code stringlengths 13 1.2M | order_type stringclasses 1
value | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
# -*- coding: utf-8 -*-
'''
Created on 2014/07/24
@author: seigo
'''
from google.appengine.api import users
from google.appengine.ext import webapp
from MyModel import HistoricalTable, PollRating, Government
from datetime import datetime
hts = [["2014/7/1","集団的自衛権行使容認の閣議決定","http://www.47news.jp/47topics/e/254919.ph... | normal | {
"blob_id": "b8957acb71d435a93b4397a24d3b5cf4b2a817f8",
"index": 2602,
"step-1": "<mask token>\n\n\nclass initDATA(webapp.RequestHandler):\n <mask token>\n\n def get(self):\n user = users.get_current_user()\n if user == None:\n self.redirect(users.create_login_url(self.request.uri)... | [
4,
5,
6,
7,
8
] |
def merge(items, temp, low, mid, high):
i = low
j = mid + 1
for k in range(low, high+1):
if i > mid:
# 왼쪽 리스트의 순회를 마쳤음
# 남은 오른쪽 리스트의 원소들은 모두 왼쪽 리스트 원소보다 작음
temp[k] = items[j]
# 뒤에 나머지는 정렬되어있으니 그대로 넣기
j += 1
elif j > high:
... | normal | {
"blob_id": "9ab119b32ceac370b744658e5fa679292609373a",
"index": 2517,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef merge_sort(items, temp, low, high):\n if high <= low:\n return None\n mid = low + (high - low) // 2\n merge_sort(items, temp, low, mid)\n merge_sort(items, temp... | [
0,
1,
2,
3,
4
] |
def format_amount(a):
return a.replace(",","").strip().replace("%","").replace("$","")
def create_json(gdp, coords):
# ------------ Split gdp data ------------ #
line_list=gdp.split('\n')
column_list = [x.split('\t') for x in line_list if x!=""]
# ------------ Split coord data ------------ #
line_list=coords.s... | normal | {
"blob_id": "1cbc37655e28ab3082fc31baf119cb2bab96379b",
"index": 3661,
"step-1": "def format_amount(a):\n return a.replace(',', '').strip().replace('%', '').replace('$', '')\n\n\n<mask token>\n",
"step-2": "def format_amount(a):\n return a.replace(',', '').strip().replace('%', '').replace('$', '')\n\n\nd... | [
1,
3,
4,
5,
6
] |
import krait
from ctrl import ws
krait.mvc.set_init_ctrl(ws.WsPageController())
| normal | {
"blob_id": "da2b946238b429188fe3fa50286658d4b5cdbf41",
"index": 5752,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nkrait.mvc.set_init_ctrl(ws.WsPageController())\n",
"step-3": "import krait\nfrom ctrl import ws\nkrait.mvc.set_init_ctrl(ws.WsPageController())\n",
"step-4": null,
"step-5": null,
... | [
0,
1,
2
] |
def maths(num):
int(num)
if num % 5 == 0 and num % 3 == 0:
print("bizzfizz")
elif num % 3 == 0:
print("fizz")
elif num % 5 == 0:
print("bizz")
else:
print(num)
value=input("enter the value ")
maths(int(value)) | normal | {
"blob_id": "91f83adbe01e2d8070f9286031b77eae71beb83e",
"index": 1107,
"step-1": "<mask token>\n",
"step-2": "def maths(num):\n int(num)\n if num % 5 == 0 and num % 3 == 0:\n print('bizzfizz')\n elif num % 3 == 0:\n print('fizz')\n elif num % 5 == 0:\n print('bizz')\n else:\... | [
0,
1,
2,
3,
4
] |
"""Testing data storage functionality in gludb.simple (see simple_tests.py for
testing of the rest of gludb.simple functionality)"""
import unittest
import datetime
import time
import gludb.config
from gludb.versioning import VersioningTypes
from gludb.data import orig_version
from gludb.simple import DBObject, Fiel... | normal | {
"blob_id": "7383ae97d6a1368896d05d0cafc9846c24004701",
"index": 2690,
"step-1": "<mask token>\n\n\nclass DefaultStorageTesting(unittest.TestCase):\n\n def setUp(self):\n gludb.config.default_database(gludb.config.Database('sqlite',\n filename=':memory:'))\n SimpleStorage.ensure_table... | [
16,
21,
24,
25,
28
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Check mean system norm errors in regression tests
This script determines the pass/fail status of a regression test by comparing
the "Mean System Norm" values output at each timestep against "gold values"
from the reference file provided by the user.
Success is deter... | normal | {
"blob_id": "d03669924233edf33fcb6645f5ed7ab118f54a95",
"index": 7610,
"step-1": "<mask token>\n\n\ndef load_norm_file(fname):\n \"\"\"Parse the norm file and return the mean system norms\"\"\"\n try:\n with open(fname, 'r') as fh:\n lines = fh.readlines()\n norms = [float(ll.s... | [
5,
6,
7,
8,
9
] |
import sys
from collections import deque
t = int(sys.stdin.readline().rstrip())
for _ in range(t):
n, m = map(int, sys.stdin.readline().split())
q = deque(map(int, sys.stdin.readline().split()))
count = 0
while q:
highest = max(q)
doc = q.popleft()
m -= 1
if doc != highes... | normal | {
"blob_id": "a571abd88184c8d8bb05245e9c3ce2e4dabb4c09",
"index": 615,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor _ in range(t):\n n, m = map(int, sys.stdin.readline().split())\n q = deque(map(int, sys.stdin.readline().split()))\n count = 0\n while q:\n highest = max(q)\n ... | [
0,
1,
2,
3
] |
import itertools
def permutations(string):
return list("".join(p) for p in set(itertools.permutations(string))) | normal | {
"blob_id": "3d49d03dbc38ee37eadd603b4b464b0e2e1a33d5",
"index": 5280,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef permutations(string):\n return list(''.join(p) for p in set(itertools.permutations(string)))\n",
"step-3": "import itertools\n\n\ndef permutations(string):\n return list('... | [
0,
1,
2,
3
] |
from PIL import Image
from pdf2image import convert_from_path
import glob
from pathlib import Path
import shutil, os
from docx import Document
import fnmatch
import re
import shutil
def find_files_ignore_case(which, where='.'):
'''Returns list of filenames from `where` path matched by 'which'
shell patter... | normal | {
"blob_id": "a9876c61578a53f29865062c0915db622aaaba72",
"index": 6916,
"step-1": "<mask token>\n\n\ndef crop_image_center(file, crop_left, crop_right, crop_top, crop_bottom):\n img = Image.open(file)\n x, y = img.size\n box = (crop_left, crop_top, x - crop_left - crop_right, y - crop_top -\n crop... | [
4,
6,
7,
8,
9
] |
#downloads project detail reports from the web and places them in the correct project folder created by makeFolders.py
import os, openpyxl, time, shutil
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
wb = openpyxl.load_workbook('ProjectSummary.xlsx')
sheet = wb.active
browser = webdri... | normal | {
"blob_id": "6e9fd8ee2a187888df07c9dd1c32fe59a111c869",
"index": 8823,
"step-1": "<mask token>\n\n\ndef pdfToFolder(projectName):\n os.chdir('/home/gmclaughlin/Downloads')\n if projectName.find('DEM') != -1:\n shutil.move('/home/gmclaughlin/Downloads/Detail Report - Basic.pdf',\n \n ... | [
1,
2,
3,
4,
5
] |
import hashlib
import json
import logging
import os
import urllib.parse
import uuid
from datetime import datetime
import pytz
from celery import states as celery_states
from django.conf import settings
from django.contrib.auth.base_user import AbstractBaseUser
from django.contrib.auth.base_user import BaseUserManager
... | normal | {
"blob_id": "32e904a39d03d3166369420b49db0b9b118110a3",
"index": 4179,
"step-1": "<mask token>\n\n\nclass ContentKind(models.Model):\n <mask token>\n\n def __str__(self):\n return self.kind\n\n\nclass FileFormat(models.Model):\n extension = models.CharField(primary_key=True, max_length=40, choice... | [
65,
102,
158,
169,
216
] |
import osfrom setuptools import setup
def read(fname): with open(fname) as fhandle: return fhandle.read()
def readMD(fname): # Utility function to read the README file. full_fname = os.path.join(os.path.dirname(__file__), fname) if 'PANDOC_PATH' in os.environ: import pandoc pandoc.core.PANDOC_PATH = os.enviro... | normal | {
"blob_id": "7b18c967cf50d87b089dc22f3fbe6d40d708483f",
"index": 8441,
"step-1": "import osfrom setuptools import setup\ndef read(fname): with open(fname) as fhandle: return fhandle.read()\ndef readMD(fname): # Utility function to read the README file. full_fname = os.path.join(os.path.dirname(__file__), fnam... | [
0
] |
from collections import defaultdict
def solve(n, seq):
flag = True
# slot = [0] * (n + 10)
freq = defaultdict()
# refer to next free slot
i = 1
p = len(seq)
j = 0
while j < p:
c = seq[j]
if i > n:
flag = False
break
if c in freq.keys():
... | normal | {
"blob_id": "89b03bb5ca86e426459e23866f86f8770e4a1613",
"index": 3420,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef solve(n, seq):\n flag = True\n freq = defaultdict()\n i = 1\n p = len(seq)\n j = 0\n while j < p:\n c = seq[j]\n if i > n:\n flag = Fals... | [
0,
2,
3,
4,
5
] |
"""
Writes day of the week and time to a file.
Script written for crontab tutorial.
Author: Jessica Yung 2016
"""
import time
filename = "record_time.txt"
# Records time in format Sun 10:00:00
current_time = time.strftime('%a %H:%M:%S')
# Append output to file. 'a' is append mode.
with open(filename, 'a') as hand... | normal | {
"blob_id": "1f0695f0e9745912d8ee3a87e6c9b1272e9ebbae",
"index": 218,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open(filename, 'a') as handle:\n handle.write(str(current_time))\n handle.write('\\n')\n",
"step-3": "<mask token>\nfilename = 'record_time.txt'\ncurrent_time = time.strftime(... | [
0,
1,
2,
3,
4
] |
"""
Batch viewset
Viewset to batch serializer
"""
# Django Rest Framework
from rest_framework import viewsets
# Inventory models
from apps.inventory.models import Batch
# Inventory serializers
from apps.inventory.serializers import BatchSerializer
class BatchViewSet(viewsets.ModelViewSet):
"""
Batch views... | normal | {
"blob_id": "3d0fe0c11e62a03b4701efb19e1c15272ccc985e",
"index": 3315,
"step-1": "<mask token>\n\n\nclass BatchViewSet(viewsets.ModelViewSet):\n <mask token>\n <mask token>\n <mask token>\n\n def perform_destroy(self, instance):\n \"\"\"\n perform_destroy is used to performance a logic ... | [
2,
3,
4,
5,
6
] |
# USAGE
# python predict_video.py --model model/activity.model --label-bin model/lb.pickle --input example_clips/lifting.mp4 --output output/lifting_128avg.avi --size 128
# python predict_video.py --model model/road_activity.model --label-bin model/rd.pickle --input example_clips/fire_footage.mp4 --ou
# tput output/fir... | normal | {
"blob_id": "ccfcc5b644d592090786ceb35a85124c9d3275ad",
"index": 5719,
"step-1": "<mask token>\n\n\n@app.route('/')\ndef index():\n return render_template('Main_page.html')\n\n\n@app.route('/prediction.html')\ndef predict():\n return render_template('prediction.html')\n\n\n@app.route('/About_us.html')\ndef... | [
4,
5,
6,
7,
8
] |
#! /usr/bin/python2
# Copyright 2007 John Kasunich and Jeff Epler
#
# modified by Rudy du Preez to fit with the kinematics component pumakins.c
# Note: DH parameters in pumakins halfile should bet set to
# A2=400, A3=50, D3=100, D4=400, D6=95
#
# z |
# ... | normal | {
"blob_id": "ae83a0e1ebf1190ab55459563bc7b86d240de89a",
"index": 4146,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nc.newpin('joint1', hal.HAL_FLOAT, hal.HAL_IN)\nc.newpin('joint2', hal.HAL_FLOAT, hal.HAL_IN)\nc.newpin('joint3', hal.HAL_FLOAT, hal.HAL_IN)\nc.newpin('joint4', hal.HAL_FLOAT, hal.HAL_IN)\... | [
0,
1,
2,
3,
4
] |
from django import forms
from django.conf import settings
class SurveyFeedback(forms.Form):
CHOICES = [('Very Satisfied', 'Very Satisfied'), ('Satisfied',
'Satisfied'), ('Neither', 'Neither'), ('Dissatisfied',
'Dissatisfied'), ('Very Dissatisfied', 'Very Dissatisfied')]
radioFeedback = forms.C... | normal | {
"blob_id": "a9b7abaaaa811cf12a15def1f2dd21f95bac3d62",
"index": 6310,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass SurveyFeedback(forms.Form):\n <mask token>\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass SurveyFeedback(forms.Form):\n CHOICES = [('Very Sat... | [
0,
1,
2,
3
] |
from cancion import *
class NodoLista:
def __init__(self, cancion, s, a):
self.elemento = cancion
self.siguiente = s
self.anterior = a
| normal | {
"blob_id": "1fb3904d48905ade8f83b6e052057e80302ec5a7",
"index": 4253,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass NodoLista:\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass NodoLista:\n\n def __init__(self, cancion, s, a):\n self.elemento = cancion\n self.siguien... | [
0,
1,
2,
3
] |
def solution(citations):
# 사이테이션을 정렬
citations.sort()
#
for i in range(len(citations)):
if citations[i] >= len(citations) - i:
return len(citations)-i
print(solution([3,0,6,1,5])) | normal | {
"blob_id": "0b3d6339faf9d66d4e1338599e4784fac0f63d3f",
"index": 5310,
"step-1": "<mask token>\n",
"step-2": "def solution(citations):\n citations.sort()\n for i in range(len(citations)):\n if citations[i] >= len(citations) - i:\n return len(citations) - i\n\n\n<mask token>\n",
"step-... | [
0,
1,
2,
3
] |
import pyttsx3
import pyglet
import time
import logging
import os
from gtts import gTTS
ROOT_DIR = os.path.dirname(os.path.abspath(__file__))
class GoogleTTS:
def utter_voice_message(self, message):
try:
# Google Text-to-Speech API - needs internet connectivity
#filename = ROOT_D... | normal | {
"blob_id": "9ed674513bebe65ece538e9ce2b3945bb0c532cc",
"index": 1357,
"step-1": "<mask token>\n\n\nclass GoogleTTS:\n <mask token>\n\n def check_google_connection(self):\n try:\n message = 'Hallo'\n filename = 'temp_voice.mp3'\n tts = gTTS(text=message, lang='de')\n... | [
5,
7,
8,
9,
10
] |
from django.db import models
from .data import REGISTER_TYPE_CHOICES
from .data import ENTRANCE_TYPE
from .data import EXPENSE_TYPE
class EstheticHouse(models.Model):
name = models.CharField(
verbose_name='nombre',
max_length=512,
unique=True,
)
def __str__(self):
return ... | normal | {
"blob_id": "df25b51010fdbcbf1a8949a7a755a3a982bbf648",
"index": 6352,
"step-1": "<mask token>\n\n\nclass Employee(models.Model):\n <mask token>\n <mask token>\n <mask token>\n\n def __str__(self):\n return self.name\n\n\n class Meta:\n ordering = ['name']\n verbose_name = 'Em... | [
7,
8,
18,
19,
20
] |
import paho.mqtt.client as paho
import RPi.GPIO as GPIO
import json, time, math
import clearblade
from clearblade import auth
from clearblade import Client
from urlparse import urlparse
#Fill init values
systemKey = ______
secretKey = ______
userName = _______
userPW = _______
edgeIP = "http://_______:9000"
auth = au... | normal | {
"blob_id": "299d13fbcdb75673026db1e3a0352c8b19d453c1",
"index": 6314,
"step-1": "import paho.mqtt.client as paho\nimport RPi.GPIO as GPIO\nimport json, time, math\nimport clearblade\nfrom clearblade import auth\nfrom clearblade import Client\nfrom urlparse import urlparse\n\n#Fill init values\nsystemKey = _____... | [
0
] |
# -*- coding: utf-8 -*-
"""Template parser for Faker"""
from datetime import datetime
from jinja2 import Template
from faker import Faker
from faker.providers.internet import Provider as InternetProvider
from ..providers.file_data_source_provider import FileDataSourceProvider
from ..providers.numbers_provider import Nu... | normal | {
"blob_id": "38f9cddfde4787ead2314fc70c1f4d91a3da9687",
"index": 1307,
"step-1": "<mask token>\n\n\nclass TemplateParser:\n <mask token>\n <mask token>\n\n def __init__(self, template=None, providers=None, date_generator=None):\n self.fake = Faker()\n self.fake.add_provider(FileDataSourceP... | [
3,
4,
6,
7,
8
] |
# encoding: utf-8
# -*- coding: utf-8 -*-
"""
The flask application package.
"""
#parse arguments
from flask import Flask
from flask_cors import CORS
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('-t', '--testing', action='store_true') #to use the testing database
parser.add_argument('-i', ... | normal | {
"blob_id": "e403a84ec2a3104cb908933f6949458cccc791c3",
"index": 4737,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nparser.add_argument('-t', '--testing', action='store_true')\nparser.add_argument('-i', '--init', action='store_true')\nparser.add_argument('-r', '--reinit', action='store_true')\n<mask to... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python3
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR ... | normal | {
"blob_id": "923a433a3a04a8538b43d162d17d379daab4698a",
"index": 7753,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nasync def sound(cube):\n sound = bytearray()\n sound.append(2)\n sound.append(9)\n sound.append(255)\n await cube.write_gatt_char(TOIO_SOUND_UUID, sound)\n\n\nasync def... | [
0,
1,
2,
3,
4
] |
'''
syntax of if-elif-else
if <condition> :
code to be
executed in
this condition
elif <new condition> :
cdode tbd
some code
else :
code runs in the else condigtion
this can all be multiline code
'''
a = 3
b = 2
if a == b :
print "Values are equal"
elif a < b :
print "a is less than b"
else:
print "b... | normal | {
"blob_id": "d7ce6efa72c9b65d3dd3ce90f9d1f2dd8a889d26",
"index": 444,
"step-1": "\n'''\nsyntax of if-elif-else\n\nif <condition> :\n\tcode to be\n\texecuted in\n\tthis condition\nelif <new condition> :\n\tcdode tbd\n\tsome code\nelse :\n\tcode runs in the else condigtion\n\tthis can all be multiline code\n\n'''\... | [
0
] |
#!/usr/bin/env python3
import operator
from functools import reduce
import music21
def get_top_line(piece):
top_part = piece.parts[0]
if len(top_part.voices) > 0:
top_part = top_part.voices[0]
# replace all chords with top note of chord
for item in top_part.notes:
if isinstance(item... | normal | {
"blob_id": "92ee66565eb1d0e3cd8fa1ec16747f15e0d92be8",
"index": 2885,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_notes(piece):\n part = piece.parts[0]\n measures = filter(lambda x: isinstance(x, music21.stream.Measure), part\n .elements)\n notes = reduce(operator.add, map... | [
0,
1,
2,
3,
4
] |
def ip_address(address):
new_address = ""
split_address = address.split(".")
seprator = "[.]"
new_address = seprator.join(split_address)
return new_address
if __name__ == "__main__":
ipaddress = ip_address("192.168.1.1")
print(ipaddress)
| normal | {
"blob_id": "7ef62e5545930ab13312f8ae1ea70a74386d8bfa",
"index": 1231,
"step-1": "<mask token>\n",
"step-2": "def ip_address(address):\n new_address = ''\n split_address = address.split('.')\n seprator = '[.]'\n new_address = seprator.join(split_address)\n return new_address\n\n\n<mask token>\n"... | [
0,
1,
2,
3
] |
# Definition for singly-linked list.
# class ListNode:
# def __init__(self, x):
# self.val = x
# self.next = None
class Solution:
# @param head, a ListNode
# @return a ListNode
def insertionSortList(self, head):
if not head:
return head
fh = List... | normal | {
"blob_id": "c234031fa6d43c19515e27c5b12f8e8338f24a1c",
"index": 6412,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n",
"step-3": "class Solution:\n\n def insertionSortList(self, head):\n if not head:\n return head\n fh = ListNode(0)\n fh.next = ... | [
0,
1,
2,
3
] |
from xml.dom import minidom
import simplejson as json
import re
camel_split = re.compile(r'(^[a-z]+|[A-Z][a-z]+|[a-z0-9]+)')
def get_items(xml):
for obj_node in xml.getElementsByTagName('item'):
obj = dict(obj_node.attributes.items())
if 'name' in obj:
obj['title'] = (' '.join(camel_sp... | normal | {
"blob_id": "69a3471ee8d2c317264b667d6ae0f9b500c6222f",
"index": 6497,
"step-1": "from xml.dom import minidom\nimport simplejson as json\nimport re\n\ncamel_split = re.compile(r'(^[a-z]+|[A-Z][a-z]+|[a-z0-9]+)')\n\ndef get_items(xml):\n for obj_node in xml.getElementsByTagName('item'):\n obj = dict(obj... | [
0
] |
from abc import ABCMeta, abstractmethod
__author__ = 'Alexiy'
class Protocol:
"""base protocol class"""
__metaclass__ = ABCMeta
FAIL = 'Failed'
@abstractmethod
def execute(self, command):
""""execute command method"""
class LocalProtocol(Protocol):
"""simple protocol for using bots ... | normal | {
"blob_id": "8d1067a9bb0629276ef27de91f63cf2370a44e24",
"index": 1369,
"step-1": "<mask token>\n\n\nclass Protocol:\n <mask token>\n <mask token>\n <mask token>\n\n @abstractmethod\n def execute(self, command):\n \"\"\"\"execute command method\"\"\"\n\n\nclass LocalProtocol(Protocol):\n ... | [
6,
7,
8,
11
] |
import struct
class H264Packet:
UNKNOWN_TYPE, I_HDR, P_HDR, B_HDR, I_DATA, P_DATA, B_DATA = range(7)
def __init__(self, packet):
self.packet = packet
self.type = None
self.data = None
if len(packet) > 3:
(self.type,) = struct.unpack('H', packet[0:2])
self.data = packet[2:]
def serialize(self):
r... | normal | {
"blob_id": "ff1db5981a0163df1dfb44869a3d4af2be03c10a",
"index": 2745,
"step-1": "<mask token>\n\n\nclass H264Packet:\n <mask token>\n\n def __init__(self, packet):\n self.packet = packet\n self.type = None\n self.data = None\n if len(packet) > 3:\n self.type, = struc... | [
4,
5,
6,
7,
8
] |
import time
import numpy as np
import matplotlib.pyplot as plt
import cv2
import matplotlib.image as mpimg
import random
import skimage
import scipy
from PIL import Image
def readimg(dirs, imgname):
img = cv2.imread(dirs + imgname)
img = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
return img
def readimg_color(d... | normal | {
"blob_id": "e08ab06be0957e5e173df798742abc493eac84d0",
"index": 6006,
"step-1": "<mask token>\n\n\ndef readimg(dirs, imgname):\n img = cv2.imread(dirs + imgname)\n img = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)\n return img\n\n\ndef readimg_color(dirs, imgname):\n img = cv2.imread(dirs + imgname)\n ... | [
9,
11,
14,
15,
16
] |
import falcon
import json
from sqlalchemy.exc import SQLAlchemyError
from db import session
import model
import util
class AchievementGrant(object):
def on_post(self, req, resp):
"""
Prideleni achievementu
Format dat:
{
"users": [ id ],
"task": (null|id),... | normal | {
"blob_id": "89ec04280ecfdfcba1923e2742e31d34750f894f",
"index": 4536,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass AchievementGrant(object):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass AchievementGrant(object):\n\n def on_post(self, req, resp):\n \"\"\"\n Prid... | [
0,
1,
2,
3,
4
] |
# Time :O(N) space: O(1)
def swap(arr, start, end):
while start < end:
arr[start], arr[end] = arr[end], arr[start]
start += 1
end -= 1
def rotation(arr, k, n):
k = k % n
swap(arr, 0, k-1)
print(arr)
swap(arr, k, n-1)
print(arr)
swap(arr, 0, n-1)
print(arr)
if _... | normal | {
"blob_id": "2180146da7ea745f5917ee66fd8c467437b5af4c",
"index": 6761,
"step-1": "<mask token>\n",
"step-2": "def swap(arr, start, end):\n while start < end:\n arr[start], arr[end] = arr[end], arr[start]\n start += 1\n end -= 1\n\n\n<mask token>\n",
"step-3": "def swap(arr, start, end... | [
0,
1,
2,
3,
4
] |
from math import degrees, sqrt, sin, cos, atan, radians
from pygame import Surface, draw
from pygame.sprite import Sprite
from constants import ARROW_MAX_SPEED, FLOOR_Y
from game_types import Radian, Degree
class Arrow(Sprite):
def __init__(self, color, screen, character, click_position):
Sprite.__in... | normal | {
"blob_id": "359db73de2c2bb5967723dfb78f98fb84b337b9d",
"index": 343,
"step-1": "<mask token>\n\n\nclass Arrow(Sprite):\n\n def __init__(self, color, screen, character, click_position):\n Sprite.__init__(self)\n self.color = color\n self.screen = screen\n self.character = character... | [
9,
10,
11,
13,
14
] |
#
# romaO
# www.fabiocrameri.ch/colourmaps
from matplotlib.colors import LinearSegmentedColormap
cm_data = [[0.45137, 0.22346, 0.34187],
[0.45418, 0.22244, 0.3361],
[0.45696, 0.22158, 0.33043],
[0.45975, 0.2209, 0.32483],
... | normal | {
"blob_id": "5082182af5a08970568dc1ab7a53ee5337260687",
"index": 45,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n import matplotlib.pyplot as plt\n import numpy as np\n try:\n from viscm import viscm\n viscm(romaO_map)\n except ImportError:\n ... | [
0,
1,
2,
3,
4
] |
import unittest
import ConvertListToDict as cldf
class MyDictTestCase(unittest.TestCase):
def test_Dict(self):
# Testcase1 (len(keys) == len(values))
actualDict1 = cldf.ConvertListsToDict([1, 2, 3],['a','b','c'])
expectedDict1 = {1: 'a', 2: 'b', 3: 'c'}
self.assertEqual(actualDict1,... | normal | {
"blob_id": "3421c3b839721694945bdbb4f17183bceaed5296",
"index": 786,
"step-1": "<mask token>\n\n\nclass MyDictTestCase(unittest.TestCase):\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass MyDictTestCase(unittest.TestCase):\n\n def test_Dict(self):\n actualDict1 = cldf.Conve... | [
1,
2,
3,
4,
5
] |
#Calculadora mediante el terminal
numero1 = 0
numero2 = 0
#Preguntamos los valores
operacion = input("¿Qué operación quiere realizar (Suma / Resta / Division / Multiplicacion)?: ").upper()
numero1 = int(input("Introduzca el valor 1: "))
numero2 = int(input("Introduzca el valor 2: "))
#Realizamos las operaciones
... | normal | {
"blob_id": "5d618acc0962447554807cbb9d3546cd4e0b3572",
"index": 3005,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif operacion == 'SUMA':\n resultado = numero1 + numero2\nelif operacion == 'RESTA':\n resultado = numero1 - numero2\nelif operacion == 'DIVISION':\n resultado = numero1 / numero2... | [
0,
1,
2,
3
] |
# 5.2 Training a convnet from scratch on a "small dataset" (p.131)
# Preprocessing (p.133)
# Copying images to train, validation and test directories
import os, shutil
# The path to the directory where the original dataset was uncompressed
original_dataset_dir = 'E:/train/'
# The directory where we will store our sma... | normal | {
"blob_id": "8340872f03c1bf7c1aee0c437258ac8e44e08bb8",
"index": 7313,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nos.mkdir(base_dir)\n<mask token>\nos.mkdir(train_dir)\n<mask token>\nos.mkdir(validation_dir)\n<mask token>\nos.mkdir(test_dir)\n<mask token>\nos.mkdir(train_cats_dir)\n<mask token>\nos.m... | [
0,
1,
2,
3,
4
] |
""" Contains different comparator classes for model output data structures.
"""
import copy
def tuple_to_string(tuptup):
""" Converts a tuple to its string representation. Uses different separators (;, /, |) for
different depths of the representation.
Parameters
----------
tuptup : list
... | normal | {
"blob_id": "9c935e9ef298484d565256a420b867e800c3df55",
"index": 3243,
"step-1": "<mask token>\n\n\nclass NVCComparator:\n \"\"\" NVC response comparator. Performs the evaluation based on NVC and non-NVC classes.\n\n \"\"\"\n\n @staticmethod\n def compare(obj_a, obj_b):\n \"\"\" Compares two r... | [
3,
6,
7,
10,
12
] |
#!/usr/bin/env python
kube_description= \
"""
Compute Server
"""
kube_instruction= \
"""
Not instructions yet
"""
#
# Standard geni-lib/portal libraries
#
import geni.portal as portal
import geni.rspec.pg as PG
import geni.rspec.emulab as elab
import geni.rspec.igext as IG
import geni.urn as URN
#
# PhantomNet ext... | normal | {
"blob_id": "ff7a865822a4f8b343ab4cb490c24d6d530b14e1",
"index": 934,
"step-1": "<mask token>\n",
"step-2": "<mask token>\npc.verifyParameters()\n<mask token>\ntour.Description(IG.Tour.TEXT, kube_description)\ntour.Instructions(IG.Tour.MARKDOWN, kube_instruction)\nrspec.addTour(tour)\npc.printRequestRSpec(rspe... | [
0,
1,
2,
3,
4
] |
from django.db import models
class FoodCategory(models.Model):
id = models.AutoField(primary_key=True)
name = models.CharField(max_length=200, default='')
class Meta:
db_table = 'kitchenrock_category'
def __str__(self):
return self.name
| normal | {
"blob_id": "9bb1fc4df80d183c70d70653faa3428964b93a94",
"index": 9494,
"step-1": "<mask token>\n\n\nclass FoodCategory(models.Model):\n <mask token>\n <mask token>\n\n\n class Meta:\n db_table = 'kitchenrock_category'\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass FoodCategory(models.... | [
1,
2,
3,
4
] |
#!/usr/bin/python
L=['ABC','ABC']
con1=[]
for i in range (0,len(L[1])):
#con.append(L[1][i])
con=[]
for j in range (0, len(L)):
print(L[j][i])
con.append(L[j][i])
con1.append(con)
con2=[]
for k in range (0,len(con1)):
if con1[k].count('A')==2:
con2.append('a')
elif con1[k].count('B')... | normal | {
"blob_id": "beb9fe8e37a4f342696a90bc624b263e341e4de5",
"index": 5459,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(0, len(L[1])):\n con = []\n for j in range(0, len(L)):\n print(L[j][i])\n con.append(L[j][i])\n con1.append(con)\n<mask token>\nfor k in range(0, len... | [
0,
1,
2,
3
] |
# -*- coding: utf-8 -*-
import scrapy
from scrapy.linkextractors import LinkExtractor
from scrapy.spiders import CrawlSpider, Rule
class ItemCrawlSpider(CrawlSpider):
name = 'auction_crwal'
allowed_domains = ['itempage3.auction.co.kr']
def __init__(self, keyword=None, *args, **kwargs):
super(Item... | normal | {
"blob_id": "cba12d076ed8cba84501983fda9bdce8312f2618",
"index": 6337,
"step-1": "<mask token>\n\n\nclass ItemCrawlSpider(CrawlSpider):\n <mask token>\n <mask token>\n\n def __init__(self, keyword=None, *args, **kwargs):\n super(ItemCrawlSpider, self).__init__(*args, **kwargs)\n keyword.re... | [
2,
3,
4,
5,
6
] |
# Generated by Django 3.1.2 on 2021-07-02 05:38
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('asset', '0001_initial'),
]
operations = [
migrations.RemoveField(
model_name='balance',
name='title',
),
]
| normal | {
"blob_id": "257f18db95e069c037341d2af372269e988b0a80",
"index": 536,
"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 = [('asset', '000... | [
0,
1,
2,
3,
4
] |
# adventofcode.com
# day19
from collections import defaultdict
INPUTFILE = 'input/input19'
TEST = False
TESTCASE = ('HOH', ['H => HO\n', 'H => OH\n', 'O => HH\n'], ['OHOH', 'HOOH', 'HHHH', 'HOHO'])
def find_idx(string, substring):
""" iterator that returns the index of the next occurence of substring
wr... | normal | {
"blob_id": "e6fa1202d829fb553423998cdbad13684405437c",
"index": 8483,
"step-1": "# adventofcode.com\n# day19\n\nfrom collections import defaultdict\n\nINPUTFILE = 'input/input19'\n\nTEST = False\nTESTCASE = ('HOH', ['H => HO\\n', 'H => OH\\n', 'O => HH\\n'], ['OHOH', 'HOOH', 'HHHH', 'HOHO'])\n\ndef find_idx(str... | [
0
] |
import time
class SequenceHeuristic(object):
def __init__(self, minChanges, minDuration, noMotionDelay):
self._minChanges = minChanges
self._minDuration = minDuration
self._noMotionDelay = noMotionDelay
self._duration = 0
def isValid(self, image, data):
numOfChanges... | normal | {
"blob_id": "e07bd4cd13209bff8bc1119a619a2954abd52592",
"index": 1515,
"step-1": "<mask token>\n\n\nclass SequenceHeuristic(object):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass SequenceHeuristic(object):\n\n def __init__(self, minChanges, minDuration, noMotionDelay):\n ... | [
1,
2,
3,
4,
5
] |
# coding=utf-8
import datetime
from django.http import JsonResponse
from django.shortcuts import render, redirect
from models import *
from hashlib import sha1
from user_decorators import user_login
from df_goods.models import GoodsInfo
# Create your views here.
def register(request):
context={'title':'注册','top':'0... | normal | {
"blob_id": "1ef40d4162ca1b1bd6a5a5010485c78eb9d8d736",
"index": 9621,
"step-1": "<mask token>\n\n\ndef register(request):\n context = {'title': '注册', 'top': '0'}\n return render(request, 'df_user/register.html', context)\n\n\ndef login(request):\n context = {'title': '登录', 'top': '0'}\n return rende... | [
6,
7,
9,
11,
12
] |
""""
articulo
cliente
venta
ventadet
"""
class Articulo:
def __init__(self,cod,des,pre,stoc):
self.codigo=cod
self.descripcion = des
self.precio=pre
self.stock=stoc
class ventaDetalle:
def __init__(self,pro,pre,cant):
self.producto=pro
sel... | normal | {
"blob_id": "f70f66926b9e2bf8b387d481263493d7f4c65397",
"index": 516,
"step-1": "<mask token>\n\n\nclass ventaDetalle:\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass ventaDetalle:\n\n def __init__(self, pro, pre, cant):\n self.producto = pro\n self.precio = pre\n self.cantidad... | [
1,
2,
3,
4,
5
] |
# 1장 말뭉치와 워드넷 - 외부 말뭉치 다운로드, 로드하고 액세스하기
from nltk.corpus import CategorizedPlaintextCorpusReader
from random import randint
# 말뭉치 읽기
reader = CategorizedPlaintextCorpusReader(r'/workspace/NLP_python/tokens', r'.*\.txt', cat_pattern=r'(\w+)/*')
print(reader.categories())
print(reader.fileids())
# 샘플 문서 출력
# pos, neg 카... | normal | {
"blob_id": "81cec5c1f28e92bf8e4adc2e2c632e072ed1f901",
"index": 5765,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(reader.categories())\nprint(reader.fileids())\n<mask token>\nprint(fileP)\nprint(fileN)\nfor w in reader.words(fileP):\n print(w + ' ', end='')\n if w is '.':\n print()... | [
0,
1,
2,
3,
4
] |
from platypush.message.response import Response
class CameraResponse(Response):
pass
# vim:sw=4:ts=4:et:
| normal | {
"blob_id": "4c38d0487f99cdc91cbce50079906f7336e51482",
"index": 5462,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass CameraResponse(Response):\n pass\n",
"step-3": "from platypush.message.response import Response\n\n\nclass CameraResponse(Response):\n pass\n",
"step-4": "from platypu... | [
0,
1,
2,
3
] |
# encoding=UTF-8
# This file serves the project in production
# See http://wsgi.readthedocs.org/en/latest/
from __future__ import unicode_literals
from moya.wsgi import Application
application = Application(
"./", ["local.ini", "production.ini"], server="main", logging="prodlogging.ini"
)
| normal | {
"blob_id": "cb0be932813a144cfb51b3aa2f6e0792e49c4945",
"index": 3021,
"step-1": "<mask token>\n",
"step-2": "<mask token>\napplication = Application('./', ['local.ini', 'production.ini'], server=\n 'main', logging='prodlogging.ini')\n",
"step-3": "from __future__ import unicode_literals\nfrom moya.wsgi i... | [
0,
1,
2,
3
] |
#Main program:
#reads IMU data from arduino uart
#receives PS3 Controller input
#Mantains Controller input frequency with CST
#!/usr/bin/env python
from map import mapControllerToDeg
from map import constrain
from map import wrap_180
from map import motorOutputLimitHandler
from uart1 import IMUDevice
import socket
fro... | normal | {
"blob_id": "5626e5a4a448630fbbbc92a67ae08f3ed24e1b9e",
"index": 4417,
"step-1": "#Main program:\n#reads IMU data from arduino uart\n#receives PS3 Controller input\n#Mantains Controller input frequency with CST\n\n#!/usr/bin/env python\nfrom map import mapControllerToDeg\nfrom map import constrain\nfrom map impo... | [
0
] |
from unittest import TestCase
from ch4.array_to_btree import to_btree
from ch4.is_subtree import is_subtree
class IsSubtreeTest(TestCase):
def test_should_be_subtree(self):
container = to_btree([1, 2, 3, 4, 5, 6])
contained = to_btree([1, 3, 2])
self.assertTrue(is_subtree(container, conta... | normal | {
"blob_id": "51f7faaad29379daa58875c7b35d9ccf569c8766",
"index": 6801,
"step-1": "<mask token>\n\n\nclass IsSubtreeTest(TestCase):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass IsSubtreeTest(TestCase):\n <mask token>\n\n def test_should_not_be_subtree(self):\n containe... | [
1,
2,
3,
4
] |
#!/usr/bin/env python
###########################################################################
# 1) connect to the MQTT broker
# 2) subscribe to the available data streams
# 3) log to google sheets
# 4) notify on critical events on the telegram channel
###############################################################... | normal | {
"blob_id": "0295d6ba962d099e76110c7a0e39748e3163e300",
"index": 5541,
"step-1": "<mask token>\n\n\ndef getUTC_TIME():\n return datetime.datetime.utcnow()\n\n\ndef pushSample(sample, topic):\n global client\n client.publish(topic, str(sample))\n\n\n<mask token>\n\n\ndef on_connect(client, userdata, flag... | [
13,
15,
16,
17,
18
] |
from pybrain3.datasets import SupervisedDataSet
inputDataSet = SupervisedDataSet(35, 20) #Creating new DataSet
#A
inputDataSet.addSample(( #Adding first sample to dataset
-1, 1, 1, 1, -1,
1, -1, -1, -1, 1,
1, -1, -1, -1, 1,
1, 1, 1, 1, 1,
1, -1, -1, -1, 1,
1, -1,... | normal | {
"blob_id": "a2569ccd509fa755f4cad026f483bcf891c6fb41",
"index": 8120,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ninputDataSet.addSample((-1, 1, 1, 1, -1, 1, -1, -1, -1, 1, 1, -1, -1, -1, 1,\n 1, 1, 1, 1, 1, 1, -1, -1, -1, 1, 1, -1, -1, -1, 1, 1, -1, -1, -1, 1), (\n 1, 0, 0, 0, 0, 0, 0, 0, 0, 0... | [
0,
1,
2,
3,
4
] |
from framework import *
from pebble_game import *
from constructive_pebble_game import *
from nose.tools import ok_
import numpy as np
# initialise the seed for reproducibility np.random.seed(102)
fw_2d = create_framework([0,1,2,3], [(0,1), (0,3), (1,2), (1,3), (2,3)], [(2,3), (4,4), (5,2), (1,1)])
# a 3d fw constric... | normal | {
"blob_id": "4e31619efcaf6eeab3b32116b21e71de8202aee2",
"index": 8646,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nok_(is_inf_rigid(fw_2d, 2))\nok_(not is_inf_rigid(fw_3d, 3))\nok_(is_inf_rigid(fw_1d, 1))\n<mask token>\nprint(len(rand_fw.nodes))\ndraw_framework(rand_fw)\n<mask token>\nprint(R)\nprint(... | [
0,
1,
2,
3,
4
] |
import numpy
from sklearn.ensemble import RandomForestClassifier
from sklearn.ensemble import GradientBoostingClassifier
from sklearn.cross_validation import cross_val_score
lag = 10
print "Loading train_data..."
train_data = numpy.loadtxt("../KddJavaToolChain/train_timelines_final.csv",
delimiter=",")
print... | normal | {
"blob_id": "68d37421b71d595510a1439c06cc31d00c23c277",
"index": 1125,
"step-1": "import numpy\nfrom sklearn.ensemble import RandomForestClassifier\nfrom sklearn.ensemble import GradientBoostingClassifier\nfrom sklearn.cross_validation import cross_val_score\n\nlag = 10\n\nprint \"Loading train_data...\"\ntrain_... | [
0
] |
#print 'g'
class Client:
def __init__(self, mechanize, WEBSERVICE_IP,WEBSERVICE_PORT, FORM_INPUT_PATH, dat , data_id = 'data', rasp_id_id = 'rasp_id',password = 'pass'):
self.WEBSERVICE_PORT = WEBSERVICE_PORT
self.mechanize = mechanize
self.WEBSERVICE_IP = WEBSERVICE_IP
self.FORM_INPUT_P... | normal | {
"blob_id": "3366d1d4ecc4cc9f971dff0c8adfbadc5511cc9e",
"index": 5403,
"step-1": "#print 'g'\nclass Client:\n def __init__(self, mechanize, WEBSERVICE_IP,WEBSERVICE_PORT, FORM_INPUT_PATH, dat , data_id = 'data', rasp_id_id = 'rasp_id',password = 'pass'):\n self.WEBSERVICE_PORT = WEBSERVICE_PORT\n ... | [
0
] |
# -*- coding: utf-8 -*-
from euler.baseeuler import BaseEuler
from os import path, getcwd
def get_name_score(l, name):
idx = l.index(name) + 1
val = sum([(ord(c) - 64) for c in name])
return idx * val
class Euler(BaseEuler):
def solve(self):
fp = path.join(getcwd(), 'euler/resources/names.t... | normal | {
"blob_id": "40d08bfa3286aa30b612ed83b5e9c7a29e9de809",
"index": 6540,
"step-1": "<mask token>\n\n\nclass Euler(BaseEuler):\n\n def solve(self):\n fp = path.join(getcwd(), 'euler/resources/names.txt')\n with open(fp, 'r') as f:\n names = sorted([name for name in f.read().replace('\"',... | [
3,
4,
5,
6,
7
] |
# -*- coding: utf-8 -*-
from django.contrib.auth.models import User
from django.contrib.auth.admin import UserAdmin
from django.contrib import admin
from accounts.models import (UserProfile)
admin.site.register(UserProfile)
admin.site.unregister(User)
class CustomUserAdmin(UserAdmin):
list_display = ('username', ... | normal | {
"blob_id": "c95eaa09241428f725d4162e0e9f6ed3ce6f8fdd",
"index": 6709,
"step-1": "<mask token>\n\n\nclass CustomUserAdmin(UserAdmin):\n <mask token>\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass CustomUserAdmin(UserAdmin):\n list_display = 'username', 'email', 'is_staff', 'is... | [
1,
2,
3,
4,
5
] |
import pygame
import time
import math
from pygame.locals import *
from pygux.widgets.widget import Widget, hlBox
from pygux.colours import Colours
class Sprite(Widget):
def __init__(self, x, y, w, h, image=None, callback=None, **kw):
"""Sprite widget
"""
Widget.__init__(self, x, y, w, h, ... | normal | {
"blob_id": "0003d104a4dcd5a5b2357016cbc0317738c2cd3c",
"index": 2007,
"step-1": "<mask token>\n\n\nclass Sprite(Widget):\n\n def __init__(self, x, y, w, h, image=None, callback=None, **kw):\n \"\"\"Sprite widget\n \"\"\"\n Widget.__init__(self, x, y, w, h, **kw)\n if image:\n ... | [
3,
4,
5,
6
] |
from tkinter import *
from tkinter.scrolledtext import ScrolledText
def load():
with open(filename.get()) as file:
# delete every between line 1 char 0 to END
# INSERT is the current insertion point
contents.delete('1.0', END)
contents.insert(INSERT, file.read())
def save():
with open(filename.g... | normal | {
"blob_id": "fcf4cb5c47e4aa51d97b633ecdfec65246e82bd8",
"index": 9011,
"step-1": "<mask token>\n\n\ndef load():\n with open(filename.get()) as file:\n contents.delete('1.0', END)\n contents.insert(INSERT, file.read())\n\n\ndef save():\n with open(filename.get(), 'w') as file:\n file.wr... | [
2,
3,
4,
5,
6
] |
import sys
from pypregel import Pypregel
from pypregel.vertex import Vertex, Edge
from pypregel.reader import Reader
from pypregel.writer import Writer
from pypregel.combiner import Combiner
class PageRankVertex(Vertex):
def compute(self):
if self.superstep() >= 1:
s = 0
while sel... | normal | {
"blob_id": "6db7189d26c63ca9f9667045b780ec11994bac28",
"index": 788,
"step-1": "<mask token>\n\n\nclass PageRankReader(Reader):\n\n def read_num_of_vertices(self):\n line = self.config_fp.readline()\n return int(line)\n\n def read_vertex(self):\n line = self.graph_fp.readline()\n ... | [
7,
9,
10,
12,
13
] |
"""
Package with a facade to the several expansion strategies.
"""
from acres.resolution import resolver
__all__ = ['resolver']
| normal | {
"blob_id": "e31267871453d87aee409f1c751c36908f7f151a",
"index": 804,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n__all__ = ['resolver']\n",
"step-3": "<mask token>\nfrom acres.resolution import resolver\n__all__ = ['resolver']\n",
"step-4": "\"\"\"\nPackage with a facade to the several expansion ... | [
0,
1,
2,
3
] |
#!/usr/bin/python3
"""takes in a URL and an email address, sends a POST request to the passed
URL with the email as a parameter, and finally
displays the body of the response.
"""
import requests
import sys
if __name__ == "__main__":
url_arg = sys.argv[1]
email = sys.argv[2]
params = {'email': email}
... | normal | {
"blob_id": "0d9c50e55df5aa5614bd5a9679729cf7fa69c5df",
"index": 1461,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n url_arg = sys.argv[1]\n email = sys.argv[2]\n params = {'email': email}\n response = requests.post(url_arg, data=params)\n print(response.text)... | [
0,
1,
2,
3
] |
import numpy as np
import random
from math import inf
class Particle:
"""
Represents a particle of the Particle Swarm Optimization algorithm.
"""
def __init__(self, lower_bound, upper_bound):
"""
Creates a particle of the Particle Swarm Optimization algorithm.
:param lower_bou... | normal | {
"blob_id": "096df1db4d8673ae7886a1b2022148c92f64a23e",
"index": 1725,
"step-1": "<mask token>\n\n\nclass ParticleSwarmOptimization:\n <mask token>\n\n def __init__(self, hyperparams, lower_bound, upper_bound):\n self.lower_bound = lower_bound\n self.upper_bound = upper_bound\n self.nu... | [
5,
7,
9,
12,
13
] |
import datetime
import json
import re
import time
import discord
from utils.ext import standards as std, checks, context, logs
DISCORD_INVITE = '(discord(app\.com\/invite|\.com(\/invite)?|\.gg)\/?[a-zA-Z0-9-]{2,32})'
EXTERNAL_LINK = '((https?:\/\/(www\.)?|www\.)[-a-zA-Z0-9@:%._\+~#=]{1,256}\.[a-zA-Z0-9()]{1,6})'
EVE... | normal | {
"blob_id": "10c9566503c43e806ca89e03955312c510092859",
"index": 5346,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef findWord(word):\n return re.compile('\\\\b({0})\\\\b'.format(word), flags=re.IGNORECASE).search\n\n\nasync def managePunishment(ctx, punishment, reason):\n await ctx.message... | [
0,
2,
3,
4,
5
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
help_txt = """
:help, show this help menu. :help [command] for detail
:dict [word], only find translation on dict.cn
:google [sentence], only find translation on google api
:lan2lan [sentence], translate from one language to another language
:add [word], add new word to yo... | normal | {
"blob_id": "3fadb91bd2367819a540f687530f4b48ed878423",
"index": 9149,
"step-1": "<mask token>\n",
"step-2": "help_txt = \"\"\"\n:help, show this help menu. :help [command] for detail\n:dict [word], only find translation on dict.cn\n:google [sentence], only find translation on google api\n:lan2lan [sentence], ... | [
0,
1,
2
] |
# Generated by Django 2.1 on 2018-12-05 00:02
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('PleniApp', '0006_auto_20181203_1144'),
]
operations = [
migrations.CreateModel(
name='Comment',
... | normal | {
"blob_id": "ccb6973910dba5897f6a12be23c74a35e848313b",
"index": 4005,
"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 = [('PleniApp', ... | [
0,
1,
2,
3,
4
] |
import numpy as np
from sklearn.metrics import mutual_info_score
def mimic_binary(max_iter=100, fitness_func=None, space=None):
assert fitness_func is not None
assert space is not None
idx = np.random.permutation(np.arange(len(space)))
pool = space[idx[:int(len(space)/2)]] # randomly sample 50% of th... | normal | {
"blob_id": "360e661d8538a8f40b7546a54e9a9582fa64bd67",
"index": 700,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef mutual_info(parent, child):\n parent = [int(x) for x in parent]\n child = [int(x) for x in child]\n return mutual_info_score(parent, child)\n",
"step-3": "<mask token>\n... | [
0,
1,
2,
3,
4
] |
from setuptools import setup, find_packages
__version__ = '2.0'
setup(
name='sgcharts-pointer-generator',
version=__version__,
python_requires='>=3.5.0',
install_requires=[
'tensorflow==1.10.0',
'pyrouge==0.1.3',
'spacy==2.0.12',
'en_core_web_sm==2.0.0',
'sgchar... | normal | {
"blob_id": "e52b01cc7363943f5f99b1fa74720c6447b1cfae",
"index": 6266,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsetup(name='sgcharts-pointer-generator', version=__version__,\n python_requires='>=3.5.0', install_requires=['tensorflow==1.10.0',\n 'pyrouge==0.1.3', 'spacy==2.0.12', 'en_core_web_... | [
0,
1,
2,
3,
4
] |
import data
import sub_vgg19
import time
import tensorflow as tf
model_syn = sub_vgg19.vgg19_syn
model_asy = sub_vgg19.vgg19_asy
train_x = data.train_x
train_y = data.train_y
test_x = data.test_x
test_y = data.test_y
def input_fn(images, labels, epochs, batch_size):
data = tf.data.Dataset.from_tensor_slices((ima... | normal | {
"blob_id": "ef6f91af5f500745fdcc23947a7e1764061c608c",
"index": 2368,
"step-1": "<mask token>\n\n\ndef input_fn(images, labels, epochs, batch_size):\n data = tf.data.Dataset.from_tensor_slices((images, labels))\n data = data.repeat(epochs).batch(batch_size)\n return data\n\n\n<mask token>\n",
"step-2... | [
1,
2,
3,
4,
5
] |
import json
import decimal
import threading
import websocket
from time import sleep
from supervisor.core.utils.math import to_nearest
def find_item_by_keys(keys, table, match_data):
for item in table:
matched = True
for key in keys:
if item[key] != match_data[key]:
matc... | normal | {
"blob_id": "ea4ec2e605ab6e8734f7631fe298c93467908b5f",
"index": 9582,
"step-1": "<mask token>\n\n\nclass TrailingShell:\n <mask token>\n\n def __init__(self, order, offset: int, tick_size: float, test=True,\n init_ws=True):\n self.tick_size = tick_size\n self.exited = False\n s... | [
14,
15,
16,
18,
25
] |
# 백준 문제(2021.5.22)
# 10039번) 상현이가 가르치는 아이폰 앱 개발 수업의 수강생은 원섭, 세희, 상근, 숭, 강수이다.
# 어제 이 수업의 기말고사가 있었고, 상현이는 지금 학생들의 기말고사 시험지를 채점하고 있다.
# 기말고사 점수가 40점 이상인 학생들은 그 점수 그대로 자신의 성적이 된다.
# 하지만, 40점 미만인 학생들은 보충학습을 듣는 조건을 수락하면 40점을 받게 된다.
# 보충학습은 거부할 수 없기 때문에, 40점 미만인 학생들은 항상 40점을 받게 된다.
# 학생 5명의 점수가 주어졌을 때, 평균 점수를 구하는 프로그램을 작성... | normal | {
"blob_id": "4a13a0d7aa2371d7c8963a01b7cc1b93f4110d5e",
"index": 5356,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(5):\n score = int(input())\n if score < 40:\n score = 40\n result += score\nprint(result // 5)\n",
"step-3": "result = 0\nfor i in range(5):\n score = ... | [
0,
1,
2,
3
] |
# encoding=utf8
from selenium import webdriver
from selenium.webdriver.common.desired_capabilities import DesiredCapabilities
from selenium.common.exceptions import NoSuchElementException, ElementNotVisibleException
from selenium.webdriver.support.select import Select
import time
import threading
import random
import ... | normal | {
"blob_id": "ae775e25179546156485e15d05491e010cf5daca",
"index": 9360,
"step-1": "<mask token>\n\n\nclass BookRoomThread(threading.Thread):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask ... | [
3,
8,
15,
17,
18
] |
# Generated by Django 3.0 on 2020-05-04 16:15
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
('game_skeleton', '0001_initial'),
('contenttypes', '0002_remove_content_type_name'),
('clas... | normal | {
"blob_id": "a718d82713503c4ce3d94225ff0db04991ad4094",
"index": 9744,
"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 pandas as pd
def _get_site_name(f,i):
data_file = f +"\\"+"new_desc_sele_data.csv"
site_name=pd.read_csv(data_file)["SITE_ID"][i]
return site_name
def _get_site_DD_dataset_csv(f,i):
'''获取经过全部数据集（经过全部的特征选择）'''
site_path=_get_site_folder(f,i)
data_path=site_path+"\\data_confirm.csv"
... | normal | {
"blob_id": "c034fba0b9204545b00ba972a17e63cf9c20854e",
"index": 3930,
"step-1": "<mask token>\n\n\ndef _get_site_name(f, i):\n data_file = f + '\\\\' + 'new_desc_sele_data.csv'\n site_name = pd.read_csv(data_file)['SITE_ID'][i]\n return site_name\n\n\n<mask token>\n\n\ndef _get_version_res_folder(f, ve... | [
3,
4,
6,
7,
8
] |
import glob
import os
import partition
import pickle
import matplotlib.pyplot as plt
import numpy as np
from Cluster import fishermans_algorithm
import argparse
parser = argparse.ArgumentParser()
plt.ion()
parser.add_argument("--fish", help="flag for using fisherman's algorithm")
parser.add_argument("--heat", help="... | normal | {
"blob_id": "805bc144a4945b46b398853e79ded17370ada380",
"index": 3940,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nplt.ion()\nparser.add_argument('--fish', help=\"flag for using fisherman's algorithm\")\nparser.add_argument('--heat', help='flag for using heatmap')\nparser.add_argument('--object', help... | [
0,
1,
2,
3,
4
] |
import numpy
def CALCB1(NVAC,KGAS,LGAS,ELECEN,ISHELL,L1):
# IMPLICIT #real*8(A-H,O-Z)
# IMPLICIT #integer*8(I-N)
#CHARACTER*6
# SCR=""#(17)
# SCR1=""#(17)
#COMMON/GENCAS/
global ELEV#[17,79]
global NSDEG#(17)
global AA#[17]
global BB#[17]
global SCR,SCR1
#COMMON/MIXC/
global PRSH#(6,3,17,17)
global ESH#(6... | normal | {
"blob_id": "09698649510348f92ea3b83f89ffa1c844929b8f",
"index": 3332,
"step-1": "<mask token>\n\n\ndef CALCB2(NVAC, KGAS, LGAS, ELECEN, ISHELL, L1):\n global ELEV\n global NSDEG\n global AA\n global BB\n global SCR, SCR1\n global PRSH\n global ESH\n global AUG\n global RAD\n global... | [
3,
4,
5,
6,
7
] |
import collections
def range(state):
ran = state["tmp"]["analysis"]["range"]
rang = {
key : [ state["rank"][i] for i in val & ran ]
for key, val in state["tmp"]["analysis"]["keys"].items()
if val & ran
}
for item in state["tmp"]["items"]:
item.setdefault("rank", 0)
item_keys = set(item.keys())
rang_... | normal | {
"blob_id": "51868f26599c5878f8eb976d928c30d0bf61547d",
"index": 9701,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef range(state):\n ran = state['tmp']['analysis']['range']\n rang = {key: [state['rank'][i] for i in val & ran] for key, val in\n state['tmp']['analysis']['keys'].items(... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/python
# -*- coding: utf-8 -*-
import optparse
import logging
from pyspark import SparkContext
from pyspark import SparkConf
logger = logging.getLogger(__name__)
def create_context(appName):
"""
Creates Spark HiveContext
"""
logger.info("Creating Spark context - may take some while")
... | normal | {
"blob_id": "d4b432735a112ccb293bf2f40929846b4ce34cd0",
"index": 9348,
"step-1": "<mask token>\n\n\ndef create_context(appName):\n \"\"\"\n Creates Spark HiveContext\n \"\"\"\n logger.info('Creating Spark context - may take some while')\n conf = SparkConf()\n conf.set('spark.hadoop.validateOutp... | [
4,
5,
6,
7,
8
] |
import mmap;
import random;
def shuffle():
l_digits = ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9'];
random.shuffle(l_digits);
return "".join(l_digits);
with open("hello.txt", "r+") as f:
map = mmap.mmap(f.fileno(), 1000);
l_i = 0;
for l_digit in shuffle():
map[l_i] = l_digit;
... | normal | {
"blob_id": "b0468e58c4d0387a92ba96e8fb8a876ece256c78",
"index": 6507,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef shuffle():\n l_digits = ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9']\n random.shuffle(l_digits)\n return ''.join(l_digits)\n\n\n<mask token>\n",
"step-3": "<mask ... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/python
from setuptools import setup, find_packages
import os
EXTRAS_REQUIRES = dict(
test=[
'pytest>=2.2.4',
'mock>=0.8.0',
'tempdirs>=0.0.8',
],
dev=[
'ipython>=0.13',
],
)
# Tests always depend on all other requirements, except dev
for k,v in EX... | normal | {
"blob_id": "f531af47431055866db72f6a7181580da461853d",
"index": 6780,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor k, v in EXTRAS_REQUIRES.iteritems():\n if k == 'test' or k == 'dev':\n continue\n EXTRAS_REQUIRES['test'] += v\n<mask token>\nwith open(path) as fp:\n long_description... | [
0,
1,
2,
3,
4
] |
import math
import numpy as np
import cv2
from matplotlib import pyplot as plt
from sklearn.cluster import KMeans
from sklearn import metrics
from scipy.spatial.distance import cdist
if (__name__ == "__main__"):
cap = cv2.VideoCapture('dfd1.mp4')
mog = cv2.createBackgroundSubtractorMOG2(detectSha... | normal | {
"blob_id": "28a0ae0492fb676044c1f9ced7a5a4819e99a8d9",
"index": 8890,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n cap = cv2.VideoCapture('dfd1.mp4')\n mog = cv2.createBackgroundSubtractorMOG2(detectShadows=0)\n count = 0\n while True:\n list = []\n ... | [
0,
1,
2,
3
] |
# -*-coding:utf-8 -*
# Copyright (c) 2011-2015, Intel Corporation
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without modification,
# are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice, thi... | normal | {
"blob_id": "3c2873add66172a5ed038949c31d514dcd5f26b3",
"index": 7152,
"step-1": "# -*-coding:utf-8 -*\n\n# Copyright (c) 2011-2015, Intel Corporation\n# All rights reserved.\n#\n# Redistribution and use in source and binary forms, with or without modification,\n# are permitted provided that the following condit... | [
0
] |
from django.shortcuts import render
from django_filters.rest_framework import DjangoFilterBackend
from django.views.decorators.csrf import csrf_exempt
from rest_framework.parsers import JSONParser
from django.http import JsonResponse, Http404
from .serializers import *
from .models import *
from .filter import *
from r... | normal | {
"blob_id": "e0c6fb414d87c0a6377538089226e37b044edc70",
"index": 8383,
"step-1": "<mask token>\n\n\n@csrf_exempt\ndef TBGRApi(request, tbgrno=0):\n if request.method == 'GET':\n tbgrs = TBGR.objects.all()\n tbgrs_serializer = TBGRSerializer(tbgrs, many=True)\n return JsonResponse(tbgrs_se... | [
3,
4,
5,
7,
8
] |
import random
import numpy as np
import os
import torch
class Agent:
def __init__(self):
self.model = torch.load(__file__[:-8] + "/agent.pkl")
def act(self, state):
state = torch.tensor(state)
with torch.no_grad():
return self.model(state.unsqueeze(0)).max(1)[1].it... | normal | {
"blob_id": "50a4084dd3028acc2e6788e77794c100efcb3fac",
"index": 132,
"step-1": "<mask token>\n\n\nclass Agent:\n\n def __init__(self):\n self.model = torch.load(__file__[:-8] + '/agent.pkl')\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Agent:\n\n def __init__(self):\... | [
2,
3,
4,
5,
6
] |
import pytest
import gadget
@pytest.mark.parametrize('invalid_line', [
'beginningGDG::',
'beginning::end',
'nothing',
])
def test_parse_invalid_line(invalid_line):
assert gadget.parse_log_line(invalid_line) is None
| normal | {
"blob_id": "0dd361239d85ed485594ac0f5e7e2168f0684544",
"index": 915,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@pytest.mark.parametrize('invalid_line', ['beginningGDG::',\n 'beginning::end', 'nothing'])\ndef test_parse_invalid_line(invalid_line):\n assert gadget.parse_log_line(invalid_lin... | [
0,
1,
2,
3
] |
#!/usr/bin/python
"""
Create a 1024-host network, and run the CLI on it.
If this fails because of kernel limits, you may have
to adjust them, e.g. by adding entries to /etc/sysctl.conf
and running sysctl -p. Check util/sysctl_addon.
This is a copy of tree1024.py that is using the Containernet
constructor. Containernet... | normal | {
"blob_id": "9c3ca2fa43c6a34d7fe06517812a6d0bf5d6dbe1",
"index": 4029,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n setLogLevel('info')\n network = TreeContainerNet(depth=2, fanout=100, switch=OVSSwitch)\n network.run(CLI, network)\n",
"step-3": "<mask token>\nfr... | [
0,
1,
2,
3
] |
#
# purpose: setup file to install the compiled-language python libraries
# usage: python setup.py config_fc --f90flags="-O2 -fopenmp" install --prefix=$PWD
#
from numpy.distutils.core import Extension
c_array_sqrt = Extension (name = "c_array_sqrt_omp",
sources = ["./src/c_array_sqrt_omp.... | normal | {
"blob_id": "c24bf42cfeaa1fb8ac188b9e08146762e0e86fed",
"index": 1542,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n from numpy.distutils.core import setup\n setup(name='array-sqrt-openmp', description=\n 'Illustration of Python extensions using OpenMP', author=... | [
0,
1,
2,
3,
4
] |
from django.contrib.auth.models import User
from django.test import Client
from django.utils.timezone import localdate
from pytest import fixture
from operations.models import ToDoList
@fixture
def user(db):
return User.objects.create(
username='test', email='saidazimovaziza@gmail.com',
password=... | normal | {
"blob_id": "347d468f15dee8a8219d201251cedffe21352f7c",
"index": 8813,
"step-1": "<mask token>\n\n\n@fixture\ndef authenticated_author_client(user, client: Client) ->Client:\n token = Token.objects.get_or_create(user=user)[0].key\n client.defaults['HTTP_AUTHORIZATION'] = f'Token {token}'\n print(client)... | [
1,
2,
3,
4,
5
] |
def findOrder(numCourses,prerequisites):
d={}
for i in prerequisites:
if i[0] not in d:
d[i[0]]=[i[1]]
if i[1] not in d:
d[i[1]]=[]
else:
d[i[0]].append(i[1])
res=[]
while d:
for i in range(numCourses):
if d[i] == []:
res.append(d[i])
tmp=d[i]
del d[i]
for j in d:
if tmp i... | normal | {
"blob_id": "75b13f4985fcf26fb9f7fb040554b52b13c1806d",
"index": 4848,
"step-1": "def findOrder(numCourses,prerequisites):\n\td={}\n\tfor i in prerequisites:\n\t\tif i[0] not in d:\n\t\t\td[i[0]]=[i[1]]\n\t\t\tif i[1] not in d:\n\t\t\t\td[i[1]]=[]\n\t\telse:\n\t\t\td[i[0]].append(i[1])\n\tres=[]\n\twhile d:\n\t\... | [
0
] |
from jabberbot import JabberBot, botcmd
import datetime
import logging
import sys
import time;
from config import username, password, chatroom, adminuser
class SystemInfoJabberBot(JabberBot):
@botcmd
def serverinfo( self, mess, args):
"""Displays information about the server"""
version = open(... | normal | {
"blob_id": "c9872fb536fd6552e2a5353566305555808747f7",
"index": 1777,
"step-1": "<mask token>\n\n\nclass SystemInfoJabberBot(JabberBot):\n\n @botcmd\n def serverinfo(self, mess, args):\n \"\"\"Displays information about the server\"\"\"\n version = open('/proc/version').read().strip()\n ... | [
4,
5,
6,
7,
9
] |
#17219
tot, inp = map(int, input().split())
ID_dict = {}
for _ in range(tot):
id, pw = map(str, input().split())
ID_dict[id] = pw
for _ in range(inp):
print(ID_dict[input()]) | normal | {
"blob_id": "cf7556034020d88ddb6b71b9f908c905e2f03cdb",
"index": 4076,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor _ in range(tot):\n id, pw = map(str, input().split())\n ID_dict[id] = pw\nfor _ in range(inp):\n print(ID_dict[input()])\n",
"step-3": "tot, inp = map(int, input().split())... | [
0,
1,
2,
3
] |
from eventnotipy import app
import json
json_data = open('eventnotipy/config.json')
data = json.load(json_data)
json_data.close()
username = data['dbuser']
password = data['password']
host = data['dbhost']
db_name = data['database']
email_host = data['email_host']
email_localhost = data['email_localhost']
sms_host = da... | normal | {
"blob_id": "1f0680c45afb36439c56a1d202537261df5f9afc",
"index": 5895,
"step-1": "<mask token>\n",
"step-2": "<mask token>\njson_data.close()\n<mask token>\n",
"step-3": "<mask token>\njson_data = open('eventnotipy/config.json')\ndata = json.load(json_data)\njson_data.close()\nusername = data['dbuser']\npass... | [
0,
1,
2,
3
] |
print('\n----------------概率与统计--------------------')
import numpy as np
import scipy
import sympy as sym
import matplotlib.pyplot as plt
import sklearn.datasets as sd
iris = sd.load_iris()
x1 = np.random.random([10000]) # 均匀分布
x2 = np.random.normal(2, 1, [10000]) # 正态分布
x3 = np.random.normal(5, 1, [10000]) # 正态分布
#... | normal | {
"blob_id": "1ab5c6a56ac229c5a9892a9848c62a9a19a0dda7",
"index": 3360,
"step-1": "<mask token>\n\n\ndef conv(dt1, dt2):\n return np.mean((dt1 - np.mean(dt1)) * (dt2 - np.mean(dt2)))\n\n\n<mask token>\n\n\ndef rho(p1, p2):\n return conv(p1, p2) / np.std(p1) / np.std(p2)\n\n\n<mask token>\n",
"step-2": "pr... | [
2,
4,
5,
6,
7
] |
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