code stringlengths 13 1.2M | order_type stringclasses 1
value | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
# -*- coding=utf-8 -*-
# Copyright (C) 2020. Huawei Technologies Co., Ltd. All rights reserved.
# This program is free software; you can redistribute it and/or modify
# it under the terms of the MIT License.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the ... | normal | {
"blob_id": "f3da38f2c4fda0a1d54e79c2c21070f98002b88d",
"index": 3351,
"step-1": "<mask token>\n\n\nclass CityscapesTestConfig(CityscapesCommonConfig):\n <mask token>\n batch_size = 1\n list_path = 'val.txt'\n\n @classmethod\n def rules(cls):\n \"\"\"Return rules for checking.\"\"\"\n ... | [
8,
18,
19,
21,
23
] |
from skimage.measure import structural_similarity as ssim
import matplotlib.pyplot as plt
import numpy as np
import cv2
import os
import pathlib
import warnings
from PIL import Image
from numpy import array
source_path = "/home/justin/Desktop/FeatureClustering/"
feature_length = len(os.listdir(source_path))
vector_da... | normal | {
"blob_id": "ff1346060141ee3504aa5ee9de3a6ec196bcc216",
"index": 3918,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor folder in os.listdir(source_path):\n for filename in os.listdir(source_path + folder + '/'):\n if filename != '---.png':\n linename = filename.split('-')\n ... | [
0,
1,
2,
3,
4
] |
# Uses python3
from decimal import Decimal
def gcd_naive(a, b):
x = 5
while x > 1:
if a % b != 0:
c = a % b
a = b
b = c
else:
x = 1
return b
there = input()
store = there.split()
a = int(max(store))
b = int(min(store))
factor = gcd_naive(a,b)
... | normal | {
"blob_id": "c70681f5ff8d49a243b7d26164aa5430739354f4",
"index": 6936,
"step-1": "<mask token>\n\n\ndef gcd_naive(a, b):\n x = 5\n while x > 1:\n if a % b != 0:\n c = a % b\n a = b\n b = c\n else:\n x = 1\n return b\n\n\n<mask token>\n",
"step-... | [
1,
2,
3,
4,
5
] |
#!/usr/bin/python3
###################################################
### Euler project
### zdrassvouitie @ 10/2016
###################################################
file_name = '013_largeSum_data'
tot = 0
with open(file_name, "r") as f:
stop = 1
while stop != 0:
line = f.readline()
if len(... | normal | {
"blob_id": "bcdf1c03d996520f3d4d8d12ec4ef34ea63ef3cf",
"index": 3936,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open(file_name, 'r') as f:\n stop = 1\n while stop != 0:\n line = f.readline()\n if len(line) < 1:\n break\n tot += float(line)\nprint(tot)\n",
... | [
0,
1,
2,
3
] |
from auth_passwordreset_reset import auth_passwordreset_reset
from auth_register import auth_register
from data import *
import pytest
#invalid reset code
def test_auth_passwordreset_reset1():
#create a test account
register = auth_register("Someemial@hotmail.com.au", "Hello123", "First", "Last")
... | normal | {
"blob_id": "a315d01f0fb16f0c74c447c07b76f33e6ff6427d",
"index": 9742,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef test_auth_passwordreset_reset1():\n register = auth_register('Someemial@hotmail.com.au', 'Hello123',\n 'First', 'Last')\n auth_passwordreset_request('Someemial@hotmai... | [
0,
2,
3,
4,
5
] |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.ticker as tick
from statistics import mean
from tqdm import tqdm
import multiprocessing as mp
from . import model as dymod
class Filter:
"""誤ベクトル数の確認，誤ベクトル数によるフィルタリング処理"""
@classmethod
def get_incorrect_vector_examp... | normal | {
"blob_id": "5d4585dc96d4ebdbc15b7382038cfea959c9a6f3",
"index": 2495,
"step-1": "<mask token>\n\n\nclass Filter:\n <mask token>\n\n @classmethod\n def get_incorrect_vector_example(cls, file_list, example_number):\n \"\"\"含まれる瞬時データの内指定した個数のデータがそれぞれ持つ誤ベクトル数\"\"\"\n incorrect_vector_list = [... | [
5,
9,
10,
11,
12
] |
import cv2 as cv
#! THESE ARE IMAGES THAT AREN'T DOWNSIZED
#original_image_1 = cv.imread("hamburger_face.JPG")
#original_image_2 = cv.imread("hammock_reading.JPG")
#original_image_3 = cv.imread("sofa_face.JPG")
#original_image_4 = cv.imread("frisbee_team.JPG")
original_image_5 = cv.imread("mans_face.JPG")
# ... | normal | {
"blob_id": "d0bd08bea65878f5fccfc4affecdf53cc36179df",
"index": 6633,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor face in detected_faces:\n x, y, w, h = face\n cv.rectangle(original_image_5, (x, y), (x + w, y + h), (0, 255, 0), 2)\ncv.imshow('orig_img', original_image_5)\ncv.waitKey(0)\ncv.... | [
0,
1,
2,
3,
4
] |
print("rap.sweeps.data_management level init") | normal | {
"blob_id": "7d138a0ad7e4d8f7047dd73ae503bdc7ae5aa065",
"index": 9801,
"step-1": "<mask token>\n",
"step-2": "print('rap.sweeps.data_management level init')\n",
"step-3": "print(\"rap.sweeps.data_management level init\")",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
} | [
0,
1,
2
] |
import unittest
import userinput
class Testing(unittest.TestCase):
def test_creation(self):
x = userinput.UserInput()
self.assertNotEqual(x, None)
def test_charset_initialization(self):
x = userinput.UserInput()
self.assertEqual(x.character_set, userinput.CHARACTERS)
def ... | normal | {
"blob_id": "4745d81558130440d35d277b586572f5d3f85c06",
"index": 7366,
"step-1": "<mask token>\n\n\nclass Testing(unittest.TestCase):\n\n def test_creation(self):\n x = userinput.UserInput()\n self.assertNotEqual(x, None)\n\n def test_charset_initialization(self):\n x = userinput.UserI... | [
4,
5,
7,
8,
9
] |
"""A simple script to create a motion plan."""
import os
import json
import logging
from logging.config import dictConfig
import argparse
import numpy as np
from opentrons_hardware.hardware_control.motion_planning import move_manager
from opentrons_hardware.hardware_control.motion_planning.types import (
AxisConst... | normal | {
"blob_id": "b7d75c2523dba0baaf06ba270045a4a344b8156c",
"index": 3023,
"step-1": "<mask token>\n\n\ndef main() ->None:\n \"\"\"Entry point.\"\"\"\n parser = argparse.ArgumentParser(description='Motion planning script.')\n parser.add_argument('--params-file-path', '-p', type=str, required=\n False... | [
1,
2,
3,
4,
5
] |
# -*- coding: utf-8 -*-
# Generated by Django 1.11.6 on 2017-10-27 21:59
from __future__ import unicode_literals
from django.db import migrations, models
import django.db.models.deletion
import phonenumber_field.modelfields
class Migration(migrations.Migration):
dependencies = [
('regions', '0002_auto_2... | normal | {
"blob_id": "1330addd53c6187a41dfea6957bf47aaecca1135",
"index": 7180,
"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 = [('regions', '... | [
0,
1,
2,
3,
4
] |
from django import forms
from .models import File, Sample, Plate, Well, Machine, Project
class MachineForm(forms.ModelForm):
class Meta:
model = Machine
fields = ['name', 'author', 'status', 'comments']
class ProjectForm(forms.ModelForm):
class Meta:
model = Project
field... | normal | {
"blob_id": "5bb894feaf9293bf70b3f831e33be555f74efde8",
"index": 6901,
"step-1": "<mask token>\n\n\nclass SampleForm(forms.ModelForm):\n\n\n class Meta:\n model = Sample\n fields = ['name', 'alias', 'sample_type', 'description', 'project',\n 'author', 'sequence', 'length', 'genbank', ... | [
3,
5,
6,
7
] |
#Sample Python Code
print("Different Code!!!")
#print("Hello World!")
| normal | {
"blob_id": "1e24952006afebb7bf10a83077fc4effd5cc9c58",
"index": 1301,
"step-1": "<mask token>\n",
"step-2": "print('Different Code!!!')\n",
"step-3": "#Sample Python Code\nprint(\"Different Code!!!\")\n#print(\"Hello World!\")\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
} | [
0,
1,
2
] |
import uvicore
from uvicore.support import module
from uvicore.typing import Dict, List
from uvicore.support.dumper import dump, dd
from uvicore.contracts import Email
@uvicore.service()
class Mail:
def __init__(self, *,
mailer: str = None,
mailer_options: Dict = None,
to: List = [],
... | normal | {
"blob_id": "c87ede0e3c6d4cc305450f68b4cf61fb63986760",
"index": 8676,
"step-1": "<mask token>\n\n\n@uvicore.service()\nclass Mail:\n\n def __init__(self, *, mailer: str=None, mailer_options: Dict=None, to:\n List=[], cc: List=[], bcc: List=[], from_name: str=None,\n from_address: str=None, subj... | [
6,
8,
9,
10,
15
] |
#!/usr/bin/env python
from anytree import Node, RenderTree
webtest = Node("WebappTest")
registration = Node("Registration", parent=webtest)
smsconfirm = Node("SMSconfirm", parent=registration)
login = Node("Login", parent=smsconfirm)
useruploadCV = Node("UserUploadCV", parent=l... | normal | {
"blob_id": "33ac328b2bf16380b50c58013bd0d4d888dc3952",
"index": 4693,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nDotExporter(webtest).to_picture('webtest.png')\n",
"step-3": "<mask token>\nwebtest = Node('WebappTest')\nregistration = Node('Registration', parent=webtest)\nsmsconfirm = Node('SMSconf... | [
0,
1,
2,
3,
4
] |
from django.contrib import admin
from .models import Invite
class InviteAdmin(admin.ModelAdmin):
list_display = ('invitee', 'inviter', 'created_on', 'approved',
'rejected', 'used')
admin.site.register(Invite, InviteAdmin)
| normal | {
"blob_id": "fcb13b087b9c967ab16b64885411cc4aae98583c",
"index": 2130,
"step-1": "<mask token>\n\n\nclass InviteAdmin(admin.ModelAdmin):\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass InviteAdmin(admin.ModelAdmin):\n list_display = ('invitee', 'inviter', 'created_on', 'approved',... | [
1,
2,
3,
4
] |
from operator import itemgetter
import math
def get_tf_idf_map(document, max_freq, n_docs, index):
tf_idf_map = {}
for term in document:
tf = 0
idf = math.log(n_docs)
if term in index and term not in tf_idf_map:
posting_list = index[term]
freq_term = sum([p... | normal | {
"blob_id": "39197b3f9f85d94457584d7e488ca376e52207f1",
"index": 5832,
"step-1": "<mask token>\n\n\ndef get_cosinus_simularity(tf_idf_map, key_words):\n sum_common_terms = 0\n sum_tf_idf_terms = 0\n for term in tf_idf_map:\n if term in key_words:\n sum_common_terms += tf_idf_map[term]\... | [
1,
2,
3,
4,
5
] |
print("Hello world! im in github")
| normal | {
"blob_id": "2db6f88b733c23063803c374d7a5b651e8443bd5",
"index": 6135,
"step-1": "<mask token>\n",
"step-2": "print('Hello world! im in github')\n",
"step-3": "print(\"Hello world! im in github\")\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
} | [
0,
1,
2
] |
from django.db import models
from django.utils import timezone
# Create your models here.
class URL(models.Model):
label = models.CharField(null=True, blank=True, max_length=30)
address = models.URLField()
slug = models.SlugField(unique=True, max_length=8)
created = models.DateTimeField(auto_now_add=T... | normal | {
"blob_id": "2dcb02ea2f36dd31eda13c1d666201f861c117e7",
"index": 4027,
"step-1": "<mask token>\n\n\nclass URL(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass URL(models.Model):\n <mask token>\n <mask token>\n ... | [
1,
2,
3,
4,
5
] |
def non_dupulicates_lette(word):
text = list(word);
print(text)
i=0
for i in range(len(text)):
for k in text:
print(c)
def has_dupulicates(word):
d= dict()
for c in word:
if c not in d:
d[c]=1
else:
d[c]+=1
... | normal | {
"blob_id": "8cd234c2ec1b36abd992cc1a46147376cc241ede",
"index": 3276,
"step-1": "<mask token>\n\n\ndef has_dupulicates(word):\n d = dict()\n for c in word:\n if c not in d:\n d[c] = 1\n else:\n d[c] += 1\n for k in d:\n if d[k] == 1:\n print(k)\n ... | [
1,
2,
3,
4,
5
] |
# -*- coding: utf-8 -*-
import sys, io,re
import regex
from collections import defaultdict
import datetime
import json
def update_key(data_base, url,kkey):
keys_saved = regex.get_data('<key>\s(.+?)\s<',data_base[url]['key'])
if kkey not in keys_saved:
data_base[url]['key'] = data_base[url... | normal | {
"blob_id": "50a5d3431693b402c15b557357eaf9a85fc02b0b",
"index": 2921,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef update_key(data_base, url, kkey):\n keys_saved = regex.get_data('<key>\\\\s(.+?)\\\\s<', data_base[url]['key'])\n if kkey not in keys_saved:\n data_base[url]['key'] =... | [
0,
7,
8,
9,
11
] |
import csv
import us
from flask import abort, Flask, request, render_template
app = Flask(__name__) # pylint: disable=invalid-name
@app.route('/')
def root():
return render_template('index.html')
@app.route('/api')
def index():
return render_template('index.html')
@app.route('/api/total/counties')
def ... | normal | {
"blob_id": "af00c6f443426b1f61e1816d7d14ebc7e6871a82",
"index": 5562,
"step-1": "<mask token>\n\n\n@app.route('/')\ndef root():\n return render_template('index.html')\n\n\n@app.route('/api')\ndef index():\n return render_template('index.html')\n\n\n@app.route('/api/total/counties')\ndef total_counties():\... | [
34,
39,
40,
41,
42
] |
from calc1 import LispTranslator, RPNTranslator, Parser, Lexer
import unittest
class TestTranslators(unittest.TestCase):
def init_rpn(self, program):
return RPNTranslator(Parser(Lexer(program)))
def init_lisp(self, program):
return LispTranslator(Parser(Lexer(program)))
def test_simple_... | normal | {
"blob_id": "d0e957abfe5646fb84aed69902f2382d554dc825",
"index": 4401,
"step-1": "<mask token>\n\n\nclass TestTranslators(unittest.TestCase):\n <mask token>\n\n def init_lisp(self, program):\n return LispTranslator(Parser(Lexer(program)))\n <mask token>\n <mask token>\n\n def test_examples_... | [
3,
5,
6,
8
] |
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import numpy as np
import matplotlib.pyplot as plt
import netCDF4
import xarray as xr
import metpy
from datetime import datetime
import datetime as dt
from metpy.units import units
import scipy.ndimage as ndimage
from metpy.plots import USCOUNTIES... | normal | {
"blob_id": "8771f71a69f3afdc5de4d38db6efe61b553ae880",
"index": 9396,
"step-1": "<mask token>\n\n\ndef mkdir_p(mypath):\n \"\"\"Creates a directory. equivalent to using mkdir -p on the command line\"\"\"\n from errno import EEXIST\n from os import makedirs, path\n try:\n makedirs(mypath)\n ... | [
2,
3,
4,
5,
6
] |
#from tkinter import Tk, Text, INSERT
import mnemonicos as mne
class Ensambler(object):
def __init__(self, fileName):
#Nombre del archivo
self.fileName = fileName
#Lineas del Archivo
self.fileLines = []
#Contador de Localidades
self.cl = 0
#Tamaño
self.size = 0
#Opcode
self.code = ""
#Intr... | normal | {
"blob_id": "3bc009271c7dd34ad09bcef81214387b63dfac59",
"index": 2549,
"step-1": "<mask token>\n\n\nclass Ensambler(object):\n\n def __init__(self, fileName):\n self.fileName = fileName\n self.fileLines = []\n self.cl = 0\n self.size = 0\n self.code = ''\n self.instru... | [
7,
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10,
12
] |
print('\n')
# Первый вариант
def fn1():
print("One")
def fn2():
print("Two")
def fn3():
print("Three")
fndict = {"A": fn1, "B": fn2, "C": fn3}
keynames = ["A", "B", "C"]
fndict[keynames[1]]()
fndict['C']()
# Второй вариант
def add(one,two):
c = one+two
print(c)
print(type(c))
def sub(one,two... | normal | {
"blob_id": "dc226a646af32d052c6d51832b95a340d6986e08",
"index": 489,
"step-1": "<mask token>\n\n\ndef fn1():\n print('One')\n\n\ndef fn2():\n print('Two')\n\n\ndef fn3():\n print('Three')\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef fn1():\n print('One')\n\n\ndef fn2():\n print('Two')... | [
3,
4,
5,
6,
8
] |
import pkgutil
import mimetypes
import time
from datetime import datetime
from pywb.utils.wbexception import NotFoundException
from pywb.utils.loaders import BlockLoader
from pywb.utils.statusandheaders import StatusAndHeaders
from pywb.framework.basehandlers import BaseHandler, WbUrlHandler
from pywb.framework.wbre... | normal | {
"blob_id": "df1486afcc99e03510512ed6ed3e8b3471459d50",
"index": 5343,
"step-1": "<mask token>\n\n\nclass WBHandler(SearchPageWbUrlHandler):\n <mask token>\n <mask token>\n <mask token>\n\n def handle_query(self, wbrequest, cdx_lines, output):\n return self.index_reader.make_cdx_response(wbreq... | [
10,
19,
21,
22,
25
] |
def mysum(*c):
print(sum([x for x in c]))
mysum(1,2,3,4,0xB) | normal | {
"blob_id": "2c4fa92b28fa46a26f21ada8826474baac204e00",
"index": 1234,
"step-1": "<mask token>\n",
"step-2": "def mysum(*c):\n print(sum([x for x in c]))\n\n\n<mask token>\n",
"step-3": "def mysum(*c):\n print(sum([x for x in c]))\n\n\nmysum(1, 2, 3, 4, 11)\n",
"step-4": "def mysum(*c):\n print(su... | [
0,
1,
2,
3
] |
<<<<<<< HEAD
{'_data': [['Common', [['Skin', u'Ospecifika hud-reakti oner'], ['General', u'Tr\xf6tthet']]],
['Uncommon',
[['GI',
u'Buksm\xe4rta, diarr\xe9, f\xf6r-stoppnin g, illam\xe5ende (dessa symptom g\xe5r vanligt-vis \xf6ver vid fortsatt behandling).']]],
['Rare',
... | normal | {
"blob_id": "efe13de4ed5a3f42a9f2ece68fd329d8e3147ca2",
"index": 4869,
"step-1": "<<<<<<< HEAD\n{'_data': [['Common', [['Skin', u'Ospecifika hud-reakti oner'], ['General', u'Tr\\xf6tthet']]],\n ['Uncommon',\n [['GI',\n u'Buksm\\xe4rta, diarr\\xe9, f\\xf6r-stoppnin g, illam\\xe5e... | [
0
] |
from __future__ import absolute_import
import itertools
from django.contrib import messages
from django.core.context_processors import csrf
from django.db import transaction
from django.http import HttpResponseRedirect
from django.views.decorators.cache import never_cache
from django.utils.decorators import method_de... | normal | {
"blob_id": "46f218829e1bf324d4c50ea0ff7003bc48b64e2a",
"index": 4258,
"step-1": "<mask token>\n\n\nclass AccountNotificationView(BaseView):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass AccountNotificationView(BaseView):\n <mask token>\n\n @method_decorator(never_cache)\n ... | [
1,
2,
3,
4,
5
] |
#
# PySNMP MIB module CISCO-LWAPP-CLIENT-ROAMING-MIB (http://snmplabs.com/pysmi)
# ASN.1 source file:///Users/davwang4/Dev/mibs.snmplabs.com/asn1/CISCO-LWAPP-CLIENT-ROAMING-MIB
# Produced by pysmi-0.3.4 at Wed May 1 12:04:56 2019
# On host DAVWANG4-M-1475 platform Darwin version 18.5.0 by user davwang4
# Using Python ... | normal | {
"blob_id": "76fbe055b53af9321cc0d57a210cfffe9188f800",
"index": 6531,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nciscoLwappClRoamMIB.setRevisions(('2010-01-29 00:00', '2006-04-11 00:00'))\nif getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0):\n if mibBuilder.loadTexts:\n ciscoLwappClRo... | [
0,
1,
2,
3
] |
from PyQt5.QtWidgets import QWidget, QHBoxLayout, QLabel, QComboBox
class ChoiceTargetNumbers(QWidget):
"""Виджет с выбором номеров целей"""
def __init__(self, parent=None) -> None:
QWidget.__init__(self, parent)
# Нужные компоненты
label = QLabel(text="Выберите номера целей:")
... | normal | {
"blob_id": "291cd789ac3ab7b794be8feafe0f608ad0c081d7",
"index": 9674,
"step-1": "<mask token>\n\n\nclass ChoiceTargetNumbers(QWidget):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass ChoiceTargetNumbers(QWidget):\n <mask token>\n\n def __init__(self, parent=None) ->None:\n ... | [
1,
2,
3,
4,
5
] |
# Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
#
# This work is licensed under the Creative Commons Attribution-NonCommercial
# 4.0 International License. To view a copy of this license, visit
# http://creativecommons.org/licenses/by-nc/4.0/ or send a letter to
# Creative Commons, PO Box 1866, Mountain ... | normal | {
"blob_id": "cb904408486ad9ea8cc0c8ff2ec393e480309a57",
"index": 2403,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nresult_dir = 'results'\ndata_dir = 'datasets'\ncache_dir = f'{ROOT_PATH}/data/cache'\nrun_dir_ignore = ['results', 'datasets', 'cache']\nuse_treeconnect = False\ntreeconnect_threshold = 1... | [
0,
1,
2,
3
] |
#Create Pandas dataframe from the DarkSage output G['']
import pandas as pd
import numpy as np
# This is a way to converte multi dimensional data into pd.Series and then load these into the pandas dataframe
Pos = []
for p in G['Pos']:
Pos.append(p)
Pos_df = pd.Series(Pos, dtype=np.dtype("object"))
Vel = []
for ... | normal | {
"blob_id": "0d565c9f92a60d25f28c903c0a27e7b93d547a4f",
"index": 2971,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor p in G['Pos']:\n Pos.append(p)\n<mask token>\nfor v in G['Vel']:\n Vel.append(v)\n<mask token>\nfor s in G['Spin']:\n Spin.append(s)\n<mask token>\nfor d in G['DiscRadii']:\n... | [
0,
1,
2,
3,
4
] |
from django import forms
from .models import Note
class NoteForm(forms.ModelForm):
class Meta:
model = Note
fields = ['title', 'text']
class NoteFullForm(NoteForm):
note_id = forms.IntegerField(required=False)
images = forms.FileField(widget=forms.ClearableFileInput(attrs={
'mu... | normal | {
"blob_id": "e0fd9663a5635873f4ffc0f73aff5106c0933781",
"index": 9180,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass NoteFullForm(NoteForm):\n note_id = forms.IntegerField(required=False)\n images = forms.FileField(widget=forms.ClearableFileInput(attrs={\n 'multiple': True}), requ... | [
0,
2,
3,
4
] |
import pytest
from django_swagger_utils.drf_server.exceptions import NotFound
from unittest.mock import create_autospec
from content_management_portal.constants.enums import TextType
from content_management_portal.interactors.storages.storage_interface \
import StorageInterface
from content_management_portal.inter... | normal | {
"blob_id": "1c66ccb80383feeee96b3fb492ff63be1a67a796",
"index": 5496,
"step-1": "<mask token>\n\n\nclass TestQuestionInteractor:\n\n def test_question_create(self, questiondto):\n user_id = 1\n short_title = 'hello'\n content_type = 'HTML'\n content = 'hi'\n storage = creat... | [
2,
3,
4,
5,
6
] |
with open("file.txt", 'r') as fh:
data = fh.readline()
lis= data.split(' ')
my_dict={}
for key in lis:
if key in my_dict.keys():
my_dict[key] += 1
else:
my_dict[key] = 1
print(my_dict)
| normal | {
"blob_id": "8cd582915c5abd96a4ef8a3a5309311f2a73a156",
"index": 460,
"step-1": "<mask token>\n",
"step-2": "with open('file.txt', 'r') as fh:\n data = fh.readline()\n<mask token>\nfor key in lis:\n if key in my_dict.keys():\n my_dict[key] += 1\n else:\n my_dict[key] = 1\nprint(my_dict)\... | [
0,
1,
2,
3
] |
from django.apps import AppConfig
class NombreaplicacionConfig(AppConfig):
name = 'nombreAplicacion'
| normal | {
"blob_id": "0c7efa99dc22154f9835b277cba5057b213a28e7",
"index": 2414,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass NombreaplicacionConfig(AppConfig):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass NombreaplicacionConfig(AppConfig):\n name = 'nombreAplicacion'\n",
"step-4": "... | [
0,
1,
2,
3
] |
from rest_framework.pagination import PageNumberPagination
class QuoteListPagination(PageNumberPagination):
page_size = 30
| normal | {
"blob_id": "4245da12eb7f9dd08c863e368efbd0bcf0b8fa04",
"index": 6816,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass QuoteListPagination(PageNumberPagination):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass QuoteListPagination(PageNumberPagination):\n page_size = 30\n",
"step-... | [
0,
1,
2,
3
] |
# -*- coding: utf-8 -*-
"""
Created on Sun Sep 19 17:15:58 2021
@author: Professional
"""
#son = int(input("Biror son kiriting: ") )
#print(son, "ning kvadrati", son*son, "ga teng")
#print (son, "ning kubi", son*son*son, "ga teng")
#yosh = int(input("Yoshingiz nechida: "))
#print("Siz", 2021 - yosh, "yil... | normal | {
"blob_id": "0d32fe36f71ffb3df56738664c5dbd0b8ae585e3",
"index": 3303,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(\"yig'indisi \", a + b)\nprint('ayirmasi ', a - b)\nprint(\"bo'linmasi \", a / b)\nprint(\"ko'paytmasi \", a * b)\n",
"step-3": "<mask token>\na = int(input('Birinchi sonni kiriti... | [
0,
1,
2,
3
] |
o = input()
v = []
s = 0
for i in range(12):
col = []
for j in range(12):
col.append(float(input()))
v.append(col)
a = 1
for i in range(1, 12):
for j in range(a):
s += v[i][j]
a+=1
if o == 'S':
print("%.1f"%s)
if o == 'M':
print("%.1f"%(s/66))
| normal | {
"blob_id": "0df20722fba6223c9d4fc9f72bfb399b479db6ac",
"index": 7917,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(12):\n col = []\n for j in range(12):\n col.append(float(input()))\n v.append(col)\n<mask token>\nfor i in range(1, 12):\n for j in range(a):\n s ... | [
0,
1,
2,
3
] |
my_order = ['spam', 'eggs', 'sausage', 'spam', 'bacon', 'spam']
while 'spam' in my_order:
print("I don't like spam!")
my_order.remove('spam')
print(my_order)
| normal | {
"blob_id": "8e8629dd2d4bb601347694b18d7cb6a94880201d",
"index": 8192,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile 'spam' in my_order:\n print(\"I don't like spam!\")\n my_order.remove('spam')\nprint(my_order)\n",
"step-3": "my_order = ['spam', 'eggs', 'sausage', 'spam', 'bacon', 'spam']... | [
0,
1,
2
] |
import requests
save_result = requests.post('http://localhost:5000/save', json={'value':
'witam'})
print(save_result.text)
read_result = requests.get('http://localhost:5000/read')
print(read_result.text)
| normal | {
"blob_id": "43362c564be0dfbc8f246a0589bcebde245ab7b5",
"index": 7015,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(save_result.text)\n<mask token>\nprint(read_result.text)\n",
"step-3": "<mask token>\nsave_result = requests.post('http://localhost:5000/save', json={'value':\n 'witam'})\nprin... | [
0,
1,
2,
3
] |
providers = {
'provider-1': {
'name': 'provider-1',
'roles': ['licensor', 'producer'],
'description': 'This is a full description of the provider',
'url': 'https://www.provider.com'
},
'provider-2': {
'name': 'provider-2',
'roles': ['licensor'],
'descr... | normal | {
"blob_id": "7801676df91a7ded6f123113acc62f3955dfe6cb",
"index": 7113,
"step-1": "<mask token>\n",
"step-2": "providers = {'provider-1': {'name': 'provider-1', 'roles': ['licensor',\n 'producer'], 'description':\n 'This is a full description of the provider', 'url':\n 'https://www.provider.com'}, 'pro... | [
0,
1,
2
] |
import pygame
from pygame.locals import *
pygame.init()
ttt = pygame.display.set_mode((300,325)) #loome mänguakna
pygame.display.set_caption = ("Trips-Traps-Trull")
võitja = None
def init_tabel(ttt):
taust = pygame.Surface(ttt.get_size())
taust = taust.convert()
taust.fill((250,250,250))
#tõm... | normal | {
"blob_id": "a667c4cb0a30ee67fe982bb96ece6bb75f25f110",
"index": 7084,
"step-1": "<mask token>\n\n\ndef näita_tabelit(ttt, tabel):\n hetkeseis(tabel)\n ttt.blit(tabel, (0, 0))\n pygame.display.flip()\n\n\ndef hiire_positsioon_tabelis(Xkoordinaat, Ykoordinaat):\n if Ykoordinaat < 100:\n rida = ... | [
6,
7,
9,
10,
11
] |
#!/usr/bin/python2
import unittest
import luna_utils as luna
import time
API_URL = "com.webos.service.videooutput/"
VERBOSE_LOG = True
SUPPORT_REGISTER = False
SINK_MAIN = "MAIN"
SINK_SUB = "SUB0"
#TODO(ekwang): If you connect SUB, HAL error occurs. Just test MAIN in the current state
#SINK_LIST = [SINK_MAIN, SINK_... | normal | {
"blob_id": "27e66b2a03bc626d5babd804e736a4652ba030d5",
"index": 8624,
"step-1": "<mask token>\n\n\nclass TestVideoMethods(luna.TestBase):\n\n def vlog(self, message):\n if VERBOSE_LOG:\n print(message)\n\n def setUp(self):\n self.vlog('setUp')\n if SUPPORT_REGISTER:\n ... | [
11,
14,
15,
17,
18
] |
class UnknownResponseFormat(Exception):
pass
| normal | {
"blob_id": "e5e460eb704e2ab5f747d1beee05e012ea95fbd2",
"index": 3871,
"step-1": "<mask token>\n",
"step-2": "class UnknownResponseFormat(Exception):\n pass\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
str="mama"
stringlength=len(str)
slicedString=str[stringlength::-1]
print (slicedString) | normal | {
"blob_id": "5c80561a3344c0240e59500e5dadc1f1ef7f380e",
"index": 7687,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(slicedString)\n",
"step-3": "str = 'mama'\nstringlength = len(str)\nslicedString = str[stringlength::-1]\nprint(slicedString)\n",
"step-4": "str=\"mama\"\r\nstringlength=len(str... | [
0,
1,
2,
3
] |
#!/usr/bin/env python
# coding: utf-8
# In[1]:
import pandas as pd
import numpy as np
import seaborn as sb
import matplotlib as mp
data = pd.read_csv("/Users/stevenbaez/Desktop/train.csv")
# In[2]:
data.head()
# In[3]:
subset = data[['Survived','Age', 'Sex']]
# In[5]:
import numpy as np
import matplotli... | normal | {
"blob_id": "41006ff35299aa72b69c6dc1c71a45b44dca7d6c",
"index": 1184,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ndata.head()\n<mask token>\nsb.catplot(x='Age', y='Sex', hue='Survived', col='Embarked', notch=False,\n palette='Set2', data=data, kind='box', height=4, aspect=0.7)\nsb.catplot(x='Age',... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import config
import web
import hashlib
import sys
db = web.database(dbn="mysql", db=config.db, user=config.user, pw=config.passwd)
def signIn(user, pw):
pwhash = hashlib.md5(pw).hexdigest()
uid = db.insert("users", uname=user, passwd=pwhash)
r... | normal | {
"blob_id": "6d032df195854703f36dce7d27524c8f5089c04d",
"index": 2334,
"step-1": "#!/usr/bin/env python\r\n# -*- coding: utf-8 -*-\r\n\r\nimport config\r\nimport web\r\nimport hashlib\r\nimport sys\r\n\r\n\r\ndb = web.database(dbn=\"mysql\", db=config.db, user=config.user, pw=config.passwd)\r\n\r\ndef signIn(use... | [
0
] |
#!/bin/python
"""
len()
lower()
upper()
str()
"""
parrot = "Norwegian Blue"
print len(parrot)
| normal | {
"blob_id": "cd8d95e2bf433020db2db06a21263f75e3f81331",
"index": 9740,
"step-1": "#!/bin/python\n\n\"\"\"\nlen()\nlower()\nupper()\nstr()\n\"\"\"\n\nparrot = \"Norwegian Blue\"\nprint len(parrot)\n",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
} | [
0
] |
import requests
import tkinter as tk
from tkinter.font import Font
from time import strptime
class Window(tk.Tk):
def __init__(self):
super().__init__()
#取得網路上的資料
res = requests.get('https://flask-robert.herokuapp.com/youbike')
jsonObj = res.json()
areas = jsonObj['areas']
... | normal | {
"blob_id": "f9becdb48583423e7bd3730d1cd74a6a016663dc",
"index": 1768,
"step-1": "<mask token>\n\n\nclass Window(tk.Tk):\n\n def __init__(self):\n super().__init__()\n res = requests.get('https://flask-robert.herokuapp.com/youbike')\n jsonObj = res.json()\n areas = jsonObj['areas']... | [
4,
5,
6,
7,
8
] |
from collections import Counter
# Complete the isValid function below.
def isValid(s):
if not s:
return True
x = Counter(s)
print(x)
first_c = x.pop(s[0])
cnt = 0
for k, c in x.items():
if c != first_c:
if first_c == 1:
cnt += 1
firs... | normal | {
"blob_id": "760daa908ca92e7fb1393bdf28fee086dc1648ef",
"index": 6418,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef isValid(s):\n if not s:\n return True\n x = Counter(s)\n print(x)\n first_c = x.pop(s[0])\n cnt = 0\n for k, c in x.items():\n if c != first_c:\n ... | [
0,
1,
2,
3,
4
] |
"""
opsi-utils
Test utilities
"""
import os
import tempfile
from contextlib import contextmanager
from pathlib import Path
from typing import Generator
@contextmanager
def temp_context() -> Generator[Path, None, None]:
origin = Path().absolute()
try:
with tempfile.TemporaryDirectory(ignore_cleanup_errors=True) ... | normal | {
"blob_id": "3c2a611fd001f145703853f5ecfe70d0e93844e4",
"index": 4665,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@contextmanager\ndef temp_context() ->Generator[Path, None, None]:\n origin = Path().absolute()\n try:\n with tempfile.TemporaryDirectory(ignore_cleanup_errors=True\n ... | [
0,
1,
2,
3
] |
from Logic.ProperLogic.helper_classes.reducer import MaxReducer
from Logic.ProperLogic.misc_helpers import log_error
import torch
from itertools import count
import logging
logging.basicConfig(level=logging.INFO)
class Cluster:
metric = 2
def __init__(self, cluster_id, embeddings=None, embeddings_ids=None,... | normal | {
"blob_id": "265c594b12ea45a2dda12e1157e5ea040f4d6ce4",
"index": 9021,
"step-1": "<mask token>\n\n\nclass Cluster:\n <mask token>\n <mask token>\n\n def __len__(self):\n return len(self.embeddings_dict)\n\n def set_label(self, label):\n self.label = label\n <mask token>\n <mask to... | [
7,
17,
20,
21,
22
] |
#!/usr/bin/env python
from __future__ import absolute_import, print_function, unicode_literals
import os
import sys
import unittest
# Allow interactive execution from CLI, cd tests; ./test_cli.py
if __package__ is None:
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from ksconf.con... | normal | {
"blob_id": "1bb953b665f48638691986e2fcae73b10a1c2ce0",
"index": 7729,
"step-1": "<mask token>\n\n\nclass CliKsconfCombineTestCase(unittest.TestCase):\n\n def build_test01(self, twd):\n twd.write_file(\n 'etc/apps/Splunk_TA_aws/default.d/10-upstream/props.conf',\n \"\"\"\n ... | [
7,
8,
10,
11,
12
] |
# SPDX-FileCopyrightText: 2023 spdx contributors
#
# SPDX-License-Identifier: Apache-2.0
from dataclasses import field
from beartype.typing import List, Optional
from spdx_tools.common.typing.dataclass_with_properties import dataclass_with_properties
from spdx_tools.common.typing.type_checks import check_types_and_se... | normal | {
"blob_id": "1c085ea8f9b21ea7bef94ad4ecbb1771a57f697a",
"index": 2208,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@dataclass_with_properties\nclass ExternalMap:\n external_id: str\n verified_using: List[IntegrityMethod] = field(default_factory=list)\n location_hint: Optional[str] = None\... | [
0,
1,
2,
3,
4
] |
# Created by MechAviv
# [Maestra Fiametta] | [9390220]
# Commerci Republic : San Commerci
if sm.hasItem(4310100, 1):
sm.setSpeakerID(9390220)
sm.sendSayOkay("You can't start your voyage until you finish the tutorial quest!")
else:
sm.setSpeakerID(9390220)
sm.sendNext("What? You threw away the coins wi... | normal | {
"blob_id": "c4b9fdba9e9eeccc52999dab9232302f159c882a",
"index": 588,
"step-1": "<mask token>\n",
"step-2": "if sm.hasItem(4310100, 1):\n sm.setSpeakerID(9390220)\n sm.sendSayOkay(\n \"You can't start your voyage until you finish the tutorial quest!\")\nelse:\n sm.setSpeakerID(9390220)\n sm.... | [
0,
1,
2
] |
import testTemplate
def getTests():
tests = []
suite=testTemplate.testSuite("Sample Test Cases")
testcase = testTemplate.testInstance("3\n1 1 1\n1 1 1\n1 1 1" , "6" , "Sample #1")
suite.add(testcase)
testcase = testTemplate.testInstance("11\n1 0 0 1 0 0 0 0 0 1 1 \n1 1 1 1 1 0 1 0 1 0 0 \n1 0 0 1 0 0 1 1 0 1 0 ... | normal | {
"blob_id": "de4c31ad474b7ce75631214aceafbe4d7334f14b",
"index": 6956,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef getTests():\n tests = []\n suite = testTemplate.testSuite('Sample Test Cases')\n testcase = testTemplate.testInstance('3\\n1 1 1\\n1 1 1\\n1 1 1', '6',\n 'Sample #... | [
0,
1,
2,
3
] |
#Script start
print"This is the two number subtraction python program."
a = 9
b = 2
c = a - b
print c
# Scrip close
| normal | {
"blob_id": "a045423edd94d985dfc9660bcfe4a88c61bf4574",
"index": 20,
"step-1": "#Script start\nprint\"This is the two number subtraction python program.\"\na = 9\nb = 2\nc = a - b\nprint c\n\n# Scrip close\n",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
} | [
0
] |
"""------------------------------------------------------------------------
MODULE
FContactRegulatoryInfoBase -
DESCRIPTION:
This file provides the custom instance of RegulatoryInfo on the Contact which has all the RegulatoryInfo related methods
VERSION: 1.0.25(0.25.7)
RESTRICTIONS/ LIMITATIONS:
1. Any modi... | normal | {
"blob_id": "d4e62950f10efeb27d19c3d9c672969342ef8c7c",
"index": 3095,
"step-1": "<mask token>\n\n\nclass FContactRegulatoryInfoBase(object):\n\n def __init__(self, contact=None):\n \"\"\"class that maintains all data related to the regulatory on the FContact\"\"\"\n try:\n self.__con... | [
13,
15,
18,
20,
23
] |
from mayan.apps.testing.tests.base import BaseTestCase
from .mixins import AssetTestMixin
class AssetModelTestCase(AssetTestMixin, BaseTestCase):
def test_asset_get_absolute_url_method(self):
self._create_test_asset()
self.test_asset.get_absolute_url()
| normal | {
"blob_id": "42c9e5039e2d5f784bf6405ea8bcaf7d6973ddcb",
"index": 6456,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass AssetModelTestCase(AssetTestMixin, BaseTestCase):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass AssetModelTestCase(AssetTestMixin, BaseTestCase):\n\n def test_as... | [
0,
1,
2,
3
] |
# ethermine.py, Copyright (c) 2019, Nicholas Saparoff <nick.saparoff@gmail.com>: Original implementation
from minermedic.pools.base_pool import BasePool
from phenome_core.util.rest_api import RestAPI
from minermedic.pools.helper import get_algo_index, get_coin_index, get_coin_cost
"""
EtherminePool
This is the ... | normal | {
"blob_id": "921c7255fad46c767f2ec1030ef9498da05b9bb1",
"index": 9958,
"step-1": "<mask token>\n\n\nclass EtherminePool(BasePool):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def build_creation_parameters(self, pool, pool_attrs, pool_classname):\n params = super(Ethermin... | [
6,
8,
9,
10,
11
] |
#%% [markdown]
# # Look at intron-less gene enrichment in Cyte biased expressed genes.
# This is a quick look at if parimary spermatocyte biased genes are enriched in intronless genes.
# Yes this is what we see.
#%%
import os
import pickle
import numpy as np
import pandas as pd
from scipy.stats import fisher_exact, c... | normal | {
"blob_id": "5f4d83aa2b530417ecb1598510fb4778b111700b",
"index": 6489,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ntry:\n os.chdir(os.path.join(os.getcwd(), 'docs'))\n print(os.getcwd())\nexcept:\n pass\n<mask token>\ng.map(sns.boxplot, 'intronless', 'pct_cyte', order=[False, True])\ng.set_yl... | [
0,
1,
2,
3,
4
] |
# coding: utf-8
# Aluno: Héricles Emanuel
# Matrícula: 117110647
# Atividade: É quadrado Mágico?
def eh_quadrado_magico(m):
somas_all = []
eh_magico = True
soma = 0
for e in range(len(m[0])):
soma += m[0][e]
# Linhas
for i in range(len(m)):
somados = 0
for e in range(len(m[i])):
somados += (m[i][e])
s... | normal | {
"blob_id": "f039ab104093eb42c3f5d3c794710a0997e85387",
"index": 8371,
"step-1": "# coding: utf-8\n# Aluno: Héricles Emanuel\n# Matrícula: 117110647\n# Atividade: É quadrado Mágico?\n\ndef eh_quadrado_magico(m):\n\tsomas_all = []\n\teh_magico = True\n\tsoma = 0\n\tfor e in range(len(m[0])):\n\t\tsoma += m[0][e]\... | [
0
] |
class Solution:
'''
先遍历整个string，并记录最小的character的出现次数。
如果最小character出现次数都不小于k，那么说明整个string就是满足条件的longest substring，返回原string的长度即可；
如果character的出现次数小于k，假设这个character是c，因为满足条件的substring永远不会包含c，所以满足条件的substring一定是在以c为分割参考下的某个substring中。所以我们需要做的就是把c当做是split的参考，在得到的String[]中再次调用我们的method，找到最大的返回值即可。
'''
... | normal | {
"blob_id": "6ba830aafbe8e4b42a0b927328ebcad1424cda5e",
"index": 8381,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n <mask token>\n",
"step-3": "class Solution:\n <mask token>\n\n def longestSubstring(self, s: str, k: int) ->int:\n\n def helper(s, k):\n ... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'meet.ui'
#
# Created by: PyQt5 UI code generator 5.8.2
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_Dialog(object):
def setupUi(self, Dialog):
Dialog.setObjectName... | normal | {
"blob_id": "c076aed1bfff51f8edf5ab4ef029b7fa7ca2422c",
"index": 9479,
"step-1": "<mask token>\n\n\nclass Ui_Dialog(object):\n\n def setupUi(self, Dialog):\n Dialog.setObjectName('Dialog')\n Dialog.resize(607, 723)\n self.start = QtWidgets.QLabel(Dialog)\n self.start.setGeometry(Qt... | [
2,
3,
4,
5,
6
] |
import sys
import networkx as nx
import bcube.generator_bcube as bcube
import dcell.generate_dcell as dcell
import fat_tree.generate_fat_tree as fatTree
import cayley_graphs.generate_bubble_sort as bubbleSort
import cayley_graphs.generate_hypercube as hypercube
import cayley_graphs.generate_pancake as pancake
import ca... | normal | {
"blob_id": "12d59697d5c2ec69d019c64dac762385c8c0cb66",
"index": 7224,
"step-1": "import sys\nimport networkx as nx\nimport bcube.generator_bcube as bcube\nimport dcell.generate_dcell as dcell\nimport fat_tree.generate_fat_tree as fatTree\nimport cayley_graphs.generate_bubble_sort as bubbleSort\nimport cayley_gr... | [
0
] |
# -*- coding:utf-8 -*-
#
from django.core.paginator import Paginator
def pagination(request, queryset, display_amount=15, after_range_num=5, bevor_range_num=4):
# 按参数分页
paginator = Paginator(queryset, display_amount)
try:
# 得到request中的page参数
page = int(request.GET['page'])
except:
... | normal | {
"blob_id": "7a2b33d1763e66335c6a72a35082e20725cab03d",
"index": 3318,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef pagination(request, queryset, display_amount=15, after_range_num=5,\n bevor_range_num=4):\n paginator = Paginator(queryset, display_amount)\n try:\n page = int(req... | [
0,
1,
2,
3
] |
import oneflow as flow
import torch
def convert_torch_to_flow(model, torch_weight_path, save_path):
parameters = torch.load(torch_weight_path)
new_parameters = dict()
for key, value in parameters.items():
if "num_batches_tracked" not in key:
val = value.detach().cpu().numpy()
ne... | normal | {
"blob_id": "8a3cf65550893367b9001369111fa19a3e998d82",
"index": 9589,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef convert_torch_to_flow(model, torch_weight_path, save_path):\n parameters = torch.load(torch_weight_path)\n new_parameters = dict()\n for key, value in parameters.items():... | [
0,
1,
2,
3
] |
"""byte - property model module."""
from __future__ import absolute_import, division, print_function
class BaseProperty(object):
"""Base class for properties."""
def get(self, obj):
"""Get property value from object.
:param obj: Item
:type obj: byte.model.Model
"""
ra... | normal | {
"blob_id": "382f7119beba81087c497baf170eb6814c26c03e",
"index": 5458,
"step-1": "<mask token>\n\n\nclass BaseProperty(object):\n <mask token>\n <mask token>\n\n def set(self, obj, value):\n \"\"\"Set property value on object.\n\n :param obj: Item\n :type obj: byte.model.Model\n\n ... | [
2,
3,
4,
5,
6
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# File: software/jetson/fastmot/utils/sot.py
# By: Samuel Duclos
# For: Myself
# Description: This file returns detection results from an image.
from cvlib.object_detection import draw_bbox
class ObjectCenter(object):
def __init__(self, args)... | normal | {
"blob_id": "8f14bbab8b2a4bc0758c6b48feb20f8b0e3e348b",
"index": 5460,
"step-1": "<mask token>\n\n\nclass ObjectCenter(object):\n\n def __init__(self, args):\n \"\"\"Initialize variables.\"\"\"\n self.args = args\n\n def load_classes(self, path):\n with open(path, 'r') as names_file:\n... | [
4,
5,
6,
8,
9
] |
#!/usr/bin/env conda-execute
# conda execute
# env:
# - python >=3
# - requests
# run_with: python
from configparser import NoOptionError
from configparser import SafeConfigParser
import argparse
import base64
import inspect
import ipaddress
import json
import logging
import logging.config
import o... | normal | {
"blob_id": "dd91ba13177aefacc24ef4a004acae0bffafadf0",
"index": 8889,
"step-1": "#!/usr/bin/env conda-execute\r\n\r\n# conda execute\r\n# env:\r\n# - python >=3\r\n# - requests\r\n# run_with: python\r\n\r\nfrom configparser import NoOptionError\r\nfrom configparser import SafeConfigParser\r\nimport argparse\r... | [
0
] |
import math
n, m, a = map(int, input().split())
top = math.ceil(n / a)
bottom = math.ceil(m / a)
print(top * bottom)
| normal | {
"blob_id": "6c426d2b165e01a7cec9f7ddbd96113ae05668f6",
"index": 4898,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(top * bottom)\n",
"step-3": "<mask token>\nn, m, a = map(int, input().split())\ntop = math.ceil(n / a)\nbottom = math.ceil(m / a)\nprint(top * bottom)\n",
"step-4": "import math... | [
0,
1,
2,
3
] |
a = list(range(1, 501))
b = list(range(1, 501))
c = list(range(1, 501))
for i in a:
for j in b:
for k in c:
if i + k + j == 1000 and i < j < k and j ** 2 + i ** 2 == k ** 2:
print(i)
print(j)
print(k)
break
| normal | {
"blob_id": "34947b7ed300f2cbcbf9042fee3902458921d603",
"index": 2912,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in a:\n for j in b:\n for k in c:\n if i + k + j == 1000 and i < j < k and j ** 2 + i ** 2 == k ** 2:\n print(i)\n print(j)\n ... | [
0,
1,
2
] |
def selectionSort(arr, low, high):
for i in range(len(arr)):
mini = i
for j in range(i + 1, len(arr)):
if arr[mini] > arr[j]:
mini = j
arr[i], arr[mini] = arr[mini], arr[i]
return arr
| normal | {
"blob_id": "c91be6cc332139c5b1e7ee5a3512482d0f8620b1",
"index": 7322,
"step-1": "<mask token>\n",
"step-2": "def selectionSort(arr, low, high):\n for i in range(len(arr)):\n mini = i\n for j in range(i + 1, len(arr)):\n if arr[mini] > arr[j]:\n mini = j\n arr[... | [
0,
1
] |
workdir = './model/adamW-BCE/model_seresnext50_32x4d_i768_runmila_2fold_50ep'
seed = 300
n_fold = 2
epoch = 50
resume_from = None
batch_size = 32
num_workers = 32
imgsize = (768, 768) #(height, width)
loss = dict(
name='BCEWithLogitsLoss',
params=dict(),
)
optim = dict(
name='AdamW',
params=dict(
... | normal | {
"blob_id": "8030bdb6c9f0b7114916d7abc245ff680d1fc917",
"index": 6790,
"step-1": "<mask token>\n",
"step-2": "workdir = './model/adamW-BCE/model_seresnext50_32x4d_i768_runmila_2fold_50ep'\nseed = 300\nn_fold = 2\nepoch = 50\nresume_from = None\nbatch_size = 32\nnum_workers = 32\nimgsize = 768, 768\nloss = dict... | [
0,
1,
2
] |
import os
def mini100(videopath, minipath,mod='train'):
with open(videopath, 'r') as video_f:
all_videos = video_f.readlines()
#if mod=='train':
# count = [400 for _ in range(0,100)]
#else:
# count = [25 for _ in range(0,100)]
count = [0 for _ in range(0,100)]
... | normal | {
"blob_id": "f6d4208afee7aacd96ea5ae6c9e38d2876466703",
"index": 7417,
"step-1": "<mask token>\n\n\ndef mini200(videopath, minipath, mod='train'):\n with open(videopath, 'r') as video_f:\n all_videos = video_f.readlines()\n count = [(0) for _ in range(0, 200)]\n with open(minipath, 'w') a... | [
2,
3,
4,
5,
6
] |
from .fieldmatrix import *
| normal | {
"blob_id": "fc4fafe4e29a7f116c38be265fce8e4fb6638330",
"index": 6848,
"step-1": "<mask token>\n",
"step-2": "from .fieldmatrix import *\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
import json
import re
from bs4 import BeautifulSoup
from bs4.element import NavigableString, Tag
from common import dir_path
def is_element(el, tag):
return isinstance(el, Tag) and el.name == tag
class ElemIterator():
def __init__(self, els):
self.els = els
self.i = 0
def peek(self):
try:
... | normal | {
"blob_id": "cb08f64d1ad7e53f1041684d4ca4ef65036c138d",
"index": 44,
"step-1": "<mask token>\n\n\ndef is_element(el, tag):\n return isinstance(el, Tag) and el.name == tag\n\n\nclass ElemIterator:\n\n def __init__(self, els):\n self.els = els\n self.i = 0\n\n def peek(self):\n try:\n... | [
10,
12,
14,
15,
16
] |
# Generated by Django 3.1.3 on 2020-11-19 06:19
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('myems', '0004_auto_20201118_1446'),
]
operations = [
migrations.RenameField(
model_name='dg',
old_name='sn',
... | normal | {
"blob_id": "11d96a8a400afb0861b92d8900e003826614c99a",
"index": 7502,
"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 = [('myems', '00... | [
0,
1,
2,
3,
4
] |
"""
리스트에 있는 숫자들의 최빈값을 구하는 프로그램을 만들어라.
[12, 17, 19, 17, 23] = 17
[26, 37, 26, 37, 91] = 26, 37
[28, 30, 32, 34, 144] = 없다
최빈값 : 자료의 값 중에서 가장 많이 나타난 값
① 자료의 값이 모두 같거나 모두 다르면 최빈값은 없다.
② 자료의 값이 모두 다를 때, 도수가 가장 큰 값이 1개 이상 있으면 그 값은 모두 최빈값이다.
"""
n_list = [[12, 17, 19, 17, 23],
[26, 37, 26, 37, 91],
[28,... | normal | {
"blob_id": "39f9341313e29a22ec5e05ce9371bf65e89c91bd",
"index": 25,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor numbers in n_list:\n n_dict = {}\n for n in numbers:\n if n in n_dict:\n n_dict[n] += 1\n else:\n n_dict[n] = 1\n mode = []\n if len(n_di... | [
0,
1,
2,
3
] |
from flask import Flask, jsonify, request
import requests, json, random
from bs4 import BeautifulSoup
import gspread
import pandas as pd
import dataservices as dss
from oauth2client.service_account import ServiceAccountCredentials
# page = requests.get("https://www.worldometers.info/coronavirus/")
# soup = BeautifulSou... | normal | {
"blob_id": "267cb37f2ccad5b02a809d9b85327eacd9a49515",
"index": 1061,
"step-1": "<mask token>\n\n\n@app.route('/')\ndef hello():\n return 'Flask setup'\n\n\ndef sheets_row_writer(data_list):\n print('sheets method invoked')\n credentials = ServiceAccountCredentials.from_json_keyfile_name(\n 'mec... | [
5,
6,
9,
10,
11
] |
import numpy as np
import cv2
FRAME_WIDTH = 320
FRAME_HEIGHT = 240
cv2.namedWindow('Measure Angle with centerline')
# WebCam Initialize
vidCapture = cv2.VideoCapture(1)
fourcc = cv2.VideoWriter_fourcc(*'XVID')
out = cv2.VideoWriter('webcam_record.avi', fourcc, 20.0, (640, 480))
while True:
# ke... | normal | {
"blob_id": "500d6f473f07b35bf2d075d3061ac2e54eab702a",
"index": 4156,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ncv2.namedWindow('Measure Angle with centerline')\n<mask token>\nwhile True:\n ret, frame = vidCapture.read()\n if ret == True:\n out.write(frame)\n cv2.imshow('frame',... | [
0,
1,
2,
3,
4
] |
auto_duration_sec = 15
teleop_duration_sec = 135
| normal | {
"blob_id": "5229002103379ff10969e64289d5a0f36641c0a3",
"index": 3497,
"step-1": "<mask token>\n",
"step-2": "auto_duration_sec = 15\nteleop_duration_sec = 135\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
from bs4 import BeautifulSoup
from pprint import pprint
from scraper.sas.sas_models import SASEvent, SASCategory, SASCategoryStage, SASEventStage
from scraper.base_models.models import Event, Category, CategoryStage, EventStage, Participant, Result
from scraper.sas.sas_config import DESTINATION_URL, MTB_EVENT_TYPE, YE... | normal | {
"blob_id": "ecc351cf95254e0bbc5021eff11c500fa0950bd3",
"index": 2653,
"step-1": "<mask token>\n\n\ndef scrape_sas():\n pprint('Scraping Events')\n get_mtb_events()\n pprint('Getting categories and stages')\n for event in db.session.query(SASEvent):\n pprint(event.event_id)\n get_catego... | [
8,
9,
10,
11,
12
] |
from ..translators.translator import Translator
| normal | {
"blob_id": "ab844143ceddf32982682f5092762af0c97db577",
"index": 391,
"step-1": "<mask token>\n",
"step-2": "from ..translators.translator import Translator\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
__author__='rhyschris'
""" Defines the set of actions.
This functions exactly the same as
Actions.cs in the Unity game.
"""
from enum import Enum
class Actions(Enum):
doNothing = 0
crouch = 1
jump = 3
walkTowards = 0x1 << 2
runTowards = 0x2 << 2
moveAway = 0x3 << 2
blockUp = 0x1 ... | normal | {
"blob_id": "bc0bfb0ff8eaf21b15b06eea2ea333381c70bc75",
"index": 6775,
"step-1": "__author__='rhyschris'\n\n\"\"\" Defines the set of actions.\n This functions exactly the same as \n Actions.cs in the Unity game.\n\"\"\"\nfrom enum import Enum\n\n\nclass Actions(Enum):\n doNothing = 0\n crouch = 1\n ... | [
0
] |
#!/usr/local/bin/python3
def printGrid(grid):
for row in grid:
print(row)
print("")
def validFormatting(grid):
if (type(grid) is not list):
return False
elif (len(grid) != 9):
return False
else:
for row in grid:
if (type(row) is not list):
... | normal | {
"blob_id": "67452f31a49f50cdb2555406287b31e53a994224",
"index": 7906,
"step-1": "<mask token>\n\n\ndef validRows(grid):\n found_zero = False\n for row in range(9):\n bit_dict = {}\n for col in range(9):\n current_item = grid[row][col]\n if current_item != 0 and current_... | [
5,
7,
9,
12,
13
] |
from django.conf.urls import patterns, include, url
from views.index import Index
from views.configuracoes import Configuracoes
from views.parametros import *
urlpatterns = patterns('',
url(r'^$', Index.as_view(), name='core_index'),
url(r'^configuracoes/', Configuracoes.as_view(), name='core.core_c... | normal | {
"blob_id": "74c60c9e37e4e13ed4c61f631c3426b685b5d38f",
"index": 8875,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = patterns('', url('^$', Index.as_view(), name='core_index'),\n url('^configuracoes/', Configuracoes.as_view(), name=\n 'core.core_configurations'), url('^parametros/dat... | [
0,
1,
2,
3
] |
import json
import os
from subprocess import PIPE, Popen as popen
from unittest import TestCase
from substra.commands import Config
objective = [[{
'descriptionStorageAddress': 'http://chunantes.substrabac:8001/objective/d5002e1cd50bd5de5341df8a7b7d11b6437154b3b08f531c9b8f93889855c66f/description/',
'key': 'd... | normal | {
"blob_id": "c55b768466309d2e655c9222e0674a6bc2a958b3",
"index": 9899,
"step-1": "<mask token>\n\n\nclass TestList(TestCase):\n <mask token>\n <mask token>\n\n def test_list_objective(self):\n output = popen(['substra', 'list', 'objective',\n '--config=/tmp/.substra_e2e'], stdout=PIPE)... | [
4,
6,
8,
9,
12
] |
"""
Read a real number. If it is positive print it's square root, if it's not print the square of it.
"""
import math
print('Insert a number')
num1 = float(input())
if num1 > 0:
print(f'The square root of {num1} is {math.sqrt(num1)}')
else:
print(f'The square of {num1} is {num1**2}')
| normal | {
"blob_id": "a68d682ba6d441b9d7fb69ec1ee318a0ef65ed40",
"index": 3146,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('Insert a number')\n<mask token>\nif num1 > 0:\n print(f'The square root of {num1} is {math.sqrt(num1)}')\nelse:\n print(f'The square of {num1} is {num1 ** 2}')\n",
"step-3"... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/python
#===============================================================================
#
# Board Data File Analyzer
#
# Copyright (c) 2017 by QUALCOMM Atheros, Incorporated.
# All Rights Reserved
# QUALCOMM Atheros Confidential and Proprietary
#
# Notifications and licenses are retained for attribution purp... | normal | {
"blob_id": "5c12ff4f88af991fa275cd08adf3678ee4a678f3",
"index": 8532,
"step-1": "#!/usr/bin/python\n#===============================================================================\n#\n# Board Data File Analyzer\n#\n# Copyright (c) 2017 by QUALCOMM Atheros, Incorporated.\n# All Rights Reserved\n# QUALCOMM Ather... | [
0
] |
def execute(n,dico):
"""
Prend en argument n, la position de la requête dans le dictionaire et dico le nom du dictionnaire.
Renvoie une liste dont chaque élément est une réponse de la requête.
"""
l = []
import sqlite3
conn = sqlite3.connect('imdb.db')
c = conn.cursor()
c.execute(dic... | normal | {
"blob_id": "7618d7fde3774a04ac2005dad104e54b9988d3e8",
"index": 9487,
"step-1": "<mask token>\n\n\ndef taille_plus_grande_reponse(reponses):\n \"\"\"\n Prend en argument une liste.\n Renvoie la taille du plus grand élément de la liste.\n \"\"\"\n l = reponses\n maxi = 0\n for i in range(len... | [
8,
11,
13,
14,
21
] |
from flask_sqlalchemy import SQLAlchemy
from sqlalchemy import func
from extensions import bcrypt
db = SQLAlchemy()
class User(db.Model):
id = db.Column(db.Integer(), primary_key=True)
username = db.Column(db.String(255))
password = db.Column(db.String(255))
posts = db.relationship('Post', backref='us... | normal | {
"blob_id": "dd0e96a1f93cbffedc11262a883dda285f5c224c",
"index": 9703,
"step-1": "<mask token>\n\n\nclass Post(db.Model):\n id = db.Column(db.Integer(), primary_key=True)\n title = db.Column(db.String(255))\n text = db.Column(db.Text())\n date = db.Column(db.DateTime())\n user_id = db.Column(db.In... | [
12,
17,
20,
21
] |
from django.db import models
from datetime import datetime
class Folder(models.Model):
folder = models.CharField(max_length=200, default = "misc")
num_of_entries = models.IntegerField(default=0)
def __str__(self):
return self.folder
class Meta:
verbose_name_plural = "Folders/Categories"
class Bookmark(model... | normal | {
"blob_id": "ca3cdbd5d5d30be4f40925366994c3ea9d9b9614",
"index": 3195,
"step-1": "<mask token>\n\n\nclass Folder(models.Model):\n <mask token>\n <mask token>\n <mask token>\n\n\n class Meta:\n verbose_name_plural = 'Folders/Categories'\n\n\nclass Bookmark(models.Model):\n name = models.Char... | [
4,
5,
6,
7,
8
] |
import os
from PIL import Image
import urllib
import json
import math
def download_images(a,b):
image_count = 0
k = a
no_of_images = b
baseURL='https://graph.facebook.com/v2.2/'
imgURL='/picture?type=large'
sil_check='/picture?redirect=false'
while image_count<no_of_images:
obj=urllib.urlopen(baseURL+str(k)+s... | normal | {
"blob_id": "533154fe58511ac9c9c693bf07f076146b0c6136",
"index": 4445,
"step-1": "import os\nfrom PIL import Image\nimport urllib\nimport json\nimport math\n\ndef download_images(a,b):\n\timage_count = 0\n\tk = a\n\tno_of_images = b\n\tbaseURL='https://graph.facebook.com/v2.2/'\n\timgURL='/picture?type=large'\n\... | [
0
] |
prompt = "Enter a message and I will repeat it to you: "
message = " "
while message != 'quit':
message = input(prompt)
if message != 'quit':
print(message)
# using the 'flag' variable
prompt = "Enter a message and I will repeat it to you: "
# active is the variable used in this case as flag
activ... | normal | {
"blob_id": "1a6f84835ec2f5fbbb064aef2cd872c24eb3839d",
"index": 8717,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile message != 'quit':\n message = input(prompt)\n if message != 'quit':\n print(message)\n<mask token>\nwhile active:\n message = input(prompt)\n if message == 'quit... | [
0,
1,
2,
3
] |
from django.db import models
from django.utils.text import slugify
# Create your models here.
class SponsorType(models.Model):
name = models.CharField(max_length=100)
def __str__(self):
return self.name
class Sponsor(models.Model):
type = models.ForeignKey(SponsorType, on_delete=models.CASCADE, ... | normal | {
"blob_id": "81f0119f6f348f6d33e8d22f588fc8c2e0593d3c",
"index": 1536,
"step-1": "<mask token>\n\n\nclass SponsorType(models.Model):\n <mask token>\n <mask token>\n\n\nclass Sponsor(models.Model):\n type = models.ForeignKey(SponsorType, on_delete=models.CASCADE, null=True)\n id = models.AutoField(pri... | [
5,
6,
7,
8,
9
] |
'''
Created on Feb 21, 2013
@author: dharadarji
'''
def get_row(row_index):
entry = [1]
if row_index == 0:
return entry
tmp = []
for i in range(1, row_index + 2):
tmp = entry
print "i: ", i, "tmp: ", tmp
entry = []
entry.append(1)
... | normal | {
"blob_id": "2579b0c31c5f7cad361ed317f87cb8b0ffcb0098",
"index": 875,
"step-1": "'''\nCreated on Feb 21, 2013\n\n@author: dharadarji\n'''\n\ndef get_row(row_index):\n entry = [1]\n \n if row_index == 0:\n return entry\n \n tmp = []\n \n for i in range(1, row_index + 2):\n tmp =... | [
0
] |
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