code stringlengths 13 1.2M | order_type stringclasses 1
value | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
class Component:
pass
class Entity:
def __init__(self, id):
self.id = id
self.components = {}
def add_component(self, component):
if type(component) in self.components:
raise Exception("This entity already has a component of that type")
# Since there is only ... | normal | {
"blob_id": "14f7f31fa64799cdc08b1363b945da50841d16b5",
"index": 3020,
"step-1": "<mask token>\n\n\nclass System:\n <mask token>\n\n def bind_manager(self, manager):\n self.manager = manager\n <mask token>\n\n def process(self, entity, deltaTime):\n pass\n <mask token>\n <mask tok... | [
13,
14,
17,
18,
24
] |
from flask import Flask, flash, abort, redirect, url_for, request, render_template, make_response, json, Response
import os, sys
import config
import boto.ec2.elb
import boto
from boto.ec2 import *
app = Flask(__name__)
@app.route('/')
def index():
list = []
creds = config.get_ec2_conf()
for region in con... | normal | {
"blob_id": "22c2425f1dc14b6b0005ebf2231af8abf43aa2e1",
"index": 5273,
"step-1": "<mask token>\n\n\n@app.route('/')\ndef index():\n list = []\n creds = config.get_ec2_conf()\n for region in config.region_list():\n conn = connect_to_region(region, aws_access_key_id=creds[\n 'AWS_ACCESS_... | [
6,
7,
8,
9
] |
# Packages
import PySimpleGUI as sg
import mysql.connector
import secrets
# TODO Add a view all button
# TODO Catch errors (specifically for TimeDate mismatches)
# TODO Add a downtime graph
# TODO Add a system feedback window instead of putting this in the out id textbox
error_sel_flag = False # Flag to check whether... | normal | {
"blob_id": "8fb5ef7244a8ca057f11cbcdf42d383665dade5e",
"index": 6884,
"step-1": "# Packages\nimport PySimpleGUI as sg\nimport mysql.connector\nimport secrets\n\n# TODO Add a view all button\n# TODO Catch errors (specifically for TimeDate mismatches)\n# TODO Add a downtime graph\n# TODO Add a system feedback win... | [
0
] |
n =int(input("nhap gia tri"))
for i in range(1,n+1):
print(i) | normal | {
"blob_id": "21b295e28a7e4443ea116df1b22ff5074dca955a",
"index": 246,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(1, n + 1):\n print(i)\n",
"step-3": "n = int(input('nhap gia tri'))\nfor i in range(1, n + 1):\n print(i)\n",
"step-4": "n =int(input(\"nhap gia tri\"))\nfor i in... | [
0,
1,
2,
3
] |
import os
import time
import uuid
import subprocess
# Global variables. ADJUST THEM TO YOUR NEEDS
chia_executable = os.path.expanduser('~')+"/chia-blockchain/venv/bin/chia" # directory of chia binary file
numberOfLogicalCores = 16 # number of logical cores that you want to use overall
run_loop_interval = 10 # seconds ... | normal | {
"blob_id": "bc536440a8982d2d4a1bc5809c0d9bab5ac6553a",
"index": 2313,
"step-1": "<mask token>\n\n\ndef fetch_logs():\n item_in_location_list = os.listdir(logs_location)\n content_path_list = list(map(lambda log: logs_location + log,\n item_in_location_list))\n text_file_list = list(filter(lambda... | [
4,
6,
8,
9,
10
] |
from helper.logger_helper import Log
from helper.mail_helper import MailHelper
import spider.spider as spider
from configuration.configuration_handler import Configuration
from configuration.products_handler import ProductsHandler
if __name__ == "__main__":
logger = Log()
conf = Configuration('configuration/co... | normal | {
"blob_id": "2e140d1174e0b2d8a97df880b1bffdf84dc0d236",
"index": 1029,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n logger = Log()\n conf = Configuration('configuration/configuration.yaml'\n ).load_configuration()\n ph = ProductsHandler(conf['products_path']... | [
0,
1,
2,
3
] |
s = input()
if len(s) < 26:
for i in range(26):
c = chr(ord("a")+i)
if c not in s:
print(s+c)
exit()
else:
for i in reversed(range(1,26)):
if s[i-1] < s[i]:
s1 = s[0:i-1]
for j in range(26):
c = chr(ord("a")+j)
... | normal | {
"blob_id": "9931fc25118981bcce80cffd3fda9dc99d951bf5",
"index": 180,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif len(s) < 26:\n for i in range(26):\n c = chr(ord('a') + i)\n if c not in s:\n print(s + c)\n exit()\nelse:\n for i in reversed(range(1, 26)):\n... | [
0,
1,
2,
3
] |
"""
Given a 2D binary matrix filled with 0's and 1's, find the largest square containing only 1's and return its area.
Example:
Input:
1 0 1 0 0
1 0 1 1 1
1 1 1 1 1
1 0 0 1 0
Output: 4
"""
# 196ms. 98 percentile
class Solution:
def maximalSquare(self, matrix: List[List[str]]) -> int:
if not matrix:
... | normal | {
"blob_id": "e5d31a2ea4a8615d24626be2414f5ae49b9cd6a1",
"index": 184,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Solution:\n <mask token>\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\nclass Solution:\n\n def maximalSquare(self, matrix: List[List[str]]) ->int:\n if not ma... | [
0,
1,
2,
3
] |
import cv2
import numpy as np
cap = cv2.VideoCapture("./vStream.h264")
count = 0
while True:
ret, frame = cap.read()
if ret:
print("Decoded frame")
# cv2.imshow("frame", frame)
cv2.imwrite("fr_"+str(count)+".png", frame)
count += 1
else:
print("Couldn\'t decoded fra... | normal | {
"blob_id": "40ac3292befa2354878927ada0e10c24368a9d73",
"index": 2643,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile True:\n ret, frame = cap.read()\n if ret:\n print('Decoded frame')\n cv2.imwrite('fr_' + str(count) + '.png', frame)\n count += 1\n else:\n prin... | [
0,
1,
2,
3,
4
] |
import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import minimize
from scipy.stats import chisquare, chi2, binom, poisson
def f_1(x, a):
return (1 / (x + 5)) * np.sin(a * x)
def f_2(x, a):
return np.sin(a * x) + 1
def f_3(x, a):
return np.sin(a * (x ** 2))
def f_4(x, a):
ret... | normal | {
"blob_id": "27edc753ebb9d60715a2ffa25d77e69ef363d010",
"index": 3568,
"step-1": "<mask token>\n\n\ndef f_1(x, a):\n return 1 / (x + 5) * np.sin(a * x)\n\n\ndef f_2(x, a):\n return np.sin(a * x) + 1\n\n\ndef f_3(x, a):\n return np.sin(a * x ** 2)\n\n\n<mask token>\n\n\ndef f_5(x):\n return x * np.tan... | [
6,
9,
12,
13,
14
] |
N,T=map(int,input().split())
nm=1000000
for i in range(N):
c,t=map(int,input().split())
if nm>c and T>=t:
nm=c
if nm==1000000:
print("TLE")
else:
print(nm)
| normal | {
"blob_id": "8a0e781f29c426161240e33b9d2adc7537b3d352",
"index": 2513,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(N):\n c, t = map(int, input().split())\n if nm > c and T >= t:\n nm = c\nif nm == 1000000:\n print('TLE')\nelse:\n print(nm)\n",
"step-3": "N, T = map(... | [
0,
1,
2,
3
] |
#implement variable!
import numpy as np
class Variable:
def __init__(self, data):
self.data = data
class Function:
'''
Base class
specific functions are implemented in the inherited class
'''
def __call__(self, input):
x = input.data #data extract
y = self.foward(x)
... | normal | {
"blob_id": "9efd83524ebb598f30c8fb6c0f9f0c65333578e6",
"index": 6292,
"step-1": "<mask token>\n\n\nclass Function:\n <mask token>\n <mask token>\n\n def foward(self, x):\n raise NotImplementedError()\n\n\nclass Square(Function):\n\n def foward(self, x):\n return x ** 2\n\n\nclass Exp(F... | [
6,
10,
11,
12,
14
] |
from django.core.paginator import Paginator, EmptyPage
from django.shortcuts import render
from django.views import View
from django.contrib.auth.mixins import LoginRequiredMixin
from logging import getLogger
from django_redis import get_redis_connection
from decimal import Decimal
import json
from django import http
f... | normal | {
"blob_id": "0402096f215ae600318d17bc70e5e3067b0a176b",
"index": 3864,
"step-1": "<mask token>\n\n\nclass OrderSuccessView(LoginRequiredMixin, View):\n \"\"\"订单成功页面\"\"\"\n\n def get(self, request):\n \"\"\"提供订单成功页面\"\"\"\n order_id = request.GET.get('order_id')\n payment_amount = requ... | [
9,
16,
17,
19,
22
] |
import math #h=g^x
h=input("h: ")
g=input("g: ")
p=input("p: ")
m=math.ceil(math.sqrt(p))
m=int(m)
aj=[0]*m
for i in range(m):
aj[i]=pow(g,i*m)
ainvm=pow(g,p-2,p)
gamma = h
for i in range(m):
if gamma in aj:
j = aj.index(gamma)
print (j*m)+i
break
gamma=(gamma*ainvm)%p
| normal | {
"blob_id": "94439ffe3303f5efe15562f26d693e1e7a8115df",
"index": 2009,
"step-1": "import math #h=g^x\nh=input(\"h: \")\ng=input(\"g: \")\np=input(\"p: \")\nm=math.ceil(math.sqrt(p))\nm=int(m)\naj=[0]*m\nfor i in range(m):\n aj[i]=pow(g,i*m)\nainvm=pow(g,p-2,p)\ngamma = h\nfor i in range(m):\n if gamma in ... | [
0
] |
# coding=utf-8
# *** WARNING: this file was generated by the Pulumi SDK Generator. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import copy
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from .. import _ut... | normal | {
"blob_id": "8535020e7157699310b3412fe6c5a28ee8e61f49",
"index": 6911,
"step-1": "<mask token>\n\n\n@pulumi.output_type\nclass ApplicationCredential(dict):\n <mask token>\n\n def __getitem__(self, key: str) ->Any:\n ApplicationCredential.__key_warning(key)\n return super().__getitem__(key)\n ... | [
10,
11,
12,
13,
16
] |
student = []
while True:
name = str(input('Name: ')).capitalize().strip()
grade1 = float(input('Grade 1: '))
grade2 = float(input('Grade 2: '))
avgrade = (grade1 + grade2) / 2
student.append([name, [grade1, grade2], avgrade])
resp = ' '
while resp not in 'NnYy':
resp = str(input('Ano... | normal | {
"blob_id": "74028a7b317c02c90603ad24c1ddb35a1d5d0e9d",
"index": 8678,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile True:\n name = str(input('Name: ')).capitalize().strip()\n grade1 = float(input('Grade 1: '))\n grade2 = float(input('Grade 2: '))\n avgrade = (grade1 + grade2) / 2\n ... | [
0,
1,
2,
3
] |
def merge_the_tools(string, k):
# your code goes here
num_sub_strings = len(string)/k
#print num_sub_strings
for idx in range(num_sub_strings):
print "".join(set(list(string[idx * k : (idx + 1) * k])))
| normal | {
"blob_id": "e95bda8be2294c295d89f1c035bc209128fa29c8",
"index": 228,
"step-1": "def merge_the_tools(string, k):\n # your code goes here\n num_sub_strings = len(string)/k\n #print num_sub_strings\n\n for idx in range(num_sub_strings):\n print \"\".join(set(list(string[idx * k : (idx + 1) * k])... | [
0
] |
class Formater():
def clean_number (posible_number):
sanitize_number = posible_number.replace(' ', '')
number_of_dots = sanitize_number.count('.')
if number_of_dots > 1:
return None
if number_of_dots == 1:
dot_position = sanitize_number.index('.')
... | normal | {
"blob_id": "02c32cf04529ff8b5edddf4e4117f8c4fdf27da9",
"index": 8612,
"step-1": "<mask token>\n",
"step-2": "class Formater:\n <mask token>\n",
"step-3": "class Formater:\n\n def clean_number(posible_number):\n sanitize_number = posible_number.replace(' ', '')\n number_of_dots = sanitize... | [
0,
1,
2,
3
] |
# -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2018-05-16 12:24
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('main', '0036_auto_20180516_1818'),
]
operations = [
migrations.AddField(
... | normal | {
"blob_id": "a7add26a919a41e52ae41c6b4c4079eadaa8aa1d",
"index": 851,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Migration(migrations.Migration):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Migration(migrations.Migration):\n dependencies = [('main', '0036... | [
0,
1,
2,
3,
4
] |
import ambulance_game as abg
import numpy as np
import sympy as sym
from sympy.abc import a, b, c, d, e, f, g, h, i, j
def get_symbolic_pi(num_of_servers, threshold, system_capacity, buffer_capacity):
Q_sym = abg.markov.get_symbolic_transition_matrix(
num_of_servers=num_of_servers,
threshold=thres... | normal | {
"blob_id": "9dd59fee46bd4bec87cc8c40099110b483ad0496",
"index": 6990,
"step-1": "<mask token>\n\n\ndef get_symbolic_state_probabilities_1222():\n num_of_servers = 1\n threshold = 2\n system_capacity = 2\n buffer_capacity = 2\n sym_pi_1222 = get_symbolic_pi(num_of_servers=num_of_servers, threshold... | [
5,
12,
13,
16,
17
] |
import matplotlib
matplotlib.use('TkAgg')
import matplotlib.pyplot as plt
import numpy as np
import struct
import wave
scale = 0.01
wav = wave.open('output.wav', 'r')
print 'channels %d'%wav.getnchannels()
print 'smpl width %d'%wav.getsampwidth()
print 'frame rate %f'%wav.getframerate()
nframes = wav.getnframes()
pri... | normal | {
"blob_id": "c105f06e302740e9b7be100df905852bb5610a2c",
"index": 49,
"step-1": "import matplotlib\nmatplotlib.use('TkAgg')\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport struct\nimport wave\n\nscale = 0.01\nwav = wave.open('output.wav', 'r')\n\nprint 'channels %d'%wav.getnchannels()\nprint 'smpl wi... | [
0
] |
import os
import glob
import pandas as pd
import xml.etree.ElementTree as ET
import argparse
import numpy as np
def run(path, output):
#xml_df = xml_to_csv(path)
#xml_df.to_csv(output, index=None)
# for filename in os.listdir(path):
# base_file, ext = os.path.splitext(filename)
# print(bas... | normal | {
"blob_id": "26d14bc74d893f6f14ee7405280f4af41854c544",
"index": 141,
"step-1": "<mask token>\n\n\ndef run(path, output):\n for xml_file in glob.glob(path + '/*.xml'):\n tree = ET.parse(xml_file)\n root = tree.getroot()\n base_file, ext = os.path.splitext(root.find('filename').text)\n ... | [
1,
2,
3,
4,
5
] |
__author__ = 'anderson'
from pyramid.security import Everyone, Allow, ALL_PERMISSIONS
class Root(object):
#Access Control List
__acl__ = [(Allow, Everyone, 'view'),
(Allow, 'role_admin', ALL_PERMISSIONS),
(Allow, 'role_usuario', 'comum')]
def __init__(self, request):
... | normal | {
"blob_id": "5ee2a51ea981f0feab688d9c571620a95d89a422",
"index": 6980,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Root(object):\n <mask token>\n\n def __init__(self, request):\n pass\n",
"step-3": "__author__ = 'anderson'\n<mask token>\n\n\nclass Root(object):\n __acl__ = ... | [
0,
2,
4,
5,
6
] |
print("n:",end="")
n=int(input())
print("a:",end="")
a=list(map(int,input().split()))
ans=0
for i in range(n):
for j in range(i+1,n):
for k in range(j+1,n):
ai,aj,ak=sorted([a[i],a[j],a[k]])
if(ai+aj>ak and ai+aj+ak>ans):
ans=ai+aj+ak
print(ans) | normal | {
"blob_id": "130f49028833bf57d7e4f9fbb0764801c3508c3b",
"index": 3055,
"step-1": "<mask token>\n",
"step-2": "print('n:', end='')\n<mask token>\nprint('a:', end='')\n<mask token>\nfor i in range(n):\n for j in range(i + 1, n):\n for k in range(j + 1, n):\n ai, aj, ak = sorted([a[i], a[j], ... | [
0,
1,
2,
3
] |
import os
from NeuralEmulator.Configurators.NormalLeakSourceConfigurator import NormalLeakSourceConfigurator
from NeuralEmulator.Configurators.OZNeuronConfigurator import OZNeuronConfigurator
from NeuralEmulator.Configurators.PulseSynapseConfigurator import PulseSynapseConfigurator
from NeuralEmulator.NormalLeakS... | normal | {
"blob_id": "177401f25471cf1cbd32dd0770acdc12bf271361",
"index": 8030,
"step-1": "<mask token>\n\n\nclass NeuronsGenerator:\n\n def __init__(self, neuronsNumber, synapse, lowerBound=100.0 * 10 ** -3,\n upperBound=800.0 * 10 ** -3, randomVals=False):\n noramalLeakSourceConfigurator = NormalLeakSo... | [
3,
4,
5,
6,
7
] |
import pygame
class BackGround:
def __init__(self, x, y):
self.y = y
self.x = x
def set_image(self, src):
self.image = pygame.image.load(src)
self.rect = self.image.get_rect()
self.rect.y = self.y
self.rect.x = self.x
def draw(self, screen):
scree... | normal | {
"blob_id": "071e3cf6b4337e0079bbb2c7694fff2468142070",
"index": 6505,
"step-1": "<mask token>\n\n\nclass BackGround:\n\n def __init__(self, x, y):\n self.y = y\n self.x = x\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass BackGround:\n\n def __init__(self, x, y):\... | [
2,
3,
4,
5
] |
# -*- coding: utf-8 -*-
# @Author: Marcela Campo
# @Date: 2016-05-06 18:56:47
# @Last Modified by: Marcela Campo
# @Last Modified time: 2016-05-06 19:03:21
import os
from flask.ext.script import Manager
from flask.ext.migrate import Migrate, MigrateCommand
from server import app, db
app.config.from_object('confi... | normal | {
"blob_id": "d7b91b0476a1f2e00408ce1f1501bf98d4c06e4e",
"index": 9540,
"step-1": "<mask token>\n",
"step-2": "<mask token>\napp.config.from_object('config.DevelopmentConfig')\n<mask token>\nmanager.add_command('db', MigrateCommand)\nif __name__ == '__main__':\n manager.run()\n",
"step-3": "<mask token>\na... | [
0,
1,
2,
3,
4
] |
n = int(input("Please input the number of 1's and 0's you want to print:"))
for i in range (1, n+1):
if i%2 == 1:
print ("1 ", end = "")
else:
print ("0 ", end = "") | normal | {
"blob_id": "bd96b31c5de2f0ad4bbc28c876b86ec238db3184",
"index": 9108,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(1, n + 1):\n if i % 2 == 1:\n print('1 ', end='')\n else:\n print('0 ', end='')\n",
"step-3": "n = int(input(\"Please input the number of 1's and 0's ... | [
0,
1,
2,
3
] |
"""added Trail.Geometry without srid
Revision ID: 56afb969b589
Revises: 2cf6c7c1f0d7
Create Date: 2014-12-05 18:13:55.512637
"""
# revision identifiers, used by Alembic.
revision = '56afb969b589'
down_revision = '2cf6c7c1f0d7'
from alembic import op
import sqlalchemy as sa
import flask_admin
import geoalchemy2
de... | normal | {
"blob_id": "d724b4f57cf7683d6b6385bf991ed23a5dd8208f",
"index": 3881,
"step-1": "<mask token>\n\n\ndef upgrade():\n with op.batch_alter_table('trail', schema=None) as batch_op:\n batch_op.add_column(sa.Column('geom', geoalchemy2.types.Geometry(\n geometry_type='MULTILINESTRING'), nullable=T... | [
1,
2,
3,
4,
5
] |
default_app_config = 'teacher.apps.A1Config'
| normal | {
"blob_id": "c466c7e05608b1fbba5eea5bec16d301cee3688f",
"index": 9817,
"step-1": "<mask token>\n",
"step-2": "default_app_config = 'teacher.apps.A1Config'\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
## @file
# Contains several utilitities shared by migration tools.
#
# Copyright (c) 2007 - 2014, Intel Corporation. All rights reserved.<BR>
# This program and the accompanying materials
# are licensed and made available under the terms and conditions of the BSD License
# which accompanies this distribution. The full... | normal | {
"blob_id": "2dbb1051b35898288db629fd0c5b3887c429e9b8",
"index": 1313,
"step-1": "<mask token>\n\n\ndef SetCommon(Common, XmlCommon):\n XmlTag = 'Usage'\n Common.Usage = XmlAttribute(XmlCommon, XmlTag).split()\n XmlTag = 'FeatureFlag'\n Common.FeatureFlag = XmlAttribute(XmlCommon, XmlTag)\n XmlTag... | [
11,
18,
20,
21,
23
] |
import sys
import os
# Module "sys"
#
# See docs for the sys module: https://docs.python.org/3.7/library/sys.html
# Print out the command line arguments in sys.argv, one per line:
# Print out the plaform from sys:
# for arg in sys.argv:
# print(arg)
# Print out the Python version from sys:print(sys.platform)
... | normal | {
"blob_id": "3fed96e9bedb157a14cf9c441de5aae8b4f6edc8",
"index": 8664,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('platform: ' + sys.platform + '\\n' + 'maxsize: ' + str(sys.maxsize) +\n '\\n' + 'argv: ' + str(sys.argv))\nprint('Process ID: ' + str(os.getpid()) + '\\n' + 'cwd: ' + os.getcwd(... | [
0,
1,
2,
3
] |
# -*- coding: utf-8 -*-
# Generated by Django 1.11.8 on 2018-04-12 12:37
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('cstasker', '0001_initial'),
]
operations = [
migrations.AlterField(
... | normal | {
"blob_id": "2fbf312e1f8388008bb9ab9ba0ee4ccee1a8beae",
"index": 3594,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Migration(migrations.Migration):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Migration(migrations.Migration):\n dependencies = [('cstasker', ... | [
0,
1,
2,
3,
4
] |
Python 3.6.8 (tags/v3.6.8:3c6b436a57, Dec 24 2018, 00:16:47) [MSC v.1916 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license()" for more information.
>>> import turtle
turtle.setup(650,350,200,200)
turtle.penup()
turtle.fd(-250)
turtle.pendown() ... | normal | {
"blob_id": "e069ad88b5173e5859f1b01b9fb45951d1e82593",
"index": 4280,
"step-1": "Python 3.6.8 (tags/v3.6.8:3c6b436a57, Dec 24 2018, 00:16:47) [MSC v.1916 64 bit (AMD64)] on win32\nType \"help\", \"copyright\", \"credits\" or \"license()\" for more information.\n>>> import turtle \nturtle.setup(65... | [
0
] |
# -*- coding: utf-8 -*-
# @Time : 2018/12/13 21:32
# @Author : sundongjian
# @Email : xiaobomentu@163.com
# @File : __init__.py.py
# @Software: PyCharm | normal | {
"blob_id": "00ec56420831d8f4ab14259c7b07f1be0bcb7d78",
"index": 9161,
"step-1": "# -*- coding: utf-8 -*-\r\n# @Time : 2018/12/13 21:32\r\n# @Author : sundongjian\r\n# @Email : xiaobomentu@163.com\r\n# @File : __init__.py.py\r\n# @Software: PyCharm",
"step-2": null,
"step-3": null,
"step-4": null,... | [
1
] |
# Copyright (c) 2012 - Samuel Loretan <tynril at gmail.com>
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modi... | normal | {
"blob_id": "109a0ba0952bd5923ecbefa41556de7aa9f9eea8",
"index": 4197,
"step-1": "# Copyright (c) 2012 - Samuel Loretan <tynril at gmail.com>\n#\n# Permission is hereby granted, free of charge, to any person obtaining a copy\n# of this software and associated documentation files (the \"Software\"), to deal\n# in... | [
0
] |
import torch
from torch import nn
import pytorch_ssim
class Custom_Loss_for_Autoencoder(nn.Module):
def __init__(self, window_size=6):
super(Custom_Loss_for_Autoencoder, self).__init__()
self.ssim = pytorch_ssim.SSIM(window_size=window_size)
self.mse = nn.MSELoss()
def forward(self, ... | normal | {
"blob_id": "ce3e2aa2534bb404b45202bcb76e9d07080560cb",
"index": 2739,
"step-1": "<mask token>\n\n\nclass Custom_Loss_for_Autoencoder(nn.Module):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Custom_Loss_for_Autoencoder(nn.Module):\n <mask token>\n\n def forward(self, reconst... | [
1,
2,
3,
4
] |
from flask import Flask
from flask import render_template
from flask import make_response
import json
from lib import powerswitch
app = Flask(__name__)
@app.route('/')
def hello_world():
return render_template('index.html')
@app.route('/on/')
def on():
state = powerswitch.on()
return json.dumps(state)
... | normal | {
"blob_id": "18d3f58048b7e5d792eb2494ecc62bb158ac7407",
"index": 254,
"step-1": "<mask token>\n\n\n@app.route('/')\ndef hello_world():\n return render_template('index.html')\n\n\n<mask token>\n\n\n@app.route('/off/')\ndef off():\n state = powerswitch.off()\n return json.dumps(state)\n\n\n@app.route('/to... | [
4,
6,
7,
8,
9
] |
import subprocess
import glob
import os
import time
import sys
import xml.etree.ElementTree as ET
import getpass
import psutil
if len(sys.argv)==1:
photoscanname = r"C:\Program Files\Agisoft\PhotoScan Pro\photoscan.exe"
scriptname = r"C:\Users\slocumr\github\SimUAS\batchphotoscan\agiproc.py"
#xmlnames ... | normal | {
"blob_id": "00f95733505b3e853a76bbdd65439bcb230fa262",
"index": 3345,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif len(sys.argv) == 1:\n photoscanname = 'C:\\\\Program Files\\\\Agisoft\\\\PhotoScan Pro\\\\photoscan.exe'\n scriptname = (\n 'C:\\\\Users\\\\slocumr\\\\github\\\\SimUAS\\\\... | [
0,
1,
2,
3,
4
] |
"""
-*- coding:utf-8 -*-
@ Time : 14:05
@ Name : handle_ini_file.py
@ Author : xiaoyin_ing
@ Email : 2455899418@qq.com
@ Software : PyCharm
...
"""
from configparser import ConfigParser
from Common.handle_path import conf_dir
import os
class HandleConfig(ConfigParser):
def __init__(self, ini_... | normal | {
"blob_id": "01e60123ad87d9ff49812fe3a6f5d55bc85921c5",
"index": 4071,
"step-1": "<mask token>\n\n\nclass HandleConfig(ConfigParser):\n\n def __init__(self, ini_file_neme):\n super().__init__()\n self.ini_file_neme = ini_file_neme\n\n def red_conf__(self):\n file_path = os.path.join(co... | [
3,
4,
5,
6,
7
] |
class Rect():
def __init__(self, w, h):
self.w = w
self.h = h
def half(self):
return self.w / 2;
bricks = [Rect(40, 25), Rect(30, 25), Rect(28, 25), Rect(13, 25)]
def setup():
size(500, 500)
noLoop()
def draw():
posx = 0
posy = 0
i = 0
for... | normal | {
"blob_id": "807f0094a9736abdfa3f5b629615a80f1e0d13ef",
"index": 3037,
"step-1": "class Rect:\n\n def __init__(self, w, h):\n self.w = w\n self.h = h\n\n def half(self):\n return self.w / 2\n\n\n<mask token>\n\n\ndef setup():\n size(500, 500)\n noLoop()\n\n\n<mask token>\n",
"s... | [
4,
5,
6,
7,
8
] |
# -*- coding: utf-8 -*-
from __future__ import absolute_import, division, unicode_literals
import urllib
def normalize_mac_address(address):
return address.lower().replace("-", ":")
def urlencode(s):
return urllib.quote(s.encode("utf-8"), "")
def urlencode_plus(s):
return urllib.quote_plus(s.encode("... | normal | {
"blob_id": "33b8baf2ca819315eaa5f16c7986390acb4d6efd",
"index": 878,
"step-1": "<mask token>\n\n\ndef normalize_mac_address(address):\n return address.lower().replace('-', ':')\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef normalize_mac_address(address):\n return address.lower().replace('-', ':... | [
1,
2,
3,
4,
5
] |
TTTSIZE = 4
def who_win_line(line):
elements = set(line)
if '.' in elements:
return '.'
elements.discard('T')
if len(elements) >= 2:
return 'D'
else:
return elements.pop()
def who_win_tic_tac_toe(original_rows):
#print('%s' % repr(original_rows))
board... | normal | {
"blob_id": "2e041e33b5c34c2bddc72b36ff641817f1e21db2",
"index": 3735,
"step-1": "<mask token>\n\n\ndef who_win_line(line):\n elements = set(line)\n if '.' in elements:\n return '.'\n elements.discard('T')\n if len(elements) >= 2:\n return 'D'\n else:\n return elements.pop()\n... | [
2,
3,
4,
5,
6
] |
from django.urls import path
from .views import (
TreeCreateView,
TreeListView,
TreeUpdateView,
)
app_name = 'trees'
urlpatterns = [
path('list/', TreeListView.as_view(),
name='list'),
path('create/', TreeCreateView.as_view(),
name='create'),
path('<int:pk>/update/', TreeCreat... | normal | {
"blob_id": "0c1de2c1eb5a4de7aeb14ad6b27aa61e07bc4c51",
"index": 602,
"step-1": "<mask token>\n",
"step-2": "<mask token>\napp_name = 'trees'\nurlpatterns = [path('list/', TreeListView.as_view(), name='list'), path(\n 'create/', TreeCreateView.as_view(), name='create'), path(\n '<int:pk>/update/', TreeCr... | [
0,
1,
2,
3
] |
import json
import requests
import boto3
import uuid
import time
profile_name = 'mine'
region = 'us-west-2'
session = boto3.Session(profile_name=profile_name)
api = session.client('apigateway', region_name=region)
cf = session.client('cloudformation', region_name=region)
def get_key(name_of_key):
print('Discover... | normal | {
"blob_id": "10fda09f47c292cb3dc901f42d38ead7757460f5",
"index": 3699,
"step-1": "<mask token>\n\n\ndef get_key(name_of_key):\n print('Discovering API Key')\n response = api.get_api_keys(includeValues=True)\n items = response['items']\n for item in items:\n if name_of_key in item['name']:\n ... | [
3,
4,
5,
6,
7
] |
# OpenWeatherMap API Key
api_key = "078c8443640961d5ce547c8269db5fd7"
| normal | {
"blob_id": "4eb3d94a5fd22fc29000ec32475de9cbae1c183a",
"index": 5255,
"step-1": "<mask token>\n",
"step-2": "api_key = '078c8443640961d5ce547c8269db5fd7'\n",
"step-3": "# OpenWeatherMap API Key\napi_key = \"078c8443640961d5ce547c8269db5fd7\"\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
... | [
0,
1,
2
] |
import random
OPTIONS = ['rock', 'paper', 'scissors']
def get_human_choice():
print('(1) Rock\n(2) Paper\n(3) Scissors')
return OPTIONS[int(input('Enter the number of your choice: ')) - 1]
def get_computer_choice():
return random.choice(OPTIONS)
def print_choices(human_choice, computer_choice):
pr... | normal | {
"blob_id": "2e6bce05c8ba21aa322e306d2cdb8871531d7341",
"index": 5499,
"step-1": "<mask token>\n\n\ndef get_human_choice():\n print('(1) Rock\\n(2) Paper\\n(3) Scissors')\n return OPTIONS[int(input('Enter the number of your choice: ')) - 1]\n\n\ndef get_computer_choice():\n return random.choice(OPTIONS)... | [
6,
7,
8,
9
] |
# 运算符的优先级
# 和数学中一样，在Python运算也有优先级，比如先乘除 后加减
# 运算符的优先级可以根据优先级的表格来查询，
# 在表格中位置越靠下的运算符优先级越高，优先级越高的越优先计算
# 如果优先级一样则自左向右计算
# 关于优先级的表格，你知道有这么一个东西就够了，千万不要去记
# 在开发中如果遇到优先级不清楚的,则可以通过小括号来改变运算顺序
a = 1 + 2 * 3
# 一样 and高 or高
# 如果or的优先级高，或者两个运算符的优先级一样高
# 则需要先进行或运算，则运算结果是3
# 如果and的优先级高，则应该先计算与运算
# 则运算结果是1
a = 1 or 2 and 3
... | normal | {
"blob_id": "25550cbaf6e0e5bdbbe3852bb8cdc05ac300d315",
"index": 8872,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(result)\n",
"step-3": "a = 1 + 2 * 3\na = 1 or 2 and 3\nresult = 1 < 2 < 3\nresult = 10 < 20 > 15\nprint(result)\n",
"step-4": "# 运算符的优先级\n# 和数学中一样，在Python运算也有优先级，比如先乘除 后加减\n# 运... | [
0,
1,
2,
3
] |
import os
import pickle
from matplotlib import pyplot as plt
cwd = os.path.join(os.getcwd(), 'DEDA_2020SS_Crypto_Options_RND_HD',
'CrypOpt_RiskNeutralDensity')
data_path = os.path.join(cwd, 'data') + '/'
day = '2020-03-11'
res = pickle.load(open(data_path + 'results_{}.pkl'.format(day), 'rb'))
... | normal | {
"blob_id": "a01f812584e4cee14c9fe15e9fb6ede4ae3e937a",
"index": 4953,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor key, ax in zip(sorted(res), axes.flatten()):\n print(key, ax)\n ax.plot(res[key]['df'].M, res[key]['df'].iv, '.')\n ax.plot(res[key]['M'], res[key]['smile'])\n ax.text(0.9... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python
from __future__ import division
from __future__ import print_function
import numpy as np
from mpi4py import MPI
from parutils import pprint
comm = MPI.COMM_WORLD
pprint("-"*78)
pprint(" Running on %d cores" % comm.size)
pprint("-"*78)
comm.Barrier()
# Prepare a vector of N=5 elements to be ... | normal | {
"blob_id": "839b3ebffebce95de25f75edc67a647bd1318268",
"index": 5077,
"step-1": "<mask token>\n",
"step-2": "<mask token>\npprint('-' * 78)\npprint(' Running on %d cores' % comm.size)\npprint('-' * 78)\ncomm.Barrier()\n<mask token>\nif comm.rank == 0:\n A = np.arange(N, dtype=np.float64)\nelse:\n A = np... | [
0,
1,
2,
3,
4
] |
# ch14_26.py
fn = 'out14_26.txt'
x = 100
with open(fn, 'w') as file_Obj:
file_Obj.write(x) # 直接輸出數值x產生錯誤
| normal | {
"blob_id": "e4f07355300003943d2fc09f80746a1201de7e37",
"index": 1678,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open(fn, 'w') as file_Obj:\n file_Obj.write(x)\n",
"step-3": "fn = 'out14_26.txt'\nx = 100\nwith open(fn, 'w') as file_Obj:\n file_Obj.write(x)\n",
"step-4": "# ch14_26.py\... | [
0,
1,
2,
3
] |
"""Largest product in a series
Problem 8
The four adjacent digits in the 1000-digit number that have the greatest product
are 9 x 9 x 8 x 9 = 5832.
73167176531330624919225119674426574742355349194934
96983520312774506326239578318016984801869478851843
85861560789112949495459501737958331952853208805511
125406987471585238... | normal | {
"blob_id": "601d32bf30aa454bbc7d31d6ce4b7296cef0fdfe",
"index": 9374,
"step-1": "\"\"\"Largest product in a series\nProblem 8\nThe four adjacent digits in the 1000-digit number that have the greatest product\nare 9 x 9 x 8 x 9 = 5832.\n\n73167176531330624919225119674426574742355349194934\n9698352031277450632623... | [
0
] |
#Embedded file name: c:/depot/games/branches/release/EVE-TRANQUILITY/eve/client/script/paperDoll/SkinRaytracing.py
import trinity
import blue
import telemetry
import ctypes
import math
import time
import geo2
import struct
import itertools
import weakref
import uthread
import paperDoll as PD
import log
import random
my... | normal | {
"blob_id": "3c01ca27a5eef877b606b93b04ffe6f73168cd6b",
"index": 9090,
"step-1": "#Embedded file name: c:/depot/games/branches/release/EVE-TRANQUILITY/eve/client/script/paperDoll/SkinRaytracing.py\nimport trinity\nimport blue\nimport telemetry\nimport ctypes\nimport math\nimport time\nimport geo2\nimport struct\... | [
0
] |
import cv2
img = cv2.imread('Chapter1/resources/jacuzi.jpg')
imgGrey = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
imgCanny = cv2.Canny(img,240,250)
cv2.imshow("output",imgCanny)
cv2.waitKey(0) | normal | {
"blob_id": "292cfecb701ecc179381d4453063aff532a0e877",
"index": 8961,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ncv2.imshow('output', imgCanny)\ncv2.waitKey(0)\n",
"step-3": "<mask token>\nimg = cv2.imread('Chapter1/resources/jacuzi.jpg')\nimgGrey = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\nimgCanny ... | [
0,
1,
2,
3,
4
] |
km=float(input())
cg=float(input())
print(round(km/cg,3),"km/l") | normal | {
"blob_id": "db33f7386d1eacbfbfd29aa367df310c557ae864",
"index": 8520,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(round(km / cg, 3), 'km/l')\n",
"step-3": "km = float(input())\ncg = float(input())\nprint(round(km / cg, 3), 'km/l')\n",
"step-4": "km=float(input())\ncg=float(input())\nprint(r... | [
0,
1,
2,
3
] |
#!/usr/bin/python
#The MIT License (MIT)
#
#Copyright (c) 2015 Stephen P. Smith
#
#Permission is hereby granted, free of charge, to any person obtaining a copy
#of this software and associated documentation files (the "Software"), to deal
#in the Software without restriction, including without limitation the rights
#to... | normal | {
"blob_id": "5d92c68e0fe7f37d4719fb9ca4274b29ff1cbb43",
"index": 4699,
"step-1": "<mask token>\n\n\nclass max31865(object):\n <mask token>\n\n def __init__(self, csPin=8, misoPin=9, mosiPin=10, clkPin=11):\n self.csPin = csPin\n self.misoPin = misoPin\n self.mosiPin = mosiPin\n ... | [
8,
9,
11,
12,
14
] |
"""
Author: Alan Danque
Date: 20210323
Purpose:Final Data Wrangling, strips html and punctuation.
"""
from sklearn.tree import export_graphviz
import pydot
import pickle
from pathlib import Path
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from sklearn.ensemble import ... | normal | {
"blob_id": "b9678b447bc6e7c4e928ffa6b8cd58639e41a801",
"index": 2688,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nresults_dir.mkdir(parents=True, exist_ok=True)\n<mask token>\nprint(data.shape)\n<mask token>\nprint(\"\"\"\nDataFrame Shape :\"\"\", shape)\nprint(\"\"\"\nNumber of rows :\"\"\", shape[0... | [
0,
1,
2,
3,
4
] |
"""
Package for haasplugin.
"""
| normal | {
"blob_id": "20518302b6a67f8f1ac01f1adf4fe06ab2eaf280",
"index": 3098,
"step-1": "<mask token>\n",
"step-2": "\"\"\"\nPackage for haasplugin.\n\"\"\"\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
'''
Take list of iam users in a csv file like
S_NO, IAM_User_Name,Programatic_Access,Console_Access,PolicyARN
1,XYZ, Yes,No,arn:aws:iam::aws:policy/AdministratorAccess
2.pqr,Yes,Yes,arn:aws:iam::aws:policy/AdministratorAccess
3.abc,No,Yes,arn:aws:iam::aws:policy/AmazonAPIGatewayInvokeFullAccess
'''
import boto3,s... | normal | {
"blob_id": "00afab442f56d364c785324f816b52b4a6be609d",
"index": 3078,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile True:\n session = boto3.session.Session(profile_name='dev_root')\n iam_re = session.resource(service_name='iam')\n for each in range(701, 1100):\n try:\n ... | [
0,
1,
2,
3
] |
import rpy2.robjects as robjects
from rpy2.robjects.packages import importr
# print(robjects.__file__)
import sys
sys.path.append('./')
import importlib
import json
import os
from web_app.function.WordCould import word_img
# importlib.reload(sys)
# #sys.setdefaultencoding('gbk')
class Ubiquitination():
def __ini... | normal | {
"blob_id": "a6ae4324580a8471969e0229c02ea1670728f25b",
"index": 3767,
"step-1": "<mask token>\n\n\nclass Ubiquitination:\n <mask token>\n\n def load_R(self):\n pass\n\n def data_path(self, name):\n exp_path = './web_app/data/disease/exp_data/{}.txt'.format(name)\n clinical_path = '... | [
7,
8,
10,
12,
13
] |
import numpy as np
import pandas as pd
import logging
import matplotlib.pyplot as plt
from sklearn.impute import SimpleImputer
from sklearn.preprocessing import LabelEncoder, OneHotEncoder, StandardScaler, RobustScaler
from sklearn.compose import ColumnTransformer
from sklearn.pipeline import Pipeline, make_pipeline
f... | normal | {
"blob_id": "dc51ca86a49dbec6f714753782494f21d4b1591d",
"index": 9091,
"step-1": "<mask token>\n\n\ndef preprocess_data(train, test):\n global train_features, test_features, train_target, categorical, numerical\n train_features = train.drop(['Sales', 'Customers'], axis=1)\n train_target = train[['Sales'... | [
2,
3,
4,
5,
6
] |
'''
filter_items = lambda a : a[0] == 'b'
fruits = ["apple", "banana", "pear", "orange"]
result = filter(filter_items, fruits)
print(list(result))
'''
'''
Given a list of integers, return the even integers in the list.
input = [11, 4, 5, 8, 9, 2, 12]
output = [4, 8, 2, 12]
input = [3, 5, 7]
output = []
'''
# even_... | normal | {
"blob_id": "7d9032b2426dbf3c285b99efa78be38d8f76ec24",
"index": 1933,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(list(result))\n<mask token>\nprint(list(result))\n",
"step-3": "<mask token>\neven_integers = lambda a: a % 2 == 0\ninput = [11, 4, 5, 8, 9, 2, 12]\nresult = filter(even_integers,... | [
0,
1,
2,
3
] |
import discord
from app.vars.client import client
from app.helpers import delete, getUser, getGuild
@client.command()
async def inviteInfo(ctx, link):
try:
await delete.byContext(ctx)
except:
pass
linkData = await client.fetch_invite(url=link)
if (linkData.inviter):
inviterData... | normal | {
"blob_id": "b8f9633ab3110d00b2f0b82c78ad047fca0d3eee",
"index": 6999,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@client.command()\nasync def inviteInfo(ctx, link):\n try:\n await delete.byContext(ctx)\n except:\n pass\n linkData = await client.fetch_invite(url=link)\n ... | [
0,
1,
2,
3
] |
import collections
s = [('yellow', 1), ('blue', 2), ('yellow', 3), ('blue', 4), ('red', 1)]
d = collections.defaultdict(list)
d2 = {'test':121}
for k, v in s:
d[k].append(v)
d['test'].append('value')
print list(d.items())
print d
print d['blue']
print type(d)
print type(d2) | normal | {
"blob_id": "15a894e6f94fc62b97d1614a4213f21331ef12a0",
"index": 7843,
"step-1": "import collections\ns = [('yellow', 1), ('blue', 2), ('yellow', 3), ('blue', 4), ('red', 1)]\n\nd = collections.defaultdict(list)\nd2 = {'test':121}\nfor k, v in s:\n d[k].append(v)\n\nd['test'].append('value')\n\nprint list(d.i... | [
0
] |
# Ques1:
# To create a program that asks the user to enter their name and their age
# and prints out a message addressed to them that tells them the year that
# they will turn 100 years old. Additionally, the program asks the user for
# another number and prints out that many copies of the previous message on
... | normal | {
"blob_id": "948b793359555f98872e0bdbf6db970ed1ff3b83",
"index": 7046,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(msg * copies)\n",
"step-3": "<mask token>\nname = input('Enter your name : ')\nage = int(input('Enter your age : '))\nyear = int(100 - age + datetime.now().year)\ncopies = int(inp... | [
0,
1,
2,
3,
4
] |
from django import forms
from crawlr.models import Route, Category, UserProfile
from django.contrib.auth.models import User
class CategoryForm(forms.ModelForm):
name = forms.CharField(max_length=128,
help_text = "Please enter the category name.")
views = forms.IntegerField(widget=for... | normal | {
"blob_id": "abf25cf3d4435754b916fa06e5e887b1e3589a1c",
"index": 5073,
"step-1": "<mask token>\n\n\nclass RouteForm(forms.ModelForm):\n error_messages = {'duplicate_title':\n 'Please enter a unique name for the crawl'}\n title = forms.CharField(max_length=128, help_text=\n 'Please enter the n... | [
6,
7,
8,
9,
10
] |
from django.urls import path
from django.contrib.auth import views as auth_views
from . views import register, channel
urlpatterns = [
path('register/', register, name="register"),
path('channel/', channel, name="channel"),
path('login/', auth_views.LoginView.as_view(template_name='user/login.html'), name... | normal | {
"blob_id": "d76c1507594bb0c1ed7a83e6c5961097c7fbf54a",
"index": 9859,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('register/', register, name='register'), path(\n 'channel/', channel, name='channel'), path('login/', auth_views.\n LoginView.as_view(template_name='user/login.h... | [
0,
1,
2,
3
] |
from socketserver import StreamRequestHandler, TCPServer
from functools import partial
class EchoHandler(StreamRequestHandler):
def __init__(self, *args, ack, **kwargs):
self.ack = ack
super.__init__(*args, **kwargs)
def handle(self):
for line in self.rfile:
self.wfile.wri... | normal | {
"blob_id": "7819e41d567daabe64bd6eba62461d9e553566b3",
"index": 5393,
"step-1": "<mask token>\n\n\nclass EchoHandler(StreamRequestHandler):\n <mask token>\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass EchoHandler(StreamRequestHandler):\n\n def __init__(self, *args, ack, **kw... | [
1,
3,
5,
6,
7
] |
from layout import UIDump
import Tkinter
from Tkinter import *
from ScriptGenerator import ScriptGen
class Divide_and_Conquer():
def __init__(self, XY):
self.XY = XY
self.user_val = 'None'
self.flag = 'green'
print self.XY
def bounds_Compare(self, bounds, filename):
""" Compares the bounds with Master... | normal | {
"blob_id": "7a65a5522db97a7a113a412883b640feede5bcee",
"index": 909,
"step-1": "from layout import UIDump\nimport Tkinter \nfrom Tkinter import *\nfrom ScriptGenerator import ScriptGen\n\nclass Divide_and_Conquer():\n\n\tdef __init__(self, XY):\n\t\tself.XY = XY\n\t\tself.user_val = 'None'\n\t\tself.flag = 'gre... | [
0
] |
from django.shortcuts import render
from django.shortcuts import redirect
# Create your views here.
from .forms import AddBookForm ,UpdateBookForm,BookCreateModelForm,SearchForm,RegistrationForm,SignInForm
from book.models import Books
from django.contrib.auth import authenticate,login,logout
def book_add(reques... | normal | {
"blob_id": "aba2a0a262c14f286c278f21ba42871410c174f0",
"index": 953,
"step-1": "<mask token>\n\n\ndef book_add(request):\n if request.user.is_authenticated:\n context = {}\n if request.method == 'GET':\n form = BookCreateModelForm()\n context['form'] = form\n re... | [
4,
6,
7,
8,
10
] |
from discord.ext import commands, tasks
from discord.utils import get
import discord
import re
import json
import time
import random
import asyncio
import os
import datetime
from live_ticker_scrape import wrangle_data
from tokens import dev, dev1, es, nas, dow, us10y, dollar, vix, btc, eth, silver , link
es_bot = d... | normal | {
"blob_id": "e57109f1c5c2e1468ef1cf9f10fba743633ca150",
"index": 8094,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@es_bot.event\nasync def on_ready():\n print('es started')\n\n\n@nas_bot.event\nasync def on_ready():\n print('nas started')\n\n\n@dow_bot.event\nasync def on_ready():\n prin... | [
0,
1,
2,
3,
4
] |
import numpy as np
import matplotlib.pyplot as plt
def sigmoid(X):
""" Applies the logistic function to x, element-wise. """
return 1 / (1 + np.exp(-X))
def x_strich(X):
return np.column_stack((np.ones(len(X)), X))
def feature_scaling(X):
x_mean = np.mean(X, axis=0)
x_std = np.std(X, axis=0)
... | normal | {
"blob_id": "36e7398f576aa1d298a20b4d4a27a7b93e3bd992",
"index": 5482,
"step-1": "<mask token>\n\n\ndef sigmoid(X):\n \"\"\" Applies the logistic function to x, element-wise. \"\"\"\n return 1 / (1 + np.exp(-X))\n\n\ndef x_strich(X):\n return np.column_stack((np.ones(len(X)), X))\n\n\n<mask token>\n\n\n... | [
7,
9,
10,
11,
13
] |
def progress_format(user):
json = dict()
json["progres_id"] = user[0]
json["percentage"] = user[1]
json["user_id"] = user[2]
json["technology"] = user[3]
return json
def progresses_format(users):
json = dict()
json["users_progresses"] = list()
for user in users:
... | normal | {
"blob_id": "6ebf6bdfc6a4a1fe49f4eed1a2c1802f8adeef08",
"index": 1195,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef progresses_format(users):\n json = dict()\n json['users_progresses'] = list()\n for user in users:\n json['users_progresses'].append(progress_format(user))\n re... | [
0,
1,
2,
3,
4
] |
import sys
n = int(input())
min_number = sys.maxsize
max_number = -sys.maxsize
for i in range(0, n):
num = int(input())
if num > max_number:
max_number = num
if num < min_number:
min_number = num
print(f"Max number: {max_number}")
print(f"Min number: {min_number}") | normal | {
"blob_id": "ac6f2287390bdad8fe20cdc73c0063f685970cfb",
"index": 5289,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(0, n):\n num = int(input())\n if num > max_number:\n max_number = num\n if num < min_number:\n min_number = num\nprint(f'Max number: {max_number}')\n... | [
0,
1,
2,
3,
4
] |
import datetime
import subprocess
from time import sleep
from flask import render_template, redirect, request, url_for, flash, abort
from dirkules import app, db, scheduler, app_version
import dirkules.manager.serviceManager as servMan
import dirkules.manager.driveManager as driveMan
import dirkules.manager.cleaning as... | normal | {
"blob_id": "ab27780b19db6854855af51eea063f07d9eb7302",
"index": 3553,
"step-1": "<mask token>\n\n\n@app.errorhandler(500)\ndef internal_server_error(e):\n return render_template('500.html', error=str(e))\n\n\n<mask token>\n\n\n@app.route('/pools', methods=['GET'])\ndef pools():\n return render_template('p... | [
5,
8,
9,
11,
13
] |
#!/usr/bin/env python
import sys
import subprocess
import mystem
def run(args, fin=sys.stdin, fout=sys.stdout, ferr=sys.stderr, input_data=None):
'''\
Generic wrapper for MyStem
'''
mystem_path = mystem.util.find_mystem()
# make utf-8 a default encoding
if '-e' not in args:
args.exten... | normal | {
"blob_id": "d4a4ea67a06107ad7ea18bb21fb1ec9e74ccd7c1",
"index": 7187,
"step-1": "<mask token>\n\n\ndef main(args):\n return run(args)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef run(args, fin=sys.stdin, fout=sys.stdout, ferr=sys.stderr, input_data=None\n ):\n \"\"\" Generic wrapper for ... | [
1,
2,
3,
4,
5
] |
from collections import deque
def my_queue(n=5):
return deque([], n)
pass
if __name__ == '__main__':
mq = my_queue()
for i in range(10):
mq.append(i)
print((i, list(mq)))
"""Queue size does not go beyond n int, this outputs:
(0, [0])
(1, [0, 1])
(2, [0, 1, 2])
(3,... | normal | {
"blob_id": "499baaa8c739c1bd846edc944e510542d76bbed5",
"index": 9312,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef my_queue(n=5):\n return deque([], n)\n pass\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef my_queue(n=5):\n return deque([], n)\n pass\n\n\nif __name__ == '_... | [
0,
1,
2,
3
] |
import pandas as pd
import matplotlib.pyplot as plt
import math
import seaborn as sns
import numpy as np
suv_data=pd.read_csv("F:/Development/Machine Learning/suv-data/suv_data.csv")
print(suv_data.head(10))
print("the no of passengers in the list is"+str(len(suv_data.index)))
sns.countplot(x="Purchased",data=suv_data... | normal | {
"blob_id": "c955057d7f8d5289898ecb96a290f5a7d241b787",
"index": 6440,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(suv_data.head(10))\nprint('the no of passengers in the list is' + str(len(suv_data.index)))\nsns.countplot(x='Purchased', data=suv_data)\nsns.countplot(x='Purchased', hue='Gender', ... | [
0,
1,
2,
3,
4
] |
class Graph:
def __init__(self, num_vertices):
self.adj_list = {}
for i in range(num_vertices):
self.adj_list[i] = []
def add_vertice(self, source):
self.adj_list[source] = []
def add_edge(self, source, dest):
self.adj_list[source].append(dest)
def print_g... | normal | {
"blob_id": "ae5ec7919b9de4fbf578547c31837add32826f60",
"index": 7448,
"step-1": "class Graph:\n\n def __init__(self, num_vertices):\n self.adj_list = {}\n for i in range(num_vertices):\n self.adj_list[i] = []\n\n def add_vertice(self, source):\n self.adj_list[source] = []\n... | [
5,
6,
7,
8
] |
A,B=map(str,input().split())
if(A>B):
print(A)
elif(B>A):
print(B)
else:
print(AorB)
| normal | {
"blob_id": "8cbe78863de535a5b83eacebe67402569b4015fa",
"index": 9189,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif A > B:\n print(A)\nelif B > A:\n print(B)\nelse:\n print(AorB)\n",
"step-3": "A, B = map(str, input().split())\nif A > B:\n print(A)\nelif B > A:\n print(B)\nelse:\n ... | [
0,
1,
2,
3
] |
import requests
from requests.auth import HTTPBasicAuth
def __run_query(self, query):
URL = 'https://api.github.com/graphql'
request = requests.post(URL, json=query,auth=HTTPBasicAuth('gleisonbt', 'Aleister93'))
if request.status_code == 200:
return request.json()
else:
... | normal | {
"blob_id": "fa511411e59880fd80fba0ccc49c95d42cb4b78d",
"index": 6962,
"step-1": "<mask token>\n\n\ndef __run_query(self, query):\n URL = 'https://api.github.com/graphql'\n request = requests.post(URL, json=query, auth=HTTPBasicAuth('gleisonbt',\n 'Aleister93'))\n if request.status_code == 200:\n... | [
1,
2,
3,
4,
5
] |
from .score_funcs import *
from cryptonita.fuzzy_set import FuzzySet
from cryptonita.helpers import are_bytes_or_fail
def scoring(msg, space, score_func, min_score=0.5, **score_func_params):
''' Run the score function over the given message and over a parametric
value x. Return all the values x as a Fuzz... | normal | {
"blob_id": "99048ddb3f42382c8b8b435d832a45011a031cf1",
"index": 8537,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef scoring(msg, space, score_func, min_score=0.5, **score_func_params):\n \"\"\" Run the score function over the given message and over a parametric\n value x. Return all t... | [
0,
1,
2,
3
] |
import requests
import os
import numpy as np
from bs4 import BeautifulSoup
from nltk import word_tokenize
from collections import Counter
import random
from utils import save_pickle
root = 'data'
ratios = [('train', 0.85), ('valid', 0.05), ('test', 0.1)]
max_len = 64
vocab_size = 16000
data = []
path = os.path.joi... | normal | {
"blob_id": "977841e0bb73cec879fbb1868f1e64102c6d8c1a",
"index": 2119,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor topic in topics:\n i += 1\n arts = os.listdir(os.path.join(path, topic))\n j = 0\n for art in arts:\n j += 1\n with open(os.path.join(path, topic, art), enco... | [
0,
1,
2,
3,
4
] |
import nltk
import A
from collections import defaultdict
from nltk.align import Alignment, AlignedSent
class BerkeleyAligner():
def __init__(self, align_sents, num_iter):
self.t, self.q = self.train(align_sents, num_iter)
# TODO: Computes the alignments for align_sent, using this model's parameters. Return... | normal | {
"blob_id": "bf40b516e202af14469cd4012597ba412e663f56",
"index": 5898,
"step-1": "import nltk\nimport A\nfrom collections import defaultdict\nfrom nltk.align import Alignment, AlignedSent\n\nclass BerkeleyAligner():\n\n def __init__(self, align_sents, num_iter):\n\tself.t, self.q = self.train(align_sents, num... | [
0
] |
#Opens the file that the user specifies
fileopen = open(input("Please enter the name of the file that you wish to open."), 'r')
#Reads the lines within the file and determines the length of the file
lines = fileopen.readlines()
count = len(lines)
#Count is how long the file is, so number is the index values basically... | normal | {
"blob_id": "258b28153124ce42578c9eede429354069d8a7d6",
"index": 2869,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile number < count:\n print(number, '.', lines[number])\n number = number + 1\nfileopen.close()\n",
"step-3": "fileopen = open(input(\n 'Please enter the name of the file tha... | [
0,
1,
2,
3
] |
if __name__ == '__main__':
import sys
import os.path
srcpath = sys.argv[1] if len(sys.argv) >= 1 else './'
verfn = sys.argv[2] if len(sys.argv) >= 2 else None
try :
with open(os.path.join(srcpath,'.svn/entries'),'r') as fp:
x = fp.read().s... | normal | {
"blob_id": "1ebf92cf40053e561b04a666eb1dd36f54999e2c",
"index": 7324,
"step-1": "\r\n\r\n\r\nif __name__ == '__main__':\r\n \r\n import sys\r\n import os.path\r\n \r\n srcpath = sys.argv[1] if len(sys.argv) >= 1 else './'\r\n verfn = sys.argv[2] if len(sys.argv) >= 2 else None\r\n \r\n t... | [
0
] |
"""
Created on 01/10/18.
Author: morgan
Copyright defined in text_classification/LICENSE.txt
"""
import torch
import torch.nn as nn
from torch.autograd import Variable
import torch.nn.functional as F
class RNNClassifier(nn.Module):
def __init__(self, batch_size, num_classes, hidden_size, vocab_size, embed_size, w... | normal | {
"blob_id": "41417e3ce52edf6aee432886bbab6d16ec5bc88d",
"index": 164,
"step-1": "<mask token>\n\n\nclass RNNClassifier(nn.Module):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass RNNClassifier(nn.Module):\n\n def __init__(self, batch_size, num_classes, hidden_size, vocab_size,\n ... | [
1,
2,
3,
4,
5
] |
#!/usr/bin/env python
'''
Usage:
dep_tree.py [-h] [-v] [-p P] [-m component_map]
repos_root top_dir [top_depfile]
Parse design dependency tree and generate build scripts and other useful files
positional arguments:
repos_root repository root
top_dir top level design directory
top_depfile ... | normal | {
"blob_id": "ccfc78ae430f835244e0618afdeebe960c868415",
"index": 6126,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main():\n lCommandLineArgs = CommandLineParser().parse()\n lPathmaker = Pathmaker(lCommandLineArgs.root, lCommandLineArgs.top,\n lCommandLineArgs.componentmap, lComma... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/python
# encoding:utf-8
from selenium.webdriver.common.by import By
import random
import basePage
# 门店入库button
stock_in = (By.XPATH, "//android.widget.TextView[contains(@text,'门店入库')]")
# 调拨入库button
transfer_in = (By.XPATH, "//android.widget.TextView[contains(@text,'调拨入库')]")
# 确认签收button
take_receive = (By... | normal | {
"blob_id": "d1b025ddbf7d0ad48ff92a098d074820a3eb35ed",
"index": 6723,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nstock_in = By.XPATH, \"//android.widget.TextView[contains(@text,'门店入库')]\"\ntransfer_in = By.XPATH, \"//android.widget.TextView[contains(@text,'调拨入库')]\"\ntake_receive = By.ID, '%s:id/tak... | [
0,
1,
2,
3
] |
import logging
from exceptions.invalid_api_usage import InvalidAPIUsage
from wgadget.endpoints.ep import EP
class EPInfoLight(EP):
NAME = 'info_light'
URL = '/info'
URL_ROUTE_PAR_PAYLOAD = '/'
URL_ROUTE_PAR_URL = '/actuatorId/<actuatorId>'
METHOD = 'GET'
ATTR_ACTUATOR_ID = 'actuatorId'
... | normal | {
"blob_id": "e5abab3f718bbbd25dcfc49290383203d53248c3",
"index": 9464,
"step-1": "<mask token>\n\n\nclass EPInfoLight(EP):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n",
"ste... | [
1,
3,
4,
6,
8
] |
# from mini_imagenet_dataloader import MiniImageNetDataLoader
import os
os.environ["KMP_DUPLICATE_LIB_OK"]="TRUE"
import matplotlib.pyplot as plt
import torch
import torch.nn as nn
from tqdm import tqdm
import torch.nn.functional as F
from torchmeta.utils.gradient_based import gradient_update_parameters
from libs.model... | normal | {
"blob_id": "e2a50fbd277ab868fbe71f9ff113a68a30b9f893",
"index": 2523,
"step-1": "<mask token>\n\n\ndef ModelConvMiniImagenet(out_features, hidden_size=84):\n return MetaConvModel(3, out_features, hidden_size=hidden_size,\n feature_size=5 * 5 * hidden_size)\n\n\n<mask token>\n",
"step-2": "<mask toke... | [
1,
2,
4,
5,
6
] |
import cv2
import numpy as np
img1 = cv2.imread('img0008.jpg')
img2 = cv2.imread('img0009.jpg')
#img3 = cv2.imread('img0009.jpg')
img3 = np.zeros(img1.shape)
iter = 51
def sumas(ux, uy, wx, wy, dx, dy, img_i, img_j):
suma = 0
x = ux - wx
y = uy - wy
while x < ux + wx:
while y < uy + wy:
... | normal | {
"blob_id": "749e6a1f807843c9e2591f51561174cc51668b11",
"index": 1588,
"step-1": "<mask token>\n\n\ndef sumas(ux, uy, wx, wy, dx, dy, img_i, img_j):\n suma = 0\n x = ux - wx\n y = uy - wy\n while x < ux + wx:\n while y < uy + wy:\n xdx = x + dx if x + dx < img1.shape[0] else x\n ... | [
2,
3,
4,
5,
6
] |
import urllib.request
def get_html(url):
"""
Returns the html of url or None if status code is not 200
"""
req = urllib.request.Request(
url,
headers={
'User-Agent': 'Python Learning Program',
'From': 'hklee310@gmail.com'
}
)
resp = urllib.reques... | normal | {
"blob_id": "4572e243f75ad92c04f5cdc0b454df7389183a6a",
"index": 3238,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_html(url):\n \"\"\"\n Returns the html of url or None if status code is not 200\n \"\"\"\n req = urllib.request.Request(url, headers={'User-Agent':\n 'Pytho... | [
0,
1,
2,
3
] |
import numpy as np
from .build_processing_chain import build_processing_chain
from collections import namedtuple
from pprint import pprint
def run_one_dsp(tb_data, dsp_config, db_dict=None, fom_function=None, verbosity=0):
"""
Run one iteration of DSP on tb_data
Optionally returns a value for optimizati... | normal | {
"blob_id": "efe2d6f5da36679b77de32d631cca50c2c1dd29e",
"index": 5170,
"step-1": "<mask token>\n\n\nclass ParGrid:\n <mask token>\n\n def __init__(self):\n self.dims = []\n\n def add_dimension(self, name, i_arg, value_strs, companions=None):\n self.dims.append(ParGridDimension(name, i_arg,... | [
11,
14,
16,
18,
19
] |
#!/usr/bin/python3
"""0. How many subs"""
def number_of_subscribers(subreddit):
"""return the number of subscribers from an Reddit API"""
import requests
resInf = requests.get("https://www.reddit.com/r/{}/about.json"
.format(subreddit),
headers={"Us... | normal | {
"blob_id": "db1e3a109af2db2c8794a7c9c7dfb0c2ccee5800",
"index": 932,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef number_of_subscribers(subreddit):\n \"\"\"return the number of subscribers from an Reddit API\"\"\"\n import requests\n resInf = requests.get('https://www.reddit.com/r/{}/... | [
0,
1,
2
] |
# -------------------------------------------
# Created by: jasper
# Date: 11/24/19
# --------------------------------------------
from os import path, mkdir
class IOHandler:
def __init__(self, directory, fName, data_instance):
"""Save the setup of a class instance or... | normal | {
"blob_id": "267276eab470b5216a2102f3e7616f7aecadcfe9",
"index": 9428,
"step-1": "<mask token>\n\n\nclass IOHandler:\n <mask token>\n\n def dump_data(self):\n \"\"\"save the data contained in data_instance, checking whether the\n directories already exist and asking whether to create them if ... | [
3,
4,
5,
6,
7
] |
from ctypes import *
import os
import sys
import time
import datetime
import subprocess
import RPi.GPIO as GPIO
from PIL import Image
from PIL import ImageDraw
from PIL import ImageFont
#import Adafruit_GPIO as GPIO
import Adafruit_GPIO.SPI as SPI
import ST7735 as TFT
import pigpio
# use BCM pin define
pin_meas = 24 ... | normal | {
"blob_id": "d250cc0aafdd48cb0eb56108d9c7148153cde002",
"index": 6840,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ntime.sleep(1)\n<mask token>\nif len(sys.argv) < 6:\n error_str = str(sys.argv[0]\n ) + ' led1_current led2_current led_stable_time int_time1 int_time2'\n print(error_str)\nel... | [
0,
1,
2,
3,
4
] |
#-*- coding: utf-8 -*-
#############################################################################
# #
# Copyright (c) 2008 Rok Garbas <rok@garbas.si> #
# ... | normal | {
"blob_id": "d0f9dd0a06023dd844b0bf70dff360f6bb46c152",
"index": 4412,
"step-1": "<mask token>\n\n\nclass MonthYearWidget(DateWidget):\n \"\"\" Month and year widget \"\"\"\n zope.interface.implementsOnly(IMonthYearWidget)\n klass = u'monthyear-widget'\n value = '', '', 1\n\n\n<mask token>\n",
"ste... | [
3,
4,
5,
6,
7
] |
import wx
from six import print_
import os
FONTSIZE = 10
class TextDocPrintout(wx.Printout):
"""
A printout class that is able to print simple text documents.
Does not handle page numbers or titles, and it assumes that no
lines are longer than what will fit within the page width. Those
features a... | normal | {
"blob_id": "2790bd80949bafe4e98ab9aca9cf80a6a0f31490",
"index": 6200,
"step-1": "<mask token>\n\n\nclass TextDocPrintout(wx.Printout):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\nclass PrintFrameworkSample(w... | [
10,
14,
16,
19,
22
] |
from accessor import *
from order import Order
from copy import deepcopy
import pandas as pd
import numpy as np
import util
class Broker:
def __init__(self, equity):
self.execute = Execute(equity) # Execute
def make_order(self, unit, limit_price, stop_loss, stop_profit):
ord... | normal | {
"blob_id": "ca0aedcfb997299240870649823fb872e0d9f99a",
"index": 6023,
"step-1": "<mask token>\n\n\nclass Broker:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def liquidation(self, pos, price, date, commission):\n \"\"\"\n clean the last position\... | [
9,
11,
12,
16,
17
] |
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