code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
# coding: utf-8
# In[1]:
import pandas as pd
import numpy as np
import itertools
# Save a nice dark grey as a variable
almost_black = '#262626'
import matplotlib
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap
sns.set()
get_ipython().magic('matplotlib inline')
# I... | normal | {
"blob_id": "f2786e445bdf66cf6bb66f4cde4c7b2bf819d8aa",
"index": 3299,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsns.set()\nget_ipython().magic('matplotlib inline')\n<mask token>\nif header_included:\n header = 0\n<mask token>\nfor item in combinations:\n index = ax[i]\n x_vis = X[:, [featu... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/python3
def file_to_code(fname):
mem = []
for line in open(fname,"r"):
mem.extend([int(i) for i in line.split(",")])
return mem
class Opcode(object):
def __init__(self, mem, ptr, code, inc):
"""
>>> o = Opcode([1001, 2, 4, 1], 0, 1, 4)
>>> o._Opcode__par_modes
[0, 1]
"""
if mem[ptr]%100 !... | normal | {
"blob_id": "653e65281984ebb06467aeadb6f0e2b11f1bcb4d",
"index": 496,
"step-1": "<mask token>\n\n\nclass Opcode1(Opcode):\n <mask token>\n\n def __init__(self, mem, ptr):\n super().__init__(mem, ptr, 1, 4)\n self.__first = self.get_val(1)\n self.__second = self.get_val(2)\n self... | [
43,
44,
55,
57,
62
] |
import sys
from PyQt5.QtWidgets import *
from PyQt5.QtGui import QIcon, QFont
from PyQt5.QtCore import QCoreApplication
import pymysql
import requests
from twisted.internet import reactor, defer
from scrapy.crawler import CrawlerRunner, CrawlerProcess
from scrapy.utils.project import get_project_settings
from spider.... | normal | {
"blob_id": "889d465ceeac57a600b2fa3bd26632edcd90a655",
"index": 2911,
"step-1": "<mask token>\n\n\nclass Example(QWidget):\n\n\n class A(QWidget):\n\n def __init__(self):\n super().__init__()\n self.initUI()\n\n def initUI(self):\n self.setGeometry(300, 300, 300... | [
7,
8,
11,
16,
17
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution(object):
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution(object):
def removeNthFromEnd(self, head, n):
dummy = ListNode(-1)
dummy.next = head
first, second = dummy, dummy
for ... | flexible | {
"blob_id": "7e71c97070285b051b23448c755e3d41b2909dda",
"index": 3884,
"step-1": "<mask token>\n",
"step-2": "class Solution(object):\n <mask token>\n",
"step-3": "class Solution(object):\n\n def removeNthFromEnd(self, head, n):\n dummy = ListNode(-1)\n dummy.next = head\n first, s... | [
0,
1,
2
] |
# -*- coding: utf-8 -*-
import scrapy
import json, time, sys, random, re, pyssdb
from scrapy.utils.project import get_project_settings
from spider.items import GoodsSalesItem
goods_list = []
'''获取店铺内产品信息'''
class PddMallGoodsSpider(scrapy.Spider):
name = 'pdd_mall_goods'
mall_id_hash = 'pdd_mall_id_ha... | normal | {
"blob_id": "f33190df35a6b0b91c4dd2d6a58291451d06e29a",
"index": 3529,
"step-1": "<mask token>\n\n\nclass PddMallGoodsSpider(scrapy.Spider):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def start_requests(self):\n mall... | [
3,
4,
5,
9,
10
] |
<|reserved_special_token_0|>
def is_mango_seller(name):
return name[-1] == 'm'
def search_mango_seller(name):
search_queue = deque()
searched = []
global graph
search_queue += graph[name]
while search_queue:
person = search_queue.popleft()
if not person in searched:
... | flexible | {
"blob_id": "e881fcfce933d8f3bafcbaab039ddcf98827bf5e",
"index": 4244,
"step-1": "<mask token>\n\n\ndef is_mango_seller(name):\n return name[-1] == 'm'\n\n\ndef search_mango_seller(name):\n search_queue = deque()\n searched = []\n global graph\n search_queue += graph[name]\n while search_queue:... | [
2,
3,
4,
5,
6
] |
#ABC114 A - クイズ
print("ABC" if input()=="1" else "chokudai")
| normal | {
"blob_id": "14d31a4b7491a7f7a64cd151e79c23546e4a3cd2",
"index": 7683,
"step-1": "<mask token>\n",
"step-2": "print('ABC' if input() == '1' else 'chokudai')\n",
"step-3": "#ABC114 A - クイズ\nprint(\"ABC\" if input()==\"1\" else \"chokudai\")\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,... | [
0,
1,
2
] |
# Generated by Django 3.2 on 2021-04-21 13:21
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('rate', '0003_auto_20210421_1316'),
]
operations = [
migrations.AlterField(
model_name='song',
name='overall_rating',
... | normal | {
"blob_id": "d46cda5354640e1c87432d39a2e949d6db034edc",
"index": 6413,
"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 = [('rate', '000... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/python
#encoding=utf8
import sys
import tushare as ts
def local_main():
if len(sys.argv) != 2:
print sys.argv[0], " [stock id]"
return
stock_id = sys.argv[1]
df = ts.get_hist_data(stock_id)
df.to_excel(stock_id + '_his.xlsx', sheet_name = stock_id)
if __name__ == '__main__... | normal | {
"blob_id": "81a53d08ab36e85dd49cf1f3d9c22c1f18605149",
"index": 6233,
"step-1": "#!/usr/bin/python\n#encoding=utf8\n\nimport sys\nimport tushare as ts\n\ndef local_main():\n if len(sys.argv) != 2:\n print sys.argv[0], \" [stock id]\"\n return\n\n stock_id = sys.argv[1]\n df = ts.get_hist_... | [
0
] |
<|reserved_special_token_0|>
class UIMainWindow(object):
<|reserved_special_token_0|>
def retranslateUI(self):
_translate = QtCore.QCoreApplication.translate
self.main_window.setWindowTitle(_translate('main_window',
'SentiCompare'))
self.add_button.setText(_translate('main... | flexible | {
"blob_id": "a555226b14223dca688d10b811eb36fb229360ce",
"index": 2457,
"step-1": "<mask token>\n\n\nclass UIMainWindow(object):\n <mask token>\n\n def retranslateUI(self):\n _translate = QtCore.QCoreApplication.translate\n self.main_window.setWindowTitle(_translate('main_window',\n ... | [
4,
6,
7,
8,
9
] |
'''
Statistics models module. This module contains the database models for the
Statistics class and the StatisticsCategory class.
@author Hubert Ngu
@author Jason Hou
'''
from django.db import models
class Statistics(models.Model):
'''
Statistics model class. This represents a single tuple in the
... | normal | {
"blob_id": "728f9402b3ce4b297be82b3ba1a17c4180ac7c0d",
"index": 8839,
"step-1": "<mask token>\n\n\nclass Statistics(models.Model):\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 token>\n... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def comp_point_ref(self, is_set=False):
"""Compute the point ref of the Surface
Parameters
----------
self : SurfLine
A SurfLine object
is_set: bool
True to update the point_ref property
... | flexible | {
"blob_id": "b7721e95cfb509a7c0c6ccdffa3a8ca2c6bd6033",
"index": 6713,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef comp_point_ref(self, is_set=False):\n \"\"\"Compute the point ref of the Surface\n\n Parameters\n ----------\n self : SurfLine\n A SurfLine object\n is_set: ... | [
0,
1,
2
] |
from scipy.stats import mannwhitneyu
import matplotlib.patches as patches
import os
import numpy
import pandas
from matplotlib.gridspec import GridSpec
from scipy.cluster.hierarchy import fcluster, linkage, dendrogram
from scipy.spatial.distance import squareform
import seaborn as sns
from scipy.stats import spearmanr
... | normal | {
"blob_id": "bfd31d0b80511721ee5117daced04eaf63679fd8",
"index": 2230,
"step-1": "<mask token>\n\n\ndef get_clusters(link, dn, inds, th=0.7):\n clst = fcluster(link, criterion='distance', t=th)\n return pandas.Series(index=inds, data=clst).iloc[dn['leaves']]\n\n\ndef draw_significant_groups(groups, dn_ax, ... | [
4,
5,
6,
7,
8
] |
from datetime import datetime
import whois
def age_domain(url):
try:
w = whois.whois(url)
if(w):
for l in w.expiration_date:
d1 = datetime.date(l)
print(d1)
for l1 in w.creation_date:
d2 = datetime.date(l1)
print(d2)
diff = (d1 - ... | normal | {
"blob_id": "07d574060ded0d98734b4f184dcba7377b3a5480",
"index": 685,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef age_domain(url):\n try:\n w = whois.whois(url)\n if w:\n for l in w.expiration_date:\n d1 = datetime.date(l)\n print(d1)\n ... | [
0,
1,
2,
3
] |
from django import forms
from . import models
from .validators import validate_metadata
class ServiceProviderForm(forms.ModelForm):
xml = forms.CharField(label='SAML Metadata XML',
widget=forms.Textarea,
validators=[validate_metadata])
class Meta:
... | normal | {
"blob_id": "e018d28cbacb568596eb9a5134581db960111e14",
"index": 9835,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass ServiceProviderForm(forms.ModelForm):\n <mask token>\n\n\n class Meta:\n model = models.ServiceProvider\n fields = 'xml',\n",
"step-3": "<mask token>\n\n\n... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class ForgotForm(FlaskForm):
email = EmailField('Email Id*', validators=[DataRequired(), Email()])
design = SelectField(u'Designation*', choices=[('admin', 'Admin'), (
'stud', 'Student')], validators=[DataRequired()])
submit = SubmitField('Change your Password')
clas... | flexible | {
"blob_id": "32ed07a89a6f929a6c4b78fd79e687b85e01015b",
"index": 535,
"step-1": "<mask token>\n\n\nclass ForgotForm(FlaskForm):\n email = EmailField('Email Id*', validators=[DataRequired(), Email()])\n design = SelectField(u'Designation*', choices=[('admin', 'Admin'), (\n 'stud', 'Student')], valida... | [
8,
10,
11,
12,
14
] |
from sklearn.model_selection import train_test_split
from azureml.core import Run
from sklearn.ensemble import RandomForestClassifier
import pandas as pd
import argparse
import os
import joblib
import numpy as np
# Get the experiment run context
run = Run.get_context()
# Get arguments
parser = argparse.ArgumentParse... | normal | {
"blob_id": "66c2d73c100f7fc802e66f2762c92664e4b93fcd",
"index": 5736,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nparser.add_argument('--in_n_estimator', type=int, default=8)\nparser.add_argument('--in_criterion', type=str, default='gini')\nparser.add_argument('--in_max_depth', type=int, default=2)\n... | [
0,
1,
2,
3,
4
] |
"""
Created on Dec 1, 2014
@author: Ira Fich
"""
import random
from igfig.containers import WeightedList
class Replacer():
"""
A class that replaces itself with a subclass of itself when you instantiate it
"""
subclass_weight = 0
def __new__(cls, *args, **kwargs):
subs = WeightedList(cls.__subclasses__(),... | normal | {
"blob_id": "3a878c91218dfbf23477ae5b7561e9eecfcd1350",
"index": 5053,
"step-1": "<mask token>\n\n\nclass Replacer:\n <mask token>\n <mask token>\n\n def __new__(cls, *args, **kwargs):\n subs = WeightedList(cls.__subclasses__(), [sub.subclass_weight for\n sub in cls.__subclasses__()])\... | [
7,
10,
11,
13,
15
] |
newList = []
noDuplicate = []
while True:
elem = input("Enter a letter : (type quit to quit) ")
if elem.lower() != "quit":
newList.append(elem)
else:
break
for item in newList:
if item not in noDuplicate:
noDuplicate.append(item)
print(noDuplicate) | normal | {
"blob_id": "7273592ab8fea10d9a3cde58690063690c74b746",
"index": 4635,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile True:\n elem = input('Enter a letter : (type quit to quit) ')\n if elem.lower() != 'quit':\n newList.append(elem)\n else:\n break\nfor item in newList:\n i... | [
0,
1,
2,
3
] |
import sys
from arguments_parser import parse_args
from open_ldap import OpenLdap
from csv_parser import parse_csv, random_password
from smtp_mail import SmtpServer
def create_user(open_ldap, smtp, entries):
"""
If the 'ldap_insert' returns True, then
the email will be send with the account info.
"""
... | normal | {
"blob_id": "4f0a0089ad128edca3052da58a4c71f935592e25",
"index": 4499,
"step-1": "<mask token>\n\n\ndef create_user(open_ldap, smtp, entries):\n \"\"\"\n If the 'ldap_insert' returns True, then\n the email will be send with the account info.\n \"\"\"\n try:\n if open_ldap.ldap_insert(entrie... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for i in range(n):
t, x, y = map(int, input().split())
diff = abs(x - p[0]) + abs(y - p[1])
time = t - b
if diff > time or time % 2 != diff % 2:
flg = False
break
else:
b = t
p[0... | flexible | {
"blob_id": "8bc465a1b546907d8a9e5eee2cae672befb1ea13",
"index": 7808,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(n):\n t, x, y = map(int, input().split())\n diff = abs(x - p[0]) + abs(y - p[1])\n time = t - b\n if diff > time or time % 2 != diff % 2:\n flg = False\n... | [
0,
1,
2,
3
] |
import csv
import hashdate as hd
with open('Grainger_Library.csv', newline='') as f:
reader = csv.reader(f)
data = list(reader)
del data[0]
gld = []
glo = []
data.sort(key=lambda x:x[1])
for i in range(0,len(data)):
gld.append((data[i][1],data[i][2]))
print('ahd:')
#print(ahd)
glh = hd.hashdate(365,2020... | normal | {
"blob_id": "79ff164c36cc5f0a2382a571ec183952a03e66cc",
"index": 9570,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('Grainger_Library.csv', newline='') as f:\n reader = csv.reader(f)\n data = list(reader)\ndel data[0]\n<mask token>\ndata.sort(key=lambda x: x[1])\nfor i in range(0, len(d... | [
0,
1,
2,
3,
4
] |
from copy import deepcopy
from datetime import date, timedelta
from hashlib import sha256
import starkbank
from starkbank import BoletoPayment
from .boleto import generateExampleBoletosJson
example_payment = BoletoPayment(
line="34191.09008 61713.957308 71444.640008 2 83430000984732",
scheduled="2020-02-29",
... | normal | {
"blob_id": "383d3b35fbfb7921111b28c3160173ce1c200387",
"index": 637,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef generateExampleBoletoPaymentsJson(n=1, next_day=False):\n boletos = generateExampleBoletosJson(n=n)\n boletos = starkbank.boleto.create(boletos)\n payments = []\n for b... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
"""Success request logging.
This logging is used by "CheckZope" to determine the amount
of work performed by Zope (in order not to bother it with monitor
probes when it is heavily active) and to detect an unreasonable
error rate.
This logging writes two files "<base>_good.<date>" and "<base>_b... | normal | {
"blob_id": "2edbf18c90da1ff40fd9abaf25a35dbdaf733bc1",
"index": 2786,
"step-1": "<mask token>\n\n\n@adapter(IProcessStarting)\ndef start_successlogging(unused):\n \"\"\"start successlogging if configured.\"\"\"\n from App.config import getConfiguration\n config = getConfiguration().product_config.get('... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
class RestApiTestSuite(unittest.TestCase):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
@pytest.fixture(autouse=True)
def setup_gateway(self, metadata):
self.gateway = proactive.ProActi... | flexible | {
"blob_id": "da2c615b8fab8de6bd63864508da254a46e65bb8",
"index": 4543,
"step-1": "<mask token>\n\n\nclass RestApiTestSuite(unittest.TestCase):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n @pytest.fixture(autouse=True)\n def setup_gateway(self, metadata):\n self.gateway... | [
4,
7,
8,
9,
10
] |
# -*- coding: utf-8 -*-
# Generated by Django 1.10.3 on 2018-12-20 13:06
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('login', '0006_usermovies_img'),
]
operations = [
migrations.AddField(
... | normal | {
"blob_id": "e67cbddf10440e8a31373e05a82840677d3045f5",
"index": 4388,
"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 = [('login', '00... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
app_name = 'Accounts'
urlpatterns = [path('update_info', views.update_info, name='update_info'),
path('create_user', views.create_user, name='create_user'), path(
'change_password', views.change_password, name='change_pass... | flexible | {
"blob_id": "bfb778a2ecf43a697bc0e3449e9302142b20e1f4",
"index": 4278,
"step-1": "<mask token>\n",
"step-2": "<mask token>\napp_name = 'Accounts'\nurlpatterns = [path('update_info', views.update_info, name='update_info'),\n path('create_user', views.create_user, name='create_user'), path(\n 'change_passw... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def create_local_imports_files(tmp_path):
path_dir = os.path.join(tmp_path, 'dir_local_imports')
fln_func = os.path.join(path_dir, 'file_func.py')
fln_gen = os.path.join(path_dir, 'file_gen.py')
os.makedirs(path_dir, exist_ok=True)
code1 = """
from bluesky_queueserver.... | flexible | {
"blob_id": "ad1ec5dd8fae290ab6cb73b17c5522e062261359",
"index": 6698,
"step-1": "<mask token>\n\n\ndef create_local_imports_files(tmp_path):\n path_dir = os.path.join(tmp_path, 'dir_local_imports')\n fln_func = os.path.join(path_dir, 'file_func.py')\n fln_gen = os.path.join(path_dir, 'file_gen.py')\n ... | [
5,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def main():
config = {'spark.jars.packages':
'io.delta:delta-core_2.12:0.8.0,org.postgresql:postgresql:9.4.1211,org.apache.spark:spark-streaming-kafka-0-10_2.12:3.0.0,org.apache.spark:spark-sql-kafka-0-10_2.12:3.0.0'... | flexible | {
"blob_id": "23099b29fb5898c2556d1612690e33860662ca35",
"index": 9846,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main():\n config = {'spark.jars.packages':\n 'io.delta:delta-core_2.12:0.8.0,org.postgresql:postgresql:9.4.1211,org.apache.spark:spark-streaming-kafka-0-10_2.12:3.0.0,or... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(msg * copies)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
name = input('Enter your name : ')
age = int(input('Enter your age : '))
year = int(100 - age + datetime.now().year)
copies = int(input('How many cop... | flexible | {
"blob_id": "948b793359555f98872e0bdbf6db970ed1ff3b83",
"index": 7046,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(msg * copies)\n",
"step-3": "<mask token>\nname = input('Enter your name : ')\nage = int(input('Enter your age : '))\nyear = int(100 - age + datetime.now().year)\ncopies = int(inp... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def gprmc_convert(line):
"""Translates $GPRMC line into documented array
str line - the GPRMC line
returns - the data documented into array
"""
gps = line.strip().split(',')
if gps[2] == 'V':
return
raw_date = gps[9]
time = ''
date = raw_d... | flexible | {
"blob_id": "dc5630e17bb6ed85157b06108250427be41416d1",
"index": 7766,
"step-1": "<mask token>\n\n\ndef gprmc_convert(line):\n \"\"\"Translates $GPRMC line into documented array\n str line - the GPRMC line\n returns - the data documented into array\n \"\"\"\n gps = line.strip().split(',')\n ... | [
2,
3,
4,
5,
6
] |
from pynput import keyboard
# list of chars entered by the user
list = []
number_of_chars = 0
# if entered chars go above MAX LENGTH they will be written inside a file
MAX_LENGTH = 300
def on_press(key):
global number_of_chars
global list
list.append(key)
number_of_chars+=1
if number_of_cha... | normal | {
"blob_id": "e60fcf19560b4826577797c8ae8b626ff984dcfd",
"index": 6923,
"step-1": "<mask token>\n\n\ndef on_release(key):\n if key == keyboard.Key.esc:\n write_in_file()\n return False\n\n\ndef write_in_file():\n file = open('strokes.txt', 'a')\n for k in list:\n file.writelines('{}\... | [
2,
3,
4,
5,
7
] |
def densenet(D,DT,F,model):
import scipy.io as sio
import time
import os
import math
import numpy as np
import matplotlib.pyplot as plt
Dataset = D
if DT == 'org':
data_type = 'original'
else:
data_type = 'augmented'
fs = model.fs
fm1 = model.fm1
batch_size = model.ba... | normal | {
"blob_id": "48270f70a9d69d15f808f22ec2d11d337b2c4845",
"index": 7414,
"step-1": "<mask token>\n\n\nclass MyModel:\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\n\n<mask token>\n",
"step-2": "<... | [
1,
2,
3,
5,
6
] |
#!/usr/bin/evn python
#-*-coding:utf8 -*-
import os, sys, json
class settings(object):
filename = ''
config = {}
def __init__(self):
self.DEBUG = os.environ.get('RdsMonitor_DEBUG', 0)
def get_settings(self):
"""Parses the settings from redis-live.conf.
"""
# TODO: Consider YAML. Human writable, mac... | normal | {
"blob_id": "2c960685eaa14861c1c5b3ddb38b366a3e0e8e86",
"index": 1339,
"step-1": "#!/usr/bin/evn python\n#-*-coding:utf8 -*-\n\n\nimport os, sys, json\n\nclass settings(object):\n\tfilename = ''\n\tconfig = {}\n\t\n\tdef __init__(self):\n\t\tself.DEBUG = os.environ.get('RdsMonitor_DEBUG', 0)\n\t\t\n\tdef get_set... | [
0
] |
import sqlite3
import argparse
import json
import index_db
from collections import defaultdict
def query_doc(cursor, lang, title):
cursor.execute(index_db.select_lang_title, (lang, title))
result = cursor.fetchone()
if not result:
return None
return {
'lang': result[0],
'doc_id... | normal | {
"blob_id": "95e7e025660e71cbdf6a6a0812964fc26d4beec0",
"index": 9657,
"step-1": "<mask token>\n\n\ndef query_doc(cursor, lang, title):\n cursor.execute(index_db.select_lang_title, (lang, title))\n result = cursor.fetchone()\n if not result:\n return None\n return {'lang': result[0], 'doc_id':... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
def main(forecast, name, levels, *args, **kwargs):
nt = len(forecast)
rows = nt / columns + 1
fig = plt.figure(figsize=(18, 10 * float(rows) / columns))
for n, cubes in enumerate(forecast):
row = n / columns
column = n - row * columns
print(row, col... | flexible | {
"blob_id": "310e6e693cdce6ff71d06eac86214a21bef236d4",
"index": 7425,
"step-1": "<mask token>\n\n\ndef main(forecast, name, levels, *args, **kwargs):\n nt = len(forecast)\n rows = nt / columns + 1\n fig = plt.figure(figsize=(18, 10 * float(rows) / columns))\n for n, cubes in enumerate(forecast):\n ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class ProductsOrderCartSerializer(ModelSerializer):
class Meta:
model = Product
fields = ['id', 'title', 'slug', 'image']
class ProductDetailSerializer(TaggitSerializer, ModelSerializer):
tags = TagListSerializerField()
gallery = SerializerMethodField()
... | flexible | {
"blob_id": "8be6031caad26ec6b6b99b8d8b8f80d16ad243d4",
"index": 7706,
"step-1": "<mask token>\n\n\nclass ProductsOrderCartSerializer(ModelSerializer):\n\n\n class Meta:\n model = Product\n fields = ['id', 'title', 'slug', 'image']\n\n\nclass ProductDetailSerializer(TaggitSerializer, ModelSerial... | [
9,
15,
16,
17,
21
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def matrix(m):
for i in range(len(m)):
for j in range(len(m[0])):
m[i][j] = m[i][j] ** 2
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def matrix(m):
for i in range(len(m)):
for j in range(len(m[0])):
... | flexible | {
"blob_id": "f46dd5217c8e015546d7fff7ee52569ecc2c8e41",
"index": 5487,
"step-1": "<mask token>\n",
"step-2": "def matrix(m):\n for i in range(len(m)):\n for j in range(len(m[0])):\n m[i][j] = m[i][j] ** 2\n\n\n<mask token>\n",
"step-3": "def matrix(m):\n for i in range(len(m)):\n ... | [
0,
1,
2,
3,
4
] |
import psycopg2
host = "datavis.cauuh8vzeelb.us-east-1.rds.amazonaws.com"
database = "top5"
user = "teamwonder"
password = "visproject"
Gentrifying = [10002,10003,10009,10026,10027,10029,10030,10031,10032,10033,10034,10035,10037,10039,10040,10454,10455,10456,10457,10458,10459,10460,10474,11102,11103,11105,11106,11206... | normal | {
"blob_id": "0ebf5646ee9693b7d0c1de61436e05b3725b2c9f",
"index": 2560,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nhost = 'datavis.cauuh8vzeelb.us-east-1.rds.amazonaws.com'\ndatabase = 'top5'\nuser = 'teamwonder'\npassword = 'visproject'\nGentrifying = [10002, 10003, 10009, 10026, 10027, 10029, 10030,... | [
0,
1,
2,
3
] |
from .__main__ import datajson_write, datajson_read
| normal | {
"blob_id": "2269e74c006833976c3a28cd52c238e2dde20051",
"index": 5871,
"step-1": "<mask token>\n",
"step-2": "from .__main__ import datajson_write, datajson_read\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
from .base import Sort
| flexible | {
"blob_id": "de3a96d46b7eaf198b33efe78b21ef0207dcc609",
"index": 8424,
"step-1": "<mask token>\n",
"step-2": "from .base import Sort\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
clf.fit(X, y)
print('class_prior:', clf.class_prior)
print('class_count_:', clf.class_count_)
print('class_log_prior_:', clf.class_log_prior_)
print('feature_count_:', clf.feature_count_)
print('n_features_:', clf.n_features_)
pri... | flexible | {
"blob_id": "98a1fab8cee91f37ceee2cfd868d3a5756a055b0",
"index": 7628,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nclf.fit(X, y)\nprint('class_prior:', clf.class_prior)\nprint('class_count_:', clf.class_count_)\nprint('class_log_prior_:', clf.class_log_prior_)\nprint('feature_count_:', clf.feature_cou... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for x in xs:
dist += min(x, K - x)
print(dist * 2)
<|reserved_special_token_1|>
N = int(input())
K = int(input())
xs = list(map(int, input().split()))
dist = 0
for x in xs:
dist += min(x, K - x)
print(dist * 2)
| flexible | {
"blob_id": "a65ab0faf08c13f007a132fb92f358a35834fdb7",
"index": 2556,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor x in xs:\n dist += min(x, K - x)\nprint(dist * 2)\n",
"step-3": "N = int(input())\nK = int(input())\nxs = list(map(int, input().split()))\ndist = 0\nfor x in xs:\n dist += min... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
while count < 9:
print('Number:', count)
count = count + 1
print('Good Bye')
<|reserved_special_token_0|>
for fruit in fruits:
print('current fruits:', fruit)
print('Good bye')
<|reserved_special_token_1|>
count = 0... | flexible | {
"blob_id": "9b3040fa02cf8f039bac146f8a73384731c56722",
"index": 9142,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile count < 9:\n print('Number:', count)\n count = count + 1\nprint('Good Bye')\n<mask token>\nfor fruit in fruits:\n print('current fruits:', fruit)\nprint('Good bye')\n",
"... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def contruct_tree(pre_order, index=0):
index += 1
if index >= len(pre_order):
raise IndexError('wtf is wrong with you?')
root = pre_order[index]
if root is None:
return None, index
node = BST(... | flexible | {
"blob_id": "3aee336956ac6f962c34f51a27dc4abebf2cc7c8",
"index": 8474,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef contruct_tree(pre_order, index=0):\n index += 1\n if index >= len(pre_order):\n raise IndexError('wtf is wrong with you?')\n root = pre_order[index]\n if root i... | [
0,
1,
2,
3
] |
# V0
class Codec:
def encode(self, strs):
s = ""
for i in strs:
s += str(len(i)) + "#" + i
return s
def decode(self, s):
i, str = 0, []
while i < len(s):
sharp = s.find("#", i)
l = int(s[i:sharp])
str.append(s[sharp + 1:sh... | normal | {
"blob_id": "b94392c9c6547415326d80ff0923cb8ba9251783",
"index": 5724,
"step-1": "<mask token>\n\n\nclass Codec:\n <mask token>\n\n def decode(self, s):\n \"\"\"Decodes a single string to a list of strings.\n \n :type s: str\n :rtype: List[str]\n \"\"\"\n i, str = ... | [
5,
6,
7,
8,
10
] |
import uuid
from datetime import date
import os
import humanize
class Context:
def __init__(self, function_name, function_version):
self.function_name = function_name
self.function_version = function_version
self.invoked_function_arn = "arn:aws:lambda:eu-north-1:000000000000:function:{}".f... | normal | {
"blob_id": "1c685514f53a320226402a4e4d8f3b3187fad615",
"index": 7814,
"step-1": "<mask token>\n\n\nclass Context:\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Context:\n\n def __init__(self, function_name, function_version):\n self.function_name = function_name\n ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class MeasurementsSerializer(serializers.ModelSerializer):
class Meta:
model = Measurements
fields = '__all__'
<|reserved_special_token_0|>
class CountSerializer(serializers.Serializer):
key = serializers.CharField(max_length=20)
value = serializers.Int... | flexible | {
"blob_id": "44cbe1face91d3ac7edcd93d0b470bce90c8b674",
"index": 2916,
"step-1": "<mask token>\n\n\nclass MeasurementsSerializer(serializers.ModelSerializer):\n\n\n class Meta:\n model = Measurements\n fields = '__all__'\n <mask token>\n\n\nclass CountSerializer(serializers.Serializer):\n ... | [
9,
10,
11,
12,
15
] |
#!/usr/bin/env python3
import argparse
import json
import os
import random
import timeit
from glob import glob
import numpy as np
def parse_args():
"""[summary]
Returns:
[type]: [description]
"""
parser = argparse.ArgumentParser()
parser.add_argument('--train_dir',
... | normal | {
"blob_id": "71eadf5073b5ed13c7d4a58b2aeb52f550a32238",
"index": 3104,
"step-1": "<mask token>\n\n\ndef parse_args():\n \"\"\"[summary]\n\n Returns:\n [type]: [description]\n \"\"\"\n parser = argparse.ArgumentParser()\n parser.add_argument('--train_dir', help=\n 'directory containin... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def lm_res(snps, gene, cov):
res = pd.DataFrame(np.zeros([snps.shape[0], 2], dtype=np.float32))
res.index = snps.index
res.columns = ['beta', 'pval']
for i in range(snps.shape[0]):
X = pd.concat([snps.ilo... | flexible | {
"blob_id": "2f64aac7032ac099870269659a84b8c7c38b2bf0",
"index": 8385,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef lm_res(snps, gene, cov):\n res = pd.DataFrame(np.zeros([snps.shape[0], 2], dtype=np.float32))\n res.index = snps.index\n res.columns = ['beta', 'pval']\n for i in rang... | [
0,
1,
2,
3,
4
] |
from collections import deque
def solution(play_time, adv_time, logs):
'''
Strategy :
adv_start_time을 log start time 부터 < 995959 - adv time
sliding window
Step 1.
String time -> integer time
Step 2. pseudo code : Two pointer algorithm
max time = 0
return max time
'''
... | normal | {
"blob_id": "cb50a5352b0ad7b04dee9393c50da54fdf507376",
"index": 2018,
"step-1": "<mask token>\n\n\ndef str2int(strtime: str):\n hh, mm, ss = strtime.split(':')\n return 3600 * int(hh) + 60 * int(mm) + int(ss)\n\n\ndef int2str(inttime: int):\n hh = inttime // 3600\n mm = inttime % 3600 // 60\n ss ... | [
2,
3,
4,
5,
6
] |
from http import HTTPStatus
from ninja import Router
mock_post_router = Router()
@mock_post_router.get(
"/mock_posts",
url_name="mock_post_list",
summary="전체 mock post의 list를 반환한다",
response={200: None},
)
def retrieve_all_mock_posts(request):
return HTTPStatus.OK
| normal | {
"blob_id": "dcb57ecf2c72b8ac816bb06986d80544ff97c669",
"index": 5915,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@mock_post_router.get('/mock_posts', url_name='mock_post_list', summary=\n '전체 mock post의 list를 반환한다', response={(200): None})\ndef retrieve_all_mock_posts(request):\n return HT... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def select(arr, k):
n = len(arr)
if not 0 <= k < n:
raise ValueError('not valid index in array')
if n <= 1:
return arr[0]
pivot = random.choice(arr)
L, E, G = [], [], []
for data in arr:
if data < pivot:
L.append(data)
el... | flexible | {
"blob_id": "69d3a39dc024929eaf6fb77e38a7a818d2886cf7",
"index": 8512,
"step-1": "<mask token>\n\n\ndef select(arr, k):\n n = len(arr)\n if not 0 <= k < n:\n raise ValueError('not valid index in array')\n if n <= 1:\n return arr[0]\n pivot = random.choice(arr)\n L, E, G = [], [], []\... | [
1,
2,
3,
4,
5
] |
"""
Question:
You are given a string s consisting only of digits 0-9, commas ,, and dots .
Your task is to complete the regex_pattern defined below, which will be used to
re.split() all of the , and . symbols in s.
It’s guaranteed that every comma and every dot in s is preceded and followed
by a digit.
Sample Input... | normal | {
"blob_id": "020691fe2c7e7092d45415b72ce1804618421a2a",
"index": 9519,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('\\n'.join(re.split(regex_pattern, input())))\n",
"step-3": "<mask token>\nregex_pattern = '[,.]'\nprint('\\n'.join(re.split(regex_pattern, input())))\n",
"step-4": "<mask token... | [
0,
1,
2,
3,
4
] |
import requests
import json
import io
import sys
names = ['abc-news', 'abc-news-au', 'aftenposten','al-jazeera-english','ars-technica','associated-press','australian-financial-review','axios', 'bbc-news', 'bbc-sport','bleacher-report', 'bloomberg','breitbart-news','business-insider', 'business-insider-uk','buzzfeed','... | normal | {
"blob_id": "590baf17d9fdad9f52869fa354112d3aa5f7d5f0",
"index": 8943,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('[')\nsys.stdout.close()\nfor name in names:\n url = ('https://newsapi.org/v2/everything?sources=' + name +\n '&pageSize=100&language=en&from=2018-04-01&to=2018-04-01&apiK... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def get_jwst_coords(outDir):
log.info('Creating and saving aperture')
jwst_pup = poppy.MultiHexagonAperture(rings=2, flattoflat=FLAT_TO_FLAT)
jwst_pup.display(colorbar=False)
plt.title('JWST telescope pupil')
for i in range(NB_SEG + 1):
ycen, xcen = jwst_pup._h... | flexible | {
"blob_id": "e59763991974f4bfcd126879dd9aabd44bd89419",
"index": 1406,
"step-1": "<mask token>\n\n\ndef get_jwst_coords(outDir):\n log.info('Creating and saving aperture')\n jwst_pup = poppy.MultiHexagonAperture(rings=2, flattoflat=FLAT_TO_FLAT)\n jwst_pup.display(colorbar=False)\n plt.title('JWST te... | [
6,
7,
8,
9,
10
] |
<|reserved_special_token_0|>
def get_version(filename):
import ast
version = None
with open(filename) as f:
for line in f:
if line.startswith('__version__'):
version = ast.parse(line).body[0].value.s
break
else:
raise ValueError('No v... | flexible | {
"blob_id": "d3b55863c6e3a1b6cbdcec37db81ee42b769938d",
"index": 9039,
"step-1": "<mask token>\n\n\ndef get_version(filename):\n import ast\n version = None\n with open(filename) as f:\n for line in f:\n if line.startswith('__version__'):\n version = ast.parse(line).body... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class PrimaryuserConfig(AppConfig):
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class PrimaryuserConfig(AppConfig):
name = 'PrimaryUser'
<|reserved_special_token_1|>
fro... | flexible | {
"blob_id": "82c10076ba73723b696e3e33280296c2a24f20b9",
"index": 4187,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass PrimaryuserConfig(AppConfig):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass PrimaryuserConfig(AppConfig):\n name = 'PrimaryUser'\n",
"step-4": "from django.app... | [
0,
1,
2,
3
] |
# Uses python3
import numpy as np
def fibonaci(n):
if n <= 1:
return n
F = np.empty(shape=(n + 1))
F[0] = 0
F[1] = 1
for i in range(2, len(F)):
F[i] = F[i - 1] + F[i - 2]
return F[n]
n = int(input())
print(int(fibonaci(n)))
| normal | {
"blob_id": "67516551b595c02e70a0ba4005df8a97ba71b17e",
"index": 1419,
"step-1": "<mask token>\n\n\ndef fibonaci(n):\n if n <= 1:\n return n\n F = np.empty(shape=n + 1)\n F[0] = 0\n F[1] = 1\n for i in range(2, len(F)):\n F[i] = F[i - 1] + F[i - 2]\n return F[n]\n\n\n<mask token>\... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
etc_dictionary = {'2 30대': '이삼십대', '20~30대': '이삼십대', '20, 30대': '이십대 삼십대',
'1+1': '원플러스원', '3에서 6개월인': '3개월에서 육개월인'}
english_dictionary = {'Devsisters': '데브시스터즈', 'track': '트랙', 'LA': '엘에이',
'LG': '엘지', 'KOREA': '코리아', 'JSA': '제이에스에이', 'PGA': '피지에이', ... | flexible | {
"blob_id": "ccd1e57518065963158984dda52297db45ce204e",
"index": 2471,
"step-1": "<mask token>\n",
"step-2": "etc_dictionary = {'2 30대': '이삼십대', '20~30대': '이삼십대', '20, 30대': '이십대 삼십대',\n '1+1': '원플러스원', '3에서 6개월인': '3개월에서 육개월인'}\nenglish_dictionary = {'Devsisters': '데브시스터즈', 'track': '트랙', 'LA': '엘에이',\n ... | [
0,
1,
2
] |
<|reserved_special_token_0|>
def test_forgotten_initialized_on_protected():
blueprint = Blueprint('Test')
@blueprint.get('/protected')
@protected()
def protected_hello_world(request):
return json({'message': 'hello world'})
@blueprint.route('/scoped')
@scoped('something')
async d... | flexible | {
"blob_id": "55fc197eebc4e06466e0fc0458957d0460602eef",
"index": 2032,
"step-1": "<mask token>\n\n\ndef test_forgotten_initialized_on_protected():\n blueprint = Blueprint('Test')\n\n @blueprint.get('/protected')\n @protected()\n def protected_hello_world(request):\n return json({'message': 'he... | [
6,
7,
8,
11,
13
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(X)
<|reserved_special_token_0|>
print(A * B)
print(X[0])
print(X[0][1])
for row in X:
print(row)
<|reserved_special_token_0|>
print(newX)
print(X > 15)
<|reserved_special_token_0|>
plt.plot(x, y)
plt.show()
<|reserved_sp... | flexible | {
"blob_id": "ba702a9c5d9d31e48b047c106d77cf1707031d70",
"index": 1795,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(X)\n<mask token>\nprint(A * B)\nprint(X[0])\nprint(X[0][1])\nfor row in X:\n print(row)\n<mask token>\nprint(newX)\nprint(X > 15)\n<mask token>\nplt.plot(x, y)\nplt.show()\n<mask... | [
0,
1,
2,
3,
4
] |
import numpy as np
def shufflelists(lists):
li = np.random.permutation(len(lists[0])
lo = []
for i in range(len(li)):
| normal | {
"blob_id": "fc01c6fb812fe78ca04496494d68fcc90ae706f5",
"index": 3605,
"step-1": "import numpy as np\n\ndef shufflelists(lists):\n li = np.random.permutation(len(lists[0])\n lo = []\n for i in range(len(li)):\n \n",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for line in fhand:
line.tranc
<|reserved_special_token_1|>
<|reserved_special_token_0|>
fhand = open('romeo-full.txt')
counts = dict()
for line in fhand:
line.tranc
<|reserved_special_token_1|>
import string
fhand = ... | flexible | {
"blob_id": "5493887e32dbe7ae27eca79d28da8488183b37a3",
"index": 8792,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor line in fhand:\n line.tranc\n",
"step-3": "<mask token>\nfhand = open('romeo-full.txt')\ncounts = dict()\nfor line in fhand:\n line.tranc\n",
"step-4": "import string\nfhand... | [
0,
1,
2,
3,
4
] |
from django.conf import settings
from django.http import HttpResponse, HttpResponseBadRequest, HttpResponseForbidden
from django.views.decorators.csrf import csrf_exempt
from linebot import LineBotApi, WebhookParser
from linebot.exceptions import InvalidSignatureError, LineBotApiError
from linebot.models import ... | normal | {
"blob_id": "19f202c32e1cf9f7ab2663827f1f98080f70b83e",
"index": 8313,
"step-1": "<mask token>\n\n\n@csrf_exempt\ndef callback(request):\n if request.method == 'POST':\n signature = request.META['HTTP_X_LINE_SIGNATURE']\n body = request.body.decode('utf-8')\n try:\n events = pa... | [
1,
2,
3,
4,
5
] |
# coding: utf-8
# ## Estimating Travel Time
#
#
# The objective of this document is proposing a prediction model for estimating the travel time of two
# specified locations at a given departure time. The main idea here is predicting the velocity of the trip. Given the distance between starting and ending point of t... | normal | {
"blob_id": "c1bb7b579e6b251ddce41384aef1243e411c5d0e",
"index": 1018,
"step-1": "<mask token>\n\n\ndef distance(row):\n source = row['start_lat'], row['start_lng']\n dest = row['end_lat'], row['end_lng']\n return vincenty(source, dest).miles\n\n\n<mask token>\n\n\ndef dropoff_to_MH(row):\n \"\"\"fin... | [
8,
9,
11,
12,
15
] |
"""Module containing class `Station`."""
from zoneinfo import ZoneInfo
import datetime
from vesper.util.named import Named
class Station(Named):
"""Recording station."""
def __init__(
self, name, long_name, time_zone_name,
latitude=None, longitude=None, elevation=None... | normal | {
"blob_id": "ad09880b9e06a129b9623be2a086ebcc8dc55c2c",
"index": 9079,
"step-1": "<mask token>\n\n\nclass Station(Named):\n <mask token>\n\n def __init__(self, name, long_name, time_zone_name, latitude=None,\n longitude=None, elevation=None):\n super().__init__(name)\n self._long_name ... | [
6,
7,
9,
10,
11
] |
#!/usr/bin/python3
"""City Module"""
from models.base_model import BaseModel
class City(BaseModel):
"""City Class
Public class attributes:
state_d: type string
name: type string
"""
state_id = ""
name = ""
| normal | {
"blob_id": "3f2c1a83ae0dfdba202038a209b90162ccddee36",
"index": 6115,
"step-1": "<mask token>\n\n\nclass City(BaseModel):\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass City(BaseModel):\n <mask token>\n state_id = ''\n name = ''\n",
"step-3": "<mask tok... | [
1,
2,
3,
4,
5
] |
import numpy
import yfinance as yf
import pandas as pd
import path
import math
pd.options.mode.chained_assignment = None # default='warn'
all_tickers = ['2020.OL',
'ABG.OL',
'ADE.OL',
'AFG.OL',
'AKAST.OL',
'AKER.OL',
'AKBM.OL',
... | normal | {
"blob_id": "22ffda3b2d84218af22bad7835689ec3d4959ab2",
"index": 3660,
"step-1": "<mask token>\n\n\ndef calculate_returns(ticker_data):\n returns_list = list()\n previous_ticker_day = None\n for ticker_day in ticker_data.itertuples():\n if previous_ticker_day == None:\n returns_list.ap... | [
6,
8,
9,
10,
11
] |
<|reserved_special_token_0|>
class DehazeNet(nn.Module):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class DehazeNet(nn.Module):
def __init__(self, input=16, groups=4):
super(DehazeNet, self).__init__()
self.conv... | flexible | {
"blob_id": "a8cf8d0965cb877d50cee403fbc30f27484f4f36",
"index": 8201,
"step-1": "<mask token>\n\n\nclass DehazeNet(nn.Module):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass DehazeNet(nn.Module):\n\n def __init__(self, input=16, groups=4):\n super(DehazeNet, self).__init_... | [
1,
2,
3,
4,
5
] |
import numpy as np
import time
import uuid
from datetime import datetime
log_host = "agent1"
class State:
def __init__(self, path, iterations):
self.path = path
self.iterations = iterations
def run(self):
assert 0, "run not implemented"
class BruteForceAttackState(State):
def ... | normal | {
"blob_id": "cf3b4e2c76091f95d24e8a987a63ece46503d6e8",
"index": 3459,
"step-1": "<mask token>\n\n\nclass BruteForceAttackState(State):\n\n def run(self):\n os_val = np.random.choice(['Windows7', 'Windows10', 'Ubuntu16',\n 'MacOS10'])\n addr_val = np.random.choice(['127.0.0.6', '127.0... | [
4,
7,
8,
9,
10
] |
# coding: UTF-8
import fileinput
import io
from locale import str
import os
__author__ = 'lidong'
def getDirList( p ):
p = p.replace( "/","\\")
if p[ -1] != "\\":
p = p+"\\"
a = os.listdir( p )
for x in a:
if(os.path.isfile( p + x )):
a, b = os.path.splitext( p + x )
... | normal | {
"blob_id": "e553da92b1bb5dfaa0fb7c702f5be4f66201c75b",
"index": 8843,
"step-1": "<mask token>\n\n\ndef getDirList(p):\n p = p.replace('/', '\\\\')\n if p[-1] != '\\\\':\n p = p + '\\\\'\n a = os.listdir(p)\n for x in a:\n if os.path.isfile(p + x):\n a, b = os.path.splitext(p... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def kind():
data = {}
with open('dataset.json', 'r') as read_file:
data = json.load(read_file)
return data['kind']
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
... | flexible | {
"blob_id": "630480e9458491a26ea9060bd36541a0d5805a11",
"index": 647,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef kind():\n data = {}\n with open('dataset.json', 'r') as read_file:\n data = json.load(read_file)\n return data['kind']\n\n\n<mask token>\n",
"step-3": "<mask toke... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def mais_populoso(dic):
p = 0
sp = 0
for t, i in dic.items():
for m in dic[t].values():
p += m
if p > sp:
sp = p
x = t
return x
| flexible | {
"blob_id": "2cbce618d1ec617d1c7dc0e9792b6a49361ec5a4",
"index": 13,
"step-1": "<mask token>\n",
"step-2": "def mais_populoso(dic):\n p = 0\n sp = 0\n for t, i in dic.items():\n for m in dic[t].values():\n p += m\n if p > sp:\n sp = p\n x = t\n return ... | [
0,
1
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print("Usa el punto '.' para los decimales")
for contador in range(1, numalumnos + 1):
print(f'\nDatos del alumno número {contador} de {numalumnos}:')
teorica = float(input('- Introduce la nota de la parte teórica: '))
... | flexible | {
"blob_id": "f2056ff46ce6e38c3b6ca553bbdec7f59d60b198",
"index": 1417,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(\"Usa el punto '.' para los decimales\")\nfor contador in range(1, numalumnos + 1):\n print(f'\\nDatos del alumno número {contador} de {numalumnos}:')\n teorica = float(input(... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class GeneralizedExtremeValueUncertaintyTestCase(UncertaintyTestCase):
def test_random_variables(self):
params = self.make_params_array()
params['loc'] = 2
params['scale'] = 5
expected_median = 2 - 5 * np.log(np.log(2))
results = GEVU.random_va... | flexible | {
"blob_id": "997c1c86848b59a3986a579d5b1b50313fdfdf44",
"index": 8161,
"step-1": "<mask token>\n\n\nclass GeneralizedExtremeValueUncertaintyTestCase(UncertaintyTestCase):\n\n def test_random_variables(self):\n params = self.make_params_array()\n params['loc'] = 2\n params['scale'] = 5\n ... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
class RegPropData:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def __init__(self, csv_path):
"""
Initialize a region proposal data instance.
Parameters
----------
... | flexible | {
"blob_id": "b10badc172be119be5b2ab8ccc32cc95a0ed1e7a",
"index": 2680,
"step-1": "<mask token>\n\n\nclass RegPropData:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def __init__(self, csv_path):\n \"\"\"\n Initialize a region proposal data instance.\n\n Param... | [
5,
7,
8,
9,
11
] |
<|reserved_special_token_0|>
class Game_Service(object):
def __init__(self, row_num, col_num):
self._row_num = row_num
self._col_num = col_num
mine_percent = 0.3
self._mine_num = int(mine_percent * float(self._row_num * self.
_col_num))
self.shifts = [-1, 0, 1]... | flexible | {
"blob_id": "4af72cab6444922ca66641a08d45bcfe5a689844",
"index": 6763,
"step-1": "<mask token>\n\n\nclass Game_Service(object):\n\n def __init__(self, row_num, col_num):\n self._row_num = row_num\n self._col_num = col_num\n mine_percent = 0.3\n self._mine_num = int(mine_percent * f... | [
5,
6,
7,
9,
10
] |
#Program written and maintained by Matthew Meyerink
#File responsible for defining the game based on user input
from cpu_game import CPU_Game
from warning_color import Warning
class User_Game(CPU_Game):
#Get the user phrase to start the game
def get_user_phrase(self):
correct_form = False
w... | normal | {
"blob_id": "d0dbf5a13b8e718ed426a254546ba13da12b2c3e",
"index": 4149,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass User_Game(CPU_Game):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass User_Game(CPU_Game):\n\n def get_user_phrase(self):\n correct_form = False\n whi... | [
0,
1,
2,
3,
4
] |
from setuptools import setup, find_packages
import sys, os
version = '0.1'
setup(
name='ckanext-MYEXTENSION',
version=version,
description="description",
long_description="""\
""",
classifiers=[], # Get strings from http://pypi.python.org/pypi?%3Aaction=list_classifiers
keywords='',
author='ldhspace',
author... | normal | {
"blob_id": "9d2c0d59b0b2b4e4fca942e648059738053c53d0",
"index": 9376,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsetup(name='ckanext-MYEXTENSION', version=version, description=\n 'description', long_description='\\t', classifiers=[], keywords='',\n author='ldhspace', author_email='ldhspace@yah... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for i in soup.find_all('a'):
if 'href' in i.attrs:
print(i.attrs['href'])
<|reserved_special_token_1|>
<|reserved_special_token_0|>
url = 'http://www.dytt8.net/'
user = {'User-Agent':
'Mozilla/5.0 (Windows NT 10... | flexible | {
"blob_id": "2e571e3412bf9f3a42bf87976ea9a5ec68d5815c",
"index": 9056,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in soup.find_all('a'):\n if 'href' in i.attrs:\n print(i.attrs['href'])\n",
"step-3": "<mask token>\nurl = 'http://www.dytt8.net/'\nuser = {'User-Agent':\n 'Mozilla/5... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def get_files_api():
"""Get the files API client."""
return get_api_client(cloudsmith_api.FilesApi)
def validate_request_file_upload(owner, repo, filepath, md5_checksum=None):
"""Validate parameters for requesting a file upload."""
client = get_files_api()
md5_checks... | flexible | {
"blob_id": "ee03263d92372899ec1feaf3a8ea48677b053676",
"index": 6281,
"step-1": "<mask token>\n\n\ndef get_files_api():\n \"\"\"Get the files API client.\"\"\"\n return get_api_client(cloudsmith_api.FilesApi)\n\n\ndef validate_request_file_upload(owner, repo, filepath, md5_checksum=None):\n \"\"\"Valid... | [
2,
3,
4,
5,
6
] |
import art
import random
print(art.guess)
print(art.the)
print(art.number)
print("I'm thinking of a number between 1 and 100")
number = random.randint(1,100)
turns = 0
difficulty = input("Chose a difficulty. 'easy' or 'hard'?\n")
if difficulty == 'easy':
turns +=10
else:
turns +=5
gameover = False
while n... | normal | {
"blob_id": "f2bf4f5b057af1d2362ec8d1472aa76e774be1c7",
"index": 2736,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(art.guess)\nprint(art.the)\nprint(art.number)\nprint(\"I'm thinking of a number between 1 and 100\")\n<mask token>\nif difficulty == 'easy':\n turns += 10\nelse:\n turns += 5\... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python
"""
Script to download and plot RaspberryShake station data
Also computes and plots theoretical phase arrival times and raypaths.
See https://docs.obspy.org/packages/obspy.taup.html for more info on
Earth models and phase-nmaing nomenclature.
Stephen Hicks
Imperial College London
Feb 2020
"""
... | normal | {
"blob_id": "8d8ea6ad7a3ed1a1e6e96ab75260ecf6e8211d32",
"index": 1305,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nst.merge()\nst.detrend(type='demean')\nst.remove_response()\nst.filter('bandpass', freqmin=F1, freqmax=F2, corners=4)\nst.trim(t1, t2)\n<mask token>\nplt.suptitle(LABEL)\n<mask token>\nax... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class _GenericBot:
<|reserved_special_token_0|>
def __init__(self, pos, inventory=None):
"""Initialize with an empty inventory.
inventory is a dictionary. If None, an empty one will be used."""
if inventory is None:
self._inventory = {}
... | flexible | {
"blob_id": "54f0ed5f705d5ada28721301f297b2b0058773ad",
"index": 2,
"step-1": "<mask token>\n\n\nclass _GenericBot:\n <mask token>\n\n def __init__(self, pos, inventory=None):\n \"\"\"Initialize with an empty inventory.\n\n inventory is a dictionary. If None, an empty one will be used.\"\"\"\... | [
52,
53,
58,
60,
79
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class ImageForm(forms.ModelForm):
<|reserved_special_token_0|>
class Meta:
model = Profile
fields = ['userimage']
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class ImageForm(forms.Mod... | flexible | {
"blob_id": "9081d0f75ac53ab8d0bafb39cd46a2fec8a5135f",
"index": 3813,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass ImageForm(forms.ModelForm):\n <mask token>\n\n\n class Meta:\n model = Profile\n fields = ['userimage']\n",
"step-3": "<mask token>\n\n\nclass ImageForm(fo... | [
0,
1,
2,
3,
4
] |
# coding: utf-8
# # Configuration
# In[1]:
CONNECTION_STRING = "mongodb://localhost:27017"
DATABASE_NAME = "off"
COLLECTION_NAME = "products"
# # MongDB connection
# In[2]:
from pymongo import MongoClient
from bson.code import Code
import plotly, pymongo
plotly.offline.init_notebook_mode()
from plotly.graph_obj... | normal | {
"blob_id": "2ecd234753fabbca2829dc86db2f740e371e4ea7",
"index": 6499,
"step-1": "\n# coding: utf-8\n\n# # Configuration\n\n# In[1]:\n\nCONNECTION_STRING = \"mongodb://localhost:27017\"\nDATABASE_NAME = \"off\"\nCOLLECTION_NAME = \"products\"\n\n\n# # MongDB connection\n\n# In[2]:\n\nfrom pymongo import MongoCli... | [
0
] |
# Copyright (C) 2020. Huawei Technologies Co., Ltd. All rights reserved.
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to us... | normal | {
"blob_id": "b77c40c89c88b49c851e9a14c67cf0799d6de847",
"index": 9235,
"step-1": "<mask token>\n\n\ndef register(locator: str, entry_point, **kwargs):\n \"\"\"Register an AgentSpec with the zoo.\n\n In order to load a registered AgentSpec it needs to be reachable from a\n directory contained in the PYTH... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
{'name': 'ldap_user', 'summary': '', 'description': '域账号用户管理，登录及查询用户信息',
'author': '', 'website': '', 'source': {'git':
'https://github.com/LeiQiao/Parasite-Plugins.git', 'branch': 'master'},
'category': '', 'version': '0.1', 'api': {'/user/token'... | flexible | {
"blob_id": "b95619f3f52ff3747e38ecc153123962d0122a4d",
"index": 387,
"step-1": "<mask token>\n",
"step-2": "{'name': 'ldap_user', 'summary': '', 'description': '域账号用户管理，登录及查询用户信息',\n 'author': '', 'website': '', 'source': {'git':\n 'https://github.com/LeiQiao/Parasite-Plugins.git', 'branch': 'master'},\... | [
0,
1,
2
] |
<|reserved_special_token_0|>
def isPrime(n):
if n <= 1:
return False
if n <= 3:
return True
if n % 2 == 0 or n % 3 == 0:
return False
i = 5
while i * i <= n:
if n % i == 0 or n % (i + 2) == 0:
return False
i = i + 6
return True
<|reserved_s... | flexible | {
"blob_id": "fe5050fdf010ce1c4d458b8a52ac92485a7d8cea",
"index": 5706,
"step-1": "<mask token>\n\n\ndef isPrime(n):\n if n <= 1:\n return False\n if n <= 3:\n return True\n if n % 2 == 0 or n % 3 == 0:\n return False\n i = 5\n while i * i <= n:\n if n % i == 0 or n % (i... | [
1,
2,
3,
4,
5
] |
import FWCore.ParameterSet.Config as cms
from RecoTracker.MeasurementDet.UpdaterService_cfi import *
from RecoTracker.MeasurementDet.MeasurementTrackerESProducer_cfi import *
| normal | {
"blob_id": "e79505e802a06f091bbb12708c45e04c4e80da60",
"index": 7618,
"step-1": "<mask token>\n",
"step-2": "import FWCore.ParameterSet.Config as cms\nfrom RecoTracker.MeasurementDet.UpdaterService_cfi import *\nfrom RecoTracker.MeasurementDet.MeasurementTrackerESProducer_cfi import *\n",
"step-3": null,
... | [
0,
1
] |
# This script is for character creation.
print ("Welcome to the character wizard creation!")
# Here you will select your race from the list.
race = ["human", "ork", "elf"]
print race
race = raw_input("Please choose your race: ")
print "You have choosen %r" %race
# Here you will select your gender.
gender = ... | normal | {
"blob_id": "243016b14f503a09147f434e7bec31dc204fafdf",
"index": 1158,
"step-1": "# This script is for character creation.\r\nprint (\"Welcome to the character wizard creation!\")\r\n\r\n# Here you will select your race from the list.\r\nrace = [\"human\", \"ork\", \"elf\"]\r\nprint race\r\nrace = raw_input(\"Pl... | [
0
] |
import shlex
class MockSOLR(object):
class MockHits(list):
@property
def hits(self):
return len(self)
@property
def docs(self):
return self
def __init__(self):
self.db = {}
def add(self, objects):
for o in objects:
o['... | normal | {
"blob_id": "4774c1f4eafc0132bab0073b60c4bcad6b69380d",
"index": 9068,
"step-1": "<mask token>\n\n\nclass MockSOLR(object):\n\n\n class MockHits(list):\n\n @property\n def hits(self):\n return len(self)\n\n @property\n def docs(self):\n return self\n <mask ... | [
3,
5,
6,
7,
8
] |
from share_settings import Settings
import urllib.request,json
import pprint as p
s = Settings()
prefix = "http://finance.google.com/finance?client=ig&output=json&q="
def get(symbol,exchange):
url = prefix+"%s:%s"%(exchange,symbol)
u = urllib.request.urlopen(url)
#translates url to string
c = u.re... | normal | {
"blob_id": "7247ef463998f6738c21ad8efa988a32f7fb99c0",
"index": 4760,
"step-1": "<mask token>\n\n\ndef get_lp(s):\n \"\"\"gets latest prices from google\"\"\"\n sl = []\n for stock in s.symbols:\n quote = get(stock, 'LON')\n x = quote.replace(',', '')\n x = float(x)\n sl.app... | [
1,
2,
3,
4,
5
] |
from flask import jsonify, request, render_template, redirect, session, flash
from init import app
from init import mysql
#Devuelve la pagina de reportes
@app.route('/reportes')
def reportes():
try:
cur = mysql.connect().cursor()
if 'usuario' in session:
return render_template('views/re... | normal | {
"blob_id": "77995aab723fb118be3f986b8cd93f349690baca",
"index": 2090,
"step-1": "<mask token>\n\n\n@app.route('/reportes')\ndef reportes():\n try:\n cur = mysql.connect().cursor()\n if 'usuario' in session:\n return render_template('views/reportes.html', id=session['id'])\n el... | [
4,
5,
6,
7,
8
] |
N = int(input())
K = int(input())
xs = list(map(int, input().split()))
dist = 0
for x in xs:
dist += min(x, K - x)
print(dist * 2)
| normal | {
"blob_id": "a65ab0faf08c13f007a132fb92f358a35834fdb7",
"index": 2556,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor x in xs:\n dist += min(x, K - x)\nprint(dist * 2)\n",
"step-3": "N = int(input())\nK = int(input())\nxs = list(map(int, input().split()))\ndist = 0\nfor x in xs:\n dist += min... | [
0,
1,
2
] |
<|reserved_special_token_0|>
@router.get('/{prefix_id}')
def redirect_to_board(project: Project=Depends(get_project_by_prefix)):
return RedirectResponse(url=project.notion_board_url)
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
@router.get('/{prefix_id}')
def redir... | flexible | {
"blob_id": "49b295c3e323695779eb32181193ef88b678b34d",
"index": 6340,
"step-1": "<mask token>\n\n\n@router.get('/{prefix_id}')\ndef redirect_to_board(project: Project=Depends(get_project_by_prefix)):\n return RedirectResponse(url=project.notion_board_url)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\n... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution(object):
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution(object):
def moveZeroes(self, nums):
"""
给定一个数组 nums，编写一个函数将所有 0 移动到数组的末尾，同时保持非零元素的相对顺序。
---
输入: [0,1,0,3,12]
输出: [1,3,12,0,0]
---
... | flexible | {
"blob_id": "ece80a7765674f9d2991029bb86486b616a90f58",
"index": 3944,
"step-1": "<mask token>\n",
"step-2": "class Solution(object):\n <mask token>\n",
"step-3": "class Solution(object):\n\n def moveZeroes(self, nums):\n \"\"\"\n\t\t给定一个数组 nums，编写一个函数将所有 0 移动到数组的末尾，同时保持非零元素的相对顺序。\n\t\t---\n\t\t... | [
0,
1,
2
] |
<|reserved_special_token_0|>
def stationarity_test(mylynxts):
from statsmodels.tsa.stattools import adfuller
print('Results of Dickey-Fuller Test:')
df_test = adfuller(mylynxts, autolag='AIC')
df_output = pd.Series(df_test[0:4], index=['Test Statistic', 'p-value',
'#lags_used', 'Number of Obse... | flexible | {
"blob_id": "8e28135da60f8e11459697c4ae9c63e60c437d7a",
"index": 9501,
"step-1": "<mask token>\n\n\ndef stationarity_test(mylynxts):\n from statsmodels.tsa.stattools import adfuller\n print('Results of Dickey-Fuller Test:')\n df_test = adfuller(mylynxts, autolag='AIC')\n df_output = pd.Series(df_test... | [
1,
2,
3,
4,
5
] |
import os
import stat
from optparse import OptionParser
from bbpgsql.configuration import get_config_from_filename_and_set_up_logging
from bbpgsql.configuration.general import get_data_dir
from subprocess import check_output
import sys
VERSION = ''
class BadArgumentException(Exception):
def __init__(self, msg):
... | normal | {
"blob_id": "eed79a3895975a0475c0b192bd8a42e80def2e78",
"index": 2502,
"step-1": "<mask token>\n\n\nclass BadArgumentException(Exception):\n\n def __init__(self, msg):\n self.msg = msg\n\n def __str__(self):\n return self.msg\n\n\nclass TooManyArgumentsException(Exception):\n\n def __init_... | [
25,
26,
29,
31,
32
] |
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