code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
__author__ = 'tcaruso'
# !/usr/bin/env python
# -*- coding: utf-8 -*-
import glob
import fnmatch
import os
import sys
import warnings
from shutil import rmtree
from setuptools import find_packages, setup, Command
from collections import namedtuple
try:
from pip._internal.req import parse_requirements
except Impo... | normal | {
"blob_id": "58438a1fb0b9e620717ba262c25a43bfbf6b8824",
"index": 8100,
"step-1": "<mask token>\n\n\nclass UploadCommand(Command):\n <mask token>\n description = 'Build and publish the package.'\n user_options = []\n\n def initialize_options(self):\n pass\n\n def finalize_options(self):\n ... | [
6,
7,
9,
10,
11
] |
import os
#defaults = {"N":20, "K":3, "POP_SIZE":200, "MUT_RATE":.05, "TOURNAMENT_SIZE":2, "SELECTION":0, "CHANGE_RATE":100000, "MAX_GENS": 5000, "FILTER_LENGTH":50}
defaults = {"N":20, "K":3, "POP_SIZE":200, "MUT_RATE":.05, "TOURNAMENT_SIZE":2, "SELECTION":0, "CHANGE_RATE":100000, "MAX_GENS": 5000, "FILTER_LENGTH":"... | normal | {
"blob_id": "a826f33361ec59824f3c4a83d01e94c6b307b0a9",
"index": 9144,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor condition in conditions:\n print(condition)\n command = ['./nk_oee -MODES_RESOLUTION 10 -SEED', seed]\n dir_name = []\n for var in defaults:\n if var not in conditi... | [
0,
1,
2,
3,
4
] |
from lilaclib import *
def pre_build():
newver = _G.newver.removeprefix('amd-drm-fixes-')
for line in edit_file('PKGBUILD'):
if line.startswith('_tag'):
line = "_tag='amd-drm-fixes-" + newver + "'"
print(line)
newver2 = newver.replace("-",".")
update_pkgver_and_pkgrel(newver2)
def post_... | normal | {
"blob_id": "32eff306444966fab47815fcbae4aefb6769d29b",
"index": 9684,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef post_build():\n git_add_files('PKGBUILD')\n git_commit()\n update_aur_repo()\n",
"step-3": "<mask token>\n\n\ndef pre_build():\n newver = _G.newver.removeprefix('amd... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def scan_files(dir, pattern):
fileList = []
for root, subFolders, files in os.walk(dir):
for file in files:
if fnmatch.fnmatch(file, pattern):
fileList.append(os.path.join(root, file))
return fileList
<|reserved_special_token_0|>
<|reser... | flexible | {
"blob_id": "187c2a56ba9360b89c8ded09861091e2deedf32e",
"index": 7783,
"step-1": "<mask token>\n\n\ndef scan_files(dir, pattern):\n fileList = []\n for root, subFolders, files in os.walk(dir):\n for file in files:\n if fnmatch.fnmatch(file, pattern):\n fileList.append(os.pa... | [
1,
2,
3,
4,
5
] |
from django.conf.urls import url, include
from django.contrib import admin
from rest_framework_swagger.views import get_swagger_view
schema_view = get_swagger_view(title='Pastebin API')
urlpatterns = [
url(r'^admin/', admin.site.urls),
url(r'^doc_u/', schema_view),
url(r'^', include('o.urls', )),
url(... | normal | {
"blob_id": "891588327046e26acb9a691fa8bb9a99420712d6",
"index": 913,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nschema_view = get_swagger_view(title='Pastebin API')\nurlpatterns = [url('^admin/', admin.site.urls), url('^doc_u/', schema_view),\n url('^', include('o.urls')), url('^api/', include('r... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class AlignmentProfile:
def __init__(self, width, df, identifier):
self.ident = identifier
self.profile = np.zeros((5, width))
self.repre_sq = ''
self.seq_alignments = None
self.seq_align_counter = -1
self.calculate_profile(df)
def... | flexible | {
"blob_id": "7ae328bcfdec2d17fceb5d707f13cf495fde4469",
"index": 7490,
"step-1": "<mask token>\n\n\nclass AlignmentProfile:\n\n def __init__(self, width, df, identifier):\n self.ident = identifier\n self.profile = np.zeros((5, width))\n self.repre_sq = ''\n self.seq_alignments = No... | [
5,
7,
8,
9,
11
] |
<|reserved_special_token_0|>
class UpdateProduct(GenericAPIView):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def get(self, request, *args, **kwargs):
data = self.get_queryset()
extract_sp = self.extract_filter_data(Product_Specification.obje... | flexible | {
"blob_id": "47e9b73fc7f6b3c8295e78d0cdb5aa51ca4c5f8d",
"index": 8140,
"step-1": "<mask token>\n\n\nclass UpdateProduct(GenericAPIView):\n <mask token>\n <mask token>\n <mask token>\n\n def get(self, request, *args, **kwargs):\n data = self.get_queryset()\n extract_sp = self.extract_fil... | [
11,
13,
16,
17,
19
] |
import os
from flask import Flask, jsonify, request, abort, make_response
from flask_sqlalchemy import SQLAlchemy
from .models import User
from .config import app_config
app = Flask(__name__)
app.config.from_object(app_config[os.getenv('FLASK_ENV', 'production')])
db = SQLAlchemy(app)
@app.route('/api/v1/users/<int:u... | normal | {
"blob_id": "f4519fa82ffc6bf945c7bb36d3761a708a06f641",
"index": 5933,
"step-1": "<mask token>\n\n\n@app.route('/api/v1/users/<int:user_id>', methods=['GET'])\ndef get_user(user_id):\n try:\n user = User.query.filter_by(id=user_id).first()\n return jsonify({'user': user.serialize})\n except:\... | [
4,
6,
7,
8
] |
from django.db import models
from django.contrib.auth.models import User
# Create your models here.
class Post(models.Model):
title = models.CharField(max_length=40)
content = models.TextField()
date_published = models.DateTimeField(auto_now=True)
author = models.ForeignKey(User, on_delete=models.CASCA... | normal | {
"blob_id": "1257b90781a213ca8e07f67a33b8e847d0525653",
"index": 9354,
"step-1": "<mask token>\n\n\nclass Comment(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def __str__(self):\n return self.user.username\n\n\nclass Comment_to_comment(models.Model):\n u... | [
7,
10,
11,
12,
13
] |
import numpy as np
er = ['why','who','how','where','which','what','when','was','were','did','do','does','is','are','many','much']
qst = []
txt = None
ans = None
fnd = []
def chek_qst(qst):
global er
for h in er:
for i in qst:
if i == h:
qst.remove(i)
# qst ... | normal | {
"blob_id": "d30129248f5245560ee0d3ee786e118427e169d7",
"index": 4616,
"step-1": "<mask token>\n\n\ndef search_word(qst):\n global txt\n for h in qst:\n temp = []\n for n, l in enumerate(txt):\n if [n for i, j in enumerate(l) if h in j] != []:\n temp.append(n)\n ... | [
3,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
def fit(x, iters=1000, eps=1e-06):
"""
Fits a 2-parameter Weibull distribution to the given data using maximum-likelihood estimation.
:param x: 1d-ndarray of samples from an (unknown) distribution. Each value must satisfy x > 0.
:param iters: Maximum number of iterations
... | flexible | {
"blob_id": "b10d3d8d0ded0d2055c1abdaf40a97abd4cb2cb8",
"index": 1631,
"step-1": "<mask token>\n\n\ndef fit(x, iters=1000, eps=1e-06):\n \"\"\"\n Fits a 2-parameter Weibull distribution to the given data using maximum-likelihood estimation.\n :param x: 1d-ndarray of samples from an (unknown) distributio... | [
1,
2,
3,
4,
5
] |
"""Scans all files in this project for FIXME and TODO comments and writes them to todos.txt
has to be invoked while being in myLambda/ and not in e.g. myLambda/src"""
import sys
import os
import re
files = []
searchFiles = []
# get all subdirs and its files
for root, dirs, f in os.walk('./'):
files.append((root, f))
... | normal | {
"blob_id": "3bc6091d822fa197dcce3cd75fa9755dc9f93592",
"index": 7520,
"step-1": "\"\"\"Scans all files in this project for FIXME and TODO comments and writes them to todos.txt\nhas to be invoked while being in myLambda/ and not in e.g. myLambda/src\"\"\"\nimport sys\nimport os\nimport re\nfiles = []\nsearchFile... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
urlpatterns = [path('', Home.as_view(), name='home'), path('signup', Signup
.as_view(), name='signup'), path('login', Login.as_view(), name='login')]
<|reserved_special_token_1|>
from django.urls import path
from .views.hom... | flexible | {
"blob_id": "979a387e29867818ffad7291511ff0be40dee118",
"index": 1938,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('', Home.as_view(), name='home'), path('signup', Signup\n .as_view(), name='signup'), path('login', Login.as_view(), name='login')]\n",
"step-3": "from django.url... | [
0,
1,
2,
3
] |
import os
import time
import pickle
from configparser import ConfigParser
from slackbot import bot
from slackbot.bot import Bot
from slackbot.bot import listen_to
from elasticsearch_dsl.connections import connections
from okcom_tokenizer.tokenizers import CCEmojiJieba, UniGram
from marginalbear_elastic.query import p... | normal | {
"blob_id": "3630f83e7e6a10f42e96f8bd6fa9714232d9176b",
"index": 4552,
"step-1": "<mask token>\n\n\n@listen_to('(.*)')\ndef receive_question(message, question_string):\n if message._body['channel'] == SLACK_CHANNEL:\n try:\n query_ccjieba = ccjieba.cut(question_string.strip())\n q... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
def removdup():
train = pd.read_csv('C:\\Users\\Lenovo\\zqrbtest\\data.csv')
train = train['titlec']
train = set(train)
data = pd.DataFrame(list(train), columns=['titlec'])
data.to_csv('redup.csv', index=False, encoding='utf_8_sig')
<|reserved_special_token_0|>
<|r... | flexible | {
"blob_id": "6f3aa4e1309745265bb9d79df5f5a352e54493f9",
"index": 6313,
"step-1": "<mask token>\n\n\ndef removdup():\n train = pd.read_csv('C:\\\\Users\\\\Lenovo\\\\zqrbtest\\\\data.csv')\n train = train['titlec']\n train = set(train)\n data = pd.DataFrame(list(train), columns=['titlec'])\n data.to... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
admin.site.register(UserProfileInfo)
<|reserved_special_token_1|>
from django.contrib import admin
from basic_app.models import UserProfileInfo
admin.site.register(UserProfileInfo)
<|reserved_special_token_1|>
from django.co... | flexible | {
"blob_id": "624212a1d73ff3a3b3092ffa27912a6ae25a2484",
"index": 6826,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nadmin.site.register(UserProfileInfo)\n",
"step-3": "from django.contrib import admin\nfrom basic_app.models import UserProfileInfo\nadmin.site.register(UserProfileInfo)\n",
"step-4": ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class Rouge(Character):
def special_attack1(self, opponent, hitdamage_callback, specatt_callback):
pass
def special_attack2(self, opponent, hitdamage_callback, specatt_callback):
pass
<|reserved_special_token_0|>
def regen_resource(self):
pass
... | flexible | {
"blob_id": "36991c3191ba48b1b9dbd843e279f8fe124f1339",
"index": 73,
"step-1": "<mask token>\n\n\nclass Rouge(Character):\n\n def special_attack1(self, opponent, hitdamage_callback, specatt_callback):\n pass\n\n def special_attack2(self, opponent, hitdamage_callback, specatt_callback):\n pass... | [
5,
6,
7,
8,
9
] |
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# d... | normal | {
"blob_id": "932502c93dd7dfc095adfe2ab88b4404396d9845",
"index": 8680,
"step-1": "<mask token>\n\n\nclass TestIetAdmDriver(tf.TargetDriverFixture):\n <mask token>\n\n def test_get_target(self):\n tmp_file = six.StringIO()\n tmp_file.write(\n \"\"\"tid:1 name:iqn.2010-10.org.opensta... | [
3,
7,
8,
9,
12
] |
#Charlie Quinn if.py
#Check < in an 'if' statement
#use a 'while' loop to make testing easier
def income_input(prompt_message):
prompt = prompt_message + ' '
temp = input(prompt)
#get input from user
return float(temp)
do_again = 'y'
while do_again =='y':
income = income_input("\nHow much did ... | normal | {
"blob_id": "d5acde6c6139833c6631a2d88a181cd019d3d2da",
"index": 5747,
"step-1": "<mask token>\n",
"step-2": "def income_input(prompt_message):\n prompt = prompt_message + ' '\n temp = input(prompt)\n return float(temp)\n\n\n<mask token>\n",
"step-3": "def income_input(prompt_message):\n prompt =... | [
0,
1,
2,
3,
4
] |
import queue
import sys
import logging
from superai.common import InitLog
logger = logging.getLogger(__name__)
# 2维到1维
def hwToidx(x: int, y: int, weight: int):
return y * weight + x
# 1维到2维
def idxTohw(idx, weight: int):
return [idx % weight, idx // weight]
# 10x10 cell idx 到 [x,y]
def idxToXY(idx, cel... | normal | {
"blob_id": "b6d8a918659f733919fe3bb4be9037e36ad32386",
"index": 272,
"step-1": "<mask token>\n\n\nclass Graph:\n\n def __init__(self, V: int, W: int):\n self.V = V\n self.E = 0\n self.adj = []\n self.W = W\n for i in range(V):\n nears = []\n self.adj.a... | [
14,
17,
18,
19,
24
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
app_name = 'authors'
urlpatterns = [path('polls/', PollsList.as_view()), path('polls/create',
PollsCreate.as_view()), path('polls/<int:pk>', SinglePollsView.as_view(
)), path('answers/', PollsAnswer.as_view())]
<|reserve... | flexible | {
"blob_id": "64ac007faeebe0e71ba0060e74fa07154e6291e2",
"index": 6053,
"step-1": "<mask token>\n",
"step-2": "<mask token>\napp_name = 'authors'\nurlpatterns = [path('polls/', PollsList.as_view()), path('polls/create',\n PollsCreate.as_view()), path('polls/<int:pk>', SinglePollsView.as_view(\n )), path('... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def convert(o):
if isinstance(o, np.generic):
return o.item()
raise TypeError
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def convert(o):
if isinstance(o, np.generic):
return o.item()
raise TypeError
<|res... | flexible | {
"blob_id": "7057b882ca1ce2c08e9ba7add5f115636b9b319e",
"index": 8745,
"step-1": "<mask token>\n\n\ndef convert(o):\n if isinstance(o, np.generic):\n return o.item()\n raise TypeError\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef convert(o):\n if isinstance(o, np.generic):\n ret... | [
1,
2,
3,
4,
5
] |
#!/usr/bin/env python
# encoding: utf-8
import multiprocessing
import time
import sys
def daemon():
p = multiprocessing.current_process()
print('Starting:', p.name, p.pid)
sys.stdout.flush()
time.sleep(2)
print('Exiting :', p.name, p.pid)
sys.stdout.flush()
def non_daemon():
p = multipr... | normal | {
"blob_id": "9bb6fd6fbe212bdc29e2d1ec37fa6ec6ca9a9469",
"index": 1060,
"step-1": "<mask token>\n\n\ndef daemon():\n p = multiprocessing.current_process()\n print('Starting:', p.name, p.pid)\n sys.stdout.flush()\n time.sleep(2)\n print('Exiting :', p.name, p.pid)\n sys.stdout.flush()\n\n\n<mask ... | [
2,
5,
6,
7,
8
] |
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
] |
#!/usr/bin/env python3
def main():
pass
def handle_result(args, result, target_window_id, boss):
if args[1] == "next":
boss.active_tab_manager.next_tab(1)
elif args[1] == "previous":
boss.active_tab_manager.next_tab(-1)
boss.active_tab.neighboring_window(args[1])
handle_result.no_ui... | normal | {
"blob_id": "3a7f9bf5420b2d3587f1988c35f2f88bd2fa2b32",
"index": 2771,
"step-1": "<mask token>\n",
"step-2": "def main():\n pass\n\n\n<mask token>\n",
"step-3": "def main():\n pass\n\n\ndef handle_result(args, result, target_window_id, boss):\n if args[1] == 'next':\n boss.active_tab_manager.... | [
0,
1,
2,
3,
4
] |
import re
import cgi
import os
import urllib
import urllib2
from time import sleep
from google.appengine.api import taskqueue
from google.appengine.ext import webapp
from google.appengine.ext.webapp.util import run_wsgi_app
from google.appengine.ext import db
from google.appengine.api import urlfetch
from google.ap... | normal | {
"blob_id": "c8a6a8633f863e0350157346106a747096d26939",
"index": 9912,
"step-1": "<mask token>\n\n\nclass lexicon0(db.Model):\n word = db.StringProperty(required=True)\n known = db.StringListProperty(indexed=False)\n\n\n<mask token>\n\n\ndef getjp(before, wordlist, after):\n global REQUESTURL\n wordl... | [
13,
14,
17,
21,
22
] |
# Definition for a binary tree node.
# class TreeNode(object):
# def __init__(self, x):
# self.val = x
# self.left = None
# self.right = None
class Solution(object):
# (119ms)
def isSubtree(self, s, t):
"""
:type s: TreeNode
:type t: TreeNode
:rtype: bool... | normal | {
"blob_id": "5ac4dd62d8e56c7baf38f9fe9f8b4a5034f1cb80",
"index": 192,
"step-1": "# Definition for a binary tree node.\n# class TreeNode(object):\n# def __init__(self, x):\n# self.val = x\n# self.left = None\n# self.right = None\n\nclass Solution(object):\n# (119ms)\n def isSubtree(... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def swap(a, b):
print(a, b)
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def swap(a, b):
print(a, b)
<|reserved_special_token_0|>
print('the vaalues after swaping the variables are below:')
print('the value of a is : ', a)
print('t... | flexible | {
"blob_id": "4fbe4d474e10e08eafee3bcc6173f8cd6b797dde",
"index": 3203,
"step-1": "<mask token>\n",
"step-2": "def swap(a, b):\n print(a, b)\n\n\n<mask token>\n",
"step-3": "def swap(a, b):\n print(a, b)\n\n\n<mask token>\nprint('the vaalues after swaping the variables are below:')\nprint('the value of ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
doc.updateStatus()
if script.run_script(doc, script.id) != False:
if doc.naming('richiesta') != 'integrazione':
doc.sendThisMail('rigetta')
script.run_script(doc, script.id, suffix='post')
<|reserved_special_toke... | flexible | {
"blob_id": "096d82e1f9e8832f6605d23c8bb324e045b6b14f",
"index": 7393,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ndoc.updateStatus()\nif script.run_script(doc, script.id) != False:\n if doc.naming('richiesta') != 'integrazione':\n doc.sendThisMail('rigetta')\n script.run_script(doc, scri... | [
0,
1,
2,
3
] |
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
] |
import numpy as np
import csv
class PriceTracker:
def __init__(self):
pass
def getValue(self, i):
pass
class CsvTracker:
def __init__(self, csv_file):
self.current_row = 61
self.csv_file_content = []
self.csv_file = csv.reader(csv_file, delimiter =',')
fo... | normal | {
"blob_id": "eb827998f1ba75ffb95751ddb2b31d4d0e54358b",
"index": 8273,
"step-1": "import numpy as np\nimport csv\n\nclass PriceTracker:\n\n def __init__(self):\n pass\n\n def getValue(self, i):\n pass\n\n\nclass CsvTracker:\n def __init__(self, csv_file):\n self.current_row = 61\n ... | [
0
] |
# SPDX-License-Identifier: Apache-2.0
# Copyright (C) 2020 ifm electronic gmbh
#
# THE PROGRAM IS PROVIDED "AS IS" WITHOUT WARRANTY OF ANY KIND.
#
"""
This module provides the recording control GUI service for the nexxT framework.
"""
import logging
from pathlib import Path
from nexxT.Qt.QtCore import Qt, QStorageInf... | normal | {
"blob_id": "3e4771d074218fb0a77332ee61a4cc49f1c301b7",
"index": 9356,
"step-1": "<mask token>\n\n\nclass MVCRecordingControlGUI(MVCRecordingControlBase):\n <mask token>\n\n def __init__(self, config):\n assertMainThread()\n super().__init__(config)\n self._directory = str(Path('.').ab... | [
6,
8,
9,
12,
15
] |
__author__ = "Sarah Hazell Pickering (sarah.pickering@anu.edu.au)"
__date__ = "2018-11-15"
""" QC and Trimming with fastp
Trimming and QC with fastp.
Then subsampling of reads via seqtk.
Now starts with a sample/sample.file structure.
Number of reads to sample is can be supplied via pairs_to_sample
... | normal | {
"blob_id": "655e6531dc21dcdf8fa827184444cee483492b81",
"index": 7715,
"step-1": "__author__ = \"Sarah Hazell Pickering (sarah.pickering@anu.edu.au)\"\n__date__ = \"2018-11-15\"\n\n\"\"\" QC and Trimming with fastp\n\n Trimming and QC with fastp.\n Then subsampling of reads via seqtk.\n\n Now starts wit... | [
0
] |
<|reserved_special_token_0|>
class Test(unittest.TestCase):
<|reserved_special_token_0|>
def test(self):
workflow_input = {'result_type': 'posts'}
wf = WeiboOnline()
r = wf.run(workflow_input)
print(json.dumps(r, ensure_ascii=False, indent=2))
def tearDown(self):
... | flexible | {
"blob_id": "7088f7233b67dcb855482a76d304aacc1a26abad",
"index": 3790,
"step-1": "<mask token>\n\n\nclass Test(unittest.TestCase):\n <mask token>\n\n def test(self):\n workflow_input = {'result_type': 'posts'}\n wf = WeiboOnline()\n r = wf.run(workflow_input)\n print(json.dumps(... | [
3,
4,
5,
6
] |
from tkinter import *
import psycopg2
import sys
import pprint
import Base_de_datos
import MergeSort
class Cliente:
def __init__(self,id=None,nombre=None):
self.id=id
self.nombre=nombre
def ingresar(self):
self.ventanaIngresar= Toplevel()
self.ventanaIngresa... | normal | {
"blob_id": "63d9aa55463123f32fd608ada83e555be4b5fe2c",
"index": 6946,
"step-1": "<mask token>\n\n\nclass Cliente:\n <mask token>\n <mask token>\n\n def BD(self):\n conectar = Base_de_datos.BaseDeDatos()\n comando = (\"INSERT INTO public.cliente(id, nombre) VALUES('\" + self\n .... | [
2,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def read_lookup_table(hole_cards, lookup_table):
"""
Reads the preflop lookup table preflop_EHSs.txt.
Args:
hole_cards: list of int (deuces cards)
lookup_table: read from preflop_EHSs.txt
Return:... | flexible | {
"blob_id": "8503998fc881f47dc695d3ea4c7f56fa65a96e8a",
"index": 2874,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef read_lookup_table(hole_cards, lookup_table):\n \"\"\"\n Reads the preflop lookup table preflop_EHSs.txt.\n Args: \n hole_cards: list of int (deuces cards)\n ... | [
0,
1,
2
] |
#!/usr/bin/env python
from django import template
from django.conf import settings
from django.utils.html import format_html
register = template.Library()
@register.simple_tag
def website_title():
return settings.WEBSITE_TITLE
def split_page(result_obj):
"""
分页模块，后台传入一个分页结果集就可以
:param result_obj:
... | normal | {
"blob_id": "c2c51dcd05c21e91e591de25fc2de034c88c48a1",
"index": 9052,
"step-1": "<mask token>\n\n\ndef split_page(result_obj):\n \"\"\"\n 分页模块，后台传入一个分页结果集就可以\n :param result_obj:\n :return:\n \"\"\"\n return_str = '<nav>'\n return_str += \"<ul class='pagination pull-right'>\"\n if resul... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
class BusRoute(Base):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class BusRoutePos(Base):
__tablename__ = 'bus_route_pos'
id... | flexible | {
"blob_id": "9e896d935cc57e580ed46cd501b41053bbaab38f",
"index": 6490,
"step-1": "<mask token>\n\n\nclass BusRoute(Base):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\nclass BusRoutePos(Base):\n __tablename__ = 'bus_route_pos'\n id = Column... | [
12,
15,
16,
17,
19
] |
<|reserved_special_token_0|>
def cut_rod2(price, n):
val = [(0) for x in range(n + 1)]
val[0] = 0
for i in range(1, n + 1):
max_val = -1
for j in range(i):
max_val = max(max_val, price[j] + val[i - j - 1])
val[i] = max_val
return val[n]
<|reserved_special_token_0|... | flexible | {
"blob_id": "9cca73ebdf2b05fe29c14dc63ec1b1a7c917b085",
"index": 6508,
"step-1": "<mask token>\n\n\ndef cut_rod2(price, n):\n val = [(0) for x in range(n + 1)]\n val[0] = 0\n for i in range(1, n + 1):\n max_val = -1\n for j in range(i):\n max_val = max(max_val, price[j] + val[i ... | [
2,
3,
4,
5,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
db.add_collection(coll)
db.add_collection(coll2)
pickle.dump(db, open(''))
<|reserved_special_token_1|>
<|reserved_special_token_0|>
console = Console()
doc = FourierDocument({'bar': 'eggs', 'xyz': 'spam'})
doc2 = FourierDocume... | flexible | {
"blob_id": "f15f96658130ac9bba748a518371ad80d9772fbc",
"index": 4121,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ndb.add_collection(coll)\ndb.add_collection(coll2)\npickle.dump(db, open(''))\n",
"step-3": "<mask token>\nconsole = Console()\ndoc = FourierDocument({'bar': 'eggs', 'xyz': 'spam'})\ndoc... | [
0,
1,
2,
3,
4
] |
# flush in poker
def IsContinuous(numbers):
if not numbers or len(numbers) < 1 :
return False
numbers.sort()
number_of_zero = 0
number_of_gap = 0
for i in range(len(numbers)):
if numbers[i] == 0:
number_of_zero += 1
small = number_of_zero
big = small + 1
whi... | normal | {
"blob_id": "68a776d7fccc8d8496a944baff51d2a862fc7d31",
"index": 1259,
"step-1": "<mask token>\n",
"step-2": "def IsContinuous(numbers):\n if not numbers or len(numbers) < 1:\n return False\n numbers.sort()\n number_of_zero = 0\n number_of_gap = 0\n for i in range(len(numbers)):\n ... | [
0,
1,
2
] |
<|reserved_special_token_0|>
def write_csv(url, recursive=False, writer=None, token=''):
response = fetch(url)
if recursive:
write_rows(writer, response)
cursor = next_cursor(response)
if cursor is not None:
print(f'next cursor exists...{cursor}')
ret = urlparse... | flexible | {
"blob_id": "b47f15a79f7a82304c2be6af00a5854ff0f6ad3e",
"index": 6987,
"step-1": "<mask token>\n\n\ndef write_csv(url, recursive=False, writer=None, token=''):\n response = fetch(url)\n if recursive:\n write_rows(writer, response)\n cursor = next_cursor(response)\n if cursor is not Non... | [
3,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for word in words:
if word_dict.has_key(word):
word_dict[word.lower()] = max(word_dict[word.lower()], words.count(
word.lower()) + words.count(word.upper()) + words.count(word))
else:
word_dict[... | flexible | {
"blob_id": "addab37cb23abead2d9f77a65336cd6026c52c68",
"index": 8559,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor word in words:\n if word_dict.has_key(word):\n word_dict[word.lower()] = max(word_dict[word.lower()], words.count(\n word.lower()) + words.count(word.upper()) + w... | [
0,
1,
2,
3,
4
] |
import sys
sys.stdin = open("sample_input_17.txt","r")
T = int(input())
def code(N): # 암호코드가 있는 열의 위치를 찾음
code = []
for i in range(N-4):
for j in range(49,53):
if S[i][j] == "1" :
code = S[i]
return code
def code_s(code): # 암호코드의 행 위치를 찾아 슬라이싱
for x in ... | normal | {
"blob_id": "b739c1de6c008158ee3806bed9fa2865eb484b4f",
"index": 5596,
"step-1": "<mask token>\n\n\ndef code(N):\n code = []\n for i in range(N - 4):\n for j in range(49, 53):\n if S[i][j] == '1':\n code = S[i]\n return code\n\n\ndef code_s(code):\n for x ... | [
3,
4,
5,
6,
7
] |
n = int(input())
a = [int(e) for e in input().split()]
ans = [0] * n
for i in range(n):
s = a[i]
ans[s - 1] = i + 1
print(*ans)
| normal | {
"blob_id": "f74e2e6b59330bd63fee9192e74a72178abc1cab",
"index": 8195,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(n):\n s = a[i]\n ans[s - 1] = i + 1\nprint(*ans)\n",
"step-3": "n = int(input())\na = [int(e) for e in input().split()]\nans = [0] * n\nfor i in range(n):\n s = ... | [
0,
1,
2
] |
# -*- coding: utf-8 -*-
import scrapy
import MySQLdb
import openpyxl
from scrapy.crawler import CrawlerProcess
import sys
class AllabolaSpider(scrapy.Spider):
name = 'allabola'
allowed_domains = ['https://www.allabolag.se']
start_urls = []
#'https://www.allabolag.se/7696250484/befattningar'
host =... | normal | {
"blob_id": "d60a2100127db859162890204655d313cdc2a4a5",
"index": 4614,
"step-1": "<mask token>\n\n\nclass AllabolaSpider(scrapy.Spider):\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 f.write('fn,ln,zip,ct,st,co... | [
2,
4,
5,
6,
8
] |
from django.shortcuts import render
from rest_framework.response import Response
from .serializers import *
from rest_framework import generics, status
class HistoryMyList(generics.ListCreateAPIView):
serializer_class = HistorySer
queryset = History.objects.all()
class HistoryListView(generics.GenericAPIVie... | normal | {
"blob_id": "8edca4c50e48734073e80de85088964837247696",
"index": 2597,
"step-1": "<mask token>\n\n\nclass HistoryListView(generics.GenericAPIView):\n <mask token>\n\n def post(self, request):\n serializer_class = self.serializer_class(data=request.data)\n serializer_class.is_valid(raise_excep... | [
8,
9,
11,
12
] |
from django.urls import path
from . import views
# url configuration for view.index function
app_name = 'movies'
urlpatterns = [
path('', views.index, name='index'), # represents a root of this app
path('<int:movie_id>', views.detail, name='detail')
]
| normal | {
"blob_id": "5aaac757b766b0143ca3ea54d8fc4b8936160ec7",
"index": 5090,
"step-1": "<mask token>\n",
"step-2": "<mask token>\napp_name = 'movies'\nurlpatterns = [path('', views.index, name='index'), path('<int:movie_id>',\n views.detail, name='detail')]\n",
"step-3": "from django.urls import path\nfrom . im... | [
0,
1,
2,
3
] |
def group(arr):
low, mid, high = 0, 0, len(arr)-1
while mid <= high:
print(arr)
if arr[mid] == 'R' :
arr[low], arr[mid] = arr[mid], arr[low]
low += 1
mid += 1
elif arr[mid] == 'G':
mid += 1
else:
arr[high], ar... | normal | {
"blob_id": "8ad47bf292e0046550cc0ef6f6bb75cf179ebd4b",
"index": 7477,
"step-1": "<mask token>\n",
"step-2": "def group(arr):\n low, mid, high = 0, 0, len(arr) - 1\n while mid <= high:\n print(arr)\n if arr[mid] == 'R':\n arr[low], arr[mid] = arr[mid], arr[low]\n low +... | [
0,
1,
2,
3,
4
] |
#coding=utf-8
import urllib.parse
import json
'''转化从charles复制下来的字串，转为json格式'''
def to_str(body_str):
'''检查需要转化的str是否符合标准'''
if not body_str == '':
par = body_str.split("&")
# print(par)
_temp = []
try:
for each in par:
if "=" not in each:
... | normal | {
"blob_id": "d8e9b9f7a8d5ec2a72f083ec2283e8c0724dbe0d",
"index": 9119,
"step-1": "<mask token>\n\n\ndef to_json(body_str):\n \"\"\"转化格式\"\"\"\n try:\n body_str = to_str(body_str)\n except:\n return False\n body_dict = {}\n for each in body_str.split('&'):\n body_dict[str(each.... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
ii = [('LeakWTI2.py', 6)]
| flexible | {
"blob_id": "997b68e42547b8f8a1059776c55c3ad16df494da",
"index": 1468,
"step-1": "<mask token>\n",
"step-2": "ii = [('LeakWTI2.py', 6)]\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
animal = 'cat'
def f():
global animal
animal = 'dog'
print('local_scope:', animal)
print('local:', locals())
f()
print('global_scope:', animal)
print('global:', locals())
| normal | {
"blob_id": "4f3908e12102cfd58737952803c710772e960b0e",
"index": 2385,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef f():\n global animal\n animal = 'dog'\n print('local_scope:', animal)\n print('local:', locals())\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef f():\n gl... | [
0,
1,
2,
3
] |
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
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def train(hp):
os.makedirs(hp.out_dir, exist_ok=True)
device = torch.device('cuda' if hp.use_cuda else 'cpu')
dataset = SVHN(root='svhn', split='train', download=True, transform=
ToTensor())
eval_dataset ... | flexible | {
"blob_id": "43db8ed10face1c668aeadd3cbc5b13f87fb0126",
"index": 4997,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef train(hp):\n os.makedirs(hp.out_dir, exist_ok=True)\n device = torch.device('cuda' if hp.use_cuda else 'cpu')\n dataset = SVHN(root='svhn', split='train', download=True, ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Convolution_Layer(Layer):
def __init__(self, shape, mean, stddev):
super(Convolution_Layer, self).__init__(shape, mean, stddev)
def feed_forward(self, input_data, stride):
conv = tf.nn.conv2d(input_data, self.weights, stride, padding='VALID')
output... | flexible | {
"blob_id": "ed246f2887f19ccf922a4d386918f0f0771fb443",
"index": 5106,
"step-1": "<mask token>\n\n\nclass Convolution_Layer(Layer):\n\n def __init__(self, shape, mean, stddev):\n super(Convolution_Layer, self).__init__(shape, mean, stddev)\n\n def feed_forward(self, input_data, stride):\n con... | [
6,
7,
8,
9,
11
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
plt.show()
<|reserved_special_token_1|>
import Individual
import Grupal
import matplotlib.pyplot as plt
import pandas as pd
plt.show()
| flexible | {
"blob_id": "bb1caf4d04c8a42279afa0ac586ced991e0dff84",
"index": 4574,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nplt.show()\n",
"step-3": "import Individual\nimport Grupal\nimport matplotlib.pyplot as plt\nimport pandas as pd\nplt.show()\n",
"step-4": null,
"step-5": null,
"step-ids": [
... | [
0,
1,
2
] |
import pickle
import numpy as np
in_dir = "C:\\Users\\ganga\\Github\\Generative-Models\\Project\\Data\\Dynamics\\"
out_dir = f"C:\\Users\\ganga\\Github\\Generative-Models\\Project\\Data\\Dynamics\\"
# Read frames
train_frames = pickle.load( open(in_dir +'\\train_frames.pkl' , 'rb' ))
test_frames = pickle.load( open(... | normal | {
"blob_id": "e048170775c589cf0a9fb3d54c72dab4df3f1bcb",
"index": 7558,
"step-1": "<mask token>\n\n\ndef sigmoid(x):\n return 0.5 * (1 + np.tanh(0.5 * x))\n\n\ndef bernoulli_array(prob_array, dim):\n sample = np.zeros(dim)\n uni_sample = np.random.uniform(0, 1, dim)\n diff = uni_sample - prob_array\n ... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
dbindexer.autodiscover()
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
dbindexer.autodiscover()
urlpatterns = patterns('harvester.views', url('^$', 'home', name='home'),
url('^settin... | flexible | {
"blob_id": "9fc9d766915bcefde4f0ba5c24cb83e33fc66272",
"index": 1094,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ndbindexer.autodiscover()\n<mask token>\n",
"step-3": "<mask token>\ndbindexer.autodiscover()\nurlpatterns = patterns('harvester.views', url('^$', 'home', name='home'),\n url('^settin... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
__version__ = '0.90.03'
| flexible | {
"blob_id": "284e4f79748c17d44518f2ce424db5b1697373dc",
"index": 3156,
"step-1": "<mask token>\n",
"step-2": "__version__ = '0.90.03'\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
from DHT_Python import dht22
from oled96 import oled
from PiBlynk import Blynk
# read data using pin 4
instance = dht22.DHT22(pin=4)
token = "---token---"
blynk = Blynk(token)
def cnct_cb():
print ("Connected: ")
blynk.on_connect(cnct_cb)
def _funCb(ACT):
result = instance.read()
if result.is_valid():
strTe... | normal | {
"blob_id": "e95ebb2aa6526e3bf3789da17d144e71cdb49aca",
"index": 2712,
"step-1": "<mask token>\n\n\ndef cnct_cb():\n print('Connected: ')\n\n\n<mask token>\n\n\ndef _funCb(ACT):\n result = instance.read()\n if result.is_valid():\n strTemp = '%.2f' % result.temperature\n strHumi = '%.2f' % ... | [
2,
3,
4,
5,
6
] |
from page_objects import PageObject, PageElement
class MainPage(PageObject):
level_menu_opened = False
level_menu_created = False
css_input = PageElement(css='input.input-strobe')
level_text_span = PageElement(css='span.level-text')
instruction_h2 = PageElement(css='h2.order')
enter_button = P... | normal | {
"blob_id": "c6cf085330f47ffb139c5acc91d91e9758f5396a",
"index": 274,
"step-1": "<mask token>\n\n\nclass MainPage(PageObject):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def __init__(self, webdriver, root_uri=None):\n ... | [
6,
7,
10,
11,
12
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
fig.tight_layout()
fig.subplots_adjust(wspace=0.05)
<|reserved_special_token_0|>
for year in years:
train = get(year, features, index)
train = pre(train)
for method in methods:
ax = axes[i, j]
Z = linka... | flexible | {
"blob_id": "8279f8a80d96a7231e35100d2c39fa5e1f34f5f5",
"index": 9777,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfig.tight_layout()\nfig.subplots_adjust(wspace=0.05)\n<mask token>\nfor year in years:\n train = get(year, features, index)\n train = pre(train)\n for method in methods:\n ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class location_accommodation(models.AbstractModel):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
@api.multi
def render_html(self, docids, data=None):
report = self.env['report']._get_report_from_name(
'sg_accommodation.view_location_report... | flexible | {
"blob_id": "ac99c19294661657d383b036c9ab83e7b610cb7d",
"index": 6896,
"step-1": "<mask token>\n\n\nclass location_accommodation(models.AbstractModel):\n <mask token>\n <mask token>\n\n @api.multi\n def render_html(self, docids, data=None):\n report = self.env['report']._get_report_from_name(\... | [
2,
3,
4,
5,
6
] |
# Generated by Django 2.2.6 on 2019-11-05 02:28
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('drchrono', '0011_patient_cell_phone'),
]
operations = [
migrations.AddField(
model_name='appointment',
name='date',
... | normal | {
"blob_id": "0c7f2412fe9a83d70d41fbc4bbaf135e6bc4149a",
"index": 8129,
"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 = [('drchrono', ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def makeoutput(path):
if os.path.exists(path):
pass
else:
os.mkdir(path)
def mailinglist_cookies(mailinglist, password):
try:
cookie_request = requests.post(URL + ADMIN + mailinglist, data={
'adminpw': password})
cookie_request.rai... | flexible | {
"blob_id": "0e337ce21450e0fdb7688183d0542ebf902a9614",
"index": 1293,
"step-1": "<mask token>\n\n\ndef makeoutput(path):\n if os.path.exists(path):\n pass\n else:\n os.mkdir(path)\n\n\ndef mailinglist_cookies(mailinglist, password):\n try:\n cookie_request = requests.post(URL + ADM... | [
4,
5,
6,
7,
8
] |
# website = urlopen("https://webservices.ulm.edu/forms/forms-list")
# data = bs(website, "lxml")
# forms = data.findAll("span", {"class": "file"})
# forms_list = []
# names = []
# for f in forms:
# forms_list.append(f.find("a")["href"])
# names.append(f.get_text())
# # print(forms_list)
# for f in forms_list:... | normal | {
"blob_id": "a61f351391ca1b18359323fd9e49f1efa4c7513c",
"index": 4007,
"step-1": "<mask token>\n\n\ndef main():\n website = input('Enter the website you want to download file from: ')\n div = input('Enter the div/span (be as specific as you can): ')\n classTag = input('Enter the class/id tag you want to... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for file in glob.glob(pwd + '/*spectrum.json'):
subj_name = os.path.basename(file)[0:6]
subj_list.append(subj_name)
df_dict[os.path.basename(file)[0:6]] = pd.read_json(file)
<|reserved_special_token_0|>
for tract in al... | flexible | {
"blob_id": "f78f8f560b7eb70232658be762e2058535a68122",
"index": 9086,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor file in glob.glob(pwd + '/*spectrum.json'):\n subj_name = os.path.basename(file)[0:6]\n subj_list.append(subj_name)\n df_dict[os.path.basename(file)[0:6]] = pd.read_json(file... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for i in range(2, N + 1):
s.add(i)
for num in sorted(s):
k = num + num
while k <= N:
if k in s:
s.remove(k)
k += num
print('Primes:', end=' ')
for num in sorted(s):
print(num, end=' ')
... | flexible | {
"blob_id": "bf5422792533f85967a5573d9e6f370a7967a914",
"index": 120,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(2, N + 1):\n s.add(i)\nfor num in sorted(s):\n k = num + num\n while k <= N:\n if k in s:\n s.remove(k)\n k += num\nprint('Primes:', end=' ... | [
0,
1,
2,
3
] |
from telethon import events
from var import Var
from pathlib import Path
from ub.config import Config
import re, logging, inspect, sys, json, os
from asyncio import create_subprocess_shell as asyncsubshell, subprocess as asyncsub
from os import remove
from time import gmtime, strftime
from traceback import format_exc
f... | normal | {
"blob_id": "4b672ad420bb67b8e2726102939ed6d369683150",
"index": 7267,
"step-1": "<mask token>\n\n\ndef load_module(shortname):\n if shortname.startswith('__'):\n pass\n elif shortname.endswith('_'):\n import ub.events\n import sys\n import importlib\n from pathlib import... | [
4,
7,
9,
13,
15
] |
s=int(input())
print(s+2-(s%2)) | normal | {
"blob_id": "0412369f89842e2f55aa115e63f46a1b71a0f322",
"index": 2685,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(s + 2 - s % 2)\n",
"step-3": "s = int(input())\nprint(s + 2 - s % 2)\n",
"step-4": "s=int(input())\nprint(s+2-(s%2))",
"step-5": null,
"step-ids": [
0,
1,
2,
... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def shift(v, i, j):
if i <= j:
return v
store = v[i]
for k in range(0, i - j - 1):
v[i - k] = v[i - k - 1]
v[j] = store
return v
def insertion(v):
for i in range(1, len(v)):
j = i
while v[i] < v[j - 1] and j > 0:
j = j ... | flexible | {
"blob_id": "35288c9ad4d3550003e3c2f9e9034f4bce1df830",
"index": 3626,
"step-1": "<mask token>\n\n\ndef shift(v, i, j):\n if i <= j:\n return v\n store = v[i]\n for k in range(0, i - j - 1):\n v[i - k] = v[i - k - 1]\n v[j] = store\n return v\n\n\ndef insertion(v):\n for i in rang... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
[1.5780628845471506e-10, -1.411490597458207e-12, -2.483949940281473e-13,
5.026488748046414e-11, -1.6612576871621329e-10, -1.6989844545344268e-15,
8.109443782655016e-16, 2.404048022255995e-05, -1.9859378185800262e-06,
... | flexible | {
"blob_id": "bdf3cb1830021b10d6c8966b3341fd9297d9a371",
"index": 2045,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n[1.5780628845471506e-10, -1.411490597458207e-12, -2.483949940281473e-13, \n 5.026488748046414e-11, -1.6612576871621329e-10, -1.6989844545344268e-15,\n 8.109443782655016e-16, 2.40404... | [
0,
1,
2,
3
] |
# from dataclasses import InitVar, dataclass
# standard library imports
from math import floor
# third-party imports
import gym
import torch
from torch.nn import Conv2d, Linear, MaxPool2d, Module, ModuleList, ReLU, Sequential
from torch.nn import functional as F
# local imports
from tmrl.nn import TanhNormalLayer
fro... | normal | {
"blob_id": "6f6d3fbb9a6a118e0f4026a7f9054b90b8cf2fca",
"index": 5677,
"step-1": "<mask token>\n\n\nclass BigCNN(Module):\n\n def __init__(self, h_in, w_in, channels_in):\n super(BigCNN, self).__init__()\n self.h_out, self.w_out = h_in, w_in\n self.conv1 = Conv2d(channels_in, 64, 8, strid... | [
14,
16,
19,
22,
24
] |
<|reserved_special_token_0|>
class MyAdmin(admin.ModelAdmin):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class CalcResultAdmin(MyAdmin):
list_display = 'result', 'message', 'time'
search_fields = 'result', 'message', 'time'
<|reserved_special_token_0|>
<|reserved_special_token_1|>... | flexible | {
"blob_id": "e2573a5dc507e9aeb811fbc254129aeb6e54cc0b",
"index": 2483,
"step-1": "<mask token>\n\n\nclass MyAdmin(admin.ModelAdmin):\n <mask token>\n <mask token>\n\n\nclass CalcResultAdmin(MyAdmin):\n list_display = 'result', 'message', 'time'\n search_fields = 'result', 'message', 'time'\n\n\n<mask... | [
3,
4,
5,
6,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
dependencies = [(... | flexible | {
"blob_id": "b92497396e711d705760db547b43cc65beba6cfd",
"index": 6172,
"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 = [('sandbox_rep... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Jun 5 10:04:05 2019
@author: cristina
"""
import numpy as np
from itertools import chain
from numpy import linalg as LA
diag = LA.eigh
import matplotlib.pyplot as plt
plt.rcParams.update({'font.size': 13})
import time
pi = np.pi
exp = np.exp
t1 = tim... | normal | {
"blob_id": "f2ad95574b65b4d3e44b85c76f3a0150a3275cec",
"index": 2356,
"step-1": "<mask token>\n\n\ndef LDOS_up(omega, E, u, Damping):\n t = sum(u ** 2 / (omega - E + 1.0j * Damping))\n tt = -1 / pi * np.imag(t)\n return tt\n\n\ndef LDOS_down(omega, E, v, Damping):\n t = sum(v ** 2 / (omega + E + 1.0... | [
2,
3,
4,
5,
6
] |
import sys
from bs4 import BeautifulSoup
def get_classes(html):
"""
returns a list of classes and titles, parsing through 'html'
"""
# elements = html.find_all("span", "code")
# titles = html.find_all("span", "title")
# classes = []
# for i in range(len(elements)):
# item = element... | normal | {
"blob_id": "9bb8e0f732eac474dbc01c374f9c74178f65dc36",
"index": 3063,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_classes(html):\n \"\"\"\n returns a list of classes and titles, parsing through 'html'\n \"\"\"\n",
"step-3": "import sys\nfrom bs4 import BeautifulSoup\n\n\ndef ge... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class ConfigLoader:
<|reserved_special_token_0|>
def __init__(self, level):
self._log = Logger('configloader', level)
self._log.info('ready.')
def configure(self, filename='config.yaml'):
"""
Read and return configuration from the specified YA... | flexible | {
"blob_id": "3a6038cb80548b98fc7e4a328092f1dc1ffd6dfd",
"index": 1154,
"step-1": "<mask token>\n\n\nclass ConfigLoader:\n <mask token>\n\n def __init__(self, level):\n self._log = Logger('configloader', level)\n self._log.info('ready.')\n\n def configure(self, filename='config.yaml'):\n ... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
_all__ = ['minning_algo']
<|reserved_special_token_1|>
_all__ = ["minning_algo"]
| flexible | {
"blob_id": "5a7b68648898818e0db47f225f3d4b0972cd5b99",
"index": 7521,
"step-1": "<mask token>\n",
"step-2": "_all__ = ['minning_algo']\n",
"step-3": "_all__ = [\"minning_algo\"]\n\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
} | [
0,
1,
2
] |
<|reserved_special_token_0|>
class CNP(torch.nn.Module):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class ANP(torch.nn.Module):
def __init__(self, in_dim, hidden_dim, query_dim, out_dim, en_layer,
dec_layer, nhead):
super(ANP, self).__init__()
if en_layer == 1:
... | flexible | {
"blob_id": "82c3bde5746d04c126a93851844f775e7ce65f4b",
"index": 9442,
"step-1": "<mask token>\n\n\nclass CNP(torch.nn.Module):\n <mask token>\n <mask token>\n\n\nclass ANP(torch.nn.Module):\n\n def __init__(self, in_dim, hidden_dim, query_dim, out_dim, en_layer,\n dec_layer, nhead):\n sup... | [
7,
8,
9,
10,
13
] |
import PySimpleGUI as sg
class TelaLisatrClientes():
def __init__(self):
self.__window = None
def init_components(self, lista_clientes):
layout = [
[sg.Text('Dados do cliente')],
[sg.Listbox(values=lista_clientes, size=(60, 10))],
[sg.Submit()]
]
... | normal | {
"blob_id": "624b34d160ea6db4f5249544f1614a20f506ca9e",
"index": 895,
"step-1": "<mask token>\n\n\nclass TelaLisatrClientes:\n <mask token>\n\n def init_components(self, lista_clientes):\n layout = [[sg.Text('Dados do cliente')], [sg.Listbox(values=\n lista_clientes, size=(60, 10))], [sg.... | [
2,
3,
4,
5,
6
] |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('guac_auth', '0001_initial'),
]
operations = [
migrations.RemoveField(
model_name='guacamoleconnectiongroup',
... | normal | {
"blob_id": "7f63097265b1058785e90441f85b7f0088946717",
"index": 7785,
"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 = [('guac_auth',... | [
0,
1,
2,
3,
4
] |
''' 简述：这里有四个数字，分别是：1、2、3、4
提问：能组成多少个互不相同且无重复数字的三位数？各是多少？ '''
for x in range(1,5):
for y in range(1,5):
for z in range(1,5):
if (x != y) & (x != z) & (y != z):
print(x,y,z)
| normal | {
"blob_id": "caac877bf6c42217ea41f51717f6a704a3a9774b",
"index": 6838,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor x in range(1, 5):\n for y in range(1, 5):\n for z in range(1, 5):\n if (x != y) & (x != z) & (y != z):\n print(x, y, z)\n",
"step-3": "''' 简述：这里有... | [
0,
1,
2
] |
<|reserved_special_token_0|>
def auto_int(x):
return int(x, 0)
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def auto_int(x):
return int(x, 0)
def load_options():
global parsed_args
base_parser = argparse.ArgumentParser(add_help=False)
base_parser.... | flexible | {
"blob_id": "3b381668dbb9b4e5a2e323dc4d6b5e3951736882",
"index": 1804,
"step-1": "<mask token>\n\n\ndef auto_int(x):\n return int(x, 0)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef auto_int(x):\n return int(x, 0)\n\n\ndef load_options():\n global parsed_args\n base_parser = argparse.Argum... | [
1,
4,
5,
6,
7
] |
from armulator.armv6.bits_ops import add_with_carry, bit_not
from armulator.armv6.enums import InstrSet
from armulator.armv6.opcodes.opcode import Opcode
class SubsPcLrThumb(Opcode):
def __init__(self, instruction, imm32, n):
super().__init__(instruction)
self.imm32 = imm32
self.n = n
... | normal | {
"blob_id": "89376b2464dfb724197a1c1e164af8277e03ad59",
"index": 2507,
"step-1": "<mask token>\n\n\nclass SubsPcLrThumb(Opcode):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass SubsPcLrThumb(Opcode):\n\n def __init__(self, instruction, imm32, n):\n super().__init__(instruct... | [
1,
2,
3,
4,
5
] |
year = int(input('西暦＞'))
if year % 4 == 0 and year % 100 != 0:
print('閏年')
pass
elif year % 400 == 0:
print('閏年')
pass
else:
print('平年')
pass
| normal | {
"blob_id": "b381d1110e6a7570cd872d689a43aba2d2580a23",
"index": 8449,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif year % 4 == 0 and year % 100 != 0:\n print('閏年')\n pass\nelif year % 400 == 0:\n print('閏年')\n pass\nelse:\n print('平年')\n pass\n",
"step-3": "year = int(input('西暦＞... | [
0,
1,
2
] |
<|reserved_special_token_0|>
def register_int_signal_handler():
def stop_thread_handler(signum, frame):
log.info('Received signal {0}. Will stop all task threads'.format(
signum))
for _ in range(len(THREAD_STOP_FLAGS)):
THREAD_STOP_FLAGS[_] = True
if platform.platform(... | flexible | {
"blob_id": "fbd5400823a8148adf358a2acc58fde146a25313",
"index": 2275,
"step-1": "<mask token>\n\n\ndef register_int_signal_handler():\n\n def stop_thread_handler(signum, frame):\n log.info('Received signal {0}. Will stop all task threads'.format(\n signum))\n for _ in range(len(THREA... | [
13,
16,
19,
20,
24
] |
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
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def main(connection, info, args, world):
"""Resets a users money"""
money = shelve.open('money-%s.db' % world.hostnicks[connection.host],
writeback=True)
money[info['sender']] = {'money': 100000, 'maxmoney': ... | flexible | {
"blob_id": "95021cc01c0b85b512fd466797d4d128472773c3",
"index": 2943,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main(connection, info, args, world):\n \"\"\"Resets a users money\"\"\"\n money = shelve.open('money-%s.db' % world.hostnicks[connection.host],\n writeback=True)\n ... | [
0,
1,
2,
3,
4
] |
import numpy as np
def get_mask(mask):
r = mask[:, :, 0]
g = mask[:, :, 1]
return r // (r.max() or 1) * -1 + g // (g.max() or 1)
def calculate_brightness(image):
weights = np.array([0.299, 0.587, 0.114])
brightness_matrix = (image*weights).sum(axis=2)
return brightness_matrix
def calculate... | normal | {
"blob_id": "7130a382784955780a3f258c81ce05c61915af56",
"index": 5000,
"step-1": "<mask token>\n\n\ndef get_mask(mask):\n r = mask[:, :, 0]\n g = mask[:, :, 1]\n return r // (r.max() or 1) * -1 + g // (g.max() or 1)\n\n\n<mask token>\n\n\ndef extend(image, mask):\n brightness = calculate_brightness(i... | [
3,
6,
7,
9,
10
] |
a = input()
b = []
ind = []
for i in a:
if i.isalpha():
b.append(i)
else:
ind.append(a.index(i))
c = list(reversed(b))
for i in ind:
c.insert(i, a[i])
print(''.join(c))
| normal | {
"blob_id": "8fedaeb13fde117cf6b7ace23b59c26e4aab2bc2",
"index": 4492,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in a:\n if i.isalpha():\n b.append(i)\n else:\n ind.append(a.index(i))\n<mask token>\nfor i in ind:\n c.insert(i, a[i])\nprint(''.join(c))\n",
"step-3": "a ... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def read_ints():
return list(map(int, input().strip().split(' ')))
def solve():
K, S = read_ints()
total = 0
for X in range(K + 1):
if S - X < 0:
break
Y_min = max(S - X - K, 0)
... | flexible | {
"blob_id": "46b1fc975fbeedcafaa66c85c378e2249a495647",
"index": 8827,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef read_ints():\n return list(map(int, input().strip().split(' ')))\n\n\ndef solve():\n K, S = read_ints()\n total = 0\n for X in range(K + 1):\n if S - X < 0:\n ... | [
0,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
setup(name='TF_Speech', version='0.2.0', extras_require={'tensorflow': [
'tensorflow'], 'tensorflow with gpu': ['tensorflow-gpu']})
<|reserved_special_token_1|>
<|reserved_special_token_0|>
from setuptools import setup
setu... | flexible | {
"blob_id": "97ebdeada3d797a971b5c3851b75f9754595f67c",
"index": 358,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsetup(name='TF_Speech', version='0.2.0', extras_require={'tensorflow': [\n 'tensorflow'], 'tensorflow with gpu': ['tensorflow-gpu']})\n",
"step-3": "<mask token>\nfrom setuptools impo... | [
0,
1,
2,
3
] |
###
# This Python module contains commented out classifiers that I will no longer
# be using
###
from sklearn.tree import DecisionTreeClassifier
from sklearn.ensemble import BaggingClassifier
from sklearn.ensemble import RandomForestClassifier
from sklearn.neighbors import KNeighborsClassifier
# Using Decision trees... | normal | {
"blob_id": "5029f3e2000c25d6044f93201c698773e310d452",
"index": 3391,
"step-1": "<mask token>\n",
"step-2": "from sklearn.tree import DecisionTreeClassifier\nfrom sklearn.ensemble import BaggingClassifier\nfrom sklearn.ensemble import RandomForestClassifier\nfrom sklearn.neighbors import KNeighborsClassifier\... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
dependencies = [(... | flexible | {
"blob_id": "e307bcc28526081141f1f2204c225d8e5f0100a8",
"index": 9015,
"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 = [('HMS', '0009... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.... | flexible | {
"blob_id": "d65d85b4573728ed32ccf987459d5a228e2a8897",
"index": 5196,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Migration(migrations.Migration):\n <mask token>\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Migration(migrations.Migration):\n initial = T... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def RepresentsInt(s):
try:
int(s)
return True
except ValueError:
return False
<|reserved_special_token_0|>
def drawOneEllipse(aoi, img, draw):
if DEBUG:
print('Ellipse centered at [{0}, {1}] with {2} {3}'.format(aoi[0],
aoi[1], a... | flexible | {
"blob_id": "833053a5a75636267feaad5ddaa21dce1de34038",
"index": 5319,
"step-1": "<mask token>\n\n\ndef RepresentsInt(s):\n try:\n int(s)\n return True\n except ValueError:\n return False\n\n\n<mask token>\n\n\ndef drawOneEllipse(aoi, img, draw):\n if DEBUG:\n print('Ellipse ... | [
6,
8,
12,
13,
17
] |
from multiprocessing import Pool
from pathlib import Path
import os
import re
import json
import string
import math
import GLOBALS
stopWords = {"a", "about", "above", "after", "again", "against", "all", "am", "an", "and", "any", "are", "aren't",
"as", "at", "be", "because", "been", "before", "being", "bel... | normal | {
"blob_id": "19f17044d48c8cc0f9d366cde7edc846ff343462",
"index": 2598,
"step-1": "<mask token>\n\n\ndef search(query, finalIndexPath):\n listOfDicts = list()\n queryList = set()\n tempList = query.strip().lower().replace(\"'\", '').split(' ')\n for word in tempList:\n if word not in stopWords:... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
class Page(webapp.RequestHandler):
def get(self):
if users.get_current_user():
url = users.create_logout_url(self.request.uri)
linktext = 'Logout'
user = users.get_current_user()
else:
url = users.create_login_url(self.r... | flexible | {
"blob_id": "64ed3c512894902f85d619020b78338e228dddb6",
"index": 4380,
"step-1": "<mask token>\n\n\nclass Page(webapp.RequestHandler):\n\n def get(self):\n if users.get_current_user():\n url = users.create_logout_url(self.request.uri)\n linktext = 'Logout'\n user = user... | [
5,
6,
7,
9,
10
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def load_json(file_name='data.json'):
with open(file_name, 'r') as json_fp:
json_data = json_fp.read()
data_arr = json.loads(json_data)
return data_arr
<|reserved_special_token_0|>
<|reserved_spec... | flexible | {
"blob_id": "63068a15d750abb29398d687495d6001ba17ab8a",
"index": 9435,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef load_json(file_name='data.json'):\n with open(file_name, 'r') as json_fp:\n json_data = json_fp.read()\n data_arr = json.loads(json_data)\n return data_arr... | [
0,
1,
2,
3,
4
] |
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