3)
mul=tf.mul(input1,intermed)
with tf.Session() as sess:
result=sess.run([mul,intermed])
print result |
987,226 | 525374d02696c5f78c771fdcc6685c826023fd21 |
# 输入函数：input
# num1 = input("num >>>")
# num2 = input("num >>>")
# print(int(num1)+int(num2))
# 输出函数：print
# print("yuan",end="")
# print("alvin")
print("张三","李四",sep=":::")
|
987,227 | 50238be2d274446ab842353ed93558372911ea32 | import numpy as np
import torch
class DataNormalizer(object):
def __init__(self, dataloader):
self.dataloader = dataloader
self._range_normalizer(magnitude_margin=0.8, IF_margin=1.0)
print("s_a:", self.s_a )
print("s_b:", self.s_b )
print("p_a:", self.p_a)
print(... |
987,228 | efbe83307a35e9e2623d46766c86605323d3026e | from bson import ObjectId
from bson.errors import InvalidId
def id_generator(doctype):
def id_gen(oid):
if doctype is None or not oid:
return None
try:
data = doctype.datatype.one({'_id':ObjectId(oid)})
if data:
return doctype(data)
re... |
987,229 | f3e0a17dda7c95527940d1301cd55279d816730c | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# vim: ai ts=4 sts=4 et sw=4
# Author: Sergio Araujo
# Last Change: 2018 mai 24 17:44
# Created: qui 26 jan 2017 07:22:20 BRT
# email: <voyeg3r ✉ gmail.com>
# Github: https://github.com/voyeg3r
# twitter: @voyeg3r
# References:
# the first ve... |
987,230 | 698a0fc43f2dfa304ef5b4443bacc6ae2ab45474 | import os
import csv
zFile = 'C:\\Users\\viresh.patel\\Documents\\Excel Docs\\global_superstore.csv'
zInfo = os.stat(zFile)
print(zInfo)
print(zInfo.st_atime)
print(zInfo.st_ctime)
print(zInfo.st_dev)
# print(zInfo.st_file_attributes)
print(zInfo.st_gid)
print(zInfo.st_ino)
print(zInfo.st_mode)
print(zInfo.st_mtime)... |
987,231 | 317a112d47850fe2140b293ecca2a97bb3ca4f24 | import graphene
from graphene_django import DjangoObjectType
from ..apps.data.models import Project
class Projects(DjangoObjectType):
class Meta:
model = Project
class ProjectQuery(graphene.ObjectType):
get_all_projects = graphene.List(Projects)
get_project_by_id = graphene.Field(Projects, i... |
987,232 | 5dc3308cbc0c24fd4d562e679319a760bd5eba85 | import os
import gdal
from glob import glob
dir_with_csvs = r"C:/anhHoangKTTV/PythonScripts_DFS0/Project_NTB/"
os.chdir(dir_with_csvs)
def find_csv_filenames(path_to_dir, suffix=".csv"):
relativePath = path_to_dir + "*.csv"
print(relativePath)
# filenames = glob.glob(relativePath)
filenames = [os.path... |
987,233 | 62e84c17900afdaa8ee39f5ec3d8536d8c5b02a6 | # -*- coding: utf-8 -*-
"""
Created on Fri Nov 13 22:24:24 2020
@author: T SRIDHAR
"""
from TOPSIS-Divij-101816056 import topsis |
987,234 | e3d8d27d292ed0a9b6aa04ecf65eacb5dd3aedd8 | from flask import Blueprint
sample = Blueprint('sample', __name__)
#profile = Blueprint('profile', __name__,
# template_folder='templates',
# static_folder='static')
@sample.route('/hello')
def hello():
# Do some stuff
return "Hello , It's a sample page" |
987,235 | 38a36d19f136d68b30d47f4090a3e481649677e5 | from base.activity import Activity
from base.titlelayout import TitleLayout
class WebViewActivity(Activity):
def __init__(self):
Activity.__init__(self, self.__class__.__name__)
self.scrollTest()
def scrollTest(self):
title = TitleLayout()
self.swipeUp(n=5)
title.finis... |
987,236 | 0eda77fc4dfed7ee40ac2df8599cb6f391dde76f | #!/usr/bin/python
import jinja2, json, re
from functools import reduce
import subprocess
import nanodurationpy as durationpy
import csv
import time
import datetime
import os
import shutil
import glob
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('--wasmoutdir', help='full path of dir containi... |
987,237 | 3260da175b41644aeaf00c743ae946ea0789e0b5 | from KMCLib import *
from .constant import *
from .rate import *
# rate_constant set here refers to prefactor
p_des = { 'N2O':{} }
p_des['N2O']['top'] = [KMCProcess(
coordinates = [Origin],
elements_before = ['top'],
elements_after ... |
987,238 | f3a18dadc546cfbd3d1c0be66d55e1ed707ff860 | #! /usr/bin/env python
import textile
import sys, os, shutil, random
from optparse import OptionParser
from BeautifulSoup import BeautifulSoup
from Cheetah.Template import Template
from xml.sax.saxutils import escape
VERSION = '0.1.1'
HOME = '/home/curtis/working/reptile'
TEMPLATE = HOME + '/templates/reptile.tpl'
# ... |
987,239 | 6e62a834acc45b0c7e8e95beb1c45b81c7d555a7 | import csv
file_to_load = "Resources/budget_data2.csv"
total_months = 0
total_revenue = 0
prev_revenue = 0
revenue_change = 0
max_i = ["", 0]
min_d = ["", 9999999999999999999999]
revenue_changes = []
with open(file_to_load) as revenue_data:
reader = csv.DictReader(revenue_data)
for row in reader:
... |
987,240 | 3e141e01eb00927d090c4d10195506577f338afd |
from django.shortcuts import render
from django.http import HttpResponse, HttpResponseRedirect
from django.conf import settings
from rest_framework import viewsets
from rest_framework.response import Response
import datetime
from .forms import DoorCombinationForm
from .models import *
from django.contrib.auth.decorato... |
987,241 | c83eaa7ba3ab76f1d31f97e449c5f5d3232379c7 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Oct 9 20:11:21 2017
@author: ERIC
"""
#import the best module ever
from twython import Twython
#config file is in same directory
from TWITTER_CONFIG import APP_KEY, APP_SECRET, OAUTH_TOKEN, OAUTH_TOKEN_SECRET
#import keys from config file
twit... |
987,242 | 839d14a11451b16cfde7628eb3a9454a52279388 | from suds.client import Client
from nova import exception
from nova import db
import logging
logging.getLogger('suds').setLevel(logging.INFO)
def update_for_run_instance(service_url, region_name, server_port1, server_port2, dpid1, dpid2):
# check region name
client = Client(service_url + "?wsdl")
client... |
987,243 | 2f267c35e3b984bba50ce62bb69770324fe018c8 | class TreeNode:
def __init__(self, val=0, left=None, right=None):
self.val = val
self.left = left
self.right = right
class Solution:
def delete_dupliate_list_elements(self, dlist):
delete_indices = set()
i = 0
while i < len(dlist) - 1:
if dlist[i].val... |
987,244 | e9d05b9902f59e61461843037094d72626dfe972 | #!/usr/bin/env python3
'''Extract gene nucleotide sequence in FASTA format from genbank records'''
import argparse
import pathlib
import Bio.SeqIO
FASTA_DESC_TEMPL = '>%s_%s %s'
def get_arguments():
parser = argparse.ArgumentParser()
parser.add_argument('--input_fp', required=True, type=pathlib.Path,
... |
987,245 | 5ca8f1cc7a273c07e0143d63b7e414845153ad2b | TOKEN = '1772291199:AAGqhnEVGIpLHDV3xe_u1BVqgAJYn5IBlX4' |
987,246 | d4af0066d6125b62f9b0de6d93f3a0c709566f2d | import matplotlib as matplt
matplt.use('Agg')
import os, sys
sys.path.insert(0, os.path.abspath('..'))
sys.path.insert(0, os.path.abspath('.'))
sys.path.insert(0, os.path.abspath('../easy_reg'))
import tools.module_parameters as pars
from abc import ABCMeta, abstractmethod
from easyreg.piplines import run_one_task
f... |
987,247 | 8e625caa2db8fa2436e03422d9a4206761a8720f | # Copyright 2015-2016 NEC Corporation. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requ... |
987,248 | 3d83ad15a32a573bbc3e3f8f23a51544d8be923f | import json
numbers = [2, 3, 4, 5, 6, 7, 11, 12]
filename = 'numbers.json'
with open(filename, 'w') as f_obj:
json.dump(numbers, f_obj)
with open(filename) as f_obj:
numbers = json.load(f_obj)
print numbers
|
987,249 | 90e94392faf1c9a16d856e335c23908f25899223 | # Machine Learning Online Class
# Exercise 7 | Principle Component Analysis and K-Means Clustering
from scipy.io import loadmat
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
from featureNormalize import featureNormalize
from pca import pca
from projectData import *
from r... |
987,250 | 1064b303a0273a0647c11e770eb64e1a9039367d | import json
from abc import ABC, abstractmethod
import numpy
import talib
import websockets
RSI_PERIOD = 14
RSI_OVERBOUGHT = 70
RSI_OVERSOLD = 30
class Watcher(ABC):
"""
Responsible for watching symbol candles and deciding when to order.
"""
def __init__(self, symbol):
self.SYMBOL = symbol ... |
987,251 | ec80412850dbe8365a6568fa9122160678586b4c | from Query import Query
import re
class ParserQuery():
def parseQRY(chemin):
"""
Fonction permettant de parser les fichers QRY (requêtes avec leurs identifiants et leur texte)
"""
file = open(chemin, 'r')
res = {}
currentI = None
currentBalise = None ... |
987,252 | a3eb3dc6e6a3a2f215b760cd0cdd9014b1a192eb | from genmod.commands import filter_command
from click.testing import CliRunner
ANNOTATED_VCF_FILE = "tests/fixtures/test_vcf_annotated.vcf"
from genmod import logger
from genmod.log import init_log
init_log(logger, loglevel="INFO")
def test_genmod_filter():
"""docstring for test_genmod_annotate_models"""
ru... |
987,253 | 5370676b064e69e7eff1df1c15d04343c15f0650 | # Generated by Django 2.2.7 on 2019-12-25 15:13
import datetime
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('courses', '0004_auto_20191129_1720'),
]
operations = [
migrations.AlterField(
model_name='course',
n... |
987,254 | dc54c1b0aadbfecdfa743fd98e1ba0c0133fa669 | # Generated by Django 3.2 on 2021-04-12 21:53
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("menu", "0005_auto_20210412_2137"),
]
operations = [
migrations.AlterField(
model_name="lunch",
name="details",
... |
987,255 | 385aee105ef70b0597d7b7110dd3fece93ab0f46 | from string import ascii_lowercase
import numpy as np
from ref_optimize import ref_optimize
def read_train(filename):
#function to read training data
mapping = list(enumerate(ascii_lowercase))
mapping = { i[1]:i[0] for i in mapping }
with open(filename, "r") as f:
raw_data = f.read()
raw_data = raw_data.split("... |
987,256 | d77180854792ffd31298ff5b61b669aa721a6a30 | import ROOT, sys, os
import numpy as np
import time
start_time = time.time()
opts = [opt for opt in sys.argv[1:] if opt.startswith("-")]
outputTitle = "h_studyETauChannel"
isData = 0
if "-b" in opts:
isData = 0
if "-dj" in opts:
isData = 1
isJetHTSample = 1
isSingleElectronSample = 0
if "de" in o... |
987,257 | ffe911b4598a8c26c2df5f53aff853789b19ceb9 | import sys
n, r = map(int, sys.stdin.readline().split())
r = min(n-r, r)
res = 1
for i in range(1, r + 1):
res *= ((n - i + 1) / (r - i + 1))
print(int(res))
|
987,258 | f9169f47597c351594c66321ed40e2010035fd6e | import torch
import os
from torch.utils.tensorboard import SummaryWriter
class Logger(object):
def __init__(self, log_dir, comment=''):
self.writer = SummaryWriter(log_dir=log_dir, comment=comment)
self.imgs_dict = {}
def scalar_summary(self, tag, value, step):
self.wr... |
987,259 | ef7e100bb1425d3aaf817141b4ca2f4b896070b6 | """learn_django_pro_V_2 URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/2.2/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: path('', views.home, name='home'... |
987,260 | e2c01fce7ad1afb4e864ea50502cacadaa223dd4 | import re
# 處理繁體中文
import jieba2 as jieba
import jieba2.analyse
import sqlite3
import pickle
from collections import defaultdict
from sklearn.feature_extraction import DictVectorizer
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.feature_extraction.text import TfidfTransformer
from sklearn.sv... |
987,261 | 72548887be201de4d8b279dcb1fff83d6ab89d33 | """ crear una fucnion que muestre el nombre y el apellido """
""" def nom (name, apellido):
print("Hola", name,apellido)
name = input("Digite su Nombre: ")
ape = input("Digite su Apellido: ")
nom(name, ape)
"""
"""
def f1():
x=100
print(x)
x=+1
f1()
"""
"""
EJERCICIOS DE CLASE
1. Solicitar al ... |
987,262 | d558dbaf4e20def09e7eeeae8fa522752d192bfd | import logging
import tornado.ioloop
import tornado.web
import tornado.websocket
SERVER_HOST = '127.0.0.1'
SERVER_PORT = 8646
logging.basicConfig(level=logging.WARNING)
class EchoWebSocket(tornado.websocket.WebSocketHandler):
def on_message(self, message):
self.write_message(message, binary=isinstance... |
987,263 | 26ea434eb570d3a9ec89ba2558116a873f497617 | def period(num, div):
assert(div > num)
idx = 0
nums = {}
while num != 0:
num = num % div
while num < div and num != 0:
num = num * 10
digit = num // div
if nums.get(num) is not None:
return idx - nums[num]
nums[num] = idx
... |
987,264 | 2d3fd113a5f2e91c8b10a1e0218d472bf1a05741 | # Generated by Django 3.0.3 on 2020-07-21 00:54
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('users', '0004_auto_20200719_1404'),
]
operations = [
migrations.AddField(
... |
987,265 | c25f0e08f235f4f00ac134b44fa6b50849f1e5d2 | # -*- coding: utf-8 -*-
from __future__ import absolute_import, unicode_literals
import logging
import os
import jpype
from future.utils import iteritems
from pyathenajdbc import (
ATHENA_CONNECTION_STRING,
ATHENA_DRIVER_CLASS_NAME,
ATHENA_JAR,
LOG4J_PROPERTIES,
)
from pyathenajdbc.converter import J... |
987,266 | 907c242c055d28432945418379fff46392a3d062 | # Validate BST: Implement a function to check if a binary tree is a binary search tree.
from typing import Tuple
# Option 1 - do in-order traversal and copy values to array then check that array is sorted
class Node:
def __init__(self, val: int) -> None:
self.left = None
self.right = None
... |
987,267 | d413c43d396dd9877352570a08eab4454b999bec | nilai = [{'nim' : 'A01', 'nama' : 'Agustina', 'mid' : 50, 'uas' : 80},
{'nim' : 'A02', 'nama' : 'Budi', 'mid' : 40, 'uas' : 90},
{'nim' : 'A03', 'nama' : 'Chicha', 'mid' : 100, 'uas' : 50},
{'nim' : 'A04', 'nama' : 'Donna', 'mid' : 20, 'uas' : 100},
{'nim' : 'A05', 'nama' : 'Fatimah', 'mid' : 70, 'uas' : 100}]
print("... |
987,268 | e68987180add0eab8abe669e0833fa63cabea811 | from tkinter import *
from functools import partial
from Resolution.resolution_hidato import *
def main_window_hidato():
root = Tk()
root.title("Résolution de Hidato")
root.resizable(0,0)
root.geometry('150x200')
button_frame=Frame(root)
grid = [['','','','','','/','/','/'],['',... |
987,269 | 58158d04182032ce4e81844993cc1cc34eb5f9da | from __future__ import division
import numpy as np
from pysd import functions
from pysd import builder
... |
987,270 | 2570a2cd12aea6ef848e4759441095d89ff8a5e8 | import uuid
from django.db import models
# Create your models here.
class Contract(models.Model):
contract_id = models.UUIDField(primary_key=True, unique=True, default=uuid.uuid4, editable=False)
client_id = models.UUIDField(editable=False)
predial = models.FloatField()
address = models.CharField(max... |
987,271 | eeac73ed8e9bfc1f6e673efab3919e4c78c95638 | from __future__ import print_function, division
import chronostar.component
"""
A script which gathers all plotting of all relevant figures into
one spot to facilitate quick and simple replotting as needed.
TODO: Maybe do again, but with the range buffer lowered to 0.1 (from 0.2)
"""
import corner
import matplotlib... |
987,272 | a4c50e20578681884054d7be779e1ce92caf732a | #!/usr/bin/python2.4 -tt
# Copyright 2008 Google Inc. All Rights Reserved.
"""Mimic pyquick exercise -- optional extra exercise.
"""
__author__ = 'nparlante@google.com (Nick Parlante)'
import random
import sys
def A(arg1, arg2):
"""Returns mimic dict mapping each word to list of words which follow it."""
# +... |
987,273 | ccc1a7d4d895d7fe9e971ed66b1895914df8ef72 | from math import *
N = 8
V = 4
Z = 2
C = 1
wordSign = 1 << 11
wordMask = (1 << 12) - 1
byteSign = 1 << 7
byteMask = (1 << 8) - 1
def adder(op, a, b, cin, siz=False):
if siz:
sign = wordSign
mask = wordMask
else:
sign = byteSign
mask = byteMask
auL = mask & a
if op == ... |
987,274 | 1a79baaf526ec0dede78ea1d4d7b105d50c3775f | #permite agrupar datos ys u comportamiento
#es como seguridad por que nos prmite controlar las modificaciones
#tambien es aplicada la programacion defensiva,para saver cuando y como se
#mofica una calase
#controla el acceso a dicho datos
#previene modificaciones no autorizadas
#decoradores se definesn con el simbol... |
987,275 | ee3aeccf4e7209f8d1da0969d38fa2a51f09fbfc | """Evaluate models on ImageNet-A"""
import os
import sys
import time
import argparse
import numpy as np
from collections import OrderedDict
import torch
import torch.nn.functional as F
import torch.utils.data
import torchvision
import torchvision.models
import torchvision.transforms as transforms
import torchvision.dat... |
987,276 | 1dec761b5e51c20d44dc2e6d27080cc94a0a0a23 | ## HEADS == 1
## TAILS == 0
import random
def coin():
heads = 0
tails = 0
for x in range(1, 5001):
rand = random.randint(0,1)
if (rand == 0):
tails += 1
print "Attempt #", x , ": Throwing a coin. . . It's a tail!.... Got ", heads, " heads and ", tails, " tails so fa... |
987,277 | 331808d8f58c9d5329b47623788a1e08d4875831 | '''attack an image classification model'''
import os
import argparse
import random
import logging
import pickle as pkl
from datetime import datetime
from tqdm import tqdm
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torchvision import datasets, transforms
import to... |
987,278 | 855a40fd30eff3b85a0f242608155d202abba9d7 | from django.db import models
from apps.gallery.models import Gallery
class Section(models.Model):
slug = models.CharField(max_length=100, unique=True)
name = models.CharField(max_length=200, null=False)
title = models.CharField(max_length=35, null=False)
sub_title = models.TextField(max_length=200, nul... |
987,279 | 7a2f856fb9cb087fd772dadaa08ce8da2acba349 | # banner = list("Congratulations")
# print(banner)
# temperatures = []
# temperatures.append(99.6)
# temperatures.append(98.4)
# print(temperatures)
# er_temp = [101.1, 100.8, 99.9]
# print(er_temp)
# total_temps = temperatures + er_temp
# print(total_temps)
# attendees = ["Ken", "Alena", "Treasure"]
# attendees.ap... |
987,280 | 01dc823e4501a3890df1c6a54abd8ee12f4e1bc0 | import pandas as pd
import numpy as np
df=pd.read_csv("AAAI.csv")
a=df["Topics"]
b=[]
for i, v in a.iteritems():
c=v.splitlines()
d=set(c)
b.append(d)
o=0
e=np.zeros((len(b), len(b)))
for x in range(150):
for i in range(len(b)):
for j in range(len(b)):
e[i][j]=(len(b[i]... |
987,281 | a99019b798d5bb924f9184bf0467916ab5bf2e80 | import cv2
import numpy as np
from matplotlib import pyplot as plt
images = ['../facedetect/images_resize/face_of_1.jpg','../facedetect/images_resize/face_of_2.jpg','../facedetect/images_resize/face_of_3.jpg']
for image in images:
gray_img = cv2.imread(image, cv2.IMREAD_GRAYSCALE)
cv2.imshow('1',gray_img)
h... |
987,282 | 79d580bb349669ede61ec3bdd5332dd1a89d9df8 | # Generated by Django 3.1.1 on 2021-03-03 15:13
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('Post', '0025_auto_20210303_1234'),
]
operations = [
migrations.AddField(
model_name='post',
name='citi... |
987,283 | ce902b5d88b54f949ed95bf1fadcbe17d8fce169 | import spacy
from elasticsearchapp.query_results import get_all_analyzed_data, elastic_greek_stemmer
import pandas as pd
import numpy as np
from sklearn.preprocessing import LabelEncoder
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn import model_selection, naive_bayes, svm
from sklearn.metric... |
987,284 | 7467f0f21cec578f5ebc144d443199e8076dd3bd | """Default values."""
DEFAULT_FILE = "data.csv"
DEFAULT_NUM_OF_TOPICS = 3
|
987,285 | 2d7906bfd73ea52be0cb167fef239da792a1f874 | # -*- coding:utf-8 -*-
"""
__author__ = 'lijianbin'
这个网站老变态了
"""
from __future__ import unicode_literals
import re
import json
from PIL import Image
from io import BytesIO
from EnterpriseCreditCrawler.common import image_recognition
from EnterpriseCreditCrawler.common import url_requests
from EnterpriseCredit... |
987,286 | bad1b8f77214b66edde61c99036b2ba971bb96eb | import re
# notice the use of pipe character below
bat_regex = re.compile(r'bat(man|mobile|women)')
mo = bat_regex.findall("I am batman vs batwomen")
print(type(mo))
for i in mo:
print(i)
|
987,287 | 0442d83409b28fe8a6a3352e1ec9df222a17331b | ######################################
# Time:2020/02/11
# alter: ZWQ
######################################
from flask_restplus import Api
from flask import Blueprint
from .views import find_task,add_task,del_task,updata_task
authorizations = {
'apikey': {
'type': 'apiKey',
'in': 'header',
... |
987,288 | 1cfb1aec0158e66ce443f68ba1667e67b698e599 | # -*- coding: UTF-8 -*-
'''
Task
Given a positive integral number n, return a strictly increasing sequence
(list/array/string depending on the language) of numbers, so that the sum of the
squares is equal to n².
If there are multiple solutions (and there will be), return the result with the
largest possible values:
... |
987,289 | 70b811a3323d52c40c24cf54d0692960c77a7353 | # 给定一个只包含 '(' 和 ')' 的字符串，找出最长的包含有效括号的子串的长度。
#
# 示例 1:
#
# 输入: "(()"
# 输出: 2
# 解释: 最长有效括号子串为 "()"
#
#
# 示例 2:
#
# 输入: ")()())"
# 输出: 4
# 解释: 最长有效括号子串为 "()()"
#
# Related Topics 字符串 动态规划
# 👍 948 👎 0
# leetcode submit region begin(Prohibit modification and deletion)
# 1. 左右括号数量相等
# 2. 任意前缀中左括号数量大于等于右括... |
987,290 | c18d6c124f5e0af562fccc01b13e23c9406478a8 | from snippet.lazy_dict import LazyDict, lazy_property
from nose import tools
class Book(LazyDict):
def __init__(self, book_id):
super(Book, self).__init__()
self.id = book_id
self.__subset__ = {'review'}
@lazy_property
def author(self):
return self._get_author()
def _... |
987,291 | c46d64d71d4a52719af8d719961336edeff2bea3 | import tensorflow as tf
import DS_input as deepSpeech_input
import rnn_cell
from helper_routines import _variable_on_cpu
from helper_routines import _variable_with_weight_decay
from helper_routines import _activation_summary
# Global constants describing the speech data set.
NUM_CLASSES = deepSpeech_input.NUM_CLASSES
... |
987,292 | 0ee8c0d834fe133fbb36ceece601436f24b4117f | import pygame
from Settings import Settings
from function import *
from pygame.sprite import Group
from Alien import *
def run_game():
pygame.init()
settings=Settings()
screen=pygame.display.set_mode((settings.screenWidth,settings.screenHeight))
pygame.display.set_caption('Alien Invasion')
ship=Shi... |
987,293 | cffdde6a558cb29c15f5b43c27ae1ff42a1b8bf1 | # 39. Escrever um algoritmo que leia uma variável n e calcule
# a tabuada de 1 até n. Mostre a tabuada na forma:
# 1 x n = n
# 2 x n = 2n
# 3 x n = 3n
# ...............
# n x n = n2
# minha
n = float(input("Digite um número, para sua tabuada: "))
contador = 0
while n * n > contador * n:
contador ... |
987,294 | fda1bfa852936d35a3ff063e18353de011b13b91 | '''클라이언트 소켓을 담당하는 서버 클래스'''
class client:
def __init__(self, cs, ip):
self.cs = cs
self.ip = ip
def send_msg(self, message):
self.cs.send(message.encode('utf-8'))
|
987,295 | 48fb18d2c94b1f0967e5f156975aeb53ac6b6271 | # -*- coding: utf-8 -*-
# Generated by Django 1.11.16 on 2019-01-08 21:32
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('lavajato_agenda', '0004_auto_20181220_1839'),
]
operations = [
migrations.... |
987,296 | ad1dd5cda6d5784284c89bba1eef0cc269e573b8 | def mi():
return map(int, input().split())
def main():
N, K = mi()
R, S, P = mi()
T = input()
pt = 0
my_choices = ['']*N
for i in range(K):
tmp = T[i::K]
for j in range(len(tmp)):
if j == 0:
if tmp[j] == 'r':
my_choices[i] = '... |
987,297 | f709aaa56f2a1514dd04b8744f18233842390ef9 | # ----------------------------------------------------------
# -------- CS50 Final Project --------
# ----------------------------------------------------------
# ----------------------------------------------------------
#Name:Prince Michael Agbo
#Title: Snakes and Ladders
#Number of Players: 2
... |
987,298 | 981fec62fc686d49073c364517e78f7f8388179f | # ## Getting Perpsective Transform
#Import necessary libraries
import cv2
import numpy as np
import matplotlib.pyplot as plt
#Load/Read input image
input_image2 = cv2.imread('ba.jpg')
#show the original image
cv2.imshow('Original', input_image2)
cv2.waitKey(0)
# Cordinates of the 4 corners of the original source ... |
987,299 | 448b5460831f4a2f43094bee63894a71f04b5dae | home_page = dict(
searchFieldByID="search_query_top",
searchButtonByName="submit_search",
cartButtonCSSSelector="a b",
dressesButtonByXpath="(//a[@class='sf-with-ul'])[4]",
dressesButtonActivateByXpath="(//ul[@class='submenu-container clearfix first-in-line-xs'])[2]",
dressesButtonCassualDresses... |
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