code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
ax.set_xlim([-0.007, 1.0])
ax.set_ylim([0.0, 1.01])
ax.set_xlabel('False Positive Rate')
ax.set_ylabel('True Positive Rate')
ax.set_title('Receiver operating characteristic (AUC: %.3f)' % auc(fpr, tpr))
ax.plot([0, 1], [0, 1], col... | flexible | {
"blob_id": "5b3514af839c132fda9a2e6e178ae62f780f291e",
"index": 3388,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nax.set_xlim([-0.007, 1.0])\nax.set_ylim([0.0, 1.01])\nax.set_xlabel('False Positive Rate')\nax.set_ylabel('True Positive Rate')\nax.set_title('Receiver operating characteristic (AUC: %.3f... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python3
import argparse
import logging
import tango
def delete_devices():
"""."""
db = tango.Database()
class_list = db.get_class_list('*')
print('class list = ', class_list)
server_list = db.get_server_list('*')
print('server list = ', server_list)
# for index in range(nu... | normal | {
"blob_id": "f3dad6a474d5882beaac7d98f8f60c347730ee55",
"index": 8428,
"step-1": "<mask token>\n\n\ndef delete_devices():\n \"\"\".\"\"\"\n db = tango.Database()\n class_list = db.get_class_list('*')\n print('class list = ', class_list)\n server_list = db.get_server_list('*')\n print('server li... | [
1,
2,
3,
4,
5
] |
#!/usr/bin/python
# This IDAPython code can be used to de-obfuscate strings generated by
# CryptoWall version 3, as well as any other malware samples that make use of
# this technique.
'''
Example disassembly:
.text:00403EC8 mov ecx, 'V'
.text:00403ECD mov [ebp+var_1C], cx
... | normal | {
"blob_id": "e38149f0d421a43f6aa34a977eee89fe29021b85",
"index": 7451,
"step-1": "#!/usr/bin/python\n# This IDAPython code can be used to de-obfuscate strings generated by\n# CryptoWall version 3, as well as any other malware samples that make use of\n# this technique. \n\n'''\nExample disassembly:\n\n\t.text:00... | [
0
] |
import unittest
from unittest.mock import patch
from fsqlfly.db_helper import *
from fsqlfly.tests.base_test import FSQLFlyTestCase
class MyTestCase(FSQLFlyTestCase):
def test_positive_delete(self):
namespace = Namespace(name='iii')
self.session.add(namespace)
self.session.commit()
... | normal | {
"blob_id": "abbefb1e426408b32fa9e125c78b572de22dbb8c",
"index": 7493,
"step-1": "<mask token>\n\n\nclass MyTestCase(FSQLFlyTestCase):\n\n def test_positive_delete(self):\n namespace = Namespace(name='iii')\n self.session.add(namespace)\n self.session.commit()\n t = Transform(name=... | [
4,
5,
7,
9,
10
] |
# Generated by Django 3.1.7 on 2021-03-24 14:51
from django.db import migrations, models
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Products_Table',
fields=[
('product_id', mo... | normal | {
"blob_id": "90b9dcd2dfc28446d1979d58ed49a12a85ce5b98",
"index": 7429,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Migration(migrations.Migration):\n <mask token>\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Migration(migrations.Migration):\n initial = T... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def inner_dsym_download(project_id: int, config_id: str) ->None:
"""Downloads the dSYMs from App Store Connect and stores them in the Project's debug files."""
with sdk.configure_scope() as scope:
scope.set_tag('project', project_id)
scope.set_tag('config_id', conf... | flexible | {
"blob_id": "51bc2668a9f9f4425166f9e6da72b7a1c37baa01",
"index": 9628,
"step-1": "<mask token>\n\n\ndef inner_dsym_download(project_id: int, config_id: str) ->None:\n \"\"\"Downloads the dSYMs from App Store Connect and stores them in the Project's debug files.\"\"\"\n with sdk.configure_scope() as scope:\... | [
3,
5,
7,
9,
10
] |
import numpy as np
import sys
import os
import cv2
if __name__ == "__main__":
# print(sys.argv[1])
# img = cv2.imread(sys.argv[1], 0)
# cv2.imshow('img', img)
# cv2.waitKey(0)
img = np.array([[1, 2], [1, 3], [1, 4]])
print(img.tolist())
sys.stdout.flush()
| normal | {
"blob_id": "54833c19d68bb7a1817639ef761367ce75a3a46f",
"index": 9200,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n img = np.array([[1, 2], [1, 3], [1, 4]])\n print(img.tolist())\n sys.stdout.flush()\n",
"step-3": "import numpy as np\nimport sys\nimport os\nimpor... | [
0,
1,
2,
3
] |
<|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": "fcfec60a2302ee0c1385add053d4371040a2aff4",
"index": 3667,
"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 = [('core', '000... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def test_input_text(expected_result, actual_result):
assert expected_result == actual_result, f'expected {expected_result}, got {actual_result}'
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_speci... | flexible | {
"blob_id": "63391b31d1746f9b3583df5353ae160a430943a9",
"index": 9027,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef test_input_text(expected_result, actual_result):\n assert expected_result == actual_result, f'expected {expected_result}, got {actual_result}'\n\n\n<mask token>\n",
"step-3":... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def create_graph():
with tf.gfile.FastGFile(out_pb_path, 'rb') as f:
graph_def = tf.GraphDef()
graph_def.ParseFromString(f.read())
tf.import_graph_def(graph_def, name='')
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|... | flexible | {
"blob_id": "50fab726b90f65a82c1206a8c7df955a8b76da99",
"index": 1572,
"step-1": "<mask token>\n\n\ndef create_graph():\n with tf.gfile.FastGFile(out_pb_path, 'rb') as f:\n graph_def = tf.GraphDef()\n graph_def.ParseFromString(f.read())\n tf.import_graph_def(graph_def, name='')\n\n\n<mask... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class LetterPage(Page):
def __init__(self, page_num, n):
super(LetterPage, self).__init__(page_num)
self.title = 'Letters'
self.in_index = False
self.n = n
self.tagline = (
'Email klbscroggsbot@gmail.com and your letter will appear ... | flexible | {
"blob_id": "e714fe0e27ec9ea5acb3120a4d2114d3d7674fcf",
"index": 5601,
"step-1": "<mask token>\n\n\nclass LetterPage(Page):\n\n def __init__(self, page_num, n):\n super(LetterPage, self).__init__(page_num)\n self.title = 'Letters'\n self.in_index = False\n self.n = n\n self.... | [
3,
4,
5,
6,
7
] |
# -*- coding: utf-8 -*-
import luigi
from luigi import *
#from luigi import Task
import pandas as pd
from pset.tasks.embeddings.load_embeding import EmbedStudentData
from pset.tasks.data.load_dataset import HashedStudentData
import numpy as npy
import pickle
import os
class NearestStudents(Task):
github_id = Par... | normal | {
"blob_id": "15eed401728e07bfe9299edd12add43ad8b9cb71",
"index": 3802,
"step-1": "<mask token>\n\n\nclass NearestStudents(Task):\n <mask token>\n <mask token>\n <mask token>\n\n def output(self):\n return luigi.LocalTarget('/Users/adcxdpf/Downloads/pset_03/sd.csv')\n\n def requires(self):\n... | [
5,
6,
7,
8,
9
] |
import django
from rest_framework import serializers
from django.shortcuts import render
from .models import Student
from .serializiers import StudentSerializer
from rest_framework.renderers import JSONRenderer
from django.http import HttpResponse,JsonResponse
import io
from rest_framework.parsers import JSONParser
f... | normal | {
"blob_id": "99785ffb4b594db1fac05ca3d3f5764151b2b7b6",
"index": 103,
"step-1": "<mask token>\n\n\n@csrf_exempt\ndef create(request):\n if request.method == 'POST':\n json_data = request.body\n stream = io.BytesIO(json_data)\n pythondata = JSONParser().parse(stream)\n serializer = ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class AbstractGraphGenerator(object):
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class AbstractGraphGenerator(object):
def generate(self, graph):
Util.abstract()
... | flexible | {
"blob_id": "e37e468d8a41b8711fb0eb4ddec7db67691f9156",
"index": 488,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass AbstractGraphGenerator(object):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass AbstractGraphGenerator(object):\n\n def generate(self, graph):\n Util.abstrac... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def get_new_pay_records(process_at, limit=200):
with zeus_session() as session:
result = session.query(SubsidyPayRecord.id, SubsidyPayRecord.
restaurant_id, SubsidyProcessRecord.card_id,
SubsidyProcessRecord.processed_at, SubsidyPayRecord.status
... | flexible | {
"blob_id": "68d537cb8488ae4f2c8300e885be78540952dec0",
"index": 450,
"step-1": "<mask token>\n\n\ndef get_new_pay_records(process_at, limit=200):\n with zeus_session() as session:\n result = session.query(SubsidyPayRecord.id, SubsidyPayRecord.\n restaurant_id, SubsidyProcessRecord.card_id,\... | [
11,
13,
14,
16,
19
] |
<|reserved_special_token_0|>
class Student(andy.Lesson_7.exercise_1.Human):
def __init__(self, firstname, lastname, grade):
super().__init__(firstname, lastname)
self.grade = grade
def do_hobby(self):
return self.full_name + ' ebet Petra Kovarskogo'
<|reserved_special_token_0|>
<... | flexible | {
"blob_id": "497f56891670f635feff983058e86055e54be493",
"index": 2618,
"step-1": "<mask token>\n\n\nclass Student(andy.Lesson_7.exercise_1.Human):\n\n def __init__(self, firstname, lastname, grade):\n super().__init__(firstname, lastname)\n self.grade = grade\n\n def do_hobby(self):\n ... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution(object):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution(object):
<|reserved_special_token_0|>
def solve_equation(self, m, n):
k_l, k_h = 2, n - 1
while k... | flexible | {
"blob_id": "de287d1bc644fdfd0f47bd8667580786b74444d0",
"index": 8863,
"step-1": "<mask token>\n",
"step-2": "class Solution(object):\n <mask token>\n <mask token>\n",
"step-3": "class Solution(object):\n <mask token>\n\n def solve_equation(self, m, n):\n k_l, k_h = 2, n - 1\n while... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class TimestechConfig(AppConfig):
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class TimestechConfig(AppConfig):
name = 'TimesTech'
<|reserved_special_token_1|>
from djan... | flexible | {
"blob_id": "94f50e371ef65e86d0d2d40a3ed16946f8811be3",
"index": 2601,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass TimestechConfig(AppConfig):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass TimestechConfig(AppConfig):\n name = 'TimesTech'\n",
"step-4": "from django.apps impo... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def isPrime(num):
if num <= 1:
return False
elif num == 2:
return True
elif num % 2 == 0:
return False
else:
sqrt_num = math.sqrt(num)
bound = int(sqrt_num) + 1
for i in range(3, bound, 2):
if num % i == 0:
... | flexible | {
"blob_id": "7ca7693b842700a7b15242b656648e8a7e58cd23",
"index": 1691,
"step-1": "<mask token>\n\n\ndef isPrime(num):\n if num <= 1:\n return False\n elif num == 2:\n return True\n elif num % 2 == 0:\n return False\n else:\n sqrt_num = math.sqrt(num)\n bound = int(s... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def ref_mod2(x0, x1, fmod):
if x0.dtype == np.float32 or fmod == True:
return np.fmod(x0, x1)
else:
return np.mod(x0, x1)
@pytest.mark.parametrize('ctx, func_name', ctxs)
@pytest.mark.parametrize('x0_sh... | flexible | {
"blob_id": "32f10c3e73a3d792416f6b2841a80f8b3c390e8c",
"index": 9194,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef ref_mod2(x0, x1, fmod):\n if x0.dtype == np.float32 or fmod == True:\n return np.fmod(x0, x1)\n else:\n return np.mod(x0, x1)\n\n\n@pytest.mark.parametrize('ct... | [
0,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
@require_GET
def Follow(request, shorturl):
link = get_object_or_404(Link, shorturl=shorturl)
link.vi += 1
print(link.vi)
link.save()
return HttpResponseRedirect(link.link)
def FormView(request):
toplink = Link.objects.annotate(Count('vi')).order_by('-vi__count')... | flexible | {
"blob_id": "11952e60ab95bc1896fd899a5ced126dcafec63a",
"index": 9882,
"step-1": "<mask token>\n\n\n@require_GET\ndef Follow(request, shorturl):\n link = get_object_or_404(Link, shorturl=shorturl)\n link.vi += 1\n print(link.vi)\n link.save()\n return HttpResponseRedirect(link.link)\n\n\ndef FormV... | [
2,
4,
5,
6,
7
] |
import subprocess
import re
class Command:
InputSize = 1
OutputSize = 2
MultiThreadable = True
ShareResources = False
def __init__(self, bin, config, showerr=False):
self.travatar = subprocess.Popen([bin, "-config_file", config, "-trace_out", "STDOUT", "-in_format", "egret", "-buffer", "... | normal | {
"blob_id": "91cef72962332e7efcc86f1b19da4382bd72a466",
"index": 9278,
"step-1": "<mask token>\n\n\nclass Command:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Command:\n <mask token>\n <mask token>\n ... | [
1,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution:
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution:
def commonFactors(self, a: int, b: int) ->int:
gcd = math.gcd(a, b)
return sum(a % i == 0 and b % i == 0 for i in range(1, gcd + 1))
| flexible | {
"blob_id": "ea696329a0cfd558fb592ffaf6339a35e8950a3c",
"index": 6721,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n",
"step-3": "class Solution:\n\n def commonFactors(self, a: int, b: int) ->int:\n gcd = math.gcd(a, b)\n return sum(a % i == 0 and b % i == 0 for ... | [
0,
1,
2
] |
#Define a function max_of_three() that takes three numbers as
#arguments and returns the largest of them.
def max_of_three(a,b,c):
max=0
if a > b:
max = a
else:
max = b
if max > c :
return max
else:
return c
print max(234,124,43)
def max_of_three2(a, b, ... | normal | {
"blob_id": "00b4a57537358797bfe37eee76bbf73ef42de081",
"index": 9775,
"step-1": "\n\n\n#Define a function max_of_three() that takes three numbers as\n#arguments and returns the largest of them.\n\n\n\n\ndef max_of_three(a,b,c):\n\n max=0\n if a > b:\n max = a\n else:\n max = b\n\n if m... | [
0
] |
<|reserved_special_token_0|>
class TestFileDisplayPane(TestCase):
def setUp(self):
self.file_display = FileDisplayPane(supported_readers={'Probe':
ProbeMultiImageReader()}, supported_parsers={'Probe':
ProbeParser()})
self.file_path = test_image_path
<|reserved_special_... | flexible | {
"blob_id": "7c65d0bdd4fd808b3d87706357a651601368e43b",
"index": 8596,
"step-1": "<mask token>\n\n\nclass TestFileDisplayPane(TestCase):\n\n def setUp(self):\n self.file_display = FileDisplayPane(supported_readers={'Probe':\n ProbeMultiImageReader()}, supported_parsers={'Probe':\n ... | [
5,
6,
7,
8,
9
] |
import numpy as np
import matplotlib.pyplot as plt
def sample_1(N):
numeros=np.array([-10, -5, 3, 9])
return np.random.choice(numeros, N, p=[0.1, 0.4, 0.2, 0.3])#devuelve distro aleatoria con las probabilidades indicadas
def sample_2(N):
return np.random.exponential(0.5,N)#devuelve numeros aleatorios con distro ex... | normal | {
"blob_id": "d2d04686b3d7f8d01ca195750ca625baa06ed098",
"index": 2835,
"step-1": "<mask token>\n\n\ndef sample_1(N):\n numeros = np.array([-10, -5, 3, 9])\n return np.random.choice(numeros, N, p=[0.1, 0.4, 0.2, 0.3])\n\n\ndef sample_2(N):\n return np.random.exponential(0.5, N)\n\n\ndef get_mean(sampling... | [
3,
4,
5,
6,
7
] |
import server.wsgi as flask
import server.grunner as gunicorn
from utils.cfgreader import EnvReader, BoolVar
def use_flask() -> bool:
env_var = BoolVar('USE_FLASK', False)
return EnvReader().safe_read(env_var)
if __name__ == '__main__':
if use_flask(): # dev mode, run the WSGI app in Flask dev server
... | normal | {
"blob_id": "ffe10ee8b2ebaad565e9aef5047440a067d4e239",
"index": 7528,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef use_flask() ->bool:\n env_var = BoolVar('USE_FLASK', False)\n return EnvReader().safe_read(env_var)\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef use_flask() ->bo... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/python
# -*- coding: utf-8 -*-
'''
Script for converting the new csv files to the desirable json format
'''
import codecs
import json
import re
def creeper():
'''
Settings for creeper file
'''
ccPrefix = False
inFilename = u'creeper.csv'
outFilename = u'Creeper.json'
mappingFil... | normal | {
"blob_id": "5a5b2d0ade5b66981218b4ecf15a2253b7d665f9",
"index": 3273,
"step-1": "<mask token>\n\n\ndef mediaCreeper():\n \"\"\"\n Settings for mediaCreeper file\n \"\"\"\n ccPrefix = True\n inFilename = u'mediacreeper.csv'\n outFilename = u'MediaCreeper.json'\n run(inFilename, outFilename, ... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
class BaseModel(object):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
@classmethod
def resolve_all(cls):
return cls.query.all()
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class BaseModel(object):
def get_id(self):
retu... | flexible | {
"blob_id": "c9079f27e3c0aca09f99fa381af5f35576b4be75",
"index": 4717,
"step-1": "<mask token>\n\n\nclass BaseModel(object):\n <mask token>\n <mask token>\n\n @classmethod\n def resolve_all(cls):\n return cls.query.all()\n",
"step-2": "<mask token>\n\n\nclass BaseModel(object):\n\n def ge... | [
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def line(body):
url = 'https://notify-api.line.me/api/notify'
access_token = 'I89UnoDRgRSInUXJOTg5fAniBE08CUuxVqj8ythMLt8'
headers = {'Authorization': 'Bearer ' + access_token}
message = body
payload = {'mess... | flexible | {
"blob_id": "8b598703df67fb8287fe6cdccda5b73bf2892da8",
"index": 4878,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef line(body):\n url = 'https://notify-api.line.me/api/notify'\n access_token = 'I89UnoDRgRSInUXJOTg5fAniBE08CUuxVqj8ythMLt8'\n headers = {'Authorization': 'Bearer ' + acces... | [
0,
1,
2,
3,
4
] |
def getmin(a, b, c):
if a <= b and a <= c:
print(a)
elif b <= a and b <= c:
print(b)
else:
print(c)
def filtername(name):
if len(name) > 3:
return name[:3]
elif len(name) < 3:
return name + " " * (3 - len(name))
return name
def filternames(names):
... | normal | {
"blob_id": "917241482dc1f234d5fae9c107a5f21b018fe6d4",
"index": 9843,
"step-1": "<mask token>\n\n\ndef filtername(name):\n if len(name) > 3:\n return name[:3]\n elif len(name) < 3:\n return name + ' ' * (3 - len(name))\n return name\n\n\ndef filternames(names):\n re = []\n for n in ... | [
2,
3,
4,
5,
6
] |
from .candles import CandleCallback
from .firestore import FirestoreTradeCallback
from .gcppubsub import GCPPubSubTradeCallback
from .thresh import ThreshCallback
from .trades import (
NonSequentialIntegerTradeCallback,
SequentialIntegerTradeCallback,
TradeCallback,
)
__all__ = [
"FirestoreTradeCallbac... | normal | {
"blob_id": "b6dc29ae5661f84273ff91a124420bc10c7b6f6e",
"index": 3704,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n__all__ = ['FirestoreTradeCallback', 'GCPPubSubTradeCallback',\n 'CandleCallback', 'TradeCallback', 'ThreshCallback',\n 'SequentialIntegerTradeCallback', 'NonSequentialIntegerTradeC... | [
0,
1,
2,
3
] |
# Generated by Django 2.2 on 2019-05-13 06:57
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('base_data_app', '0008_key_keyslider'),
]
operations = [
migrations.AddField(
model_name='key',
name='image',
... | normal | {
"blob_id": "ad53b100a1774f5429278379302b85f3a675adea",
"index": 8986,
"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 = [('base_data_a... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Model(pl.LightningModule):
<|reserved_special_token_0|>
def init_training_parameters(self, criterion, optimizer):
self.criterion = criterion
self.optimizer = optimizer
def set_criterion(self, criterion):
self.criterion = criterion
<|reserved... | flexible | {
"blob_id": "324081eb4e133f6d16e716f3119e4cbc5e045ede",
"index": 8526,
"step-1": "<mask token>\n\n\nclass Model(pl.LightningModule):\n <mask token>\n\n def init_training_parameters(self, criterion, optimizer):\n self.criterion = criterion\n self.optimizer = optimizer\n\n def set_criterion(... | [
8,
10,
12,
15
] |
import pandas as pd
from pandas import DataFrame
myencoding = 'utf-8'
chikenList = ['pelicana', 'nene', 'cheogajip', 'goobne']
# chikenList = ['pelicana']
newframe = DataFrame()
for onestore in chikenList:
filename = onestore + '.csv'
myframe = pd.read_csv(filename, index_col=0, encoding=myencoding)
# pr... | normal | {
"blob_id": "11a31d3276201105ca7485fa4e4eb711012accd5",
"index": 2190,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor onestore in chikenList:\n filename = onestore + '.csv'\n myframe = pd.read_csv(filename, index_col=0, encoding=myencoding)\n newframe = pd.concat([newframe, myframe], axis=0,... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def gameOver(board, symbol):
if board[0] == board[3] == board[6] == symbol or board[1] == board[7
] == board[4] == symbol or board[2] == board[5] == board[8
] == symbol or board[0] == board[1] == board[2] == symbol or board[5
] == board[3] == board[4] == symbol... | flexible | {
"blob_id": "d2f6d7c779d3d6e61d9da7af01a2931fdabec828",
"index": 371,
"step-1": "<mask token>\n\n\ndef gameOver(board, symbol):\n if board[0] == board[3] == board[6] == symbol or board[1] == board[7\n ] == board[4] == symbol or board[2] == board[5] == board[8\n ] == symbol or board[0] == board[1... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
api.main()
<|reserved_special_token_1|>
from xrouter import api
api.main()
<|reserved_special_token_1|>
#!/usr/bin/env python
from xrouter import api
api.main()
| flexible | {
"blob_id": "64368679aa2e387e25a36b2f3d0312a99b819e95",
"index": 2147,
"step-1": "<mask token>\n",
"step-2": "<mask token>\napi.main()\n",
"step-3": "from xrouter import api\napi.main()\n",
"step-4": "#!/usr/bin/env python\nfrom xrouter import api\napi.main()\n",
"step-5": null,
"step-ids": [
0,
... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
while True:
a, b = input().split()
a = float(a)
b = float(b)
if b == 0:
print('error')
else:
c = a / b + 0.5
c = int(c)
print(c)
<|reserved_special_token_1|>
# coding=utf-8
while True:
a,b=input().spl... | flexible | {
"blob_id": "dab5e7ee1d14cba485cbaece1354ec8d686ca4ab",
"index": 9080,
"step-1": "<mask token>\n",
"step-2": "while True:\n a, b = input().split()\n a = float(a)\n b = float(b)\n if b == 0:\n print('error')\n else:\n c = a / b + 0.5\n c = int(c)\n print(c)\n",
"step... | [
0,
1,
2
] |
<|reserved_special_token_0|>
@jd.get('/routerjson')
def apply_jd_waybill(db):
query = bottle.request.query
if query['method'] == 'jingdong.etms.waybillcode.get':
jd_code, resp = jd_get_response_normal()
logging.debug('JD response: {} {}'.format(jd_code, resp))
db.add(JdWaybillApplyResp... | flexible | {
"blob_id": "a93884757069393b4d96de5ec9c7d815d58a2ea5",
"index": 935,
"step-1": "<mask token>\n\n\n@jd.get('/routerjson')\ndef apply_jd_waybill(db):\n query = bottle.request.query\n if query['method'] == 'jingdong.etms.waybillcode.get':\n jd_code, resp = jd_get_response_normal()\n logging.deb... | [
4,
5,
6,
7,
8
] |
import random #import random module
guesses_taken = 0 #assign 0 to guesses_taken variable
print('Hello! What is your name?')# print Hello! What is your name? to console
myName = input()#take an input from user(name)
number = random.randint(1, 20)# make random number between 1 and 19 and save in number variable
print... | normal | {
"blob_id": "3302dc058032d9fe412bde6fd89699203526a72d",
"index": 4695,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('Hello! What is your name?')\n<mask token>\nprint('Well, ' + myName + ', I am thinking of a number between 1 and 20.')\nwhile guesses_taken < 6:\n print('Take a guess.')\n gue... | [
0,
1,
2,
3,
4
] |
from datetime import datetime
from sqlalchemy import Column, Integer, String, ForeignKey, DateTime
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import relationship
Base = declarative_base()
class BusLine(Base):
__tablename__ = "bus_lines"
id = Column(Integer, primary_key=True)... | normal | {
"blob_id": "9e896d935cc57e580ed46cd501b41053bbaab38f",
"index": 6490,
"step-1": "<mask token>\n\n\nclass BusRoute(Base):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\nclass BusRoutePos(Base):\n __tablename__ = 'bus_route_pos'\n id = Column... | [
12,
15,
16,
17,
19
] |
include('f469-disco/manifest_f469.py')
freeze('src')
| normal | {
"blob_id": "3b29912788fa4cc76f34f52da7728e934ee96637",
"index": 7117,
"step-1": "<mask token>\n",
"step-2": "include('f469-disco/manifest_f469.py')\nfreeze('src')\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
from django.urls import path
from .views import *
urlpatterns = [path('country', Country_Data, name='country_data'), path(
'tours', Scrape_Data, name='scrape_data'), path('draws', Draw_Data,
name='Draw_data')]
| normal | {
"blob_id": "b39c783cbaff2915c8864ce0b081b5bf052baee5",
"index": 6731,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('country', Country_Data, name='country_data'), path(\n 'tours', Scrape_Data, name='scrape_data'), path('draws', Draw_Data,\n name='Draw_data')]\n",
"step-3": "... | [
0,
1,
2
] |
<|reserved_special_token_0|>
class DBException(Exception):
"""
Represents a generic exception thrown by the Database Manager
"""
pass
class DBManager:
def __init__(self, cfg):
self.cfg = cfg
self.__companies = {}
self.__loggedIn = False
self.connection = None
... | flexible | {
"blob_id": "31b87a3ceca1f48665ecc9754d5f87bb9b7bbf13",
"index": 7579,
"step-1": "<mask token>\n\n\nclass DBException(Exception):\n \"\"\"\n Represents a generic exception thrown by the Database Manager\n \"\"\"\n pass\n\n\nclass DBManager:\n\n def __init__(self, cfg):\n self.cfg = cfg\n ... | [
15,
17,
18,
19,
22
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Login(models.Model):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Login(models.Model):
trinity_... | flexible | {
"blob_id": "1c5cb9363c2903905f1026ede77615e8373c250b",
"index": 7321,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Login(models.Model):\n <mask token>\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Login(models.Model):\n trinity_id = models.CharField('', m... | [
0,
1,
2,
3,
4
] |
import tensorflow as tf
import numpy as np
import OpenAi.Pendulum.ActorCritic.Models as Models
"""
The `Buffer` class implements Experience Replay.
---
---
**Critic loss** - Mean Squared Error of `y - Q(s, a)`
where `y` is the expected return as seen by the Target netw... | normal | {
"blob_id": "8a9ed10bf25f3aa13fde43079303194fc6db26c0",
"index": 4248,
"step-1": "<mask token>\n\n\nclass Agent:\n <mask token>\n\n def record(self, obs_tuple):\n index = self.buffer_counter % self.buffer_capacity\n self.state_buffer[index] = obs_tuple[0]\n self.action_buffer[index] = ... | [
8,
9,
10,
12,
13
] |
<|reserved_special_token_0|>
class _BaseNevergradOptimizer:
<|reserved_special_token_0|>
def __init__(self, method):
self.method = method
self.valid_methods = [x[0] for x in ng.optimizers.registry.items()]
self.sequential_methods = ['SQPCMA', 'chainCMAPowell', 'Powell']
self.i... | flexible | {
"blob_id": "4a136a6284add3bcbd7f9546e18e79151cea685f",
"index": 623,
"step-1": "<mask token>\n\n\nclass _BaseNevergradOptimizer:\n <mask token>\n\n def __init__(self, method):\n self.method = method\n self.valid_methods = [x[0] for x in ng.optimizers.registry.items()]\n self.sequentia... | [
3,
4,
5,
6,
8
] |
from pathlib import Path
import eyed3
import csv
import sys
import filetype
import os
pathFile = Path(
'C:\\Users\\JORGE\\Music\\Vicente Garcia - Te Soñé (Lyric Video)(MP3_160K).mp3'
)
audiofile = eyed3.load(pathFile)
with open('loveMusic.csv', 'w', newline='') as csvFile:
fieldsName = ['nameFile', 'tittle... | normal | {
"blob_id": "629649abe9d855122a5db6d61a20735ceb89c5cf",
"index": 6426,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('loveMusic.csv', 'w', newline='') as csvFile:\n fieldsName = ['nameFile', 'tittle', 'artist', 'gender', 'path']\n writer = csv.DictWriter(csvFile, fieldnames=fieldsName)\n... | [
0,
1,
2,
3
] |
from tkinter import *
import re
class Molecule:
def __init__(self, nom, poids, adn):
self.nom = nom
self.poids = poids
self.adn = adn
def __repr__(self):
return "{} : {} g".format(self.nom, self.poids)
class Menu:
def __init__(self):
self.data = dict()
se... | normal | {
"blob_id": "4d05e65dce9f689ae533a57466bc75fa24db7b4d",
"index": 4558,
"step-1": "<mask token>\n\n\nclass Menu:\n\n def __init__(self):\n self.data = dict()\n self.main = Tk()\n self.main.title('Molécules')\n self.main.config(bg='black')\n self.main.minsize(210, 220)\n ... | [
17,
18,
23,
24,
26
] |
<|reserved_special_token_0|>
class REvolution:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def get_pop(self):
ids = ['x: {} => y: {}'.format('%.3f' % i.value[0], '%.3f' % self.
fitness(i.value)) for i in self.population.individuals]
... | flexible | {
"blob_id": "fe13b57484e0f0796164fda99c0d759238a67153",
"index": 7215,
"step-1": "<mask token>\n\n\nclass REvolution:\n <mask token>\n <mask token>\n <mask token>\n\n def get_pop(self):\n ids = ['x: {} => y: {}'.format('%.3f' % i.value[0], '%.3f' % self.\n fitness(i.value)) for i in... | [
2,
4,
5,
6,
7
] |
# Comic Downloader
#! python3
import urllib, bs4, requests
url = 'http://explosm.net/comics/39/'
base_url = 'http://explosm.net'
for i in range(1,4000):
req = requests.get(url)
req.raise_for_status()
soup = bs4.BeautifulSoup(req.text, "lxml")
comic = soup.select('#main-comic')
comicUrl = 'http:'... | normal | {
"blob_id": "66e77b8237850a29127402310bfab3061f7ebca4",
"index": 2346,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(1, 4000):\n req = requests.get(url)\n req.raise_for_status()\n soup = bs4.BeautifulSoup(req.text, 'lxml')\n comic = soup.select('#main-comic')\n comicUrl = '... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/python
# This script deletes and recreates the NIC BoD intents.
# Use nic-bod-setup.py to set up the physical network and NEMO nodes first
import requests,json
import argparse, sys
from requests.auth import HTTPBasicAuth
USERNAME='admin'
PASSWORD='admin'
NIC_INTENTS="http://%s:8181/restconf/config/intent... | normal | {
"blob_id": "955017ad7cc9dde744b8d8a9439f63f4725d50bc",
"index": 1673,
"step-1": "#!/usr/bin/python\n\n# This script deletes and recreates the NIC BoD intents.\n# Use nic-bod-setup.py to set up the physical network and NEMO nodes first\n\nimport requests,json\nimport argparse, sys\nfrom requests.auth import HTTP... | [
0
] |
#!/usr/bin/python
# -*- coding: utf-8 -*-
import pandas as pd
import numpy as np
import datetime
import time
from sys import exit
from matplotlib import colors, pyplot as plt
from functools import reduce
import matplotlib.cm as cm
import seaborn as sns
from astropy.io import ascii, fits
from astropy.wcs import wcs
fr... | normal | {
"blob_id": "736fee6f9a46b8568b2dd217b81d54d689306630",
"index": 970,
"step-1": "<mask token>\n\n\nclass bcolors:\n HEADER = '\\x1b[95m'\n OKBLUE = '\\x1b[94m'\n OKGREEN = '\\x1b[92m'\n WARNING = '\\x1b[93m'\n FAIL = '\\x1b[91m'\n ENDC = '\\x1b[0m'\n BOLD = '\\x1b[1m'\n UNDERLINE = '\\x1b... | [
3,
4,
5,
6,
7
] |
L5 = [0]*10
print(L5)
L5[2] = 20
print(L5)
print(L5[1:4])
L5.append(30)
print(L5)
L5.remove(30) #Elimina la primera ocurrencia del objeto
print(L5)
L6 = [1,2,3,4,5,6]
print(L6[1::2])
print(L6[::2]) | normal | {
"blob_id": "052824082854c5f7721efb7faaf5a794e9be2789",
"index": 6517,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(L5)\n<mask token>\nprint(L5)\nprint(L5[1:4])\nL5.append(30)\nprint(L5)\nL5.remove(30)\nprint(L5)\n<mask token>\nprint(L6[1::2])\nprint(L6[::2])\n",
"step-3": "L5 = [0] * 10\nprint... | [
0,
1,
2,
3
] |
import tcod as libtcod
import color
from input_handlers import consts
from input_handlers.ask_user_event_handler import AskUserEventHandler
class SelectIndexHandler(AskUserEventHandler):
"""
Handles asking the user for an index on the map.
"""
def __init__(self, engine):
super().__init__(eng... | normal | {
"blob_id": "8c7dcff80eeb8d7d425cfb25da8a30fc15daf5f9",
"index": 4872,
"step-1": "<mask token>\n\n\nclass SelectIndexHandler(AskUserEventHandler):\n <mask token>\n <mask token>\n\n def on_render(self, console):\n \"\"\"\n Highlight the tile under the cursor.\n \"\"\"\n super(... | [
3,
6,
7,
8,
9
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Time : 2017/6/20 下午4:00
# @Author : Huang HUi
# @Site :
# @File : query_parse.py
# @Software: PyCharm
from mysqlConnection import mysqlConnection
import yaml
import copy
import time
import csv
import json
from collections import OrderedDict
import ast
#
# GIV... | normal | {
"blob_id": "b52807a15cef8f07f685f8761a470d4a24d9c3dc",
"index": 6603,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef query_parse(GIVEN_QUERY):\n try:\n countryIds_query = list(map(lambda x: x['country_id'], GIVEN_QUERY[\n 'countries']))\n except:\n countryIds_query... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class max31865(object):
<|reserved_special_token_0|>
def __init__(self, csPin=8, misoPin=9, mosiPin=10, clkPin=11):
self.csPin = csPin
self.misoPin = misoPin
self.mosiPin = mosiPin
self.clkPin = clkPin
self.setupGPIO()
<|reserved_specia... | flexible | {
"blob_id": "5d92c68e0fe7f37d4719fb9ca4274b29ff1cbb43",
"index": 4699,
"step-1": "<mask token>\n\n\nclass max31865(object):\n <mask token>\n\n def __init__(self, csPin=8, misoPin=9, mosiPin=10, clkPin=11):\n self.csPin = csPin\n self.misoPin = misoPin\n self.mosiPin = mosiPin\n ... | [
8,
9,
11,
12,
14
] |
#!/usr/bin/env python3
import pandas as pd
import csv
def get_apriori_input(input_file,output_file,sample_col="Sample",gene_id_col="Gene_ID"):
df=pd.read_csv(input_file,sep="\t")
sample_names=df[sample_col].unique()
with open(output_file,"w") as out:
csv_writer=csv.writer(out,delimiter="\t")
... | normal | {
"blob_id": "e14bea6376c8649bf9c9c5759d530af773664cd4",
"index": 891,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_apriori_input(input_file, output_file, sample_col='Sample',\n gene_id_col='Gene_ID'):\n df = pd.read_csv(input_file, sep='\\t')\n sample_names = df[sample_col].unique(... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class BaseSearchFilterSet(django_filters.FilterSet):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def __init__(self, *args, **kwargs):
self.facet_config = kwargs.pop('facet_config', {})
self.view = kwargs.pop('view', None)
super().__init__... | flexible | {
"blob_id": "f225fbf363f1b170704418ed339f2e57ca790975",
"index": 5317,
"step-1": "<mask token>\n\n\nclass BaseSearchFilterSet(django_filters.FilterSet):\n <mask token>\n <mask token>\n\n def __init__(self, *args, **kwargs):\n self.facet_config = kwargs.pop('facet_config', {})\n self.view =... | [
4,
5,
6,
7,
8
] |
import h5py
import numpy as np
from matplotlib import pyplot
from IPython.Shell import IPShellEmbed
ipshell = IPShellEmbed("Dropping to IPython shell")
filename = "SPY-VXX-20090507-20100427.hdf5"
start_day = 1
end_day = 245
#start_day = 108
#end_day = 111
start_day = 120
end_day = 245
start_day = 1
end_day = 120
s... | normal | {
"blob_id": "175e8ecdd0c9faa5fc981447f821763e0eb58b4d",
"index": 5609,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nipshell = IPShellEmbed('Dropping to IPython shell')\nfilename = 'SPY-VXX-20090507-20100427.hdf5'\nstart_day = 1\nend_day = 245\nstart_day = 120\nend_day = 245\nstart_day = 1\nend_day = 12... | [
0,
1,
2,
3
] |
#! /usr/bin/env python
# coding: utf-8
'''
Author: xiezhw3@163.com
@contact: xiezhw3@163.com
@version: $Id$
Last modified: 2016-01-17
FileName: consumer.py
Description: 从 rabbitmq 拿到消息并存储到数据库
'''
import pika
import json
import logging
import pymongo
import traceback
from conf import config
from code.modules.db_proce... | normal | {
"blob_id": "ff26a2c2d8427f1ad4617669e701ea88b34616cd",
"index": 9152,
"step-1": "<mask token>\n\n\nclass Consumer(object):\n <mask token>\n\n def __init__(self):\n self.db_processor = DbProcessor()\n credentials = pika.PlainCredentials(config.RABBITMQ_USER, config.\n RABBITMQ_PASS... | [
3,
5,
6,
7,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print("""
Your current directory is: """ + curr_path +
"""
It contains the following files and directories:
""" + str(os.
listdir('.')))
<|reserved_special_token_0|>
os.mkdir(project)
os.chdir(project)
<|reserved_special... | flexible | {
"blob_id": "0131657a7675904ee2743448f514a9f11e0dc0ad",
"index": 7561,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(\"\"\"\nYour current directory is: \"\"\" + curr_path +\n \"\"\"\n\nIt contains the following files and directories:\n\n\"\"\" + str(os.\n listdir('.')))\n<mask token>\nos.mkd... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class ClassromConfig(AppConfig):
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class ClassromConfig(AppConfig):
name = 'classrom'
<|reserved_special_token_1|>
from django.... | flexible | {
"blob_id": "a995305cb5589fa0cbb246ae3ca6337f4f2c3ca1",
"index": 8798,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass ClassromConfig(AppConfig):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass ClassromConfig(AppConfig):\n name = 'classrom'\n",
"step-4": "from django.apps import ... | [
0,
1,
2,
3
] |
# 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
] |
#Answer to The Ship Teams - https://py.checkio.org/en/mission/the-ship-teams/
def two_teams(sailors):
result = [] #To store the result
temp = [[],[]] #To store the intermediatary values
for i in sailors.items(): #To get the values of dictionary as Tuple
if i[1] > 40 or i[1] < 20: #To get the people... | normal | {
"blob_id": "de634c95fddf4591cb15cd0eb20e798043075798",
"index": 2464,
"step-1": "<mask token>\n",
"step-2": "def two_teams(sailors):\n result = []\n temp = [[], []]\n for i in sailors.items():\n if i[1] > 40 or i[1] < 20:\n temp[0].append(i[0])\n else:\n temp[1].ap... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
cv2.imshow('Original', image)
cv2.waitKey(0)
<|reserved_special_token_0|>
cv2.imshow('Rotated by 45 degrees', rotated)
cv2.waitKey(0)
<|reserved_special_token_0|>
cv2.imshow('Rotated by -90 degrees', rotated)
cv2.waitKey(0)
<|rese... | flexible | {
"blob_id": "4462fec6e0edc25530c93ffeeae2372c86fef2cc",
"index": 528,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ncv2.imshow('Original', image)\ncv2.waitKey(0)\n<mask token>\ncv2.imshow('Rotated by 45 degrees', rotated)\ncv2.waitKey(0)\n<mask token>\ncv2.imshow('Rotated by -90 degrees', rotated)\ncv2.... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class PluginSetupTests(unittest.TestCase):
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class PluginSetupTests(unittest.TestCase):
def test_plugin_setup(self):
self... | flexible | {
"blob_id": "4296dc5b79fd1d2c872eb1115beab52a0f067423",
"index": 4816,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass PluginSetupTests(unittest.TestCase):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass PluginSetupTests(unittest.TestCase):\n\n def test_plugin_setup(self):\n ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
urlpatterns = [path('users/', views.UserCreateAPIView.as_view(), name=
'user-list'), path('users/login/', CustomObtainAuthToken.as_view()),
path('users/<int:pk>/', views.ReadUserAPIView.as_view()), path(
'users/<int:pk... | flexible | {
"blob_id": "49d76458b8adcf6eea9db2ef127609ff96e03ad1",
"index": 6270,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('users/', views.UserCreateAPIView.as_view(), name=\n 'user-list'), path('users/login/', CustomObtainAuthToken.as_view()),\n path('users/<int:pk>/', views.ReadUse... | [
0,
1,
2
] |
def parse(filename):
t1, t2 = open(filename).read().strip().split('\n\n')
return tuple(map(lambda x: list(map(int, x.split('\n')[1:])), [t1, t2]))
def score(deck):
res = 0
for i in range(len(deck)):
res += deck[i] * (len(deck) - i)
return res
<|reserved_special_token_0|>
def combat(dec... | flexible | {
"blob_id": "508d016161131481ace41f3d3bda005423125fe5",
"index": 5635,
"step-1": "def parse(filename):\n t1, t2 = open(filename).read().strip().split('\\n\\n')\n return tuple(map(lambda x: list(map(int, x.split('\\n')[1:])), [t1, t2]))\n\n\ndef score(deck):\n res = 0\n for i in range(len(deck)):\n ... | [
4,
5,
6,
8,
9
] |
#List methods allow you to modify lists. The following are some list methods for you to practice with. Feel free to google resources to help you with this assignment.
#append(element) adds a single element to the list
#1. 'Anonymous' is also deserving to be in the hacker legends list. Add him in to the hacker legends ... | normal | {
"blob_id": "53fd020946a2baddb1bb0463d2a56744de6e3822",
"index": 5506,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nhacker_legends.append('Anonymous')\nprint(hacker_legends)\n<mask token>\nnetworking.insert(3, 'SSH')\nprint(networking)\n<mask token>\nip_addy.remove(5102018)\nprint(ip_addy)\n<mask token... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for ti in range(tn):
rn, cn = [int(x) for x in input().split()]
evenRow = '-'.join(['+'] * (cn + 1))
oddRow = '.'.join(['|'] * (cn + 1))
artrn = rn * 2 + 1
print(f'Case #{ti + 1}:')
for ri in range(artrn):
... | flexible | {
"blob_id": "1972e3733918da654cd156a500432a35a239aed4",
"index": 1841,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor ti in range(tn):\n rn, cn = [int(x) for x in input().split()]\n evenRow = '-'.join(['+'] * (cn + 1))\n oddRow = '.'.join(['|'] * (cn + 1))\n artrn = rn * 2 + 1\n print(... | [
0,
1,
2,
3
] |
from graphviz import Digraph
dot = Digraph()
dot.edge("BaseException", "SystemExit")
dot.edge("BaseException", "KeyboardInterrupt")
dot.edge("BaseException", "GeneratorExit")
dot.edge("BaseException", "Exception")
dot.edge("Exception", "StopIteration")
dot.edge("Exception", "StopAsyncIteration")
dot.edge("Exception",... | normal | {
"blob_id": "a7db627c49b53cd3a073d866a0373336a46b4053",
"index": 1088,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ndot.edge('BaseException', 'SystemExit')\ndot.edge('BaseException', 'KeyboardInterrupt')\ndot.edge('BaseException', 'GeneratorExit')\ndot.edge('BaseException', 'Exception')\ndot.edge('Exce... | [
0,
1,
2,
3,
4
] |
from functools import partial
import numpy as np
import scipy.stats as sps
# SPMs HRF
def spm_hrf_compat(t,
peak_delay=6,
under_delay=16,
peak_disp=1,
under_disp=1,
p_u_ratio = 6,
normalize=True,
... | normal | {
"blob_id": "596ee5568a32c3044e797375fbc705e2091f35c2",
"index": 4340,
"step-1": "<mask token>\n\n\ndef spm_hrf_compat(t, peak_delay=6, under_delay=16, peak_disp=1, under_disp\n =1, p_u_ratio=6, normalize=True):\n \"\"\" SPM HRF function from sum of two gamma PDFs\n\n This function is designed to be par... | [
4,
5,
6,
7,
8
] |
import unittest
import gym
import torch
from all.environments import DuplicateEnvironment, GymEnvironment
def make_vec_env(num_envs=3):
env = [GymEnvironment('CartPole-v0') for i in range(num_envs)]
return env
class DuplicateEnvironmentTest(unittest.TestCase):
def test_env_name(self):
env = Dupl... | normal | {
"blob_id": "e01eced7c43aae354047fbf29028c601d1daae50",
"index": 9636,
"step-1": "<mask token>\n\n\nclass DuplicateEnvironmentTest(unittest.TestCase):\n <mask token>\n\n def test_num_envs(self):\n num_envs = 5\n env = DuplicateEnvironment(make_vec_env(num_envs))\n self.assertEqual(env.... | [
4,
5,
6,
7,
9
] |
#Sorting for a number list
#ascending and descending
ls=[1,34,23,56,34,67,87,54,62,31,66]
ls.sort(reverse=True)
print(ls)
ls.sort()
print(ls)
#Sorting a letter's list with different scenarios
ls_l=["aaa","ertdf","ieurtff","fnjr","resdjx","jfh","r","fd"]
#1-sort according to string length from small length to bigger
ls... | normal | {
"blob_id": "0e0e51904f05b41b4769b730c836568b8bb63869",
"index": 9564,
"step-1": "<mask token>\n\n\ndef secondItem(ls):\n return ls[2]\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef FirstLetter(string):\n return string[0]\n\n\n<mask token>\n\n\ndef secondItem(ls):\n return ls[2]\n\n\n<mask tok... | [
1,
2,
3,
4,
5
] |
import logging
import azure.functions as func
def main(event: func.EventHubEvent):
logging.info('Python EventHub trigger processed an event: %s', event.
get_body().decode('utf-8'))
| normal | {
"blob_id": "58f8924a9cd2af4106e54b163e96bcd8517282b5",
"index": 2803,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main(event: func.EventHubEvent):\n logging.info('Python EventHub trigger processed an event: %s', event.\n get_body().decode('utf-8'))\n",
"step-3": "import logging\ni... | [
0,
1,
2
] |
# pylint: disable=C0103, C0413, E1101, W0611
"""Covid Catcher Backend"""
import os
from os.path import join, dirname
import json
import requests
import flask
from flask import request
import flask_sqlalchemy
import flask_socketio
from dotenv import load_dotenv
from covid import get_covid_stats_by_state
from covid impor... | normal | {
"blob_id": "8d48b5b831edb62b2d9624bc23cae45d390fd224",
"index": 8035,
"step-1": "<mask token>\n\n\ndef emit_all_users(channel):\n \"\"\"emits all users\"\"\"\n all_users = [user.name for user in db.session.query(models.User1).all()]\n socketio.emit(channel, {'allUsers': all_users})\n return channel\... | [
12,
13,
14,
18,
19
] |
<|reserved_special_token_0|>
class UndoDelegator:
<|reserved_special_token_0|>
def undo_block_start(*args):
pass
def undo_block_stop(*args):
pass
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Editor:
<|reserved_special_token_0|>
def __init__(self, flist=No... | flexible | {
"blob_id": "3b7c30718838a164eaf3aa12cd7b6a68930346f8",
"index": 8604,
"step-1": "<mask token>\n\n\nclass UndoDelegator:\n <mask token>\n\n def undo_block_start(*args):\n pass\n\n def undo_block_stop(*args):\n pass\n",
"step-2": "<mask token>\n\n\nclass Editor:\n <mask token>\n\n d... | [
3,
7,
8,
9,
10
] |
"""Unit tests for misc. ticket functions."""
from pdm_utils.classes import bundle
from pdm_utils.classes import genome
from pdm_utils.classes import ticket
from pdm_utils.classes import eval
from pdm_utils.functions import tickets
from pdm_utils.constants import constants
import unittest
class TestTicketFunctions... | normal | {
"blob_id": "d8ba2557e20920eaadd2fd35f0ebdf1b4a5b33da",
"index": 9010,
"step-1": "<mask token>\n\n\nclass TestTicketFunctions1(unittest.TestCase):\n\n def setUp(self):\n self.required_keys = constants.IMPORT_TABLE_STRUCTURE['required']\n self.optional_keys = constants.IMPORT_TABLE_STRUCTURE['opt... | [
22,
24,
27,
39,
40
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def dir_slash():
slash = '/'
if 'win' in sys.platform:
slash = '\\'
return slash
<|reserved_special_token_1|>
import sys
def dir_slash():
slash = '/'
if 'win' in sys.platform:
slash = '\\... | flexible | {
"blob_id": "b12c8d0cb1cd1e48df6246fe3f16467b2db296e0",
"index": 745,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef dir_slash():\n slash = '/'\n if 'win' in sys.platform:\n slash = '\\\\'\n return slash\n",
"step-3": "import sys\n\n\ndef dir_slash():\n slash = '/'\n if 'w... | [
0,
1,
2
] |
#!/usr/bin/python
##
# @file
# This file is part of SeisSol.
#
# @author Sebastian Rettenberger (rettenbs AT in.tum.de, http://www5.in.tum.de/wiki/index.php/Sebastian_Rettenberger,_M.Sc.)
#
# @section LICENSE
# Copyright (c) 2013, SeisSol Group
# All rights reserved.
#
# Redistribution and use in source and binary for... | normal | {
"blob_id": "91e1ac12ba99a8efd8f7f26310244d83bdd4aa52",
"index": 2510,
"step-1": "<mask token>\n\n\nclass Partitioner:\n <mask token>\n\n def __init__(self, mesh, partitions, tmpdir):\n metisMesh = tmpdir.path(METIS_MESH)\n metis.MeshWriter(metisMesh, mesh.elements())\n metisGraph = tm... | [
3,
4,
5,
6,
7
] |
# -*- coding: utf-8 -*-
"""
Created on Fri Apr 10 01:03:35 2020
@author: Jordan
"""
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from datetime import date
## from COVID19_Simple import *
from COVID19_Diff import calc_diff_country
### Dash Stuff ###
import dash
import dash_core... | normal | {
"blob_id": "1e02d584cde0cdf251aa36abd27b683219ef87ed",
"index": 7539,
"step-1": "<mask token>\n\n\n@app.callback(Output(component_id='global-box-1', component_property=\n 'figure'), [Input(component_id='global-dropdown', component_property=\n 'value')])\ndef global_update(select_global):\n if select_gl... | [
3,
4,
5,
6,
7
] |
import torch
from torchelie.data_learning import *
def test_pixel_image():
pi = PixelImage((1, 3, 128, 128), 0.01)
pi()
start = torch.randn(3, 128, 128)
pi = PixelImage((1, 3, 128, 128), init_img=start)
assert start.allclose(pi() + 0.5, atol=1e-7)
def test_spectral_image():
pi = SpectralIm... | normal | {
"blob_id": "73cacc1317c8624b45c017144bc7449bc99bd045",
"index": 9542,
"step-1": "<mask token>\n\n\ndef test_pixel_image():\n pi = PixelImage((1, 3, 128, 128), 0.01)\n pi()\n start = torch.randn(3, 128, 128)\n pi = PixelImage((1, 3, 128, 128), init_img=start)\n assert start.allclose(pi() + 0.5, at... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
def corner(data, bins=20, *, range=None, axes_scale='linear', weights=None,
color=None, hist_bin_factor=1, smooth=None, smooth1d=None, labels=None,
label_kwargs=None, titles=None, show_titles=False, title_quantiles=None,
title_fmt='.2f', title_kwargs=None, truths=None, truth_c... | flexible | {
"blob_id": "ae998fb17b8d6f4f5c8871a0ebe86a039501ec99",
"index": 5959,
"step-1": "<mask token>\n\n\ndef corner(data, bins=20, *, range=None, axes_scale='linear', weights=None,\n color=None, hist_bin_factor=1, smooth=None, smooth1d=None, labels=None,\n label_kwargs=None, titles=None, show_titles=False, titl... | [
1,
2,
3,
4,
5
] |
from flask import Blueprint, render_template, request, session, url_for, redirect
from flask_socketio import join_room, leave_room, send, emit
from models.game.game import Game
from models.games.games import Games
from decorators.req_login import requires_login
game_blueprint = Blueprint('game', __name__)
@game_bluep... | normal | {
"blob_id": "1ccb23435d8501ed82debf91bd6bf856830d01cb",
"index": 6063,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@game_blueprint.route('/<string:game_id>')\n@requires_login\ndef game_index(game_id):\n return render_template('game/game.html')\n",
"step-3": "<mask token>\ngame_blueprint = Blu... | [
0,
1,
2,
3
] |
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.datasets import load_digits
from sklearn.metrics import confusion_matrix, classification_report
from sklearn.preprocessing import LabelBinarizer
def tanh(x):
return np.tanh(x)
def tanh_deriv(x):
return 1.0 - np.tanh(x) * np... | normal | {
"blob_id": "a6a5fddb8e1eda4cc8e9c79ad83019f55d149a80",
"index": 2988,
"step-1": "<mask token>\n\n\ndef tanh(x):\n return np.tanh(x)\n\n\ndef tanh_deriv(x):\n return 1.0 - np.tanh(x) * np.tanh(x)\n\n\n<mask token>\n\n\nclass NeuralNetwork:\n\n def __init__(self, layers, activation='tanh'):\n \"\"... | [
6,
8,
9,
11,
12
] |
<|reserved_special_token_0|>
class DevelopmentConfig(Config):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class ProductionConfig(Config):
DATABASE_URI = ''
class TestingConfig(Config):
TESTING = True
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class DevelopmentConf... | flexible | {
"blob_id": "d89f0ef24d8e8d23a77cbbb0ae8723c7dec8c00a",
"index": 4954,
"step-1": "<mask token>\n\n\nclass DevelopmentConfig(Config):\n <mask token>\n <mask token>\n\n\nclass ProductionConfig(Config):\n DATABASE_URI = ''\n\n\nclass TestingConfig(Config):\n TESTING = True\n",
"step-2": "<mask token>\... | [
5,
6,
7,
8,
9
] |
from django.contrib.auth.models import BaseUserManager
class MyUserManager(BaseUserManager):
def create_user(self, email, password, full_name, national_code, mobile, address):
if not email :
raise ValueError('ایمیل الزامی است')
if not full_name :
raise ValueError('نام و نام... | normal | {
"blob_id": "f5f14e4d114855b7eef555db182ee991bdf26c39",
"index": 8832,
"step-1": "<mask token>\n\n\nclass MyUserManager(BaseUserManager):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass MyUserManager(BaseUserManager):\n <mask token>\n\n def create_superuser(self, email, passwor... | [
1,
2,
3,
4,
5
] |
from selenium import webdriver
from selenium.common.exceptions import TimeoutException
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.common.keys import Keys
from selenium.webdri... | normal | {
"blob_id": "5f490d6a3444b3b782eed5691c82ab7e4b2e55db",
"index": 8883,
"step-1": "from selenium import webdriver\nfrom selenium.common.exceptions import TimeoutException\nfrom selenium.webdriver.common.by import By\nfrom selenium.webdriver.support.ui import WebDriverWait\nfrom selenium.webdriver.support import e... | [
0
] |
import numpy as np
import cv2
import colorsys
from matplotlib import pyplot as plt
img = cv2.imread('coins.jpg')
b,g,r = cv2.split(img)
rgb_img = cv2.merge([r,g,b])
gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
# Blurring image
grayBlur = cv2.medianBlur(gray, 3)
# Binary threshold
ret, thresh = cv2.threshold(grayBl... | normal | {
"blob_id": "39dda191ab2137b5f5538660f17e39b0a1358bf4",
"index": 206,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(nodes):\n r, g, b = colorsys.hsv_to_rgb(float(i) / nodes, 1.0, 1.0)\n R, G, B = int(255 * r), int(255 * g), int(255 * b)\n color = [R, G, B]\n print(color)\n ... | [
0,
1,
2,
3,
4
] |
from _math import Vector2, Vector3, Quaternion, Transform, Vector3Immutable, QuaternionImmutable, minimum_distance
from _math import mod_2pi
from math import pi as PI, sqrt, fmod, floor, atan2, acos, asin, ceil, pi, e
import operator
from sims4.repr_utils import standard_repr
import enum
import native.animation
import ... | normal | {
"blob_id": "a0310b1bab339064c36ff0fe92d275db7a6c5ba9",
"index": 8734,
"step-1": "<mask token>\n\n\ndef rad_to_deg(rad):\n return rad * 180 / PI\n\n\ndef angle_abs_difference(a1, a2):\n delta = sims4.math.mod_2pi(a1 - a2)\n if delta > sims4.math.PI:\n delta = sims4.math.TWO_PI - delta\n return... | [
52,
53,
55,
64,
75
] |
from Eutils.pathmagic import context
with context():
import argparse
import numpy as np
from model.hourglass_yolo_net_multi_gpu import HOURGLASSYOLONet
from evaluator.Eutils.pascal_val import PASCAL_VAL
# from evaluator.Eutils.coco_val import COCO_VAL
from evaluator.Eutils.detector import Detect... | normal | {
"blob_id": "3bb6305ceb1491db57c7f8b03e438398644c8f90",
"index": 8124,
"step-1": "<mask token>\n\n\nclass EVALUATOR(object):\n\n def __init__(self, detector, data):\n self.detector = detector\n self.data = data\n self.gt = self.data.gt\n self.image_ids, self.bboxes, self.prob, self... | [
5,
6,
7,
8,
9
] |
#THIS BUILD WORKS, BUT IS VERY SLOW. CURRENTLY YIELDS A DECENT SCORE, NOT GREAT
alphabet = "abcdefghijklmnopqrstuvwxyz"
def author():
return ""
def student_id():
return ""
def fill_words(pattern,words,scoring_f,minlen,maxlen):
foundWords = find_words(pattern,words,scoring_f,minlen,maxlen)
f... | normal | {
"blob_id": "9bd659bb3bf812e48710f625bb65a848d3a8d074",
"index": 594,
"step-1": "<mask token>\n\n\ndef author():\n return ''\n\n\ndef student_id():\n return ''\n\n\n<mask token>\n\n\ndef find_words(pattern, words, scoring_f, minlen, maxlen):\n patternCopy = pattern\n bestWord = '', 0\n bestState =... | [
5,
7,
8,
9,
10
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(contador_letras(lista_animais))
<|reserved_special_token_1|>
contador_letras = lambda lista: [len(x) for x in lista]
lista_animais = ['cachorro', 'pato', 'marreco']
print(contador_letras(lista_animais))
<|reserved_speci... | flexible | {
"blob_id": "d13957c3d3f4d34279dc660d80ca91ca84ba4a77",
"index": 4504,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(contador_letras(lista_animais))\n",
"step-3": "contador_letras = lambda lista: [len(x) for x in lista]\nlista_animais = ['cachorro', 'pato', 'marreco']\nprint(contador_letras(list... | [
0,
1,
2,
3
] |
#SEE /etc/rc.local FOR BOOTUP COMMANDS
from Measure_and_File import *
from WebServer import *
from multiprocessing import *
web = WebServer()
board_boy = Measurer_and_Filer()
#try:
proc1 = Process( target=board_boy.measure_and_file, args=() )
proc1.start()
proc2 = Process( target=web.serve, args=() )
proc2.start()
#... | normal | {
"blob_id": "26744d51dbce835d31d572a053294c9d280e1a8b",
"index": 3956,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nproc1.start()\n<mask token>\nproc2.start()\n",
"step-3": "<mask token>\nweb = WebServer()\nboard_boy = Measurer_and_Filer()\nproc1 = Process(target=board_boy.measure_and_file, args=())\... | [
0,
1,
2,
3,
4
] |
class Point:
def __init__(self,x,y):
self.x=x
self.y=y
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)
p1=Point(1,2)
p2=Point(3,4)
p... | normal | {
"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
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class DrawApp(models.Model):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class SavedDrawings(models.Model):
username = models.ForeignK... | flexible | {
"blob_id": "fa566eb77b17830acad8c7bfc2b958760d982925",
"index": 7623,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass DrawApp(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\nclass SavedDrawings(models.Model):\n username = models.ForeignKey(settings... | [
0,
3,
4,
5,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(message, type(message))
<|reserved_special_token_0|>
for msg in message:
print(msg, message.count(msg))
msg_dict[msg] = message.count(msg)
print(msg_dict)
<|reserved_special_token_1|>
message = (
'It was a bri... | flexible | {
"blob_id": "20671470c087719fa9ea8ffa25be55e9ade67681",
"index": 5373,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(message, type(message))\n<mask token>\nfor msg in message:\n print(msg, message.count(msg))\n msg_dict[msg] = message.count(msg)\nprint(msg_dict)\n",
"step-3": "message = (\... | [
0,
1,
2,
3
] |
from __future__ import division, print_function, unicode_literals
import sys
import os
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..'))
from pyglet.gl import *
from pyglet.window import key
from cocos.actions import *
from cocos.director import director
from cocos.layer import Layer
from cocos.scene... | normal | {
"blob_id": "2678aac08104a580e866984bc4cf4adf8cb8ac5c",
"index": 5930,
"step-1": "<mask token>\n\n\nclass SpriteMoveTo(SpriteLayer):\n <mask token>\n\n\nclass FontLayer(Layer):\n\n def __init__(self, title='Sprite Exmaple #', subtitle='Goto()'):\n super(FontLayer, self).__init__()\n self.titl... | [
4,
9,
10,
11,
13
] |
<|reserved_special_token_0|>
def get_content(t):
content = t['full_text']
if 'entities' in t:
raw_urls = re.findall(
'http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*\\(\\),]|(?:%[0-9a-fA-F][0-9a-fA-F]))+'
, content)
for m in t['entities']['user_mentions']:
screen... | flexible | {
"blob_id": "001d2ae89a2d008fdf6621a1be73de94c766c65f",
"index": 4570,
"step-1": "<mask token>\n\n\ndef get_content(t):\n content = t['full_text']\n if 'entities' in t:\n raw_urls = re.findall(\n 'http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*\\\\(\\\\),]|(?:%[0-9a-fA-F][0-9a-fA-F]))+'\n ... | [
3,
8,
11,
14,
15
] |
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