code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for topic in topics:
i += 1
arts = os.listdir(os.path.join(path, topic))
j = 0
for art in arts:
j += 1
with open(os.path.join(path, topic, art), encoding='UTF-8') as f:
lines = f.read()
... | flexible | {
"blob_id": "977841e0bb73cec879fbb1868f1e64102c6d8c1a",
"index": 2119,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor topic in topics:\n i += 1\n arts = os.listdir(os.path.join(path, topic))\n j = 0\n for art in arts:\n j += 1\n with open(os.path.join(path, topic, art), enco... | [
0,
1,
2,
3,
4
] |
def solution(skill, skill_trees):
answer = 0
for tree in skill_trees:
able = True
for i in range(len(skill) - 1, 0, -1):
index = tree.find(skill[i])
if index != -1 and i > 0:
if tree[:index].find(skill[i - 1]) == -1:
able = False
... | normal | {
"blob_id": "a72d878d246a459038640bf9c1deff562994b345",
"index": 7338,
"step-1": "<mask token>\n",
"step-2": "def solution(skill, skill_trees):\n answer = 0\n for tree in skill_trees:\n able = True\n for i in range(len(skill) - 1, 0, -1):\n index = tree.find(skill[i])\n ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class Dripper(BoxLayout):
def __init__(self, **kwargs):
super(Dripper, self).__init__(**kwargs)
self.index = 0.0
self.sections = 20
self.section_height = 1
self.lasttime = time.time()
Clock.schedule_once(self.redraw)
self.drip_h... | flexible | {
"blob_id": "96086885e5353f3b4b3277c1daf4ee74831c3b73",
"index": 8841,
"step-1": "<mask token>\n\n\nclass Dripper(BoxLayout):\n\n def __init__(self, **kwargs):\n super(Dripper, self).__init__(**kwargs)\n self.index = 0.0\n self.sections = 20\n self.section_height = 1\n self.... | [
10,
12,
14,
15,
19
] |
import os
import lasagne
import theano
import theano.tensor as T
import numpy as np
from lasagne.layers import Conv2DLayer,\
MaxPool2DLayer,\
InputLayer
from lasagne.nonlinearities import elu, sigmoid, rectify
from lasagne.regularization import l2, regularize_layer_... | normal | {
"blob_id": "1dd5c25cd3b7bc933ba0b63d9a42fdddc92b8531",
"index": 8737,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass FaceTrigger(CascadeBase):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass FaceTrigger(CascadeBase):\n\n def build_network(self):\n net = lasagne.layers.batc... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
urlpatterns = [url(regex='^(?P<pk>\\d+)$', view=views.UserDetailView.
as_view(), name='user_detail'), url(regex='^update/(?P<pk>\\d+)$', view
=views.UserUpdateView.as_view(), name='user_update'), url(regex=
'^email/upd... | flexible | {
"blob_id": "1ac0f5c62ee3cb60d4443b65d429f4f0e6815100",
"index": 5488,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [url(regex='^(?P<pk>\\\\d+)$', view=views.UserDetailView.\n as_view(), name='user_detail'), url(regex='^update/(?P<pk>\\\\d+)$', view\n =views.UserUpdateView.as_view()... | [
0,
1,
2,
3
] |
from matplotlib import pyplot as plt
# Function for testing
# Maps x => x*x
def calculate(x):
return x * x
inputs = [-0.5, -0.4, -0.3, -0.2, -0.1, 0, 0.1, 0.2, 0.3, 0.4, 0.5]
outputs = [calculate(x) for x in inputs]
plt.plot(inputs, outputs)
plt.savefig("plot.png") | normal | {
"blob_id": "1b3891565f776064cfcca02fb22ea65853f7e66f",
"index": 3629,
"step-1": "<mask token>\n\n\ndef calculate(x):\n return x * x\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef calculate(x):\n return x * x\n\n\n<mask token>\nplt.plot(inputs, outputs)\nplt.savefig('plot.png')\n",
"step-3": "<... | [
1,
2,
3,
4,
5
] |
"""This file parses vbulletin forums"""
import re
import logging
from BeautifulSoup import BeautifulSoup as bs
import imaget
import pdb
logger = logging.getLogger(__name__)
logger.setLevel(logging.DEBUG)
date_marker = ["<!-- status icon and date -->", "<!-- / status icon and date -->"]
message_marker = ["<!-- messa... | normal | {
"blob_id": "0846f73482ad86158c3f4e37713d6d965e21d796",
"index": 2671,
"step-1": "\"\"\"This file parses vbulletin forums\"\"\"\n\nimport re\nimport logging\nfrom BeautifulSoup import BeautifulSoup as bs\nimport imaget\nimport pdb\n\nlogger = logging.getLogger(__name__)\nlogger.setLevel(logging.DEBUG)\n\n\ndate_... | [
0
] |
from flask import Flask, url_for, render_template, request
import os
import blescan
import sys
import requests
import logging
from logging.handlers import RotatingFileHandler
import json
from datetime import datetime
import bluetooth._bluetooth as bluez
app = Flask(__name__)
@app.route('/sivut/')
def default_... | normal | {
"blob_id": "040942e2e09b5c2df5c08207b9c033471b117608",
"index": 500,
"step-1": " \nfrom flask import Flask, url_for, render_template, request\nimport os\nimport blescan\nimport sys\nimport requests\nimport logging\nfrom logging.handlers import RotatingFileHandler\nimport json\nfrom datetime import datetime\n... | [
0
] |
<|reserved_special_token_0|>
class SystemTrayIcon(QSystemTrayIcon):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def set_icon_state(self, state):
pixmap = QApplication.instance().windowIcon().pixmap(256, 256, state)
self.setIcon(QIcon(pixmap))
<|reserved_special_token_1|>
... | flexible | {
"blob_id": "c6e315d7dd44b998f64eee079f2d8455ffecdc30",
"index": 9931,
"step-1": "<mask token>\n\n\nclass SystemTrayIcon(QSystemTrayIcon):\n <mask token>\n <mask token>\n\n def set_icon_state(self, state):\n pixmap = QApplication.instance().windowIcon().pixmap(256, 256, state)\n self.setIc... | [
2,
3,
4,
5
] |
#"countinu" example : repeat printing "Too small" or "Input is..." according to input's lenth
while True:
s=raw_input('Enter something: ')
if s == 'quit' :
break
if len(s) <3:
print 'Too small'
continue
#continue : not exc... | normal | {
"blob_id": "915d6547057f43c1cc5d96d9cb4529c56bc85559",
"index": 3412,
"step-1": "#\"countinu\" example : repeat printing \"Too small\" or \"Input is...\" according to input's lenth\r\n\r\nwhile True:\r\n s=raw_input('Enter something: ')\r\n if s == 'quit' :\r\n break\r\n if l... | [
0
] |
from src.testcase.case import Case
from src.utils import *
from src.protocol.register import get_conn
from src.precondition import *
class OneCase(object):
"""
Main flow of running one case's autotest
"""
PASS = True
FAIL = False
def __init__(self, case_path, *args, **kwargs):
self._c... | normal | {
"blob_id": "f658959bf7fa5e02a577119930c9b9c1ef59f432",
"index": 2845,
"step-1": "<mask token>\n\n\nclass OneCase(object):\n <mask token>\n <mask token>\n <mask token>\n\n def __init__(self, case_path, *args, **kwargs):\n self._case_path = str(case_path)\n self._case_dict = {}\n ... | [
7,
9,
10,
13,
14
] |
#
# * Python 57, Correct Lineup
# * Easy
# * For the opening ceremony of the upcoming sports event an even number of
# * athletes were picked. They formed a correct lineup, i.e. such a lineup in
# * which no two boys or two girls stand together. The first person in the lineup
# * was a girl. As a part of the perfor... | normal | {
"blob_id": "6c5f60e7a122e3da5e6705bfacf73a361f6c1362",
"index": 1120,
"step-1": "def correctLineup1(athletes: list) ->list:\n return [(athletes[i + 1] if i % 2 == 0 else athletes[i - 1]) for i in\n range(len(athletes))]\n\n\n<mask token>\n",
"step-2": "def correctLineup1(athletes: list) ->list:\n ... | [
1,
2,
3,
4,
5
] |
# coding=utf-8
# Copyright 2021-Present The THUCTC Authors
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import math
import torch
import torch.nn as nn
import thuctc.utils as utils
from thuctc.modules.module import Module
from thuctc.modules.layer_norm ... | normal | {
"blob_id": "c773b273ad6953bf9c74b11c44aff16e9fd0860e",
"index": 3468,
"step-1": "<mask token>\n\n\nclass Embedding(Module):\n\n def __init__(self, embed_nums, embed_dims, bias=False, name='embedding'):\n super(Embedding, self).__init__(name=name)\n self.embed_nums = embed_nums\n self.emb... | [
7,
9,
10,
12,
13
] |
from __future__ import annotations
import asyncio
import signal
from functools import wraps
from typing import TYPE_CHECKING, Awaitable, Callable
import click
from .utils import import_obj
if TYPE_CHECKING:
from donald.manager import Donald
from .types import TV
def import_manager(path: str) -> Donald:
... | normal | {
"blob_id": "3da4896f368f067a339db5cc89201c93ba8166ce",
"index": 6220,
"step-1": "<mask token>\n\n\ndef process_await(fn: Callable[..., Awaitable[TV]]) ->Callable[..., TV]:\n\n @wraps(fn)\n @click.pass_context\n def wrapper(ctx, *args, **kwargs):\n loop = ctx.obj['loop']\n return loop.run_... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
def project(X, U, p=None):
if p == None:
p = X.shape[1]
Z = np.matmul(X, U)
Z[:, p:] = np.mean(Z[:, p:], axis=0)
X2 = np.matmul(Z, U.transpose())
return Z, X2
<|reserved_special_token_0|>
def whiteningTransform(X, W, U):
L = np.diag(W)
Z = np.transp... | flexible | {
"blob_id": "c00db6d6fd903236de37ccc029ed30fd46dccdef",
"index": 7711,
"step-1": "<mask token>\n\n\ndef project(X, U, p=None):\n if p == None:\n p = X.shape[1]\n Z = np.matmul(X, U)\n Z[:, p:] = np.mean(Z[:, p:], axis=0)\n X2 = np.matmul(Z, U.transpose())\n return Z, X2\n\n\n<mask token>\n\... | [
2,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
class PayForList(LoginRequiredMixin, ListView):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class PayForDetailView(LoginRequiredMixin, DetailView):
template_name = 'money_easy/payfor_detail.html'
model = PayFor
<|reserved_sp... | flexible | {
"blob_id": "dc9b5fbe082f7cf6cd0a9cb0d1b5a662cf3496f0",
"index": 4768,
"step-1": "<mask token>\n\n\nclass PayForList(LoginRequiredMixin, ListView):\n <mask token>\n <mask token>\n\n\n<mask token>\n\n\nclass PayForDetailView(LoginRequiredMixin, DetailView):\n template_name = 'money_easy/payfor_detail.htm... | [
22,
23,
28,
29,
31
] |
"""
进程对象属性
"""
from multiprocessing import Process
import time
def tm():
for i in range(3):
print(time.ctime())
time.sleep(2)
p = Process(target=tm,name='Tarena')
# 设置子进程随父进程退出
p.daemon = True
p.start()
print("Name:",p.name) # 进程名称
print("PID:",p.pid) # 进程PID
print("is alive：",p.is_alive()) #... | normal | {
"blob_id": "9d7bc2d93b855fbd22a4707a6237ac51069beb53",
"index": 9385,
"step-1": "<mask token>\n\n\ndef tm():\n for i in range(3):\n print(time.ctime())\n time.sleep(2)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef tm():\n for i in range(3):\n print(time.ctime())\n ti... | [
1,
2,
3,
4,
5
] |
from django import forms
from django.contrib.auth.forms import UserCreationForm
from django.contrib.auth.models import User
from . import models
class RegisterForm(UserCreationForm):
email = forms.EmailField(required=True)
class Meta:
model = User
fields = ("username", "email", "password1", "... | normal | {
"blob_id": "503726cd2d70286189f4b8e02acaa3d5f6e29e12",
"index": 8538,
"step-1": "<mask token>\n\n\nclass ChangeEmail(forms.Form):\n <mask token>\n\n\nclass ChangePassword(forms.Form):\n oldPassword = forms.CharField(required=True, min_length=8, max_length=\n 80, widget=forms.PasswordInput(attrs={'n... | [
3,
5,
6,
7,
8
] |
# -*- coding: utf-8 -*-
# Generated by Django 1.9.8 on 2016-10-28 17:08
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('KYusers', '0017_caprofile_regs'),
]
operations = [
migrations.AddField(
... | normal | {
"blob_id": "12c3fe8a3ca1e660eeb90b16eca17eddd47e5de7",
"index": 7124,
"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 = [('KYusers', '... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
# Generated by Django 1.11.10 on 2018-02-26 13:14
from __future__ import unicode_literals
import datetime
from django.db import migrations, models
import django.db.models.deletion
from django.utils.timezone import utc
class Migration(migrations.Migration):
dependencies = [
('user... | normal | {
"blob_id": "c6170678b523a105312d8ce316853859657d3c94",
"index": 2235,
"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 = [('user_detail... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import cProfile
import re
import pstats
import os
import functools
# cProfile.run('re.compile("foo|bar")')
def do_cprofile(filename):
"""
decorator for function profiling
:param filename:
:return:
"""
def wrapper(func):
@functools.wraps... | normal | {
"blob_id": "8c055816def1c0a19e672ab4386f9b9a345b6323",
"index": 7837,
"step-1": "<mask token>\n\n\nclass Memoized(object):\n\n def __init__(self, func):\n self.func = func\n self.results = {}\n <mask token>\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass Memoized... | [
2,
4,
7,
8,
9
] |
with open('vocabulary.txt', 'r') as f:
for line in f:
information = line.strip().split(': ')
# print(information[0], information[1])
question = information[1]
answer = information[0]
my_answer = input(f'{question}:')
if my_answer == answer:
print('맞았습니다!'... | normal | {
"blob_id": "34009d1aa145f4f5c55d0c5f5945c3793fbc6429",
"index": 7823,
"step-1": "<mask token>\n",
"step-2": "with open('vocabulary.txt', 'r') as f:\n for line in f:\n information = line.strip().split(': ')\n question = information[1]\n answer = information[0]\n my_answer = input... | [
0,
1,
2
] |
import unittest
from theoktany.serializers import serialize
class SerializerTest(unittest.TestCase):
class TestObject(object):
def __init__(self, **kwargs):
for name, value in kwargs.items():
self.__setattr__(name, value)
def test_serialize(self):
object_dict = ... | normal | {
"blob_id": "4e4d6a9ed07aa03c79dade05e01f226017b13de5",
"index": 9250,
"step-1": "<mask token>\n\n\nclass SerializerTest(unittest.TestCase):\n\n\n class TestObject(object):\n\n def __init__(self, **kwargs):\n for name, value in kwargs.items():\n self.__setattr__(name, value)\n... | [
3,
4,
5,
7
] |
import sys
sys.stdin = open('줄긋기.txt')
T = int(input())
for tc in range(1, T + 1):
N = int(input())
dot = [list(map(int, input().split())) for _ in range(N)]
ran = []
for a in range(N - 1):
for b in range(a + 1, N):
if dot[a][1] - dot[b][1] == 0:
if 'inf' not in ran:
... | normal | {
"blob_id": "03854f48751460fdc27d42ee5c766934ee356cfd",
"index": 6161,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor tc in range(1, T + 1):\n N = int(input())\n dot = [list(map(int, input().split())) for _ in range(N)]\n ran = []\n for a in range(N - 1):\n for b in range(a + 1, N)... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def write_csv(filename, train_acc, test_acc, train_loss, test_loss,
train_error, test_error, epoch):
if epoch == 0:
with open(filename, 'w') as f:
f.write(
'train_acc,test_acc,train_lo... | flexible | {
"blob_id": "93150eb1c6746e2b1967eb5305fa526ae36968fd",
"index": 2003,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef write_csv(filename, train_acc, test_acc, train_loss, test_loss,\n train_error, test_error, epoch):\n if epoch == 0:\n with open(filename, 'w') as f:\n f.wr... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(fruits)
<|reserved_special_token_1|>
fruits = ['orange', ' apple', 'pear', 'banana', 'kiwi']
print(fruits)
<|reserved_special_token_1|>
# common methods to delete data from list
fruits = ['orange', ' apple', 'pear', '... | flexible | {
"blob_id": "a245cb1f232b152edf40b6399686c6811c522d99",
"index": 6458,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(fruits)\n",
"step-3": "fruits = ['orange', ' apple', 'pear', 'banana', 'kiwi']\nprint(fruits)\n",
"step-4": "# common methods to delete data from list\r\nfruits = ['orange', ' a... | [
0,
1,
2,
3
] |
__author__ = "那位先生Beer"
import matplotlib.pyplot as plt
from matplotlib.font_manager import FontProperties
import xlrd
import numpy as np
print('输入鲈鱼的先验概率例如：70，对应70%')
a=input('输入鲈鱼的先验概率（鲑鱼对应的1减去剩余的）：')
font_set = FontProperties(fname=r"c:\windows\fonts\simsun.ttc", size=15)
#根据生成的数据画出图像（横坐标为长度，纵坐标为亮度）
data=xlrd.open_w... | normal | {
"blob_id": "077b6d3d7417bbc26e9f23af6f437ff05e3d5771",
"index": 812,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('输入鲈鱼的先验概率例如：70，对应70%')\n<mask token>\nfor i in range(0, int(a) * 50):\n rowa_data = sh.row_values(i)\n L.append(rowa_data)\n<mask token>\nfor j in range(5000, 5000 + (100 - in... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class TestVCSBoxfill(basevcstest.VCSBaseTest):
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class TestVCSBoxfill(basevcstest.VCSBaseTest):
def testRobinsonBoxfill(self):
... | flexible | {
"blob_id": "c1475209d9c9a98d72d7f703e0516aceaeb13163",
"index": 6820,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass TestVCSBoxfill(basevcstest.VCSBaseTest):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass TestVCSBoxfill(basevcstest.VCSBaseTest):\n\n def testRobinsonBoxfill(self)... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Nov 18 18:21:37 2021
@author: benoitdeschrynmakers
"""
import requests
url = 'http://127.0.0.1:8888/productionplan'
if __name__ == "__main__":
filename = "example_payloads/payload1.json"
data = open(filename, 'rb').read()
headers = {'Acc... | normal | {
"blob_id": "255130082ee5f8428f1700b47dee717465fed72f",
"index": 4067,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n filename = 'example_payloads/payload1.json'\n data = open(filename, 'rb').read()\n headers = {'Accept': 'application/json', 'Content-Type': 'applicat... | [
0,
1,
2,
3,
4
] |
import ambulance_game as abg
import numpy as np
import sympy as sym
from sympy.abc import a, b, c, d, e, f, g, h, i, j
def get_symbolic_pi(num_of_servers, threshold, system_capacity, buffer_capacity):
Q_sym = abg.markov.get_symbolic_transition_matrix(
num_of_servers=num_of_servers,
threshold=thres... | normal | {
"blob_id": "9dd59fee46bd4bec87cc8c40099110b483ad0496",
"index": 6990,
"step-1": "<mask token>\n\n\ndef get_symbolic_state_probabilities_1222():\n num_of_servers = 1\n threshold = 2\n system_capacity = 2\n buffer_capacity = 2\n sym_pi_1222 = get_symbolic_pi(num_of_servers=num_of_servers, threshold... | [
5,
12,
13,
16,
17
] |
#!/usr/bin/env python3
import os
import subprocess
import logging
class color:
PURPLE = '\033[95m'
CYAN = '\033[96m'
DARKCYAN = '\033[36m'
BLUE = '\033[94m'
GREEN = '\033[92m'
YELLOW = '\033[93m'
RED = '\033[91m'
BOLD = '\033[1m'
UNDERLINE = '\033[4m'
END = '\033[0m'
# Recov... | normal | {
"blob_id": "2c834c734de8f8740176bb5dbb6b123c49924718",
"index": 1697,
"step-1": "<mask token>\n\n\nclass color:\n PURPLE = '\\x1b[95m'\n CYAN = '\\x1b[96m'\n DARKCYAN = '\\x1b[36m'\n BLUE = '\\x1b[94m'\n GREEN = '\\x1b[92m'\n YELLOW = '\\x1b[93m'\n RED = '\\x1b[91m'\n BOLD = '\\x1b[1m'\n... | [
5,
7,
9,
10,
12
] |
from estmd import ESTMD
input_directory = "test.avi"
e = ESTMD()
e.open_movie(input_directory)
e.run(by_frame=True)
r = e.create_list_of_arrays()
print "Done testing!"
| normal | {
"blob_id": "1fd4d1a44270ef29512e601af737accb916dc441",
"index": 974,
"step-1": "from estmd import ESTMD\n\ninput_directory = \"test.avi\"\ne = ESTMD()\ne.open_movie(input_directory)\ne.run(by_frame=True)\nr = e.create_list_of_arrays()\n\nprint \"Done testing!\"\n",
"step-2": null,
"step-3": null,
"step-4"... | [
0
] |
__author__ = 'simon.hughes'
from sklearn.feature_extraction import DictVectorizer
from WindowFeatures import compute_middle_index
from collections import Counter
class WindowFeatureExtractor(object):
"""
A simple wrapper class that takes a number of window based feature extractor
functions and applies the... | normal | {
"blob_id": "48677d73f6489ce789884a9dff5d50c23f47d8b3",
"index": 260,
"step-1": "<mask token>\n\n\nclass WindowFeatureExtractor(object):\n <mask token>\n <mask token>\n <mask token>\n\n def transform(self, X, y=None):\n return self.vectorizer.transform(X, y)\n <mask token>\n <mask token>... | [
2,
7,
8,
9,
10
] |
# System import
import os
# Docutils import
from docutils import nodes
from docutils.parsers.rst.directives.admonitions import BaseAdmonition
from docutils.statemachine import ViewList
# Add node
class link_to_block(nodes.Admonition, nodes.Element):
""" Node for inserting a link to button."""
pass
# Add di... | normal | {
"blob_id": "63cce356b792949b90b215e0a5826f7b33d2d375",
"index": 8064,
"step-1": "<mask token>\n\n\nclass link_to_block(nodes.Admonition, nodes.Element):\n <mask token>\n pass\n\n\nclass LinkToBlock(BaseAdmonition):\n \"\"\" Hidden technical block\"\"\"\n node_class = link_to_block\n has_content =... | [
5,
6,
7,
9,
11
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def clean_room(update):
char, db_sess = get_data_character(update, return_sess=True)
if char and char.room:
if char.room.mobs:
for mob in char.room.mobs:
db_sess.delete(mob)
if... | flexible | {
"blob_id": "4d57fa22282d7b3f8adabedd7a04e32767181890",
"index": 5693,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef clean_room(update):\n char, db_sess = get_data_character(update, return_sess=True)\n if char and char.room:\n if char.room.mobs:\n for mob in char.room.mob... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
urlpatterns = [path('', views.index, name='listings'), path(
'<int:listing_id>', views.listing, name='listing'), path('search',
views.search, name='search')]
<|reserved_special_token_1|>
from django.urls import path
fro... | flexible | {
"blob_id": "be894830bb0dde6bacaea6be823391e0445603c3",
"index": 1192,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('', views.index, name='listings'), path(\n '<int:listing_id>', views.listing, name='listing'), path('search',\n views.search, name='search')]\n",
"step-3": "fr... | [
0,
1,
2,
3
] |
import functools
import shutil
import tempfile
import unittest
import unittest.mock
from pathlib import Path
import numpy as np
import pandas as pd
import one.alf.io as alfio
from ibllib.io.extractors import training_trials, biased_trials, camera
from ibllib.io import raw_data_loaders as raw
from ibllib.io.extractors... | normal | {
"blob_id": "f17d33f1d035da42dc9a2b4c0c60beefc6a48dea",
"index": 64,
"step-1": "<mask token>\n\n\nclass TestExtractTrialData(unittest.TestCase):\n\n def setUp(self):\n self.main_path = Path(__file__).parent\n self.training_lt5 = {'path': self.main_path / 'data' /\n 'session_training_l... | [
27,
34,
37,
45,
49
] |
<|reserved_special_token_0|>
class SnakeGame:
def __init__(self, board_width=10, board_height=10, gui=False,
enemy_epsilon=0.1):
self.score = 0
self.board = {'width': board_width, 'height': board_height}
self.gui = gui
self.lives = LIVES
self.player = []
se... | flexible | {
"blob_id": "3bb408f2b2ac63a2555258c05844881ccdfc5057",
"index": 5428,
"step-1": "<mask token>\n\n\nclass SnakeGame:\n\n def __init__(self, board_width=10, board_height=10, gui=False,\n enemy_epsilon=0.1):\n self.score = 0\n self.board = {'width': board_width, 'height': board_height}\n ... | [
12,
14,
18,
22,
24
] |
#!/usr/bin/env python
"""
##############################################################################
Software Package Risk Analysis Development Environment Specific Work Book View
##############################################################################
"""
# -*- coding: utf-8 -*-
#
# rtk.softw... | normal | {
"blob_id": "327371d373819273a2f77f63e0cedee6950dbc46",
"index": 976,
"step-1": "<mask token>\n\n\nclass RiskAnalysis(gtk.VPaned):\n <mask token>\n <mask token>\n\n def create_risk_analysis_page(self, notebook):\n \"\"\"\n Method to create the development environment risk analysis page and... | [
4,
5,
7,
9,
10
] |
# -*- coding: utf-8 -*-
import logging
from django.contrib.auth import authenticate, login as django_login, logout as django_logout
from django.contrib.auth.models import User
from django.core.paginator import Paginator, EmptyPage, PageNotAnInteger
from django.core.urlresolvers import reverse
from django.db.utils imp... | normal | {
"blob_id": "b739a5d359b4d1c0323c7cd8234e4fe5eb9f3fcb",
"index": 6286,
"step-1": "<mask token>\n\n\n@require_superuser\ndef index(request):\n template_name = 'users/index.html'\n msg = ''\n try:\n users = User.objects.exclude(id=request.user.id)\n except:\n msg = _('Unable to list users... | [
8,
9,
10,
11,
12
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
client.request(method='POST', url='/', body=post_data.encode('utf-8'),
headers=head_dict)
<|reserved_special_token_0|>
client.close()
print(content)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
client = http.cl... | flexible | {
"blob_id": "ee1ce3ea4b31246703530478d6550b0c8866197e",
"index": 1190,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nclient.request(method='POST', url='/', body=post_data.encode('utf-8'),\n headers=head_dict)\n<mask token>\nclient.close()\nprint(content)\n",
"step-3": "<mask token>\nclient = http.c... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def longest_substring(string1, string2):
mat = np.zeros(shape=(len(string1), len(string2)))
for x in range(len(string1)):
for y in range(len(string2)):
if x == 0 or y == 0:
if string1[... | flexible | {
"blob_id": "6bb7dafea73aff7aca9b0ddc1393e4db6fcf0151",
"index": 4828,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef longest_substring(string1, string2):\n mat = np.zeros(shape=(len(string1), len(string2)))\n for x in range(len(string1)):\n for y in range(len(string2)):\n ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def run_main():
"""
Main function to process user input and then generate the description files for each run
:return: exit code -- 0 on success, 1 otherwise
"""
parser = argparse.ArgumentParser(description=
... | flexible | {
"blob_id": "6e6c6c5795e8723a86ae5dfc8f40df57d3dd10f7",
"index": 3336,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef run_main():\n \"\"\"\n Main function to process user input and then generate the description files for each run\n\n :return: exit code -- 0 on success, 1 otherwise\n \... | [
0,
1,
2,
3,
4
] |
from typing import Dict, List, Sequence, Iterable, Tuple
from allennlp.data.dataset_readers.dataset_reader import DatasetReader
from allennlp.data.instance import Instance
from allennlp.common.file_utils import cached_path
import logging
from overrides import overrides
import itertools
from allennlp.data.tokenizers imp... | normal | {
"blob_id": "21172985bf36302f6b0b2101e353d9fbcafb0673",
"index": 6653,
"step-1": "<mask token>\n\n\n@DatasetReader.register('bertclassification')\nclass ClassificationReader(DatasetReader):\n <mask token>\n\n @overrides\n def _read(self, file_path: str) ->Iterable[Instance]:\n file_path = cached_... | [
3,
4,
5,
6,
7
] |
# ARGS:
# 1: total train reviews
# 2: number of iterations (for csv output)
# 3: size of vector
# 4: good/bad sizes
# import dependencies
from gensim import utils
from gensim.models.doc2vec import LabeledSentence
from gensim.models import Doc2Vec
from matplotlib import pyplot as plt
from sklearn.manifold import TSNE
f... | normal | {
"blob_id": "95015c467dd6371f575fb5535fe652a914650ef1",
"index": 2016,
"step-1": "<mask token>\n\n\ndef compute_accuracy(model, good, bad):\n train_arrays = numpy.zeros((25000, 400))\n train_labels = numpy.zeros(25000)\n classifier = LogisticRegression()\n for i in range(25000 / 2):\n prefix_t... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for _ in stack_numbers:
stacks.append([])
for line in stacks_input_lines[:-1]:
for stack_index, i in enumerate(range(1, len(line), 4)):
crate = line[i]
if crate != ' ':
stacks[stack_index].inser... | flexible | {
"blob_id": "4927a440093e822250af25dfd6a2ce62d7cc099e",
"index": 8786,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor _ in stack_numbers:\n stacks.append([])\nfor line in stacks_input_lines[:-1]:\n for stack_index, i in enumerate(range(1, len(line), 4)):\n crate = line[i]\n if cra... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def test_relative_path(session_app_data, monkeypatch):
sys_executable = Path(PythonInfo.current_system(app_data=
session_app_data).system_executable)
cwd = sys_executable.parents[1]
monkeypatch.chdir(str(cwd))
relative = str(sys_executable.relative_to(cwd))
res... | flexible | {
"blob_id": "55d4f4bba2b72ec93cb883527d2a9c2ebe8ec337",
"index": 4910,
"step-1": "<mask token>\n\n\ndef test_relative_path(session_app_data, monkeypatch):\n sys_executable = Path(PythonInfo.current_system(app_data=\n session_app_data).system_executable)\n cwd = sys_executable.parents[1]\n monkeyp... | [
1,
4,
5,
6,
7
] |
'''
You're playing casino dice game. You roll a die once. If you reroll, you earn the amount equal to the number on your second roll otherwise, you earn the amount equal to the number on your first roll.
Assuming you adopt a profit-maximizing strategy, what would be the expected amount of money you would win?
This qu... | normal | {
"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
] |
<|reserved_special_token_0|>
def __line_into_col__(line):
tokens = dl_style_transfer.workspace.data_helpers.clean_str(line).split(' '
)
for wor in tokens:
if col.get(wor) is None:
col[wor] = 1
else:
col[wor] = col[wor] + 1
<|reserved_special_token_0|>
def vo... | flexible | {
"blob_id": "2317a2fff493588ad6cc3a4ac2b600fbf1c5583c",
"index": 8594,
"step-1": "<mask token>\n\n\ndef __line_into_col__(line):\n tokens = dl_style_transfer.workspace.data_helpers.clean_str(line).split(' '\n )\n for wor in tokens:\n if col.get(wor) is None:\n col[wor] = 1\n ... | [
2,
4,
6,
8,
10
] |
<|reserved_special_token_0|>
class WRITE_TO_FILE(tarr.compiler_base.Instruction):
@property
def __name__(self):
return 'POINT OF INTEREST - WRITE("{}")'.format(self.filename)
def __init__(self, filename, formatter=format_data):
self.format = formatter
self.filename = filename
... | flexible | {
"blob_id": "75393d39b147097a7ac1d82938ac102491ea9441",
"index": 8469,
"step-1": "<mask token>\n\n\nclass WRITE_TO_FILE(tarr.compiler_base.Instruction):\n\n @property\n def __name__(self):\n return 'POINT OF INTEREST - WRITE(\"{}\")'.format(self.filename)\n\n def __init__(self, filename, formatte... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
class _ab_test_plotting(_ab_test_utils):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def plot_pos... | flexible | {
"blob_id": "3eaa898d1428e48aeb0449c7216d0a994262f76a",
"index": 9107,
"step-1": "<mask token>\n\n\nclass _ab_test_plotting(_ab_test_utils):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def plot_positive_lift(self, variant_on... | [
2,
5,
7,
10,
12
] |
<|reserved_special_token_0|>
class StereoBM:
<|reserved_special_token_0|>
def runAsync(self, left_img, right_img):
self.m_runStartTime = int(round(time.time() * 1000000))
if left_img is None:
raise RuntimeError('Invalid left image')
if right_img is None:
raise ... | flexible | {
"blob_id": "66f3590381fe96c49a8926a806b4a845f0d7e25d",
"index": 4681,
"step-1": "<mask token>\n\n\nclass StereoBM:\n <mask token>\n\n def runAsync(self, left_img, right_img):\n self.m_runStartTime = int(round(time.time() * 1000000))\n if left_img is None:\n raise RuntimeError('Inv... | [
4,
5,
6,
7,
8
] |
# Generated by Django 3.2.4 on 2021-06-16 13:41
import ckeditor.fields
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('FAQ', '0004_auto_20210616_1253'),
]
operations = [
migrations.RemoveField(
model_name='question',
nam... | normal | {
"blob_id": "a4c4a5cc63c345d1fa8cbf426f7857a0f3d4357f",
"index": 8360,
"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 = [('FAQ', '0004... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def findNearestPoint(points, no_used, src):
dest = src
minDist = sys.float_info.max
for i in range(len(points)):
if no_used[i] and i != src:
dist = utils.length(points[src], points[i])
... | flexible | {
"blob_id": "943db90aa7721ddad3d7f5103c4d398fbf4e143b",
"index": 2768,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef findNearestPoint(points, no_used, src):\n dest = src\n minDist = sys.float_info.max\n for i in range(len(points)):\n if no_used[i] and i != src:\n dist ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class projectile(pygame.sprite.Sprite):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class enemy(pygame.sprite.Sprite):
im = pygame.image.load(os.path.join(path, 'Gallery', 'stateczek.png'))
im2 = pygame.image.load(os.path.jo... | flexible | {
"blob_id": "0dd5511c0e39f113c46785be78a898e79bc45a21",
"index": 5188,
"step-1": "<mask token>\n\n\nclass projectile(pygame.sprite.Sprite):\n <mask token>\n <mask token>\n <mask token>\n\n\nclass enemy(pygame.sprite.Sprite):\n im = pygame.image.load(os.path.join(path, 'Gallery', 'stateczek.png'))\n ... | [
6,
9,
13,
14,
18
] |
#########################################################
# Author: Todd A. Reisel
# Date: 2/24/2003
# Class: StaticTemplateList
#########################################################
from BaseClasses.TemplateList import *;
class StaticTemplateList(TemplateList):
def __init__(self, viewMode = None):
Te... | normal | {
"blob_id": "7de3c0ab2e7c8ac00d37f1dfb5948027cfa7806c",
"index": 5084,
"step-1": "<mask token>\n\n\nclass StaticTemplateList(TemplateList):\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass StaticTemplateList(TemplateList):\n\n def __init__(self, viewMode=None):\n ... | [
1,
3,
4,
5,
6
] |
"""
A module to generate simulated 2D time-series SOSS data
Authors: Joe Filippazzo
"""
import os
from pkg_resources import resource_filename
import multiprocessing
import time
from functools import partial
import warnings
import numpy as np
from astropy.io import fits
from bokeh.plotting import figure, show
from ho... | normal | {
"blob_id": "9f478df4ff19cfe6c6559b6489c874d49377b90e",
"index": 4949,
"step-1": "<mask token>\n\n\ndef calculate_psf_tilts():\n \"\"\"\n Calculate the tilt of the psf at the center of each column\n using all binned pixels in the given wavelength calibration file\n for both orders and save to file\n ... | [
7,
10,
11,
13,
14
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class CameraResponse(Response):
pass
<|reserved_special_token_1|>
from platypush.message.response import Response
class CameraResponse(Response):
pass
<|reserved_special_token_1|>
from platypush.message.response ... | flexible | {
"blob_id": "4c38d0487f99cdc91cbce50079906f7336e51482",
"index": 5462,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass CameraResponse(Response):\n pass\n",
"step-3": "from platypush.message.response import Response\n\n\nclass CameraResponse(Response):\n pass\n",
"step-4": "from platypu... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def get_ticket():
ticket = ''
s = 'abcdefghijkrmnopqrstuvwxyz1234567890'
for i in range(28):
r_num = random.choice(s)
ticket += r_num
return ticket
<|reserved_special_token_1|>
import random
... | flexible | {
"blob_id": "d2a9a2fd3a1118c0855b8f77ce4c25cc6b4e8f87",
"index": 4328,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_ticket():\n ticket = ''\n s = 'abcdefghijkrmnopqrstuvwxyz1234567890'\n for i in range(28):\n r_num = random.choice(s)\n ticket += r_num\n return tick... | [
0,
1,
2
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Time : 2019/4/14 14:31
# @Author : lixiaofeng
# @File : page_zaojiao.py
# @Software: PyCharm
# @desc :
from common.basics import Crazy
class Zaojiaopage(Crazy):
"""早教小程序"""
zao_btn_loc = ('xpath', '//*[@resource-id="com.tencent.mm:id/cx" and @text="... | normal | {
"blob_id": "1980fb4d6e7d3c6fe51f4a242610b5489e553859",
"index": 128,
"step-1": "<mask token>\n\n\nclass Zaojiaopage(Crazy):\n <mask token>\n <mask token>\n\n def click_zao(self):\n self.click(self.zao_btn_loc)\n <mask token>\n <mask token>\n\n def click_find(self):\n self.click(s... | [
73,
89,
121,
148,
152
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def select_from_model(dataframe):
X = dataframe.iloc[:, :-1]
y = dataframe.iloc[:, -1]
np.random.seed(9)
model = RandomForestClassifier()
sfm = SelectFromModel(model)
sfm = sfm.fit(X, y)
feature_idx =... | flexible | {
"blob_id": "d6791c8122129a46631582e7d9339ea08bd2e92b",
"index": 3183,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef select_from_model(dataframe):\n X = dataframe.iloc[:, :-1]\n y = dataframe.iloc[:, -1]\n np.random.seed(9)\n model = RandomForestClassifier()\n sfm = SelectFromMode... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class State(DocumentTemplate):
_key = ValueHashKey()
country: 'Country'
name: str
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Address(DocumentTemplate):
<|reserved_special_token_0|>
city: 'City'
coordinates: List['Coordinates']
postal_c... | flexible | {
"blob_id": "f702cdef3782ddc96244f3cf8e2026581d60baa9",
"index": 1537,
"step-1": "<mask token>\n\n\nclass State(DocumentTemplate):\n _key = ValueHashKey()\n country: 'Country'\n name: str\n",
"step-2": "<mask token>\n\n\nclass Address(DocumentTemplate):\n <mask token>\n city: 'City'\n coordin... | [
2,
13,
14,
15,
16
] |
import json
import boto3
import os
from helper import getEC2Regions, sendDataToSNS, OPTOUT_TAG, SNS_NOTIFICATION_IIAS_EC2
def getEC2FilteredRegionalInstanceInfo(region):
ec2RegionalClient = boto3.client('ec2', region_name = region)
paginator = ec2RegionalClient.get_paginator('describe_instances')
page_ite... | normal | {
"blob_id": "d5f1601d11eb54e6c3dafab0137ec8f2358bb568",
"index": 4101,
"step-1": "<mask token>\n\n\ndef getEC2FilteredRegionalInstanceInfo(region):\n ec2RegionalClient = boto3.client('ec2', region_name=region)\n paginator = ec2RegionalClient.get_paginator('describe_instances')\n page_iterator = paginato... | [
3,
4,
5,
6,
7
] |
#coding=utf-8
from django import template
from classytags.helpers import InclusionTag
from classytags.core import Tag, Options
from classytags.arguments import Argument
from ratings.models import RatedItem
from blogs.permissions import Permissions
class RatingBlock(InclusionTag):
name = 'rating'
template = '... | normal | {
"blob_id": "1a05817c4c16f2d9234e504b0c98f9c9ae2dc3f7",
"index": 1525,
"step-1": "<mask token>\n\n\nclass RatingBlock(InclusionTag):\n name = 'rating'\n template = 'ratings/rating.html'\n options = Options(Argument('obj', required=True))\n\n def get_context(self, context, obj):\n if not hasatt... | [
3,
4,
5,
6,
7
] |
from pynput.keyboard import Listener
import logging
import daemon
import socket
import thread
logging.basicConfig(format="%(asctime)s:%(message)s")
file_logger = logging.FileHandler("/home/user0308/logger.log", "a")
logger = logging.getLogger()
logger.addHandler(file_logger)
logger.setLevel(logging.DEBUG)
def press(... | normal | {
"blob_id": "3dc2d9a5e37ce1f546c0478de5a0bb777238ad00",
"index": 4306,
"step-1": "<mask token>\n\n\ndef press(key):\n logging.info(key)\n\n\ndef work():\n with Listener(on_press=press) as listener:\n listener.join()\n\n\n<mask token>\n",
"step-2": "<mask token>\nlogging.basicConfig(format='%(ascti... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
@pytest.fixture(scope='session', autouse=True)
def set_up(request):
""" conftest.py set_up - the first to start.... """
print('\nSETUP before all tests')
request.addfinalizer(tear_down)
<|reserved_special_token_1|>... | flexible | {
"blob_id": "816b1a932208a4525230dd886adf8c67dec3af3e",
"index": 349,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@pytest.fixture(scope='session', autouse=True)\ndef set_up(request):\n \"\"\" conftest.py set_up - the first to start.... \"\"\"\n print('\\nSETUP before all tests')\n request... | [
0,
1,
2,
3,
4
] |
import os
from dataclasses import dataclass
from dotenv import load_dotenv
from fastapi.security import OAuth2PasswordBearer
from passlib.context import CryptContext
load_dotenv()
@dataclass
class Settings:
SECRET_KEY = os.getenv("SECRET_KEY", "mysecret")
ALGORITHM = "HS256"
ACCESS_TOKEN_EXPIRE_MINUTES ... | normal | {
"blob_id": "a1c5d86a3f042d9e5ba522726191c8aeb9b738ed",
"index": 8018,
"step-1": "<mask token>\n\n\n@dataclass\nclass Settings:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\nload_dotenv()\n\n\n@dataclass\nclass Settings:... | [
1,
3,
4,
5,
6
] |
def solution(name):
Len = len(name)
nameList = [name[i] for i in range(Len)]
nameField = ['A' for i in range(Len)]
answer = 0
# 정방향
for i in range(Len):
a = ord(nameField[i])
b = ord(nameList[i])
if b-a <= 13 : # 절반 이하면 그냥 더하고
answer += b-a
... | normal | {
"blob_id": "8766003a85b1ed83927988df147b0b3004cb91f9",
"index": 7691,
"step-1": "<mask token>\n",
"step-2": "def solution(name):\n Len = len(name)\n nameList = [name[i] for i in range(Len)]\n nameField = ['A' for i in range(Len)]\n answer = 0\n for i in range(Len):\n a = ord(nameField[i]... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def inverse_rescale(y):
return tf.round(tf.multiply(tf.add(y, 1), 127.5))
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def data_rescale(x):
return tf.subtract(tf.divide(x, 127.5), 1)
def inverse_resca... | flexible | {
"blob_id": "1a09b38838f40c4c6049da8e6a72ba3d56806c07",
"index": 3703,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef inverse_rescale(y):\n return tf.round(tf.multiply(tf.add(y, 1), 127.5))\n",
"step-3": "<mask token>\n\n\ndef data_rescale(x):\n return tf.subtract(tf.divide(x, 127.5), 1)\... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class coreGetHome(TestCase):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def test_200_template_home(self):
self.assertEqual(200, self.resp.status_code)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class coreGetHome(TestCase):
def s... | flexible | {
"blob_id": "d20e41dd7054ff133be264bebf13e4e218710ae5",
"index": 933,
"step-1": "<mask token>\n\n\nclass coreGetHome(TestCase):\n <mask token>\n <mask token>\n\n def test_200_template_home(self):\n self.assertEqual(200, self.resp.status_code)\n",
"step-2": "<mask token>\n\n\nclass coreGetHome(T... | [
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class QueueOutputMJPEG(object):
def __init__(self, queue, finished):
self.queue = queue
self.finished = finished
self.stream = io.BytesIO()
def write(self, buf):
if buf.startswith(b'\xff\xd8'):
size = self.stream.tell()
if ... | flexible | {
"blob_id": "ffd034eb5f0482c027dcc344bddb01b90249511c",
"index": 3198,
"step-1": "<mask token>\n\n\nclass QueueOutputMJPEG(object):\n\n def __init__(self, queue, finished):\n self.queue = queue\n self.finished = finished\n self.stream = io.BytesIO()\n\n def write(self, buf):\n i... | [
12,
13,
16,
17,
18
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def test_sendto_cli_runs_ok():
runner = CliRunner()
result = runner.invoke(cli, ['sendto'])
assert result.exit_code == 0
<|reserved_special_token_1|>
from click.testing import CliRunner
from apitest.actions.cli im... | flexible | {
"blob_id": "7537deb4560e880365b23a99584d0b1f8fa3daf4",
"index": 5675,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef test_sendto_cli_runs_ok():\n runner = CliRunner()\n result = runner.invoke(cli, ['sendto'])\n assert result.exit_code == 0\n",
"step-3": "from click.testing import CliR... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if x > 0 and y > 0:
print('1')
elif x > 0 and y < 0:
print('4')
elif x < 0 and y > 0:
print('2')
else:
print('3')
<|reserved_special_token_1|>
x = int(input())
y = int(input())
if x > 0 and y > 0:
print('1')... | flexible | {
"blob_id": "e9908e32204da8973f06d98430fc660c90b5e303",
"index": 3987,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif x > 0 and y > 0:\n print('1')\nelif x > 0 and y < 0:\n print('4')\nelif x < 0 and y > 0:\n print('2')\nelse:\n print('3')\n",
"step-3": "x = int(input())\ny = int(input()... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for i in range(0, y):
list.append(randint(1, 10))
<|reserved_special_token_0|>
print(f'Исходный список: {list}')
print(f'Новый список список: {new}')
<|reserved_special_token_1|>
<|reserved_special_token_0|>
list = []
y = i... | flexible | {
"blob_id": "bfc4f5e90b7c22a29d33ae9b4a5edfb6086d79f4",
"index": 2344,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(0, y):\n list.append(randint(1, 10))\n<mask token>\nprint(f'Исходный список: {list}')\nprint(f'Новый список список: {new}')\n",
"step-3": "<mask token>\nlist = []\ny =... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def parse_doc_line(line):
parsed = re.search('\\d[\\d\\s]+\\d', line)
return 'empty' if parsed is None else parsed[0]
def get_roc_point(clf, x_set, y_set, threshold):
loo = LeaveOneOut()
vectorizer = CountVectorizer(ngram_range=n_gram_range)
roc_predictions = np.empt... | flexible | {
"blob_id": "8bb67317ede277e03e8cbdefefeffa3d206ece65",
"index": 9434,
"step-1": "<mask token>\n\n\ndef parse_doc_line(line):\n parsed = re.search('\\\\d[\\\\d\\\\s]+\\\\d', line)\n return 'empty' if parsed is None else parsed[0]\n\n\ndef get_roc_point(clf, x_set, y_set, threshold):\n loo = LeaveOneOut(... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
def create_file(out_path, ref_path):
os.makedirs(out_path, exist_ok=True)
copyfile(os.path.join(ref_path, 'attributes.json'), os.path.join(
out_path, 'attributes.json'))
def copy_to_scratch(in_path, out_path, out_key):
if out_key in z5py.File(out_path, 'r'):
... | flexible | {
"blob_id": "9d3db4ca5bf964c68e9778a3625c842e74bf9dbd",
"index": 1228,
"step-1": "<mask token>\n\n\ndef create_file(out_path, ref_path):\n os.makedirs(out_path, exist_ok=True)\n copyfile(os.path.join(ref_path, 'attributes.json'), os.path.join(\n out_path, 'attributes.json'))\n\n\ndef copy_to_scratch... | [
3,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
plt.plot([1, 2, 3, 4, 5], [1, 2, 3, 4, 5], 'go-', label='line 1', linewidth=2)
plt.plot([1, 2, 3, 4, 5], [1, 4, 9, 16, 25], 'rs--', label='line 2',
linewidth=4)
plt.axis([0, 6, 0, 26])
plt.legend(loc='upper right')
plt.show()
... | flexible | {
"blob_id": "7eeba06e78bd1e7139b1706574c4d040465d4566",
"index": 4178,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nplt.plot([1, 2, 3, 4, 5], [1, 2, 3, 4, 5], 'go-', label='line 1', linewidth=2)\nplt.plot([1, 2, 3, 4, 5], [1, 4, 9, 16, 25], 'rs--', label='line 2',\n linewidth=4)\nplt.axis([0, 6, 0, ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def flatten(l):
return [j for i in l for j in i]
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def flatten(l):
return [j for i in l for j in i]
def filter_sequences_by_le... | flexible | {
"blob_id": "1fdb9db4c1c8b83c72eeb34f10ef9d289b43b79f",
"index": 3166,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef flatten(l):\n return [j for i in l for j in i]\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef flatten(l):\n return [j for i in l for j in i]\n\n\ndef filter_sequen... | [
0,
1,
2,
3
] |
input = open('input').read()
stacks_input, instructions = input.split('\n\n')
stacks_input_lines = stacks_input.split('\n')
stack_numbers = map(int, stacks_input_lines[-1].split())
stacks = []
for _ in stack_numbers:
stacks.append([])
for line in stacks_input_lines[:-1]:
for stack_index, i in enumerate(range(1... | normal | {
"blob_id": "4927a440093e822250af25dfd6a2ce62d7cc099e",
"index": 8786,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor _ in stack_numbers:\n stacks.append([])\nfor line in stacks_input_lines[:-1]:\n for stack_index, i in enumerate(range(1, len(line), 4)):\n crate = line[i]\n if cra... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
st.write('hi')
<|reserved_special_token_1|>
import streamlit as st
st.write('hi')
| flexible | {
"blob_id": "62ca95a871c16191fb8f56213646e8173f400630",
"index": 8017,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nst.write('hi')\n",
"step-3": "import streamlit as st\nst.write('hi')\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
} | [
0,
1,
2
] |
<|reserved_special_token_0|>
class Rank:
class Stats(object):
"""Holds info used to calculate amount of xp a player gets"""
post_likes = 0
post_dislikes = 0
comment_likes = 0
comment_dislikes = 0
usage = 0
class Interval(object):
"""A class represent... | flexible | {
"blob_id": "cd0b55e163851344273ad020d434cc8662083d19",
"index": 6593,
"step-1": "<mask token>\n\n\nclass Rank:\n\n\n class Stats(object):\n \"\"\"Holds info used to calculate amount of xp a player gets\"\"\"\n post_likes = 0\n post_dislikes = 0\n comment_likes = 0\n comment... | [
5,
6,
7,
9,
11
] |
<|reserved_special_token_0|>
class channel(gr.hier_block2):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def set_k(self, k):
self.k = k
self.channels_fading_model_0.set_K(self.k)
def get_tchannel(self):
return self.tchannel
def set_tchannel(self, tchannel):
... | flexible | {
"blob_id": "8adf25fbffc14d6927d665931e54a7d699a3b439",
"index": 6202,
"step-1": "<mask token>\n\n\nclass channel(gr.hier_block2):\n <mask token>\n <mask token>\n\n def set_k(self, k):\n self.k = k\n self.channels_fading_model_0.set_K(self.k)\n\n def get_tchannel(self):\n return ... | [
5,
6,
7,
8,
10
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(grade)
print(total)
print(avg)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
total = totalMarks(85, 67, 56, 45, 78)
avg = average(total)
grade = findGrade(avg)
print(grade)
print(total)
print(avg)
<|reserved... | flexible | {
"blob_id": "05f77472625e902b66c4a97a4c640835826bd494",
"index": 3635,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(grade)\nprint(total)\nprint(avg)\n",
"step-3": "<mask token>\ntotal = totalMarks(85, 67, 56, 45, 78)\navg = average(total)\ngrade = findGrade(avg)\nprint(grade)\nprint(total)\npri... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
app_name = 'orders'
urlpatterns = [path('checkout', views.order_checkout_view, name=
'orders-checkout')]
<|reserved_special_token_1|>
from django.urls import path
from . import views
app_name = 'orders'
urlpatterns = [path(... | flexible | {
"blob_id": "031f668fbf75b54ec874a59f53c60ceca53779cf",
"index": 8942,
"step-1": "<mask token>\n",
"step-2": "<mask token>\napp_name = 'orders'\nurlpatterns = [path('checkout', views.order_checkout_view, name=\n 'orders-checkout')]\n",
"step-3": "from django.urls import path\nfrom . import views\napp_name... | [
0,
1,
2,
3
] |
# Created by MechAviv
# [Maestra Fiametta] | [9390220]
# Commerci Republic : San Commerci
if sm.hasItem(4310100, 1):
sm.setSpeakerID(9390220)
sm.sendSayOkay("You can't start your voyage until you finish the tutorial quest!")
else:
sm.setSpeakerID(9390220)
sm.sendNext("What? You threw away the coins wi... | normal | {
"blob_id": "c4b9fdba9e9eeccc52999dab9232302f159c882a",
"index": 588,
"step-1": "<mask token>\n",
"step-2": "if sm.hasItem(4310100, 1):\n sm.setSpeakerID(9390220)\n sm.sendSayOkay(\n \"You can't start your voyage until you finish the tutorial quest!\")\nelse:\n sm.setSpeakerID(9390220)\n sm.... | [
0,
1,
2
] |
<|reserved_special_token_0|>
class Lang:
def __init__(self):
super(Lang, self).__init__()
self.word2index = {}
self.word2count = {}
self.index2word = {}
self.n_words = 0
def index_words(self, sentence):
for word in sentence:
self.index_word(word)
... | flexible | {
"blob_id": "2da7892722afde5a6f87e3bd6d5763c895ac96c9",
"index": 284,
"step-1": "<mask token>\n\n\nclass Lang:\n\n def __init__(self):\n super(Lang, self).__init__()\n self.word2index = {}\n self.word2count = {}\n self.index2word = {}\n self.n_words = 0\n\n def index_word... | [
5,
8,
9,
11,
13
] |
import API.enum as enum
import re
class ObjectValidator():
def __init__(self, validationData={}, *args, **kwargs):
self.data = validationData
self.statusCode = 200
self.validationPipeline = []
self.errors = {}
self.invalidFields = []
def flush(self):
self = Obj... | normal | {
"blob_id": "e8daf03f987c7512ff245bfbe16c447acd6b5986",
"index": 7574,
"step-1": "<mask token>\n\n\nclass FieldValidator:\n\n def __init__(self, validationData={}, *args, **kwargs):\n self.data = validationData\n self.validationPipeline = []\n self.statusCode = 200\n self.errors = ... | [
40,
58,
62,
63,
65
] |
from django.test import TestCase
from .models import Post, Category, Tag
# Create your tests here.
class TestPost(TestCase):
def test_str(self):
my_title = Post(title='This is a basic title for a basic test case')
self.assertEquals(str(my_title), 'This is a basic title for a basic test case')
c... | normal | {
"blob_id": "825c9510b055c0fa570f577b1c9616e8bde9c98b",
"index": 7653,
"step-1": "<mask token>\n\n\nclass TestCategory(TestCase):\n\n def test_str(self):\n category = Category(name='Test Category')\n self.assertEquals(str(category), 'Test Category')\n\n\nclass TestTag(TestCase):\n\n def test_... | [
4,
5,
6,
7,
8
] |
import os , sys , time
print("""
███████████████████████████████
█ █
█═╬═════════════════════════╬═█
█ ║░░░░░░░░░░░░░░░░░░░░░░░░░║ █
█ ║░░░░Wi-fi Fucker Tool░░░░║ █
█ ║░░░░░░░░░░░░░░░░░░░░░░░░░║ █
█ ║░░░░░coded by arda6░░░░░░║ █
█ ║░░░░░░░░░░░░░░░░░... | normal | {
"blob_id": "15eb205e6bd36844fdfc8c05efbc3a3d584c122d",
"index": 7238,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(\n \"\"\"\n\n ███████████████████████████████\n █ █\n █═╬═════════════════════════╬═█\n █ ║░░░░░░░░░░░░░░░░░░░░░░░░░║ █\n █ ║░░░░Wi-fi ... | [
0,
1,
2,
3,
4
] |
import math
import torch
from torch import nn
from d2l import torch as d2l
def masked_softmax(X, valid_lens):
"""通过在最后一个轴上掩蔽元素来执行softmax操作"""
# X:3D张量，valid_lens:1D或2D张量
if valid_lens is None:
return nn.functional.softmax(X, dim=-1)
else:
shape = X.shape
if valid_lens.dim() == ... | normal | {
"blob_id": "cda01bc7b0ebcfaf010bb87e7d9be34fd310d7a7",
"index": 9626,
"step-1": "<mask token>\n\n\nclass AdditiveAttention(nn.Module):\n <mask token>\n\n def __init__(self, key_size, query_size, num_hiddens, dropout, **kwargs):\n super(AdditiveAttention, self).__init__(**kwargs)\n self.W_k =... | [
7,
9,
10,
11,
13
] |
###########################################################
# 2019-02-07: 删除了marginalized prior
#
###########################################################
import sys,os
import numpy as np
import matplotlib.pylab as plt
from scipy.linalg import eig
from scipy.stats import norm, kstest, normaltest
# use default col... | normal | {
"blob_id": "ac35672661e1dd0b97567ae4335f537dc69f98f7",
"index": 6240,
"step-1": "<mask token>\n\n\ndef read_jla_mock(mock_filename):\n fp = open(mock_filename, 'r')\n lines = fp.readlines()\n fp.close()\n jla = []\n for line in lines:\n sn = line.split()\n temp = []\n temp.ap... | [
1,
2,
3,
4,
5
] |
#!/usr/bin/env python3
class interceptThread(threading.Thread):
def __init__(self):
threading.Thread.__init__(self)
self.curPkt = None
self.seq = 0
self.foundUAV = False
def run(self):
sniff(prn=self.interceptPkt, filter='udp port 5556')
def interceptPkt(self, pkt):
... | normal | {
"blob_id": "d9908d1ff155390dcd456dd15f92db03f093089e",
"index": 8146,
"step-1": "#!/usr/bin/env python3\n\nclass interceptThread(threading.Thread):\n def __init__(self):\n threading.Thread.__init__(self)\n self.curPkt = None\n self.seq = 0\n self.foundUAV = False\n def run(self... | [
0
] |
<|reserved_special_token_0|>
def filtername(name):
if len(name) > 3:
return name[:3]
elif len(name) < 3:
return name + ' ' * (3 - len(name))
return name
def filternames(names):
re = []
for n in names:
if len(n) != 3:
re += [filtername(n)]
return re
<|res... | flexible | {
"blob_id": "917241482dc1f234d5fae9c107a5f21b018fe6d4",
"index": 9843,
"step-1": "<mask token>\n\n\ndef filtername(name):\n if len(name) > 3:\n return name[:3]\n elif len(name) < 3:\n return name + ' ' * (3 - len(name))\n return name\n\n\ndef filternames(names):\n re = []\n for n in ... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
random.seed(int(sys.argv[3]))
<|reserved_special_token_0|>
print('%d' % n)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
randmin = int(sys.argv[1])
randmax = int(sys.argv[2])
random.seed(int(sys.argv[3]))
n = random... | flexible | {
"blob_id": "83e1c86095de88692d0116f7e32bd485ab381b29",
"index": 7040,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nrandom.seed(int(sys.argv[3]))\n<mask token>\nprint('%d' % n)\n",
"step-3": "<mask token>\nrandmin = int(sys.argv[1])\nrandmax = int(sys.argv[2])\nrandom.seed(int(sys.argv[3]))\nn = rand... | [
0,
1,
2,
3,
4
] |
import datetime
import calendar
import re
def cardinal(ordinal):
return int(''.join([char for char in ordinal if char.isdigit()]))
def meetup_day(year, month, day_of_week, ordinal):
days = {
0: 'Monday',
1: 'Tuesday',
2: 'Wednesday',
3: 'Thursday',
4: 'Friday',
... | normal | {
"blob_id": "d4b1b6bdf125f2791c219b7db579c234eda0a73c",
"index": 9220,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef cardinal(ordinal):\n return int(''.join([char for char in ordinal if char.isdigit()]))\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef cardinal(ordinal):\n return i... | [
0,
1,
2,
3,
4
] |
import random
print(random.choice(['python', 'c++', 'java']))
print(random.choice((1.1, -5, 6, 4, 7)))
| normal | {
"blob_id": "44f18d7e7713073c27fec38f0b847803eceefbc9",
"index": 2687,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(random.choice(['python', 'c++', 'java']))\nprint(random.choice((1.1, -5, 6, 4, 7)))\n",
"step-3": "import random\nprint(random.choice(['python', 'c++', 'java']))\nprint(random.cho... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def find_neighbors():
previous_zero_index = -1
count = 0
result = []
for index, value in enumerate(source):
count += 1
if value == 0:
if index == 0:
previous_zero_index... | flexible | {
"blob_id": "6d362b87b595fc59df31d1f0bb561dc83633a2ac",
"index": 9216,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef find_neighbors():\n previous_zero_index = -1\n count = 0\n result = []\n for index, value in enumerate(source):\n count += 1\n if value == 0:\n ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class NeuralNetwork:
def __init__(self, input_size, hidden_size, output_size):
self.input_size = input_size
self.hidden_size = hidden_size
self.output_size = output_size
reshape = partial(fn.translate, start1=0, stop1=1, start2=-1, stop2=1)
sel... | flexible | {
"blob_id": "f24516d8977b10b1ccece2f8eaec6e08ce0c2e16",
"index": 9689,
"step-1": "<mask token>\n\n\nclass NeuralNetwork:\n\n def __init__(self, input_size, hidden_size, output_size):\n self.input_size = input_size\n self.hidden_size = hidden_size\n self.output_size = output_size\n ... | [
5,
6,
7,
8,
9
] |
import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.model_selection import GroupKFold
from sklearn.linear_model import LinearRegression
from sklearn.metrics import mean_squared_log_error
from sklearn.preprocessing import OneHotEncoder
from sklearn.linear_model import... | normal | {
"blob_id": "6028b46eab422dea02af24e9cf724fe0d8b3ecc4",
"index": 9531,
"step-1": "<mask token>\n\n\ndef test_lasso():\n test = pd.read_csv('./data/test.csv')\n building_metadata = pd.read_csv('./data/building_metadata.csv')\n weather_test = pd.read_csv('./data/weather_test.csv')\n test.sort_values(by... | [
1,
2,
3,
4,
5
] |
from .. import db
class Account(db.Model):
id = db.Column(db.Integer, primary_key=True)
acc = db.Column(db.String(50), unique=True)#TODO 调整长度
pwd = db.Column(db.String(50))#TODO 调整长度
name = db.Column(db.String(20))
sex = db.Column(db.SmallInteger)
idno = db.Column(db.String(20))
phone = db... | normal | {
"blob_id": "b6824251b1165ca6c66049d40c79fccee6bc7d3a",
"index": 159,
"step-1": "<mask token>\n\n\nclass Consignor(db.Model):\n id = db.Column(db.Integer, db.ForeignKey('account.id'), primary_key=True)\n account = db.relationship('Account', uselist=False)\n indents = db.relationship('Indent', lazy='dyna... | [
8,
14,
15,
16,
18
] |
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