text stringlengths 38 1.54M |
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import numpy
class IndicatorHistoryDataFrameRenderer(object):
@staticmethod
def render_indicator_data(plots_per_axis, snapshot_data, ymin, ymax, progress_plot, progress_bar_location):
# draw individual indicators
for indicator_name, plot in plots_per_axis.items():
snapshot_data_per... |
# Given an array of ints, return True
# if one of the first 4 elements in
# the array is a 9. The array length
# may be less than 4.
from test import Tester
def array_front9(nums):
num_range = len(nums)
if num_range > 4:
num_range = 4
for i in range(0,num_range):
if nums[i] == 9:
... |
# from itertools import chain
from notifUpdate import Notification
from issues import Issues
import time
import pandas as pd
pd.set_option('display.width', None)
issues = Issues()
notif = Notification()
class gendarmerieUpdate:
def __init__(self, connexion, annee_update):
self.annee = annee_update
... |
# -*- coding: utf-8 -*-
"""
Created on Wed Jul 8 11:50:03 2020
@author: norma
"""
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import curvefunc
import ulxlc
data_file = '../data/external/variable_ulxlc/tlag_f0p2_m10_mdot20_test.dat'
df = pd.read_csv(data_file, sep=' ', he... |
# -*- coding: utf-8 -*-
# Generated by Django 1.10.5 on 2017-06-22 20:12
from __future__ import unicode_literals
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('enot_app', '0106_trip_direct'),
('enot_app', '0106_merge_20170611_1250'),
]
operati... |
import utils
import training
import numpy as np
from random import shuffle
if __name__ == '__main__':
utils.word_extract()
input_nn = []
targets = []
samples_per_category = 5000
a,b = utils.load_inputs("aclImdb/train/neg", 0, samples_per_category, input_nn, targets)
input_nn=list(a)
targe... |
# Esto es un comentario
def cuadrado_f(x):
"""Calcula el numero
al cuadrado"""
y = x * x
return y
def cuadrado_p(x):
"""Imprime el numero al cuadrado"""
# return 1000
y = x * x
print("El cuadrado es:",y)
# a = cuadrado_f(5)
# print("el cuadrado de 5 es",a)
# b = cuadrado_p(5)
# print("e... |
# Copyright 2014 Symantec 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... |
import re
import pyfumbbl
from . import field
import cibblbibbl
@cibblbibbl.helper.idkey
class Coach(metaclass=cibblbibbl.helper.InstanceRepeater):
apiget = field.fumbblapi.CachedFUMBBLAPIGetField(
pyfumbbl.coach.get
)
def __init__(self, coachId: int, name: str=None):
self._name = name
if se... |
# Copyright 2014 The Oppia Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable ... |
def maximum_sum(array, window_size):
array_size = len(array)
if array_size <= window_size:
return -1
window_sum = 0
for i in range(window_size):
window_sum += array[i]
max_sum = window_sum
for i in range(array_size - window_size):
window_sum = window_sum - array[i] + a... |
from behave import given, when, then
from pages.rsi.rsi_date_adjusted_response_validation import RsiDateAdjustedResponseValidation
from pages.test_survey.test_survey_contributor_details_page import TestSurveyContributorDetailsPage
from pages.rsi.rsi_contributor_details_page import RsiContributorDetailsPage
@given(u'... |
import cs50
import sys
if len(sys.argv) != 2:
print("Usage: python caesar.py k")
exit(1)
else:
k = int(sys.argv[1])
#print("{}".format(k))
c=[None] * 100
d=[None] * 100
#print("{}".format(len(d)))
print("plaintext: ",end="")
p=cs50.get_string()
... |
import os
import unittest
from pyats.topology import loader
from genie.libs.sdk.apis.iosxe.snmp.configure import unconfigure_snmp_server_user
class TestUnconfigureSnmpServerUser(unittest.TestCase):
@classmethod
def setUpClass(self):
testbed = f"""
devices:
csr:
connectio... |
import sqlite3
import ihm.console as ihm
def ouvrir_connexion(db_name):
"""
Connexion à une base de données
"""
conn = sqlite3.connect(db_name)
# création d'un curseur pour accéder à cette base
cur = conn.cursor()
return conn, cur
def executer_requete(cur, req, variables=()... |
#!/usr/bin/env python3
import matplotlib.pyplot as plt
import sys
import pandas as pd
import numpy as np
file = sys.argv[1]
gwas = pd.read_csv(sys.argv[1] , sep = "\s+")
gwas['logP'] = -1 * np.log10(gwas['P'])
gwas['snp_index'] = range(len(gwas))
df_subset = gwas.query('logP > 5')
gwas['snp_index'] = range(len(gw... |
import torch.utils.data as data
import os
import sys
import random
import numpy as np
import cv2
import scipy.io as scio
class VideoNet(data.Dataset):
def __init__(self,
root,
source,
phase,
modality="rbg",
name_pattern=None,
... |
from django import forms
from django.contrib.auth.forms import UserCreationForm
from django.forms import ModelForm
from django.contrib.auth.models import User
from .models import *
from accounts.models import *
from hoitymoppet.models import *
class UserCustomSizeform(forms.ModelForm):
class Meta:
model =... |
from random import shuffle
from threading import Thread
import irc
import irc.bot
import util
import speech
class Carte:
VALEURS = ['As', 'Deux', 'Trois', 'Quatre', 'Cinq', 'Six', 'Sept',
'Huit', 'Neuf', 'Dix', 'Valet', 'Dame', 'Roi']
def __init__(self, valeur):
self._valeur = valeur
def __lt__(self... |
#!/usr/bin/env python2
import copy
import hashlib
import json
import os
import sys
class FileTail(object):
def __init__(self, file_name, state_dir='.', debug=False):
self._data = None
self._debug = debug
self._file_object = None
self._state = None
self._tailed_file = file_... |
import cv2
import numpy as np
image = cv2.imread('blox.jpg')
sift_feature = cv2.xfeatures2d.SIFT_create()
surf_feature = cv2.xfeatures2d.SURF_create()
orb_feature = cv2.ORB_create()
sift_kp = sift_feature.detect(image)
surf_kp = surf_feature.detect(image)
orb_kp = orb_feature.detect(image)
sift_out = cv2.drawKeypo... |
import itertools
import sys
# Reading the file (ToDO: Better way to remove the label spaces)
def read_training_file(filename):
f = open(filename, 'r')
df = f.read()
data = []
training_data = []
data = df.split("\n")
for row in data:
temp_data = []
if(len(row) < 1):
... |
# Generated by Django 2.1.4 on 2018-12-18 12:37
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Documento',
fields=[
... |
from django.http import HttpResponseRedirect
from insight.models import Origin
from insight.signals import origin_hit
def set_origin_code(request, code):
try:
origin = Origin.objects.get(code=code)
if origin.track_registrations:
request.session['insight_code'] = code
reque... |
import torch as th
import torch.nn as nn
import torch.nn.functional as F
from latent_dialog.enc2dec.base_modules import BaseRNN
class EncoderGRUATTN(BaseRNN):
def __init__(self, input_dropout_p, rnn_cell, input_size, hidden_size, num_layers, output_dropout_p, bidirectional, variable_lengths):
super(Encode... |
from django.shortcuts import render
from django.contrib.auth.models import User
from cars.models import Car
# Create your views here.
def main(request):
br = []
for i in range(1, Car.objects.count()+1):
if i % 4 == 0:
br.append(i)
return render(request, 'cars/cars.html', {'cars': Car.... |
import requests
from bs4 import BeautifulSoup
#from .. models import Tournament, Position
#from .... apps.players.models import Player
import datetime
import pdb
from models.tournament import Tournament
import mongoengine as me
me.connect('fg')
def tournaments_scrape():
tour_champ_end = datetime.datetime(year=2014,... |
#! /usr/bin/env python
# -*- coding: utf-8 -*-
""" Test module for ErrorMetrics """
import ErrorMetrics as em
from collections.abc import Iterable
x = [2.7, 3.7, 5.7, 9.1, 2.0]
y = [9.0, 9.4, 6.6, 6.3, 0.6]
def assert_almost_equal(x, y, th=0.0001):
if isinstance(x, Iterable) and isinstance(y, Iterable):
... |
class DescendingFrequency:
@staticmethod
def frequency_sort(input_str: str) -> str:
# the smallest character in dataset
zero_ord = ord('0')
# an array that saves the frequency of each character as it appears.
char_frequency = [0] * 75
for current_char in input_str:
... |
#!/usr/bin/python
import argparse
from azure.devops.connection import Connection
from msrest.authentication import BasicAuthentication
from azure.devops.v6_0.work_item_tracking.models import Wiql
def parse_args():
'''Defines cmdline arguments'''
parser = argparse.ArgumentParser()
parser.add_argument('--ac... |
from common.protocolmeta import protocols
from itertools import islice
def first(iterable):
try:
return islice(iterable, 1).next()
except StopIteration:
return None
def im_service_compatible(to_service, from_service):
'''
Returns True if a buddy on to_service can be IMed from a connect... |
import os
from os import path as pt
from zipfile import ZipFile
import numpy as np
import pandas as pd
import requests
import torch
import wfdb
from tqdm import tqdm
import os
from tqdm import tqdm
import pandas as pd
import numpy as np
import glob
import torch
from lib.utils import sample_indices
from fbm import fbm... |
from django.urls import path
from django.conf.urls import url
from . import views
urlpatterns = [
url('snips/', views.api_snip),
url('^snip/(?P<id>\d+)$', views.list_snip),
]
|
def main():
#image_path = "C:\\Users\\MAHE\\Desktop\\8th Sem Project\\Dicom_to_Image-Python-master\\Dicom_to_Image-Python-master\\Series13_png\\0012.png"
image_path = input()
numpy_for_image = imgToNumpy(image_path)
print(numpy_for_image)
transformed_matrix = transformNumpyToMartix(numpy_for_image,poly)
#pr... |
from controller import Controller
import time
x = Controller(4)
print("\nPut car at stop sign 3")
x.new_car(2)
print(x.queue)
time.sleep(1)
print("\nPut car at stop sign 1")
x.new_car(0)
print(x.queue)
print("\nRemove car at front of queue")
x.remove_car()
print(x.queue)
print("\nCheck safety of sign 2")
x.... |
from django.contrib import admin
from django.urls import path
from . import views
urlpatterns = [
path('reservation', views.reservation, name='reservation'),
]
|
#i want see all images and turn them into trainable data
import cv2
import os
from PIL import Image
import numpy as np
import pickle
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
image_dir = os.path.join(BASE_DIR,'images')
faceCascade = cv2.CascadeClassifier('cascades/data/haarcascade_frontalface_... |
line = 'Good,100,490.10'
field_type = [str, int, float]
raw_fields = line.split(',')
print(raw_fields)
fields = [ty(val) for ty, val in zip(field_type, raw_fields)]
print(fields)
for i in zip(field_type, raw_fields):
print(i,type(i)) |
b=input()
b=int(b)
X=[]
for i in range(0,b):
y=input()
X.append(y)
C=[]
for i in zip(*X):
if i.count(i[0])==len(i):
C.append(i[0])
else:
break
print(''.join(C))
|
import re
from solutions import helpers
from solutions.day07.file_system import Directory, File
def parse_shell_output(filename):
strings = helpers.read_each_line_as_string(filename)
root_dir = Directory(parent=None, name="/")
pwd = root_dir
for string in strings:
print(string)
if s... |
COLORS = {"UTILTIES": (127,127,127),
"RAILWAY STATIONS":(50,50,50),
"INDIGO COLOR":(75,60,130),
"LIGHTBLUE COLOR":(128,225,255),
"PURPLE COLOR":(170,40,150),
"ORANGE COLOR":(250,140,10),
"RED COLOR":(250,10,10),
"YELLOW COLOR":(240,240,0),
... |
from bot_app import api_func
import requests
import json
from bot_app import localization
from vedis import Vedis
from bot_app import tech_info
from logistic_bot import settings
# a = api_func.Api()
#
# a.set_user_id(telegram_id='test', user_id='D87hd487ft4')
# a.set_zipcode('test', 33815)
# print(a.return_param('test... |
"""
Classes and functions for interacting with Gen3's Discovery Metadata and configured
external sources to obtain DOI metadata and mint real DOIs using Datacite's API.
"""
import csv
from cdislogging import get_logger
from gen3.doi import DataCite, DigitalObjectIdentifier
from gen3.external.nih.dbgap_doi import dbg... |
foo = input()
hasDuplicate = 1
for index, letter in enumerate(foo):
if foo.index(letter) != index:
hasDuplicate = 0
break
print(hasDuplicate) |
#！、usr/bin/env python
#-*- coding:utf-8 -*-
from django.forms import ModelForm
from .models import Student,State
class StudentForm(ModelForm):
class Meta:
model=Student
fields='__all__'
class StateForm(ModelForm):
class Meta:
model=State
# field='__all__'
exclude=['user... |
import unittest
import os
from essentialdb import PickleSerializer, JSONSerializer
class TestSerializers(unittest.TestCase):
json_file_path = "test.json"
pickle_file_path = "test.pickle"
def __get_data(self):
return dict({'f1': [1,2,3], 'f2': {'n1':'a', 'n2': 2}})
def test_pickle(self):
... |
#!/usr/bin/env python
# -*- coding:utf-8 -*-
import re
import Token as token
import sbd.util.Util as util
class Tokenizer:
def __init__(self):
self.tokens = []
self.util = util.Common()
def __del__(self):
self.clear()
def clear(self):
del self.tokens[:]
def parse(sel... |
import configparser
_SPORTSBOOK_CONFIG_FILE_ = '/Users/leoshang/workspace/football_data_analysis/asianbookie/' \
'sportsbook/spiders/premier-league.ini'
data_feed_config = configparser.ConfigParser()
data_feed_config.read(_SPORTSBOOK_CONFIG_FILE_)
class SportsbookConfiguration:
def _... |
'''
python版本:3.6.1
1.对/var/log/nginx/access.log的ip进行分组统计并且排序
2.加入IP地址地理查询及限制输出多少条
使用方法:
python count.py
python count.py log 1 #输出1条IP对应的地址
python count.py log 2 #输出2条IP对应的地址
python count.py log 3 #输出3条IP对应的地址
'''
import re
import sys
from fn_get_ip_area import get_ip_area
fp = ope... |
r"""Efficient implementation of the Gaussian curl-free kernel."""
from time import time
from pympler.asizeof import asizeof
from numpy.random import rand, seed
from numpy import dot, zeros, logspace, log10, matrix, int, float
from scipy.sparse.linalg import LinearOperator
from sklearn.kernel_approximation import RBF... |
from __future__ import unicode_literals
import urllib.request, urllib.parse, urllib.error
import json
import ssl
#忽略SSL证书错误
ctx = ssl.create_default_context()
ctx.check_hostname = False
ctx.verify_mode = ssl.CERT_NONE
serviceurl = 'https://apis.map.qq.com/ws/geocoder/v1/?'
while True:
address = input('Enter locat... |
# Generated by Django 3.2.13 on 2022-08-18 16:09
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('action_plans', '0021_auto_20220728_0828'),
]
operations = [
migrations.AddField(
model_name='actionplan',
name='has... |
# read files with numbered lines
#Autumn (worked with Mandy)
counter = 0
infile = open((input("Name of file (include extension): ")),"r")
for line in infile.readlines():
print(counter, line)
counter = counter + 1
|
from bean import *
from datetime import datetime,timedelta
def today_range():
#show the current doing task
today = datetime.now()
today = datetime(today.year,today.month,today.day)
yesterday = today
today = datetime(today.year,today.month,today.day) + timedelta(days = 1)
return
class TaskMa... |
from cs50 import get_string
from sys import argv
if len(argv) != 3:
print("Please read documents to follow the format of program")
exit(0)
csv_file =open(argv[1],"r")
groups =[]
people= {}
for index,row in enumerate(csv_file):
if index ==0:
groups =[group for group in row.strip().split(",")][1:]... |
from lxml import objectify
from pandas import DataFrame, Series
import pandas as pd
from datetime import datetime
def read_file(filepath):
parse_file = objectify.parse(open(filepath))
root = parse_file.getroot()
elt = root.Document
flightname = elt.name.text
print flightname
#get the three placemarks
... |
# -*- coding: utf-8 -*-
'''
将n-gram embedding作为lstm的输入
'''
import pickle
import numpy as np
import keras
from keras.preprocessing.text import Tokenizer
from keras.preprocessing.sequence import pad_sequences
from keras.models import Model
from keras.layers import Input, Embedding, AveragePooling1D, Dense, GlobalMax... |
from dicom_to_cnn.model.petctviewer.Roi import Roi
class RoiNifti(Roi):
"""Derivated Class for automatic Nifti ROI of PetCtViewer.org
Returns:
[RoiNifti] -- Nifti ROI
"""
def __init__(self, roi_number:int, list_point:list, volume_dimension:tuple):
"""constructor
Args:
... |
from typing import List
class TreeNode:
def __init__(self, x):
self.val = x
self.left = None
self.right = None
class Solution:
def postorderTraversal(self, root: TreeNode) -> List[int]:
"""
https://leetcode.com/problems/binary-tree-postorder-traversal/
Given ... |
import dbus
import time
import json
import lxml
from lxml import etree
from dbus.mainloop.glib import DBusGMainLoop
# DBusGMainLoop(set_as_default=True)
class BT_Manager:
# Open a connection to the SystemBus
def __init__(self):
self.__bus = dbus.SystemBus()
self.__adapter_proxy = self.get_Ada... |
#!/usr/bin/env python2
from __future__ import print_function
import argparse
import collections
import ConfigParser
import os
import subprocess
import sys
import time
from datetime import datetime, timedelta
class ExecutionError(Exception):
def __init__(self, returncode, output):
self.returncode = retur... |
class tcp8088(Protocol):
def connectionMade(self):
logprint("[honeypot.HoneyPotFactory] New connection: %s:%s (%s:%s) [Session: %d]" % \
(self.transport.getPeer().host, self.transport.getPeer().port, self.transport.getHost().host, self.transport.getHost().port, self.transport.sessionno))
def dataReceived(self, da... |
#!/usr/bin/env python
# Copyright 2019 Google LLC
#
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or... |
# SPDX-License-Identifier: MIT
# Copyright (c) 2018-2023 Amano LLC
import asyncio
from pyrogram import Client, filters
from pyrogram.types import ChatPrivileges, Message
from config import PREFIXES
from eduu.database.admins import check_if_del_service, toggle_del_service
from eduu.utils import commands
from eduu.uti... |
import os
import torch
import numpy as np
from . import img_process
def get_real_sketch_batch(batch_size, img_name_list, dataset_filter):
img_name_list_all = np.array([x.strip() for x in open(img_name_list).readlines()])
img_name_list = []
for idx, i in enumerate(img_name_list_all):
for j in d... |
from typing import List, Tuple
def cross_add(input_vals: List[int]) -> List[int]:
""" Traverses <input_vals> from both directions, adding the ith element to the (n-i)th, and storing
the result in the ith element of <result>.
Examples:
[1, 2, 3] -> [4, 4, 4]
[3, 4, 7, 13] ... |
import sys
def maxSubArraySum(a,size):
max_so_far = -sys.maxsize - 1
max_ending_here = 0
for i in range(0, size):
max_ending_here = max_ending_here + a[i]
if (max_so_far < max_ending_here):
max_so_far = max_ending_here
if max_ending_here < 0:
m... |
#!/usr/bin/env python
# coding: utf-8
# In[108]:
# Importing the necessary libraries
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression
from sklearn import metrics
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
im... |
import numpy as np
from functions import deg2rad, eulermethod
from math import sqrt, pi
initial_yaw = 40
initial_pitch = 30
initial_roll = 80
initial_angles = [initial_yaw, initial_pitch, initial_roll]
initial_angles = deg2rad(initial_angles)
tstart = 0.0
tstop = 42.0
step = 0.01
length = int(round(tst... |
lista = [20, 10, 5, 4, 6, 8]
listb = [3, 8, 15, 6, 12, 9]
def add(a, b):
return a+b
listc = list(map(add, lista, listb))
print(listc)
|
from __future__ import print_function
# Import MNIST data
from tensorflow.examples.tutorials.mnist import input_data
data = input_data.read_data_sets('/tmp/data/', one_hot=True)
import tensorflow as tf
# Parameters
learning_rate = 0.1
training_epochs = 15
batch_size = 100
# Network Parameters
n_hidden = 256 # numb... |
"""
Solution for Algorithms #21: Merge Two Sorted Lists
Runtime: 44 ms, faster than 88.71% of Python3 online submissions for Merge Two Sorted Lists.
Memory Usage: 13.2 MB, less than 5.06% of Python3 online submissions for Merge Two Sorted Lists.
"""
# Definition for singly-linked list.
# class ListNode:
# def __in... |
# 【问题描述】深度优先遍历
# 【输入形式】同上题
# 【输出形式】同上题
# 【样例输入】
# 4 A
# A: {B:1, C:1, D:1}
# B: {A:1, C:1, D:1}
# C: {A:1, B:1, D:1}
# D: {A:1, B:1, C:1}
# 【样例输出】
# A B C D
dic = {0: "A", 1: "B", 2: "C", 3: "D", 4: "E",
5: "F", 6: "G", 7: "H", 8: "I", 9: "J"}
ans = []
def travelsal(mat, ver):
global ans
global n
... |
import RPi.GPIO as IO
import time as t
IN1 = 19
IN2 = 26
def DC_setup():
IO.setmode(IO.BCM)
IO.setup(IN1, IO.OUT)
IO.setup(IN2, IO.OUT)
d1 = IO.PWM(IN1, 50)
d2 = IO.PWM(IN2, 50)
d1.start(0)
d2.start(0)
return d1, d2
d1, d2 = DC_setup()
while True:
d1.ChangeDutyCycl... |
from django.conf.urls import url
from . import views
urlpatterns = [
url(r'^client/$',views.index,name='index'),
#url(r'^client/(?P<client_id>[0-9]+)/$',views.client,name='client'),
url(r'^client/(?P<client_id>[0-9]+)/$',views.detail,name='detail'),
url(r'^client/addclient/$',views.addclient,name='addclient'),
... |
# docker container rm spark-submit -f
# docker run -it --name spark-submit --network spark-net --volume /home/liming:/home -e HADOOP_USER_NAME=liming -p 4040:4040 mingsqtt/spark_submit:3.0.1 bash
# $SPARK_HOME/bin/pyspark --conf spark.executor.memory=14G --conf spark.executor.cores=6 --master spark://spark-master:7077... |
//Robot_Arm.ino
#include <Servo.h>
#include <Wire.h>
#include <LCD.h>
#include <LiquidCrystal_I2C.h>
LiquidCrystal_I2C lcd(0x3F,2,1,0,4,5,6,7);
const int arrLen = 20;
Servo clawServo, lowerServo, upperServo, baseServo;
int claw, lower, upper, base;
int clawPot = 3;
int lowerPot = 2;
int upperPot = 1;
int basePot ... |
class LRUCacheNode:
def __init__(self, key, val, parent=None, child=None):
self.key = key
self.val = val
self.parent = parent
self.child = child
class LRUCache:
def __init__(self, capacity: int):
self.head = None
self.tail = None
self.nums ... |
s = 1
n1 = 3
n2 = 2
cont = 0
while n1 < 40:
s = s + (n1/n2)
n1 += 2
n2 = n2*2
print("%.2f"%s)
|
class Solution:
def checkStraightLine(self, coordinates: List[List[int]]) -> bool:
for i in range(1, len(coordinates)):
xyc = coordinates[i]
xyp = coordinates[i-1]
print(xyc, xyp)
if xyc[0] == xyp[0]:
return False
pslope = (coordinates[... |
import binascii
from Crypto.Util.number import bytes_to_long, long_to_bytes
# KEY1 = 0xa6c8b6733c9b22de7bc0253266a3867df55acde8635e19c73313
# KEY2 = 0x37dcb292030faa90d07eec17e3b1c6d8daf94c35d4c9191a5e1e ^ KEY1
# KEY3 = 0xc1545756687e7573db23aa1c3452a098b71a7fbf0fddddde5fc1 ^ KEY2
# FLAG = 0x04ee9855208a2cd59091d04767... |
__author__ = "Jieshu Wang and Bilal El Uneis"
__since__ = "July 2019"
__email__ = "foundwonder@gmail.com and bilaleluneis@gmail.com"
from unittest import TestCase
from abstract_array import *
import logging as log
class TestArrayListImpl(TestCase):
@classmethod
def setUpClass(cls):
log.basicConfig(l... |
from collections import namedtuple
MessageSource = namedtuple('MessageSource', 'id type service config')
|
# -*- coding: utf-8 -*-
##############################################################################
#
# OpenERP, Open Source Management Solution
# Copyright (C) 2004-2010 Tiny SPRL (<http://tiny.be>).
#
# Corrections & modifications by Noviat nv/sa, (http://www.noviat.be):
# - VAT listing based upon year... |
import data
from keras.layers import Dense, Flatten, Conv2D, MaxPooling2D
from keras.models import Sequential, load_model
model = Sequential()
model.add(Conv2D(16, (3, 3)))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Conv2D(16, (3, 3)))
model.add(Flatten())
model.add(Dense(128, activation='relu'))
model.add(D... |
import xlrd
import sqlite3 as sqlite
import itertools
def xls2db(infile, outfile):
"""
Convert an xls file into an sqlite db!
"""
#Now you can pass in a workbook!
if type(infile) == str:
wb = xlrd.open_workbook(infile)
elif type(infile) == xlrd.Book:
wb = infile
else:
... |
#!/usr/bin/env python3
import argparse
import logging
import re
import os
import shutil
from os import listdir
from os.path import isdir, isfile, join
logging.basicConfig(format='%(levelname)s:%(message)s', level=logging.INFO)
logger = logging.getLogger()
file_path = os.path.dirname(__file__)
unsorted_roms_folder =... |
#!/bin/python
# -*- coding: utf-8 -*-
import os as _os
import platform as _platform
# Setting up the proper libraries and paths, mainly for Windows support
_libpath = _os.path.abspath(_os.path.dirname(__file__))
_plat_info = dict(plat=_platform.system())
if _plat_info['plat'] == 'Windows':
_plat_info['l... |
# coding:utf-8
import socket
# from jetbot import Robot
import subprocess
from multiprocessing import Process
def handle_client(client):
"""
处理客户端请求
"""
request_bytes = client.recv(1024)
# data = self.__client.recv(1024) # 判断空
# if data == b"":
# print('这里返回二进制空，不知道在哪儿看到的返回None，感觉逻辑合理，浪费... |
# mybot/app.py
import os
from kbbi import KBBI
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.metrics.pairwise import cosine_similarity
import nltk
import random
import string
import time
import _thread
from decouple import config
from flask import (
Flask, request, abort
)
from linebot... |
__author__ = 'Danyang'
class Solution:
def maxKSubArrays(self, nums, k):
n = len(nums)
f = [[0 for _ in xrange(k+1)] for _ in xrange(n+1)]
g = [[0 for _ in xrange(k+1)] for _ in xrange(n+1)]
s = [0 for _ in xrange(n+1)]
for i in xrange(1, n+1):
s[i]... |
# euler38
import time
t0 = time.time()
for n in range(1,60000):
val1 = n * 1
val2 = n * 2
val = str(val1) + str(val2)
for v in range(3,10):
if len(val) >= 9:
break
valn = n * v
val += str(valn)
if len(val) == 9:
if '1' in val and '2' in val and '3' i... |
F1,D2= map(list,input().split())
F1[0] = F1[0].upper()
D2[0] = D2[0].upper()
fstr = "".join(F1)
dstr = "".join(D2)
print(fstr,dstr)
|
from sys import argv
import cleanup
import tokenize
import wordcount
import sample
def sentance(histogram, total, loop):
looper = int(loop)
sentance1= []
word_string = " "
# loop
for i in range(0,looper):
weight_word = sample.weighted_random(histogram, total)
sentance1.append(weig... |
# Generated by Django 3.1.6 on 2021-05-08 11:08
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('teachers', '0008_auto_20210507_2047'),
]
operations = [
migrations.RenameModel(
old_name='Responses',
new_name... |
import requests
from bs4 import BeautifulSoup
import csv
from fake_useragent import UserAgent
UserAgent().chrome
def get_html(url):
r = requests.get(url, headers={'User-Agent': UserAgent().chrome})
print(r.text)
return r.text
def write_csv(data):
with open('csvs/Raif.csv', 'a') as f:
writer ... |
a= float(input("Valor disponivel: "))
b= int(input("Quantidades de tickets do RU: "))
c= float(input("Valor dos tickets: "))
d= int(input("Quantidade de passes de onibus: "))
e= float(input("Valor dos passes: "))
f= ((b * c) + (d * e))
if (a >= f):
print("SUFICIENTE")
else:
print("INSUFICIENTE") |
# Created: 12.04.2014, 2018 rewritten for pytest
# Copyright (C) 2014-2018, Manfred Moitzi
# License: MIT License
from __future__ import unicode_literals
import pytest
from ezdxf.modern.spline import Spline, _SPLINE_TPL
from ezdxf.lldxf.extendedtags import ExtendedTags
@pytest.fixture
def spline():
return Spline(... |
#
# THIS IS AN IMPLEMENTATION OF THE CLASSIC MEMORY GAME IN 2D
#
# COPYRIGHT BELONGS TO THE AUTHOR OF THIS CODE
#
# AUTHOR : LAKSHMAN KUMAR
# AFFILIATION : UNIVERSITY OF MARYLAND, MARYLAND ROBOTICS CENTER
# EMAIL : LKUMAR93@UMD.EDU
# LINKEDIN : WWW.LINKEDIN.COM/IN/LAKSHMANKUMAR1993
#
# THE WORK (AS DEFINED BELOW) IS PR... |
#!/usr/bin/python
#import sys
#import json
#import subprocess
import mechanize
import urlparse
import urllib,urllib2
from bs4 import BeautifulSoup
import multiprocessing
class Search:
"""Search class for new google search"""
def __init__(self, keyword):
self.keyword = keyword
self.crawl_topic = 'escort'
self... |
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