code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
a = [3, 4, 2, 3, 5, 8, 23, 32, 35, 34, 4, 6, 9]
print("")
print("Lesson #2")
print("Program start:")
for i in a:
if i < 9:
print(i)
print("End") | normal | {
"blob_id": "58f7810e2731721562e3459f92684589dc66862c",
"index": 881,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('')\nprint('Lesson #2')\nprint('Program start:')\nfor i in a:\n if i < 9:\n print(i)\nprint('End')\n",
"step-3": "a = [3, 4, 2, 3, 5, 8, 23, 32, 35, 34, 4, 6, 9]\nprint('... | [
0,
1,
2,
3
] |
import hashlib
import json
#import logger
import Login.loger as logger
#configurations
import Configurations.config as config
def generate_data(*args):
#add data into seperate variables
try:
station_data = args[0]
except KeyError as e:
logger.log(log_type=config.log_error,params=e)
... | normal | {
"blob_id": "2a5c6f442e6e6cec6c4663b764c8a9a15aec8c40",
"index": 6971,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef generate_id(parameter, station_id):\n meta_data = parameter + station_id\n hash_id = hashlib.sha256(config.encryption_key)\n hash_id.update(json.dumps(meta_data).encode()... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.... | flexible | {
"blob_id": "a91d42764fa14111afca4551edd6c889903ed9bd",
"index": 8056,
"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|>
class ModelTest(TestCase):
def test_expense_form_valid_data(self):
form = StudentForm(data={'student_id': 500, 'firstName': 'Emre',
'lastName': 'Tan', 'department': 'Panama', 'mathScore': 100,
'physicsScore': 70, 'chemistryScore': 40, 'biologyScore': 1... | flexible | {
"blob_id": "6dc7c7de972388f3984a1238a2d62e53c60c622e",
"index": 6252,
"step-1": "<mask token>\n\n\nclass ModelTest(TestCase):\n\n def test_expense_form_valid_data(self):\n form = StudentForm(data={'student_id': 500, 'firstName': 'Emre',\n 'lastName': 'Tan', 'department': 'Panama', 'mathScor... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
INPUT_MINBIAS = '/build/RAWReference/MinBias_RAW_320_STARTUP.root'
INPUT_TTBAR = '/build/RAWReference/TTbar_RAW_320_STARTUP.root'
puSTARTUP_TTBAR = (
'/build/RAWReference/TTbar_Tauola_PileUp_RAW_320_STARTUP.root')
relval = {'step1': {'step': 'GEN-HLT', 't... | flexible | {
"blob_id": "78c9f92349ba834bc64dc84f884638c4316a9ea4",
"index": 352,
"step-1": "<mask token>\n",
"step-2": "INPUT_MINBIAS = '/build/RAWReference/MinBias_RAW_320_STARTUP.root'\nINPUT_TTBAR = '/build/RAWReference/TTbar_RAW_320_STARTUP.root'\npuSTARTUP_TTBAR = (\n '/build/RAWReference/TTbar_Tauola_PileUp_RAW_... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
os.system('dir ' + org_GIS + '*' + ext + ' /s/d/b >' + org_GIS + 'tempext.txt')
<|reserved_special_token_0|>
for line in lines:
ln = line.rstrip('\n')
shutil.copy(ln, outputfolder)
file1.close()
os.system('del ' + org_GIS ... | flexible | {
"blob_id": "778cf8064fa45e3e25a66f2165dcf6885c72fb8a",
"index": 634,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nos.system('dir ' + org_GIS + '*' + ext + ' /s/d/b >' + org_GIS + 'tempext.txt')\n<mask token>\nfor line in lines:\n ln = line.rstrip('\\n')\n shutil.copy(ln, outputfolder)\nfile1.clo... | [
0,
1,
2,
3,
4
] |
import os
from setuptools import setup
from django_spaghetti import __version__
with open(os.path.join(os.path.dirname(__file__), 'README.rst')) as readme:
README = readme.read()
# allow setup.py to be run from any path
os.chdir(os.path.normpath(os.path.join(os.path.abspath(__file__), os.pardir)))
setup(
nam... | normal | {
"blob_id": "6e557c2b85031a0038afd6a9987e3417b926218f",
"index": 6184,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open(os.path.join(os.path.dirname(__file__), 'README.rst')) as readme:\n README = readme.read()\nos.chdir(os.path.normpath(os.path.join(os.path.abspath(__file__), os.pardir)))\nse... | [
0,
1,
2,
3
] |
from flask import Flask
from flask import render_template
from flask import make_response
import json
from lib import powerswitch
app = Flask(__name__)
@app.route('/')
def hello_world():
return render_template('index.html')
@app.route('/on/')
def on():
state = powerswitch.on()
return json.dumps(state)
... | normal | {
"blob_id": "18d3f58048b7e5d792eb2494ecc62bb158ac7407",
"index": 254,
"step-1": "<mask token>\n\n\n@app.route('/')\ndef hello_world():\n return render_template('index.html')\n\n\n<mask token>\n\n\n@app.route('/off/')\ndef off():\n state = powerswitch.off()\n return json.dumps(state)\n\n\n@app.route('/to... | [
4,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
class Response:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def chain_size(self):
server_chain_size = self.node.get_ledger_size()
self.return_response(1, server_chain_size)
def chain_sync(self):
u = Utils()
blocks = [u.dict_t... | flexible | {
"blob_id": "55b8590410bfe8f12ce3b52710238a79d27189a7",
"index": 5125,
"step-1": "<mask token>\n\n\nclass Response:\n <mask token>\n <mask token>\n\n def chain_size(self):\n server_chain_size = self.node.get_ledger_size()\n self.return_response(1, server_chain_size)\n\n def chain_sync(s... | [
5,
6,
8,
9,
10
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print('Os valores são \x1b[32m{}\x1b[m e \x1b[31m{}\x1b[m !!!'.format(a, b))
<|reserved_special_token_0|>
print('Prazer em te conhecer, {}{}{}!!!'.format(cores['azul'], nome, cores[
'amarelo']))
<|reserved_special_token_1|>
... | flexible | {
"blob_id": "7bbbd30ba1578c1165ccf5c2fff22609c16dfd64",
"index": 393,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('Os valores são \\x1b[32m{}\\x1b[m e \\x1b[31m{}\\x1b[m !!!'.format(a, b))\n<mask token>\nprint('Prazer em te conhecer, {}{}{}!!!'.format(cores['azul'], nome, cores[\n 'amarelo'])... | [
0,
1,
2,
3
] |
# accessing array elements rows/columns
import numpy as np
a = np.array([[1, 2, 3, 4, 5, 6, 7], [9, 8, 7, 6, 5, 4, 3]])
print(a.shape) # array shape
print(a)
print('\n')
# specific array element [r,c]
# item 6
print(a[0][5])
# item 8
print(a[1][1]) # or
print(a[1][-6])
# get a specific row/specific column
print(a... | normal | {
"blob_id": "8cc97ebe0ff7617eaf31919d40fa6c312d7b6f94",
"index": 8814,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(a.shape)\nprint(a)\nprint('\\n')\nprint(a[0][5])\nprint(a[1][1])\nprint(a[1][-6])\nprint(a[1])\nprint(a[0])\nprint(a[0, :])\nprint(a[:, 1])\nprint('\\n')\nprint('even numbers from f... | [
0,
1,
2,
3,
4
] |
import time
from wxpy import *
bot = Bot(cache_path='wxpy.pkl')
def get(i):
with open('晚安.txt', 'r', encoding='utf-8') as f:
line = f.readlines()[i]
return line
def send(i):
myfriend = bot.friends().search('微信好友昵称')[0]
myfriend.send(get(i))
i += 1
def main():
for i in range(3650):
... | normal | {
"blob_id": "a7d11f130e0d5d6c9b4ac7c5d3a804fb9f79b943",
"index": 2284,
"step-1": "<mask token>\n\n\ndef get(i):\n with open('晚安.txt', 'r', encoding='utf-8') as f:\n line = f.readlines()[i]\n return line\n\n\n<mask token>\n\n\ndef main():\n for i in range(3650):\n send(i)\n time.slee... | [
2,
4,
5,
6
] |
#!/usr/bin/env python
import serial
from action import Action
import math
comm = serial.Serial("/dev/ttyACM3", 115200, timeout=1)
#comm = None
robot = Action(comm)
from flask import Flask
from flask import send_from_directory
import os
static_dir = os.path.join(os.getcwd(), "ControlApp")
print "serving from " + sta... | normal | {
"blob_id": "54a6405e3447d488aa4fca88159ccaac2506df2c",
"index": 5995,
"step-1": "#!/usr/bin/env python\n\nimport serial\nfrom action import Action\nimport math\n\ncomm = serial.Serial(\"/dev/ttyACM3\", 115200, timeout=1)\n#comm = None\nrobot = Action(comm)\n\nfrom flask import Flask\nfrom flask import send_from... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def line_evaluation(param_list, param_eval, file_name='line evaluation', **
kwargs):
"""
Evaluates a list of parameter pairs across repeated trials and aggregates the result.
Parameters
----------
param_... | flexible | {
"blob_id": "d65f858c3ad06226b83d2627f6d38e03eae5b36c",
"index": 266,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef line_evaluation(param_list, param_eval, file_name='line evaluation', **\n kwargs):\n \"\"\"\n Evaluates a list of parameter pairs across repeated trials and aggregates the... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python
# encoding: utf-8
'''
1D2DCNN抽取特征,LSTM后提取特征，最后将提取的特征进行拼接，CNN与LSTM是交叉在一起的
'''
# 导入相关的包
import keras
# 导入相关层的结构
from keras.models import Sequential
from keras.layers import Conv1D, Conv2D, MaxPooling1D, MaxPooling2D, Flatten, Dense, Dropout,LSTM,Reshape
from keras import Model
# 可视化神经网络
from ... | normal | {
"blob_id": "cce1b6f8e4b3f78adfa2243fe49b4994d35c5a38",
"index": 9898,
"step-1": "<mask token>\n\n\ndef merge_model(model_1, model_2):\n \"\"\"\n keras将两个独立的模型融合起来\n :param model_1:\n :param model_2:\n :return:\n \"\"\"\n inp1 = model_1.input\n inp2 = model_2.input\n r1 = model_1.outpu... | [
2,
3,
4,
5,
6
] |
# Number Guessing Game
import random
#assign secrectNumber to random number from range 1-10, inclusive of 10
secrectNumber = random.randint (1, 11)
#initialize number or guesses to 1 and call it guess
numGuesses = 1
#prompt user to enter their name and enter their guess
name = int (input("Enter your name: ))
print(... | normal | {
"blob_id": "d2da346e11fa9508cab22a3a2fd3ca57a0a755e6",
"index": 5420,
"step-1": "# Number Guessing Game\nimport random\n#assign secrectNumber to random number from range 1-10, inclusive of 10\nsecrectNumber = random.randint (1, 11)\n#initialize number or guesses to 1 and call it guess\nnumGuesses = 1\n#prompt ... | [
0
] |
from aws_cdk import core as cdk
# For consistency with other languages, `cdk` is the preferred import name for
# the CDK's core module. The following line also imports it as `core` for use
# with examples from the CDK Developer's Guide, which are in the process of
# being updated to use `cdk`. You may delete this im... | normal | {
"blob_id": "12cd3dbf211b202d25dc6f940156536c9fe3f76f",
"index": 3385,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass kdECSDemo(cdk.Stack):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass kdECSDemo(cdk.Stack):\n\n def __init__(self, scope: cdk.Construct, construct_id: str, **kwarg... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
time.sleep(2)
def write(i):
ser.write(struct.pack('>BBB', 255, 0, i))
write(0)
time.sleep(1)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
usbport = '/dev/ttyS3'
ser = serial.Serial(usbport, 9600, timeout=1)... | flexible | {
"blob_id": "6c98be473bf4cd458ea8a801f8b1197c9d8a07b3",
"index": 3514,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ntime.sleep(2)\n\n\ndef write(i):\n ser.write(struct.pack('>BBB', 255, 0, i))\n\n\nwrite(0)\ntime.sleep(1)\n",
"step-3": "<mask token>\nusbport = '/dev/ttyS3'\nser = serial.Serial(usb... | [
0,
2,
3,
4,
5
] |
from abc import ABC, abstractmethod
class Shape(ABC): # Shape is a child class of ABC
@abstractmethod
def area(self):
pass
@abstractmethod
def perimeter(self):
pass
class Square(Shape):
def __init__(self, length):
self.length = length
square = Square(4)
# this will co... | normal | {
"blob_id": "520b9246c3c617b18ca57f31ff51051cc3ff51ca",
"index": 5517,
"step-1": "<mask token>\n\n\nclass Shape(ABC):\n\n @abstractmethod\n def area(self):\n pass\n <mask token>\n\n\nclass Square(Shape):\n\n def __init__(self, length):\n self.length = length\n\n\n<mask token>\n",
"ste... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
get_train_data(sys.argv[1], sys.argv[2])
<|reserved_special_token_1|>
from Classify import get_train_data
import sys
<|reserved_special_token_0|>
get_train_data(sys.argv[1], sys.argv[2])
<|reserved_special_token_1|>
#-*-codi... | flexible | {
"blob_id": "513aff6cf29bbce55e2382943767a9a21df2e98e",
"index": 5080,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nget_train_data(sys.argv[1], sys.argv[2])\n",
"step-3": "from Classify import get_train_data\nimport sys\n<mask token>\nget_train_data(sys.argv[1], sys.argv[2])\n",
"step-4": "#-*-codi... | [
0,
1,
2,
3
] |
import os
import json
from page import Page
from random import choice
from os.path import join, expanduser
from file_handler import f_read, f_readlines, open_local
import config
class LetterPage(Page):
def __init__(self, page_num,n):
super(LetterPage, self).__init__(page_num)
self.title = "Letters"... | normal | {
"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
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def classify(img, c_model):
""" classifies images in a given folder using the 'model'"""
im_size = 128
img = cv2.resize(img, (im_size, im_size))
img = img.astype('float') / 255.0
img = np.expand_dims(img, axi... | flexible | {
"blob_id": "c7d51f6448400af5630bdc0c29493320af88288e",
"index": 7424,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef classify(img, c_model):\n \"\"\" classifies images in a given folder using the 'model'\"\"\"\n im_size = 128\n img = cv2.resize(img, (im_size, im_size))\n img = img.as... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def merge_the_tools(string, k):
if len(string) % k != 0:
exit()
else:
L = []
for i in range(0, len(string), k):
L.append(''.join(list(dict.fromkeys(string[i:i + k]))))
print('\n'.join(L))
<|reserved_specia... | flexible | {
"blob_id": "0004e90622f8b13ec7ce0c1f49e8c8df7ea07269",
"index": 7098,
"step-1": "<mask token>\n",
"step-2": "def merge_the_tools(string, k):\n if len(string) % k != 0:\n exit()\n else:\n L = []\n for i in range(0, len(string), k):\n L.append(''.join(list(dict.fromkeys(str... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def createNewDataFrame():
columns = ['document_id', 'content', 'cat', 'subcat']
df_ = pd.DataFrame(columns=columns)
return df_
def getcategories(foldername):
cats = foldername.split('_')
print('The cats are ', cats, len(cats))
cat = ''
sub = ''
if len(cat... | flexible | {
"blob_id": "1aa01845ab98005b1fee33b4fc153bb029e450e0",
"index": 2061,
"step-1": "<mask token>\n\n\ndef createNewDataFrame():\n columns = ['document_id', 'content', 'cat', 'subcat']\n df_ = pd.DataFrame(columns=columns)\n return df_\n\n\ndef getcategories(foldername):\n cats = foldername.split('_')\n... | [
2,
3,
4,
5,
6
] |
import sys
import numpy as np
####################################################################################################
### These functions all perform QA checks on input files.
### These should catch many errors, but is not exhaustive.
#####################################################################... | normal | {
"blob_id": "7413c06a990894c34ee5174d84f0e3bd20abf51f",
"index": 3294,
"step-1": "<mask token>\n\n\ndef check_controls(subpuc_names, subpuc_controls):\n if len(subpuc_names) == len(subpuc_controls):\n pass\n else:\n sys.exit(\n 'There is an issue with your subpuc_controls.csv file.... | [
3,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
class PredictDigitView(MethodView):
def post(self):
repo = ClassifierRepo(CLASSIFIER_STORAGE)
service = PredictDigitService(repo)
image_data_uri = request.json['image']
prediction = service.handle(image_data_uri)
return Response(str(prediction)... | flexible | {
"blob_id": "3ea42e7ad5301314a39bf522280c084342cd18c5",
"index": 332,
"step-1": "<mask token>\n\n\nclass PredictDigitView(MethodView):\n\n def post(self):\n repo = ClassifierRepo(CLASSIFIER_STORAGE)\n service = PredictDigitService(repo)\n image_data_uri = request.json['image']\n pr... | [
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def main():
""" main entry point for module execution
"""
argument_spec = dict(src=dict(type='path'), replace_src=dict(), lines=
dict(aliases=['commands'], type='list'), parents=dict(type='list'),
before=dict(type='list'), after=di... | flexible | {
"blob_id": "99b5ac74da95dff399c31d58e19bac65e538a34b",
"index": 8012,
"step-1": "<mask token>\n",
"step-2": "def main():\n \"\"\" main entry point for module execution\n \"\"\"\n argument_spec = dict(src=dict(type='path'), replace_src=dict(), lines=\n dict(aliases=['commands'], type='list'), p... | [
0,
1,
2
] |
import random
import csv
# 提取随机问，同类组成正例，异类组成负例，正:负=1:3
with open('final_regroup.csv', 'w', newline='') as train:
writer = csv.writer(train)
with open('final_syn_train.csv', 'r') as zhidao:
reader = csv.reader(zhidao)
cluster = []
cur = []
stand = ''
# 将同一标准问... | normal | {
"blob_id": "3a09cbd71d23b1320af9b8ddcfc65b223e487b21",
"index": 1811,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('final_regroup.csv', 'w', newline='') as train:\n writer = csv.writer(train)\n with open('final_syn_train.csv', 'r') as zhidao:\n reader = csv.reader(zhidao)\n ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if __name__ == '__main__':
logging.basicConfig(level=logging.INFO)
logging.getLogger('crawl').setLevel(logging.INFO)
logging.getLogger('elasticsearch').setLevel(logging.ERROR)
es = Elasticsearch()
crawl.crawl_d... | flexible | {
"blob_id": "21d07c2b80aa00d0c75da342d37195b6829593b6",
"index": 1110,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n logging.basicConfig(level=logging.INFO)\n logging.getLogger('crawl').setLevel(logging.INFO)\n logging.getLogger('elasticsearch').setLevel(logging.ERR... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
start()
<|reserved_special_token_1|>
from adventurelib import *
from horror import *
from dating import *
from popquiz import *
from comedy import *
from island import *
start()
| flexible | {
"blob_id": "8a37299154aded37147e1650cbf52a5cdf7d91da",
"index": 4225,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nstart()\n",
"step-3": "from adventurelib import *\nfrom horror import *\nfrom dating import *\nfrom popquiz import *\nfrom comedy import *\nfrom island import *\nstart()\n",
"step-4":... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for threshold in range(1, 6):
rolls = np.random.randint(1, 7, size=10 ** 7)
rerolls = np.random.randint(1, 7, size=10 ** 7)
avg_roll = np.mean(np.where(rolls <= threshold, rerolls, rolls))
print(
f'Rerollin... | flexible | {
"blob_id": "e5d704541acd0f68a7885d7323118e1552e064c9",
"index": 6170,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor threshold in range(1, 6):\n rolls = np.random.randint(1, 7, size=10 ** 7)\n rerolls = np.random.randint(1, 7, size=10 ** 7)\n avg_roll = np.mean(np.where(rolls <= threshold, ... | [
0,
1,
2,
3
] |
from django.contrib import admin
# Register your models here.
from .models import Participant
class ParticipantAdmin(admin.ModelAdmin):
fieldsets = [
("Personal information", {'fields': ['email', 'name', 'institution', 'assistant']}),
("Asistance", {'fields': ['assistant', 'participant_hash']}),
... | normal | {
"blob_id": "c43b899234ffff09225153dcaf097591c7176430",
"index": 841,
"step-1": "<mask token>\n\n\nclass ParticipantAdmin(admin.ModelAdmin):\n <mask token>\n <mask token>\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass ParticipantAdmin(admin.ModelAdmin):\n fieldsets = [('Per... | [
1,
2,
3,
4,
5
] |
import os
import subprocess
import sys
import time
# print sys.argv
start = time.time()
subprocess.call(sys.argv[1:], shell=True)
stop = time.time()
print "\nTook %.1f seconds" % (stop - start)
| normal | {
"blob_id": "530ec3df27cc4c8f0798566f0c66cfbffe510786",
"index": 8611,
"step-1": "import os\r\nimport subprocess\r\nimport sys\r\nimport time\r\n\r\n# print sys.argv\r\nstart = time.time()\r\nsubprocess.call(sys.argv[1:], shell=True)\r\nstop = time.time()\r\nprint \"\\nTook %.1f seconds\" % (stop - start)\r\n",
... | [
0
] |
<|reserved_special_token_0|>
class ActionWeather(Action):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class ActionWeather(Action):
<|reserved_special_token_0|>
def run(self, dispatcher, tracker, domain):
loc = tracke... | flexible | {
"blob_id": "f87d08f3bb6faa237cce8379de3aaaa3270a4a34",
"index": 3854,
"step-1": "<mask token>\n\n\nclass ActionWeather(Action):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass ActionWeather(Action):\n <mask token>\n\n def run(self, dispatcher, tracker, domain):\n loc = ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for i in range(5):
score = int(input())
if score < 40:
score = 40
result += score
print(result // 5)
<|reserved_special_token_1|>
result = 0
for i in range(5):
score = int(input())
if score < 40:
... | flexible | {
"blob_id": "4a13a0d7aa2371d7c8963a01b7cc1b93f4110d5e",
"index": 5356,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(5):\n score = int(input())\n if score < 40:\n score = 40\n result += score\nprint(result // 5)\n",
"step-3": "result = 0\nfor i in range(5):\n score = ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def check(request):
if not request.user.is_authenticated:
return redirect('/auth/login/')
else:
return redirect('/worker/')
def loginpg(request):
return render(request, 'registration/login.html')
<|reserved_special_token_0|>
<|reserved_special_token_1|>
... | flexible | {
"blob_id": "fc2afc99dc754b58c36bc76c723727337851cc3e",
"index": 5326,
"step-1": "<mask token>\n\n\ndef check(request):\n if not request.user.is_authenticated:\n return redirect('/auth/login/')\n else:\n return redirect('/worker/')\n\n\ndef loginpg(request):\n return render(request, 'regis... | [
2,
3,
4,
5,
6
] |
__all__ = ['language']
from StringTemplate import *
| normal | {
"blob_id": "e70c25ce1d61437aacfe7fad0a51e096e1ce4f5d",
"index": 5212,
"step-1": "<mask token>\n",
"step-2": "__all__ = ['language']\n<mask token>\n",
"step-3": "__all__ = ['language']\nfrom StringTemplate import *\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
} | [
0,
1,
2
] |
<|reserved_special_token_0|>
def generar_numero_aleatorio():
return random.randint(1, 100)
def es_el_numero(resp_usuario, resp_correc):
return resp_usuario == resp_correc
def numero_dado_es_mayor(resp_usuario, resp_correc):
return resp_usuario > resp_correc
<|reserved_special_token_0|>
def el_nume... | flexible | {
"blob_id": "8498ba69e4cc5c5f480644ac20d878fb2a632bee",
"index": 5128,
"step-1": "<mask token>\n\n\ndef generar_numero_aleatorio():\n return random.randint(1, 100)\n\n\ndef es_el_numero(resp_usuario, resp_correc):\n return resp_usuario == resp_correc\n\n\ndef numero_dado_es_mayor(resp_usuario, resp_correc)... | [
5,
6,
7,
9,
10
] |
"""
Given the root of a binary tree, check whether it is a mirror of itself (i.e., symmetric around its center).
Example 1:
Input: root = [1, 2, 2, 3, 4, 4, 3]
Output: true
1
/ \
2 2
/ \ / \
3 4 4 3
Example 2:
Input: root = [1, 2, 2, None, 3, None, 3]
Output: false
1
/ ... | normal | {
"blob_id": "9cfbb06df4bc286ff56983d6e843b33e4da6ccf8",
"index": 7803,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef is_symmetric(root):\n\n def helper(left, right):\n if left is None and right is None:\n return True\n elif left and right:\n return helper(l... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for line in sys.stdin:
line = line.strip()
twits = line.split()
i = 0
while i < len(twits):
j = 0
while j < len(twits):
if i != j:
print('%s%s\t%d' % (twits[i] + ' ', twi... | flexible | {
"blob_id": "e884825325ceb401142cab0618d9d4e70e475cf5",
"index": 893,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor line in sys.stdin:\n line = line.strip()\n twits = line.split()\n i = 0\n while i < len(twits):\n j = 0\n while j < len(twits):\n if i != j:\n ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
dependencies = [(... | flexible | {
"blob_id": "24ed29dfaaf7ce508b2d80740bad1304b291c596",
"index": 8466,
"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 = [('projects', ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
with io.open(file_name, 'rb') as image_file:
content = image_file.read()
<|reserved_special_token_0|>
print(response)
print(response.safe_search_annotation.adult)
for label in response.label_annotations:
print(label.descri... | flexible | {
"blob_id": "800573786913ff2fc37845193b5584a0a815533f",
"index": 8340,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith io.open(file_name, 'rb') as image_file:\n content = image_file.read()\n<mask token>\nprint(response)\nprint(response.safe_search_annotation.adult)\nfor label in response.label_ann... | [
0,
1,
2,
3,
4
] |
from django.shortcuts import render
from .. login.models import *
def user(request):
context = {
"users" : User.objects.all(),
"user_level" : User.objects.get(id = request.session['user_id'])
}
return render(request, 'dashboard/user.html', context)
def admin(request):
context = {
... | normal | {
"blob_id": "3d737d0ee9c3af1f8ebe4c6998ad30fa34f42856",
"index": 570,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef user(request):\n context = {'users': User.objects.all(), 'user_level': User.objects.get(\n id=request.session['user_id'])}\n return render(request, 'dashboard/user.htm... | [
0,
1,
2,
3,
4
] |
class Solution:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution:
def twoSum(self, nums, target):
d = dict([(nums[i], i) for i in range(len(nums))])
for n in range(len(nums)):
dif = target - nums[n]
if dif in d an... | flexible | {
"blob_id": "16cc85324b555f0cfec8d577b776b86872578822",
"index": 6016,
"step-1": "class Solution:\n <mask token>\n\n\n<mask token>\n",
"step-2": "class Solution:\n\n def twoSum(self, nums, target):\n d = dict([(nums[i], i) for i in range(len(nums))])\n for n in range(len(nums)):\n ... | [
1,
2,
3,
4,
5
] |
'''import math
x = 5
print("sqrt of 5 is", math.sqrt(64))
str1 = "bollywood"
str2 = 'ody'
if str2 in str1:
print("String found")
else:
print("String not found")
print(10+20)'''
#try:
#block of code
#except Exception l:
#block of code
#else:
#this code executes if except block is executed
try... | normal | {
"blob_id": "c5b40b373953a2375eeca453a65c49bdbb8715f1",
"index": 6586,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ntry:\n fh = open('testfile.txt', 'w')\n fh.write('This is my test file for exception handling! !')\nexcept IOError:\n print(\"Error: can't find file or read data\")\nelse:\n p... | [
0,
1,
2
] |
<|reserved_special_token_0|>
def my_kron(A, B):
D = A[..., :, None, :, None] * B[..., None, :, None, :]
ds = D.shape
newshape = *ds[:-4], ds[-4] * ds[-3], ds[-2] * ds[-1]
return D.reshape(newshape)
def _identity(x):
return x
<|reserved_special_token_0|>
def sde_fn1(x, _):
lam = 0.1
s... | flexible | {
"blob_id": "c5e7fdcbd4a9281597a35a180f2853caac68f811",
"index": 7562,
"step-1": "<mask token>\n\n\ndef my_kron(A, B):\n D = A[..., :, None, :, None] * B[..., None, :, None, :]\n ds = D.shape\n newshape = *ds[:-4], ds[-4] * ds[-3], ds[-2] * ds[-1]\n return D.reshape(newshape)\n\n\ndef _identity(x):\n... | [
97,
100,
123,
125,
137
] |
<|reserved_special_token_0|>
def daemon():
p = multiprocessing.current_process()
print('Starting:', p.name, p.pid)
sys.stdout.flush()
time.sleep(2)
print('Exiting :', p.name, p.pid)
sys.stdout.flush()
<|reserved_special_token_0|>
def main2():
d = multiprocessing.Process(name='daemon_pr... | flexible | {
"blob_id": "9bb6fd6fbe212bdc29e2d1ec37fa6ec6ca9a9469",
"index": 1060,
"step-1": "<mask token>\n\n\ndef daemon():\n p = multiprocessing.current_process()\n print('Starting:', p.name, p.pid)\n sys.stdout.flush()\n time.sleep(2)\n print('Exiting :', p.name, p.pid)\n sys.stdout.flush()\n\n\n<mask ... | [
2,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
def initialize():
hands_file = open('euler54_poker.txt')
hands_string = hands_file.read()
tempList = []
newString = hands_string.replace('\n', ' ').replace(' ', '')
for i in range(0, len(newString), 2):
tempList.append(newString[i:i + 2])
hands_list = []
... | flexible | {
"blob_id": "a2a3e8d52fd467178460b178c5dbf9ccd72706e7",
"index": 8251,
"step-1": "<mask token>\n\n\ndef initialize():\n hands_file = open('euler54_poker.txt')\n hands_string = hands_file.read()\n tempList = []\n newString = hands_string.replace('\\n', ' ').replace(' ', '')\n for i in range(0, len(... | [
6,
7,
8,
9,
10
] |
<|reserved_special_token_0|>
def test_configuration(host):
sshd = host.file('/etc/ssh/sshd_config')
assert sshd.contains('^PermitRootLogin no$')
assert sshd.contains('^X11Forwarding no$')
assert sshd.contains('^UsePAM yes$')
assert sshd.contains('\\sPermitTTY no$')
ssh = host.file('/etc/ssh/ss... | flexible | {
"blob_id": "2345d1f72fb695ccec5af0ed157c0606f197009c",
"index": 3398,
"step-1": "<mask token>\n\n\ndef test_configuration(host):\n sshd = host.file('/etc/ssh/sshd_config')\n assert sshd.contains('^PermitRootLogin no$')\n assert sshd.contains('^X11Forwarding no$')\n assert sshd.contains('^UsePAM yes$... | [
1,
2,
3,
4,
5
] |
import pyttsx3
from pydub import AudioSegment
engine = pyttsx3.init() # object creation
""" RATE"""
#printing current voice rate
engine.setProperty('rate', 150) # setting up new voice rate
rate = engine.getProperty('rate') # getting details of current speaking rate
print (rate)
... | normal | {
"blob_id": "32f4f7ad61b99848c907e092c5ed7a839f0b352b",
"index": 6399,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nengine.setProperty('rate', 150)\n<mask token>\nprint(rate)\n<mask token>\nwhile i < l:\n engine.save_to_file(a[i], 'TTS/trump/{}.mp3'.format(str(i)))\n engine.runAndWait()\n if i... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print('\n\n\n\n')
<|reserved_special_token_0|>
admin1.describe_user()
print('\n')
admin1.set_user_name('Reven10')
print('\n')
admin1.describe_user()
admin1.privileges.show_privileges()
<|reserved_special_token_1|>
<|reserved_sp... | flexible | {
"blob_id": "169ad888e7629faff9509399ac7ead7a149a9602",
"index": 543,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('\\n\\n\\n\\n')\n<mask token>\nadmin1.describe_user()\nprint('\\n')\nadmin1.set_user_name('Reven10')\nprint('\\n')\nadmin1.describe_user()\nadmin1.privileges.show_privileges()\n",
... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print('-' * 40)
print('LOJA SUPER BARATÃO')
print('-' * 40)
while True:
produto = str(input('Nome do Produto: '))
preco = float(input('Preço: '))
cont += 1
total += preco
if preco > 1000:
totmil += 1
... | flexible | {
"blob_id": "35b24ffa14f8b3c2040d5becc8a35721e86d8b3d",
"index": 345,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('-' * 40)\nprint('LOJA SUPER BARATÃO')\nprint('-' * 40)\nwhile True:\n produto = str(input('Nome do Produto: '))\n preco = float(input('Preço: '))\n cont += 1\n total += ... | [
0,
1,
2
] |
<|reserved_special_token_0|>
def main(targetsrting):
email = ''
key = ''
target = base64.b64encode(targetsrting.encode('utf-8')).decode('utf-8')
url = (
'https://fofa.so/api/v1/search/all?email={}&key={}&qbase64={}&fields=host,server,title&size=1000'
.format(email, key, target))
re... | flexible | {
"blob_id": "5f13866bd5c6d20e8ddc112fb1d1335e3fd46c3e",
"index": 1817,
"step-1": "<mask token>\n\n\ndef main(targetsrting):\n email = ''\n key = ''\n target = base64.b64encode(targetsrting.encode('utf-8')).decode('utf-8')\n url = (\n 'https://fofa.so/api/v1/search/all?email={}&key={}&qbase64={... | [
1,
2,
3,
4,
5
] |
import pandas as pd
import numpy as np
#import data
df = pd.read_csv('../.gitignore/PPP_data_to_150k.csv')
counties = pd.read_csv('../data/zip_code_database.csv')
demographics = pd.read_csv('../data/counties.csv')
#filter out all unanswered ethnicities
df2 = df[~df.RaceEthnicity.str.contains("Unanswered")]
#drop non... | normal | {
"blob_id": "732478fd826e09cf304760dfcc30cd077f74d83e",
"index": 2250,
"step-1": "import pandas as pd\nimport numpy as np\n\n#import data\ndf = pd.read_csv('../.gitignore/PPP_data_to_150k.csv')\ncounties = pd.read_csv('../data/zip_code_database.csv')\ndemographics = pd.read_csv('../data/counties.csv')\n\n#filter... | [
0
] |
#!/usr/bin/env python 3
# -*- coding: utf-8 -*-
#
# Copyright (c) 2020 PanXu, Inc. All Rights Reserved
#
"""
测试 label index decoder
Authors: PanXu
Date: 2020/07/05 15:10:00
"""
import pytest
import torch
from easytext.tests import ASSERT
from easytext.data import LabelVocabulary
from easytext.modules import Cond... | normal | {
"blob_id": "f64138ee5a64f09deb72b47b86bd7795acddad4d",
"index": 9980,
"step-1": "<mask token>\n\n\nclass CRFData:\n \"\"\"\n 测试用的 crf 数据\n \"\"\"\n\n def __init__(self):\n bio_labels = [['O', 'I-X', 'B-X', 'I-Y', 'B-Y']]\n self.label_vocabulary = LabelVocabulary(labels=bio_labels, padd... | [
3,
5,
6,
7,
8
] |
default_app_config = 'teacher.apps.A1Config'
| normal | {
"blob_id": "c466c7e05608b1fbba5eea5bec16d301cee3688f",
"index": 9817,
"step-1": "<mask token>\n",
"step-2": "default_app_config = 'teacher.apps.A1Config'\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
<|reserved_special_token_0|>
def date_handler(obj):
return obj.isoformat() if hasattr(obj, 'isoformat') else obj
def run():
parser = argparse.ArgumentParser(description='Process some integers.')
parser.add_argument('--input-base', required=True, help='')
parser.add_argument('--output-base', default=... | flexible | {
"blob_id": "2c22f891f30825bcb97987c78a98988ad2a92210",
"index": 385,
"step-1": "<mask token>\n\n\ndef date_handler(obj):\n return obj.isoformat() if hasattr(obj, 'isoformat') else obj\n\n\ndef run():\n parser = argparse.ArgumentParser(description='Process some integers.')\n parser.add_argument('--input... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def get_sgd_optimizer(args, model):
opimizer = torch.optim.SGD(model.parameters(), lr=args.lr, weight_decay
=0.0001)
return opimizer
<|reserved_special_token_1|>
<|reserved_special_token_0|>
import torch
def... | flexible | {
"blob_id": "5dca187cfe221f31189ca9a9309ece4b9144ac66",
"index": 2812,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_sgd_optimizer(args, model):\n opimizer = torch.optim.SGD(model.parameters(), lr=args.lr, weight_decay\n =0.0001)\n return opimizer\n",
"step-3": "<mask token>\n... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class SpecValidator:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class SpecValidator:
def __init__(self, type=None, default=None, choices=[]... | flexible | {
"blob_id": "4db93bdab2d73e7226dcad61827f5faea8513767",
"index": 9888,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass SpecValidator:\n <mask token>\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\nclass SpecValidator:\n\n def __init__(self, type=None, default=None, choices=[], min=Non... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def test_lazymap():
data = list(range(10))
lm = LazyMap(data, lambda x: 2 * x)
assert len(lm) == 10
assert lm[1] == 2
assert isinstance(lm[1:4], LazyMap)
assert lm.append == data.append
assert repr(lm... | flexible | {
"blob_id": "3e7d80fdd1adb570934e4b252bc25d5746b4c68e",
"index": 3912,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef test_lazymap():\n data = list(range(10))\n lm = LazyMap(data, lambda x: 2 * x)\n assert len(lm) == 10\n assert lm[1] == 2\n assert isinstance(lm[1:4], LazyMap)\n ... | [
0,
1,
2,
3
] |
print('SYL_2整型数组_12 合并排序数组')
| normal | {
"blob_id": "571636be9d213d19bddfd1d04688bc0955c9eae5",
"index": 4427,
"step-1": "<mask token>\n",
"step-2": "print('SYL_2整型数组_12 合并排序数组')\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
from eventnotipy import app
import json
json_data = open('eventnotipy/config.json')
data = json.load(json_data)
json_data.close()
username = data['dbuser']
password = data['password']
host = data['dbhost']
db_name = data['database']
email_host = data['email_host']
email_localhost = data['email_localhost']
sms_host = da... | normal | {
"blob_id": "1f0680c45afb36439c56a1d202537261df5f9afc",
"index": 5895,
"step-1": "<mask token>\n",
"step-2": "<mask token>\njson_data.close()\n<mask token>\n",
"step-3": "<mask token>\njson_data = open('eventnotipy/config.json')\ndata = json.load(json_data)\njson_data.close()\nusername = data['dbuser']\npass... | [
0,
1,
2,
3
] |
from setuptools import setup
from os import path
this_directory = path.abspath(path.dirname(__file__))
with open(path.join(this_directory, 'README.md'), encoding='utf-8') as f:
long_description = f.read()
setup(
name='SumoSound',
packages=['SumoSound'],
version='1.0.2',
license='MIT',
description='A pyt... | normal | {
"blob_id": "81c9cabaa611f8e884708d535f0b99ff83ec1c0d",
"index": 8319,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open(path.join(this_directory, 'README.md'), encoding='utf-8') as f:\n long_description = f.read()\nsetup(name='SumoSound', packages=['SumoSound'], version='1.0.2', license=\n ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
l1: list = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
print('The original list: ', l1)
<|reserved_special_token_0|>
while i < len(l1):
l1[i] = l1[i] + 100
i = i + 1
print('The modified new list is: ', l1)
<|reserved_special_token_0|>... | flexible | {
"blob_id": "6a3fd3323ed8792853afdf5af76161f3e20d4896",
"index": 4443,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nl1: list = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]\nprint('The original list: ', l1)\n<mask token>\nwhile i < len(l1):\n l1[i] = l1[i] + 100\n i = i + 1\nprint('The modified new list is: ',... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def calc_common_prefix_length(lhs_iterable, rhs_iterable, /, *, __eq__=None):
if __eq__ is None:
__eq__ = operator.__eq__
idx = -1
for a, b, idx in zip(lhs_iterable, rhs_iterable, itertools.count(0)):
if not __eq__(a, b):
return idx
else:
... | flexible | {
"blob_id": "2b73c4e07bba7ed5c89a31ebd45655eaa85dcdcc",
"index": 2689,
"step-1": "<mask token>\n\n\ndef calc_common_prefix_length(lhs_iterable, rhs_iterable, /, *, __eq__=None):\n if __eq__ is None:\n __eq__ = operator.__eq__\n idx = -1\n for a, b, idx in zip(lhs_iterable, rhs_iterable, itertools... | [
1,
2,
3,
4,
5
] |
#!/usr/bin/python
# -*- coding: latin-1 -*-
from flask import Flask, render_template
app = Flask(__name__)
@app.route('/')
def index():
return render_template('index.html', titre="Ludovic DELSOL - Portfolio")
@app.route('/etude')
def etude():
return render_template('etude.html', titre="Portfolio Ludovic DEL... | normal | {
"blob_id": "c7037b6a576374f211580b304f8447349bbbbea3",
"index": 9583,
"step-1": "<mask token>\n\n\n@app.route('/etude')\ndef etude():\n return render_template('etude.html', titre=\n 'Portfolio Ludovic DELSOL - Etude')\n\n\n@app.route('/experience')\ndef experience():\n return render_template('exper... | [
4,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def scoring(msg, space, score_func, min_score=0.5, **score_func_params):
""" Run the score function over the given message and over a parametric
value x. Return all the values x as a FuzzySet (guess)
which sc... | flexible | {
"blob_id": "99048ddb3f42382c8b8b435d832a45011a031cf1",
"index": 8537,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef scoring(msg, space, score_func, min_score=0.5, **score_func_params):\n \"\"\" Run the score function over the given message and over a parametric\n value x. Return all t... | [
0,
1,
2,
3
] |
#!/usr/bin/python3
"""Locked class module"""
class LockedClass:
"""test class with locked dynamic attruibute creation
"""
__slots__ = 'first_name'
| normal | {
"blob_id": "d90a4b00d97cecf3612915a72e48a363c5dcc97b",
"index": 5006,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass LockedClass:\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass LockedClass:\n <mask token>\n __slots__ = 'first_name'\n",
"step-4": "<mask tok... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def downgrade():
op.drop_constraint(None, 'user', type_='unique')
op.drop_constraint(None, 'user', type_='unique')
op.drop_column('user', 'money')
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def upgrade():
op.add_column('user', sa.Column('money', sa.Inte... | flexible | {
"blob_id": "f727c0551f20fb0dc72b4d81b7b3ed8ce9b1b6f4",
"index": 2072,
"step-1": "<mask token>\n\n\ndef downgrade():\n op.drop_constraint(None, 'user', type_='unique')\n op.drop_constraint(None, 'user', type_='unique')\n op.drop_column('user', 'money')\n",
"step-2": "<mask token>\n\n\ndef upgrade():\n... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
while currentWeight > goalWeight:
endDate += datetime.timedelta(days=7)
currentWeight -= avgKgPerWeek
print(endDate, round(currentWeight, 2))
print(f'Start date: {startDate.month.no}, end date: {endDate} ')
print(
... | flexible | {
"blob_id": "7fb568880c40895870a0c541d9a88a8070a79e5b",
"index": 5762,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile currentWeight > goalWeight:\n endDate += datetime.timedelta(days=7)\n currentWeight -= avgKgPerWeek\n print(endDate, round(currentWeight, 2))\nprint(f'Start date: {startDat... | [
0,
1,
2,
3,
4
] |
from django.contrib import admin
from .models import Predictions
@admin.register(Predictions)
class PredictionsAdmin(admin.ModelAdmin):
pass
| normal | {
"blob_id": "bab78e8a88f9a26cc13fe0c301f82880cee2b680",
"index": 965,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@admin.register(Predictions)\nclass PredictionsAdmin(admin.ModelAdmin):\n pass\n",
"step-3": "from django.contrib import admin\nfrom .models import Predictions\n\n\n@admin.registe... | [
0,
1,
2
] |
import time, json, glob, os, enum
import serial
import threading
import responder
# 環境によって書き換える変数
isMCUConnected = True # マイコンがUSBポートに接続されているか
SERIALPATH_RASPI = '/dev/ttyACM0' # ラズパイのシリアルポート
SERIALPATH_WIN = 'COM16' # Windowsのシリアルポート
# 各種定数
PIN_SERVO1 = 12 # GPIO12 PWM0 Pin
PIN_SERVO2 = 13 # GP... | normal | {
"blob_id": "25532102cc36da139a22a61d226dff613f06ab31",
"index": 4714,
"step-1": "<mask token>\n\n\nclass Meters:\n <mask token>\n\n def indicate(self, kmh=None, amp=None, led=None):\n if self.pi:\n if kmh != None:\n kmh = SPEED_MAX if kmh > SPEED_MAX else kmh\n ... | [
8,
11,
12,
13,
14
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
with open(file_name, 'r') as f:
stop = 1
while stop != 0:
line = f.readline()
if len(line) < 1:
break
tot += float(line)
print(tot)
<|reserved_special_token_1|>
file_name = '013_large... | flexible | {
"blob_id": "bcdf1c03d996520f3d4d8d12ec4ef34ea63ef3cf",
"index": 3936,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open(file_name, 'r') as f:\n stop = 1\n while stop != 0:\n line = f.readline()\n if len(line) < 1:\n break\n tot += float(line)\nprint(tot)\n",
... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class LoginPage(BasePage, LoginPageLocators):
def __init__(self, driver=None):
super(LoginPage, self).__init__(driver=driver)
self.identifier = self.IDENTIFIER
<|reserved_special_token_0|>
def get_error_messages(self):
invalid_user = self.get_text(sel... | flexible | {
"blob_id": "c1bcce809aa073ecd6e64dfa65ead9bd48aee3ff",
"index": 7406,
"step-1": "<mask token>\n\n\nclass LoginPage(BasePage, LoginPageLocators):\n\n def __init__(self, driver=None):\n super(LoginPage, self).__init__(driver=driver)\n self.identifier = self.IDENTIFIER\n <mask token>\n\n def... | [
3,
4,
5,
6
] |
import asyncio
import secrets
import pytest
from libp2p.host.ping import ID, PING_LENGTH
from libp2p.tools.factories import pair_of_connected_hosts
@pytest.mark.asyncio
async def test_ping_once():
async with pair_of_connected_hosts() as (host_a, host_b):
stream = await host_b.new_stream(host_a.get_id(),... | normal | {
"blob_id": "0233b46da3b9351f110ffc7f8622ca8f9ee9944d",
"index": 3000,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@pytest.mark.asyncio\nasync def test_ping_once():\n async with pair_of_connected_hosts() as (host_a, host_b):\n stream = await host_b.new_stream(host_a.get_id(), (ID,))\n ... | [
0,
1,
2,
3,
4
] |
ss = str(input())
print(len(ss) - ss.count(' '))
| normal | {
"blob_id": "7f72f6a2ff0c7ceacb0f893d04c20402e850421a",
"index": 1840,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(len(ss) - ss.count(' '))\n",
"step-3": "ss = str(input())\nprint(len(ss) - ss.count(' '))\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
} | [
0,
1,
2
] |
import datetime
import logging
from typing import TYPE_CHECKING, Any, Dict, List, NamedTuple, Optional
from dagster import check
from dagster.core.utils import coerce_valid_log_level, make_new_run_id
if TYPE_CHECKING:
from dagster.core.events import DagsterEvent
DAGSTER_META_KEY = "dagster_meta"
class DagsterM... | normal | {
"blob_id": "f900e08c06ae736f5e32ac748e282700f9d0a969",
"index": 7922,
"step-1": "<mask token>\n\n\nclass DagsterMessageProps(NamedTuple('_DagsterMessageProps', [(\n 'orig_message', Optional[str]), ('log_message_id', Optional[str]), (\n 'log_timestamp', Optional[str]), ('dagster_event', Optional[Any])])):\... | [
16,
18,
21,
22,
25
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def build_shift_dict(self, shift):
"""
Creates a dictionary that can be used to apply a cipher to a letter.
The dictionary maps every uppercase and lowercase letter to a
character shifted down the alphabet by the input shift. The dictionary
... | flexible | {
"blob_id": "07d2da14d0122ad2c8407bb13b8567ca62356bef",
"index": 7515,
"step-1": "<mask token>\n",
"step-2": "def build_shift_dict(self, shift):\n \"\"\"\n Creates a dictionary that can be used to apply a cipher to a letter.\n The dictionary maps every uppercase and lowercase letter to a\n characte... | [
0,
1,
2
] |
<|reserved_special_token_0|>
@api_view(['POST'])
@permission_classes((IsAuthenticated,))
def create_account_genre_view(request):
title = request.data.get('title', '0')
try:
genre = Genre.objects.get(title=title)
except Genre.DoesNotExist:
return Response(status=status.HTTP_404_NOT_FOUND)
... | flexible | {
"blob_id": "ff53a549222b0d5e2fcb518c1e44b656c45ce76e",
"index": 5183,
"step-1": "<mask token>\n\n\n@api_view(['POST'])\n@permission_classes((IsAuthenticated,))\ndef create_account_genre_view(request):\n title = request.data.get('title', '0')\n try:\n genre = Genre.objects.get(title=title)\n exce... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
flow_data.registerTempTable('flowtab')
<|reserved_special_token_0|>
df.show(1000)
<|reserved_special_token_0|>
df.show(1000)
<|reserved_special_token_0|>
for dstip in dstIPs:
sql = (
"select src_address, dst_address, s... | flexible | {
"blob_id": "691075aa5c629e2d0c486ec288cd39bc142cdc7a",
"index": 3448,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nflow_data.registerTempTable('flowtab')\n<mask token>\ndf.show(1000)\n<mask token>\ndf.show(1000)\n<mask token>\nfor dstip in dstIPs:\n sql = (\n \"select src_address, dst_addres... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def datingClassTest():
horatio = 0.1
data, datalabels = KNN_1.filel2matrix('datingTestSet2.txt')
normMat = KNN_3.autoNorm(data)
ml = normMat.shape[0]
numTestset = int(ml * horatio)
errorcount = 0
a = ... | flexible | {
"blob_id": "3086f62d4057812fc7fb4e21a18bc7d0ba786865",
"index": 2526,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef datingClassTest():\n horatio = 0.1\n data, datalabels = KNN_1.filel2matrix('datingTestSet2.txt')\n normMat = KNN_3.autoNorm(data)\n ml = normMat.shape[0]\n numTests... | [
0,
2,
3,
4,
5
] |
"""These are views that are used for viewing and editing characters."""
from django.contrib import messages
from django.contrib.auth.mixins import UserPassesTestMixin,\
LoginRequiredMixin, PermissionRequiredMixin
from django.db import transaction
from django.db.models import F
from django.http import HttpResponseR... | normal | {
"blob_id": "55ea522b096b189ff67b0da0058af777b0a910e3",
"index": 4970,
"step-1": "<mask token>\n\n\nclass CharacterDropHeaderView(APIView):\n \"\"\"\n Set of AJAX views for a Characters\n\n This handles different API calls for character actions.\n \"\"\"\n authentication_classes = [SessionAuthenti... | [
33,
48,
59,
68,
81
] |
<|reserved_special_token_0|>
class TestTNSWatcher:
<|reserved_special_token_0|>
@pytest.mark.xfail(raises=pandas.errors.ParserError)
def test_tns_watcher(self):
log('Connecting to DB')
mongo = Mongo(host=config['database']['host'], port=config[
'database']['port'], replica_set... | flexible | {
"blob_id": "e7ffa852d16e8e55b4e2b6ab2383561fe359a169",
"index": 1778,
"step-1": "<mask token>\n\n\nclass TestTNSWatcher:\n <mask token>\n\n @pytest.mark.xfail(raises=pandas.errors.ParserError)\n def test_tns_watcher(self):\n log('Connecting to DB')\n mongo = Mongo(host=config['database'][... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
options.register('file', '', VarParsing.VarParsing.multiplicity.singleton,
VarParsing.VarParsing.varType.string, 'File path for storing output')
options.parseArguments()
<|reserved_special_token_0|>
process.load('FWCore.Messag... | flexible | {
"blob_id": "6aff61ce5cef537e6b1b19e382d8bf80e3a61693",
"index": 1423,
"step-1": "<mask token>\n",
"step-2": "<mask token>\noptions.register('file', '', VarParsing.VarParsing.multiplicity.singleton,\n VarParsing.VarParsing.varType.string, 'File path for storing output')\noptions.parseArguments()\n<mask toke... | [
0,
1,
2,
3,
4
] |
class Graph:
def __init__(self, num_vertices):
self.adj_list = {}
for i in range(num_vertices):
self.adj_list[i] = []
def add_vertice(self, source):
self.adj_list[source] = []
def add_edge(self, source, dest):
self.adj_list[source].append(dest)
<|reserved_s... | flexible | {
"blob_id": "ae5ec7919b9de4fbf578547c31837add32826f60",
"index": 7448,
"step-1": "class Graph:\n\n def __init__(self, num_vertices):\n self.adj_list = {}\n for i in range(num_vertices):\n self.adj_list[i] = []\n\n def add_vertice(self, source):\n self.adj_list[source] = []\n... | [
5,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if __name__ == '__main__':
SERVICE = MediathekViewService()
SERVICE.init()
SERVICE.run()
SERVICE.exit()
del SERVICE
<|reserved_special_token_1|>
<|reserved_special_token_0|>
from resources.lib.service import... | flexible | {
"blob_id": "e769e930ab8f0356116679bc38a09b83886eb8f6",
"index": 4003,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n SERVICE = MediathekViewService()\n SERVICE.init()\n SERVICE.run()\n SERVICE.exit()\n del SERVICE\n",
"step-3": "<mask token>\nfrom resources.... | [
0,
1,
2,
3
] |
# coding=utf-8
import sys
if len(sys.argv) == 2:
filepath = sys.argv[1]
pRead = open(filepath,'r')#wordlist.txt
pWrite = open("..\\pro\\hmmsdef.mmf",'w')
time = 0
for line in pRead:
if line != '\n':
line = line[0: len(line) - 1] #去除最后的\n
if line == "sil ":
... | normal | {
"blob_id": "9bd6da909baeb859153e3833f0f43d8cbcb66200",
"index": 9324,
"step-1": "# coding=utf-8\nimport sys\nif len(sys.argv) == 2:\n filepath = sys.argv[1]\n pRead = open(filepath,'r')#wordlist.txt\n pWrite = open(\"..\\\\pro\\\\hmmsdef.mmf\",'w')\n time = 0\n for line in pRead:\n if line... | [
0
] |
<|reserved_special_token_0|>
def start(caller):
if not caller:
return
caller.ndb._menutree.points = {'attributes': 20, 'skills': 20}
caller.ndb._menutree.character = {'home_planet': None, 'full_name':
None, 'origin': None, 'stats': {}, 'age': 16, 'is_psionic': False,
'current_term'... | flexible | {
"blob_id": "99eeb039e1a369e450247d10ba22a1aa0b35dae9",
"index": 6875,
"step-1": "<mask token>\n\n\ndef start(caller):\n if not caller:\n return\n caller.ndb._menutree.points = {'attributes': 20, 'skills': 20}\n caller.ndb._menutree.character = {'home_planet': None, 'full_name':\n None, 'o... | [
14,
15,
19,
22,
27
] |
<|reserved_special_token_0|>
class SerialTester:
def write(self, line):
print(line)
def read(self, num):
return
class Antenna:
azimuth = initial_az
altitude = initial_alt
parked = True
def set_position(self, az, alt):
self.azimuth = az
self.altitude = alt
... | flexible | {
"blob_id": "468b5bd8d7b045ca8dd46c76a1829fc499e16950",
"index": 5756,
"step-1": "<mask token>\n\n\nclass SerialTester:\n\n def write(self, line):\n print(line)\n\n def read(self, num):\n return\n\n\nclass Antenna:\n azimuth = initial_az\n altitude = initial_alt\n parked = True\n\n ... | [
15,
18,
21,
25,
26
] |
import strawberry as stb
from app.crud import cruduser
from app.db import get_session
@stb.type
class Query:
@stb.field
async def ReadUser(self, info, username: str):
ses = await get_session()
fields = info.field_nodes[0].selection_set.selections[0]
return await cruduser.get_user(ses,... | normal | {
"blob_id": "0992297ffc19b1bc4dc3d5e8a75307009c837032",
"index": 5134,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@stb.type\nclass Query:\n\n @stb.field\n async def ReadUser(self, info, username: str):\n ses = await get_session()\n fields = info.field_nodes[0].selection_set.se... | [
0,
1,
2
] |
"""
commands/map.py
description:
Generates a blank configuration file in the current directory
"""
from json import dumps
from .base_command import BaseCommand
class Map(BaseCommand):
def run(self):
from lib.models import Mapping
from lib.models import Migration
migration = Migration.load(self.options['MI... | normal | {
"blob_id": "07783921da2fb4ae9452324f833b08b3f92ba294",
"index": 546,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Map(BaseCommand):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Map(BaseCommand):\n\n def run(self):\n from lib.models import Mapping\n from lib.mod... | [
0,
1,
2,
3,
4
] |
from django.contrib.auth import authenticate, login, logout
from django.template import loader
from django.http import (HttpResponse, JsonResponse,
HttpResponseForbidden, HttpResponseBadRequest)
from django.shortcuts import redirect
from django.views.decorators.http import require_POST
import ... | normal | {
"blob_id": "41ca762fe6865613ae4ef2f657f86b516353676f",
"index": 9784,
"step-1": "<mask token>\n\n\ndef index(request, err_msg=None):\n \"\"\"\n Renders the index page.\n \"\"\"\n template = loader.get_template('aimodel/index.html')\n context = {}\n context['err_msg'] = err_msg\n return Http... | [
13,
16,
17,
19,
22
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.... | flexible | {
"blob_id": "a718d82713503c4ce3d94225ff0db04991ad4094",
"index": 9744,
"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|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print('number of lines :' + str(len(read)))
while i <= len(read) - 1:
counter = counter + read[i].count('\n') + read[i].count(' ')
total += len(read[i]) - read[i].count('\n') - read[i].count(' ')
i += 1
counter += 1
pr... | flexible | {
"blob_id": "5ad8db85f4f705173cf5d0649af6039ebe1544b2",
"index": 7488,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('number of lines :' + str(len(read)))\nwhile i <= len(read) - 1:\n counter = counter + read[i].count('\\n') + read[i].count(' ')\n total += len(read[i]) - read[i].count('\\n')... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class TestIsBalanced(unittest.TestCase):
def test_is_balanced(self):
self.assertEquals(descending_order(0), 0)
self.assertEquals(descending_order(15), 51)
self.assertEquals(descending_order(123456789), 987654321)
self.assertEquals(descending_order(1201... | flexible | {
"blob_id": "fc5d0dd16b87ab073bf4b054bd2641bdec88e019",
"index": 6594,
"step-1": "<mask token>\n\n\nclass TestIsBalanced(unittest.TestCase):\n\n def test_is_balanced(self):\n self.assertEquals(descending_order(0), 0)\n self.assertEquals(descending_order(15), 51)\n self.assertEquals(descen... | [
2,
3,
4,
5
] |
#!/usr/bin/env python3
import operator
from functools import reduce
import music21
def get_top_line(piece):
top_part = piece.parts[0]
if len(top_part.voices) > 0:
top_part = top_part.voices[0]
# replace all chords with top note of chord
for item in top_part.notes:
if isinstance(item... | normal | {
"blob_id": "92ee66565eb1d0e3cd8fa1ec16747f15e0d92be8",
"index": 2885,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_notes(piece):\n part = piece.parts[0]\n measures = filter(lambda x: isinstance(x, music21.stream.Measure), part\n .elements)\n notes = reduce(operator.add, map... | [
0,
1,
2,
3,
4
] |
from flask import request, Flask
import ldap3
app = Flask(__name__)
@app.route("/normal")
def normal():
"""
A RemoteFlowSource is used directly as DN and search filter
"""
unsafe_dc = request.args['dc']
unsafe_filter = request.args['username']
dn = "dc={}".format(unsafe_dc)
search_filte... | normal | {
"blob_id": "b51591de921f6e153c1dd478cec7fad42ff4251a",
"index": 749,
"step-1": "<mask token>\n\n\n@app.route('/direct')\ndef direct():\n \"\"\"\n A RemoteFlowSource is used directly as DN and search filter using a oneline call to .search\n \"\"\"\n unsafe_dc = request.args['dc']\n unsafe_filter =... | [
1,
2,
3,
4,
5
] |
# -*- coding: utf-8 -*-
"""
CST 383, measles simulation homework
# Here's a question. Suppose 1% of people have measles, that the
# test for measles if 98% accurate if you do have measles, and 98%
# accurate if you don't have measles. Then what is the probability
# that you have measles, given that you have... | normal | {
"blob_id": "076d9f0c14a8070993039bbda2ffe4d52c8d2273",
"index": 1512,
"step-1": "<mask token>\n\n\ndef t200():\n return np.random.choice(2, 200, p=[0.1, 0.9])\n\n\n<mask token>\n\n\ndef t1000():\n return np.random.choice(2, 1000, p=[0.1, 0.9])\n\n\n<mask token>\n\n\ndef prob_cond_given_pos(prob_cond, prob... | [
4,
6,
7,
8,
9
] |
class Node:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Node:
def __init__(self, val):
self.childleft = None
self.childright = None
self.nodedata = val
<|reserved_special_token_0|>
def trying():
if message == 'root':
... | flexible | {
"blob_id": "73e4346007acae769b94a55ef53a48a9d3325002",
"index": 7262,
"step-1": "class Node:\n <mask token>\n\n\n<mask token>\n",
"step-2": "class Node:\n\n def __init__(self, val):\n self.childleft = None\n self.childright = None\n self.nodedata = val\n\n\n<mask token>\n\n\ndef try... | [
1,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
class TestMicrophone:
<|reserved_special_token_0|>
def test_config(self):
required_config = ['card_number', 'device_index', 'sample_rate',
'phrase_time_limit', 'energy_threshold']
for config_key in required_config:
assert config_key in self... | flexible | {
"blob_id": "164167590051fac3f3fd80c5ed82621ba55c4cc4",
"index": 9597,
"step-1": "<mask token>\n\n\nclass TestMicrophone:\n <mask token>\n\n def test_config(self):\n required_config = ['card_number', 'device_index', 'sample_rate',\n 'phrase_time_limit', 'energy_threshold']\n for co... | [
3,
4,
5,
6,
7
] |
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