code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print('hello word!')
<|reserved_special_token_1|>
import ply.lex as lex
print('hello word!')
<|reserved_special_token_1|>
import ply.lex as lex
print("hello word!")
| flexible | {
"blob_id": "84d0c439fcee4339250ced11dd2264740cc20d9c",
"index": 9567,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('hello word!')\n",
"step-3": "import ply.lex as lex\nprint('hello word!')\n",
"step-4": "import ply.lex as lex\n\nprint(\"hello word!\")\n",
"step-5": null,
"step-ids": [
... | [
0,
1,
2,
3
] |
from django.db import models
from django.db.models.base import Model
# Create your models here.
class Categoria(models.Model):
categoria = models.CharField(max_length=40)
def __str__(self):
return self.categoria
class Producto(models.Model):
codigo = models.CharField(max_length=40)
nombre = mo... | normal | {
"blob_id": "0e19d7251db3382c34ad2d38a7984b65325ecfbf",
"index": 7584,
"step-1": "<mask token>\n\n\nclass Descuento(models.Model):\n <mask token>\n <mask token>\n\n def __str__(self):\n return self.codigo_descuento\n\n\nclass Venta(models.Model):\n descripcion = models.CharField(max_length=100... | [
22,
29,
33,
34,
40
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if __name__ == '__main__':
from numpy.distutils.core import setup
setup(name='array-sqrt-openmp', description=
'Illustration of Python extensions using OpenMP', author=
'Mihai Duta', author_email='mihai.dut... | flexible | {
"blob_id": "c24bf42cfeaa1fb8ac188b9e08146762e0e86fed",
"index": 1542,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n from numpy.distutils.core import setup\n setup(name='array-sqrt-openmp', description=\n 'Illustration of Python extensions using OpenMP', author=... | [
0,
1,
2,
3,
4
] |
from datetime import datetime
from app import db
class Vocabulary(db.Model):
_id = db.Column(db.Integer, primary_key=True)
language = db.Column(db.String(64), index=True)
word = db.Column(db.String(64), index=True, unique=True)
date = db.Column(db.DateTime, index=True, default=datetime.utcnow)
| normal | {
"blob_id": "834469f9c6e065fb29dfe1fd3e421fbb752f5094",
"index": 7708,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Vocabulary(db.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Vocabulary(db.Model):\n _id = db.Column... | [
0,
1,
2,
3
] |
import configparser
config = configparser.ConfigParser()
config.read('config.ini')
settings=config['Settings']
colors=config['Colors']
import logging
logger = logging.getLogger(__name__)
logLevel = settings.getint('log-level')
oneLevelUp = 20
#I don't know if this will work before loading the transformers module?
#s... | normal | {
"blob_id": "e4fb932c476ca0222a077a43499bf9164e1f27d0",
"index": 8896,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nconfig.read('config.ini')\n<mask token>\nlogging.getLogger('transformers.tokenization_utils').setLevel(logLevel +\n oneLevelUp)\nlogging.getLogger('transformers.modeling_utils').setLev... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class BaseHandler(webapp2.RequestHandler):
@webapp2.cached_property
def auth(self):
"""Shortcut to access the auth instance as a property."""
return auth.get_auth()
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
... | flexible | {
"blob_id": "fe7fb9a4a5ca2bb8dab0acf440eb2fac127264ce",
"index": 2631,
"step-1": "<mask token>\n\n\nclass BaseHandler(webapp2.RequestHandler):\n\n @webapp2.cached_property\n def auth(self):\n \"\"\"Shortcut to access the auth instance as a property.\"\"\"\n return auth.get_auth()\n <mask t... | [
40,
42,
48,
49,
51
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for i in my_list:
new_list.append(i ** 2)
<|reserved_special_token_0|>
print(my_dict)
<|reserved_special_token_0|>
print(new_list_round)
<|reserved_special_token_1|>
my_list = [1, 2, 3, 4, 5]
new_list = []
for i in my_list:... | flexible | {
"blob_id": "e54eea2261517a2b15fde23c46b3fe75c0efec64",
"index": 7746,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in my_list:\n new_list.append(i ** 2)\n<mask token>\nprint(my_dict)\n<mask token>\nprint(new_list_round)\n",
"step-3": "my_list = [1, 2, 3, 4, 5]\nnew_list = []\nfor i in my_li... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class GPTD_fixedGrid:
def __init__(self, env, sigma0, gamma, kernel, D, V_mu=[]):
self.env = env
self.gamma = gamma
self.sigma0 = sigma0
self.kernel = kernel.kernel
if not V_mu:
V_mu = lambda s: np.zeros((s.shape[1], 1))
sel... | flexible | {
"blob_id": "92eaceb46974ba3a5944300139d5929d44673181",
"index": 1223,
"step-1": "<mask token>\n\n\nclass GPTD_fixedGrid:\n\n def __init__(self, env, sigma0, gamma, kernel, D, V_mu=[]):\n self.env = env\n self.gamma = gamma\n self.sigma0 = sigma0\n self.kernel = kernel.kernel\n ... | [
3,
5,
6,
7,
8
] |
import cv2
import numpy as np
import copy
imgpath = 'D:\\DIP-Project1/b.jpg'
img = cv2.imread(imgpath)
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
cv2.imshow('img', img)
row = len(img)
col = len(img[0])
def medianflt(img, i, j, msize, mr, mc):
pxls = []
for a in range(msize):
for b in range(msize):
... | normal | {
"blob_id": "cfcce8c760f6ba49ce450d78782cb8f3b5fc1188",
"index": 2857,
"step-1": "<mask token>\n\n\ndef medianflt(img, i, j, msize, mr, mc):\n pxls = []\n for a in range(msize):\n for b in range(msize):\n mi = i + a - mr\n mj = j + b - mc\n pxls.append(img[mi][mj])\n... | [
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class Post:
def __init__(self, date, text, medias):
self.date = date
self.text = text
self.medias = medias
self.dcim = []
self.daterank = 0
self.extra = False
def __lt__(self, other):
return self.date < other.date
@cla... | flexible | {
"blob_id": "6018f35afc6646d0302ca32de649ffe7d544a765",
"index": 3377,
"step-1": "<mask token>\n\n\nclass Post:\n\n def __init__(self, date, text, medias):\n self.date = date\n self.text = text\n self.medias = medias\n self.dcim = []\n self.daterank = 0\n self.extra =... | [
79,
84,
88,
100,
110
] |
# Author: Sam Erickson
# Date: 2/23/2016
#
# Program Description: This program gives the integer coefficients x,y to the
# equation ax+by=gcd(a,b) given by the extended Euclidean Algorithm.
def extendedEuclid(a,b):
"""
Preconditions - a and b are both positive integers.
Posconditions - The equation for ax... | normal | {
"blob_id": "36e5b0f40b8016f39120f839766db0ac518c9bed",
"index": 4712,
"step-1": "<mask token>\n",
"step-2": "def extendedEuclid(a, b):\n \"\"\"\n Preconditions - a and b are both positive integers.\n Posconditions - The equation for ax+by=gcd(a,b) has been returned where\n x and y ... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution(object):
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution(object):
def gcdOfStrings(self, str1, str2):
if str1 == str2:
return str1
elif not str1 or not str2:
return ''... | flexible | {
"blob_id": "ab632c3c8a7f295a890de19af82fde87c6d600bc",
"index": 1674,
"step-1": "<mask token>\n",
"step-2": "class Solution(object):\n <mask token>\n",
"step-3": "class Solution(object):\n\n def gcdOfStrings(self, str1, str2):\n if str1 == str2:\n return str1\n elif not str1 o... | [
0,
1,
2
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from datetime import datetime
archivo = open("salida2.csv", "a+")
startTime = datetime.now()
def mergeSort(alist):
print("Splitting ",alist)
if len(alist)>1:
mid = len(alist)//2
lefthalf = alist[:mid]
righthalf = alist[mid:]
merge... | normal | {
"blob_id": "9e98c6b59433369bca3d4f7ae261f7e7ab3aae6b",
"index": 4161,
"step-1": "<mask token>\n\n\ndef mergeSort(alist):\n print('Splitting ', alist)\n if len(alist) > 1:\n mid = len(alist) // 2\n lefthalf = alist[:mid]\n righthalf = alist[mid:]\n mergeSort(lefthalf)\n m... | [
1,
2,
3,
4,
5
] |
import sys
sys.setrecursionlimit(10 ** 6)
n, s = map(int, input().split())
value = list(map(int, input().split()))
count = 0
def recursive(index, sum):
global count
if index == n:
if sum == s:
count += 1
return
recursive(index + 1, sum + value[index])
recursive(index + 1, s... | normal | {
"blob_id": "f1aa12ec4ee2482db8abf1121a3443502544e1a2",
"index": 2815,
"step-1": "<mask token>\n\n\ndef recursive(index, sum):\n global count\n if index == n:\n if sum == s:\n count += 1\n return\n recursive(index + 1, sum + value[index])\n recursive(index + 1, sum)\n\n\n<mas... | [
1,
2,
3,
4
] |
from setup import app, manager
from Users.controller import user_controller
from Test.controller import test_controller
app.register_blueprint(test_controller, url_prefix="/test") #registeting test_controller blueprint with the main "app" and asking it to handle all url that begins with "/test". For eg: http://127.0.0... | normal | {
"blob_id": "afa22db946f77e9b33a443657592c20fbea21eb1",
"index": 6146,
"step-1": "<mask token>\n",
"step-2": "<mask token>\napp.register_blueprint(test_controller, url_prefix='/test')\napp.register_blueprint(user_controller, url_prefix='/')\nif __name__ == '__main__':\n app.run(debug=True)\n",
"step-3": "... | [
0,
1,
2,
3
] |
# Copyright (c) 2017, Matt Layman
import bisect
import configparser
import os
import smartypants
from werkzeug.contrib.atom import AtomFeed, FeedEntry
from handroll import logger
from handroll.exceptions import AbortError
from handroll.extensions.base import Extension
from handroll.i18n import _
class BlogPost(obj... | normal | {
"blob_id": "c3d9ad49b62c56dfbd9674cb1ac5c206e6401a27",
"index": 830,
"step-1": "<mask token>\n\n\nclass BlogBuilder(object):\n <mask token>\n\n def _generate_output(self):\n \"\"\"Generate output that belongs in the destination file.\n\n Subclasses must implement this method.\n \"\"\"... | [
13,
24,
28,
32,
38
] |
<|reserved_special_token_0|>
class StudentListView(ListView):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def get_queryset(self):
return Student.objects.filter(course='Python')
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|res... | flexible | {
"blob_id": "bcad9869e6bc9b17eee490897b4b706171381366",
"index": 2093,
"step-1": "<mask token>\n\n\nclass StudentListView(ListView):\n <mask token>\n <mask token>\n <mask token>\n\n def get_queryset(self):\n return Student.objects.filter(course='Python')\n <mask token>\n <mask token>\n",... | [
2,
4,
5,
6,
7
] |
from flask import Blueprint, request, make_response
from untils import restful, cacheuntil
from untils.captcha import Captcha
from exts import smsapi
from .forms import SMSCaptchaForm
from io import BytesIO
bp = Blueprint('common', __name__, url_prefix='/c')
# @bp.route('/sms_captcha/', methods=['post'])
# def sms_c... | normal | {
"blob_id": "856beaf3b9dad333d5b48c1be3a8ad917f8d020c",
"index": 3634,
"step-1": "<mask token>\n\n\n@bp.route('/captcha/')\ndef CaptchaView():\n text, image = Captcha.gene_graph_captcha()\n cacheuntil.set(text.lower(), text.lower())\n out = BytesIO()\n image.save(out, 'png')\n out.seek(0)\n res... | [
1,
2,
3,
4,
5
] |
from typing import Sized
import pygame
import time
from pygame.locals import *
import random
SIZE = 20
BACKGROUND = (45, 34, 44)
W = 800
H = 400
SCREEN = (W, H)
class Snake:
def __init__(self, parent_screen, length):
self.parent_screen = parent_screen
self.length = length
self.snake = pyg... | normal | {
"blob_id": "935853a4afdb50a4652e14913d0cdb251a84ea14",
"index": 6427,
"step-1": "<mask token>\n\n\nclass Food:\n <mask token>\n\n def draw(self):\n seq = [self.food1, self.food2]\n self.parent_screen.blit(random.choice(seq), (self.food_x, self.food_y))\n pygame.display.flip()\n\n d... | [
17,
26,
29,
30,
31
] |
TOTAL = 1306336
ONE = {
'0': 1473,
'1': 5936,
'2': 3681,
'3': 2996,
'4': 2480,
'5': 2494,
'6': 1324,
'7': 1474,
'8': 1754,
'9': 1740,
'a': 79714,
'b': 83472,
'c': 78015,
'd': 61702,
'e': 42190,
'f': 68530,
'g': 48942,
'h': 63661,
'i': 34947,
'j': 24312,
'k': 26724,
'l': 66351,
'm': 77245,
'n': 36942,
'o': 40744,
'p': ... | normal | {
"blob_id": "f254f93193a7cb7ed2e55e4481ed85821cafcd7b",
"index": 4339,
"step-1": "<mask token>\n",
"step-2": "TOTAL = 1306336\nONE = {'0': 1473, '1': 5936, '2': 3681, '3': 2996, '4': 2480, '5': 2494,\n '6': 1324, '7': 1474, '8': 1754, '9': 1740, 'a': 79714, 'b': 83472, 'c':\n 78015, 'd': 61702, 'e': 4219... | [
0,
1,
2
] |
import signal
import time
import sdnotify
n = sdnotify.SystemdNotifier()
if __name__ == '__main__':
n.notify("READY=1")
time.sleep(2)
| normal | {
"blob_id": "78dc2193c05ddb4cd4c80b1c0322890eca7fcf19",
"index": 789,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n n.notify('READY=1')\n time.sleep(2)\n",
"step-3": "<mask token>\nn = sdnotify.SystemdNotifier()\nif __name__ == '__main__':\n n.notify('READY=1')\n ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class KaliteUI(object):
def __init__(self, kaliteApp):
dropdown = DropDown()
dropdown_btn = Button(text='menu', size_hint_x=None, size_hint_y=
None, size=(150, 40), font_size=18, color=(0.06, 0.6, 0.2, 1),
bold=True, background_color=(1, 1, 1, ... | flexible | {
"blob_id": "35cd1c45294b826784eab9885ec5b0132624c957",
"index": 4028,
"step-1": "<mask token>\n\n\nclass KaliteUI(object):\n\n def __init__(self, kaliteApp):\n dropdown = DropDown()\n dropdown_btn = Button(text='menu', size_hint_x=None, size_hint_y=\n None, size=(150, 40), font_size=... | [
9,
11,
14,
15,
16
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def get(url):
return requests.get(url).text
<|reserved_special_token_1|>
import requests
def get(url):
return requests.get(url).text
| flexible | {
"blob_id": "671ecf23df1da659d186014afa738d0608ad404d",
"index": 9251,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get(url):\n return requests.get(url).text\n",
"step-3": "import requests\n\n\ndef get(url):\n return requests.get(url).text\n",
"step-4": null,
"step-5": null,
"step... | [
0,
1,
2
] |
# Testing
import sys, os
sys.dont_write_bytecode = True
import argparse, socket
from requestframe import RequestFrame
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--header-mutate-level", type=int, choices=range(11), nargs='?', help="Set the mutation level for the headers ... | normal | {
"blob_id": "350a79d6cead6814ad48292b14a204e753dc938c",
"index": 4363,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n parser = argparse.ArgumentParser()\n parser.add_argument('--header-mutate-level', type=int, choices=range(11\n ), nargs='?', help=\n 'Set ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def main():
str1 = 'パトカー'
str2 = 'タクシー'
print(''.join([(x[0] + x[1]) for x in zip(str1, str2)]))
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def question():
print('02. 「パトカー」＋「タクシー」＝「パタトクカシーー」'... | flexible | {
"blob_id": "32869a88bb59d47281249b6ebe2357328beb0359",
"index": 3572,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main():\n str1 = 'パトカー'\n str2 = 'タクシー'\n print(''.join([(x[0] + x[1]) for x in zip(str1, str2)]))\n\n\n<mask token>\n",
"step-3": "def question():\n print('02. 「パトカ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Lenet(nn.Module):
<|reserved_special_token_0|>
def forward(self, x):
layer_w = self.fc2.weight
sigma = layer_w.std().data.cpu().numpy()
layer_w_numpy = layer_w.data.cpu().numpy()
scale = 0.17
noise = np.random.normal(0, scale * sigma,... | flexible | {
"blob_id": "a38a5010c9edbed0929da225b4288396bb0d814e",
"index": 6989,
"step-1": "<mask token>\n\n\nclass Lenet(nn.Module):\n <mask token>\n\n def forward(self, x):\n layer_w = self.fc2.weight\n sigma = layer_w.std().data.cpu().numpy()\n layer_w_numpy = layer_w.data.cpu().numpy()\n ... | [
2,
4,
5,
6,
7
] |
b = int(input('enter anum '))
for a in range(1, 11, 1):
print(b, 'x', a, '=', a * b)
| normal | {
"blob_id": "bf83556b8e8855a0e410fcfb3b42161fbc681830",
"index": 3075,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor a in range(1, 11, 1):\n print(b, 'x', a, '=', a * b)\n",
"step-3": "b = int(input('enter anum '))\nfor a in range(1, 11, 1):\n print(b, 'x', a, '=', a * b)\n",
"step-4": nul... | [
0,
1,
2
] |
<|reserved_special_token_0|>
@micropython.viper
def viper_int(x: int, y: int) ->int:
return x + y + 3
<|reserved_special_token_0|>
@micropython.viper
def viper_local(x: int) ->int:
y = 4
return x + y
<|reserved_special_token_0|>
@micropython.viper
def viper_no_annotation(x, y):
return x * y
... | flexible | {
"blob_id": "eec52695e5afcc21e5fed6453e96cc3a58e7c1df",
"index": 101,
"step-1": "<mask token>\n\n\n@micropython.viper\ndef viper_int(x: int, y: int) ->int:\n return x + y + 3\n\n\n<mask token>\n\n\n@micropython.viper\ndef viper_local(x: int) ->int:\n y = 4\n return x + y\n\n\n<mask token>\n\n\n@micropyt... | [
9,
10,
12,
14,
15
] |
def main():
num = int(input('dia: '))
dia(num)
def dia(a):
if a == 1:
print('Domingo !')
elif a == 2:
print('Segunda !')
else:
print('valor invalido !')
main()
| normal | {
"blob_id": "07332e2da5458fda2112de2507037a759d3c62db",
"index": 3382,
"step-1": "<mask token>\n",
"step-2": "def main():\n num = int(input('dia: '))\n dia(num)\n\n\n<mask token>\n",
"step-3": "def main():\n num = int(input('dia: '))\n dia(num)\n\n\ndef dia(a):\n if a == 1:\n print('Dom... | [
0,
1,
2,
3
] |
"""
contains generic code for use in main menus. currently this is a function which turns dictionaries of functions
into a menu. I envision any further menu functions being stored here so don't expect it to run like a pipeline but
rather like a suite of individual menus.
TODO - refactor spider selection function as je... | normal | {
"blob_id": "f28b47e1b07011ce9d0708331f68d7f16195c567",
"index": 7225,
"step-1": "<mask token>\n\n\ndef final_option(dict_of_options, back):\n \"\"\"\n adds the final option to the dictionary based on a boolean\n\n :param dict_of_options: dictionary with readable labels as keys and uncalled functions as... | [
8,
10,
11,
12,
13
] |
<|reserved_special_token_0|>
class Post(models.Model):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def __str__(self):
return self.title
class User(mo... | flexible | {
"blob_id": "3aa8c9b39174f0ed5799d6991516b34ca669b7d6",
"index": 9765,
"step-1": "<mask token>\n\n\nclass Post(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def __str__(self):\n return self.title\n\n\nclass User(models.Mod... | [
6,
7,
8,
9,
10
] |
<|reserved_special_token_0|>
class Button:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def read_button(self):
self.status = GPIO.input(self.button_pin)
def light(self, stat):
if stat:
GPIO.out... | flexible | {
"blob_id": "878937e19d6a48a0d44309efbac1d41c208ce849",
"index": 6195,
"step-1": "<mask token>\n\n\nclass Button:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def read_button(self):\n self.status = GPIO.input(self.button_pin)\n\n def light(self, stat):\n if stat... | [
4,
5,
6,
7,
8
] |
import os
from flask import Flask, request, redirect, url_for, render_template, send_from_directory
from werkzeug.utils import secure_filename
import chardet as chardet
import pandas as pd
UPLOAD_FOLDER = os.path.dirname(os.path.abspath(__file__)) + '/uploads/'
DOWNLOAD_FOLDER = os.path.dirname(os.path.abspath(__file_... | normal | {
"blob_id": "eb17de8828a600832253c4cfeeb91503b6876dd7",
"index": 9963,
"step-1": "<mask token>\n\n\ndef allowed_file(filename):\n return '.' in filename and filename.rsplit('.', 1)[1].lower(\n ) in ALLOWED_EXTENSIONS\n\n\n@app.route('/', methods=['GET', 'POST'])\ndef index():\n if request.method == ... | [
5,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
class SQLiteConnection(ConnectionBackend):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
async def connect(self):
self.db = await aiosqlite.connect(self.db_name)
self.db.row_factory = aiosqlite.Row
async def disconnect(self):
await sel... | flexible | {
"blob_id": "191a57d3f13fcbe217ff6d0bd92dea163d5fb3cf",
"index": 4822,
"step-1": "<mask token>\n\n\nclass SQLiteConnection(ConnectionBackend):\n <mask token>\n <mask token>\n\n async def connect(self):\n self.db = await aiosqlite.connect(self.db_name)\n self.db.row_factory = aiosqlite.Row\... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
while no != 0:
r = no % 10
no = no // 10
rev = rev * 10 + r
print('reverse no is:', rev)
<|reserved_special_token_1|>
no = int(input('enter no:'))
rev = 0
while no != 0:
r = no % 10
no = no // 10
rev = r... | flexible | {
"blob_id": "b2371f9c774c605a52ff1a4fae2dd44a856076aa",
"index": 5522,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile no != 0:\n r = no % 10\n no = no // 10\n rev = rev * 10 + r\nprint('reverse no is:', rev)\n",
"step-3": "no = int(input('enter no:'))\nrev = 0\nwhile no != 0:\n r = no... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def process_std(standard_input_file):
try:
with open(standard_input_file, 'r') as in_handle:
lin_reg_lst = []
for line in in_handle:
line = line.strip('\n')
lin_reg_lst.append(line)
except IOError:
print('Coul... | flexible | {
"blob_id": "19949b07c866d66b3ef00b6a386bf89f03e06294",
"index": 7984,
"step-1": "<mask token>\n\n\ndef process_std(standard_input_file):\n try:\n with open(standard_input_file, 'r') as in_handle:\n lin_reg_lst = []\n for line in in_handle:\n line = line.strip('\\n'... | [
3,
4,
5,
6,
8
] |
# -*- coding: utf-8 -*-
"""
Created on Tue Oct 9 16:22:21 2018
@author: SDis
"""
#import Code.Members_module
class Resources:
""" Parent class for Books and eResources containg the main data fields and related setters and getters"""
def __init__(self, title, author, publisher, year):
self.title = tit... | normal | {
"blob_id": "0709d413ddbe41a0c97f94b7819fdfded241d3fc",
"index": 691,
"step-1": "<mask token>\n\n\nclass Resources:\n <mask token>\n\n def __init__(self, title, author, publisher, year):\n self.title = title\n self.author = author\n self.publisher = publisher\n self.year = year\... | [
4,
8,
9,
10,
13
] |
from __future__ import unicode_literals
import json, alice_static
import logging
from random import choice
# Импортируем подмодули Flask для запуска веб-сервиса.
from flask import Flask, request
app = Flask(__name__)
logging.basicConfig(level=logging.DEBUG)
# Хранилище данных о сессиях.
sessionStorage = {}
# Задаем... | normal | {
"blob_id": "2df679fc3407c15f5d0c006e9da8d1fc74bcf875",
"index": 5705,
"step-1": "from __future__ import unicode_literals\nimport json, alice_static\nimport logging\nfrom random import choice\n# Импортируем подмодули Flask для запуска веб-сервиса.\nfrom flask import Flask, request\napp = Flask(__name__)\n\n\nlog... | [
0
] |
<|reserved_special_token_0|>
class BaseCollectionSerializer(ResolweBaseSerializer):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
... | flexible | {
"blob_id": "d6f8ec0fd8be0fa7019a84af47d08ab8b5b32d92",
"index": 1449,
"step-1": "<mask token>\n\n\nclass BaseCollectionSerializer(ResolweBaseSerializer):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def get_status(self, coll... | [
6,
8,
9,
11,
12
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
@pytest.mark.asyncio
async def test_authenticator(aioresponse: aioresponses) ->None:
with open('tests/fixtures/auth_pin_status.xml') as file:
aioresponse.get('http://1.2.3.4:8080/ws/apps/CloudPINPage', body=
... | flexible | {
"blob_id": "e1448e62020f87e315d219be97d9af84607441df",
"index": 9104,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@pytest.mark.asyncio\nasync def test_authenticator(aioresponse: aioresponses) ->None:\n with open('tests/fixtures/auth_pin_status.xml') as file:\n aioresponse.get('http://1.... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def parse_response(permission, response):
return response
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def get_command(session, parsed_message):
return 'stop', 'restart'
def parse_response(permission,... | flexible | {
"blob_id": "acd5cf675522c90fc9fbc96bdeb52f66835626b4",
"index": 3489,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef parse_response(permission, response):\n return response\n",
"step-3": "<mask token>\n\n\ndef get_command(session, parsed_message):\n return 'stop', 'restart'\n\n\ndef pars... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class USBHandler:
<|reserved_special_token_0|>
def __init__(self):
self.initialized = False
self.run_task = None
self.waiters = {}
self.queues = {}
self.logger = logging.getLogger('.'.join((__name__, self.__class__.
__name__)))
... | flexible | {
"blob_id": "50b630b762251f8646044b234ac4b82b8e4b645b",
"index": 8460,
"step-1": "<mask token>\n\n\nclass USBHandler:\n <mask token>\n\n def __init__(self):\n self.initialized = False\n self.run_task = None\n self.waiters = {}\n self.queues = {}\n self.logger = logging.ge... | [
3,
7,
8,
9,
10
] |
"""Derivation of variable ``co2s``."""
import dask.array as da
import iris
import numpy as np
import stratify
from ._baseclass import DerivedVariableBase
def _get_first_unmasked_data(array, axis):
"""Get first unmasked value of an array along an axis."""
mask = da.ma.getmaskarray(array)
numerical_mask = ... | normal | {
"blob_id": "7c9b68b2d32d8e435f332d4412ea1ba899607ec4",
"index": 9395,
"step-1": "<mask token>\n\n\nclass DerivedVariable(DerivedVariableBase):\n <mask token>\n\n @staticmethod\n def required(project):\n \"\"\"Declare the variables needed for derivation.\"\"\"\n required = [{'short_name': ... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
class Solution:
<|reserved_special_token_0|>
class Solution:
def isPowerOfTwo(self, n: int) ->bool:
return n > 0 and n & n - 1 == 0
class Solution:
def isPowerOfTwo(self, n: int) ->bool:
return n > 0 and math.log10(n) / math.log10(2) % 1 == 0
class Solu... | flexible | {
"blob_id": "32066db8b43bc70c564cce5a33f50921285b3627",
"index": 6477,
"step-1": "<mask token>\n\n\nclass Solution:\n <mask token>\n\n\nclass Solution:\n\n def isPowerOfTwo(self, n: int) ->bool:\n return n > 0 and n & n - 1 == 0\n\n\nclass Solution:\n\n def isPowerOfTwo(self, n: int) ->bool:\n ... | [
11,
17,
19,
21,
22
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
ap.add_argument('-D', '--dir', required=False, help='Directory to sort')
<|reserved_special_token_0|>
if args['dir'] == None:
DIR = os.getcwd()
elif os.path.exists(args['dir']):
DIR = args['dir']
for file in os.listdir(DIR... | flexible | {
"blob_id": "93737e4c409d0efb1ae2263cb60d4b03d9aad0d8",
"index": 247,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nap.add_argument('-D', '--dir', required=False, help='Directory to sort')\n<mask token>\nif args['dir'] == None:\n DIR = os.getcwd()\nelif os.path.exists(args['dir']):\n DIR = args['d... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def isSubsetSum(set, n, sum):
subset = [[(False) for i in range(sum + 1)] for i in range(n + 1)]
for i in range(n + 1):
subset[i][0] = True
for i in range(1, sum + 1):
subset[0][i] = False
for i in range(1, n + 1):
for ... | flexible | {
"blob_id": "830e7e84eebd6a4adb411cc95c9e9c8ff7bdac30",
"index": 778,
"step-1": "<mask token>\n",
"step-2": "def isSubsetSum(set, n, sum):\n subset = [[(False) for i in range(sum + 1)] for i in range(n + 1)]\n for i in range(n + 1):\n subset[i][0] = True\n for i in range(1, sum + 1):\n s... | [
0,
1,
2,
3,
4
] |
import unittest
from app.party import Party
from app.guest import Guest
from app.shoppingList import ShoppingList
def test_aPartywithNoGuestsShouldHaveNoPartyGuests():
party = Party()
assert 0 == party.numberOfGuests()
def test_aPartywithOneGuestShouldHaveOnePartyGuest():
party = Party()
lisa = Guest("Lisa", 'fe... | normal | {
"blob_id": "a8df6b575afbf6db415e0676a796623f2a9b7a70",
"index": 8416,
"step-1": "<mask token>\n\n\ndef test_aPartywithOneGuestShouldHaveOnePartyGuest():\n party = Party()\n lisa = Guest('Lisa', 'female')\n party.attendedBy(lisa)\n assert 1 == party.numberOfGuests()\n\n\ndef test_aPartywithThreeGuest... | [
6,
8,
9,
10,
12
] |
#=======================================================================
__version__ = '''0.0.01'''
__sub_version__ = '''20130714221105'''
__copyright__ = '''(c) Alex A. Naanou 2011'''
#-----------------------------------------------------------------------
import os
import sha
import md5
import base64
... | normal | {
"blob_id": "d03f87b7dfa8fe2c63500effda1bea5e41f17ffc",
"index": 3787,
"step-1": "#=======================================================================\r\n\r\n__version__ = '''0.0.01'''\r\n__sub_version__ = '''20130714221105'''\r\n__copyright__ = '''(c) Alex A. Naanou 2011'''\r\n\r\n\r\n#---------------------... | [
0
] |
import rdflib
import csv
from time import sleep
gtypes = {}
dtypes = {}
atypes = {}
g = rdflib.Graph()
g.parse("http://geographicknowledge.de/vocab/CoreConceptData.rdf#")
g.parse("./ontology.ttl", format="ttl")
sleep(.5)
results = g.query("""
prefix skos: <http://www.w3.org/2004/02/skos/core#>
prefix ccd: ... | normal | {
"blob_id": "eb1fbe2de3c8548175eb3c8720353e466e3b68c7",
"index": 7336,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ng.parse('http://geographicknowledge.de/vocab/CoreConceptData.rdf#')\ng.parse('./ontology.ttl', format='ttl')\nsleep(0.5)\n<mask token>\nfor result in results:\n uri, geometry_type = re... | [
0,
1,
2,
3,
4
] |
__path__.append(
'/cvmfs/cms.cern.ch/slc6_amd64_gcc481/cms/cmssw-patch/CMSSW_7_0_6_patch3/python/ggAnalysis'
)
| normal | {
"blob_id": "0345c3c2049c972370cd7bde5a6e0a1dfa5dfe66",
"index": 3719,
"step-1": "<mask token>\n",
"step-2": "__path__.append(\n '/cvmfs/cms.cern.ch/slc6_amd64_gcc481/cms/cmssw-patch/CMSSW_7_0_6_patch3/python/ggAnalysis'\n )\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,... | [
0,
1
] |
import logging
import os
import time
from datetime import datetime
from pathlib import Path
from configargparse import ArgumentParser
from cryptography import x509
from cryptography.hazmat.backends import default_backend
from cryptography.x509.oid import ExtensionOID
from cryptography.x509.extensions import ExtensionN... | normal | {
"blob_id": "83be35b79dcaa34f9273281976ebb71e81c58cdd",
"index": 8673,
"step-1": "<mask token>\n\n\nclass SslExporter(object):\n gauges = {}\n\n def __init__(self, cert_paths):\n self.cert_paths = cert_paths\n\n def collect(self):\n self.gauges['ssl_valid_days'] = GaugeMetricFamily('ssl_va... | [
6,
7,
8,
9,
10
] |
import java.io.BufferedReader;
import java.io.IOException;
import java.io.InputStreamReader;
public class Main {
public static void findSubNode(Node root) {
}
public static void main(String args[]) throws IOException {
BufferedReader br = new BufferedReader(new InputStreamReader(System.in));
... | normal | {
"blob_id": "6d0a945c9eaf6564a327928880df1f0aeed2e5d0",
"index": 9649,
"step-1": "import java.io.BufferedReader;\nimport java.io.IOException;\nimport java.io.InputStreamReader;\n\npublic class Main {\n\n public static void findSubNode(Node root) {\n\n }\n\n public static void main(String args[]) throws ... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def bigquery(datafile, dataset=os.environ['BQDATASET'], project=os.environ[
'GCPPROJECT'], schema=[{'name': 'conversation', 'type': 'STRING'}, {
'name': 'id', 'type': 'INTEGER'}, {'name': 'from', 'type': 'STRING'}, {
... | flexible | {
"blob_id": "d6046217308745b85455aed78734700b9622782c",
"index": 7559,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef bigquery(datafile, dataset=os.environ['BQDATASET'], project=os.environ[\n 'GCPPROJECT'], schema=[{'name': 'conversation', 'type': 'STRING'}, {\n 'name': 'id', 'type': 'INTEG... | [
0,
1,
2,
3
] |
import numpy as np
import cv2
from PIL import Image
import pytesseract as tess
#Function to check the area range and width-height ratio
def ratio(area, width,height):
ratio = float(width)/float(height)
if ratio < 1:
ratio = 1/ ratio
if (area<1063.62 or area> 73862.5) or (ratio<3 or ratio> 6):
return False... | normal | {
"blob_id": "ab610af97d2b31575ea496b8fddda693353da8eb",
"index": 2870,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef ratio(area, width, height):\n ratio = float(width) / float(height)\n if ratio < 1:\n ratio = 1 / ratio\n if (area < 1063.62 or area > 73862.5) or (ratio < 3 or rat... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class TestSTCHANGE:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class TestSTCHANGE:
def setup_method(self... | flexible | {
"blob_id": "87f8cc65cf7d0ea932de79a6daf5b29ad387ec6f",
"index": 7103,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass TestSTCHANGE:\n <mask token>\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass TestSTCHANGE:\n\n def setup_method(self, method):\n self.d... | [
0,
1,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def fetchsquare(request, id):
try:
therm = Therm.objects.get(id=id)
except Therm.DoesNotExist:
raise Http404('This item does not exist')
return render(request, 'thermometer/fetchsquare.html', {'therm'... | flexible | {
"blob_id": "504d4afc4b3e708d43110a2d85676fb745f1aba8",
"index": 9874,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef fetchsquare(request, id):\n try:\n therm = Therm.objects.get(id=id)\n except Therm.DoesNotExist:\n raise Http404('This item does not exist')\n return render... | [
0,
1,
2,
3,
4
] |
# Copyright 2011 Isaku Yamahata
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required b... | normal | {
"blob_id": "d56e313318635788ae5b3d3a3f767450ab2f2296",
"index": 4985,
"step-1": "<mask token>\n\n\nclass BlockDeviceTestCase(test.NoDBTestCase):\n <mask token>\n\n def test_properties(self):\n root_device0 = '/dev/sda'\n root_device1 = '/dev/sdb'\n mappings = [{'virtual': 'root', 'dev... | [
37,
38,
43,
46,
55
] |
from django.apps import AppConfig
class ModuloConfig(AppConfig):
name = 'modulo'
verbose_name = 'TUM:JungeAkademie - Modulo'
def ready(self):
#start-up / initialization code here!!!
from .recommender import Recommender
Recommender.initialize() | normal | {
"blob_id": "31275ca9e20da9d2709ea396e55c113b3ff4f571",
"index": 7738,
"step-1": "<mask token>\n\n\nclass ModuloConfig(AppConfig):\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass ModuloConfig(AppConfig):\n <mask token>\n <mask token>\n\n def ready(self):\n ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class LogoutSerializer(ModelSerializer):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class Meta:
model = DeviceUser
fields = ['device_user_token', 'device_os', 'is_active']
<|reserved_special_token_0|>
<|reserved_special_token_0|>
clas... | flexible | {
"blob_id": "01900c1d14a04ee43553c8602a07e0c6ecfabded",
"index": 1803,
"step-1": "<mask token>\n\n\nclass LogoutSerializer(ModelSerializer):\n <mask token>\n <mask token>\n\n\n class Meta:\n model = DeviceUser\n fields = ['device_user_token', 'device_os', 'is_active']\n <mask token>\n ... | [
9,
11,
15,
17,
19
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.... | flexible | {
"blob_id": "87e0b9dc518d439f71e261d5c5047153324919ba",
"index": 9547,
"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
] |
<|reserved_special_token_0|>
def get_repo_url(repo):
url = repo.replace('upstream:', 'git://git.baserock.org/delta/')
url = url.replace('baserock:baserock/',
'git://git.baserock.org/baserock/baserock/')
url = url.replace('freedesktop:', 'git://anongit.freedesktop.org/')
url = url.replace('gith... | flexible | {
"blob_id": "955cf040aaf882328e31e6a943bce04cf721cb11",
"index": 538,
"step-1": "<mask token>\n\n\ndef get_repo_url(repo):\n url = repo.replace('upstream:', 'git://git.baserock.org/delta/')\n url = url.replace('baserock:baserock/',\n 'git://git.baserock.org/baserock/baserock/')\n url = url.replac... | [
5,
7,
8,
10,
11
] |
import rospy
#: the parameter namespace for the arni_countermeasure node
ARNI_CTM_NS = "arni/countermeasure/"
#: the parameter namespace for configuration files
#: of the arni_countermeasure node
ARNI_CTM_CFG_NS = ARNI_CTM_NS + "config/"
def get_param_num(param):
#dummy val
value = 1
try:
value... | normal | {
"blob_id": "70c9d75dabfa9eac23e34f94f34d39c08e21b3c0",
"index": 6070,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_param_num(param):\n value = 1\n try:\n value = rospy.get_param(param)\n if not isinstance(value, (int, float, long)):\n err_msg = 'Param %s is n... | [
0,
2,
3,
4,
5
] |
import sys
filepath = 'input.txt'
def intersection(list1, list2):
return set(list1).intersection(list2)
def computeSteps(x, y, step, steps):
# build dictionary with steps for each point
curr = 0
if (x,y) in steps:
curr = steps.get((x,y))
steps[(x,y)] = step + curr
... | normal | {
"blob_id": "e9e119dd69f9416e007e748d7f494741140efc8e",
"index": 8182,
"step-1": "<mask token>\n\n\ndef intersection(list1, list2):\n return set(list1).intersection(list2)\n\n\ndef computeSteps(x, y, step, steps):\n curr = 0\n if (x, y) in steps:\n curr = steps.get((x, y))\n steps[x, y] = step... | [
2,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
def plot_loss(history):
plt.plot(history.history['loss'], label='loss')
plt.plot(history.history['val_loss'], label='val_loss')
plt.ylim([0, 10])
plt.xlabel('Epoch')
plt.ylabel('Error')
plt.legend()
plt.grid(True)
<|reserved_special_token_0|>
<|reserved_spe... | flexible | {
"blob_id": "196147d7b2b0cf7176b5baa50d7e7618f88df493",
"index": 7911,
"step-1": "<mask token>\n\n\ndef plot_loss(history):\n plt.plot(history.history['loss'], label='loss')\n plt.plot(history.history['val_loss'], label='val_loss')\n plt.ylim([0, 10])\n plt.xlabel('Epoch')\n plt.ylabel('Error')\n ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class MyLoop(dopehr_loopmodel):
<|reserved_special_token_0|>
def select_loop_atoms(self):
return selection(self.residue_range('218:', '231:'))
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class... | flexible | {
"blob_id": "d058c3df8513e07e4ff7035aa5c5885819e43687",
"index": 7295,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass MyLoop(dopehr_loopmodel):\n <mask token>\n\n def select_loop_atoms(self):\n return selection(self.residue_range('218:', '231:'))\n",
"step-3": "<mask token>\n\n\n... | [
0,
2,
3,
4,
5
] |
from Config_paar import *
from Envelopefkt import *
from Kinematik import *
def A_m_n(M,N,x_plus,p_el,p_pos,k_photon,k_laser):
def f1(p):
return -(m*a0)/(pk(p)) * g(phi,sigma,Envelope) *( pe(1,p) * cos(ksi) * cos(phi) + pe(2,p) * sin(ksi) * sin(phi) )
def f2(p):
return -(m*a0)**2/(2.... | normal | {
"blob_id": "ad170f67e5b9f54d950ead91dd60cd4f3b753eca",
"index": 6660,
"step-1": "from Config_paar import *\nfrom Envelopefkt import *\nfrom Kinematik import *\n\n\ndef A_m_n(M,N,x_plus,p_el,p_pos,k_photon,k_laser):\n\n def f1(p):\n return -(m*a0)/(pk(p)) * g(phi,sigma,Envelope) *( pe(1,p) * cos(ksi) *... | [
0
] |
from django.core import management
from django.conf import settings
def backup_cron():
if settings.DBBACKUP_STORAGE is not '':
management.call_command('dbbackup')
| normal | {
"blob_id": "ae9f1c4f70801dace0455c051ba4d4bfb7f3fe67",
"index": 4813,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef backup_cron():\n if settings.DBBACKUP_STORAGE is not '':\n management.call_command('dbbackup')\n",
"step-3": "from django.core import management\nfrom django.conf impo... | [
0,
1,
2
] |
import os
import inspect
import pytest
from ._common import copy_default_profile_collection, patch_first_startup_file
from bluesky_queueserver.manager.profile_tools import global_user_namespace, load_devices_from_happi
from bluesky_queueserver.manager.profile_ops import load_profile_collection
def create_local_impor... | normal | {
"blob_id": "ad1ec5dd8fae290ab6cb73b17c5522e062261359",
"index": 6698,
"step-1": "<mask token>\n\n\ndef create_local_imports_files(tmp_path):\n path_dir = os.path.join(tmp_path, 'dir_local_imports')\n fln_func = os.path.join(path_dir, 'file_func.py')\n fln_gen = os.path.join(path_dir, 'file_gen.py')\n ... | [
5,
6,
7,
8,
9
] |
import RPi.GPIO as GPIO
import time
from datetime import datetime
led1 = [('g', 40), ('f', 38), ('a', 36), ('b', 32),
('e', 26), ('d', 24), ('c', 22)]
led2 = [('g', 19), ('f', 15), ('a', 13),
('b', 11), ('e', 7), ('d', 5), ('c', 3)]
numbers = [
('a', 'b', 'c', 'd', 'e', 'f'),
('b', 'c'),
('... | normal | {
"blob_id": "0d022291f9ace02ef1ee5c462657ea6376a0e6a4",
"index": 9436,
"step-1": "<mask token>\n\n\ndef setupLed1():\n for port in led1:\n GPIO.setup(port[1], GPIO.OUT)\n\n\ndef setupLed2():\n for port in led2:\n GPIO.setup(port[1], GPIO.OUT)\n\n\ndef statusLed(port, status):\n GPIO.output... | [
10,
11,
12,
13,
15
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
dependencies = [(... | flexible | {
"blob_id": "8cdd7646dbf23259e160186f332b5cb02b67291b",
"index": 5121,
"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 = [('app1', '000... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class ModD(Soppa):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class ModD(Soppa):
needs = ['test_project.modf']
something = 1
<|reser... | flexible | {
"blob_id": "13da16ba89e4743b12d9b8e24929864747f8bbf2",
"index": 1308,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass ModD(Soppa):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass ModD(Soppa):\n needs = ['test_project.modf']\n something = 1\n",
"step-4": "fro... | [
0,
1,
2,
3
] |
'''
This program will simulate leveling a DnD character, showing their ending HP, and stats.
'''
import argparse
import csv
import json
import re
import time
from openpyxl import load_workbook
from pandas import DataFrame
from src import classes, util
def import_race_data(file_path):
'''
This method imports d... | normal | {
"blob_id": "022c8d6c31ad5494b03bfe93d17396eac25b011e",
"index": 8706,
"step-1": "<mask token>\n\n\ndef update_mode(args):\n \"\"\"\n This method is the main method for running this program in Update mode.\n\n Update mode takes in a specifically formated XLSX file and outputs a JSON\n file containing... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Messages(SQLMixin, SQLBase):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1... | flexible | {
"blob_id": "6fbf64e2dc2836a54e54ee009be1d0d8d7c7037a",
"index": 1688,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Messages(SQLMixin, SQLBase):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Messages(SQLMixin... | [
0,
1,
2,
3
] |
import re, os, nltk, pymorphy2, sys
from suffix_trees.STree import STree
def make_rules(folder):
rules_dictionary = {}
try:
path = os.path.join(os.getcwd(), 'rules', 'data', folder)
files = os.listdir(path)
except:
path = os.path.join(os.getcwd(), 'data', folder)
files = os... | normal | {
"blob_id": "1bf9785135f6105301d02602e54cbbcbdd249144",
"index": 9283,
"step-1": "<mask token>\n\n\ndef make_rules(folder):\n rules_dictionary = {}\n try:\n path = os.path.join(os.getcwd(), 'rules', 'data', folder)\n files = os.listdir(path)\n except:\n path = os.path.join(os.getcwd... | [
4,
5,
7,
8,
9
] |
# The project is based on Tensorflow's Text Generation with RNN tutorial
# Copyright Petros Demetrakopoulos 2020
import tensorflow as tf
import numpy as np
import os
import time
# The project is based on Tensorflow's Text Generation with RNN tutorial
# Copyright Petros Demetrakopoulos 2020
import tensorflow as tf
impor... | normal | {
"blob_id": "5ff0c6bde8f3ffcb1f5988b0bbd1dfdd7fa2e818",
"index": 8800,
"step-1": "<mask token>\n\n\ndef yuh():\n corpus_path = '/tmp/data.txt'\n text = open(corpus_path, 'rb').read().decode(encoding='utf-8')\n text = preprocessText(text)\n corpus_words = corpusToList(text)\n map(str.strip, corpus_... | [
6,
7,
8,
9,
11
] |
class CustomPrinter(object):
def __init__(self, val):
self.val = val
def to_string(self):
res = "{"
for m in xrange(64):
res += hex(int(self.val[m]))
if m != 63:
res += ", "
res += " }"
return res
def lookup_type(val):
if str... | normal | {
"blob_id": "4d5b2ed016cfc6740c3ee5397c894fabc1bec73f",
"index": 6963,
"step-1": "class CustomPrinter(object):\n <mask token>\n\n def to_string(self):\n res = '{'\n for m in xrange(64):\n res += hex(int(self.val[m]))\n if m != 63:\n res += ', '\n re... | [
2,
3,
4,
5,
6
] |
# -*- coding:utf-8 -*-
"""
逆波兰表达式，中缀表达式可以对应一棵二叉树，逆波兰表达式即该二叉树后续遍历的结果。
"""
def isOperator(c):
return c == '+' or c == '-' or c == '*' or c == '/'
def reversePolishNotation(p):
stack = list()
for cur in p:
if not isOperator(cur):
stack.append(cur)
else:
b = float(sta... | normal | {
"blob_id": "93a47d6ba1f699d881f0d22c4775433e4a451890",
"index": 6168,
"step-1": "# -*- coding:utf-8 -*-\n\n\"\"\"\n逆波兰表达式，中缀表达式可以对应一棵二叉树，逆波兰表达式即该二叉树后续遍历的结果。\n\"\"\"\n\ndef isOperator(c):\n return c == '+' or c == '-' or c == '*' or c == '/'\n\n\ndef reversePolishNotation(p):\n stack = list()\n for cur ... | [
0
] |
<|reserved_special_token_0|>
class Cuneiform(pp.unicode_set):
<|reserved_special_token_0|>
_ranges: List[Tuple[int, ...]] = [(66432, 66517), (73728, 74751), (
74752, 74879)]
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Cuneiform(pp.unicode_set):
... | flexible | {
"blob_id": "bc1aefd0b0a87b80a10cecf00407b4608a6902b5",
"index": 3897,
"step-1": "<mask token>\n\n\nclass Cuneiform(pp.unicode_set):\n <mask token>\n _ranges: List[Tuple[int, ...]] = [(66432, 66517), (73728, 74751), (\n 74752, 74879)]\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass Cuneif... | [
1,
3,
4,
5,
6
] |
#!/usr/bin/python
#_*_coding:utf-8_*_
import random
def main():
source = "I couldn't believe that I could actually understand what I was reading : the phenomenal power of the human mind ."
words = source.strip().split(" ")
new_str = list()
for word in words:
if len(word) > 4:
shuff... | normal | {
"blob_id": "14b98186fbc9c275cea3c042cdb4899f6d0c54c6",
"index": 3419,
"step-1": "#!/usr/bin/python\n#_*_coding:utf-8_*_\n\nimport random\n\ndef main():\n source = \"I couldn't believe that I could actually understand what I was reading : the phenomenal power of the human mind .\"\n words = source.strip().... | [
0
] |
#!/usr/bin/python
import platform
from numpy import ctypeslib,empty,array,exp,ascontiguousarray,zeros,asfortranarray
from ctypes import c_float,c_double,c_int
from time import time
def resize(img,scale):
"""
downsample img to scale
"""
sdims=img.shape
datatype=c_double
if img.dtype!=data... | normal | {
"blob_id": "816f4cfe98f5e5b23f2c8f9f42c5f3ed8458042f",
"index": 3700,
"step-1": "#!/usr/bin/python \n\nimport platform\nfrom numpy import ctypeslib,empty,array,exp,ascontiguousarray,zeros,asfortranarray\nfrom ctypes import c_float,c_double,c_int\nfrom time import time\n\ndef resize(img,scale):\n \"\"\"\n ... | [
0
] |
#!/usr/bin/env python
#coding:utf-8
"""
Author: Wusf --<wushifan221@gmail.com>
Purpose:
Created: 2016/2/29
"""
import os,sys,sqlite3
MyQtLibPath = os.path.abspath("D:\\MyQuantLib\\")
sys.path.append(MyQtLibPath)
import PCA.PCA_For_Stat_Arb2 as pca
import pandas as pd
import numpy as np
import time
def Compu... | normal | {
"blob_id": "70cda2d6d3928cd8008daf221cd78665a9b05eea",
"index": 7064,
"step-1": "#!/usr/bin/env python\n#coding:utf-8\n\"\"\"\n Author: Wusf --<wushifan221@gmail.com>\n Purpose: \n Created: 2016/2/29\n\"\"\"\n\nimport os,sys,sqlite3\nMyQtLibPath = os.path.abspath(\"D:\\\\MyQuantLib\\\\\")\nsys.path.append(M... | [
0
] |
<|reserved_special_token_0|>
class CNN(object):
def __init__(self):
self.model = tf.keras.Sequential([tf.keras.layers.Conv2D(32, (3, 3),
activation='relu', input_shape=(150, 150, 1)), tf.keras.layers.
MaxPool2D((2, 2)), tf.keras.layers.Conv2D(64, (3, 3),
activation='re... | flexible | {
"blob_id": "9535335c70129f997d7b8739444a503d0b984ac8",
"index": 9753,
"step-1": "<mask token>\n\n\nclass CNN(object):\n\n def __init__(self):\n self.model = tf.keras.Sequential([tf.keras.layers.Conv2D(32, (3, 3),\n activation='relu', input_shape=(150, 150, 1)), tf.keras.layers.\n ... | [
12,
13,
14,
15,
16
] |
a=int(input())
s=0
t=0
while(a!=0):
t=a%10
s=s+t
a=a//10
print(s)
| normal | {
"blob_id": "6050e83e73faaf40cbd5455efd3ad01e4e131188",
"index": 2587,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile a != 0:\n t = a % 10\n s = s + t\n a = a // 10\nprint(s)\n",
"step-3": "a = int(input())\ns = 0\nt = 0\nwhile a != 0:\n t = a % 10\n s = s + t\n a = a // 10\npri... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(type(data))
<|reserved_special_token_0|>
print(data)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
url = 'http://icanhazdadjoke.com/'
response = requests.get(url, headers={'Accept': 'application/json'})
data =... | flexible | {
"blob_id": "f94894e5d3e6a0ff367911c72f4d863ac32c8baa",
"index": 1435,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(type(data))\n<mask token>\nprint(data)\n",
"step-3": "<mask token>\nurl = 'http://icanhazdadjoke.com/'\nresponse = requests.get(url, headers={'Accept': 'application/json'})\ndata ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def segment_ts():
ts_len = len(x1)
mod = ts_len % window_size
rnge = 0
if skip_offset == 0:
ts_len = int((ts_len - mod - window_size) / 1)
rnge = int(ts_len / window_size)
else:
ts_len = int(math.ceil((ts_len - window_size) / skip_offset))
... | flexible | {
"blob_id": "16215ee42c4ea284dca0ebb7372fef04c0cc54b9",
"index": 2149,
"step-1": "<mask token>\n\n\ndef segment_ts():\n ts_len = len(x1)\n mod = ts_len % window_size\n rnge = 0\n if skip_offset == 0:\n ts_len = int((ts_len - mod - window_size) / 1)\n rnge = int(ts_len / window_size)\n ... | [
4,
5,
6,
7,
8
] |
def isSubsetSum(set, n, sum):
subset =([[False for i in range(sum + 1)] for i in range(n + 1)])
for i in range(n + 1):
subset[i][0] = True
for i in range(1, sum + 1):
subset[0][i]= False
for i in range(1, n + 1):
for j in range(1, sum + 1):
if j<set[i-1]:
... | normal | {
"blob_id": "830e7e84eebd6a4adb411cc95c9e9c8ff7bdac30",
"index": 778,
"step-1": "<mask token>\n",
"step-2": "def isSubsetSum(set, n, sum):\n subset = [[(False) for i in range(sum + 1)] for i in range(n + 1)]\n for i in range(n + 1):\n subset[i][0] = True\n for i in range(1, sum + 1):\n s... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def split_matrix(ratings, num_users, num_movies):
X = np.zeros((num_users, num_movies))
for r in np.arange(len(ratings)):
X[ratings[r, 0] - 1, ratings[r, 1] - 1] = ratings[r, 2]
return X
def mf_gd(ratings, num_users, num_movies):
X_data = split_matrix(ratings, nu... | flexible | {
"blob_id": "b4267612e7939b635542099e1ba31e661720607a",
"index": 3129,
"step-1": "<mask token>\n\n\ndef split_matrix(ratings, num_users, num_movies):\n X = np.zeros((num_users, num_movies))\n for r in np.arange(len(ratings)):\n X[ratings[r, 0] - 1, ratings[r, 1] - 1] = ratings[r, 2]\n return X\n\... | [
2,
3,
4,
5,
7
] |
<|reserved_special_token_0|>
def on_identity_changed(app, identity):
g.identity = identity
session['identity'] = identity
def configure_signals(app):
identity_changed.connect(on_identity_changed, app)
<|reserved_special_token_0|>
def configure_before_handlers(app):
@app.before_request
def a... | flexible | {
"blob_id": "ef124e8c15ef347efd709a5e3fb104c7fd1bccde",
"index": 2753,
"step-1": "<mask token>\n\n\ndef on_identity_changed(app, identity):\n g.identity = identity\n session['identity'] = identity\n\n\ndef configure_signals(app):\n identity_changed.connect(on_identity_changed, app)\n\n\n<mask token>\n\n... | [
6,
8,
9,
10,
13
] |
from PyQt5.QtWidgets import *
import sys
import math
Data = ''
class Button:
def __init__(self, text, results):
self.b = QPushButton(str(text))
self.text = text
self.results = results
self.b.clicked.connect(lambda: self.handleInput(
self.text)) # Important because we ... | normal | {
"blob_id": "b08cface601ee07125090f3ae03a3120974688f2",
"index": 8765,
"step-1": "<mask token>\n\n\nclass Widget2:\n\n def setup(self, MainWindow, res):\n self.widget = QWidget()\n self.grid = QGridLayout()\n self.results = QLineEdit()\n self.results.setText(res)\n row = 3\n... | [
8,
9,
11,
13,
17
] |
import random
my_randoms = random.sample(100, 10)
print(my_randoms)
| normal | {
"blob_id": "d39f6fca80f32a4d13764eb5cfb29999785b1d16",
"index": 1629,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(my_randoms)\n",
"step-3": "<mask token>\nmy_randoms = random.sample(100, 10)\nprint(my_randoms)\n",
"step-4": "import random\nmy_randoms = random.sample(100, 10)\nprint(my_rando... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def hdfs_get_filelist(blob_path, delimiter='_'):
""" Lists hdfs dir and returns named tuples with information of file based on its filename. """
def hdfs_listdir(blob_path):
command = 'hdfs dfs -ls ' + blob_path... | flexible | {
"blob_id": "6909e70db4f907e26ad604f95c79a405010907bd",
"index": 2086,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef hdfs_get_filelist(blob_path, delimiter='_'):\n \"\"\" Lists hdfs dir and returns named tuples with information of file based on its filename. \"\"\"\n\n def hdfs_listdir(blo... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def transform_word(word):
"""
将低频词转为四种形式之一。
"""
if any(c.isdigit() for c in word):
return '_NUMERIC_'
if word.isupper():
return '_ALL_CAP_'
if word[-1].isupper():
return '_LAST_CAP... | flexible | {
"blob_id": "92a1f86ce8cc9563d455f9b1336dbcd298f01b6d",
"index": 1747,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef transform_word(word):\n \"\"\"\n 将低频词转为四种形式之一。\n \"\"\"\n if any(c.isdigit() for c in word):\n return '_NUMERIC_'\n if word.isupper():\n return '_ALL_... | [
0,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class CommentViewSet(viewsets.GenericViewSet, mixins.ListModelMixin, mixins
.RetrieveModelMixin):
queryset = Comment.objects.all()
def get_serializer_class(self):
if self.action == 'retrieve':
if self.get_object().level < 3:
return CommentS... | flexible | {
"blob_id": "9bc13c608c079cbf23ed04f29edd1fd836214cde",
"index": 282,
"step-1": "<mask token>\n\n\nclass CommentViewSet(viewsets.GenericViewSet, mixins.ListModelMixin, mixins\n .RetrieveModelMixin):\n queryset = Comment.objects.all()\n\n def get_serializer_class(self):\n if self.action == 'retrie... | [
3,
4,
5,
6
] |
import numpy as np
from scipy.stats import multivariate_normal
from functions.io_data import read_data, write_data
np.random.seed(0)
class IsingModel():
def __init__(self, image, J, rate, sigma):
self.width = image.shape[0]
self.height = image.shape[1]
self._J = J
self._rate = rat... | normal | {
"blob_id": "6aa74826f9ca0803fa8c1d5af1d4cec4980e2ce6",
"index": 9064,
"step-1": "<mask token>\n\n\nclass IsingModel:\n\n def __init__(self, image, J, rate, sigma):\n self.width = image.shape[0]\n self.height = image.shape[1]\n self._J = J\n self._rate = rate\n self._sigma =... | [
4,
5,
6,
7,
10
] |
from unittest import TestCase, main
class Solution:
def productExceptSelf(self, nums):
right, rs = 1, [1]*len(nums)
for i in range(1,len(nums)): rs[i] = nums[i-1]*rs[i-1]
for i in range(len(nums)-1, -1, -1): rs[i], right = rs[i]*right, right*nums[i]
return rs
class testsolution(Tes... | normal | {
"blob_id": "9e34fcec3af746af37cb68fd8617c706cc1066f6",
"index": 1743,
"step-1": "<mask token>\n\n\nclass testsolution(TestCase):\n\n def setUp(self):\n self.solution = Solution()\n self.inout = [([1, 2, 3, 4], [24, 12, 8, 6]), ([4, 5, 1, 8, 2], [80,\n 64, 320, 40, 160])]\n\n def t... | [
3,
4,
5,
6,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def divide_img(img_path, img_name, save_path):
imgg = img_path + '\\' + img_name
print(imgg)
img = cv2.imread(imgg)
print(img)
h = img.shape[0]
w = img.shape[1]
n = 8
m = 8
print('h={},w={},n=... | flexible | {
"blob_id": "03f3fcb38877570dea830a56460061bd3ccb8927",
"index": 8830,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef divide_img(img_path, img_name, save_path):\n imgg = img_path + '\\\\' + img_name\n print(imgg)\n img = cv2.imread(imgg)\n print(img)\n h = img.shape[0]\n w = img... | [
0,
1,
2,
3,
4
] |
# import libraries
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import warnings
import pickle
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import accuracy_score
from sklearn.metrics import mean_squared_error
impor... | normal | {
"blob_id": "1508697f93114d7f20182a3e9c1df5617904529a",
"index": 8725,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nlr.fit(x_train, y_train)\n<mask token>\npickle.dump(lr, open('model.pkl', 'wb'))\n",
"step-3": "<mask token>\ndataset = pd.read_csv('heart.csv')\ndf = dataset.copy()\nX = df.drop(['targ... | [
0,
1,
2,
3,
4
] |
#! /usr/bin/env python
import tensorflow as tf
import numpy as np
import os
import time
import datetime
import data_helpers
from text_rnn import TextRNN
from tensorflow.contrib import learn
# Parameters
# ==================================================
# Data loading params
flags = tf.app.flags
FLAGS = flags.FLA... | normal | {
"blob_id": "aa1a7de92b971b6d10d09b2f8ca2c55516e538e4",
"index": 9904,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ntf.flags.DEFINE_integer('embedding_dim', 100,\n 'Dimensionality of character embedding (default: 100)')\ntf.flags.DEFINE_float('dropout_keep_prob', 0.5,\n 'Dropout keep probability ... | [
0,
1,
2,
3,
4
] |
# 1로 만들기
import sys
N = int(sys.stdin.readline())
dp_table = [0 for _ in range(10**6 + 1)]
dp_table[2], dp_table[3] = 1, 1
for i in range(4,N+1):
two_per = 10**6
three_per = 10**6
if i % 3 ==0:
three_per = dp_table[i//3] + 1
if i % 2 ==0:
two_per = dp_table[i//2] + 1
minus = dp_tabl... | normal | {
"blob_id": "34a8fc38ed875e1c564f535348dc0d5d88c76ab1",
"index": 7281,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(4, N + 1):\n two_per = 10 ** 6\n three_per = 10 ** 6\n if i % 3 == 0:\n three_per = dp_table[i // 3] + 1\n if i % 2 == 0:\n two_per = dp_table[i /... | [
0,
1,
2,
3,
4
] |
import pyForp
import pprint
pp = pprint.PrettyPrinter(indent=4)
def fib(n):
if n < 2:
return n
return fib(n-2) + fib(n-1)
forp = pyForp.pyForp()
forp.start()
print fib(2)
forp.stop()
pp.pprint(forp.dump())
| normal | {
"blob_id": "80f9c4b7261a894aad2c738d976cfb8efc4d228c",
"index": 4784,
"step-1": "import pyForp\nimport pprint\npp = pprint.PrettyPrinter(indent=4)\ndef fib(n):\n if n < 2:\n return n\n return fib(n-2) + fib(n-1)\n\nforp = pyForp.pyForp()\nforp.start()\nprint fib(2)\nforp.stop()\npp.pprint(forp.dump... | [
0
] |
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