code stringlengths 13 1.2M | order_type stringclasses 1
value | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
# -*- coding: utf-8 -*-
file1 = raw_input("Enter the path of your first file: ")
file2 = raw_input("Enter the path of your second file: ")
Basex = open(file1).read().split()
Basey = open(file2).read().split()
if Basex != Basey:
print("The files are different!")
else:
print("The files are the same!")
| normal | {
"blob_id": "661d82adc7d0746635fb57abf6d0e70ee615ada4",
"index": 5974,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif Basex != Basey:\n print('The files are different!')\nelse:\n print('The files are the same!')\n",
"step-3": "file1 = raw_input('Enter the path of your first file: ')\nfile2 = r... | [
0,
1,
2,
3
] |
import sys
sys.stdin = open('줄긋기.txt')
T = int(input())
for tc in range(1, T + 1):
N = int(input())
dot = [list(map(int, input().split())) for _ in range(N)]
ran = []
for a in range(N - 1):
for b in range(a + 1, N):
if dot[a][1] - dot[b][1] == 0:
if 'inf' not in ran:
... | normal | {
"blob_id": "03854f48751460fdc27d42ee5c766934ee356cfd",
"index": 6161,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor tc in range(1, T + 1):\n N = int(input())\n dot = [list(map(int, input().split())) for _ in range(N)]\n ran = []\n for a in range(N - 1):\n for b in range(a + 1, N)... | [
0,
1,
2,
3
] |
def drive(carspeed):
if carspeed>200:
print("very fast")
elif carspeed>100:
print("toofast")
elif carspeed>70 and carspeed<80:
print("optimal speed")
else:
print("below speed limit")
print(drive(234))
print(drive(34))
drive(134)
#how none will be removed?
def compare(a):
if a>11:
print("big")
elif a==1... | normal | {
"blob_id": "de3eaa5823fb396050527c148273c30bed6ce8ca",
"index": 2644,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef compare(a):\n if a > 11:\n print('big')\n elif a == 10:\n print('reallybig')\n\n\n<mask token>\n",
"step-3": "def drive(carspeed):\n if carspeed > 200:\n ... | [
0,
1,
2,
3,
4
] |
# -*- coding=utf-8 -*-
# ! /usr/bin/env python3
"""
抽奖活动-摇一摇活动
"""
import time
import allure
from libs.selenium_libs.common.base import Base
from libs.selenium_libs.page_object.page_activity import PageActivity
from libs.selenium_libs.page_object.page_personal_center import PagePersonalCenter
class LuckDrawActivity... | normal | {
"blob_id": "6b1970ee2b0d24504f4dea1f2ad22a165101bfbe",
"index": 8958,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass LuckDrawActivity(Base):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass LuckDrawActivity(Base):\n\n @allure.step('参加抽奖活动')\n def join_luck_draw_activity(self, d... | [
0,
1,
2,
3,
4
] |
#loadconc.py - possibly these classes will be added to ajustador/loader.py when ready
# -*- coding:utf-8 -*-
from __future__ import print_function, division
import numpy as np
from ajustador import xml,nrd_fitness
import glob
import os
import operator
msec_per_sec=1000
nM_per_uM=1000
nM_per_mM=1e6
class trace(ob... | normal | {
"blob_id": "20649decd3ff21b1aa814d0a04180195cac3629b",
"index": 498,
"step-1": "<mask token>\n\n\nclass CSV_conc(object):\n <mask token>\n <mask token>\n\n\nclass CSV_conc_set(object):\n\n def __init__(self, rootname, stim_time=0, features=[]):\n self.stim_time = stim_time * msec_per_sec\n ... | [
3,
7,
8,
9,
10
] |
from flask import Flask, request
from flask import jsonify
from preprocessing import QueryProcessor
from flask_cors import CORS
app = Flask(__name__)
CORS(app)
qp = QueryProcessor()
@app.route('/search_general', methods=['POST'])
def query():
message = None
searchQuery = request.json['searchQuery']
resul... | normal | {
"blob_id": "e582787a912f479830ed99575b2c6adb8088b4e5",
"index": 257,
"step-1": "<mask token>\n\n\n@app.route('/search_general', methods=['POST'])\ndef query():\n message = None\n searchQuery = request.json['searchQuery']\n result = qp.generateQuery(searchQuery)\n response = jsonify(result)\n resp... | [
2,
3,
4,
5,
6
] |
#Write your function here
def over_nine_thousand(lst):
sum = 0
for number in lst:
sum += number
if (sum > 9000):
break
return sum
#Uncomment the line below when your function is done
print(over_nine_thousand([8000, 900, 120, 5000]))
#9020 | normal | {
"blob_id": "c2f39e33030cbe7c5d4827b47fb28d7604bdbc6d",
"index": 8135,
"step-1": "<mask token>\n",
"step-2": "def over_nine_thousand(lst):\n sum = 0\n for number in lst:\n sum += number\n if sum > 9000:\n break\n return sum\n\n\n<mask token>\n",
"step-3": "def over_nine_thou... | [
0,
1,
2,
3
] |
import torch
import util
import numpy as np
import argparse
import losses
args = argparse.Namespace()
args.device = torch.device('cpu')
args.num_mixtures = 20
args.init_mixture_logits = np.ones(args.num_mixtures)
args.softmax_multiplier = 0.5
args.relaxed_one_hot = False
args.temperature = None
temp = np.arange(args.... | normal | {
"blob_id": "8f558593e516aa4a769b7c5e1c95c8bc23a36420",
"index": 1232,
"step-1": "<mask token>\n\n\ndef get_grads_correct(seed):\n util.set_seed(seed)\n theta_grads_correct = []\n phi_grads_correct = []\n log_weight, log_q = losses.get_log_weight_and_log_q(generative_model,\n inference_network... | [
5,
6,
8,
9,
10
] |
"""
Primos <generadores> 30 pts
Realice una generador que devuelva de todos lo numeros primos
existentes de 0 hasta n-1 que cumpla con el siguiente prototipo:
def gprimo(N):
pass
a = gprimo(10)
z = [e for e in a]
print(z)
# [2, 3 ,5 ,7 ]
"""
def gprimo(nmax):
for x in range(1,nmax):
for i in ra... | normal | {
"blob_id": "732886306d949c4059b08e1bc46de3ad95ba56cb",
"index": 1685,
"step-1": "<mask token>\n\n\ndef gprimo(nmax):\n for x in range(1, nmax):\n for i in range(2, x):\n if x % i != 0:\n continue\n else:\n break\n else:\n yield x\n\... | [
1,
2,
3,
4,
5
] |
# Cutting a Rod | DP-13
# Difficulty Level : Medium
# Last Updated : 13 Nov, 2020
# Given a rod of length n inches and an array of prices that contains prices of all pieces of size smaller than n. Determine the maximum value obtainable by cutting up the rod and selling the pieces. For example, if length of the rod is... | normal | {
"blob_id": "9cca73ebdf2b05fe29c14dc63ec1b1a7c917b085",
"index": 6508,
"step-1": "<mask token>\n\n\ndef cut_rod2(price, n):\n val = [(0) for x in range(n + 1)]\n val[0] = 0\n for i in range(1, n + 1):\n max_val = -1\n for j in range(i):\n max_val = max(max_val, price[j] + val[i ... | [
2,
3,
4,
5,
7
] |
import rasterio as rio
from affine import Affine
colour_data = []
def generate_colour_data(width, height, imagiry_data, pixel2coord):
"""Extract color data from the .tiff file """
for i in range(1, height):
for j in range(1, width):
colour_data.append(
[
... | normal | {
"blob_id": "7e8b192e77e857f1907d5272d03c1138a10c61f4",
"index": 4803,
"step-1": "<mask token>\n\n\ndef generate_colour_data(width, height, imagiry_data, pixel2coord):\n \"\"\"Extract color data from the .tiff file \"\"\"\n for i in range(1, height):\n for j in range(1, width):\n colour_d... | [
1,
2,
3,
4,
5
] |
"""
Author: Yudong Qiu
Functions for solving unrestricted Hartree-Fock
"""
import numpy as np
from qc_python import basis_integrals
from qc_python.common import chemical_elements, calc_nuclear_repulsion
def solve_unrestricted_hartree_fock(elems, coords, basis_set, charge=0, spinmult=1, maxiter=150, enable_DIIS=True... | normal | {
"blob_id": "ccc2a976d06e2fa6c91b25c4f95a8f0da32e9b5e",
"index": 7878,
"step-1": "<mask token>\n\n\ndef DIIS_extrapolate_F(diis_err_mats, diis_fmats):\n n_diis = len(diis_err_mats)\n assert n_diis == len(diis_fmats\n ), 'Number of Fock matrices should equal to number of error matrices'\n Bmat = -... | [
1,
2,
3,
4,
5
] |
import random
from common.ast import *
from mutate.mutate_ctrl import *
def _check_parent_type(node, nodes, types):
par = node
while(nodes[par] != None):
par = nodes[par]
if type(par) in types:
return True
return False
def mutate_operator(root, nodes, path):
candidates = [... | normal | {
"blob_id": "c0524301a79788aa34a039fc46799021fb45362c",
"index": 7141,
"step-1": "<mask token>\n\n\ndef mutate_operator(root, nodes, path):\n candidates = [node for node in nodes.keys() if type(node) in OP_TYPES.\n keys() and _check_parent_type(node, nodes, OP_PARENT_TYPES)]\n if len(candidates) == ... | [
3,
4,
5,
6,
7
] |
import pygame
class SpriteObject(pygame.sprite.Sprite):
def __init__(self, x, y, w, h, color):
pygame.sprite.Sprite.__init__(self)
self.angle = 0
self.original_image = pygame.Surface([w, h], pygame.SRCALPHA)
self.original_image.fill(color)
self.image = self.original_... | normal | {
"blob_id": "b90c6a3f8fe084bc2acc0b733750124a1387527c",
"index": 1712,
"step-1": "<mask token>\n\n\nclass SpriteObject(pygame.sprite.Sprite):\n <mask token>\n\n def update(self):\n self.rotate()\n\n def rotate(self):\n self.angle += 0.3\n self.image = pygame.transform.rotate(self.or... | [
3,
4,
5,
6,
8
] |
# -*- coding: utf-8 -*-
try:
from greenlet import getcurrent as get_current_greenlet
except ImportError:
get_current_greenlet = int
from thread import get_ident as get_current_thread
from threading import Lock
if get_current_greenlet is int: # Use thread
get_ident = get_current_thread
else: # Use gree... | normal | {
"blob_id": "f55b286448f114f3823f099a576af7bec1780a8c",
"index": 461,
"step-1": "<mask token>\n\n\nclass Local(object):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def __delattr__(self, item):\n self.__lock__.acquire()\n try:\n try:\n ... | [
8,
11,
12,
15,
16
] |
from collections import OrderedDict
import torch
from torch import nn, Tensor
import warnings
from typing import Tuple, List, Dict, Optional, Union
class GeneralizedRCNN(nn.Module):
def __init__(self, backbone, rpn, roi_heads, transform):
super(GeneralizedRCNN, self).__init__()
self.transform = t... | normal | {
"blob_id": "83ecb6b6237d7ee61f762b191ebc891521067a41",
"index": 9206,
"step-1": "<mask token>\n\n\nclass GeneralizedRCNN(nn.Module):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass GeneralizedRCNN(nn.Module):\n\n def __init__(self, backbone, rpn, roi_heads, transform):\n s... | [
1,
2,
3,
4,
5
] |
""" Url router for the federated search application
"""
from django.conf.urls import include
from django.urls import re_path
urlpatterns = [
re_path(r"^rest/", include("core_federated_search_app.rest.urls")),
]
| normal | {
"blob_id": "6903584b27c0720cebf42ed39968b18f0f67f796",
"index": 6167,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [re_path('^rest/', include(\n 'core_federated_search_app.rest.urls'))]\n",
"step-3": "<mask token>\nfrom django.conf.urls import include\nfrom django.urls import re_pat... | [
0,
1,
2,
3
] |
import numpy as np
import urllib2
from io import StringIO
def demo_polyfit0():
x, y = np.loadtxt('stock.txt', unpack=True)
print '-'.join(map(str, np.polyfit(x, y, 1)))
def demo_polyfit1():
d = urllib2.urlopen("http://www.qlcoder.com/download/145622513871043.txt").read().decode("utf-8")
print d
... | normal | {
"blob_id": "61571ba9f647f430879b9fa5db884ec4c93c334f",
"index": 9659,
"step-1": "import numpy as np\nimport urllib2\nfrom io import StringIO\n\n\ndef demo_polyfit0():\n x, y = np.loadtxt('stock.txt', unpack=True)\n print '-'.join(map(str, np.polyfit(x, y, 1)))\n\n\ndef demo_polyfit1():\n d = urllib2.ur... | [
0
] |
tabela = [[1,-45,-20,0,0,0,0],[0,20,5,1,0,0,9500],[0,0.04,0.12,0,1,0,40],[0,1,1,0,0,1,551]]
colunas = ["Z","A","B","S1","S2","S3","Solução"]
linhas = ["Z","S1","S2","S3"]
n_colunas=7
n_linhas=4
#Inicio do algoritmo
#Buscar o menor numero negativo na linha 0
menor_posicao=-1
menor_valor=0
for coluna in rang... | normal | {
"blob_id": "785dcaf7de68174d84af3459cde02927bc2e10cc",
"index": 8951,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor coluna in range(0, n_colunas):\n if tabela[0][coluna] < menor_valor:\n menor_valor = tabela[0][coluna]\n menor_posicao = coluna\n<mask token>\nwhile menor_posicao != ... | [
0,
1,
2,
3
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
@File : corr2d.py
@Author : jeffsheng
@Date : 2020/1/3
@Desc : 卷积层中的互相关（cross-correlation）运算
卷积层需要学习的参数是：卷积核和偏置大小
"""
import tensorflow as tf
def corr2d(X, K):
"""
定义二维互相关运算函数
:param X:输入数组
:param K: 核数组
:return:二维互相关的运算结果
"""
h, w = K.sh... | normal | {
"blob_id": "3f473701b186b5287258ba74e478cccdad0f29bf",
"index": 2463,
"step-1": "<mask token>\n\n\ndef corr2d(X, K):\n \"\"\"\n 定义二维互相关运算函数\n :param X:输入数组\n :param K: 核数组\n :return:二维互相关的运算结果\n \"\"\"\n h, w = K.shape\n Y = tf.Variable(tf.zeros((X.shape[0] - h + 1, X.shape[1] - w + 1)))... | [
1,
2,
3,
4,
5
] |
Dict={0:0, 1:1}
def fibo(n):
if n not in Dict:
val=fibo(n-1)+fibo(n-2)
Dict[n]=val
return Dict[n]
n=int(input("Enter the value of n:"))
print("Fibonacci(", n,")= ", fibo(n))
# uncomment to take input from the user
nterms = int(input("How many terms? "))
# check if the number of terms is valid
... | normal | {
"blob_id": "5a1c4cc572431f89709d20296d43e8d889e8c5b0",
"index": 5180,
"step-1": "Dict={0:0, 1:1}\ndef fibo(n):\n if n not in Dict:\n val=fibo(n-1)+fibo(n-2)\n Dict[n]=val\n return Dict[n]\nn=int(input(\"Enter the value of n:\"))\nprint(\"Fibonacci(\", n,\")= \", fibo(n))\n\n# uncomment to ta... | [
0
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# sockdemo.py
#
# test
import struct, threading, signal
a = ''
if not a:
print 'a'
else:
print 'b'
import datetime, time, os
print datetime.datetime.now().strftime('%m-%d %H:%M:%S')
def double(x): return x*x
arr = [1, 2, 3, 4, 5]
print map(double, arr)
print 2**16
... | normal | {
"blob_id": "54d6121898dc027d6ecaf9c9e7c25391778e0d21",
"index": 7311,
"step-1": "#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n# sockdemo.py\n#\n# test\n\nimport struct, threading, signal\n\na = ''\n\nif not a:\n\tprint 'a'\nelse:\n\tprint 'b'\n\nimport datetime, time, os\n\nprint datetime.datetime.now().strf... | [
0
] |
# Generated by Django 2.0.2 on 2018-06-10 18:24
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Expression',
fields=[
... | normal | {
"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
] |
import sys
import vector
import matrix
def convert_arg_to_list(arg):
try:
return [float(elem) for elem in arg]
except:
sys.exit("Invalid content inside {}".format(arg))
if __name__ == "__main__":
try:
vector1 = sys.argv[1].split(' ')
vector2 = sys.argv[2].split(' ')
exc... | normal | {
"blob_id": "347bfb2d8809b55046f698620a690099cc83fb56",
"index": 6433,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef convert_arg_to_list(arg):\n try:\n return [float(elem) for elem in arg]\n except:\n sys.exit('Invalid content inside {}'.format(arg))\n\n\n<mask token>\n",
"... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env pybricks-micropython
from pybricks import ev3brick as brick
from pybricks.ev3devices import (Motor, TouchSensor, ColorSensor,
InfraredSensor, UltrasonicSensor, GyroSensor)
from pybricks.parameters import (Port, Stop, Direction, Button, Color,
... | normal | {
"blob_id": "f6ebc3c37a69e5ec49d91609db394eec4a94cedf",
"index": 9982,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nbrick.sound.beep()\nwait(1000)\nmotor_a.run_target(500, 720)\nwait(1000)\nbrick.sound.beep(1000, 500)\n",
"step-3": "<mask token>\nmotor_a = Motor(Port.A)\nbrick.sound.beep()\nwait(1000... | [
0,
1,
2,
3,
4
] |
from rest_framework import serializers
from films.models import *
from django.contrib.auth.models import User
class UserSerializer(serializers.ModelSerializer):
films = serializers.PrimaryKeyRelatedField(many=True, queryset=Film.objects.all())
theaters = serializers.PrimaryKeyRelatedField(many=True, queryset=F... | normal | {
"blob_id": "e6aa28ae312ea5d7f0f818b7e86b0e76e2e57b48",
"index": 4652,
"step-1": "<mask token>\n\n\nclass FilmSerializer(serializers.ModelSerializer):\n owner = serializers.ReadOnlyField(source='owner.username')\n\n\n class Meta:\n model = Film\n fields = 'id', 'title', 'year_prod', 'genre', ... | [
7,
9,
10,
11,
13
] |
"""
Ниже на четырёх языках программирования записана программа, которая вводит натуральное число 𝑥,
выполняет преобразования, а затем выводит результат. Укажите наименьшее значение 𝑥,
при вводе которого программа выведет число 10.
Тупо вручную ввёл. Крч 9. Хз, как на экзамене делать))
"""
x = int(input())
a = 3 * x ... | normal | {
"blob_id": "181e9ac4acf0e69576716f3589359736bfbd9bef",
"index": 2380,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile a != b:\n if a > b:\n a -= b\n else:\n b -= a\nprint(a)\nprint('---')\n<mask token>\nwhile number < 100:\n x = number\n a = 3 * x + 23\n b = 3 * x - 17\... | [
0,
1,
2,
3
] |
import time
import os
import psutil
start = time.time()
from queue import Queue
from copy import copy
process = psutil.Process(os.getpid())
class Node:
object_id = 0
weight = 0
value = 0
def __init__(self,object_id,weight,value):
self.object_id=object_id
self.weight=weight
... | normal | {
"blob_id": "be408b349e2795101b525ad8d948dbf52cab81bf",
"index": 4281,
"step-1": "<mask token>\n\n\nclass Node:\n object_id = 0\n weight = 0\n value = 0\n\n def __init__(self, object_id, weight, value):\n self.object_id = object_id\n self.weight = weight\n self.value = value\n\n\... | [
4,
5,
7,
8,
9
] |
#!/usr/bin/python
# coding=utf-8
import time
import atexit
# for signal handling
import signal
import sys
# ----------------------
# Encoder stuff
# ----------------------
import RPi.GPIO as GPIO
# init
GPIO.setmode(GPIO.BCM) # use the GPIO names, _not_ the pin numbers on the board
# Raspberry Pi pin configuratio... | normal | {
"blob_id": "53841ba56589955e09b03018af1d0ae79b3756c4",
"index": 5595,
"step-1": "<mask token>\n\n\ndef leftEncoderCallback(answer):\n global leftSteps\n leftSteps = leftSteps + 1\n global leftDistance\n leftDistance = leftDistance + 0.24\n print('Left Encoder.')\n\n\ndef rightEncoderCallback(answ... | [
5,
7,
8,
9,
10
] |
from .models import Stock
from .serializers import StockSerializer
from rest_framework import generics
class StockListCreate(generics.ListCreateAPIView):
queryset = Stock.objects.all()
serializer_class = StockSerializer
| normal | {
"blob_id": "9adf18b3a65bf58dd4c22a6fe026d0dd868533fb",
"index": 5468,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass StockListCreate(generics.ListCreateAPIView):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass StockListCreate(generics.ListCreateAPIView):\n query... | [
0,
1,
2,
3
] |
from threading import Lock
from typing import Callable, Any
from remote.domain.commandCallback import CommandCallback
from remote.domain.commandStatus import CommandStatus
from remote.service.remoteService import RemoteService
from ui.domain.subroutine.iSubroutineRunner import ISubroutineRunner
class RemoteSubroutin... | normal | {
"blob_id": "75270fb4ed059f134b47b8937717cb7fe05d9499",
"index": 8833,
"step-1": "<mask token>\n\n\nclass RemoteSubroutineRunner(ISubroutineRunner):\n <mask token>\n\n def execute_charge_subroutine(self, callback: CommandCallback) ->None:\n \"\"\"\n\n :raises BlockingIOError: command already ... | [
14,
15,
17,
19,
21
] |
# coding: utf-8
# In[1]:
import sys
sys.path.extend(['detection', 'train'])
# from detection folder
from MtcnnDetector import MtcnnDetector
from detector import Detector
from fcn_detector import FcnDetector
# from train folder
from model_factory import P_Net, R_Net, O_Net
import config as config
from preprocess.uti... | normal | {
"blob_id": "f97a892e6e0aa258ad917c4a73a66e89b0dc3253",
"index": 267,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsys.path.extend(['detection', 'train'])\n<mask token>\nif test_mode in ['RNet', 'ONet']:\n detectors[1] = Detector(R_Net, 24, batch_size[1], model_path[1])\n if test_mode == 'ONet':\... | [
0,
1,
2,
3,
4
] |
import itertools
def zbits(n,k):
zeros = "0" * k
ones = "1" * (n-k)
binary = ones+zeros
string = {''.join(i) for i in itertools.permutations(binary, n)}
return(string)
assert zbits(4, 3) == {'0100', '0001', '0010', '1000'}
assert zbits(4, 1) == {'0111', '1011', '1101', '1110'}
assert zbits(5, 4)... | normal | {
"blob_id": "a8d13c3fbf6051eba392bcdd6dcb3e946696585f",
"index": 9065,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef zbits(n, k):\n zeros = '0' * k\n ones = '1' * (n - k)\n binary = ones + zeros\n string = {''.join(i) for i in itertools.permutations(binary, n)}\n return string\n\n... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python3
import numpy as np
import os
import random
import pandas as pd
def read_chunk(reader, chunk_size):
data = {}
for i in range(chunk_size):
ret = reader.read_next()
for k, v in ret.items():
if k not in data:
data[k] = []
data[k].appe... | normal | {
"blob_id": "dc28c3426f47bef8b691a06d54713bc68696ee44",
"index": 8309,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef read_chunk(reader, chunk_size):\n data = {}\n for i in range(chunk_size):\n ret = reader.read_next()\n for k, v in ret.items():\n if k not in data:\... | [
0,
1,
2,
3
] |
# Copyright 2014-2018 The PySCF Developers. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | normal | {
"blob_id": "f82ddc34fde76ddfbbe75116526af45b83c1b102",
"index": 7895,
"step-1": "<mask token>\n\n\nclass KnowValues(unittest.TestCase):\n\n def test_ls_contributing(self):\n \"\"\" To test the list of contributing centers \"\"\"\n sv = nao(gto=mol)\n pb = prod_basis()\n pb.sv = sv... | [
2,
3,
4,
5,
6
] |
# -*- coding: utf-8 -*-
from __future__ import absolute_import, unicode_literals
import swapper
from haystack.constants import Indexable
from haystack.fields import CharField, DateTimeField
from haystack.indexes import SearchIndex
class BasePageIndex(SearchIndex):
text = CharField(document=True, use_template=True... | normal | {
"blob_id": "8e1eef3c5a9ca3ea504bbc269b48446527637626",
"index": 1323,
"step-1": "<mask token>\n\n\nclass PageIndex(BasePageIndex, Indexable):\n template = CharField(model_attr='template')\n template_title = CharField(model_attr='get_template_display')\n get_template_display = CharField(model_attr='get_... | [
2,
4,
5,
6,
7
] |
'''
Project Euler
Problem #41 - Pandigital prime
David 07/06/2017
'''
import time
import math
maxPandigitalPrime = 2
def isPrime(num):
if(num<=1):
return False
elif(num==2):
return True
elif(num%2==0):
return False
else:
sqrt_num = math.sqrt(num)
bound = int(... | normal | {
"blob_id": "7ca7693b842700a7b15242b656648e8a7e58cd23",
"index": 1691,
"step-1": "<mask token>\n\n\ndef isPrime(num):\n if num <= 1:\n return False\n elif num == 2:\n return True\n elif num % 2 == 0:\n return False\n else:\n sqrt_num = math.sqrt(num)\n bound = int(s... | [
2,
3,
4,
5,
6
] |
from ctypes import *
class GF_AVCConfigSlot(Structure):
_fields_=[
("size", c_uint16),
("data", c_char),
("id", int)
] | normal | {
"blob_id": "f3b194bbc3c174549b64d6e6b1a8f4438a0c9d38",
"index": 4791,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass GF_AVCConfigSlot(Structure):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass GF_AVCConfigSlot(Structure):\n _fields_ = [('size', c_uint16), ('data', c_char), ('id'... | [
0,
1,
2,
3,
4
] |
from torch.utils.data import DataLoader
from config import Config
from torchnet import meter
import numpy as np
import torch
from torch import nn
from tensorboardX import SummaryWriter
from Funcs import MAvgMeter
from vae.base_vae import VAE
from vae.data_util import Zinc_dataset
import time
import torch.optim
class ... | normal | {
"blob_id": "8b7894e274647e48e3a1fe12473937bd6c62e943",
"index": 8741,
"step-1": "<mask token>\n\n\nclass Trainer:\n\n def __init__(self, model=None, opt=Config()):\n self.model = model\n self.opt = opt\n self.criterion = opt.criterion\n self.pred_id = self.opt.predictor_id\n ... | [
4,
5,
6,
7,
8
] |
import subprocess
from collections import namedtuple
from os.path import basename, splitext
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_pa... | normal | {
"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
] |
# Imports
from __future__ import print_function
import numpy
from numpy.random import randint
from enum import Enum
__all__ = ["common", "plot"]
class result(Enum):
CRIT = 16
HIT = 8
EVADE = 4
FOCUS = 2
BLANK = 1
def result_str(res):
str = ""
if res & result.BLANK:
str += "BLANK"
i... | normal | {
"blob_id": "5261346f96e7520b6ef75a292b3d44a6f00d868c",
"index": 5566,
"step-1": "<mask token>\n\n\nclass result(Enum):\n CRIT = 16\n HIT = 8\n EVADE = 4\n FOCUS = 2\n BLANK = 1\n\n\n<mask token>\n\n\nclass die:\n\n def __init__(self):\n self.rerolled = False\n\n def __str__(self):\n ... | [
24,
26,
29,
33,
38
] |
# Generated by Django 3.2.5 on 2021-08-05 23:59
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('lectures', '0003_auto_20210805_1954'),
]
operations = [
migrations.RenameField(
model_name='lecture',
old_name='is_requird',... | normal | {
"blob_id": "e5bf4518f3834c73c3743d4c711a8d1a4ce3b944",
"index": 6788,
"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 = [('lectures', ... | [
0,
1,
2,
3,
4
] |
# ===================================================================
# Setup
# ===================================================================
from time import sleep
import sys, termios, tty, os, pygame, threading
# ===================================================================
# Functions
# ================... | normal | {
"blob_id": "44274446673225c769f63191d43e4747d8ddfbf7",
"index": 6934,
"step-1": "<mask token>\n\n\ndef play_emergency_sound():\n print('Playing emergency sound. There are ' + str(threading.\n active_count()) + ' threads active')\n while getattr(emergency_sound_thread, 'do_run', True):\n pyga... | [
2,
3,
4,
5,
6
] |
import re
print("Welcome to the Python Calculator")
print("To stop calculator type: quit")
previous = 0
run = True
def perform_math():
'''(numbers) -> numbers
accepts numbers from the user and performs continuous
mathematical equations on them.
precondition input must be numbers and m... | normal | {
"blob_id": "4122da21abab462a28c925c1afa5792ec729a75a",
"index": 5087,
"step-1": "<mask token>\n\n\ndef perform_math():\n \"\"\"(numbers) -> numbers\n\n accepts numbers from the user and performs continuous\n mathematical equations on them.\n\n precondition input must be numbers and mathematical sign... | [
1,
2,
3,
4,
5
] |
from qiskit import QuantumCircuit,execute,Aer
from qiskit.visualization import plot_histogram
import matplotlib.pyplot as plt
qc_ha=QuantumCircuit(4,2)
qc_ha.x(0)
qc_ha.x(1)
qc_ha.barrier()
qc_ha.cx(0,2)
qc_ha.cx(1,2)
qc_ha.ccx(0,1,3)
qc_ha.barrier()
qc_ha.measure(2,0)
qc_ha.measure(3,1)
#qc_ha.draw(output='mpl')
coun... | normal | {
"blob_id": "02381f28ef20aa0c2c235ef6563e1810a5931e35",
"index": 5556,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nqc_ha.x(0)\nqc_ha.x(1)\nqc_ha.barrier()\nqc_ha.cx(0, 2)\nqc_ha.cx(1, 2)\nqc_ha.ccx(0, 1, 3)\nqc_ha.barrier()\nqc_ha.measure(2, 0)\nqc_ha.measure(3, 1)\n<mask token>\nplot_histogram(counts... | [
0,
1,
2,
3,
4
] |
import face_recognition
from glob import glob
import os.path as osp
class FaceRecognitionLib(object):
"""
face_recognition library を利用した顔認証検証
"""
# クラス変数設定
__data_set_dir = './../../dataset/japanese' # データ・セットディレクトリ
__known_image_idx = (1,) # 既存画像のインデックス
... | normal | {
"blob_id": "2d69a39be3931aa4c62cadff4cdfad76f6b32c59",
"index": 6473,
"step-1": "<mask token>\n\n\nclass FaceRecognitionLib(object):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def __init__(self):\n sub_dirs = glob(FaceRecognitionLib.__data_set_dir + '... | [
3,
4,
5,
8,
9
] |
from __future__ import print_function
import zmq
import time
import random
import numpy as np
import msgpack as serializer
port = '42000'
# let the OS choose the IP and PORT
ipc_sub_url = 'tcp://*:*'
ipc_push_url = 'tcp://*:*'
# starting communication threads
zmq_ctx = zmq.Context()
pub_socket = zmq_ctx.socket(zmq.... | normal | {
"blob_id": "cb469b69bf974d39609f79c4f3be686d8106f971",
"index": 1431,
"step-1": "<mask token>\n",
"step-2": "<mask token>\npub_socket.bind('tcp://*:%s' % port)\nwhile True:\n topic = 'test'\n thisX = np.random.rand()\n thisY = np.random.rand()\n testDict = {'gaze': (thisX, thisY)}\n pub_socket.... | [
0,
1,
2,
3,
4
] |
# -* coding: utf-8 -*-
# A headless media player based on gstreamer.
from gi.repository import Gst
Gst.init(None)
class Player:
def __init__(self, uri=None):
# Creates a playbin (plays media from an uri).
self.player = Gst.ElementFactory.make('playbin', 'player')
self.uri = uri
@pro... | normal | {
"blob_id": "01e9ceb516a323a2017c65e368da419c6570dce2",
"index": 7304,
"step-1": "<mask token>\n\n\nclass Player:\n <mask token>\n\n @property\n def uri(self):\n return self._uri\n\n @uri.setter\n def uri(self, value):\n self._uri = value\n self.player.set_state(Gst.State.NULL... | [
3,
6,
8,
9,
10
] |
# To add a new cell, type '# %%'
# To add a new markdown cell, type '# %% [markdown]'
# %% [markdown]
# ### Bài tập 1.
# - <ins>Yêu cầu</ins>: Ý tưởng cơ bản của thuật toán ``Support Vector Machine`` (``SVM``) là gì? Ý tưởng của thuật toán biên mềm (``soft margin``) ``SVM``. Nêu ý nghĩa của siêu tham số ``C`` trong bà... | normal | {
"blob_id": "1b1b646a75fe2ff8d54e66d025b60bde0c9ed2d6",
"index": 9361,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ndf.pivot_table(index=['classes'], aggfunc='size')\n<mask token>\nfor n in np.arange(0.5, C_parameter, 0.5):\n clf = svm.SVC(C=n).fit(X_train, y_train)\n yhat = clf.predict(X_test)\n... | [
0,
1,
2,
3,
4
] |
from Bio import SeqIO
def flatten(l):
return [j for i in l for j in i]
def filter_sequences_by_len_from_fasta(file, max_len):
with open(file) as handle:
return [str(record.seq) for record in SeqIO.parse(handle, 'fasta') if
len(record.seq) <= max_len]
| normal | {
"blob_id": "1fdb9db4c1c8b83c72eeb34f10ef9d289b43b79f",
"index": 3166,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef flatten(l):\n return [j for i in l for j in i]\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef flatten(l):\n return [j for i in l for j in i]\n\n\ndef filter_sequen... | [
0,
1,
2,
3
] |
#!/usr/bin/env python
# -*- coding: UTF-8 -*-
#
# Copyright (C) 2011 Lionel Bergeret
#
# ----------------------------------------------------------------
# The contents of this file are distributed under the CC0 license.
# See http://creativecommons.org/publicdomain/zero/1.0/
# ----------------------------------------... | normal | {
"blob_id": "b7aa99e9e4af3bef4b2b3e7d8ab9bf159a093af6",
"index": 574,
"step-1": "#!/usr/bin/env python\n# -*- coding: UTF-8 -*-\n#\n# Copyright (C) 2011 Lionel Bergeret\n#\n# ----------------------------------------------------------------\n# The contents of this file are distributed under the CC0 license.\n# S... | [
0
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Apr 24 22:05:12 2019
@author: admin
"""
for index in range(test_set.shape[0]):
print(index) | normal | {
"blob_id": "35647ed5e2c128a5bf819a1e47ead7e958172b1c",
"index": 9711,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor index in range(test_set.shape[0]):\n print(index)\n",
"step-3": "#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Apr 24 22:05:12 2019\n\n@author: admin\n\... | [
0,
1,
2
] |
import time
class DISTRICT:
def __init__(
self, cdcode, county, district, street, city, zipcode,
state, mailstreet, mailcity, mailzip, mailstate, phone, extphone,
faxnumber, email, admfname, admlname, admemail, lat, long,
distrownercode, doctype, statustype, lastup... | normal | {
"blob_id": "462d73195680118d19a3d4e8a855e65aaeecb3c6",
"index": 892,
"step-1": "<mask token>\n\n\nclass DISTRICT:\n\n def __init__(self, cdcode, county, district, street, city, zipcode,\n state, mailstreet, mailcity, mailzip, mailstate, phone, extphone,\n faxnumber, email, admfname, admlname, a... | [
5,
9,
10,
12,
13
] |
"""
Creating flask server that response with a json
"""
from flask import Flask
from flask import jsonify
micro_service = Flask(__name__)
@micro_service.route('/') # http://mysite.com/
def home():
return jsonify({'message': 'Hello, world!'})
if __name__ == '__main__':
micro_service.run()
| normal | {
"blob_id": "4b14dee3625d5d0c703176ed2f0a28b2583fd84d",
"index": 6519,
"step-1": "<mask token>\n\n\n@micro_service.route('/')\ndef home():\n return jsonify({'message': 'Hello, world!'})\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\n@micro_service.route('/')\ndef home():\n return jsonify({'message': ... | [
1,
2,
3,
4,
5
] |
# -*- coding: utf-8 -*-
# This file is auto-generated, don't edit it. Thanks.
from typing import Dict
from Tea.core import TeaCore
from alibabacloud_tea_openapi.client import Client as OpenApiClient
from alibabacloud_tea_openapi import models as open_api_models
from alibabacloud_tea_util.client import Client as UtilCl... | normal | {
"blob_id": "2e5d66033c2a049ba2423d01792a629bf4b8176d",
"index": 8728,
"step-1": "<mask token>\n\n\nclass Client(OpenApiClient):\n <mask token>\n <mask token>\n\n def get_endpoint(self, product_id: str, region_id: str, endpoint_rule:\n str, network: str, suffix: str, endpoint_map: Dict[str, str],... | [
8,
10,
11,
12,
14
] |
# -*- coding:utf-8 -*-
import sys
import time
class ProgressBar:
@staticmethod
def progress_test():
bar_length = 100
for percent in range(0, 101):
hashes = '#' * int(percent / 100.0 * bar_length)
spaces = ' ' * (bar_length - len(hashes))
sys.stdout.write("\... | normal | {
"blob_id": "f928eb34155046107c99db8ded11747d5960c767",
"index": 2527,
"step-1": "<mask token>\n\n\nclass ProgressBar:\n <mask token>\n\n\n class ProgressBar1:\n\n def __init__(self, width=50):\n self.pointer = 0\n self.width = width\n\n def __call__(self, x):\n ... | [
1,
3,
4,
5,
6
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Tests for the file entry implementation using pyfshfs."""
import unittest
from dfvfs.lib import definitions
from dfvfs.path import factory as path_spec_factory
from dfvfs.resolver import context
from dfvfs.vfs import hfs_attribute
from dfvfs.vfs import hfs_file_entry
f... | normal | {
"blob_id": "520672f8607751b65fe9e4b975a9978ed0ab71b6",
"index": 8242,
"step-1": "<mask token>\n\n\nclass HFSFileEntryTest(shared_test_lib.BaseTestCase):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def tearDown(self):\n \"\"\"Cleans up... | [
18,
19,
20,
25,
27
] |
import subprocess as sp
from .dummy_qsub import dummy_qsub
from os.path import exists
from os import makedirs
from os import remove
from os.path import dirname
QUEUE_NAME = 'fact_medium'
def qsub(job, exe_path, queue=QUEUE_NAME):
o_path = job['o_path'] if job['o_path'] is not None else '/dev/null'
e_path = jo... | normal | {
"blob_id": "427d3d386d4b8a998a0b61b8c59984c6003f5d7b",
"index": 6975,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef qsub(job, exe_path, queue=QUEUE_NAME):\n o_path = job['o_path'] if job['o_path'] is not None else '/dev/null'\n e_path = job['e_path'] if job['e_path'] is not None else '/de... | [
0,
1,
2,
3
] |
"""
Author : Gülşah Büyük
Date : 17.04.2021
"""
import numpy as np
A = np.array([[22, -41, 2], [61, 17, -18], [-9, 74, -13]])
# For a square matrix A the QR Decomposition converts into the product of an orthogonal matrix Q
# (Q.T)Q= I and an upper triangular matrix R.
def householder_reflection(A):
# A H... | normal | {
"blob_id": "0d1fda864edc73cc6a9853727228c6fa3dfb19a1",
"index": 3039,
"step-1": "<mask token>\n\n\ndef householder_reflection(A):\n size = len(A)\n Q = np.identity(size)\n R = np.copy(A)\n for i in range(size - 1):\n x = R[i:, i]\n e = np.zeros_like(x)\n e[0] = np.linalg.norm(x)... | [
1,
2,
3,
4,
5
] |
from convert_data2 import array_rule
from convert_data2 import array_packet
import tensorflow as tf
import numpy as np
train_x, train_y = array_packet()
x_input, input_ip = array_rule()
n_nodes_hl1 = 210
n_nodes_hl2 = 210
n_nodes_hl3 = 210
n_classes = 2
batch_size = 500
hm_epochs = 20
x = tf.placeholder('float')
y ... | normal | {
"blob_id": "1446268583bf9fa3375319eae3c21cf47f47faca",
"index": 7279,
"step-1": "<mask token>\n\n\ndef neural_network_model(data):\n l1 = tf.add(tf.matmul(data, hidden_1_layer['weight']), hidden_1_layer[\n 'bias'])\n l1 = tf.nn.relu(l1)\n l2 = tf.add(tf.matmul(l1, hidden_2_layer['weight']), hidd... | [
2,
3,
4,
5,
6
] |
from redis_interval.client import RedisInterval
class TestRedisIntervalIADD(object):
""" Tests the IADD command """
@classmethod
def setup_class(cls):
cls.redis = RedisInterval(host="localhost")
def test_add_simple_text(self):
""" Add simple text inside an interval """
value ... | normal | {
"blob_id": "0e7732ffcada864fb83b59625c5b9abb01150aaa",
"index": 1702,
"step-1": "<mask token>\n\n\nclass TestRedisIntervalIADD(object):\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass TestRedisIntervalIADD(object):\n <mask token>\n\n @classmethod\n def set... | [
1,
3,
4,
5,
6
] |
from ..scope_manager import ScopeManager
from ..span import Span
from ..tracer import Tracer
from .propagator import Propagator
class MockTracer(Tracer):
def __init__(self, scope_manager: ScopeManager | None = ...) -> None: ...
def register_propagator(self, format: str, propagator: Propagator) -> None: ...
... | normal | {
"blob_id": "76d2c80c673f9a0444e72721909a51479ff35521",
"index": 1785,
"step-1": "<mask token>\n\n\nclass MockTracer(Tracer):\n\n def __init__(self, scope_manager: (ScopeManager | None)=...) ->None:\n ...\n\n def register_propagator(self, format: str, propagator: Propagator) ->None:\n ...\n ... | [
3,
4,
5,
6,
7
] |
# -*- coding: utf-8 -*-
"""microcms package, minimalistic flatpage enhancement.
THIS SOFTWARE IS UNDER BSD LICENSE.
Copyright (c) 2010-2012 Daniele Tricoli <eriol@mornie.org>
Read LICENSE for more informations.
"""
VERSION = (0, 2, 0)
| normal | {
"blob_id": "3e1c2d0c5bb30d093a99f10020af14db5436bf02",
"index": 5551,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nVERSION = 0, 2, 0\n",
"step-3": "# -*- coding: utf-8 -*-\n\"\"\"microcms package, minimalistic flatpage enhancement.\n\nTHIS SOFTWARE IS UNDER BSD LICENSE.\nCopyright (c) 2010-2012 Dani... | [
0,
1,
2
] |
import hashlib
def md5_hexdigest(data):
return hashlib.md5(data.encode('utf-8')).hexdigest()
def sha1_hexdigest(data):
return hashlib.sha1(data.encode('utf-8')).hexdigest()
def sha224_hexdigest(data):
return hashlib.sha224(data.encode('utf-8')).hexdigest()
def sha256_hexdigest(data):
return hash... | normal | {
"blob_id": "35a95c49c2dc09b528329433a157cf313cf59667",
"index": 8955,
"step-1": "<mask token>\n\n\ndef md5_hexdigest(data):\n return hashlib.md5(data.encode('utf-8')).hexdigest()\n\n\ndef sha1_hexdigest(data):\n return hashlib.sha1(data.encode('utf-8')).hexdigest()\n\n\ndef sha224_hexdigest(data):\n re... | [
4,
5,
6,
7
] |
import json
import sys
from copy import deepcopy
from argparse import ArgumentParser
# TODO: Ord category's IDs after deletion
def return_cat_name(json_coco, category):
"""Return the category name of a category ID
Arguments:
json_coco {dict} -- json dict file from coco file
category {int} --... | normal | {
"blob_id": "467327b98ab99bdad429943c701c751be4f67940",
"index": 9378,
"step-1": "<mask token>\n\n\ndef main():\n \"\"\"Remove a category from a coco json file\n \"\"\"\n parser = ArgumentParser(description=\n 'Category Filter: Filter a List of Categories from a JSON')\n parser.add_argument('j... | [
1,
2,
3,
4,
5
] |
import os
import random
import cv2
import numpy as np
from keras.preprocessing.image import img_to_array
import numpy as np
import keras
from scipy import ndimage, misc
def preprocess_image(img):
img = img.astype(np.uint8)
(channel_b, channel_g, channel_r) = cv2.split(img)
result = ndimage.maximum_filter(... | normal | {
"blob_id": "586d39556d2922a288a2bef3bcffbc6f9e3dc39d",
"index": 6707,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef preprocess_image(img):\n img = img.astype(np.uint8)\n channel_b, channel_g, channel_r = cv2.split(img)\n result = ndimage.maximum_filter(channel_g, size=5)\n ret, resu... | [
0,
1,
2,
3,
4
] |
def presses(phrase):
keyboard = ['1', 'ABC2', 'DEF3', 'GHI4', 'JKL5', 'MNO6', 'PQRS7',
'TUV8', 'WXYZ9', '*', ' 0', '#']
amount = 0
for lttr in phrase.upper():
for key in keyboard:
try:
i = key.index(lttr)
i += 1
amount += i
... | normal | {
"blob_id": "c2e9a93861080be616b6d833a9343f1a2f018a0b",
"index": 5039,
"step-1": "<mask token>\n",
"step-2": "def presses(phrase):\n keyboard = ['1', 'ABC2', 'DEF3', 'GHI4', 'JKL5', 'MNO6', 'PQRS7',\n 'TUV8', 'WXYZ9', '*', ' 0', '#']\n amount = 0\n for lttr in phrase.upper():\n for key i... | [
0,
1
] |
#THIS BUILD WORKS, BUT IS VERY SLOW. CURRENTLY YIELDS A DECENT SCORE, NOT GREAT
alphabet = "abcdefghijklmnopqrstuvwxyz"
def author():
return ""
def student_id():
return ""
def fill_words(pattern,words,scoring_f,minlen,maxlen):
foundWords = find_words(pattern,words,scoring_f,minlen,maxlen)
f... | normal | {
"blob_id": "9bd659bb3bf812e48710f625bb65a848d3a8d074",
"index": 594,
"step-1": "<mask token>\n\n\ndef author():\n return ''\n\n\ndef student_id():\n return ''\n\n\n<mask token>\n\n\ndef find_words(pattern, words, scoring_f, minlen, maxlen):\n patternCopy = pattern\n bestWord = '', 0\n bestState =... | [
5,
7,
8,
9,
10
] |
#coding=utf-8
'''
Created on 2013-3-28
@author: jemmy
'''
import telnetlib
import getpass
import sys
import os
import time
import xlrd
from pyExcelerator import *
import
#define
Host = "192.168.0.1"
Port = "70001"
#Host = raw_iput("IP",)
username = "admin"
password = "admin"
filename = str(time.strftime('%Y%m%d%H%M%S... | normal | {
"blob_id": "153c02585e5d536616ec4b69757328803ac2fb71",
"index": 3394,
"step-1": "#coding=utf-8\n'''\nCreated on 2013-3-28\n\n@author: jemmy\n'''\nimport telnetlib\nimport getpass\nimport sys\nimport os\nimport time\nimport xlrd\nfrom pyExcelerator import *\nimport\n#define\nHost = \"192.168.0.1\"\nPort = \"7000... | [
0
] |
from twitter.MyStreamListener import MyStreamListener
import tweepy
from threading import Thread
class TwitterWorker(Thread):
def __init__(self):
Thread.__init__(self)
CONSUMER_KEY = 'IwZZeJHjLXq55ewwQwD0SogHU'
CONSUMER_SECRET = '80kELQhDGNvLNFfNZ7qliIbzAoA3tsgQ... | normal | {
"blob_id": "c475e095571b211693e66583637442edbf72c260",
"index": 7741,
"step-1": "<mask token>\n\n\nclass TwitterWorker(Thread):\n <mask token>\n\n def run(self):\n streamListener = MyStreamListener()\n self.stream = tweepy.Stream(auth=self.api.auth, listener=streamListener\n )\n ... | [
2,
3,
4,
5,
6
] |
import joblib
import os
import shutil
import re
from scipy import stats
from functools import partial
import pandas as pd
from multiprocessing import Process, Pool
from nilearn import masking, image
import nibabel as nib
import numpy as np
from tqdm import tqdm
import matplotlib
matplotlib.use('Agg')
import matplotlib... | normal | {
"blob_id": "2e9d71b8055e1bab107cedae69ca3bc4219e7d38",
"index": 7460,
"step-1": "<mask token>\n\n\ndef get_paths(debug, dataset):\n if debug and dataset == 'OASIS':\n project_wd = os.getcwd()\n project_data = os.path.join(project_wd, 'data')\n project_sink = os.path.join(project_data, 'o... | [
16,
17,
18,
21,
23
] |
import os,sys
import logging
from flask import Flask
from flask_bootstrap import Bootstrap
from flask_sqlalchemy import SQLAlchemy
def create_app():
app = Flask(__name__)
Bootstrap(app)
return app
logging.basicConfig(level=logging.DEBUG)
app = create_app()
app.config['WTF_CSRF_ENABLED'] = True
app.config[... | normal | {
"blob_id": "bd726c86bdecd0b63eb48d056932706d3ecf147d",
"index": 7665,
"step-1": "<mask token>\n\n\ndef create_app():\n app = Flask(__name__)\n Bootstrap(app)\n return app\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef create_app():\n app = Flask(__name__)\n Bootstrap(app)\n return ap... | [
1,
2,
3,
4,
5
] |
# created by RomaOkorosso at 21.03.2021
# models.py
from datetime import datetime
from sqlalchemy import (
Column,
Integer,
String,
Boolean,
DateTime,
ForeignKey,
Date
)
from sqlalchemy.dialects import postgresql
from sqlalchemy.orm import relationship
from Database.database import Base
... | normal | {
"blob_id": "a288e66e64d386afd13bfc7b5b13d4a47d15cd6d",
"index": 1316,
"step-1": "<mask token>\n\n\nclass Client(Base):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\nclass TakenBook(Base):\n __tablename__ = 'taken_books'\n id = Column(Integ... | [
3,
7,
8,
10,
12
] |
from selenium import webdriver
from selenium.common.exceptions import TimeoutException
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.common.keys import Keys
from selenium.webdri... | normal | {
"blob_id": "5f490d6a3444b3b782eed5691c82ab7e4b2e55db",
"index": 8883,
"step-1": "from selenium import webdriver\nfrom selenium.common.exceptions import TimeoutException\nfrom selenium.webdriver.common.by import By\nfrom selenium.webdriver.support.ui import WebDriverWait\nfrom selenium.webdriver.support import e... | [
0
] |
# Imports
import os
from flask import Flask, redirect, render_template, url_for, request, flash
from flask_login import LoginManager, login_user, logout_user, login_required, current_user
# Import - Database
from flask_sqlalchemy import SQLAlchemy
# Import - Models
from werkzeug.security import generate_password_hash... | normal | {
"blob_id": "6ff4aff5811d2bd7ad150d7e8f925308d120ef74",
"index": 2566,
"step-1": "<mask token>\n\n\nclass User(UserMixin, db.Model):\n __tablename__ = 'users'\n id = db.Column(db.Integer, primary_key=True)\n name = db.Column(db.String(64))\n email = db.Column(db.String(64), unique=True, index=True)\n... | [
23,
24,
26,
27,
32
] |
#!/usr/bin/env python
import argparse
import xml.etree.cElementTree as ET
from datetime import datetime, timedelta
from requests import codes as requests_codes
from requests_futures.sessions import FuturesSession
from xml.etree import ElementTree as ET
parser = argparse.ArgumentParser(description='Fetch dqm images')... | normal | {
"blob_id": "0d18272f8056f37eddabb024dd769a2793f88c24",
"index": 6064,
"step-1": "#!/usr/bin/env python\n\nimport argparse\nimport xml.etree.cElementTree as ET\n\nfrom datetime import datetime, timedelta\nfrom requests import codes as requests_codes\nfrom requests_futures.sessions import FuturesSession\nfrom xml... | [
0
] |
def readfasta (fasta):
input = open(fasta, 'r')
seqs = {}
for line in input:
if line[0] == '>':
name = line[1:].rstrip()
seqs[name] = []
else:
seqs[name].append(line.rstrip())
for name in seqs:
seqs[name] = ''.join(seqs[name])
r... | normal | {
"blob_id": "6072fc22872ee75c9501ac607a86ee9137af6a5d",
"index": 4918,
"step-1": "def readfasta (fasta):\r\n input = open(fasta, 'r')\r\n seqs = {}\r\n for line in input:\r\n if line[0] == '>':\r\n name = line[1:].rstrip()\r\n seqs[name] = [] \r\n else:\r\n ... | [
0
] |
"""
Read all the images from a directory,
resize, rescale and rename them.
"""
| normal | {
"blob_id": "670efbd9879099b24a87e19a531c4e3bbce094c6",
"index": 1666,
"step-1": "<mask token>\n",
"step-2": "\n\n\"\"\"\nRead all the images from a directory,\nresize, rescale and rename them.\n\"\"\"\n\n\n\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
# DATA TYPES (DATA TİPLERİ)
# STRİNGS (KARAKTER DİZİNLERİ)
# Bir karakter dizinini tanımlamak için tırnaklar kullanılır. birkaç satır ka-
# rakter dizini yazıyorsak 3 tırnak kullanılır:
print("""Üç tırnaklı
karakter
dizinine
örnek""")
üç tırnaklı
karakter
dizinine
örnek
print('Tek tırnak: Tek satırlık... | normal | {
"blob_id": "61f2fbed184ff6f842ba9527456da453844f8dc6",
"index": 1362,
"step-1": "# DATA TYPES (DATA TİPLERİ)\r\n\r\n# STRİNGS (KARAKTER DİZİNLERİ)\r\n\r\n# Bir karakter dizinini tanımlamak için tırnaklar kullanılır. birkaç satır ka-\r\n# rakter dizini yazıyorsak 3 tırnak kullanılır:\r\nprint(\"\"\"Üç tırnaklı\r... | [
0
] |
import math
import numpy as np
import torch
import torch.nn as nn
from torch.utils.data import DataLoader
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
def value(energy, noise, x, gen):
logp_x = energy(x)
logq_x = noise.log_prob(x).unsqueeze(1)
logp_gen = energy(gen)
logq_ge... | normal | {
"blob_id": "010a132645883915eff605ae15696a1fac42d570",
"index": 8276,
"step-1": "<mask token>\n\n\ndef value(energy, noise, x, gen):\n logp_x = energy(x)\n logq_x = noise.log_prob(x).unsqueeze(1)\n logp_gen = energy(gen)\n logq_gen = noise.log_prob(gen).unsqueeze(1)\n ll_data = logp_x - torch.log... | [
7,
8,
9,
11,
12
] |
from random import randint
cantidad = int(input("Numero de preguntas: "))
contador_bien = 0
contador_mal = 0
while cantidad <= 0:
print ("El numero de preguntas debe ser al menos 1")
cantidad = int(input("Numero de preguntas: "))
for i in range(cantidad):
numero = randint(2,10)
numero2 = randint(2,10)
aleatorio ... | normal | {
"blob_id": "48bc5d4b191fa631650b60240560dbece6396312",
"index": 655,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile cantidad <= 0:\n print('El numero de preguntas debe ser al menos 1')\n cantidad = int(input('Numero de preguntas: '))\nfor i in range(cantidad):\n numero = randint(2, 10)\n ... | [
0,
1,
2,
3,
4
] |
#Charlie Quinn if.py
#Check < in an 'if' statement
#use a 'while' loop to make testing easier
def income_input(prompt_message):
prompt = prompt_message + ' '
temp = input(prompt)
#get input from user
return float(temp)
do_again = 'y'
while do_again =='y':
income = income_input("\nHow much did ... | normal | {
"blob_id": "d5acde6c6139833c6631a2d88a181cd019d3d2da",
"index": 5747,
"step-1": "<mask token>\n",
"step-2": "def income_input(prompt_message):\n prompt = prompt_message + ' '\n temp = input(prompt)\n return float(temp)\n\n\n<mask token>\n",
"step-3": "def income_input(prompt_message):\n prompt =... | [
0,
1,
2,
3,
4
] |
import time
import random
from BlockchainNetwork.MVB import *
from threading import Thread
coloredlogs.install()
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
log = logging.getLogger(__name__)
class MVBTest:
def __init__(self, initialNodeCnt):
sel... | normal | {
"blob_id": "8ad9efbbb2d9e2a5f73ebbb999da3ed93e4c1974",
"index": 9655,
"step-1": "<mask token>\n\n\nclass MVBTest:\n <mask token>\n <mask token>\n\n def doubleSpendTest(self):\n \"\"\"\n txOutputs is the genesis output.\n txOutputs[0] was used twice in this test.\n ... | [
11,
15,
17,
18,
19
] |
from ccapi.interfaces.bitfinex import Bitfinex
from ccapi.interfaces.bittrex import Bittrex
from ccapi.interfaces.poloniex import Poloniex
from ccapi.interfaces.bithumb import Bithumb
from ccapi.interfaces.coinone import Coinone
from ccapi.interfaces.korbit import Korbit
# from ccapis.interfaces.coinbase import Coinbas... | normal | {
"blob_id": "098c91f4aa367cb389e542c0199b633e7ecd4003",
"index": 4369,
"step-1": "<mask token>\n",
"step-2": "from ccapi.interfaces.bitfinex import Bitfinex\nfrom ccapi.interfaces.bittrex import Bittrex\nfrom ccapi.interfaces.poloniex import Poloniex\nfrom ccapi.interfaces.bithumb import Bithumb\nfrom ccapi.in... | [
0,
1,
2
] |
import pygame
from .Coin import Coin
from .Snake import Snake, Block
from .Bomb import Bomb
from .Rocket import Rocket
from pygame.math import Vector2
cell_size = 16
cell_number = 30
sprite_cell = pygame.image.load("Assets/Cell.png")
bg = pygame.image.load("Assets/BG.png")
bg2 = pygame.image.load("Assets/BG2.png")
c... | normal | {
"blob_id": "2b14607aa2527f5da57284917d06ea60e89f784c",
"index": 1659,
"step-1": "<mask token>\n\n\nclass GAME:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def check_timer(self):\n if self.count >= self.crowd:\n self.game_timer += 1\n if self.game_t... | [
5,
7,
9,
10,
13
] |
# -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'mapGraph.ui'
#
# Created by: PyQt5 UI code generator 5.9.2
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_MapGraphTab(object):
def setupUi(self, MapGraphTab):
MapGra... | normal | {
"blob_id": "03a13037a9a102397c8be4d9f0f4c5e150965808",
"index": 8666,
"step-1": "<mask token>\n\n\nclass Ui_MapGraphTab(object):\n <mask token>\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass Ui_MapGraphTab(object):\n\n def setupUi(self, MapGraphTab):\n MapGraphTab.setO... | [
1,
2,
3,
4,
5
] |
# -*- coding: utf-8 -*-
"""
Created on Wed Feb 7 17:42:18 2018
@author: Tim
"""
import music21 as m21
import music21.features.jSymbolic as jsym
import scipy.stats
from collections import Counter
import numpy as np
import matplotlib.pyplot as plt
from timeit import default_timer as timer
# round all duration values t... | normal | {
"blob_id": "eb9135c6bcf89a62534cfc8480e5d44a089fe5a8",
"index": 1216,
"step-1": "<mask token>\n\n\ndef extractPatternOccurrence(songName, inStart, inEnd, useTies, songs):\n \"\"\"\n given song name, occurrence start, occurrence end, and the database of score files,\n return the notes of the associated ... | [
3,
8,
9,
10,
11
] |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('sub_adjuster', '0002_parameters'),
]
operations = [
migrations.AlterField(
model_name='subtitles',
n... | normal | {
"blob_id": "156203042ed8a9bde0e9d8587ea3d37de6bcfdf7",
"index": 5155,
"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 = [('sub_adjuste... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python
import argparse
import requests
import sys
import os
import xml.dom.minidom
__author__ = 'Tighe Schlottog || tschlottog@paloaltonetworks.com'
'''
wf.py is a script to interact with the WildFire API to upload files or pull back reports on specific hashes. You
need to have the argparse a... | normal | {
"blob_id": "e8e78610df4461a96f7d9858870de0e3482801fd",
"index": 5083,
"step-1": "#!/usr/bin/env python\n\nimport argparse\nimport requests\nimport sys\nimport os\nimport xml.dom.minidom\n\n__author__ = 'Tighe Schlottog || tschlottog@paloaltonetworks.com'\n\n'''\n wf.py is a script to interact with the WildFi... | [
0
] |
from sympy import *
import sys
x = Symbol("x")
# EOF
try:
in_str = input()
except Exception as e:
print("WRONG FORMAT!") # Wrong Format!
sys.exit(0)
in_str = in_str.replace("^", "**") #change '^'into'**' for recognition
# wrong expression
try:
in_exp = eval(in_str) # turn s... | normal | {
"blob_id": "1634ae0e329b4f277fa96a870fbd19626c0ece81",
"index": 6516,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ntry:\n in_str = input()\nexcept Exception as e:\n print('WRONG FORMAT!')\n sys.exit(0)\n<mask token>\ntry:\n in_exp = eval(in_str)\nexcept Exception as e:\n print('WRONG FO... | [
0,
1,
2,
3,
4
] |
import collections
# Definition for a binary tree node.
class TreeNode:
def __init__(self, val=0, left=None, right=None):
self.val = val
self.left = left
self.right = right
class Solution:
def isSymmetric(self, root: TreeNode) -> bool:
if not root:
return True
... | normal | {
"blob_id": "24a4b9246a9b15334bebc45c532a25bd81266918",
"index": 9650,
"step-1": "<mask token>\n\n\nclass Solution:\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass TreeNode:\n <mask token>\n\n\nclass Solution:\n\n def isSymmetric(self, root: TreeNode) ->bool:\n if not root:\n r... | [
1,
3,
4,
5,
6
] |
#!/usr/bin/env python
#coding:gbk
"""
Author: pengtao --<pengtao@baidu.com>
Purpose:
1. 管理和交互式调用hadoop Job的框架
History:
1. 2013/12/11 created
"""
import sys
import inspect
import cmd
import readline
#import argparse
#from optparse import (OptionParser, BadOptionError, AmbiguousOptionError)
from job i... | normal | {
"blob_id": "9178d39a44cfb69e74b4d6cd29cbe56aea20f582",
"index": 3984,
"step-1": "#!/usr/bin/env python\n#coding:gbk\n\n\"\"\"\n Author: pengtao --<pengtao@baidu.com>\n Purpose: \n 1. 管理和交互式调用hadoop Job的框架\n History:\n 1. 2013/12/11 created\n\"\"\"\n\n\n\nimport sys\nimport inspect\nimport cmd\nimport r... | [
0
] |
# SPDX-License-Identifier: Apache-2.0
"""
.. _example-lightgbm-pipe:
Convert a pipeline with a LightGbm model
========================================
.. index:: LightGbm
*sklearn-onnx* only converts *scikit-learn* models into *ONNX*
but many libraries implement *scikit-learn* API so that their models
can be inclu... | normal | {
"blob_id": "32227029cb4e852536611f7ae5dec5118bd5e195",
"index": 8324,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nnumpy.random.shuffle(ind)\n<mask token>\npipe.fit(X, y)\nupdate_registered_converter(LGBMClassifier, 'LightGbmLGBMClassifier',\n calculate_linear_classifier_output_shapes, convert_ligh... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
import numpy as np
from . import BOID_NOSE_LEN
from .utils import normalize_angle, unit_vector
class Individual:
def __init__(self, color, pos, ror, roo, roa, angle=0, speed=1.0, turning_rate=0.2):
"""Constructor of Individual.
Args:
color (Color): color for ... | normal | {
"blob_id": "386e491f6b10ca27f513d678c632571c29093ad2",
"index": 5825,
"step-1": "<mask token>\n\n\nclass Individual:\n <mask token>\n\n @property\n def dir(self):\n \"\"\"Get the unitary vector of direction.\n\n Returns:\n numpy.ndarray: The unitary vector of direction.\n\n ... | [
5,
6,
7,
8,
9
] |
# Chris DeBoever
# cdeboeve@ucsd.edu
import sys, argparse, pdb, glob, os, re
import numpy as np
from bisect import bisect_left
from scipy.stats import binom
### helper functions ###
def find_lt(a,x):
"""
Find rightmost value less than x in list a
Input: list a and value x
Output: rightmost value les... | normal | {
"blob_id": "da751e96c225ebc2d30f3cce01ba2f64d0a29257",
"index": 3763,
"step-1": "<mask token>\n\n\ndef find_lt(a, x):\n \"\"\"\n Find rightmost value less than x in list a\n Input: list a and value x\n Output: rightmost value less than x in a\n \"\"\"\n i = bisect_left(a, x)\n if i:\n ... | [
7,
8,
9,
11,
12
] |
# -*- coding: utf-8 -*-
# Form implementation generated from reading ui file '/home/cypher/.eric6/eric6plugins/vcsGit/ConfigurationPage/GitPage.ui'
#
# Created by: PyQt5 UI code generator 5.8
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_GitPage(object):... | normal | {
"blob_id": "80891a4c9703f91509d2c1b22304f33426dfb962",
"index": 4419,
"step-1": "<mask token>\n\n\nclass Ui_GitPage(object):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Ui_GitPage(object):\n\n def setupUi(self, GitPage):\n GitPage.setObjectName('GitPage')\n GitP... | [
1,
2,
3,
4,
5
] |
class Solution:
def countLetters(self, S: str) ->int:
ans = 0
for _, g in itertools.groupby(S):
cnt = len(list(g))
ans += (1 + cnt) * cnt // 2
return ans
| normal | {
"blob_id": "f9cee552dde5ecf229fda559122b4b0e780c3b88",
"index": 7350,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n",
"step-3": "class Solution:\n\n def countLetters(self, S: str) ->int:\n ans = 0\n for _, g in itertools.groupby(S):\n cnt = len(list(g... | [
0,
1,
2
] |
# import adafruit_ads1x15 as adс
# from adafruit_ads1x15 import ads1x15 as adc
# from adafruit_ads1x15 import analog_in
import time
import busio
import board
from adafruit_ads1x15 import ads1015 as ADS
from adafruit_ads1x15.analog_in import AnalogIn
i2c = busio.I2C(board.SCL, board.SDA)
ads = ADS.ADS1015(i2c... | normal | {
"blob_id": "388904b6b826a1c718b85f2951a3189bb5abea2a",
"index": 9755,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('{:>5}\\t{:>5}'.format('raw', 'v'))\nwhile True:\n print('{:>5}\\t{:>5.3f}'.format(chan.value, chan.voltage))\n time.sleep(0.5)\n",
"step-3": "<mask token>\ni2c = busio.I2C(... | [
0,
1,
2,
3,
4
] |
from .net import *
| normal | {
"blob_id": "73337246bd54df53842360510148f3a6f4763ace",
"index": 6251,
"step-1": "<mask token>\n",
"step-2": "from .net import *\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
#!/usr/bin/env python
from setuptools import setup
import NagAconda
setup(name=NagAconda.__name__,
version=NagAconda.__version__,
description="NagAconda is a Python Nagios wrapper.",
long_description=open('README').read(),
author='Steven Schlegel',
author_email='steven@schlegel.tech',
... | normal | {
"blob_id": "c3719f30bcf13061134b34b0925dfa2af4535f14",
"index": 7854,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsetup(name=NagAconda.__name__, version=NagAconda.__version__, description=\n 'NagAconda is a Python Nagios wrapper.', long_description=open('README'\n ).read(), author='Steven Schle... | [
0,
1,
2,
3
] |
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