code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
from flask import Flask, render_template, request
from distance import get_distance
app = Flask(__name__)
@app.route('/hello')
@app.route('/hello/<name>')
def hello(name=None):
name = "World" if not name else name
return "Hello %s" % name
@app.route('/')
def index():
return render_template('index.html'... | normal | {
"blob_id": "05052e9ccbd076e71e9ec6148887ce7b82ed316d",
"index": 6256,
"step-1": "<mask token>\n\n\n@app.route('/hello')\n@app.route('/hello/<name>')\ndef hello(name=None):\n name = 'World' if not name else name\n return 'Hello %s' % name\n\n\n@app.route('/')\ndef index():\n return render_template('inde... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
class Solution:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Solution:
def uniquePaths(self, m: int, n: int) ->int:
map_: List[List[int]] = [[(0 if i > 0 and j > 0 else 1) for j in
... | flexible | {
"blob_id": "e2a38d38d2ab750cf775ed0fbdb56bc6fc7300c4",
"index": 8934,
"step-1": "<mask token>\n\n\nclass Solution:\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass Solution:\n\n def uniquePaths(self, m: int, n: int) ->int:\n map_: List[List[int]] = [[(0 if i > 0 and j > 0 e... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def main():
A1, A2, A3 = map(int, input().split())
A = A1 + A2 + A3
if A >= 22:
ans = 'bust'
else:
ans = 'win'
print(ans)
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def main():
A1, A2, A3 = map(int, ... | flexible | {
"blob_id": "753e062940e0580d7d33c88c1165977142dcd202",
"index": 8060,
"step-1": "<mask token>\n",
"step-2": "def main():\n A1, A2, A3 = map(int, input().split())\n A = A1 + A2 + A3\n if A >= 22:\n ans = 'bust'\n else:\n ans = 'win'\n print(ans)\n\n\n<mask token>\n",
"step-3": "d... | [
0,
1,
2,
3
] |
import numpy as np
import matplotlib.pyplot as plt
import math
filename = '/home/kolan/mycode/python/dektak/data/t10_1_1_normal.csv'
#filename = '/home/kolan/mycode/python/dektak/t10_1_3_normal.csv'
#filename = '/home/kolan/mycode/python/dektak/t10_1_6_normal.csv'
#filename = '/home/kolan/mycode/python/dektak/t10_1_7... | normal | {
"blob_id": "139d06497a44031f6414980ad54454477e3d0b2c",
"index": 4540,
"step-1": "import numpy as np \nimport matplotlib.pyplot as plt\nimport math\n\nfilename = '/home/kolan/mycode/python/dektak/data/t10_1_1_normal.csv'\n#filename = '/home/kolan/mycode/python/dektak/t10_1_3_normal.csv'\n#filename = '/home/kolan... | [
0
] |
<|reserved_special_token_0|>
def decode(value):
out_value = ''
char = [value[i:i + 2] for i in range(0, len(value), 2)]
for i in range(0, len(char)):
out_value += decoded[encoded.index(char[i])]
return out_value
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_... | flexible | {
"blob_id": "23236cd8262eb414666db88215c01d973abf1d97",
"index": 1247,
"step-1": "<mask token>\n\n\ndef decode(value):\n out_value = ''\n char = [value[i:i + 2] for i in range(0, len(value), 2)]\n for i in range(0, len(char)):\n out_value += decoded[encoded.index(char[i])]\n return out_value\n... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
def exercise_gen(ret_val, times):
"""Return `ret_value` `times` times.
If generator will receive some value from outside, update `ret_value`"""
def exercise1():
"""Make it pass"""
g1 = exercise_gen(42, 3)
assert next(g1) == 42
assert g1.send('new val') == 'new va... | flexible | {
"blob_id": "e5979aeb7cff0e2a75966924382bae87aebcfcb2",
"index": 3312,
"step-1": "<mask token>\n\n\ndef exercise_gen(ret_val, times):\n \"\"\"Return `ret_value` `times` times.\n If generator will receive some value from outside, update `ret_value`\"\"\"\n\n\ndef exercise1():\n \"\"\"Make it pass\"\"\"\n... | [
2,
4,
6,
9,
10
] |
from random import randrange
import random
"""
both user and computer funcs:
"""
def check_ok(boat, taken_positions):
# input: boat, taken_positions
# this func checks if the boat outside the playground or the position of the boat is already in taken_position
# return: boat. boat will returned as [-1] or its... | normal | {
"blob_id": "95584dfdb232be7f507dc9d29ed2f1d95fa2b653",
"index": 9642,
"step-1": "<mask token>\n\n\ndef check_ok(boat, taken_positions):\n boat.sort()\n for i in range(len(boat)):\n if boat[i] in taken_positions:\n boat = [-1]\n break\n elif boat[i] > 99 or boat[i] < 0:\... | [
7,
10,
11,
12,
16
] |
import os
import requests
import sqlite3
from models import analytics, jcanalytics
def populate():
url = 'https://api.clicky.com/api/stats/4?site_id=100716069&sitekey=93c104e29de28bd9&type=visitors-list'
date = '&date=last-30-days'
limit = '&limit=all'
output = '&output=json'
total = url+date+limi... | normal | {
"blob_id": "e8226ab6be5c21335d843cba720e66646a2dee4e",
"index": 241,
"step-1": "import os\nimport requests\nimport sqlite3\nfrom models import analytics, jcanalytics\n\n\ndef populate():\n url = 'https://api.clicky.com/api/stats/4?site_id=100716069&sitekey=93c104e29de28bd9&type=visitors-list'\n date = '&d... | [
0
] |
from pet import Pet
class Ninja:
def __init__(self, first_name, last_name, treats, pet_food, pet):
self.first_name = first_name
self.last_name = last_name
self.treats = treats
self.pet_food = pet_food
self.pet = pet
def walk(self):
self.pet.play()
def fe... | normal | {
"blob_id": "b210784a198eaa3e57b5a65ec182a746aecc0e2b",
"index": 1695,
"step-1": "<mask token>\n\n\nclass Ninja:\n\n def __init__(self, first_name, last_name, treats, pet_food, pet):\n self.first_name = first_name\n self.last_name = last_name\n self.treats = treats\n self.pet_food ... | [
3,
5,
6,
7,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def K_Wilson(w, Tr, Pr):
import numpy as np
K_value_Output = 1 / Pr * np.exp(5.37 * (1 + w) * (1 - 1 / Tr))
return K_value_Output
<|reserved_special_token_1|>
def K_Wilson(w, Tr, Pr):
# Inserting necessary libraries
import numpy... | flexible | {
"blob_id": "0b42f458097d11d66160bcb8e706ccb9b5c4682a",
"index": 5744,
"step-1": "<mask token>\n",
"step-2": "def K_Wilson(w, Tr, Pr):\n import numpy as np\n K_value_Output = 1 / Pr * np.exp(5.37 * (1 + w) * (1 - 1 / Tr))\n return K_value_Output\n",
"step-3": "def K_Wilson(w, Tr, Pr):\r\n \r\n ... | [
0,
1,
2
] |
import sys
import math
def get_max_sum(arr):
max_sum = -math.inf
for i in range(1, 5):
for j in range(1, 5):
temp = arr[i][j] + arr[i - 1][j - 1] + arr[i - 1][j] + arr[i - 1][
j + 1] + arr[i + 1][j + 1] + arr[i + 1][j] + arr[i + 1][j - 1]
max_sum = max(max_sum, ... | normal | {
"blob_id": "c99f1333c5ca3221e9932d9a9ba1d95a77924f0d",
"index": 351,
"step-1": "<mask token>\n\n\ndef get_max_sum(arr):\n max_sum = -math.inf\n for i in range(1, 5):\n for j in range(1, 5):\n temp = arr[i][j] + arr[i - 1][j - 1] + arr[i - 1][j] + arr[i - 1][\n j + 1] + arr... | [
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class BaseMyAdminView(object):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class GlobalSettings(object):
"""
site_title 左上角名称
site_footer 底部名称
menu_style 更改左边样式
"""
site_title = '学习网后台管理系统'
site_footer = ... | flexible | {
"blob_id": "d7b830890400203ee45c9ec59611c0b20ab6bfc7",
"index": 8496,
"step-1": "<mask token>\n\n\nclass BaseMyAdminView(object):\n <mask token>\n <mask token>\n <mask token>\n\n\nclass GlobalSettings(object):\n \"\"\"\n site_title 左上角名称\n site_footer 底部名称\n menu_style 更改左边样式\n \"\"\"\n ... | [
8,
10,
11,
12,
13
] |
<|reserved_special_token_0|>
def main(lista, getnum):
password = ''
for i in range(0, getnum):
passchar = random.choice(lista)
password = password + passchar
print(password)
passwordagain()
def passwordagain():
again = input('Do you want to generate another password(y/n)?: ')
... | flexible | {
"blob_id": "c40bb410ad68808c2e0cc636820ec6a2ec2739b8",
"index": 4053,
"step-1": "<mask token>\n\n\ndef main(lista, getnum):\n password = ''\n for i in range(0, getnum):\n passchar = random.choice(lista)\n password = password + passchar\n print(password)\n passwordagain()\n\n\ndef passw... | [
2,
3,
4,
5,
6
] |
#!/usr/bin/env python
# coding: utf-8
# In[1]:
import pandas as pd
import numpy as np
import seaborn as sb
import matplotlib as mp
data = pd.read_csv("/Users/stevenbaez/Desktop/train.csv")
# In[2]:
data.head()
# In[3]:
subset = data[['Survived','Age', 'Sex']]
# In[5]:
import numpy as np
import matplotli... | normal | {
"blob_id": "41006ff35299aa72b69c6dc1c71a45b44dca7d6c",
"index": 1184,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ndata.head()\n<mask token>\nsb.catplot(x='Age', y='Sex', hue='Survived', col='Embarked', notch=False,\n palette='Set2', data=data, kind='box', height=4, aspect=0.7)\nsb.catplot(x='Age',... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class classifier(nn.Module):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class AT_LSTM(nn.Module):
def __init__(self, embedding_dim, aspect_embedding_dim, hidden_dim,
output_dim, n_layers, embed_weights, at=True, ae=False, dropout=0):
super()._... | flexible | {
"blob_id": "4692b2d19f64b3b4bd10c5eadd22a4b5a2f2ef37",
"index": 3923,
"step-1": "<mask token>\n\n\nclass classifier(nn.Module):\n <mask token>\n <mask token>\n\n\nclass AT_LSTM(nn.Module):\n\n def __init__(self, embedding_dim, aspect_embedding_dim, hidden_dim,\n output_dim, n_layers, embed_weigh... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
s.connect((RHOST, RPORT))
<|reserved_special_token_0|>
shellcode_calc += b'\xba\xd5\x90\xd2}\xdb\xd5\xd9t$'
shellcode_calc += b'\xf4X1\xc9\xb161P\x13\x83'
shellcode_calc += b"\xe8\xfc\x03P\xdar'\x81\x0c\xf0"
shellcode_calc += b'\x... | flexible | {
"blob_id": "280a4e1fb35937bb5a5c604f69337d30a4b956a9",
"index": 6302,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ns.connect((RHOST, RPORT))\n<mask token>\nshellcode_calc += b'\\xba\\xd5\\x90\\xd2}\\xdb\\xd5\\xd9t$'\nshellcode_calc += b'\\xf4X1\\xc9\\xb161P\\x13\\x83'\nshellcode_calc += b\"\\xe8\\xfc\... | [
0,
1,
2,
3,
4
] |
import json
import os
import numpy as np
import pandas as pd
import py4design.py2radiance as py2radiance
import py4design.py3dmodel.calculate as calculate
from py4design import py3dmodel
__author__ = "Jimeno A. Fonseca"
__copyright__ = "Copyright 2017, Architecture and Building Systems - ETH Zurich"
__credits__ = ["J... | normal | {
"blob_id": "164b0afde225119a8fbd4ccfccbbbc3550aa75fe",
"index": 2634,
"step-1": "<mask token>\n\n\ndef create_sensor_input_file(rad, chunk_n):\n sensor_file_path = os.path.join(rad.data_folder_path, 'points_' + str(\n chunk_n) + '.pts')\n sensor_file = open(sensor_file_path, 'w')\n sensor_pts_da... | [
6,
7,
9,
10,
11
] |
<|reserved_special_token_0|>
class ModelBase:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def __init__(self, schema):
self.schema = schema
<|reserved_special_token_0|>
@property
def uid(self):
return self.schema.uid
def refr... | flexible | {
"blob_id": "5917c891d2885f779dc33f189f1a875efbd0c302",
"index": 163,
"step-1": "<mask token>\n\n\nclass ModelBase:\n <mask token>\n <mask token>\n <mask token>\n\n def __init__(self, schema):\n self.schema = schema\n <mask token>\n\n @property\n def uid(self):\n return self.sc... | [
6,
8,
9,
12,
13
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(dic['name'])
<|reserved_special_token_1|>
dic = {'name': 'Eric', 'age': '25'}
print(dic['name'])
<|reserved_special_token_1|>
dic = {'name': 'Eric', 'age': '25'} # 딕셔너리 형태
print(dic['name'])
| flexible | {
"blob_id": "09c3a10230e7d0b3b893ccf236c39fc2dc12b2c6",
"index": 1097,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(dic['name'])\n",
"step-3": "dic = {'name': 'Eric', 'age': '25'}\nprint(dic['name'])\n",
"step-4": "dic = {'name': 'Eric', 'age': '25'} # 딕셔너리 형태\n\n\nprint(dic['name'])\n",
... | [
0,
1,
2,
3
] |
import discord
from discord.ext import commands
from discord.ext.commands import Bot
import asyncio
import random
import requests
import os
#Discord Tech Stuff
BOT_PREFIX = ("!")
client = discord.Client()
client = Bot(command_prefix=BOT_PREFIX)
#Functions of the Funny Coin
@client.command()
async def wasitfunny():... | normal | {
"blob_id": "f047afeb6462ab01a8fea1f3c8693608335eb960",
"index": 3488,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@client.command()\nasync def wasitfunny():\n possible_responses = [\n 'Per the judgement from the committee of comedy, we have decided that the joke was indeed funny'\n ... | [
0,
1,
2,
3,
4
] |
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
from matplotlib.lines import Line2D
np.random.seed(42)
n_samples = 5000
MU = np.array([0.5, 1.5])
COV = np.array([[1., 0.7], [0.7, 2.]])
def get_samples(n):
return np.random.multivariate_normal(me... | normal | {
"blob_id": "d61b04539295f6b25e7f6589d32f313e3c6df82f",
"index": 1180,
"step-1": "<mask token>\n\n\nclass BackgroundCheck(object):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def predict_proba(self, x):\n return self.prob_background(x)\n\n\nclass GaussianEstimation(objec... | [
8,
10,
12,
13,
17
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def ex(x, y):
max = 0
print(x) if x > y else print(y)
return max
| flexible | {
"blob_id": "4ffc00e9425992bdd8277341d67a0739119a4798",
"index": 2773,
"step-1": "<mask token>\n",
"step-2": "def ex(x, y):\n max = 0\n print(x) if x > y else print(y)\n return max\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
<|reserved_special_token_0|>
@api.route('/predict')
@api.expect(parser)
class Predict(Resource):
<|reserved_special_token_0|>
@api.route('/predict/<string:companyid>/<string:accountid>')
@api.expect(parser)
class PredictEmployeeByCompany(Resource):
@api.marshal_with(modelByEmployee)
def get(self, compa... | flexible | {
"blob_id": "c76fd9b196b50e6fcced7e56517c0cd8ab30e24e",
"index": 7891,
"step-1": "<mask token>\n\n\n@api.route('/predict')\n@api.expect(parser)\nclass Predict(Resource):\n <mask token>\n\n\n@api.route('/predict/<string:companyid>/<string:accountid>')\n@api.expect(parser)\nclass PredictEmployeeByCompany(Resour... | [
6,
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10,
15
] |
from Task2.src.EmailInterpreter import EmailInterpreter
import os
# Part B:
# -------
# Write a child-class of the previously written base class, which
# implements the 'split_file' function, simply by treating each line as a
# unit (it returns the list of lines).
class LineBreaker(EmailInterpreter):
def split_file... | normal | {
"blob_id": "1c6077d965f5bc8c03344b53d11851f5cd50bca8",
"index": 3346,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass LineBreaker(EmailInterpreter):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass LineBreaker(EmailInterpreter):\n\n def split_file(self, file_name):\n with op... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def click():
ent_text = ent.get()
lab = Label(root, text=ent_text)
lab.pack()
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
ent.pack()
def click():
ent_text = ent.get()
lab = Label(root, text=ent_text)
lab.pack()
<|... | flexible | {
"blob_id": "49f1b4c9c6d15b8322b83396c22e1027d241da33",
"index": 2311,
"step-1": "<mask token>\n\n\ndef click():\n ent_text = ent.get()\n lab = Label(root, text=ent_text)\n lab.pack()\n\n\n<mask token>\n",
"step-2": "<mask token>\nent.pack()\n\n\ndef click():\n ent_text = ent.get()\n lab = Label... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
def arena_preprocess(frame, M):
processed_arena = cv2.warpPerspective(frame, M, (900, 600))
in_corners = np.array([[10, 18], [10, 590], [890, 590], [890, 15]])
h, w = processed_arena.shape[:2]
result_mask = np.zeros((h, w), np.uint8)
mask = np.zeros((h + 2, w + 2), np.... | flexible | {
"blob_id": "228852f960e9343d9f45abdd3204cfab7bb54bc6",
"index": 8230,
"step-1": "<mask token>\n\n\ndef arena_preprocess(frame, M):\n processed_arena = cv2.warpPerspective(frame, M, (900, 600))\n in_corners = np.array([[10, 18], [10, 590], [890, 590], [890, 15]])\n h, w = processed_arena.shape[:2]\n ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Reader:
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Reader:
def read(self, filePath):
"""
Reads text file with nodes and returns the result dict wi... | flexible | {
"blob_id": "c796123fbbf3adcde59779a104dcafb30a673a79",
"index": 6422,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Reader:\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Reader:\n\n def read(self, filePath):\n \"\"\"\n Reads text file with nodes and returns the resul... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
import logging
from django.db import transaction
from ralph_scrooge.models import ProfitCenter
from ralph_scrooge.plugins import plugin_runner
... | normal | {
"blob_id": "d3f52d4713ba4b7b4cd736b26809968e259be63c",
"index": 6883,
"step-1": "<mask token>\n\n\n@plugin_runner.register(chain='scrooge')\ndef ralph3_profit_center(**kwargs):\n new_pc = total = 0\n for pc in get_from_ralph('profit-centers', logger):\n created = update_profit_center(pc)\n i... | [
1,
2,
3,
4,
5
] |
# --- Do not remove these libs ---
from freqtrade.strategy.interface import IStrategy
from typing import Dict, List
from functools import reduce
from pandas import DataFrame
# --------------------------------
import datetime
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
import numpy... | normal | {
"blob_id": "7b047ba110732d1b0a749bcbbaa9b55306ca2071",
"index": 6434,
"step-1": "<mask token>\n\n\nclass ema(IStrategy):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask ... | [
2,
4,
5,
6,
7
] |
import easyocr
import cv2
import json
import numpy as np
import os
import os.path
import glob
def convert(o):
if isinstance(o, np.generic): return o.item()
raise TypeError
readers = [
easyocr.Reader(['la', 'en', 'de', 'fr', 'es', 'cs', 'is'], gpu = False),
#easyocr.Reader(['ch_tra'], g... | normal | {
"blob_id": "7057b882ca1ce2c08e9ba7add5f115636b9b319e",
"index": 8745,
"step-1": "<mask token>\n\n\ndef convert(o):\n if isinstance(o, np.generic):\n return o.item()\n raise TypeError\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef convert(o):\n if isinstance(o, np.generic):\n ret... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print('Please enter your name:')
<|reserved_special_token_0|>
if user_name in names:
print('Hi there, {}!'.format(user_name))
else:
print('Who goes there?')
<|reserved_special_token_1|>
names = ['Mia', 'Francis', 'Eva']... | flexible | {
"blob_id": "59c33383365d10c108253f7b5a210d40718913a2",
"index": 9653,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('Please enter your name:')\n<mask token>\nif user_name in names:\n print('Hi there, {}!'.format(user_name))\nelse:\n print('Who goes there?')\n",
"step-3": "names = ['Mia', ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if LDB_TOKEN == '':
raise Exception(
'Please configure your OpenLDBWS token in getDepartureBoardExample!')
<|reserved_special_token_0|>
def main(stdscr):
res = client.service.GetDepartureBoard(numRows=10, crs='NA... | flexible | {
"blob_id": "302634b93725ceb9333e236021cbb64e023ff798",
"index": 2135,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif LDB_TOKEN == '':\n raise Exception(\n 'Please configure your OpenLDBWS token in getDepartureBoardExample!')\n<mask token>\n\n\ndef main(stdscr):\n res = client.service.Get... | [
0,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
@app.route('/')
def index():
return render_template('Main_page.html')
@app.route('/prediction.html')
def predict():
return render_template('prediction.html')
@app.route('/About_us.html')
def about_us():
return render_template('About_us.html')
@app.route('/Result1.html', ... | flexible | {
"blob_id": "ccfcc5b644d592090786ceb35a85124c9d3275ad",
"index": 5719,
"step-1": "<mask token>\n\n\n@app.route('/')\ndef index():\n return render_template('Main_page.html')\n\n\n@app.route('/prediction.html')\ndef predict():\n return render_template('prediction.html')\n\n\n@app.route('/About_us.html')\ndef... | [
4,
5,
6,
7,
8
] |
# Tip Calculator
# Dan Soloha
# 9/12/2019
total = int(input("What was the total your bill came to? "))
print(f"With a total of {total}, you should tip ${int(total + (total * 0.15))}. If the waiter did a really good job, you should tip ${int(total + (total * 0.20))}. ") # Multiplying by 1.x was returning the numb... | normal | {
"blob_id": "45d5c75a993ff50e1a88510bdb16e963403c5356",
"index": 8588,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(\n f'With a total of {total}, you should tip ${int(total + total * 0.15)}. If the waiter did a really good job, you should tip ${int(total + total * 0.2)}. '\n )\n",
"step-3... | [
0,
1,
2,
3
] |
# -*- coding: utf-8 -*-
"""
Created on Tue Mar 24 12:16:15 2020
@author: zhangjuefei
"""
import sys
sys.path.append('../..')
import numpy as np
from sklearn.datasets import fetch_openml
from sklearn.preprocessing import OneHotEncoder
import matrixslow as ms
# 加载MNIST数据集，取一部分样本并归一化
X, y = fetch_openml('mnist_784', v... | normal | {
"blob_id": "63f155f7da958e9b6865007c701f7cf986b0cbac",
"index": 7800,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsys.path.append('../..')\n<mask token>\nfor epoch in range(60):\n batch_count = 0\n for i in range(len(X)):\n feature = np.mat(X.values[i]).reshape(img_shape)\n label ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
ROOT_PATH = os.path.split(os.path.abspath(__name__))[0]
DEBUG = True
JWT_SECRET_KEY = 'shop'
SQLALCHEMY_TRACK_MODIFICATIONS = False
user = 'shop'
passwd = 'shopadmin'
db = 'shopdb'
SQLALCHEMY_DATABASE_URI = (
f'mysql+pymysql:/... | flexible | {
"blob_id": "3908d303d0e41677aae332fbdbe9b681bffe5391",
"index": 1044,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nROOT_PATH = os.path.split(os.path.abspath(__name__))[0]\nDEBUG = True\nJWT_SECRET_KEY = 'shop'\nSQLALCHEMY_TRACK_MODIFICATIONS = False\nuser = 'shop'\npasswd = 'shopadmin'\ndb = 'shopdb'\... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class abelectronicsiopiBinarySensor(BinarySensorEntity):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def __init__(self, pinname, pin, pull_mode, invert_logic, bus):
"""Initialize the pin."... | flexible | {
"blob_id": "73d056d4ab0d268841156b21dfc2c54b5fb2f5f1",
"index": 5218,
"step-1": "<mask token>\n\n\nclass abelectronicsiopiBinarySensor(BinarySensorEntity):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def __init__(self, pinname, pin, pull_mode, invert_logic, bus):\n \"\"... | [
5,
7,
8,
10,
11
] |
<|reserved_special_token_0|>
def delete_pdp(pdp_id):
from moon_manager.db_driver import PDPManager
PDPManager.delete_pdp('', pdp_id)
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def delete_pdp(pdp_id):
from moon_manager.db_driver import PDPManager
PDPMa... | flexible | {
"blob_id": "af35075eaca9bba3d6bdb73353eaf944869cdede",
"index": 799,
"step-1": "<mask token>\n\n\ndef delete_pdp(pdp_id):\n from moon_manager.db_driver import PDPManager\n PDPManager.delete_pdp('', pdp_id)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef delete_pdp(pdp_id):\n from moon_manager.... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class SearchProblem:
"""
This class outlines the structure of a search problem, but doesn't implement
any of the methods (in object-oriented terminology: an abstract class).
You do not need to change anything in this class, ever.
"""
def getStartState(self):
... | flexible | {
"blob_id": "e7b96c0161e65f3f22f2ad0832fc6d1bb529f150",
"index": 9772,
"step-1": "<mask token>\n\n\nclass SearchProblem:\n \"\"\"\n This class outlines the structure of a search problem, but doesn't implement\n any of the methods (in object-oriented terminology: an abstract class).\n\n You do not nee... | [
8,
10,
12,
13,
15
] |
<|reserved_special_token_0|>
def _render(resp):
response = make_response(jsonify(resp))
return response
<|reserved_special_token_0|>
def json_detail_render(code, data=[], message=None):
if message is None:
message = STATUS_CODE.get(code)
resp = dict(code=code, message=message, data=data)
... | flexible | {
"blob_id": "a87ab07bb1502a75a7e705cd5c92db829ebdd966",
"index": 8689,
"step-1": "<mask token>\n\n\ndef _render(resp):\n response = make_response(jsonify(resp))\n return response\n\n\n<mask token>\n\n\ndef json_detail_render(code, data=[], message=None):\n if message is None:\n message = STATUS_C... | [
2,
3,
5,
6,
7
] |
__version__ = "1.2.0"
import hashlib
from collections import Counter
from re import findall
from secrets import choice
from string import ascii_letters, ascii_lowercase, ascii_uppercase
from string import digits as all_digits
from string import punctuation
import requests
def check_password(password):
"""Check ... | normal | {
"blob_id": "eafe89de10c4187057b0cc1e0e9772f03a576b0d",
"index": 9771,
"step-1": "<mask token>\n\n\nclass PasswordGenerator:\n <mask token>\n\n def __init__(self, length, *, uppercase=True, lowercase=True, digits=\n True, special=True):\n self.length = length\n self.uppercase = upperca... | [
4,
6,
10,
12,
13
] |
from emulator import Emulator
from device import Device
from devices.compactflash import CompactFlash
from devices.mc68681 import MC68681
from musashi import m68k
def add_arguments(parser):
parser.add_argument('--rom',
type=str,
help='ROM image')
parser.add_argu... | normal | {
"blob_id": "9eef202a42bfc10b2f52d1b9153d664c5046c13f",
"index": 1965,
"step-1": "<mask token>\n\n\nclass CB030Ticker(Device):\n\n def __init__(self, args, **options):\n super().__init__(args=args, name='CB030Ticker', required_options=[\n 'address'], **options)\n self.size = 4096\n ... | [
7,
11,
13,
14,
15
] |
class Leg():
__smelly = True
def bend_knee(self):
print("knee bent")
@property
def smelly(self):
return self.__smelly
@smelly.setter
def smelly(self,smell):
self.__smelly = smell
def is_smelly(self):
return self.__smelly | normal | {
"blob_id": "a4ecc578a163ee4657a2c9302f79f15c2e4e39de",
"index": 672,
"step-1": "class Leg:\n <mask token>\n <mask token>\n\n @property\n def smelly(self):\n return self.__smelly\n <mask token>\n\n def is_smelly(self):\n return self.__smelly\n",
"step-2": "class Leg:\n <mask ... | [
3,
4,
5,
6,
7
] |
# terrascript/spotinst/__init__.py
import terrascript
class spotinst(terrascript.Provider):
pass | normal | {
"blob_id": "0ae626df5a471af77f7361bb765b46b861ee8a2c",
"index": 7142,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass spotinst(terrascript.Provider):\n pass\n",
"step-3": "import terrascript\n\n\nclass spotinst(terrascript.Provider):\n pass\n",
"step-4": "# terrascript/spotinst/__init... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution:
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution:
def letterCombinations(self, digits):
"""
:type digits: str
:rtype: List[str]
"""
if not digits:
return [... | flexible | {
"blob_id": "aec311cae7cb6cbe3e3a927a133ec20a2d2afbf5",
"index": 1312,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n",
"step-3": "class Solution:\n\n def letterCombinations(self, digits):\n \"\"\"\n :type digits: str\n :rtype: List[str]\n \"\"\"\n ... | [
0,
1,
2
] |
# Алексей Головлев, группа БСБО-07-19
def lucky(ticket):
def sum_(number):
number = str(number)
while len(number) != 6:
number = '0' + number
x = list(map(int, number))
return sum(x[:3]) == sum(x[3:])
return 'Счастливый' if sum_(ticket) == sum_(lastTicket) else 'Нес... | normal | {
"blob_id": "85ac851e28dba3816f18fefb727001b8e396cc2b",
"index": 5278,
"step-1": "<mask token>\n",
"step-2": "def lucky(ticket):\n\n def sum_(number):\n number = str(number)\n while len(number) != 6:\n number = '0' + number\n x = list(map(int, number))\n return sum(x[:... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class State(object):
def __init__(self, i, j, is_cliff=False, is_goal=False):
self.i = i
self.j = j
self.is_cliff = is_cliff
self.is_goal = is_goal
self.q_values = np.array([0.0, 0.0, 0.0, 0.0])
def __str__(self):
return '({}, {})'... | flexible | {
"blob_id": "cb2e800cc2802031847b170a462778e5c0b3c6f9",
"index": 40,
"step-1": "<mask token>\n\n\nclass State(object):\n\n def __init__(self, i, j, is_cliff=False, is_goal=False):\n self.i = i\n self.j = j\n self.is_cliff = is_cliff\n self.is_goal = is_goal\n self.q_values =... | [
14,
16,
20,
21,
22
] |
<|reserved_special_token_0|>
class web_scrap:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def __init__(self, seed):
self.seed = seed
self.set_tag()
self.set_attr()
self.fetch_web(self.seed)
self.crawl()
def fetch_... | flexible | {
"blob_id": "f26dc3139413c4ed4b04484c095a433e53039cdb",
"index": 3028,
"step-1": "<mask token>\n\n\nclass web_scrap:\n <mask token>\n <mask token>\n <mask token>\n\n def __init__(self, seed):\n self.seed = seed\n self.set_tag()\n self.set_attr()\n self.fetch_web(self.seed)... | [
8,
10,
11,
12,
13
] |
from extras.plugins import PluginConfig
from .version import __version__
class QRCodeConfig(PluginConfig):
name = 'netbox_qrcode'
verbose_name = 'qrcode'
description = 'Generate QR codes for the objects'
version = __version__
author = 'Nikolay Yuzefovich'
author_email = 'mgk.kolek@gmail.com'
... | normal | {
"blob_id": "6306acd1508698687842ba6b55a839743af420cc",
"index": 5840,
"step-1": "<mask token>\n\n\nclass QRCodeConfig(PluginConfig):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\n<mask token>\n",
"step-2": "... | [
1,
2,
3,
4,
5
] |
class Violation(object):
def __init__(self, line, column, code, message):
self.line = line
self.column = column
self.code = code
self.message = message
def __str__(self):
return self.message
def __repr__(self):
return 'Violation(line={}, column={}, code="{}... | normal | {
"blob_id": "c513ad6ef12ae7be5d17d8d44787691cbc065207",
"index": 9989,
"step-1": "class Violation(object):\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "class Violation(object):\n\n def __init__(self, line, column, code, message):\n self.line = line\n self.column = colum... | [
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class State:
<|reserved_special_token_0|>
def __init__(self, x, y, theta, parent=None, parent_action=None, g=
float('inf'), h=float('inf')):
self.x = x
self.y = y
self.theta = theta % (2 * math.pi)
self.g = g
self.h = h
self... | flexible | {
"blob_id": "c8f899958ce19e7e2bf1307a685e65873695f140",
"index": 9028,
"step-1": "<mask token>\n\n\nclass State:\n <mask token>\n\n def __init__(self, x, y, theta, parent=None, parent_action=None, g=\n float('inf'), h=float('inf')):\n self.x = x\n self.y = y\n self.theta = theta... | [
8,
9,
10,
11,
12
] |
<|reserved_special_token_0|>
def _get_environmentdef():
"""
Retreive the EnvironmentDefinition from the fabric env.
"""
if 'environmentdef' not in env:
abort('Environment needs to be configured')
environmentdef = env.environmentdef
if env.host_string:
environmentdef = environme... | flexible | {
"blob_id": "cc019c732003ed72db80a7893096a0bef0f12e47",
"index": 4168,
"step-1": "<mask token>\n\n\ndef _get_environmentdef():\n \"\"\"\n Retreive the EnvironmentDefinition from the fabric env.\n \"\"\"\n if 'environmentdef' not in env:\n abort('Environment needs to be configured')\n enviro... | [
5,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
class Neural_Network(nn.Module):
<|reserved_special_token_0|>
def __init__(self, input_size=2, output_size=1, hidden_size=3):
super(Neural_Network, self).__init__()
self.input_size = input_size
self.output_size = output_size
self.hidden_size = hidd... | flexible | {
"blob_id": "2d5e7c57f58f189e8d0c7d703c1672ea3586e4ac",
"index": 6771,
"step-1": "<mask token>\n\n\nclass Neural_Network(nn.Module):\n <mask token>\n\n def __init__(self, input_size=2, output_size=1, hidden_size=3):\n super(Neural_Network, self).__init__()\n self.input_size = input_size\n ... | [
9,
10,
12,
13,
14
] |
from random import randint, shuffle
class Generator:
opset = ['+', '-', '*', '/', '²', '√', 'sin', 'cos', 'tan']
@staticmethod
def generate(level):
"""
根据 level 生成指定等级的算术题
0：小学；1：初中；2：高中
"""
"""
生成操作数序列以及二元运算符序列
"""
length = randint(0 if lev... | normal | {
"blob_id": "6e3bb17696953256af6d8194128427acebf1daac",
"index": 524,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Generator:\n <mask token>\n\n @staticmethod\n def generate(level):\n \"\"\"\n 根据 level 生成指定等级的算术题\n 0：小学；1：初中；2：高中\n \"\"\"\n \"\"\"\n... | [
0,
2,
3,
4
] |
import os
import pytest
def get_client():
from apiserver import app, is_caching_enabled
app.config['TESTING'] = True
app.enable_cache(is_caching_enabled())
return app.test_client()
@pytest.fixture
def client():
os.environ['FLASK_ENV'] = 'testing'
yield get_client()
@pytest.fixture
def clie... | normal | {
"blob_id": "c0b5a0605bdfcb7cb84211d3ad0d24f78f838cdf",
"index": 5421,
"step-1": "<mask token>\n\n\n@pytest.fixture\ndef client():\n os.environ['FLASK_ENV'] = 'testing'\n yield get_client()\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_client():\n from apiserver import app, is_caching_ena... | [
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def get_csv_path():
path = input('enter csv path:')
if os.path.isfile(path):
return path
else:
print('csv file not exsit,try again:')
return get_csv_path()
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def... | flexible | {
"blob_id": "857e3e04b99cb346fd89b34c0d14957d65b7ac38",
"index": 9566,
"step-1": "<mask token>\n\n\ndef get_csv_path():\n path = input('enter csv path:')\n if os.path.isfile(path):\n return path\n else:\n print('csv file not exsit,try again:')\n return get_csv_path()\n\n\n<mask toke... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def usuario():
global usser
usser = input('Introduce un usuario : ')
if len(usser) < 5 or len(usser) > 15:
print('El usuario debe tener entre 5 y 15 caracteres')
usuario()
elif usser.isalnum() == ... | flexible | {
"blob_id": "ce75c23c6b0862dde797225f53c900b4ebc56428",
"index": 514,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef usuario():\n global usser\n usser = input('Introduce un usuario : ')\n if len(usser) < 5 or len(usser) > 15:\n print('El usuario debe tener entre 5 y 15 caracteres'... | [
0,
1,
2,
3,
4
] |
import dash_table
import pandas as pd
import dash_html_components as html
import dash_core_components as dcc
from dash.dependencies import Input, Output
from dash_oop_components import DashComponent
import dash_table
import dash_bootstrap_components as dbc
from dash.dependencies import Input, Output, State
from dash_oo... | normal | {
"blob_id": "485f85ec5e3f38148978453ea5e7f9a54eb310e1",
"index": 160,
"step-1": "<mask token>\n\n\nclass Table(DashComponent):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Table(DashComponent):\n\n def __init__(self, plot_factory, df, title='... | [
1,
3,
5,
6,
7
] |
import torch
import torch.nn.functional as f
import time
import matplotlib.pyplot as plt
from matplotlib.lines import Line2D
import numpy as np
dtype = torch.float
device = torch.device("cpu")
# device = torch.device("cuda:0") # Uncomment this to run on GPU
N, D_in, H, D_out = 64, 1000, 100, 10
x = torch.randn(N, D... | normal | {
"blob_id": "0fb424dafaac184882ea56f36265e0b19b5a4c50",
"index": 9758,
"step-1": "<mask token>\n\n\ndef plot_grad_flow(named_parameters):\n \"\"\"Plots the gradients flowing through different layers in the net during training.\n Can be used for checking for possible gradient vanishing / exploding problems.... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def registry_names():
return iter(_registry)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def registry(name):
_registry.append(name)
def registry_names():
return iter(_registry)
<|reserved_speci... | flexible | {
"blob_id": "51642dbb210600f9ca4e035fb884fbdda030fd04",
"index": 1491,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef registry_names():\n return iter(_registry)\n",
"step-3": "<mask token>\n\n\ndef registry(name):\n _registry.append(name)\n\n\ndef registry_names():\n return iter(_regis... | [
0,
1,
2,
3
] |
import time
from typing import List
from classiclikeiguana.timeout import timeout
class ExecutionMetrics:
def __init__(self, duration, succeeded: bool, timed_out: bool, lines: int, error: List[str] = None):
if error is None:
error = list()
self.duration = duration
self.succeed... | normal | {
"blob_id": "f870c776a62f3b743356c5515cd25e588dbfca15",
"index": 8183,
"step-1": "<mask token>\n\n\nclass ExecutionMetrics:\n <mask token>\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass ExecutionMetrics:\n\n def __init__(self, duration, succeeded: bool, timed_out: bool, lines:... | [
1,
3,
4,
5,
6
] |
import sqlite3
connection = sqlite3.connect("../db.sqlite3")
cursor = connection.cursor()
sql_file = open("sample.sql")
sql_as_string = sql_file.read()
cursor.executescript(sql_as_string)
for row in cursor.execute("SELECT * FROM results_states"):
print(row)
| normal | {
"blob_id": "10a981e35ce00ee8e32a613823d3bc919fafaae8",
"index": 8225,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ncursor.executescript(sql_as_string)\nfor row in cursor.execute('SELECT * FROM results_states'):\n print(row)\n",
"step-3": "<mask token>\nconnection = sqlite3.connect('../db.sqlite3'... | [
0,
1,
2,
3,
4
] |
import datetime
import logging
import random
import transform
import timelapse
# merge two iterators producing sorted values
def merge(s1, s2):
try:
x1 = next(s1)
except StopIteration:
yield from s2
return
try:
x2 = next(s2)
except StopIteration:
yield from s1
... | normal | {
"blob_id": "c651d49c98a4cf457c8252c94c6785dea8e9af60",
"index": 3909,
"step-1": "<mask token>\n\n\nclass Sliders(timelapse.TimeLapse):\n\n def __init__(self, server_list, nick='Sliders', channel='#sliders',\n realname='Sliders', sliding_window=60, **params):\n super().__init__(server_list, nick... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
model.to(device)
<|reserved_special_token_0|>
...
for epoch in range(epochs):
running_loss = 0
running_acc = 0
train_loss = 0
model.train()
for image, label in tqdm(train_dataloader, desc='Epoch [%d/%d]' % (
... | flexible | {
"blob_id": "c3aee5d822d48c9dc826f8f2f8d4a56e11513b9c",
"index": 2882,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nmodel.to(device)\n<mask token>\n...\nfor epoch in range(epochs):\n running_loss = 0\n running_acc = 0\n train_loss = 0\n model.train()\n for image, label in tqdm(train_data... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def sleeping():
time.sleep(5)
print('Ended')
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def sleeping():
time.sleep(5)
print('Ended')
Thread(target=sleeping, da... | flexible | {
"blob_id": "628fdf848079d0ecf5bf4f5bd46e07ad6cd10358",
"index": 5070,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef sleeping():\n time.sleep(5)\n print('Ended')\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef sleeping():\n time.sleep(5)\n print('Ended')\n\n\nThread(target=s... | [
0,
1,
2,
3
] |
T = int(input())
for cnt in range(1, T + 1):
S = input()
S_list = []
card = {'S': 13, 'D': 13, 'H': 13, 'C': 13}
print('#' + str(cnt), end=' ')
for i in range(0, len(S), 3):
S_list.append(S[i:i + 3])
if len(set(S_list)) != len(S_list):
print('ERROR')
else:
for i in S_... | normal | {
"blob_id": "45750152313fd3670867c61d0173e4cb11a806ba",
"index": 4468,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor cnt in range(1, T + 1):\n S = input()\n S_list = []\n card = {'S': 13, 'D': 13, 'H': 13, 'C': 13}\n print('#' + str(cnt), end=' ')\n for i in range(0, len(S), 3):\n ... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
from . import find_resault
from . import sql
| flexible | {
"blob_id": "6f05d1915cd2e123dd72233b59d4de43fd724035",
"index": 7743,
"step-1": "<mask token>\n",
"step-2": "from . import find_resault\nfrom . import sql\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
<|reserved_special_token_0|>
def draw_text(surf, text, size, x, y):
font_name = pygame.font.match_font('OCR A Extended')
font = pygame.font.Font(font_name, size)
text_surface = font.render(text, True, WHITE)
text_rect = text_surface.get_rect()
text_rect.midtop = x, y
surf.blit(text_surface, te... | flexible | {
"blob_id": "7301a521586049ebb5e8e49b604cc96e3acc1fe9",
"index": 3512,
"step-1": "<mask token>\n\n\ndef draw_text(surf, text, size, x, y):\n font_name = pygame.font.match_font('OCR A Extended')\n font = pygame.font.Font(font_name, size)\n text_surface = font.render(text, True, WHITE)\n text_rect = te... | [
3,
4,
5,
6,
7
] |
import collections
import re
from collections import Counter
import operator
import pickle
import math
import json
path='C:/Users/rahul/Desktop/CSCI 544/HW 2/op_spam_train/'
#path=sys.argv[1]
badWordList = ['and','the','was','for']
RE=r'\b[^\W\d_]+\b'
# NEGATIVE TWEETS
c=collections.Counter()
NT="negativeTweets.txt/... | normal | {
"blob_id": "42e16def0fcf234f3d7c2709de36a321d8ddf29e",
"index": 7598,
"step-1": "import collections\nimport re\nfrom collections import Counter\nimport operator\nimport pickle\nimport math\nimport json\n\npath='C:/Users/rahul/Desktop/CSCI 544/HW 2/op_spam_train/'\n#path=sys.argv[1]\n\nbadWordList = ['and','the'... | [
0
] |
<|reserved_special_token_0|>
class NoViz:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def addfile(self, *a, **kw):
pass
def addgcode(self, *a, **kw):
pass
def addgcodehighlight(self, *a, **kw):
pass
<|reserved_special_to... | flexible | {
"blob_id": "3cc473f6bb4b2e1dd806edb8b096a6118fe7056a",
"index": 7202,
"step-1": "<mask token>\n\n\nclass NoViz:\n <mask token>\n <mask token>\n <mask token>\n\n def addfile(self, *a, **kw):\n pass\n\n def addgcode(self, *a, **kw):\n pass\n\n def addgcodehighlight(self, *a, **kw):... | [
9,
10,
11,
15,
16
] |
from . import utils
from . import objects
START = (0, 0)
STARTING_LIFE = 10
WHITE = (255, 255, 255)
class RoughLightGame:
def __init__(self, game_map, width, height, **kwargs):
self.map = game_map
self.width = width
self.height = height
self.objects = kwargs.get('objects', list... | normal | {
"blob_id": "5f089c3e67452fe6d14f96a70d792bc0d056b375",
"index": 9227,
"step-1": "<mask token>\n\n\nclass RoughLightGame:\n\n def __init__(self, game_map, width, height, **kwargs):\n self.map = game_map\n self.width = width\n self.height = height\n self.objects = kwargs.get('object... | [
4,
5,
6,
8,
10
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Solution:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Solution:
def mostCommonWord(self, paragraph, banned):
"""
... | flexible | {
"blob_id": "3bb50b61c7a3e98ede0a31e574f39b4ea7f22de5",
"index": 9197,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Solution:\n <mask token>\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\nclass Solution:\n\n def mostCommonWord(self, paragraph, banned):\n \"\"\"\n :ty... | [
0,
1,
2,
3,
4
] |
from django.shortcuts import render, redirect
from .models import Game, Player, CardsInHand, Feedback
from django.db.models import Q
from .forms import GameForm, JoinForm, FeedbackForm
from django.shortcuts import get_object_or_404
from django.http import HttpResponse, HttpResponseRedirect, JsonResponse
from django.vie... | normal | {
"blob_id": "d650f578ea30772489625ee26f3e4bf04131964b",
"index": 6140,
"step-1": "<mask token>\n\n\ndef join_game(request):\n if request.method != 'POST':\n return HttpResponseRedirect('/game')\n form_data = json.loads(request.body.decode('utf-8'))\n form = JoinForm(form_data)\n if form.is_val... | [
3,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
class UserFormView(View):
form_class = UserForm
template_name = 'shop/signup.html'
def get(self, request):
form = self.form_class(None)
return render(request, self.template_name, {'form': form})
def post(self, request):
form = self.form_class(requ... | flexible | {
"blob_id": "1d72a9882aea1e0f808969828ed2e69ecd79ac71",
"index": 7522,
"step-1": "<mask token>\n\n\nclass UserFormView(View):\n form_class = UserForm\n template_name = 'shop/signup.html'\n\n def get(self, request):\n form = self.form_class(None)\n return render(request, self.template_name,... | [
4,
6,
8,
9,
10
] |
<|reserved_special_token_0|>
class UserService(object):
<|reserved_special_token_0|>
@staticmethod
def get(id):
"""获取单条记录
[description]
Arguments:
id int -- 主键
return:
User Model 实例 | None
"""
if not id:
raise JsonErro... | flexible | {
"blob_id": "d1ed43bab6171c876b2ad9ef9db834ab8f9026d5",
"index": 8411,
"step-1": "<mask token>\n\n\nclass UserService(object):\n <mask token>\n\n @staticmethod\n def get(id):\n \"\"\"获取单条记录\n\n [description]\n\n Arguments:\n id int -- 主键\n\n return:\n Us... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
@dataclass
class Actions:
""" The class for a set of actions.
This class is a collection of actions. It is used to for the four primary
usecases:
- to serialize the list of actions into a dataframe
- to serialize the list of actions into a markdown/html table
... | flexible | {
"blob_id": "4d0f612c74dc175766f489580fc4a492e1bfd085",
"index": 4345,
"step-1": "<mask token>\n\n\n@dataclass\nclass Actions:\n \"\"\" The class for a set of actions.\n\n This class is a collection of actions. It is used to for the four primary\n usecases:\n - to serialize the list of actions in... | [
10,
13,
19,
23,
25
] |
# -*- coding:utf-8 -*-
# Author: hankcs
# Date: 2019-01-13 15:01
import pickle
import numpy as np
from bert_serving.client import BertClient
from pyhanlp import *
CharTable = JClass('com.hankcs.hanlp.dictionary.other.CharTable')
# bc = BertClient(ip='192.168.1.88') # ip address of the server
bc = BertClient(ip='127... | normal | {
"blob_id": "38e167630519b73bffea4ff527bc7b7272a49f1a",
"index": 348,
"step-1": "<mask token>\n\n\ndef embed_last_token(text):\n result = bc.encode(text, show_tokens=True)\n batch = []\n for sent, tensor, tokens in zip(text, result[0], result[1]):\n valid = []\n tid = 0\n buffer = '... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
def get_ports():
ports = serial.tools.list_ports.comports()
ports_str = []
for port in ports:
ports_str.append(port.device)
return ports_str
def start():
opt_mode = mode.get()
opt_filename = filename.get()
opt_port = portname.get()
if not opt_mode... | flexible | {
"blob_id": "6455741bbda42b9d84428545ddd50a5d1b54a7ba",
"index": 1376,
"step-1": "<mask token>\n\n\ndef get_ports():\n ports = serial.tools.list_ports.comports()\n ports_str = []\n for port in ports:\n ports_str.append(port.device)\n return ports_str\n\n\ndef start():\n opt_mode = mode.get(... | [
2,
4,
5,
6,
7
] |
"""
CP1404 Practical
unreliable car test
"""
from unreliable_car import UnreliableCar
def main():
good_car = UnreliableCar("good car", 100, 80)
bad_car = UnreliableCar("bad car", 100, 10)
for i in range(10):
print("try to drive {} km".format(i))
print("{:10} drove {:2}km".format(good_car.... | normal | {
"blob_id": "f29ad02f3781c7a7d2a1f0c97626dd5c7ea2417e",
"index": 7867,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main():\n good_car = UnreliableCar('good car', 100, 80)\n bad_car = UnreliableCar('bad car', 100, 10)\n for i in range(10):\n print('try to drive {} km'.format(i))... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(f'resultado: {resultado} || seu tipo: {type(resultado)}')
print('--------------\n')
print(f"""Nasca de bacana:
{Counter('Nasca de bacana')}""")
print('--------------\n')
<|reserved_special_token_0|>
print(f'ocorrencias de ... | flexible | {
"blob_id": "4989d01f31ca034aacdda28eff56adb2e0bb15da",
"index": 1889,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(f'resultado: {resultado} || seu tipo: {type(resultado)}')\nprint('--------------\\n')\nprint(f\"\"\"Nasca de bacana: \n {Counter('Nasca de bacana')}\"\"\")\nprint('--------------\\n... | [
0,
1,
2,
3,
4
] |
# Inspiration: [Fake Album Covers](https://fakealbumcovers.com/)
from IPython.display import Image as IPythonImage
from PIL import Image
from PIL import ImageFont
from PIL import ImageDraw
import requests
from xml.etree import ElementTree as ET
def display_cover(top,bottom ):
name='album_art_raw.png'
alb... | normal | {
"blob_id": "07215403750be53994ae36727b6f790202b88697",
"index": 253,
"step-1": "# Inspiration: [Fake Album Covers](https://fakealbumcovers.com/)\nfrom IPython.display import Image as IPythonImage\nfrom PIL import Image\nfrom PIL import ImageFont\nfrom PIL import ImageDraw\n\nimport requests\nfrom xml.etree impo... | [
0
] |
<|reserved_special_token_0|>
def Viterbi(sentence, q, e):
K = list(Count_y.keys())
Pi = {}
bp = {}
n = len(sentence)
for i in range(n + 1):
Pi[i - 1] = {}
bp[i - 1] = {}
Pi[-1]['*', '*'] = 1
for k in range(n):
K0 = K
K1 = K
K2 = K
if k == 0:
... | flexible | {
"blob_id": "9683c7df01eda0d97615fb3e8f9496ecc95d1d32",
"index": 8494,
"step-1": "<mask token>\n\n\ndef Viterbi(sentence, q, e):\n K = list(Count_y.keys())\n Pi = {}\n bp = {}\n n = len(sentence)\n for i in range(n + 1):\n Pi[i - 1] = {}\n bp[i - 1] = {}\n Pi[-1]['*', '*'] = 1\n ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
@api.route('/login/', methods=['POST'])
def login():
email = request.get_json().get('email')
pwd = request.get_json().get('password')
user = User.query.filter_by(email=email).first()
if not user:
return j... | flexible | {
"blob_id": "a0dbb374f803cb05a35f823f54ef5f14eaf328b2",
"index": 3688,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@api.route('/login/', methods=['POST'])\ndef login():\n email = request.get_json().get('email')\n pwd = request.get_json().get('password')\n user = User.query.filter_by(email... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def main():
""" Execute main program
"""
import argparse
parser = argparse.ArgumentParser(description='Check nodes status.')
parser.add_argument('-o', '--show-job-owners', action='store_true',
help='List jobs running on nodes')
parser.add_argument('-s', '--... | flexible | {
"blob_id": "381b59ab9fa85561932a9bfb9ab8cef635901a35",
"index": 7249,
"step-1": "<mask token>\n\n\ndef main():\n \"\"\" Execute main program\n \"\"\"\n import argparse\n parser = argparse.ArgumentParser(description='Check nodes status.')\n parser.add_argument('-o', '--show-job-owners', action='st... | [
1,
2,
3,
4,
5
] |
import time
# Returns time in seconds for func(arg) to run
def time_func(func, arg):
start = time.time()
func(arg)
return time.time() - start
| normal | {
"blob_id": "7f406c1cd4d56da3a7d5f8739e0b65b0e61cf637",
"index": 5290,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef time_func(func, arg):\n start = time.time()\n func(arg)\n return time.time() - start\n",
"step-3": "import time\n\n\ndef time_func(func, arg):\n start = time.time()\... | [
0,
1,
2,
3
] |
from .gsclient import GSClient
from .gspath import GSPath
__all__ = [
"GSClient",
"GSPath",
]
| normal | {
"blob_id": "7b726dd8ebbd5c49f9ce5bddb4779fcfbaaeb479",
"index": 5651,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n__all__ = ['GSClient', 'GSPath']\n",
"step-3": "from .gsclient import GSClient\nfrom .gspath import GSPath\n__all__ = ['GSClient', 'GSPath']\n",
"step-4": "from .gsclient import GSCli... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if __name__ == '__main__':
conn = sqlite3.connect('donations.sqlite')
c = conn.cursor()
query = 'DROP TABLE IF EXISTS factions;'
c.execute(query)
query = 'DROP TABLE IF EXISTS members;'
c.execute(query)
... | flexible | {
"blob_id": "b6b8dfaa9644fa4f4c250358b89f4a30c26c317f",
"index": 4788,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n conn = sqlite3.connect('donations.sqlite')\n c = conn.cursor()\n query = 'DROP TABLE IF EXISTS factions;'\n c.execute(query)\n query = 'DROP TA... | [
0,
1,
2,
3
] |
from ROOT import *
gSystem.Load("libAnalysis")
import sys
import argparse
parser = argparse.ArgumentParser(description="Python script to process and merge showers.")
group = parser.add_mutually_exclusive_group()
group.add_argument("-v", "--verbose", help="Turn on verbose output",
action="store_tru... | normal | {
"blob_id": "d57b91bf41f031e3362dabdef8c67a0da04fe577",
"index": 7540,
"step-1": "from ROOT import *\ngSystem.Load(\"libAnalysis\")\nimport sys\n\nimport argparse\n\nparser = argparse.ArgumentParser(description=\"Python script to process and merge showers.\")\ngroup = parser.add_mutually_exclusive_group()\ngroup... | [
0
] |
# coding: utf-8
# In[50]:
## Description
## Adds the Fibonacci numbers smaller than 4 million
## Weekly Journal
## When using while True, "break" MUST be used to avoid infinite loops
## Questions
## None
fib=[1,2]
counter=1
while True:
if fib[counter]>4000000:
flag=0
break
else:
f... | normal | {
"blob_id": "e2572b48f7183353ba2aab0500130dc8a71a0b22",
"index": 5286,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile True:\n if fib[counter] > 4000000:\n flag = 0\n break\n else:\n fib.append(fib[counter] + fib[counter - 1])\n counter += 1\n<mask token>\nprint(tot... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print('bob' in adict)
print('name' in adict)
for key in adict:
print('%s:%s' % (key, adict[key]))
print('%(name)s:%(age)s' % adict)
<|reserved_special_token_1|>
adict = {'name': 'bob', 'age': 23}
print('bob' in adict)
print... | flexible | {
"blob_id": "aa4d872c6a529d8acf18f1c3b477bc1816ac2887",
"index": 575,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('bob' in adict)\nprint('name' in adict)\nfor key in adict:\n print('%s:%s' % (key, adict[key]))\nprint('%(name)s:%(age)s' % adict)\n",
"step-3": "adict = {'name': 'bob', 'age': ... | [
0,
1,
2
] |
print("calificacion de los alumnos")
lista2_calificaciones=[]
for i in range (0,5):
lista2_calificaciones.append(int(input(f"ingrese la calificacion corresponfiente al alumno")))
print(lista2_calificaciones)
for n in range(0,len(lista2_calificaciones)):
if lista2_calificaciones[i] >=0 and lista2_calific... | normal | {
"blob_id": "1cc9c89182f69a5f1eb9a0e7f3433dc30c8d7035",
"index": 2938,
"step-1": "<mask token>\n",
"step-2": "print('calificacion de los alumnos')\n<mask token>\nfor i in range(0, 5):\n lista2_calificaciones.append(int(input(\n f'ingrese la calificacion corresponfiente al alumno')))\n print(lista2... | [
0,
1,
2,
3
] |
from .server import CanvasServer
try:
from .jupyter import JupyterCanvas, create_jupyter_canvas
HAS_JUPYTER = True
except:
HAS_JUPYTER = False
JupyterCanvas = None # type: ignore
def http_server(
file: str = None, host: str = "localhost", port: int = 5050
) -> CanvasServer:
"""Creates a new... | normal | {
"blob_id": "b11e2837d3ba9c14770b8039186a2175adc41ea1",
"index": 283,
"step-1": "<mask token>\n\n\ndef http_server(file: str=None, host: str='localhost', port: int=5050\n ) ->CanvasServer:\n \"\"\"Creates a new HTTP server for displaying the network, using WebSockets to\n transmit data. The server will ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
with open('Quotes.txt', 'w') as ff:
for q in quote:
msg = q.find('span', {'class': 'text'})
print(msg.text)
ff.write(msg.text)
author = q.find('small', {'class': 'author'})
print(author.... | flexible | {
"blob_id": "777c08876a2de803fc95de937d9e921044545ef8",
"index": 3674,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('Quotes.txt', 'w') as ff:\n for q in quote:\n msg = q.find('span', {'class': 'text'})\n print(msg.text)\n ff.write(msg.text)\n author = q.find('sm... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
db.execute(
'CREATE TABLE IF NOT EXISTS employee (id INTEGER PRIMAR KEY, employee_name TEXT, employee_salary INTEGER, employee_age INTEGER, profile_image BLOB)'
)
for employee in packages_json['data']:
db.execute('INSE... | flexible | {
"blob_id": "497203be99643e2bb0087977f292f4ed890f9ead",
"index": 7111,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ndb.execute(\n 'CREATE TABLE IF NOT EXISTS employee (id INTEGER PRIMAR KEY, employee_name TEXT, employee_salary INTEGER, employee_age INTEGER, profile_image BLOB)'\n )\nfor employee ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def f(q):
for i in range(0, 100):
print('come on baby')
q.put([42, None, 'hello'])
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def f(q):
for i in range(0, 100... | flexible | {
"blob_id": "c7258d77db2fe6e1470c972ddd94b2ed02f48003",
"index": 3390,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef f(q):\n for i in range(0, 100):\n print('come on baby')\n q.put([42, None, 'hello'])\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef f(q):\n for i in rang... | [
0,
1,
2,
3,
4
] |
import stockquote
import time
import datetime
from datetime import date
from connection import db
start_date='20100101'
def prices(symbol):
"""
Loads the prices from the start date for the given symbol
Only new quotes are downloaded.
"""
to = date.today().strftime("%Y%m%d")
c = db.cursor()
c.execute("SEL... | normal | {
"blob_id": "1b58d294f02ce85bf19da03f94100af87408081d",
"index": 1326,
"step-1": "import stockquote\nimport time\nimport datetime\nfrom datetime import date\nfrom connection import db\n\nstart_date='20100101'\ndef prices(symbol):\n \"\"\"\n Loads the prices from the start date for the given symbol\n Only new ... | [
0
] |
<|reserved_special_token_0|>
class Trainer(object):
<|reserved_special_token_0|>
def __init__(self, data_loader, model_name, model, optimizer_fn,
final_steps, lr_scheduler_fn=None, step=0, ckpt_path=None, log_path
=None, n_epochs=None, save_steps=None, log_steps=10, device='cuda',
use... | flexible | {
"blob_id": "9fa534664056a8cf9e9a64ccc7d6dd4de2ec0936",
"index": 1514,
"step-1": "<mask token>\n\n\nclass Trainer(object):\n <mask token>\n\n def __init__(self, data_loader, model_name, model, optimizer_fn,\n final_steps, lr_scheduler_fn=None, step=0, ckpt_path=None, log_path\n =None, n_epoch... | [
8,
12,
13,
14,
15
] |
import uuid
from fastapi import APIRouter, Depends, HTTPException, Form, Body
from fastapi.security import OAuth2PasswordBearer, OAuth2PasswordRequestForm
from sqlalchemy.orm import Session
# dependency
from configs.config_sqlalchemy import get_db
# schema
from schema import store_schema
# define the url the clie... | normal | {
"blob_id": "64bbf2e3b961a6e0b5d7e551278bb21990df2ed9",
"index": 5526,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@router.post('/account/register', summary='register to create a new store',\n response_model=store_schema.Store, status_code=201)\nasync def account_register(StoreName: str=Body(..... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def test_stringify_nums():
"""."""
from radixsort import stringify_nums
nums = [1, 2, 3, 4, 5]
stringified_nums = stringify_nums(nums)
assert stringified_nums == ['1', '2', '3', '4', '5']
def test_while_condition():
"""."""
from radixsort import while_conditi... | flexible | {
"blob_id": "fd907dbcea01679c08aeae6bcbf6e61786f40260",
"index": 2511,
"step-1": "<mask token>\n\n\ndef test_stringify_nums():\n \"\"\".\"\"\"\n from radixsort import stringify_nums\n nums = [1, 2, 3, 4, 5]\n stringified_nums = stringify_nums(nums)\n assert stringified_nums == ['1', '2', '3', '4',... | [
4,
5,
6,
7,
8
] |
<|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):
def reachNumber(self, target):
target = abs(target)
k = 0
while target > 0:
... | flexible | {
"blob_id": "4b255b648f67e6bcc30eecc7975bbb1a356b2499",
"index": 2656,
"step-1": "<mask token>\n",
"step-2": "class Solution(object):\n <mask token>\n\n\n<mask token>\n",
"step-3": "class Solution(object):\n\n def reachNumber(self, target):\n target = abs(target)\n k = 0\n while ta... | [
0,
1,
2,
3,
4
] |
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