code stringlengths 13 1.2M | order_type stringclasses 1
value | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
a = [3, 4, 2, 3, 5, 8, 23, 32, 35, 34, 4, 6, 9]
print("")
print("Lesson #2")
print("Program start:")
for i in a:
if i < 9:
print(i)
print("End") | normal | {
"blob_id": "58f7810e2731721562e3459f92684589dc66862c",
"index": 881,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('')\nprint('Lesson #2')\nprint('Program start:')\nfor i in a:\n if i < 9:\n print(i)\nprint('End')\n",
"step-3": "a = [3, 4, 2, 3, 5, 8, 23, 32, 35, 34, 4, 6, 9]\nprint('... | [
0,
1,
2,
3
] |
import sys
if __name__ == '__main__':
cases = sys.stdin.readline()
for i in range(int(cases)):
sys.stdin.readline()
lineas, columnas = sys.stdin.readline().strip().split(" ")
lineas = int(lineas)
columnas = int(columnas)
list_lines = []
for linea in range(linea... | normal | {
"blob_id": "22909e41e4f9ad0280c22ec11ecfbccff87efae1",
"index": 1402,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n cases = sys.stdin.readline()\n for i in range(int(cases)):\n sys.stdin.readline()\n lineas, columnas = sys.stdin.readline().strip().split(... | [
0,
1,
2,
3
] |
"""MPI-supported kernels for computing diffusion flux in 2D."""
from sopht.numeric.eulerian_grid_ops.stencil_ops_2d import (
gen_diffusion_flux_pyst_kernel_2d,
gen_set_fixed_val_pyst_kernel_2d,
)
from sopht_mpi.utils.mpi_utils import check_valid_ghost_size_and_kernel_support
from mpi4py import MPI
def gen_dif... | normal | {
"blob_id": "ba8cb18544e4ded8b229bfb9cc4b28599119414f",
"index": 854,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef gen_diffusion_flux_pyst_mpi_kernel_2d(real_t, mpi_construct,\n ghost_exchange_communicator):\n diffusion_flux_pyst_kernel = gen_diffusion_flux_pyst_kernel_2d(real_t=\n ... | [
0,
1,
2,
3
] |
from django.urls import reverse_lazy
from django.views.generic import (
ListView,
DetailView,
CreateView,
UpdateView,
DeleteView,
)
from .models import Entry
class EntryListView(ListView):
model = Entry
queryset = Entry.objects.all().order_by("-date_created")
class EntryDetailView(Detai... | normal | {
"blob_id": "37c03732ae52171fc24aec85c940848b02d76dc1",
"index": 1176,
"step-1": "<mask token>\n\n\nclass EntryCreateView(CreateView):\n <mask token>\n <mask token>\n <mask token>\n\n\nclass EntryUpdateView(UpdateView):\n model = Entry\n fields = ['title', 'content']\n\n def get_success_url(sel... | [
6,
7,
10,
11,
13
] |
#!/usr/local/autopkg/python
"""
JamfScriptUploader processor for uploading items to Jamf Pro using AutoPkg
by G Pugh
"""
import os.path
import sys
from time import sleep
from autopkglib import ProcessorError # pylint: disable=import-error
# to use a base module in AutoPkg we need to add this path to the sys.pa... | normal | {
"blob_id": "35d99713df754052a006f76bb6f3cfe9cf875c0b",
"index": 3993,
"step-1": "<mask token>\n\n\nclass JamfScriptUploader(JamfUploaderBase):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass JamfScriptUploader(J... | [
1,
4,
5,
7,
8
] |
# Generated by Django 3.1.6 on 2021-05-06 10:29
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('core', '0028_auto_20210506_1020'),
]
operations = [
migrations.AlterField(
model_name='user',
... | normal | {
"blob_id": "39ac4e0d543048ea02123baa39b6c8ce7618d16b",
"index": 6802,
"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 = [('core', '002... | [
0,
1,
2,
3,
4
] |
import time
import datetime
import math
import os
import random
import logzero
import logging
from logzero import logger
from sense_hat import SenseHat
import ephem
anyException = False
# program Time is here for easy acces (in minutes)
programTime = 175
# 2:55 min of runtime
# _________________________... | normal | {
"blob_id": "05e468c2f64e33d6b390f681314ed7961bd4def7",
"index": 2684,
"step-1": "<mask token>\n\n\ndef setLoggingFile():\n \"\"\"\n This function will setup a logger and logfile\n \"\"\"\n try:\n dirPath = os.path.dirname(os.path.realpath(__file__))\n dirFiles = os.listdir(dirPath)\n ... | [
10,
12,
14,
15,
16
] |
# -*- coding: utf-8 -*-
#
# Copyright (C) 2015 Brandon Bennett <bennetb@gmail.com>
#
# Send a notification via notifyserver (https://github.com/nemith/notifyserver)
# on highlight/private message or new DCC.
#
# History:
#
# 2015-02-07, Brandon Bennett <bennetb@gmail.com>:
# version 0.1: initial release
#
SCRIPT... | normal | {
"blob_id": "0ae9ad7af26e3d19f2d3967c02611503c32aea70",
"index": 2593,
"step-1": "<mask token>\n\n\nclass Config(object):\n _DEFAULT = {'url': 'http://localhost:9999/notify', 'title':\n 'IRC Notification', 'activate_label': '', 'sound': ''}\n\n def __init__(self):\n self._opts = {}\n f... | [
5,
7,
9,
10,
12
] |
# Напишите программу, которая вводит с клавиатуры последовательность чисел и выводит её
# отсортированной в порядке возрастания.
def is_numb_val(val):
try:
x = float(val)
except ValueError:
return False
else:
return True
def main():
num_seq = input("Введите последовательность ... | normal | {
"blob_id": "4c8a873c816678532b029af409be13258757eae1",
"index": 7577,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main():\n num_seq = input('Введите последовательность чисел через пробел: ').split()\n num_lst = [float(s) for s in num_seq if is_numb_val(s)]\n print(sorted(num_lst))\n\... | [
0,
1,
2,
3,
4
] |
#!/bin/python
import sys
arr = map(int, raw_input().strip().split(' '))
smallest = 1000000001
largest = 0
smi = -1
lri = -1
for i, num in enumerate(arr):
if num < smallest:
smallest = num
smi = i
if num > largest:
largest = num
lri = i
smsum = 0
lrsum = 0
for i in range(len(a... | normal | {
"blob_id": "164665c7d037f1e4128d8227d5fc148940d5c2b8",
"index": 6235,
"step-1": "#!/bin/python\n\nimport sys\n\narr = map(int, raw_input().strip().split(' '))\n\nsmallest = 1000000001\nlargest = 0\nsmi = -1\nlri = -1\nfor i, num in enumerate(arr):\n if num < smallest:\n smallest = num\n smi = i... | [
0
] |
"""
This is the hourly animation program. It displays a series of images across the board.
It is hard coded to work with the Sonic images. Adjustments would need to be made to
the y values which are distance traveled. Change sonicFrame < 8 value to the total
number of frames the new animation has.
"""
from runImages im... | normal | {
"blob_id": "ede675c971ed233e93c14aa4d2ffb66fe7ba775a",
"index": 5613,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef animationDisplay():\n matrix.Clear()\n sonicRun = 0\n sonicFrame = 0\n y = 0\n while y < 70:\n sonicFrame = 0\n if sonicRun >= 100:\n sonic... | [
0,
1,
2,
3
] |
import numpy as np
x = np.zeros(10)
idx = [1, 4, 5, 9]
np.put(x, ind=idx, v=1)
print(x)
| normal | {
"blob_id": "9e2485554a5a8de07dd3df39cc255f2a1ea2f164",
"index": 4769,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nnp.put(x, ind=idx, v=1)\nprint(x)\n",
"step-3": "<mask token>\nx = np.zeros(10)\nidx = [1, 4, 5, 9]\nnp.put(x, ind=idx, v=1)\nprint(x)\n",
"step-4": "import numpy as np\nx = np.zeros(... | [
0,
1,
2,
3
] |
# -*- coding: utf-8 -*-
import graphviz
import fa_util
class Graph:
def draw(self, directory, filename, rules, start_state, accept_states):
g = graphviz.Digraph(format="svg", graph_attr={'rankdir': 'LR'})
self.add_start_edge(g, start_state)
edges = {}
for rule in rules:
... | normal | {
"blob_id": "c0e94a0d20397ebbbdddf726307b19b6c5c85ae6",
"index": 9082,
"step-1": "<mask token>\n\n\nclass Graph:\n\n def draw(self, directory, filename, rules, start_state, accept_states):\n g = graphviz.Digraph(format='svg', graph_attr={'rankdir': 'LR'})\n self.add_start_edge(g, start_state)\n ... | [
6,
7,
9,
10,
12
] |
import random
import numpy as np
import torch
from utils import print_result, set_random_seed, get_dataset, get_extra_args
from cogdl.tasks import build_task
from cogdl.datasets import build_dataset
from cogdl.utils import build_args_from_dict
DATASET_REGISTRY = {}
def build_default_args_for_node_classification(da... | normal | {
"blob_id": "2396f7acab95260253c367c62002392760157705",
"index": 1236,
"step-1": "<mask token>\n\n\ndef build_default_args_for_node_classification(dataset):\n cpu = not torch.cuda.is_available()\n args = {'lr': 0.01, 'weight_decay': 0.0005, 'max_epoch': 1000,\n 'max_epochs': 1000, 'patience': 100, '... | [
5,
6,
7,
8,
10
] |
import pygame
import numpy as np
import glob
from entities.base import AnimatedSprite
images_path = sorted(glob.glob('./resources/trophy_sparkle_*.png'))
trophy_im_dict = {'sparkle':[pygame.transform.scale(pygame.image.load(img_path),(400,400)) for img_path in images_path]}
class Trophy(AnimatedSprite):
def __in... | normal | {
"blob_id": "883cb1e3ea227bb5ac5aa3b4348336ab1a7fba70",
"index": 3476,
"step-1": "<mask token>\n\n\nclass Trophy(AnimatedSprite):\n\n def __init__(self, position, image_dict, hold_for_n_frames=3):\n super().__init__(position, image_dict, hold_for_n_frames)\n self.initial_position = position\n ... | [
2,
3,
4,
5,
6
] |
from __future__ import absolute_import, print_function, unicode_literals
import six
from six.moves import zip, filter, map, reduce, input, range
import pathlib
import unittest
import networkx as nx
import multiworm
TEST_ROOT = pathlib.Path(__file__).parent.resolve()
DATA_DIR = TEST_ROOT / 'data'
SYNTH1 = DATA_DIR ... | normal | {
"blob_id": "dfee0407eaed7b1ab96467874bbfe6463865bcb4",
"index": 6238,
"step-1": "<mask token>\n\n\nclass TestExperimentOpen(unittest.TestCase):\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 TestMalformed... | [
18,
19,
24,
27,
29
] |
from PrStatusWorker import PrStatusWorker
import threading
def initialize_worker():
worker = PrStatusWorker()
worker.start_pr_status_polling()
print("Starting the PR status monitor worker thread...")
worker_thread = threading.Thread(target=initialize_worker, name="pr_status_worker")
worker_thread.start()
| normal | {
"blob_id": "4b5f58d471b05428caef3ca7a3bdc0d30a7e3881",
"index": 5265,
"step-1": "<mask token>\n\n\ndef initialize_worker():\n worker = PrStatusWorker()\n worker.start_pr_status_polling()\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef initialize_worker():\n worker = PrStatusWorker()\n worke... | [
1,
2,
3,
4,
5
] |
#!/usr/bin/env python
import pyaudio
import wave
import winshell
"""
This script accesses the Laptop's microphone using the library pyaudio and opens a stream to record the voice
and writes it to an mp3 file
"""
def start():
try:
CHUNK = 1024
FORMAT = pyaudio.paInt16
CHANNELS = 2
RA... | normal | {
"blob_id": "bbbbf0e1bbd7ead034d8cd88ee6a09a61cde7803",
"index": 3463,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef start():\n try:\n CHUNK = 1024\n FORMAT = pyaudio.paInt16\n CHANNELS = 2\n RATE = 44100\n dest_path = winshell.desktop() + '\\\\Spyware\\\\Ou... | [
0,
1,
2,
3
] |
# user_events.py
import dataclasses
from typing import Optional
@dataclasses.dataclass
class UserUpdateMessage:
id: str
name: Optional[str] = None
age: Optional[int] = None
async def receive_user_update(message: UserUpdateMessage) -> None:
print(f"Received update for user id={message.id}")
| normal | {
"blob_id": "b2fb5564d44f7481c6de2a5d4af09df4903026b8",
"index": 8222,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@dataclasses.dataclass\nclass UserUpdateMessage:\n id: str\n name: Optional[str] = None\n age: Optional[int] = None\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\n@data... | [
0,
1,
2,
3,
4
] |
#Pràctica 9 Condicionals, Exercici 2:
print("Introduce un valor par:")
numpar=int(input())
print("Introduce un valor impar:")
numimp=int(input())
if numpar==numimp*2:
print(numpar," es el doble que ",numimp,".")
else:
print(numpar," no es el doble que ",numimp,".") | normal | {
"blob_id": "8ad5f3e5f73eae191a3fe9bc20f73b4bfcfedc8c",
"index": 4884,
"step-1": "<mask token>\n",
"step-2": "print('Introduce un valor par:')\n<mask token>\nprint('Introduce un valor impar:')\n<mask token>\nif numpar == numimp * 2:\n print(numpar, ' es el doble que ', numimp, '.')\nelse:\n print(numpar,... | [
0,
1,
2,
3
] |
animals = ['bear', 'python', 'peacock', 'kangaroo', 'whale', 'platypus']
The animal at 1.
The third (3rd) animal.
The first (1st) animal.
The animal at 3.
The fifth (5th) animal.
The animal at 2.
The sixth (6th) animal.
The animal at 4.
| normal | {
"blob_id": "a319ebb05e9034f19aef39bd46830c8a607ed121",
"index": 1013,
"step-1": "animals = ['bear', 'python', 'peacock', 'kangaroo', 'whale', 'platypus']\nThe animal at 1.\nThe third (3rd) animal.\nThe first (1st) animal.\nThe animal at 3.\nThe fifth (5th) animal.\nThe animal at 2.\nThe sixth (6th) animal.\nThe... | [
0
] |
# Mac File
import platform
import os
def Mac(SystemArray = [], ProcessorArray = []):
# System Info
OSName = str()
OSVersionMajor = str()
OSArchitecture = str()
# Processor Info
command = '/usr/sbin/sysctl -n machdep.cpu.brand_string'
ProcInfo = os.popen(command).read().strip()
ProcNam... | normal | {
"blob_id": "f652fa6720582d50f57f04d82fb2f5af17859ebd",
"index": 8211,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef Mac(SystemArray=[], ProcessorArray=[]):\n OSName = str()\n OSVersionMajor = str()\n OSArchitecture = str()\n command = '/usr/sbin/sysctl -n machdep.cpu.brand_string'\n... | [
0,
1,
2,
3
] |
# Q. In How many ways N stair can be climb if allowesd steps are 1, 2 or 3.
# triple Sort
def noOfSteps(n, k):
if n<0: return 0
if n == 0: return 1
t_steps = 0
for i in range(1, k+1):
t_steps += noOfSteps(n-i, k)
return t_steps
def noOfStepsDP(n,k):
dp = [0]*max((... | normal | {
"blob_id": "6c2699ff8e739595a2648d53745dc3c788536d7b",
"index": 1907,
"step-1": "<mask token>\n\n\ndef noOfStepsDP(n, k):\n dp = [0] * max(n + 1, 3)\n dp[0] = 1\n dp[1] = 1\n dp[2] = 2\n for i in range(3, n + 1):\n dp[i] = dp[i - 1] + dp[i - 2] + dp[i - 3]\n return dp[n]\n\n\n<mask toke... | [
1,
2,
3,
4,
5
] |
'''
Twitter settings
Input your app credentials below
https://apps.twitter.com
'''
# consumer key
CONSUMER_KEY = ''
# consumer secret
CONSUMER_SECRET = ''
'''
App settings
'''
# Where to save tokens (JSON)
TOKENS_PATH = '/tmp/twitter-tokens.json'
# Redirect-back to URL after authenticated (optional)
REDIRECT_TO = ''... | normal | {
"blob_id": "9cc64edc81ab39b0ab2cd47661c9809545b03ac6",
"index": 3230,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nCONSUMER_KEY = ''\nCONSUMER_SECRET = ''\n<mask token>\nTOKENS_PATH = '/tmp/twitter-tokens.json'\nREDIRECT_TO = ''\nFLASK_SECRET = 'S$2[ShC-=BKKOQ.Z-|fa 6f;,5 <[QngmG)}5,s%0vX>B}?o-0X9PM;.... | [
0,
1,
2
] |
# -*- coding: utf-8 -*-
from fw.api import dadata_proxy
from flask import current_app
from fw.cache.cache_wrapper import CacheWrapper
cache = CacheWrapper()
def dadata_suggest(method, data):
return dadata_proxy.dadata_suggest(method, data)
def dadata_clean(method, data):
return dadata_proxy.dadata_clean(... | normal | {
"blob_id": "af4d2380f92ea636594695e5ad4ba766d6874dd3",
"index": 1355,
"step-1": "<mask token>\n\n\ndef dadata_clean(method, data):\n return dadata_proxy.dadata_clean(method, data)\n\n\ndef get_detailed_address(address):\n from fw.utils.address_utils import get_detailed_address as _get_detailed_address\n ... | [
9,
11,
12,
13,
14
] |
from .file_uploader_routes import FILE_UPLOADER_BLUEPRINT
| normal | {
"blob_id": "c7dacdb53efb6935314c5e3718a4a2f1d862b07d",
"index": 2340,
"step-1": "<mask token>\n",
"step-2": "from .file_uploader_routes import FILE_UPLOADER_BLUEPRINT\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
x = 5
y = x
print(id(x))
print(id(y))
print()
y = 3
print(id(x))
print(id(y))
print()
z = [1, 4, 3, 25]
w = z
print(z)
print(w)
print(id(z))
print(id(w))
print()
w[1] = 10
print(z)
print(w)
print(id(z))
print(id(w))
# So when you assign a mutable, you're actually assigning a reference to the mutable,
# and I... | normal | {
"blob_id": "956adc5961188458393b56564649ad0a3a787669",
"index": 7327,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(id(x))\nprint(id(y))\nprint()\n<mask token>\nprint(id(x))\nprint(id(y))\nprint()\n<mask token>\nprint(z)\nprint(w)\nprint(id(z))\nprint(id(w))\nprint()\n<mask token>\nprint(z)\nprin... | [
0,
1,
2,
3
] |
from mpi4py import MPI
from random import random
comm = MPI.COMM_WORLD
mydata = comm.rank
data = comm.gather(mydata)
if comm.rank == 0:
print("Data = ", data)
| normal | {
"blob_id": "acf3d188bd6c99774ddf538dcc83f99ad56c7057",
"index": 7431,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif comm.rank == 0:\n print('Data = ', data)\n",
"step-3": "<mask token>\ncomm = MPI.COMM_WORLD\nmydata = comm.rank\ndata = comm.gather(mydata)\nif comm.rank == 0:\n print('Data = ... | [
0,
1,
2,
3,
4
] |
import matplotlib.pyplot as pt
import numpy as np
from scipy.optimize import leastsq
####################################
# Setting up test data
def norm(x, media, sd):
norm = []
for i in range(x.size):
norm += [1.0/(sd*np.sqrt(2*np.pi))*np.exp(-(x[i] - media)**2/(2*sd**2))]
return np.array(norm)... | normal | {
"blob_id": "b3ce17401476afe2edfda3011d5602ba492cd705",
"index": 5817,
"step-1": "<mask token>\n\n\ndef res(p, y, x):\n m, dm, sd1, sd2 = p\n m1 = m\n m2 = m1 + m\n y_fit = norm(x, m1, sd1) + norm(x, m2, sd2)\n error = y - y_fit\n return error\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n... | [
1,
2,
3,
4,
5
] |
from setuptools import setup
setup(name='RedHatSecurityAdvisory',
version='0.1',
description='Script that automatically checks the RedHat security advisories to see if a CVE applies',
author='Pieter-Jan Moreels',
url='https://github.com/PidgeyL/RedHat-Advisory-Checker',
entry_points={'con... | normal | {
"blob_id": "3f8c13be547099aa6612365452926db95828b9a0",
"index": 554,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsetup(name='RedHatSecurityAdvisory', version='0.1', description=\n 'Script that automatically checks the RedHat security advisories to see if a CVE applies'\n , author='Pieter-Jan Mo... | [
0,
1,
2,
3
] |
from selenium import webdriver
import math
import time
browser = webdriver.Chrome()
website = 'http://suninjuly.github.io/find_link_text'
link_text = str(math.ceil(math.pow(math.pi, math.e) * 10000))
browser.get(website)
find_link = browser.find_element_by_link_text(link_text)
find_link.click()
input_first_name = brows... | normal | {
"blob_id": "aa17e22bc13436333b1db4aee41eeced373119a8",
"index": 5704,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nbrowser.get(website)\n<mask token>\nfind_link.click()\n<mask token>\ninput_first_name.send_keys('Timur')\n<mask token>\ninput_last_name.send_keys('Atabaev')\n<mask token>\ninput_city.send... | [
0,
1,
2,
3
] |
#!/usr/bin/python3
def square_matrix_simple(matrix=[]):
'''This function will compute the square root of all integers in
a matrix. '''
new_matrix = []
for index in matrix:
jndex = 0
new_row = []
while jndex < len(index):
... | normal | {
"blob_id": "b090e92fe62d9261c116529ea7f480daf8b3e84e",
"index": 6543,
"step-1": "<mask token>\n",
"step-2": "def square_matrix_simple(matrix=[]):\n \"\"\"This function will compute the square root of all integers in\n a matrix. \"\"\"\n new_matrix = ... | [
0,
1,
2
] |
"""
Copyright © 2017 Bilal Elmoussaoui <bil.elmoussaoui@gmail.com>
This file is part of Authenticator.
Authenticator is free software: you can redistribute it and/or
modify it under the terms of the GNU General Public License as published
by the Free Software Foundation, either version 3 of the License, or
(at ... | normal | {
"blob_id": "a7d8efe3231b3e3b9bfc5ef64a936816e8b67d6c",
"index": 3127,
"step-1": "<mask token>\n\n\n@Gtk.Template(resource_path=\n '/com/github/bilelmoussaoui/Authenticator/settings.ui')\nclass SettingsWindow(Handy.PreferencesWindow):\n <mask token>\n dark_theme_switch: Gtk.Switch = Gtk.Template.Child()... | [
10,
11,
13,
19,
21
] |
#-*- coding: utf-8 -*-
espacos = ["__1__", "__2__", "__3__", "__4__"]
facil_respostas=["ouro","leao","capsula do poder","relampago de plasma"]
media_respostas=["Ares","Saga","Gemeos","Athena"]
dificil_respostas=["Shion","Aries","Saga","Gemeos"]
def inicio_game():
apresentacao=raw_input("Bem vindo ao qui... | normal | {
"blob_id": "d205c38e18b1acf8043a5976a90939b14358dc40",
"index": 7855,
"step-1": "#-*- coding: utf-8 -*-\r\nespacos = [\"__1__\", \"__2__\", \"__3__\", \"__4__\"]\r\nfacil_respostas=[\"ouro\",\"leao\",\"capsula do poder\",\"relampago de plasma\"]\r\nmedia_respostas=[\"Ares\",\"Saga\",\"Gemeos\",\"Athena\"]\r\ndi... | [
0
] |
import io
import xlsxwriter
import zipfile
from django.conf import settings
from django.http import Http404, HttpResponse
from django.contrib.auth.mixins import LoginRequiredMixin, UserPassesTestMixin
from django.contrib.auth.decorators import login_required
from django.contrib import messages
from django.views.generic... | normal | {
"blob_id": "a9ebd323d4b91c7e6a7e7179329ae80e22774927",
"index": 4843,
"step-1": "<mask token>\n\n\nclass PeriodoUpdateView(LoginRequiredMixin, UpdateView):\n <mask token>\n <mask token>\n <mask token>\n\n def get_form_kwargs(self, *args, **kwargs):\n kwargs = super(PeriodoUpdateView, self).ge... | [
67,
76,
95,
101,
108
] |
import math
print ("programa que calcula hipotenusa tomando el valor de los catetos en tipo double---")
print ("------------------------------------------------------------------------")
print (" ")
catA = float(input("igrese el valor del cateto A"))
catB = float(input("ingrese el valor del catebo B"))
def calcularHi... | normal | {
"blob_id": "af217d0cc111f425282ee21bd47d9007a69a6239",
"index": 6297,
"step-1": "<mask token>\n\n\ndef calcularHipotenusa(catA, catB):\n hipotenusa = catA ** 2 + catB ** 2\n hipotenusa = math.sqrt(hipotenusa)\n hipotenusa = float(hipotenusa)\n print('la hipotenusa es: ', hipotenusa)\n\n\n<mask token... | [
1,
2,
3,
4,
5
] |
try:
from setuptools import setup, find_packages
except ImportError:
import ez_setup
ez_setup.use_setuptools()
from setuptools import setup, find_packages
setup(
name = "pip-utils",
version = "0.0.1",
url = 'https://github.com/mattpaletta/pip-utils',
packages = find_packages(),
inc... | normal | {
"blob_id": "5fe81a6143642d671686c6623a9ecc93e04a82bf",
"index": 5711,
"step-1": "<mask token>\n",
"step-2": "try:\n from setuptools import setup, find_packages\nexcept ImportError:\n import ez_setup\n ez_setup.use_setuptools()\n from setuptools import setup, find_packages\nsetup(name='pip-utils', ... | [
0,
1,
2
] |
'''
Generate the output images and videos, including rendering of the pipeline
'''
import os
import matplotlib.image as mpimg
import cv2
from moviepy.editor import VideoFileClip
from networkx.drawing.nx_agraph import to_agraph
import lanespipeline
import lanefinder
from compgraph import CompGraph, CompGraphRunner
C... | normal | {
"blob_id": "456d79a69c170a59af742648f16e0171cd5a2412",
"index": 1412,
"step-1": "<mask token>\n\n\ndef create_dir(directory):\n if not os.path.exists(directory):\n os.makedirs(directory)\n\n\ndef get_full_paths_to_files(files_dir, filenames):\n return [os.path.join(files_dir, f) for f in filenames]... | [
5,
6,
7,
8,
10
] |
# https://www.hackerrank.com/challenges/bon-appetit
n, k = map(int, input().split())
prices = [int(temp) for temp in input().split()]
taken = int(input())
if (sum(prices) - prices[k]) // 2 == taken:
print("Bon Appetit")
else:
print(taken - (sum(prices) - prices[k])// 2)
| normal | {
"blob_id": "aa15f684d23d97a45a416b1fdcfb192710ebb56f",
"index": 2151,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif (sum(prices) - prices[k]) // 2 == taken:\n print('Bon Appetit')\nelse:\n print(taken - (sum(prices) - prices[k]) // 2)\n",
"step-3": "n, k = map(int, input().split())\nprices =... | [
0,
1,
2,
3
] |
# stdlib
from typing import Any
# third party
import numpy as np
# syft absolute
import syft as sy
from syft.core.common.uid import UID
from syft.core.node.new.action_object import ActionObject
from syft.core.node.new.action_store import DictActionStore
from syft.core.node.new.context import AuthedServiceContext
from... | normal | {
"blob_id": "b76d3b6a4c15833ee2b25fede5923e1fe1dc4dd7",
"index": 5422,
"step-1": "<mask token>\n\n\ndef test_signing_key() ->None:\n test_signing_key = SyftSigningKey.from_string(test_signing_key_string)\n assert isinstance(test_signing_key, SyftSigningKey)\n assert str(test_signing_key) == test_signing... | [
3,
7,
10,
11,
12
] |
from src.produtos import *
class Estoque(object):
def __init__(self):
self.categorias = []
self.subcategorias = []
self.produtos = []
self.menu_estoque()
def save_categoria(self, categoria):
pass
def save_subcategorias(self, subcategoria):
pa... | normal | {
"blob_id": "9f3ca0d5a10a27d926a0f306665889418f8d6a0c",
"index": 5884,
"step-1": "<mask token>\n\n\nclass Estoque(object):\n <mask token>\n\n def save_categoria(self, categoria):\n pass\n <mask token>\n\n def save_produtos(self, produto):\n pass\n <mask token>\n\n def create_subca... | [
7,
11,
12,
17,
18
] |
"""
Декоратор parser_stop - парсер результата вывода комманды docker stop.
"""
from functools import wraps
def parser_stop(func):
@wraps(func)
def wrapper(*args, **kwargs):
result = func(*args, **kwargs)
stdout = result['stdout']
"""
stdout: строки разделены \n
"""
... | normal | {
"blob_id": "4af573fa17f86ee067b870dce1f6ee482d1b14ff",
"index": 8281,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef parser_stop(func):\n\n @wraps(func)\n def wrapper(*args, **kwargs):\n result = func(*args, **kwargs)\n stdout = result['stdout']\n \"\"\"\n stdou... | [
0,
1,
2,
3
] |
N = int(input())
l = []
for n in range(N):
x = int(input())
l.append(x)
l.sort()
print(*l, sep='\n')
| normal | {
"blob_id": "a699b43c57c315967a6d1881d7012fee4a93607b",
"index": 6347,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor n in range(N):\n x = int(input())\n l.append(x)\nl.sort()\nprint(*l, sep='\\n')\n",
"step-3": "N = int(input())\nl = []\nfor n in range(N):\n x = int(input())\n l.append... | [
0,
1,
2
] |
#!/usr/bin/env python
# Copyright (c) 2019, University of Stuttgart
# All rights reserved.
#
# Permission to use, copy, modify, and distribute this software for any purpose
# with or without fee is hereby granted, provided that the above copyright
# notice and this permission notice appear in all copies.
#
# THE ... | normal | {
"blob_id": "007cce815f3ad4e47593ff00ff2e73d5d9961d9e",
"index": 3211,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(2):\n renderer.set_drawing_axis(i)\n renderer.draw_ws_obstacles()\n renderer.draw_ws_point(source, color='k', shape='o')\n renderer.background_matrix_eval = Fal... | [
0,
1,
2,
3,
4
] |
def decorate(a):
def inner(f):
def decorated(*args, **kwargs):
return f(a, *args, **kwargs)
return decorated
return inner
@decorate(3)
def func(a, b, c):
print a, b, c
func(1, 2)
| normal | {
"blob_id": "d2049b20e00b45df9fb0772d9a654a58a00191c5",
"index": 9865,
"step-1": "def decorate(a):\n def inner(f):\n def decorated(*args, **kwargs):\n return f(a, *args, **kwargs)\n return decorated\n return inner\n\n\n@decorate(3)\ndef func(a, b, c):\n print a, b, c\n\n\nfunc(1... | [
0
] |
# addtwo_run-py
"""
Train and test a TCN on the add two dataset.
Trying to reproduce https://arxiv.org/abs/1803.01271.
"""
print('Importing modules')
import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
from torch.utils.tensorboard import SummaryWriter
from torch.uti... | normal | {
"blob_id": "fe1a9804862942491b11b9baceecd37bf628fbb8",
"index": 8732,
"step-1": "<mask token>\n\n\ndef run():\n torch.manual_seed(1729)\n \"\"\" Setup \"\"\"\n args = parse()\n device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')\n print(device)\n \"\"\" Dataset \"\"\"\n ... | [
1,
2,
3,
4,
5
] |
from os import environ
from process import process
from s3Service import put_object
environ['ACCESS_KEY'] = '1234567890'
environ['SECRET_KEY'] = '1234567890'
environ['ENDPOINT_URL'] = 'http://localhost:4566'
environ['REGION'] = 'us-east-1'
environ['BUCKET_GLOBAL'] = 'fl2-statement-global'
environ['BUCKET_GLOBAL_BACKUP... | normal | {
"blob_id": "a4eca0f5b7d5a03ca3600554ae3fe3b94c59fc68",
"index": 8622,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef execute(event, context):\n print(event)\n pass\n",
"step-3": "<mask token>\nenviron['ACCESS_KEY'] = '1234567890'\nenviron['SECRET_KEY'] = '1234567890'\nenviron['ENDPOINT_U... | [
0,
1,
2,
3,
4
] |
class Action(dict):
def __init__(self, action, player=None, target=None):
self['action'] = action
self['player'] = player
if target != None:
self['target'] = target
| normal | {
"blob_id": "1c9345923fe83aa0ee7165ce181ce05ac55e2b2f",
"index": 7773,
"step-1": "<mask token>\n",
"step-2": "class Action(dict):\n <mask token>\n",
"step-3": "class Action(dict):\n\n def __init__(self, action, player=None, target=None):\n self['action'] = action\n self['player'] = player... | [
0,
1,
2
] |
from django.apps import AppConfig
class ScambioConfig(AppConfig):
name = 'scambio'
| normal | {
"blob_id": "b091d00f5b5e997de87b36adbe9ce603a36ca49c",
"index": 3347,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass ScambioConfig(AppConfig):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass ScambioConfig(AppConfig):\n name = 'scambio'\n",
"step-4": "from django.apps import App... | [
0,
1,
2,
3
] |
from django.contrib import admin
from xchanger.models import Currency, Rates, UpdateInfo
class CurrencyAdmin(admin.ModelAdmin):
pass
class UpdAdmin(admin.ModelAdmin):
pass
class RatesAdmin(admin.ModelAdmin):
list_filter = ['c_code_id', 'upd_id']
admin.site.register(Currency, CurrencyAdmin)
admin.sit... | normal | {
"blob_id": "20ccdd319bfbbb4f17e8518eb60d125112c05d8e",
"index": 6828,
"step-1": "<mask token>\n\n\nclass RatesAdmin(admin.ModelAdmin):\n list_filter = ['c_code_id', 'upd_id']\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass CurrencyAdmin(admin.ModelAdmin):\n pass\n\n\nclass UpdAdmin(admin.ModelA... | [
2,
4,
5,
6
] |
# 4, [[1,0],[2,0],[3,1],[3,2]]
# 3->1->0
# \ ^
# \ |
# \> 2
# 1,0,2,3
# stack 3
#
# 0 1 2 3
# 1,0
# stack 1
# 0
#
# def findOrder(numCourses, prerequisites):
# if len(prerequisites) == 0:
# order = []
# for i in range(0, numCourses):
# order.append(i)
# return or... | normal | {
"blob_id": "56892e125934d5de937b92a08bd7707c12c70928",
"index": 689,
"step-1": "<mask token>\n",
"step-2": "def findOrder(numCourses, prerequisites):\n if len(prerequisites) == 0:\n order = []\n for i in range(0, numCourses):\n order.append(i)\n return order\n edges = {}\... | [
0,
1,
2,
3
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# This file is part of CbM (https://github.com/ec-jrc/cbm).
# Author : Konstantinos Anastasakis
# Credits : GTCAP Team
# Copyright : 2021 European Commission, Joint Research Centre
# License : 3-Clause BSD
from ipywidgets import (Text, VBox, HBox, Label, Password... | normal | {
"blob_id": "22afc6b9df87ef1eba284da20a807366278c24d4",
"index": 1343,
"step-1": "<mask token>\n\n\ndef rest_api(mode=None):\n \"\"\"\"\"\"\n values = config.read()\n wt_url = Text(value=values['api']['url'], placeholder='Add URL',\n description='API URL:', disabled=False)\n wt_user = Text(val... | [
2,
3,
4,
5,
6
] |
"""
This file goes through the data to find the frequencies of words in the corpus
"""
import csv
import time, datetime
import calendar
from collections import defaultdict
import chardet
import re
REVIEW_ID_COL = 0;
USER_ID_COL = 1
BUSINESS_ID_COL = 2
STARS_COL = 3
DATE_COL = 4
TEXT_COL = 5
USEFUL_CO... | normal | {
"blob_id": "ba54b3a148a34ced74a337665ddd5f2d9084553b",
"index": 1489,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('yelp_review.csv', encoding='utf8') as csvfile:\n wordFrequencies = defaultdict(int)\n\n def beautifyDate(res):\n dt = time.strptime(res, '%Y-%m-%d')\n retur... | [
0,
1,
2,
3,
4
] |
import torch
import torchvision.transforms.functional as F
import numpy as np
import yaml
from pathlib import Path
IGNORE_LABEL = 255
STATS = {
"vit": {"mean": (0.5, 0.5, 0.5), "std": (0.5, 0.5, 0.5)},
"deit": {"mean": (0.485, 0.456, 0.406), "std": (0.229, 0.224, 0.225)},
}
def seg_to_rgb(seg, colors):
i... | normal | {
"blob_id": "6c641ace8f1e5e8c42fa776bd7604daf243f9a41",
"index": 2113,
"step-1": "<mask token>\n\n\ndef dataset_cat_description(path, cmap=None):\n desc = yaml.load(open(path, 'r'), Loader=yaml.FullLoader)\n colors = {}\n names = []\n for i, cat in enumerate(desc):\n names.append(cat['name'])\... | [
2,
4,
5,
6,
7
] |
import os
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
IS_TESTING = False
FOLDER_TO_ORGANIZE = ''
FOLDER_FOR_OTHERS = ''
FOLDER_TO_ORGANIZE_TEST = ''
LOG_FILE = ''
IGNORE_HIDDEN_FILES = True
FILES_DESTINATION = {
'images': ['.jpg', '.jpeg', '.png'],
'documents': ['.pdf', '.xlsx', '.... | normal | {
"blob_id": "83e2f9c56c45a288aabd777fb244089367649258",
"index": 1165,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nBASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))\nIS_TESTING = False\nFOLDER_TO_ORGANIZE = ''\nFOLDER_FOR_OTHERS = ''\nFOLDER_TO_ORGANIZE_TEST = ''\nLOG_FILE = ''\nI... | [
0,
1,
2,
3
] |
import os, sys, string
import linecache, math
import numpy as np
import datetime , time
from pople import NFC
from pople import uniqatoms
from pople import orca_printbas
####### orca_run - S
def orca_run(method, basis,optfreq,custombasis, correlated, values, charge, multip, sym, R_coord):
"""
Runs orca
... | normal | {
"blob_id": "019e8d7159fe07adc245e6476ac1fed5e9c457b5",
"index": 3035,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef orca_run(method, basis, optfreq, custombasis, correlated, values,\n charge, multip, sym, R_coord):\n \"\"\"\n Runs orca\n\n Parameters:\n me... | [
0,
1,
2,
3
] |
import os
import pathlib
from global_settings import *
def get_bits(x):
return np.where(x < 0, 0, 1)
def check_wrong_bits(bits, bits_estimated):
return len(np.argwhere(bits != bits_estimated))
def mkdir(file_path):
folder = os.path.dirname(file_path)
if not os.path.exists(folder):
os.make... | normal | {
"blob_id": "74ffbd55867c4b2c6ccbef7d94e0c65aef139057",
"index": 7602,
"step-1": "<mask token>\n\n\ndef get_bits(x):\n return np.where(x < 0, 0, 1)\n\n\n<mask token>\n\n\ndef mkdir(file_path):\n folder = os.path.dirname(file_path)\n if not os.path.exists(folder):\n os.makedirs(folder)\n\n\n<mask ... | [
7,
9,
11,
13,
14
] |
import csv
import datetime
with open('/Users/wangshibao/SummerProjects/analytics-dashboard/myapp/CrimeHistory.csv','rU') as f:
reader = csv.reader(f)
header = reader.next()
date_time = "20140501 00:00"
date_time = datetime.datetime.strptime(date_time, "%Y%m%d %H:%M")
print date_t... | normal | {
"blob_id": "cfb49d78dc14e6f4b6d2357d292fd6275edec711",
"index": 6844,
"step-1": "import csv\nimport datetime\nwith open('/Users/wangshibao/SummerProjects/analytics-dashboard/myapp/CrimeHistory.csv','rU') as f:\n reader = csv.reader(f)\n header = reader.next()\n date_time = \"20140501 00:00\... | [
0
] |
# Generated by Django 3.1 on 2020-08-28 14:03
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('api_rest', '0004_auto_20200828_0749'),
]
operations = [
migrations.RemoveField(
model_name='event',
name='user_id',
... | normal | {
"blob_id": "bfd8385e8f4886b91dde59c04785134b9cd6a2b6",
"index": 3893,
"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 = [('api_rest', ... | [
0,
1,
2,
3,
4
] |
import deform
import deform.widget
from deform import (widget) # decorator, default_renderer, field, form,
import colander
# import htmllaundry
# from htmllaundry import sanitize
from validators import (cyber_validator,
phone_validator,
stor_validator,
... | normal | {
"blob_id": "3a3400426b054b2fc3d060141a1f84e5db553e59",
"index": 3424,
"step-1": "<mask token>\n\n\n@colander.deferred\ndef deferred_country_widget(node, kw):\n country_codes_data = kw.get('country_codes_data', [])\n return widget.Select2Widget(values=country_codes_data)\n\n\n<mask token>\n\n\n@colander.de... | [
5,
6,
7,
8,
9
] |
# -*- coding: utf-8 -*-
"""Testing constants for Bio2BEL FlyBase."""
import logging
import os
log = logging.getLogger(__name__)
dir_path = os.path.dirname(os.path.realpath(__file__))
TEST_FILE = os.path.join(dir_path, 'test_gene_map_table.tsv.gz')
| normal | {
"blob_id": "bad719d968b4e358f863b7ef13bc12127f726806",
"index": 682,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nlog = logging.getLogger(__name__)\ndir_path = os.path.dirname(os.path.realpath(__file__))\nTEST_FILE = os.path.join(dir_path, 'test_gene_map_table.tsv.gz')\n",
"step-3": "<mask token>\ni... | [
0,
1,
2,
3
] |
#8
def matrix(m):
for i in range(len(m)):
for j in range (len(m[0])):
m[i][j]=(m[i][j])**2
a=[[1,2,3],[4,5,6],[8,9,0]]
print('The matrix is ',a)
matrix(a)
print('The updated matrix is ',a)
| normal | {
"blob_id": "f46dd5217c8e015546d7fff7ee52569ecc2c8e41",
"index": 5487,
"step-1": "<mask token>\n",
"step-2": "def matrix(m):\n for i in range(len(m)):\n for j in range(len(m[0])):\n m[i][j] = m[i][j] ** 2\n\n\n<mask token>\n",
"step-3": "def matrix(m):\n for i in range(len(m)):\n ... | [
0,
1,
2,
3,
4
] |
#List methods allow you to modify lists. The following are some list methods for you to practice with. Feel free to google resources to help you with this assignment.
#append(element) adds a single element to the list
#1. 'Anonymous' is also deserving to be in the hacker legends list. Add him in to the hacker legends ... | normal | {
"blob_id": "53fd020946a2baddb1bb0463d2a56744de6e3822",
"index": 5506,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nhacker_legends.append('Anonymous')\nprint(hacker_legends)\n<mask token>\nnetworking.insert(3, 'SSH')\nprint(networking)\n<mask token>\nip_addy.remove(5102018)\nprint(ip_addy)\n<mask token... | [
0,
1,
2,
3
] |
from keras.preprocessing.text import text_to_word_sequence
import os
# keras NLP tools filter out certain tokens by default
# this function replaces the default with a smaller set of things to filter out
def filter_not_punctuation():
return '"#$%&()*+-/:;<=>@[\\]^_`{|}~\t\n'
def get_first_n_words(text, n):
... | normal | {
"blob_id": "365e2059d5ed3d7f8d9dbb4e44f563b79d68b087",
"index": 1856,
"step-1": "<mask token>\n\n\ndef get_labelled_data_from_directories(data_dir, maxlen=None):\n texts = []\n labels_index = {}\n labels = []\n for name in sorted(os.listdir(data_dir)):\n path = os.path.join(data_dir, name)\n ... | [
1,
2,
3,
4,
5
] |
from flask import Flask, render_template, redirect, request, session
app = Flask(__name__)
app.secret_key = 'ThisIsSecret' #this line is always needed when using the import 'session'
@app.route('/') #methods=['GET'] by default
def index():
return render_template('index.html')
@app.route('/ninja'... | normal | {
"blob_id": "001198459b038186ab784b6a9bed755924784866",
"index": 4687,
"step-1": "from flask import Flask, render_template, redirect, request, session\r\n\r\napp = Flask(__name__)\r\napp.secret_key = 'ThisIsSecret' #this line is always needed when using the import 'session'\r\n\r\n\r\n@app.route('/') #meth... | [
0
] |
# -*- coding: utf-8 -*-
# @File : config.py
# @Author: TT
# @Email : tt.jiaqi@gmail.com
# @Date : 2018/12/4
# @Desc : config file
from utils.general import getchromdriver_version
from chromedriver.path import path
import os
import sys
chromedriver = os.path.abspath(os.path.dirname(__file__)) + "\\chromedriver\\"+ g... | normal | {
"blob_id": "5b4a196de60a3a30bc571c559fe5f211563b8999",
"index": 5449,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nchromedriver = os.path.abspath(os.path.dirname(__file__)\n ) + '\\\\chromedriver\\\\' + getchromdriver_version()\ndownload_path = os.path.abspath(os.path.dirname(__file__)) + '\\\\'\nS... | [
0,
1,
2,
3
] |
import abc
import numpy as np
import ray
from tqdm.autonotebook import tqdm
from src.algorithm.info_theory.it_estimator import (CachingEstimator,
MPCachingEstimator)
from src.algorithm.utils import differ, independent_roll, union
class FeatureSelector(metaclass=ab... | normal | {
"blob_id": "983473129bfd56138a615e0f5bdb1353e9c6d8af",
"index": 6441,
"step-1": "<mask token>\n\n\nclass FeatureSelector(metaclass=abc.ABCMeta):\n <mask token>\n\n def _setup(self):\n self.n_features = self.trajectories[0].shape[1] - 1\n self.id_reward = self.n_features\n self.set_rew... | [
16,
18,
20,
22,
23
] |
from firstfuncs_1618 import *
figdir='/home/isabela/Documents/projects/OSNAP/figures_OSNAPwide/Freshwater/Linear/'
figdir_paper='/home/isabela/Documents/projects/OSNAP/figures_OSNAPwide/Freshwater/paperfigs'
########################################################################################################
#####... | normal | {
"blob_id": "40b94a3be27ebb0d8e3e67fddabe1dc68646169c",
"index": 9881,
"step-1": "<mask token>\n\n\ndef get_U_S_T_from_WM(WM):\n U = {}\n S = {}\n T = {}\n for wm in WM.WM:\n U[str(wm.values)] = float(WM['TRANS'].sel(WM=wm).groupby(\n 'TIME.month').mean('TIME').mean(dim='month').val... | [
10,
11,
13,
14,
16
] |
# Copyright 2017 The LUCI Authors. All rights reserved.
# Use of this source code is governed under the Apache License, Version 2.0
# that can be found in the LICENSE file.
DEPS = [
'step',
]
def RunSteps(api):
try:
api.step('test step', [{}])
except AssertionError as e:
assert str(e) == 'Type <type \'... | normal | {
"blob_id": "25d210144ef209fd5e4ff7e4e4c2e77fd7eb79ac",
"index": 3480,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef GenTests(api):\n yield api.test('basic')\n",
"step-3": "<mask token>\n\n\ndef RunSteps(api):\n try:\n api.step('test step', [{}])\n except AssertionError as e:\n... | [
0,
1,
2,
3,
4
] |
"""Sherlock Tests
This package contains various submodules used to run tests.
"""
import sys
import os
import subprocess as sp
from time import sleep
# uncomment this if using nose
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '../sherlock')))
# import sherlock | normal | {
"blob_id": "8f7b1313ba31d761edcadac7b0d04b62f7af8dff",
"index": 4759,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__),\n '../sherlock')))\n",
"step-3": "<mask token>\nimport sys\nimport os\nimport subprocess as sp\nfrom time i... | [
0,
1,
2,
3
] |
import pygame
import numpy as np
import random
from enum import Enum
from .config import *
class Actions(Enum):
FORWARD = 0
RIGHT = 1
LEFT = 2
BACK = 3
class MazeEnv():
''' TODO '''
def __init__(self, GW, GH, SW, SH):
global GRID_WIDTH, GRID_HEIGHT, SCREEN_WIDTH, SCREEN_HEIGHT, BOX_WID... | normal | {
"blob_id": "751d2a07b97d080988c54511ca13a97a969e06bd",
"index": 6405,
"step-1": "<mask token>\n\n\nclass MazeEnv:\n <mask token>\n\n def __init__(self, GW, GH, SW, SH):\n global GRID_WIDTH, GRID_HEIGHT, SCREEN_WIDTH, SCREEN_HEIGHT, BOX_WIDTH, BOX_HEIGHT\n GRID_WIDTH = GW\n GRID_HEIGHT... | [
9,
10,
12,
13,
14
] |
class Background(object):
def __init__(self, name):
self.name = name
self.description = ''
self.prTraits = []
self.ideals = []
self.bonds = []
self.flaws = []
def getBackName(self):
return self.name
def setBackDesc(self,desc):
self.descriptio... | normal | {
"blob_id": "45449e728dadd241b00f5c4bfb3fd3950f04037c",
"index": 2627,
"step-1": "class Background(object):\n\n def __init__(self, name):\n self.name = name\n self.description = ''\n self.prTraits = []\n self.ideals = []\n self.bonds = []\n self.flaws = []\n\n def ... | [
11,
13,
14,
15,
16
] |
import os
import tensorflow as tf
import torch
from tqdm import tqdm
from glob import glob
import numpy as np
from collections.abc import Iterable
from utils.hparams import HParam
#from utils.audio import Audio
#import librosa
#python encoder_inference.py --in_dir training_libri_mel/train/ --gpu_str 5
#python tfrecord... | normal | {
"blob_id": "df40b0628d6a180a98cd385145ee7c65ecb78256",
"index": 270,
"step-1": "<mask token>\n\n\nclass TFRecordProducer:\n\n def remove_list(self, list1, list2):\n i, j = 0, 0\n tmp_list1 = []\n tmp_list2 = []\n while i < len(list1) and j < len(list2):\n item1 = int(li... | [
4,
5,
6,
9,
10
] |
import re
#lines = open("input.1").read()
lines = open("input.2").read()
lines = lines.splitlines()
moves = {}
moves["nw"] = [-1, -1]
moves["ne"] = [ 0, -1]
moves["w"] = [-1, 0]
moves["e"] = [ 1, 0]
moves["sw"] = [ 0, 1]
moves["se"] = [ 1, 1]
tiles = {}
def fliptile(tile):
if tile == "B":
tile = "... | normal | {
"blob_id": "167c36627c7c3377266bde266e610792ba29b3e4",
"index": 3808,
"step-1": "import re\n\n#lines = open(\"input.1\").read()\nlines = open(\"input.2\").read()\nlines = lines.splitlines()\n\nmoves = {}\nmoves[\"nw\"] = [-1, -1]\nmoves[\"ne\"] = [ 0, -1]\nmoves[\"w\"] = [-1, 0]\nmoves[\"e\"] = [ 1, 0]\nmov... | [
0
] |
__author__ = 'liwenchang'
#-*- coding:utf-8 -*-
import os
import time
import win32api, win32pdhutil, win32con, win32com.client
import win32pdh, string
def check_exsit(process_name):
WMI = win32com.client.GetObject('winmgmts:')
processCodeCov = WMI.ExecQuery('select * from Win32_Process where Name="%s"' % pro... | normal | {
"blob_id": "bb6d6061365fad809448d09a1c031b984423b5e0",
"index": 8658,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef check_exsit(process_name):\n WMI = win32com.client.GetObject('winmgmts:')\n processCodeCov = WMI.ExecQuery(\n 'select * from Win32_Process where Name=\"%s\"' % proces... | [
0,
2,
3,
4,
5
] |
# (C) Datadog, Inc. 2018
# All rights reserved
# Licensed under a 3-clause BSD style license (see LICENSE)
from .agent import agent
from .clean import clean
from .config import config
from .create import create
from .dep import dep
from .env import env
from .meta import meta
from .release import release
from .run impor... | normal | {
"blob_id": "7a69a9fd6ee5de704a580e4515586a1c1d2b8017",
"index": 5874,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nALL_COMMANDS = (agent, clean, config, create, dep, env, meta, release, run,\n test, validate)\n",
"step-3": "from .agent import agent\nfrom .clean import clean\nfrom .config import c... | [
0,
1,
2,
3
] |
# -*- coding: utf-8 -*-
##################################
# @program synda
# @description climate models data transfer program
# @copyright Copyright "(c)2009 Centre National de la Recherche Scientifique CNRS.
# All Rights Reserved"
# @license CeCILL (https://raw.g... | normal | {
"blob_id": "0e6e84a31b626639e2aa149fd1ef89f3ef251cd7",
"index": 207,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Context(Base):\n\n def __init__(self, dataset='', capsys=None):\n super(Context, self).__init__(capsys=capsys)\n self.dataset = ''\n self.dataset = datase... | [
0,
4,
5,
6,
7
] |
# Import
import sys
from .step import Step
from .repeat import Repeat
# Workout
class Workout(object):
def __init__(self):
self.workout = []
self.steps = []
self.postfixEnabled = True
# TODO: check that len(name) <= 6
def addStep(self, name, duration):
self.workout.append(... | normal | {
"blob_id": "3f80c4c212259a8f3ff96bcc745fd28a85dac3ba",
"index": 8807,
"step-1": "<mask token>\n\n\nclass Workout(object):\n <mask token>\n <mask token>\n\n def addRepeat(self, names, durations, count):\n self.workout.append(Repeat(names, durations, count))\n\n def generateCode(self, filename=... | [
3,
4,
5,
6,
7
] |
import numpy as np
def GradientDescent(f, gradf, x0, epsilon, num_iter, line_search,
disp=False, callback=None, **kwargs):
x = x0.copy()
iteration = 0
opt_arg = {"f": f, "grad_f": gradf}
for key in kwargs:
opt_arg[key] = kwargs[key]
while True:
gradient = -gradf(x)
alpha = line_search(x... | normal | {
"blob_id": "dca36de5556b120b8b93eac0ad7b971ad735d907",
"index": 313,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef GradientDescent(f, gradf, x0, epsilon, num_iter, line_search, disp=\n False, callback=None, **kwargs):\n x = x0.copy()\n iteration = 0\n opt_arg = {'f': f, 'grad_f': gr... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/python
import os, sys
# Assuming /tmp/foo.txt exists and has read/write permissions.
ret = os.access("/tmp/foo.txt", os.F_OK)
print "F_OK - return value %s"% ret
ret = os.access("/tmp/foo.txt", os.R_OK)
print "R_OK - return value %s"% ret
ret = os.access("/tmp/foo.txt", os.W_OK)
print "W_OK -... | normal | {
"blob_id": "c9b76fed088b85cf68e96778016d8974fea84933",
"index": 4050,
"step-1": "#!/usr/bin/python\r\nimport os, sys\r\n\r\n# Assuming /tmp/foo.txt exists and has read/write permissions.\r\n\r\nret = os.access(\"/tmp/foo.txt\", os.F_OK)\r\nprint \"F_OK - return value %s\"% ret\r\n\r\nret = os.access(\"/tmp/foo.... | [
0
] |
# -*- coding: utf-8 -*-
# Generated by Django 1.11.6 on 2017-10-18 07:31
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
initial = True
dependencies = [
('auth', '0008_alter_user_username_max_length'),
]
operations = [... | normal | {
"blob_id": "ab343f88c84d45cf90bddd52623362f047c72d3c",
"index": 5754,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Migration(migrations.Migration):\n <mask token>\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Migration(migrations.Migration):\n initial = T... | [
0,
1,
2,
3,
4
] |
# from models import dist_model
# model = dist_model.DistModel()
from os.path import join
import models
import util.util as util
import matplotlib.pylab as plt
use_gpu = True
fig_outdir = r"C:\Users\ponce\OneDrive - Washington University in St. Louis\ImageDiffMetric"
#%%
net_name = 'squeeze'
SpatialDist = models.Percep... | normal | {
"blob_id": "8fcbaf2663c22015a0c47f00c2d4fb8db6a5c308",
"index": 6209,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif use_gpu:\n img0 = img0.cuda()\n<mask token>\nif use_gpu:\n img1 = img1.cuda()\n<mask token>\nplt.figure(figsize=[9, 3.5])\nplt.subplot(131)\nplt.imshow(img0_)\nplt.subplot(132)\n... | [
0,
1,
2,
3,
4
] |
def solution(record):
answer = []
db = {}
chatting = []
for log in record:
log_list = log.split()
if log_list[0] == 'Enter':
db[log_list[1]] = log_list[2]
chatting.append([True, log_list[1]])
elif log_list[0] == 'Leave':
chatting.append([Fals... | normal | {
"blob_id": "3ffe16494eb45896563a2952f3bcf80fc19b2750",
"index": 1226,
"step-1": "<mask token>\n",
"step-2": "def solution(record):\n answer = []\n db = {}\n chatting = []\n for log in record:\n log_list = log.split()\n if log_list[0] == 'Enter':\n db[log_list[1]] = log_lis... | [
0,
1,
2,
3
] |
# [SIG Python Task 1]
"""
Tasks to performs:
a) Print 'Hello, World! From SIG Python - <your name>' to the screen
b) Calculate Volume of a Sphere
c) Create a customised email template for all students,
informing them about a workshop.
PS: This is called a docstring... and it will not be interepreted
... | normal | {
"blob_id": "150e0180567b74dfcd92a6cd95cf6c6bf36f6b5d",
"index": 4228,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('hello, World! From SIG Python - Gaurangi Rawat')\n<mask token>\nprint('volume=', volume)\n<mask token>\nprint(email_msg)\n",
"step-3": "<mask token>\nprint('hello, World! From SI... | [
0,
1,
2,
3
] |
def solution(n, money):
save = [0] * (n+1)
save[0] = 1
for i in range(len(money)):
for j in range(1, n+1):
if j - money[i] >= 0:
save[j] += (save[j - money[i]] % 1000000007)
return save[n] | normal | {
"blob_id": "deeba82536d0366b3793bcbe78f78e4cfeabb612",
"index": 6241,
"step-1": "<mask token>\n",
"step-2": "def solution(n, money):\n save = [0] * (n + 1)\n save[0] = 1\n for i in range(len(money)):\n for j in range(1, n + 1):\n if j - money[i] >= 0:\n save[j] += sav... | [
0,
1,
2
] |
#!/usr/bin/python3
#https://github.com/pfnet-research/chainer-gan-lib/blob/master/wgan_gp/updater.py
import numpy as np
import chainer
import chainer.functions as F
from chainer import Variable
from chainer.dataset import convert
class WGANUpdater(chainer.training.updaters.StandardUpdater):
def __init__(self, *a... | normal | {
"blob_id": "a7099b2506de08893ca849146813505d88784895",
"index": 2402,
"step-1": "<mask token>\n\n\nclass WGANUpdater(chainer.training.updaters.StandardUpdater):\n\n def __init__(self, *args, **kwargs):\n self.gen, self.dis = kwargs.pop('models')\n self.n_dis = kwargs.pop('n_dis')\n self.... | [
3,
4,
5,
6,
7
] |
from django.contrib.auth.forms import UserCreationForm
from django.contrib.auth.views import LoginView
from django.shortcuts import render
from django.views import View
from django.views.generic import CreateView
from resume.forms import NewResumeForm
from vacancy.forms import NewVacancyForm
class MenuView(View):
... | normal | {
"blob_id": "a75691af17f6d1effd469d5c2ded340c71521ee1",
"index": 9310,
"step-1": "<mask token>\n\n\nclass MyLoginView(LoginView):\n redirect_authenticated_user = True\n template_name = 'login.html'\n\n\nclass HomeView(View):\n\n def get(self, request, *args, **kwargs):\n form = NewVacancyForm() i... | [
4,
6,
7,
8,
10
] |
import scraperwiki
html = scraperwiki.scrape('http://www.denieuwereporter.nl/')
# scrape headlines van denieuwereporter-alle h1 koppen
import lxml.html
root = lxml.html.fromstring(html)
tds = root.cssselect('h1')
for h1 in tds:
#print lxml.html.tostring(h1)
print h1.text_content()
record = {'h1': h1.text_c... | normal | {
"blob_id": "107b09696ac671e689235da55aaf4c26ae7c321c",
"index": 6353,
"step-1": "import scraperwiki\nhtml = scraperwiki.scrape('http://www.denieuwereporter.nl/')\n# scrape headlines van denieuwereporter-alle h1 koppen\n\nimport lxml.html\nroot = lxml.html.fromstring(html)\ntds = root.cssselect('h1')\nfor h1 in ... | [
0
] |
#
# -*- coding: utf-8 -*-
# Copyright 2019 Fortinet, Inc.
# GNU General Public License v3.0+
# (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
"""
The fortios firewall monitor class
It is in this file the runtime information is collected from the device
for a given resource, parsed, and the facts tree is popu... | normal | {
"blob_id": "62bc8fec6833c5e8bc1598941eaad141ab6c9d5a",
"index": 3758,
"step-1": "<mask token>\n\n\nclass FirewallFacts(object):\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass FirewallFacts(object):\n <mask token>\n <mask token>\n\n def populate_facts(self... | [
1,
2,
5,
6,
7
] |
import pandas as pd
dict_data = {'c0': [1, 2, 3], 'c1': [4, 5, 6], 'c2': [
7, 8, 9], 'c3': [10, 11, 12], 'c4': [13, 14, 15]}
df = pd.DataFrame(dict_data)
print(type(df))
print('\n')
print(df)
# <class 'pandas.core.frame.DataFrame'>
# c0 c1 c2 c3 c4
# 0 1 4 7 10 13
# 1 2 5 8 11 14
# 2 ... | normal | {
"blob_id": "22f4ae755e7ea43604db39452ca80f44f540708a",
"index": 9503,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(type(df))\nprint('\\n')\nprint(df)\n",
"step-3": "<mask token>\ndict_data = {'c0': [1, 2, 3], 'c1': [4, 5, 6], 'c2': [7, 8, 9], 'c3': [10, \n 11, 12], 'c4': [13, 14, 15]}\ndf =... | [
0,
1,
2,
3,
4
] |
from sklearn.naive_bayes import *
from sklearn import svm
from sklearn.pipeline import Pipeline
from sklearn.metrics import classification_report, confusion_matrix
from optparse import OptionParser
from helper import FileHelper, Word2VecHelper, GraphHelper
import helper
from helper.VectorHelper import *
import os
impo... | normal | {
"blob_id": "3bc9c6a66f749858ea5801202b0ac80755c1b347",
"index": 6493,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef trainW2v(args):\n clazz = [['Accidents', 'Arts', 'Attacks', 'Economy', 'Miscellaneous',\n 'Politics', 'Science', 'Sports', 'undefined'], ['Accidents', 'Arts',\n '... | [
0,
1,
2,
3,
4
] |
import pytest
import app
import urllib.parse
@pytest.fixture
def client():
app.app.config['TESTING'] = True
with app.app.test_client() as client:
yield client
def test_query_missing_args(client):
response = client.get('/data/query')
assert 'errors' in response.json and '400' in response.sta... | normal | {
"blob_id": "a598da0a749fcc5a6719cec31ede0eb13fab228e",
"index": 3171,
"step-1": "<mask token>\n\n\n@pytest.fixture\ndef client():\n app.app.config['TESTING'] = True\n with app.app.test_client() as client:\n yield client\n\n\ndef test_query_missing_args(client):\n response = client.get('/data/que... | [
6,
7,
9,
10,
11
] |
# -*- coding: utf-8 -*-
# DATE 2018-08-21
# AUTHER = tongzz
#
import MySQLdb
from Elements.LoginElements import *
import datetime
import sys
class Tradepasswd():
def __init__(self):
self.db_config={
'host': '172.28.38.59',
'usr': 'mysqladmin',
'passwd': '12... | normal | {
"blob_id": "ed66e8028d653cf6b7ea4703fef5a658665c48db",
"index": 1034,
"step-1": "# -*- coding: utf-8 -*-\r\n# DATE 2018-08-21\r\n# AUTHER = tongzz\r\n#\r\n\r\nimport MySQLdb\r\nfrom Elements.LoginElements import *\r\nimport datetime\r\nimport sys\r\nclass Tradepasswd():\r\n def __init__(self):\r\n sel... | [
0
] |
from django.core import serializers
from django.db import models
from uuid import uuid4
from django.utils import timezone
from django.contrib.auth.models import User
class Message(models.Model):
uuid=models.CharField(max_length=50)
user=models.CharField(max_length=20)
message=models.CharField(max_length=20... | normal | {
"blob_id": "1476d4f488e6c55234a34dc5b6182e3b8ad4f702",
"index": 6201,
"step-1": "<mask token>\n\n\nclass Message(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Message(models.Mo... | [
1,
4,
5,
6,
7
] |
import json
from logger import logger
def parse_json(text):
start = text.find("{")
end = text.find("}") + 1
try:
data = json.loads(text[start:end])
return data
except Exception:
logger.error("json解析失败：%s" % text)
| normal | {
"blob_id": "9f8fbfb8a9c849ca0e8881c479800c8e190e4a1c",
"index": 6485,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef parse_json(text):\n start = text.find('{')\n end = text.find('}') + 1\n try:\n data = json.loads(text[start:end])\n return data\n except Exception:\n ... | [
0,
1,
2,
3
] |
import sys, string, math
s = input()
print(ord(s))
| normal | {
"blob_id": "ade300f2921ca860bbe92aa351df2c88238b7996",
"index": 6039,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(ord(s))\n",
"step-3": "<mask token>\ns = input()\nprint(ord(s))\n",
"step-4": "import sys, string, math\ns = input()\nprint(ord(s))\n",
"step-5": null,
"step-ids": [
0,
... | [
0,
1,
2,
3
] |
import pandas as pd
import numpy as np
import inspect
from script.data_handler.Base.df_plotterMixIn import df_plotterMixIn
from script.util.MixIn import LoggerMixIn
from script.util.PlotTools import PlotTools
DF = pd.DataFrame
Series = pd.Series
class null_clean_methodMixIn:
@staticmethod
def drop_col(df: D... | normal | {
"blob_id": "198beb5a17575d781f7bce1ab36a6213ad7331b3",
"index": 5853,
"step-1": "<mask token>\n\n\nclass Base_dfCleaner(LoggerMixIn, null_clean_methodMixIn, df_plotterMixIn):\n <mask token>\n <mask token>\n\n def __init__(self, df: DF, df_Xs_keys, df_Ys_key, silent=False, verbose=0):\n LoggerMix... | [
8,
15,
16,
17,
19
] |
"""
openAI gym 'cart pole-v0'
"""
import numpy as np
import tensorflow as tf
from collections import deque
import random
import dqn
import gym
import matplotlib.pyplot as plt
# define environment
env = gym.make('CartPole-v0')
# define parameters
INPUT_SIZE = env.observation_space.shape[0]
OUTPUT_SIZE = env.action_sp... | normal | {
"blob_id": "9a40861239268aa62075b77b3ed452f31bb14fac",
"index": 2458,
"step-1": "<mask token>\n\n\ndef get_copy_var_ops(src_scope_name: str, dest_scope_name: str) ->list:\n holder = []\n src_vars = tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES, scope=\n src_scope_name)\n dest_vars = tf.get_... | [
4,
5,
6,
7,
8
] |
from tree import Tree, createIntTree
t = createIntTree()
print('show', t.root.show())
print('sum', t.root.sum())
print('find 3', t.root.find(3) != False)
print('evens', t.root.evens())
print('min depth', t.root.min_depth())
| normal | {
"blob_id": "21a7fd5148f73ac47adafc9d5c2361ebe318ae59",
"index": 2842,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('show', t.root.show())\nprint('sum', t.root.sum())\nprint('find 3', t.root.find(3) != False)\nprint('evens', t.root.evens())\nprint('min depth', t.root.min_depth())\n",
"step-3": ... | [
0,
1,
2,
3
] |
# -*- coding: utf-8 -*-
import pickle
import pathlib
from pathlib import Path
from typing import List, Tuple, Dict
import numpy as np
import torch
import torch.nn as nn
from torch.optim import SGD, Adam
from torch.utils.data import Dataset, DataLoader
from torchtext.data import get_tokenizer
from matplotlib import py... | normal | {
"blob_id": "9c653719ea511d78de9ddcc19442d9f9f7dc11dc",
"index": 4560,
"step-1": "<mask token>\n\n\nclass Vocabulary:\n \"\"\"\n Helper class that maps words to unique indices and the other way around\n \"\"\"\n\n def __init__(self, tokens: List[str]):\n self.word_to_idx = {'<PAD>': 0}\n ... | [
20,
23,
25,
30,
31
] |
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