code stringlengths 13 1.2M | order_type stringclasses 1
value | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
from mcpi.minecraft import Minecraft
from time import sleep
import random
mc = Minecraft.create()
myID=mc.getPlayerEntityId("Baymax1112")
mineral = [14,15,16,56,73,129,57]
while True:
sleep(0.5)
r=random.choice(mineral)
x,y,z = mc.entity.getTilePos(myID)
mc.setBlocks(x+1,y+3,z+1,x-1,y-3,z-1,r) | normal | {
"blob_id": "b28ae19f31ae746f901dea645dfeaa211a15cd31",
"index": 1879,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile True:\n sleep(0.5)\n r = random.choice(mineral)\n x, y, z = mc.entity.getTilePos(myID)\n mc.setBlocks(x + 1, y + 3, z + 1, x - 1, y - 3, z - 1, r)\n",
"step-3": "<mask... | [
0,
1,
2,
3,
4
] |
"""
Compare 1-D analytical sphere solution to 1-D numerical and 3-D Comsol solutions
for transient heat conduction in solid sphere with constant k and Cp.
Assumptions:
Convection boundary condition at surface.
Symmetry about the center of the solid.
Heat transfer via radiation assumed to be negligable.
Particle does n... | normal | {
"blob_id": "15ca54aff4c688733c9c514ba5856e6bf29a3292",
"index": 8345,
"step-1": "<mask token>\n\n\ndef despine():\n ax = py.gca()\n ax.spines['top'].set_visible(False)\n ax.spines['right'].set_visible(False)\n py.tick_params(axis='both', bottom='off', top='off', left='off', right=\n 'off')\n\... | [
1,
2,
3,
4,
5
] |
import numpy as np
from sklearn.naive_bayes import BernoulliNB
X = np.array([[1, 2, 3, 3], [1, 3, 4, 4], [2, 4, 5, 5]])
y = np.array([1, 2, 3])
"""
alpha: 平滑系数
binarize: 将特征二值化的阈值
fit_prior： 使用数据拟合先验概率
"""
clf = BernoulliNB(alpha=2.0, binarize=3.0, fit_prior=True)
clf.fit(X, y)
print("class_prior:", clf.class_prior)
... | normal | {
"blob_id": "98a1fab8cee91f37ceee2cfd868d3a5756a055b0",
"index": 7628,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nclf.fit(X, y)\nprint('class_prior:', clf.class_prior)\nprint('class_count_:', clf.class_count_)\nprint('class_log_prior_:', clf.class_log_prior_)\nprint('feature_count_:', clf.feature_cou... | [
0,
1,
2,
3,
4
] |
from flask import logging
from flask_sqlalchemy import SQLAlchemy
from passlib.apps import custom_app_context as pwd_context
logger = logging.getLogger(__name__)
db = SQLAlchemy() # flask-sqlalchemy
class User(db.Model):
__tablename__ = 'users'
id = db.Column(db.Integer, primary_key=True)
username = db... | normal | {
"blob_id": "e976f7e423d75f7fc8a3d5cd597bdd9358ae317e",
"index": 5243,
"step-1": "<mask token>\n\n\nclass User(db.Model):\n __tablename__ = 'users'\n id = db.Column(db.Integer, primary_key=True)\n username = db.Column(db.String(32), index=True)\n password_hash = db.Column(db.String(128))\n\n def h... | [
11,
13,
15,
16,
17
] |
list_1 = ['color','white','black']#taking the colors of t-shirts as input
list_2 = ['short','medium','large','xl']#taking sizes of t-shirts as input
for color in list_1:
for size in list_2:
#using cartesien product asking to give output as the combinations of color and size of t-shirts we ... | normal | {
"blob_id": "6cba431650ee8b74baa8310c144321b2e587155e",
"index": 2163,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor color in list_1:\n for size in list_2:\n print(color, size)\n<mask token>\nlist_3.reverse()\nprint(list_3)\n",
"step-3": "list_1 = ['color', 'white', 'black']\nlist_2 = ['... | [
0,
1,
2,
3
] |
import sys
sys.path.insert(0, ".") | normal | {
"blob_id": "b95eadd60093d5235dc0989205edff54ef611215",
"index": 2399,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsys.path.insert(0, '.')\n",
"step-3": "import sys\nsys.path.insert(0, '.')\n",
"step-4": "\nimport sys\n\nsys.path.insert(0, \".\")",
"step-5": null,
"step-ids": [
0,
1,
... | [
0,
1,
2,
3
] |
import RPi.GPIO as GPIO
import numpy as np
import array
import time
import json
import LED_GPIO as led
import BUTTON_GPIO as btn
import parseJson as gjs
rndBtnState = False
interval = .1
rndbtn = gjs.getJsonRnd()
gpioValues = gjs.getJsonData()
strArray = gpioValues[0]
btnArray = gpioValues[1]
ledArray = gpioValue... | normal | {
"blob_id": "1b741b34649193b64479724670244d258cfbbdfc",
"index": 5055,
"step-1": "import RPi.GPIO as GPIO\nimport numpy as np\nimport array\nimport time\nimport json\n\nimport LED_GPIO as led \nimport BUTTON_GPIO as btn\nimport parseJson as gjs\n\nrndBtnState = False\ninterval = .1\n\nrndbtn = gjs.getJsonRnd()\n... | [
0
] |
from django.shortcuts import render
from rest_framework import status, viewsets , response
from . import models
from . import serializers
# Create your views here.
class TodoViewset(viewsets.ModelViewSet):
queryset = models.Todo.objects.all()
serializer_class = serializers.TodoSerializer
| normal | {
"blob_id": "1c668cf6f145b85a09b248fefda46e928de64e41",
"index": 5041,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass TodoViewset(viewsets.ModelViewSet):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass TodoViewset(viewsets.ModelViewSet):\n queryset = models.Todo.... | [
0,
1,
2,
3,
4
] |
"""Admin module for Django."""
from django.contrib import admin
from django.utils.translation import gettext_lazy as _
from django_q.conf import Conf, croniter
from django_q.models import Failure, OrmQ, Schedule, Success
from django_q.tasks import async_task
class TaskAdmin(admin.ModelAdmin):
"""model admin for ... | normal | {
"blob_id": "5aebebb7f22e094a1a897b3266ff07d59400b76c",
"index": 2209,
"step-1": "<mask token>\n\n\nclass ScheduleAdmin(admin.ModelAdmin):\n \"\"\"model admin for schedules\"\"\"\n list_display = ('id', 'name', 'func', 'schedule_type', 'repeats',\n 'cluster', 'next_run', 'last_run', 'success')\n ... | [
10,
21,
22,
23,
26
] |
import tensorflow.contrib.slim as slim
import tensorflow as tf
from tensorflow.python.framework import dtypes
from tensorflow.python.ops import random_ops
from tensorflow.python.ops import init_ops
import numpy as np
WEIGHT_DECAY = 0.0005
class ScaledVarianceUniform(init_ops.Initializer):
"""Initializer that genera... | normal | {
"blob_id": "9da6bfa614d64956a302abbfeeea30c0339e9db3",
"index": 5583,
"step-1": "<mask token>\n\n\nclass ConvLayer(object):\n <mask token>\n\n def apply(self, h):\n if self.activation_fn == False:\n if self.normalizer_fn == False:\n if self.dropout == False:\n ... | [
19,
21,
23,
33,
35
] |
#OpenCV create samples commands
#opencv_createsamples -img watch5050.jpg -bg bg.txt -info info/info.lst -pngoutput info -maxxangle 0.5 -maxyangle 0.5 -maxzangle 0.5 -num 1950
#opencv_createsamples -info info/info.lst -num 1950 -w 20 -h 20 -vec positives.vec
#Training command
#opencv_traincascade -data data -vec p... | normal | {
"blob_id": "62e0c3b6095a65a4508eddfa9c0a1cb31d6c917b",
"index": 8887,
"step-1": "#OpenCV create samples commands\r\n#opencv_createsamples -img watch5050.jpg -bg bg.txt -info info/info.lst -pngoutput info -maxxangle 0.5 -maxyangle 0.5 -maxzangle 0.5 -num 1950\r\n#opencv_createsamples -info info/info.lst -num 195... | [
1
] |
# 作者：西岛闲鱼
# https://github.com/globien/easy-python
# https://gitee.com/globien/easy-python
# 用蒙特卡洛法计算圆周率，即，往一个正方形里扔豆子，计算有多少比例的豆子扔在了该正方形的内切圆中
import random
num_all = 0 #随机点总计数器
num_cir = 0 #随机点在圆内的计数器
num_halt = 10000000 #每产生这么多个随机点后，计算并打印一次目前的结果
print("将进行无限计算，请用Ctrl_C或其他方式强制退出！！！")
input("按回车(Enter... | normal | {
"blob_id": "5d9afef2a748782659b82b329ea08d5815162cbc",
"index": 3744,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('将进行无限计算，请用Ctrl_C或其他方式强制退出！！！')\ninput('按回车(Enter)键开始...')\nprint('开始计算...，退出请用Ctrl_C或其他强制退出方式...')\nprint(\"\"\"\n实验次数 计算结果\"\"\")\nwhile 1:\n for i in range(num_halt):\n... | [
0,
1,
2,
3,
4
] |
def addnumber(i,j):
sum= i+j
print(sum)
num1 = int(input("Enter 1st number"))
num2 = int(input("Enter 2nd number"))
z = addnumber(num1,num2)
| normal | {
"blob_id": "2350c2ab05499f1b40ba61f2101c51d9581d57f6",
"index": 8668,
"step-1": "<mask token>\n",
"step-2": "def addnumber(i, j):\n sum = i + j\n print(sum)\n\n\n<mask token>\n",
"step-3": "def addnumber(i, j):\n sum = i + j\n print(sum)\n\n\nnum1 = int(input('Enter 1st number'))\nnum2 = int(inp... | [
0,
1,
2,
3
] |
'''
Binary_to_C
Converts any binary data to an array of 'char' type to be used inside of a C program.
The reason to want to do that, is to emulate a 'Windows Resource System' on Linux.
Linux does not allow inclusion of binary data in application (I am OK with that, I like that actually).
Windows, however, does. On... | normal | {
"blob_id": "c9f29a92ec8627593b54f7d9569dcfd589fa7fff",
"index": 5811,
"step-1": "'''\nBinary_to_C\n\tConverts any binary data to an array of 'char' type to be used inside of a C program.\n\tThe reason to want to do that, is to emulate a 'Windows Resource System' on Linux.\n\tLinux does not allow inclusion of bi... | [
0
] |
import os
import json
from .utils import *
def _unique_predict(solve_list):
valid_solve_list = filter(lambda x: x[0] is not None, solve_list)
valid_solve_list = sorted(valid_solve_list, key=lambda x: x[0])
unique_solve_list = list()
current_no = -1
for e in valid_solve_list:
if current_no ... | normal | {
"blob_id": "00a1b5f20f15994a659eda56201ba7c45d49a4db",
"index": 4186,
"step-1": "<mask token>\n\n\ndef _unique_predict(solve_list):\n valid_solve_list = filter(lambda x: x[0] is not None, solve_list)\n valid_solve_list = sorted(valid_solve_list, key=lambda x: x[0])\n unique_solve_list = list()\n cur... | [
3,
4,
5,
6,
7
] |
# coding: utf-8
from pyquery import PyQuery as pq
html = '''
<div id="container">
<ul class="list">
<li class="item-0">first item</li>
<li class="item-1"><a href="link2.html">second item</a></li>
<li class="item-0 active"><a href="link3.html">third item</a></li>
... | normal | {
"blob_id": "02ab822dacb26d623a474fa45ebb034f9c1291b8",
"index": 1604,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(a, type(a))\nprint(a.attr('href'))\nprint(a.attr.href)\n",
"step-3": "<mask token>\nhtml = \"\"\"\n <div id=\"container\">\n <ul class=\"list\">\n <li class=\... | [
0,
1,
2,
3,
4
] |
import sys, os
def carp():
sys.stderr = sys.stdin
print "content-type: text/plain"
print
#carp()
import sesspool
import cornerhost.config
## set up session
pool = sesspool.SessPool("sess/sessions.db")
SESS = sesspool.Sess(pool, REQ, RES)
SESS.start()
ENG.do_on_exit(SESS.stop)
CLERK = cornerhost.config... | normal | {
"blob_id": "adae1d7cc2a866c9bc3cd21cb54a0191389f8083",
"index": 3914,
"step-1": "import sys, os\ndef carp():\n sys.stderr = sys.stdin\n print \"content-type: text/plain\"\n print \n#carp()\n\nimport sesspool\nimport cornerhost.config\n\n\n## set up session\npool = sesspool.SessPool(\"sess/sessions.db\"... | [
0
] |
import pymysql
pymysql.install_as_MySQLdb()
# from keras.models import load_model
# from keras.models import Model
# from ai import settings
#
# print('load model ...')
# model = load_model(settings.MODEL_PATH)
# model = Model(inputs=model.input, outputs=model.get_layer('dnsthree').output)
# print('load done.')
| normal | {
"blob_id": "b7d3af29e024b0b2cf5d2c054290f799eae7fed1",
"index": 4476,
"step-1": "<mask token>\n",
"step-2": "<mask token>\npymysql.install_as_MySQLdb()\n",
"step-3": "import pymysql\npymysql.install_as_MySQLdb()\n",
"step-4": "import pymysql\n\npymysql.install_as_MySQLdb()\n\n# from keras.models import lo... | [
0,
1,
2,
3
] |
from django.conf import settings
from django.db import migrations, models
import django_otp.plugins.otp_totp.models
class Migration(migrations.Migration):
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
]
operations = [
migrations.CreateModel(
nam... | normal | {
"blob_id": "2e448176a755828e5c7c90e4224102a285098460",
"index": 4852,
"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 = [migrations.sw... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
from odoo import models, fields, api
class ResPartner(models.Model):
_inherit = 'res.partner'
purchase_type = fields.Many2one('purchase.order.type', string='Purchase Order Type')
| normal | {
"blob_id": "f26b127b4d968c1a168a57825a5acfffbf027bef",
"index": 3372,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass ResPartner(models.Model):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass ResPartner(models.Model):\n _inherit = 'res.partner'\n purchase_type... | [
0,
1,
2,
3,
4
] |
207. Course Schedule
Some courses may have prerequisites, for example to take course 0 you have to first take course 1,
which is expressed as a pair: [0,1]
Given the total number of courses and a list of prerequisite pairs, is it possible for you to finish all courses?
For example:
2, [[1,0]]
There are a total of... | normal | {
"blob_id": "34aa08b9a5a89d3fca129271a9e812e2382ca88e",
"index": 4196,
"step-1": "207. Course Schedule \n\nSome courses may have prerequisites, for example to take course 0 you have to first take course 1, \nwhich is expressed as a pair: [0,1]\n\nGiven the total number of courses and a list of prerequisite pairs... | [
0
] |
# created by ahmad on 17-07-2019
# last updated on 21-07-2019
#recommended font size of console in pydroid is 12
from decimal import Decimal
def fromTen():
global fin
fin = num
nnum = num
base = base2
if count == 1:
nnum = sum(milst) + sum(mdlst)
Ipart = int(nnum)
Dpart = Dec... | normal | {
"blob_id": "9cf32e127664cb4c3290e665e35245acc936e064",
"index": 4090,
"step-1": "<mask token>\n\n\ndef fromTen():\n global fin\n fin = num\n nnum = num\n base = base2\n if count == 1:\n nnum = sum(milst) + sum(mdlst)\n Ipart = int(nnum)\n Dpart = Decimal(nnum - Ipart)\n strDpart =... | [
3,
5,
6,
7,
8
] |
# -*- coding: utf-8 -*-
# Define your item pipelines here
#
# Don't forget to add your pipeline to the ITEM_PIPELINES setting
# See: http://doc.scrapy.org/en/latest/topics/item-pipeline.html
from sqlalchemy import create_engine, MetaData, Table
class DoubanPipeline(object):
conn = None
film_table = None
... | normal | {
"blob_id": "5ef6b2ff89ee1667ddb01b1936557f1f11a49910",
"index": 4673,
"step-1": "# -*- coding: utf-8 -*-\n\n# Define your item pipelines here\n#\n# Don't forget to add your pipeline to the ITEM_PIPELINES setting\n# See: http://doc.scrapy.org/en/latest/topics/item-pipeline.html\nfrom sqlalchemy import create_eng... | [
0
] |
#Diagonal Traverse
#Given a matrix of M x N elements (M rows, N columns), return all elements of the matrix in diagonal
order as shown in the below image.
#Example:
#Input:
#[
# [ 1, 2, 3 ],
# [ 4, 5, 6 ],
# [ 7, 8, 9 ]
#]
#Output: [1,2,4,7,5,3,6,8,9]
#Explanation:
#Note:
# The total number of elements of the given... | normal | {
"blob_id": "0a5ea7ad0ee34c8a3f0299908c61fa0a09139d2f",
"index": 8558,
"step-1": "#Diagonal Traverse\n#Given a matrix of M x N elements (M rows, N columns), return all elements of the matrix in diagonal\norder as shown in the below image.\n#Example:\n#Input:\n#[\n# [ 1, 2, 3 ],\n# [ 4, 5, 6 ],\n# [ 7, 8, 9 ]\n#]... | [
0
] |
# https://www.acmicpc.net/problem/2751
# n 개 수가 주어짐
# 목표 오름차순정렬
# 첫 줄 n개
# 둘째줄부터 n개의 줄에 수가 주어짐 세로로
# 출력 오름차순 정렬한 결과를 한 줄에 하나씩 출력한다?
n=int(input())
n_list=[int(input()) for _ in range(n)]
# print(n_list)
nn_list = []
# 인덱스 2개 관리
mid_idx = len(n_list) //2
left_idx = 0
right_idx = mid_idx +1
while left_idx <= mid... | normal | {
"blob_id": "fb5508b1b5aa36c4921358d6ca7f96fc7d565241",
"index": 5104,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile left_idx <= mid_idx and right_idx <= n - 1:\n if n_list[left_idx] < n_list[right_idx]:\n nn_list.append(n_list[left_idx])\n left_idx += 1\n elif n_list[left_idx]... | [
0,
1,
2,
3
] |
import unittest
"""
Find the largest 0 to 9 pandigital that can be formed by concatenating products
Take the number 6 and multiply it by each of 1273 and 9854:
6 × 1273 = 7638
6 × 9854 = 59124
By concatenating these products we get the 1 to 9 pandigital 763859124. We will call 763859124 the "concatenated product of ... | normal | {
"blob_id": "cb08b95e3b9c80fb74d4415b3798ddbb36cd76e7",
"index": 419,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Test(unittest.TestCase):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Test(unittest.TestCase):\n\n def test(self):\n pass\n",
"step-4": "import unittest... | [
0,
1,
2,
3,
4
] |
# Generated by Django 3.1.7 on 2021-03-19 14:38
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
('news', '0002_auto_202103... | normal | {
"blob_id": "8b4bc312bf4b64f98c4f84f4bf89984291be0428",
"index": 6033,
"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 = [migrations.sw... | [
0,
1,
2,
3,
4
] |
#Program to create and store Employee Salary Records in a file
import os
def appendEmployee(eno,name,basic):
fh=open("Employee.txt","a")
hra=basic*0.10
da=basic*0.73
gross=basic+hra+da
tax=gross*0.3
net=gross-tax
line=str(eno)+","+name+","+str(basic)+","+str(hra)+","+str(da)+","+str(gross)+","+str(tax)+","+str... | normal | {
"blob_id": "5b6241907cc97f82d6c6e0a461f4f71a9a567204",
"index": 5395,
"step-1": "<mask token>\n\n\ndef displayEmployees():\n fh = open('Employee.txt', 'r')\n for line in fh:\n emp = line.split(',')\n print('\\nEmployee No:', emp[0], '\\nEmployee Name:', emp[1],\n '\\nBasic:', emp[... | [
3,
5,
6,
7,
8
] |
from __future__ import with_statement
from fabric.api import *
from fabric.colors import *
from fabric.utils import puts
from fabric.context_managers import shell_env
env.hosts = ['git@tweetset.com']
def deploy():
"deploys the project to the server"
with prefix('source /srv/django-envs/tweetset/bin/activate')... | normal | {
"blob_id": "6111c9730c556ab3ab95f7685ffa135a2bbeb2ca",
"index": 5950,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef deploy():\n \"\"\"deploys the project to the server\"\"\"\n with prefix('source /srv/django-envs/tweetset/bin/activate'):\n with shell_env(DJANGO_SETTINGS_MODULE='twe... | [
0,
1,
2,
3,
4
] |
'''
Note: a TimeOutException appear when distance even 0.
'''
import smbus
import time
#slave arduino address
address_arduino = 0x04
bus = smbus.SMBus(1)
#get a measure by i2c
def getUSMeasure():
bus.write_byte(address_arduino, 1)
distance = bus.read_byte(address_arduino)
return distance
#request rotate... | normal | {
"blob_id": "6fa7aef7c2b91de409a0e8574e362efefa642ee7",
"index": 1715,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef getUSMeasure():\n bus.write_byte(address_arduino, 1)\n distance = bus.read_byte(address_arduino)\n return distance\n\n\ndef forward():\n bus.write_byte(address_arduino... | [
0,
2,
3,
6,
7
] |
#! /usr/bin/env python
# -*- conding:utf-8 -*-
import MySQLdb
import os
import commands
from common import logger_init
from logging import getLogger
import re
from db import VlanInfo,Session,WafBridge
def getVlan(): # get vlan data from t_vlan
session=Session()
vlanport=[]
for info in session.query(VlanIn... | normal | {
"blob_id": "cd564ebb51cf91993d2ed1810707aead44c19a6b",
"index": 6959,
"step-1": "<mask token>\n\n\ndef getVlan():\n session = Session()\n vlanport = []\n for info in session.query(VlanInfo):\n a = []\n a.append(info.nets)\n a.append(info.vlan_id)\n vlanport.append(a)\n in... | [
3,
4,
5,
6,
7
] |
import abc
try:
import cPickle as pickle
except ImportError:
import pickle
from typing import *
T = TypeVar('T')
class BaseSerializer(Generic[T]):
"""
The serializer is responsible for converting complex python data types
into primitive types that can be sent over zmq ports via msgpack.
""... | normal | {
"blob_id": "94f5fa411f8a41985caaf4eb7ab1cb4e45439405",
"index": 1524,
"step-1": "<mask token>\n\n\n@MultiSerializer.register(lambda x: True)\nclass PickleSerializer(BaseSerializer):\n <mask token>\n <mask token>\n <mask token>\n\n def deserialize(self, data):\n return pickle.loads(data)\n\n\n... | [
18,
26,
32,
33,
37
] |
def ex7(*siruri, x=1, flag=True):
res = ()
for sir in siruri:
chars = []
for char in sir:
if ord(char) % x == (not flag):
chars.append(char)
res += (chars,)
return res
print(ex7("test", "hello", "lab002", x=2, flag=False))
| normal | {
"blob_id": "90a402cccf383ed6a12b70ecdc3de623e6e223f9",
"index": 8365,
"step-1": "<mask token>\n",
"step-2": "def ex7(*siruri, x=1, flag=True):\n res = ()\n for sir in siruri:\n chars = []\n for char in sir:\n if ord(char) % x == (not flag):\n chars.append(char)\n ... | [
0,
1,
2,
3
] |
#coding: utf8
import sqlite3
from random import shuffle
import argparse
def wordCount(db):
words = {}
for sent, labels in iterReviews(db):
for word in sent:
if word not in words:
words[word] = 1
else:
words[word] += 1
return words
def filt... | normal | {
"blob_id": "04867e8911f7cb30af6cefb7ba7ff34d02a07891",
"index": 7970,
"step-1": "<mask token>\n\n\ndef wordCount(db):\n words = {}\n for sent, labels in iterReviews(db):\n for word in sent:\n if word not in words:\n words[word] = 1\n else:\n words... | [
3,
5,
6,
7,
8
] |
'''
Sample Input
1
5
1 2 3 2 1
Sample Output
3
'''
for _ in range(int(input())):
noe = int(input())
arr = [int(x) for x in input().split()]
left = arr[0]
rite = sum(arr) - left
mins = abs(rite - left)
for i in range(1, noe-1):
left += arr[i]
rite -= arr[i]
print(left, rit... | normal | {
"blob_id": "825f3b930fee319314d520a32c2f9dcd718505ab",
"index": 2424,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor _ in range(int(input())):\n noe = int(input())\n arr = [int(x) for x in input().split()]\n left = arr[0]\n rite = sum(arr) - left\n mins = abs(rite - left)\n for i i... | [
0,
1,
2
] |
You are given a 2 x N board, and instructed to completely cover the board with
the following shapes:
Dominoes, or 2 x 1 rectangles.
Trominoes, or L-shapes.
For example, if N = 4, here is one possible configuration, where A is
a domino, and B and C are trominoes.
A B B C
A B C C
Given an in... | normal | {
"blob_id": "834fa5d006188da7e0378246c1a019da6fa413d2",
"index": 4882,
"step-1": "You are given a 2 x N board, and instructed to completely cover the board with\nthe following shapes:\n\n Dominoes, or 2 x 1 rectangles.\n Trominoes, or L-shapes.\n For example, if N = 4, here is one possible configuration... | [
0
] |
import sys
sys.path.append('../')
from IntcodeComputer.intcode import Program
if __name__ == '__main__':
fn = 'input.txt'
with open(fn) as f:
program = Program([int(i) for i in f.readline().split(',')])
program.run()
result = program.instructions
| normal | {
"blob_id": "a54c8ab63c1e0f50d254d6c97ca3f167db7142e9",
"index": 4956,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsys.path.append('../')\n<mask token>\nif __name__ == '__main__':\n fn = 'input.txt'\n with open(fn) as f:\n program = Program([int(i) for i in f.readline().split(',')])\n ... | [
0,
1,
2
] |
from django.contrib.staticfiles.storage import CachedFilesMixin
from storages.backends.s3boto3 import S3Boto3Storage
class CachedS3Storage(CachedFilesMixin, S3Boto3Storage):
pass
StaticRootS3BotoStorage = lambda : CachedS3Storage(location='static')
MediaRootS3BotoStorage = lambda : S3Boto3Storage(location='medi... | normal | {
"blob_id": "e99ff1c75d5108efc8d587d4533c34eeb15c6978",
"index": 9425,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass CachedS3Storage(CachedFilesMixin, S3Boto3Storage):\n pass\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\nclass CachedS3Storage(CachedFilesMixin, S3Boto3Storage):\n p... | [
0,
1,
2,
3
] |
import retro # pip install gym-retro
import numpy as np # pip install numpy
#import cv2 # pip install opencv-python
import neat # pip install neat-python
import pickle # pip install cloudpickle
import os
import multiprocessing
import cv2
import time
env = retro.make(game='Pong-... | normal | {
"blob_id": "36e350e0d578e169efaafb9e311566d71d6bc59e",
"index": 1438,
"step-1": "<mask token>\n\n\ndef eval_genome(genome, config):\n net = neat.nn.FeedForwardNetwork.create(genome, config)\n env.reset()\n ob, _, _, _ = env.step(env.action_space.sample())\n inx = int(ob.shape[0] / 8)\n iny = int(... | [
3,
4,
5,
6,
7
] |
# Generated by Django 3.2.9 on 2021-11-10 13:36
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('settings', '0003_auto_20210814_2246'),
]
operations = [
migrations.AlterField(
model_name='building',
name='id',
... | normal | {
"blob_id": "9dfbf14a2005aad87be82e5e482c6b0347f32f2c",
"index": 8007,
"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 = [('settings', ... | [
0,
1,
2,
3,
4
] |
from collections import defaultdict
def solution(tickets):
# 출발지가 키, 목적지가 value 인 딕셔너리 생성
routes = defaultdict(list)
for t in tickets:
routes[t[0]].append(t[1])
# 알파벳 빠른순으로 정렬해야함으로 reverse=True
for r in routes:
routes[r].sort(reverse=True)
# 시작 위치 ICN
stack = ['ICN']
... | normal | {
"blob_id": "15c6841052882406d7c7b6cd05c0186c6a4a5924",
"index": 2021,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef solution(tickets):\n routes = defaultdict(list)\n for t in tickets:\n routes[t[0]].append(t[1])\n for r in routes:\n routes[r].sort(reverse=True)\n stack... | [
0,
1,
2,
3,
4
] |
"""
Convert file containing histograms into the response function
"""
import h5py
import wx
import numpy as np
import matplotlib.pyplot as plt
#############################################################################
# Select the file cantoning histograms,
# which will be converted to response function
app = wx.A... | normal | {
"blob_id": "c4898f3298c2febed476f99fe08bc5386527a47e",
"index": 9344,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif openFileDialog.ShowModal() == wx.ID_CANCEL:\n raise ValueError('HDF5 file is not selected')\n<mask token>\ndel app\nwith h5py.File(hist_filename, 'r') as F:\n for histogram in F[... | [
0,
1,
2,
3,
4
] |
from .start_node import StartNode
from .character_appearance import CharacterAppearance
from .character_disappearance import CharacterDisappearance
from .replica import Replica
from .end_node import EndNode
from .choice import Choice
from .set_landscape import SetLandscape
from .add_item import AddItem
from .switch_by_... | normal | {
"blob_id": "cd6e15daa2360ead47f0bac95843b1c030164996",
"index": 6879,
"step-1": "<mask token>\n",
"step-2": "from .start_node import StartNode\nfrom .character_appearance import CharacterAppearance\nfrom .character_disappearance import CharacterDisappearance\nfrom .replica import Replica\nfrom .end_node impor... | [
0,
1
] |
from torch.utils.data import IterableDataset, DataLoader
from torch import nn
from torch.nn import functional as F
from triplet_training_generator import get_train_test_apikeys, training_generator
from pathlib import Path
from transformers import AutoModel
import torch
from tqdm import tqdm
import pandas as pd
MEMMAP_... | normal | {
"blob_id": "650f00dd9740d62546eb58724e6e5a74398b3e59",
"index": 2522,
"step-1": "<mask token>\n\n\nclass DataGenerator(IterableDataset):\n <mask token>\n <mask token>\n\n\nclass CrossEncoderModel(torch.nn.Module):\n\n def __init__(self):\n super(CrossEncoderModel, self).__init__()\n self.... | [
4,
7,
9,
10,
11
] |
#!/usr/bin/env python3
# Licensed under the Apache License, Version 2.0 or the MIT License.
# SPDX-License-Identifier: Apache-2.0 OR MIT
# Copyright Tock Contributors 2023.
# Prints out the source locations of panics in a Tock kernel ELF
#
# This tool attempts to trace all panic locations in a Tock kernel ELF by
# tr... | normal | {
"blob_id": "8c0a4d5a86d9ebd38ea05efb5b5b570368ce1449",
"index": 1336,
"step-1": "<mask token>\n\n\ndef matches_panic_funcs(name):\n \"\"\"If the passed name contains one of the known panic_functions,\n return the match\n \"\"\"\n for func in panic_functions:\n if func in name:\n re... | [
7,
10,
11,
12,
13
] |
from gymnasium.spaces import Box, Discrete
import numpy as np
from typing import Optional, TYPE_CHECKING, Union
from ray.rllib.env.base_env import BaseEnv
from ray.rllib.models.action_dist import ActionDistribution
from ray.rllib.models.modelv2 import ModelV2
from ray.rllib.models.tf.tf_action_dist import Categorical,... | normal | {
"blob_id": "b2b47b394eadebda5c51e89abd27832f9dbd4c8c",
"index": 4193,
"step-1": "<mask token>\n\n\n@PublicAPI\nclass ParameterNoise(Exploration):\n <mask token>\n\n def __init__(self, action_space, *, framework: str, policy_config: dict,\n model: ModelV2, initial_stddev: float=1.0, random_timesteps... | [
16,
17,
20,
21,
22
] |
from django.urls import path
from .views import PasswordList
urlpatterns = [
path('', PasswordList.as_view()),
]
| normal | {
"blob_id": "0f3430cbfc928d26dc443fde518881923861f2e3",
"index": 3188,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('', PasswordList.as_view())]\n",
"step-3": "from django.urls import path\nfrom .views import PasswordList\nurlpatterns = [path('', PasswordList.as_view())]\n",
"st... | [
0,
1,
2,
3
] |
# --------------------------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for license information.
#
# Code generated by aaz-dev-tools
# --------------------------------... | normal | {
"blob_id": "8197d918b86f0e38fb4320434b61aa4186853af9",
"index": 1131,
"step-1": "<mask token>\n\n\n@register_command('sig gallery-application version show')\nclass Show(AAZCommand):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n ... | [
5,
8,
9,
10,
16
] |
"""Base class for an array of annotated genomic regions."""
import logging
from typing import Callable, Dict, Iterable, Iterator, Mapping, Optional, Sequence, Union
from collections import OrderedDict
import numpy as np
import pandas as pd
from .chromsort import sorter_chrom
from .intersect import by_ranges, into_ran... | normal | {
"blob_id": "0b833276ca10118f2d60e229ff03400b03915958",
"index": 2429,
"step-1": "<mask token>\n\n\nclass GenomicArray:\n <mask token>\n <mask token>\n <mask token>\n\n def __init__(self, data_table: Optional[Union[Sequence, pd.DataFrame]],\n meta_dict: Optional[Mapping]=None):\n if dat... | [
36,
38,
48,
49,
55
] |
# coding: utf-8
# In[50]:
## Description
## Adds the Fibonacci numbers smaller than 4 million
## Weekly Journal
## When using while True, "break" MUST be used to avoid infinite loops
## Questions
## None
fib=[1,2]
counter=1
while True:
if fib[counter]>4000000:
flag=0
break
else:
f... | normal | {
"blob_id": "e2572b48f7183353ba2aab0500130dc8a71a0b22",
"index": 5286,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile True:\n if fib[counter] > 4000000:\n flag = 0\n break\n else:\n fib.append(fib[counter] + fib[counter - 1])\n counter += 1\n<mask token>\nprint(tot... | [
0,
1,
2,
3
] |
import pandas as pd
import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['SimHei']
def get_ratings(file_path):
# 图书的ISBN中可能包含字符，所以在使用pandas读取文件时，需要指定编码
ratings = pd.read_table(file_path, header=0,
sep=';', encoding='ISO-8859-1')
print('前5条数据：\n{}\n'.format(rating... | normal | {
"blob_id": "be5178f013e639d5179ed1af380dd7a63044bff2",
"index": 5636,
"step-1": "<mask token>\n\n\ndef get_ratings(file_path):\n ratings = pd.read_table(file_path, header=0, sep=';', encoding='ISO-8859-1'\n )\n print('前5条数据：\\n{}\\n'.format(ratings.head(5)))\n print('总的数据条数：\\n{}\\n'.format(rati... | [
1,
2,
3,
4,
5
] |
from introduction import give_speech
from staring import stare_at_people
from dow_jones import visualize_dow_jones
from art_critic import give_art_critiques
from hipster import try_hipster_social_interaction
from empathy import share_feelings_with_everyone
from slapstick import perform_slapstick_humor
from ending impor... | normal | {
"blob_id": "d218b72d1992a30ad07a1edca1caf04b7b1985f6",
"index": 7834,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef performance():\n give_speech()\n visualize_dow_jones()\n give_art_critiques()\n stare_at_people()\n try_hipster_social_interaction()\n share_feelings_with_everyo... | [
0,
1,
2,
3
] |
import smtplib
from email.mime.text import MIMEText
from email.mime.multipart import MIMEMultipart
import base64
import configobj
import datetime
import os
config = configobj.ConfigObj('.env')
port = 2525
smtp_server = "smtp.mailtrap.io"
login = config['SMTP_USERNAME']
password = config['SMTP_PASSWORD']
sender_email... | normal | {
"blob_id": "a21ac29911931bb71460175cba584e0011fa2ece",
"index": 1055,
"step-1": "<mask token>\n\n\ndef send():\n global last_index_sent\n global last_sent\n DIR = './videos'\n videosToSend = len([name for name in os.listdir(DIR) if os.path.isfile(\n os.path.join(DIR, name))])\n for i in ra... | [
1,
2,
3,
4,
5
] |
from django.shortcuts import render
# Create your views here.
def test_petite_vue(request):
return render(request, 'petite_vue_app/test-form.html')
| normal | {
"blob_id": "709f2425bc6e0b0b650fd6c657df6d85cfbd05fe",
"index": 84,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef test_petite_vue(request):\n return render(request, 'petite_vue_app/test-form.html')\n",
"step-3": "from django.shortcuts import render\n\n\ndef test_petite_vue(request):\n r... | [
0,
1,
2,
3
] |
from django.db import models
from django.contrib.auth.models import User
from django.core.validators import MaxValueValidator, MinValueValidator
class Person(models.Model):
user = models.OneToOneField(User, on_delete=models.CASCADE, related_name='person')
age = models.PositiveSmallIntegerField()
bio = mode... | normal | {
"blob_id": "6de9fffd91d2f7602f7c681253211077704ba8c4",
"index": 2039,
"step-1": "<mask token>\n\n\nclass Product(models.Model):\n title = models.CharField(max_length=32)\n description = models.TextField(max_length=360)\n price = models.IntegerField()\n image = models.CharField(max_length=255, null=T... | [
6,
7,
9,
10,
12
] |
from Bio.PDB import *
import urllib.request
import numpy as np
import pandas as pd
from math import sqrt
import time
import os
import heapq
from datetime import datetime
dir_path = os.getcwd()
peptidasesList = pd.read_csv("./MCSA_EC3.4_peptidases.csv")
peptidasesList = peptidasesList[peptidasesList.iloc[:, 4] == "res... | normal | {
"blob_id": "67b1cdfa514aac4fdac3804285ec8d0aebce944d",
"index": 6068,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(len(peptidasesList))\n<mask token>\nfor i in range(len(peptidasesList)):\n if peptidasesList.loc[i, 'PDB'] not in bindingSiteDic:\n bindingSiteDic[peptidasesList.loc[i, 'P... | [
0,
1,
2,
3,
4
] |
from bs4 import BeautifulSoup
import requests
import pymongo
client = pymongo.MongoClient('localhost', 27017)
ku = client['ku']
url_list1 = ku['url_list_index']
start_url="http://news.ccsu.cn/index.htm"
url_host="http://news.ccsu.cn/"
def get_channel_urls(url):
wb_data = requests.get(url)
wb_data.encoding = 'ut... | normal | {
"blob_id": "4791b210f328dff5d48ff5afc381a98a5a1a2b7b",
"index": 1969,
"step-1": "<mask token>\n\n\ndef get_channel_urls(url):\n wb_data = requests.get(url)\n wb_data.encoding = 'utf-8'\n soup = BeautifulSoup(wb_data.text, 'lxml')\n links = soup.select('body > div.navWrap.clearfix > div > ul > li > a... | [
1,
2,
3,
4,
5
] |
# Write a program to accept a no & count number of zeros in it.(int=32bits)
def countOfZeros(num):
cnt = 0
while(num!=0):
cnt+=1
num = num&(num-1)
return (32-cnt)
def main():
num = eval(input('Enter number to count zeros in it\'s binary: '))
print('Assumung int... | normal | {
"blob_id": "7affd79fb0bb47283bbd9a7fbcaa0ba43aa8e6a6",
"index": 106,
"step-1": "<mask token>\n",
"step-2": "def countOfZeros(num):\n cnt = 0\n while num != 0:\n cnt += 1\n num = num & num - 1\n return 32 - cnt\n\n\n<mask token>\n",
"step-3": "def countOfZeros(num):\n cnt = 0\n w... | [
0,
1,
2,
3,
4
] |
# This simulation obtains dose on a cylindical disk phantom at various
# distances from a 14MeV photon source. Dose in millisieverts is found
# and compared to the yearly limit
# The model is built to have a human tissue and human height and volume which
# is typically referred to as a phantom.
# source details based... | normal | {
"blob_id": "28bf11cb4205dd186b84cc7b7c8b9009f35fe408",
"index": 7415,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nmat_tissue.add_element('O', 0.079013)\nmat_tissue.add_element('C', 0.32948)\nmat_tissue.add_element('H', 0.546359)\nmat_tissue.add_element('N', 0.008619)\nmat_tissue.add_element('Mg', 0.0... | [
0,
1,
2,
3,
4
] |
from datetime import datetime
from unittest import TestCase
from vpnmupd import versions
class TestClass01(TestCase):
"""Software dependency versions compared"""
def setUp(self) -> None:
super().setUp()
self.any_string = "Some string containing v1.1.1"
def test_case01(self):
"""... | normal | {
"blob_id": "21d2de5719fafd94605f31bc07231644f4be18c5",
"index": 8749,
"step-1": "<mask token>\n\n\nclass TestClass01(TestCase):\n <mask token>\n <mask token>\n\n def test_case01(self):\n \"\"\"Version extraction\"\"\"\n version = versions.extract_version(self.any_string)\n self.ass... | [
4,
5,
8,
9,
10
] |
import errno
import os
import shutil
from calendar import monthrange
from datetime import datetime, timedelta
from pavilion import output
from pavilion import commands
from pavilion.status_file import STATES
from pavilion.test_run import TestRun, TestRunError, TestRunNotFoundError
class CleanCommand(commands.Command... | normal | {
"blob_id": "18aafb71d7e6f5caa2f282126c31eb052c08ad3c",
"index": 4307,
"step-1": "<mask token>\n\n\nclass CleanCommand(commands.Command):\n <mask token>\n\n def __init__(self):\n super().__init__('clean', 'Clean up Pavilion working directory.',\n short_help='Clean up Pavilion working dire... | [
4,
5,
6,
7,
8
] |
# module for comparing stats and making recommendataions
"""
Read team names from user input, retrieve features of teams from MySQL DB, compute odds of winning and recommend features to care
"""
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import pymysql as mdb
def FeatureImprove(tgtName, yo... | normal | {
"blob_id": "e5f8301ae22e99c967b2ff3d791379deba7d154a",
"index": 2341,
"step-1": "# module for comparing stats and making recommendataions\n\"\"\"\nRead team names from user input, retrieve features of teams from MySQL DB, compute odds of winning and recommend features to care\n\"\"\"\n\nimport numpy as np\nimpo... | [
0
] |
def create_meme(word):
return f'this is your meme NEW VERSION {word}'
| normal | {
"blob_id": "32b3e65add5fb44320898b682e8f94f1460a32e7",
"index": 628,
"step-1": "<mask token>\n",
"step-2": "def create_meme(word):\n return f'this is your meme NEW VERSION {word}'\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
# Game Tebak Angka
from random import randint
nyawa = 3
angka_rahasia = randint(0,10)
limit = 0
print(f"Selamat datang di Game Tebak angka")
while nyawa > limit:
print(f"Percobaan anda tersisa {nyawa}")
jawaban = int(input("Masukkan angka 0-10 = "))
if jawaban == angka_rahasia:
... | normal | {
"blob_id": "d4b01b015723950a4d8c3453d736cd64f306d27b",
"index": 2940,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(f'Selamat datang di Game Tebak angka')\nwhile nyawa > limit:\n print(f'Percobaan anda tersisa {nyawa}')\n jawaban = int(input('Masukkan angka 0-10 = '))\n if jawaban == ang... | [
0,
1,
2,
3,
4
] |
'''
Confeccionar un programa que genere un número aleatorio entre 1 y 100 y no se muestre.
El operador debe tratar de adivinar el número ingresado.
Cada vez que ingrese un número mostrar un mensaje "Gano" si es igual al generado o "El número aleatorio el mayor" o "El número aleatorio es menor".
Mostrar cuando gana el j... | normal | {
"blob_id": "8498ba69e4cc5c5f480644ac20d878fb2a632bee",
"index": 5128,
"step-1": "<mask token>\n\n\ndef generar_numero_aleatorio():\n return random.randint(1, 100)\n\n\ndef es_el_numero(resp_usuario, resp_correc):\n return resp_usuario == resp_correc\n\n\ndef numero_dado_es_mayor(resp_usuario, resp_correc)... | [
5,
6,
7,
9,
10
] |
# [백준] https://www.acmicpc.net/problem/11053 가장 긴 증가하는 부분 수열
# 일단 재귀식으로 풀어보기
# 이분탐색 어떻게 할 지 모르겠다
import sys
N = int(sys.stdin.readline().strip())
A = list(map(int, sys.stdin.readline().split()))
def recur():
if A[i] < A[i-1]:
| normal | {
"blob_id": "afccf460bcf04f38b8c66177c86debd39a1b165f",
"index": 5159,
"step-1": "# [백준] https://www.acmicpc.net/problem/11053 가장 긴 증가하는 부분 수열\n# 일단 재귀식으로 풀어보기\n# 이분탐색 어떻게 할 지 모르겠다\n\nimport sys\n\nN = int(sys.stdin.readline().strip())\nA = list(map(int, sys.stdin.readline().split()))\n\ndef recur():\n\n if A... | [
0
] |
import os, sys
sys.path.append('./Pytorch-UNet/')
import torch
from torch import optim
import torchvision.transforms as transforms
import torchvision.datasets as dset
import wandb
from datasets import parse_dataset_args, create_dataset
from wt_utils import wt, create_filters, load_checkpoint, load_weights
from argumen... | normal | {
"blob_id": "fbd5c7fa335d6bde112e41a55d15aee31e3ebaf7",
"index": 2759,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsys.path.append('./Pytorch-UNet/')\n<mask token>\nif __name__ == '__main__':\n logger = Logger()\n torch.backends.cudnn.benchmark = True\n args = parse_args()\n logger.update_... | [
0,
1,
2,
3
] |
# coding: utf-8
# In[1]:
import pandas as pd
import numpy as np
import itertools
# Save a nice dark grey as a variable
almost_black = '#262626'
import matplotlib
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap
sns.set()
get_ipython().magic('matplotlib inline')
# I... | normal | {
"blob_id": "f2786e445bdf66cf6bb66f4cde4c7b2bf819d8aa",
"index": 3299,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsns.set()\nget_ipython().magic('matplotlib inline')\n<mask token>\nif header_included:\n header = 0\n<mask token>\nfor item in combinations:\n index = ax[i]\n x_vis = X[:, [featu... | [
0,
1,
2,
3,
4
] |
"""You are given a string .
Your task is to find out if the string contains:
alphanumeric characters, alphabetical characters, digits,
lowercase and uppercase characters."""
s = raw_input()
print(any(i.isalnum()for i in s))
print(any(i.isalpha()for i in s))
print(any(i.isdigit()for i in s))
print(any(i.islow... | normal | {
"blob_id": "f29fa3d796d9d403d6bf62cb28f5009501c55545",
"index": 3650,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(any(i.isalnum() for i in s))\nprint(any(i.isalpha() for i in s))\nprint(any(i.isdigit() for i in s))\nprint(any(i.islower() for i in s))\nprint(any(i.isupper() for i in s))\n<mask t... | [
0,
1,
2,
3
] |
# Generated by Django 3.1.6 on 2021-04-03 20:16
import django.contrib.postgres.fields
from django.db import migrations, models
import enrolments.validators
class Migration(migrations.Migration):
dependencies = [
("enrolments", "0007_merge_20210320_1853"),
]
operations = [
migrations.Add... | normal | {
"blob_id": "dbea2b1555368460b7d14369d2dfe4f0a01f9e4f",
"index": 8423,
"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 = [('enrolments'... | [
0,
1,
2,
3,
4
] |
import re
class Zout:
def __init__(self, aline):
self.Str = aline
self.Var = ''
self.StN = ''
self.ZN = ''
self.ZName = ''
self.Motion = ''
self.Ztype = ''
self.tozout(aline)
def tozout(self, aline):
"""transform station sta... | normal | {
"blob_id": "71ebc6e9218085e887eda7843b5489837ed45c97",
"index": 880,
"step-1": "<mask token>\n\n\nclass Zouts:\n <mask token>\n\n def search(self, StN, ZN, Motion):\n for elem in self.elements:\n print('elem:')\n print(str(type(elem.StN)) + str(type(StN)))\n print(e... | [
3,
6,
7,
10,
11
] |
# 10.13.20 - sjg
# Exercise 15 - solution A
# Write a function called greatestCommomFactor that,
#given two distinct positive integers,
#returns the greatest common factor of those two values
#Input: greatestCommonFactor(9,12)
#Output: 3
#Input: greatestCommonFactor(6,18)
#Output: 6
#Input: greatestCommonFactor(11... | normal | {
"blob_id": "a3f6ea649fc5e60b0f8353b1404912d060686b99",
"index": 9550,
"step-1": "<mask token>\n",
"step-2": "def greatestCommonFactor(posInt1, posInt2):\n range_posInt1 = list(range(1, posInt1 + 1))\n factors_posInt1 = []\n for i in range_posInt1:\n if posInt1 % i == 0:\n factors_po... | [
0,
1,
2,
3
] |
from room import Room
from player import Player
from item import Item
# Declare all the rooms
room = {
'outside': Room("Outside Cave Entrance",
"North of you, the cave mount beckons"),
'foyer': Room("Foyer", """Dim light filters in from the south. Dusty
passages run north and east."""... | normal | {
"blob_id": "beb536b6d8883daaa7e41da03145dd98aa223cbf",
"index": 5036,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile True:\n print('\\nPlayer Items:')\n for item in player.items:\n print('\\t', item)\n print('Room - ', player.current_room)\n print('Items in Room:')\n for item... | [
0,
1,
2,
3,
4
] |
def watch():
print("시청하다")
watch()
print("tv.py의 module 이름은",__name__) #name은 __main__으로 나옴 | normal | {
"blob_id": "b9622bede471c76ae36d3f59130d2be113310d4c",
"index": 7045,
"step-1": "<mask token>\n",
"step-2": "def watch():\n print('시청하다')\n\n\n<mask token>\n",
"step-3": "def watch():\n print('시청하다')\n\n\nwatch()\nprint('tv.py의 module 이름은', __name__)\n",
"step-4": "def watch():\n print(\"시청하다\")\... | [
0,
1,
2,
3
] |
"""
Tests based on: https://github.com/pydata/xarray/blob/071da2a900702d65c47d265192bc7e424bb57932/xarray/tests/test_backends_file_manager.py
"""
import concurrent.futures
import gc
import pickle
from unittest import mock
import pytest
from rioxarray._io import URIManager
def test_uri_manager_mock_write():
mock... | normal | {
"blob_id": "8fe71e87512dfd2ccfcd21c9c175cb50274d9661",
"index": 1867,
"step-1": "<mask token>\n\n\ndef test_uri_manager_mock_write():\n mock_file = mock.Mock()\n opener = mock.Mock(spec=open, return_value=mock_file)\n manager = URIManager(opener, 'filename')\n f = manager.acquire()\n f.write('con... | [
5,
6,
7,
8,
9
] |
from django.db import models
#from ingredients.models import *
class Unit(models.Model):
short_name = models.CharField(max_length=20)
full_name = models.CharField(max_length=255, null=True)
weight_in_grams = models.FloatField(default=1.0)
def __str__(self):
return f"{self.short_name}" | normal | {
"blob_id": "fa880adcb9f009ffc206de59e8284ac6350fef4c",
"index": 5948,
"step-1": "<mask token>\n\n\nclass Unit(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Unit(models.Model):\n <mask token>\n <mask token>\n <mask token>\... | [
1,
2,
3,
4,
5
] |
vozrast=int(input("сколько вам лет?"))
print ("через 10 лет вам бóдет", vozrast+10) | normal | {
"blob_id": "8e3f23733235d73fab14e80ee0a3706ae351c7a2",
"index": 4525,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('через 10 лет вам бóдет', vozrast + 10)\n",
"step-3": "vozrast = int(input('сколько вам лет?'))\nprint('через 10 лет вам бóдет', vozrast + 10)\n",
"step-4": "vozrast=int(input(\... | [
0,
1,
2,
3
] |
import pymongo
import redis
import json
from time import time
user_timeline_mongodb = "mongodb://user-timeline-mongodb.sdc-socialnetwork-db.svc.cluster.local:27017/"
user_timeline_redis = "user-timeline-redis.sdc-socialnetwork-db.svc.cluster.local"
def handle(req):
"""handle a request to the function
Args:
... | normal | {
"blob_id": "37969899aa646f4cdd7a5513f17d26b334870f1b",
"index": 6598,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef handle(req):\n \"\"\"handle a request to the function\n Args:\n req (str): request body\n \"\"\"\n start = time()\n event = json.loads(req)\n user_id = ev... | [
0,
1,
2,
3,
4
] |
'''
Given a binary tree, find its maximum depth.
The maximum depth is the number of nodes along the longest path from the root node down to the farthest leaf node.
Note: A leaf is a node with no children.
'''
# Definition for a binary tree node.
class TreeNode(object):
def __init__(self, x):
self.val... | normal | {
"blob_id": "fa081ccd8081f5c3319f482b7d8abd7415d8e757",
"index": 1273,
"step-1": "'''\nGiven a binary tree, find its maximum depth.\n\nThe maximum depth is the number of nodes along the longest path from the root node down to the farthest leaf node.\n\nNote: A leaf is a node with no children.\n\n'''\n\n\n\n# Def... | [
0
] |
import requests
seesion = requests.Session()
header = {'User-Agent':
'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2785.104 Safari/537.36 Core/1.53.3387.400 QQBrowser/9.6.11984.400'
}
cookie = {'Cookie':
'_ga=GA1.2.1866009938.1500885157; xmuuid=XMGUEST-B6484440-71B... | normal | {
"blob_id": "8c652f30cd256912512b6b91d1682af7da0ff915",
"index": 8265,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(html.decode('utf-8'))\n",
"step-3": "<mask token>\nseesion = requests.Session()\nheader = {'User-Agent':\n 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like... | [
0,
1,
2,
3
] |
def add_route_distance(routes, cities, source):
c = source.split()
citykey = c[0] + ':' + c[2]
cities.add(c[0])
routes[citykey] = c[4]
def get_route_distance(routes, source, dest):
if (source+":"+dest in routes):
return routes[source+":"+dest]
else:
return routes[dest+":"+sourc... | normal | {
"blob_id": "810e9e4b18ff8cb388f9e16607b8ab3389a9831d",
"index": 7402,
"step-1": "<mask token>\n\n\ndef get_route_distance(routes, source, dest):\n if source + ':' + dest in routes:\n return routes[source + ':' + dest]\n else:\n return routes[dest + ':' + source]\n\n\n<mask token>\n",
"step... | [
1,
2,
3,
4,
5
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Created with YooLiang Technology (侑良科技).
# Author: Qi-Liang Wen (温啓良）
# Web: http://www.yooliang.com/
# Date: 2015/7/12.
from monkey import BasicModel
from monkey import Fields
class WebInformationModel(BasicModel):
class Meta:
label_name = {
"... | normal | {
"blob_id": "3d55a5b4e332523025f65e5f5859f4633f4ee9a3",
"index": 7501,
"step-1": "<mask token>\n\n\nclass WebInformationModel(BasicModel):\n\n\n class Meta:\n label_name = {'title': u'通用名稱', 'name': u'識別碼',\n 'domain_registration': u'網域註冊地', 'domain_registration_price':\n u'網域註冊費用... | [
1,
2,
3,
4,
5
] |
#!/home/liud/anaconda3/envs/python/bin/python
# -*- coding: utf-8 -*-
'''
线性回归
公式：W = 1/(xTx) * xT * y
'''
#导入的包
import numpy as np
from numpy import linalg
from numpy import corrcoef
from sklearn import linear_model
import matplotlib.pyplot as plt
#加载数据
def loadDataSet(filename):
xList = []
yList = []
with open(... | normal | {
"blob_id": "a6eab1e5e7985de917d707c904fcd90f223c108c",
"index": 2559,
"step-1": "#!/home/liud/anaconda3/envs/python/bin/python\n# -*- coding: utf-8 -*-\n'''\n\t线性回归\n\t公式：W = 1/(xTx) * xT * y\n'''\n#导入的包\nimport numpy as np\nfrom numpy import linalg\nfrom numpy import corrcoef\nfrom sklearn import linear_model\... | [
0
] |
__version__ = "alph 1.0"
| normal | {
"blob_id": "2c4eb07a32c6903ae31006f42c13c55e6cc42eb5",
"index": 5245,
"step-1": "<mask token>\n",
"step-2": "__version__ = 'alph 1.0'\n",
"step-3": "__version__ = \"alph 1.0\"\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
} | [
0,
1,
2
] |
import subprocess
from flask import Flask, render_template, request
from subprocess import Popen, PIPE, check_output
def toggle_relay(value):
session = subprocess.Popen("./relay " + value, stdout=PIPE, stderr=PIPE, shell=True)
stdout, stderr = session.communicate()
if stderr:
raise Exception("Error... | normal | {
"blob_id": "18d1722529a63f9a1696b09c40dabb1c68ed55f4",
"index": 3423,
"step-1": "<mask token>\n\n\ndef toggle_relay(value):\n session = subprocess.Popen('./relay ' + value, stdout=PIPE, stderr=PIPE,\n shell=True)\n stdout, stderr = session.communicate()\n if stderr:\n raise Exception('Err... | [
2,
3,
4,
5,
6
] |
###########################################################
# 2019-02-07: 删除了marginalized prior
#
###########################################################
import sys,os
import numpy as np
import matplotlib.pylab as plt
from scipy.linalg import eig
from scipy.stats import norm, kstest, normaltest
# use default col... | normal | {
"blob_id": "ac35672661e1dd0b97567ae4335f537dc69f98f7",
"index": 6240,
"step-1": "<mask token>\n\n\ndef read_jla_mock(mock_filename):\n fp = open(mock_filename, 'r')\n lines = fp.readlines()\n fp.close()\n jla = []\n for line in lines:\n sn = line.split()\n temp = []\n temp.ap... | [
1,
2,
3,
4,
5
] |
# -*- coding: utf-8 -*-
"""
Created on Fri Oct 5 17:05:12 2018
@author: Shane
"""
import math
import scipy.integrate as integrate
import random
import numpy as np
import sympy as sym
'''
Question 1
plug and play into formula for VC generalization
'''
print('Question 1')
error = 0.05
for N in [400000,420000,4400... | normal | {
"blob_id": "abe53120a485f608431142c6b9452666fcd72dbf",
"index": 7464,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('Question 1')\n<mask token>\nfor N in [400000, 420000, 440000, 460000, 480000]:\n print(4 * (2 * N) ** 10 * math.exp(-(1 / 8) * error ** 2 * N))\n<mask token>\nprint('Question 2'... | [
0,
1,
2,
3,
4
] |
from Crypto.Hash import SHA512
from Crypto.PublicKey import RSA
from Crypto import Random
from collections import Counter
from Tkinter import Tk
from tkFileDialog import askopenfilename
import ast
import os
import tkMessageBox
from Tkinter import Tk
from tkFileDialog import askopenfilename
import Tkinter
import tkSimpl... | normal | {
"blob_id": "da696961fea72e1482beae73c19b042b94d93886",
"index": 1660,
"step-1": "<mask token>\n\n\ndef read_file_all(file_name):\n filename = os.path.join(fileDir, str(file_name))\n with open(filename, 'r') as f:\n read_data = f.readlines()\n return read_data\n\n\n<mask token>\n\n\ndef selec... | [
3,
9,
10,
11,
12
] |
#!/usr/bin/env python
import argparse
import sys
import logging
import vafator
from vafator.power import DEFAULT_FPR, DEFAULT_ERROR_RATE
from vafator.hatchet2bed import run_hatchet2bed
from vafator.ploidies import PloidyManager
from vafator.annotator import Annotator
from vafator.multiallelic_filter import Mul... | normal | {
"blob_id": "1651865f120ba4fe440549567a8d9903e5455788",
"index": 5774,
"step-1": "<mask token>\n\n\ndef annotator():\n parser = argparse.ArgumentParser(description='vafator v{}'.format(\n vafator.VERSION), formatter_class=argparse.\n ArgumentDefaultsHelpFormatter, epilog=epilog)\n parser.add_... | [
3,
4,
5,
6,
7
] |
"""4. Начните работу над проектом «Склад оргтехники». Создайте класс, описывающий склад. А также класс «Оргтехника»,
который будет базовым для классов-наследников. Эти классы — конкретные типы оргтехники (принтер, сканер, ксерокс).
В базовом классе определить параметры, общие для приведенных типов. В классах-наследника... | normal | {
"blob_id": "03bc377bef1de7d512b7982a09c255af1d82fb7d",
"index": 3905,
"step-1": "<mask token>\n\n\nclass Whouse:\n <mask token>\n\n def get_tech_to_whouse(self, equip: Equipment):\n if self.total == self.max_volume:\n raise OverflowError('Склад заполнен!')\n self.storage[self.add_... | [
9,
11,
12,
16,
17
] |
### we prepend t_ to tablenames and f_ to fieldnames for disambiguity
import uuid
crud.settings.formstyle="table2cols"
########################################
db.define_table('t_form',
Field('id','id',
represent=lambda id:SPAN(id,' ',A('view',_href=URL('form_read',args=id)))),
Field('f_name', type=... | normal | {
"blob_id": "e2e275c48f28843931412f8e620f1be90289b40c",
"index": 8184,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ndb.define_table('t_form', Field('id', 'id', represent=lambda id: SPAN(id,\n ' ', A('view', _href=URL('form_read', args=id)))), Field('f_name', type\n ='string', label=T('Name')), Fi... | [
0,
1,
2,
3,
4
] |
STATUS_CHOICES = (
(-1, 'Eliminado'),
(0, 'Inactivo'),
(1, 'Activo'),
)
USERTYPES_CHOICES = ()
#-- Activation Request Values
ACTIVATION_CHOICES = (
(1, 'Activacion'),
(2, 'Solicitud Password'),
(3, 'Invitacion'),
)
#-- Activation Status Values
ACTIVATIONSTATUS_CHOICES = (
(-1, 'Expirado... | normal | {
"blob_id": "200552b638d6b1a6879b455837677b82689e0069",
"index": 5479,
"step-1": "<mask token>\n",
"step-2": "STATUS_CHOICES = (-1, 'Eliminado'), (0, 'Inactivo'), (1, 'Activo')\nUSERTYPES_CHOICES = ()\nACTIVATION_CHOICES = (1, 'Activacion'), (2, 'Solicitud Password'), (3,\n 'Invitacion')\nACTIVATIONSTATUS_C... | [
0,
1,
2
] |
# -*- coding: utf-8 -*-
"""Utilities for reading BEL Script."""
import time
from typing import Iterable, Mapping, Optional, Set
from .constants import (
ANNOTATION_PATTERN_FMT, ANNOTATION_URL_FMT, NAMESPACE_PATTERN_FMT, NAMESPACE_URL_FMT, format_annotation_list,
)
__all__ = [
'make_knowledge_header',
]
de... | normal | {
"blob_id": "46b8d0ba58d4bf17021b05fc03bd480802f65adf",
"index": 6132,
"step-1": "<mask token>\n\n\ndef make_knowledge_header(name: str, version: Optional[str]=None,\n description: Optional[str]=None, authors: Optional[str]=None, contact:\n Optional[str]=None, copyright: Optional[str]=None, licenses: Optio... | [
3,
4,
5,
6,
7
] |
# Class 1: Flight which contains the flight number(f_id), its origin and destination, the number of stops between the
# origin and destination and the type of airlines(f_type)
class Flight():
# INIT CONSTRUCTOR
def __init__(self, f_id, f_origin, f_destination, no_of_stops, flight_type, p_id, p_type):
s... | normal | {
"blob_id": "95a2f5abb37642651316a8954a4289e5b04e4916",
"index": 4357,
"step-1": "<mask token>\n\n\nclass Passenger(Person):\n <mask token>\n <mask token>\n\n def __init__(self, p_id, p_type, p_gender, p_name, p_phonenumber, f_id,\n pno, f_origin, f_destination, no_of_stops, flight_type):\n ... | [
5,
7,
13,
16,
17
] |
print raw_input().count(raw_input()) | normal | {
"blob_id": "2d4b0e7b430ffb5d236300079ded4b848e6c6485",
"index": 3602,
"step-1": "print raw_input().count(raw_input())",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
} | [
0
] |
from __future__ import division
import re
import sys
import six
from six.moves import queue
import os
import io
from google.cloud import language
from google.cloud.language import enums
from google.cloud.language import types
from google.cloud import speech as speech1
from google.cloud.speech import enums as enums2
fr... | normal | {
"blob_id": "6868a8b5d36403f1417301acdca5f5dc9e45c682",
"index": 9849,
"step-1": "<mask token>\n\n\nclass Google_Cloud:\n <mask token>\n\n def sentiment(self):\n google_sentiment = self.client.analyze_sentiment(self.document\n ).document_sentiment\n sent = {}\n sent['sentime... | [
7,
8,
10,
11,
14
] |
import os
from sources.lol.status import LOLServerStatusCollector
from util.abstract.feed import Feed
from util.abstract.handler import Handler
from util.functions.load_json import load_json
class LoLServerStatusHandler(Handler):
def load_servers(self):
servers_filepath = os.path.join(os.path.dirname(__f... | normal | {
"blob_id": "493552469943e9f9f0e57bf92b874c8b67943de5",
"index": 6751,
"step-1": "<mask token>\n\n\nclass LoLServerStatusHandler(Handler):\n\n def load_servers(self):\n servers_filepath = os.path.join(os.path.dirname(__file__),\n '../../data/lol/status.json')\n return load_json(server... | [
3,
4,
5,
6
] |
import pandas as pd
from bokeh.models import ColumnDataSource, LinearColorMapper, HoverTool
from bokeh.plotting import figure
from bokeh.transform import transform
from sklearn.metrics import confusion_matrix
from reporter.settings import COLORS
from reporter.metrics import Metric
class ConfusionMatrix(Metric):
d... | normal | {
"blob_id": "9a2002b5ff0fe41f2b5b568f4c278d4376bf4fb1",
"index": 6117,
"step-1": "<mask token>\n\n\nclass ConfusionMatrix(Metric):\n <mask token>\n <mask token>\n\n def draw(self, size=400):\n index_label = 'Predicted'\n column_label = 'Actual'\n matrix = self.generate_data()\n ... | [
2,
3,
4,
5,
6
] |
from django.contrib import admin
from django.urls import path
from .views import NewsCreateListView, NewsDetailGenericView
urlpatterns = [
path('news/', NewsCreateListView.as_view()),
path('news_detailed/<int:id>/', NewsDetailGenericView.as_view()),
] | normal | {
"blob_id": "afdb14d60374049753b3c980c717a13456c7ff5c",
"index": 9745,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('news/', NewsCreateListView.as_view()), path(\n 'news_detailed/<int:id>/', NewsDetailGenericView.as_view())]\n",
"step-3": "from django.contrib import admin\nfrom... | [
0,
1,
2,
3
] |
#!/bin/python3
def solveMeFirst(a,b):
return a + b
print(solveMeFirst(int(input()),int(input())))
| normal | {
"blob_id": "5d55c586c57de8f287d9f51f0cb1f188c8046c29",
"index": 2977,
"step-1": "<mask token>\n",
"step-2": "def solveMeFirst(a, b):\n return a + b\n\n\n<mask token>\n",
"step-3": "def solveMeFirst(a, b):\n return a + b\n\n\nprint(solveMeFirst(int(input()), int(input())))\n",
"step-4": "#!/bin/pytho... | [
0,
1,
2,
3
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.