code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
<|reserved_special_token_0|>
def qInitResources():
QtCore.qRegisterResourceData(1, qt_resource_struct, qt_resource_name,
qt_resource_data)
def qCleanupResources():
QtCore.qUnregisterResourceData(1, qt_resource_struct, qt_resource_name,
qt_resource_data)
<|reserved_special_token_0|>
<|res... | flexible | {
"blob_id": "2a6b373c443a1bbafe644cb770bc163536dd5573",
"index": 3348,
"step-1": "<mask token>\n\n\ndef qInitResources():\n QtCore.qRegisterResourceData(1, qt_resource_struct, qt_resource_name,\n qt_resource_data)\n\n\ndef qCleanupResources():\n QtCore.qUnregisterResourceData(1, qt_resource_struct, ... | [
2,
3,
4,
5,
6
] |
#
# PySNMP MIB module AN-MIB (http://snmplabs.com/pysmi)
# ASN.1 source file:///Users/davwang4/Dev/mibs.snmplabs.com/asn1/AN-MIB
# Produced by pysmi-0.3.4 at Wed May 1 11:22:33 2019
# On host DAVWANG4-M-1475 platform Darwin version 18.5.0 by user davwang4
# Using Python version 3.7.3 (default, Mar 27 2019, 09:23:15)
... | normal | {
"blob_id": "b16e64edd0ff55a424ce3d4589321ee4576e930c",
"index": 3965,
"step-1": "<mask token>\n\n\nclass DisplayString(OctetString):\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass DisplayString(OctetString):\n subtypeSpec = OctetString.subtypeSpec + ValueSizeConstraint(0, 255)\n... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(list(numbers))
<|reserved_special_token_1|>
<|reserved_special_token_0|>
numbers = array('i', [1, 2, 3])
numbers[0] = 0
print(list(numbers))
<|reserved_special_token_1|>
from array import array
numbers = array('i', [1,... | flexible | {
"blob_id": "ae5f87f1c383478ea5f370af1c85d63a472a7788",
"index": 455,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(list(numbers))\n",
"step-3": "<mask token>\nnumbers = array('i', [1, 2, 3])\nnumbers[0] = 0\nprint(list(numbers))\n",
"step-4": "from array import array\nnumbers = array('i', [1,... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Role(db.Model, RoleMixin):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def __repr__(self):
return f'<Role {self.name}'
class User(db.Model, UserMixin):
id = db.Column(db.Integer, primary_key=True)
username... | flexible | {
"blob_id": "f561846c943013629e417d16f4dae77df43b25c4",
"index": 3806,
"step-1": "<mask token>\n\n\nclass Role(db.Model, RoleMixin):\n <mask token>\n <mask token>\n <mask token>\n\n def __repr__(self):\n return f'<Role {self.name}'\n\n\nclass User(db.Model, UserMixin):\n id = db.Column(db.I... | [
10,
11,
12,
13,
14
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def move_files(src_folder, to_folder, list_file):
with open(list_file) as f:
for line in f.readlines():
line = line.rstrip()
dirname = os.path.dirname(line)
dest = os.path.join(to_... | flexible | {
"blob_id": "6b2fc94d9a53b8f669cab5e1fb625dd01e20ba98",
"index": 664,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef move_files(src_folder, to_folder, list_file):\n with open(list_file) as f:\n for line in f.readlines():\n line = line.rstrip()\n dirname = os.path.d... | [
0,
1,
2,
3,
4
] |
"""
Copyright 2020 Google LLC
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
https://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
di... | normal | {
"blob_id": "cce40ff190f7790ac4eca7d6cb3c032955bb4849",
"index": 8288,
"step-1": "<mask token>\n\n\nclass SA360Validator(object):\n <mask token>\n\n def __init__(self, sa360_service: Resource=None, agency: int=None,\n advertiser: int=None) ->None:\n self.sa360_service = sa360_service\n ... | [
7,
8,
9,
11,
12
] |
from django.shortcuts import render
from django.views.generic import ListView
from auth_person.models import Post_news, User
# Create your views here.
def blog(request, foo):
inf = {'login': foo}
return render(request, 'blog/blog.html', context=inf)
class feed(ListView):
template_name = 'blog/feed.html'... | normal | {
"blob_id": "b216c0f92bcf91fd538eabf0239cf149342ef2eb",
"index": 4493,
"step-1": "from django.shortcuts import render\nfrom django.views.generic import ListView\nfrom auth_person.models import Post_news, User\n\n# Create your views here.\n\n\ndef blog(request, foo):\n inf = {'login': foo}\n return render(r... | [
0
] |
# Generated by Django 2.1 on 2018-12-09 21:53
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('api', '0001_initial'),
]
operations = [
migrations.RemoveField(
model_name='replays',
name='id',
),
mi... | normal | {
"blob_id": "2c1ea45d3c7ee822ec58c2fadaf7fc182acc4422",
"index": 9264,
"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 = [('api', '0001... | [
0,
1,
2,
3,
4
] |
import sys, os
sys.path.append(os.pardir)
import numpy as np
from dataset.mnist import load_mnist
from two_layer_net import TwoLayerNet
(x_train, t_train), (x_test, t_test) = load_mnist(normalize=True, one_hot_label = True)
train_loss_list = []
#hiper param
iters_num = 1000
train_size = x_train.shape[0]
batch_size =... | normal | {
"blob_id": "dbe3aa107de8e62822803d1740773a4b22f41edf",
"index": 971,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsys.path.append(os.pardir)\n<mask token>\nfor i in range(iters_num):\n print(i)\n batch_mask = np.random.choice(train_size, batch_size)\n x_batch = x_train[batch_mask]\n t_batc... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
le.fit(labels)
<|reserved_special_token_0|>
print('[info] compile model...')
<|reserved_special_token_0|>
model.compile(loss='categorical_crossentropy', optimizer=opt, metrics=[
'accuracy'])
<|reserved_special_token_0|>
print(... | flexible | {
"blob_id": "28cdb59e97f3052dd80f8437574f9ffe09fc1e84",
"index": 6690,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nle.fit(labels)\n<mask token>\nprint('[info] compile model...')\n<mask token>\nmodel.compile(loss='categorical_crossentropy', optimizer=opt, metrics=[\n 'accuracy'])\n<mask token>\nprin... | [
0,
1,
2,
3,
4
] |
import pytz
import datetime
def apply_timezone_datetime(_local_tz: str, _time: datetime.time):
"""
set time zone + merge now().date() with time()
:param _local_tz:
:param _time:
:return:
"""
return pytz.timezone(_local_tz).localize(datetime.datetime.combine(
datetime.datetime.now()... | normal | {
"blob_id": "347627df4b08eca6e2137161472b4d31534cf81b",
"index": 1238,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef apply_timezone_datetime(_local_tz: str, _time: datetime.time):\n \"\"\"\n set time zone + merge now().date() with time()\n :param _local_tz:\n :param _time:\n :retu... | [
0,
1,
2
] |
# Generated by Django 2.2.6 on 2019-12-23 16:38
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('Pages', '0014_auto_20191223_2032'),
]
operations = [
migrations.AlterField(
model_name='dept',
... | normal | {
"blob_id": "d09984c6e6a0ce82389dbbbade63507e9687355d",
"index": 771,
"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 = [('Pages', '001... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Lexer:
def __init__(self, items):
self.items = split(items)
self.index = 0
self.item = ''
self.stringOn = False
self.stringList = ''
self.intOn = False
<|reserved_special_token_0|>
def advance(self):
self.item = s... | flexible | {
"blob_id": "8d5b75dc945844d48f52159be08fc1e6aa51fdf5",
"index": 497,
"step-1": "<mask token>\n\n\nclass Lexer:\n\n def __init__(self, items):\n self.items = split(items)\n self.index = 0\n self.item = ''\n self.stringOn = False\n self.stringList = ''\n self.intOn = F... | [
8,
10,
14,
18,
19
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print('model:', module)
<|reserved_special_token_0|>
print('model:', module)
<|reserved_special_token_1|>
thisdict = {'brand': 'ford', 'model': 'Mustang', 'year': 1964}
module = thisdict['modal']
print('model:', module)
thisdic... | flexible | {
"blob_id": "3d854c83488eeafa035ccf5d333eeeae63505255",
"index": 6908,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('model:', module)\n<mask token>\nprint('model:', module)\n",
"step-3": "thisdict = {'brand': 'ford', 'model': 'Mustang', 'year': 1964}\nmodule = thisdict['modal']\nprint('model:',... | [
0,
1,
2,
3
] |
'''
Copyright (C) 2014 mdm
marco[dot]masciola[at]gmail
Licensed to the Apache Software Foundation (ASF) under one
or more contributor license agreements. See the NOTICE file
d... | normal | {
"blob_id": "4daf029c4bc9f0726080bd67f37b1e77c9697d1c",
"index": 3669,
"step-1": "'''\n Copyright (C) 2014 mdm \n marco[dot]masciola[at]gmail \n \nLicensed to the Apache Software Fo... | [
0
] |
<|reserved_special_token_0|>
class MainWindow(Frame):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class MainWindow(Frame):
def __init__(self, root):
Frame.__init__(self, root)
self.root = root
self.root.tit... | flexible | {
"blob_id": "63e5ead200fb2884d93f19e7d9b8dc76c7f4f0e3",
"index": 4611,
"step-1": "<mask token>\n\n\nclass MainWindow(Frame):\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass MainWindow(Frame):\n\n def __init__(self, root):\n Frame.__init__(self, root)\n self.root = ro... | [
1,
2,
3,
4,
5
] |
from setuptools import find_packages, setup
NAME = 'compoelem'
VERSION = "0.1.1"
setup(
name=NAME,
packages=['compoelem', 'compoelem.generate', 'compoelem.compare', 'compoelem.visualize', 'compoelem.detect', 'compoelem.detect.openpose', 'compoelem.detect.openpose.lib'],
include_package_data=True,
versio... | normal | {
"blob_id": "4f81eb7218fa1341bd7f025a34ec0677d46151b0",
"index": 6542,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsetup(name=NAME, packages=['compoelem', 'compoelem.generate',\n 'compoelem.compare', 'compoelem.visualize', 'compoelem.detect',\n 'compoelem.detect.openpose', 'compoelem.detect.open... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
try:
from setuptools import setup, find_packages
except ImportError:
from distutils.core import setup
def find_packages():
return ['sqlpython']
<|reserved_special_token_0|>
setup(name='sqlpython', version='1.7.3', description=
'Comman... | flexible | {
"blob_id": "f960c95afe1f7a161e0144bb523bfaca117ae61e",
"index": 2260,
"step-1": "<mask token>\n",
"step-2": "try:\n from setuptools import setup, find_packages\nexcept ImportError:\n from distutils.core import setup\n\n def find_packages():\n return ['sqlpython']\n<mask token>\nsetup(name='sql... | [
0,
1,
2,
3
] |
from io import StringIO
from pathlib import Path
from unittest import TestCase
from doculabs.samon import constants
from doculabs.samon.elements import BaseElement, AnonymusElement
from doculabs.samon.expressions import Condition, ForLoop, Bind
class BaseElementTest(TestCase):
def assertXmlEqual(self, generated_... | normal | {
"blob_id": "c6b98cf309e2f1a0d279ec8dc728ffd3fe45dfdb",
"index": 4792,
"step-1": "<mask token>\n\n\nclass BaseElementTest(TestCase):\n <mask token>\n <mask token>\n\n def test_parse_expressions(self):\n xml_attrs = {(constants.XML_NAMESPACE_FLOW_CONTROL, 'if'):\n 'val == 7', (constants... | [
5,
7,
8,
9,
11
] |
<|reserved_special_token_0|>
class DepartmentAdmin(admin.ModelAdmin):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def save_model(self, request, obj, form, change):
if obj.code == '':
obj.code = obj.name.re... | flexible | {
"blob_id": "77e4bbe625251254cdadaeeb23dddf51e729e747",
"index": 832,
"step-1": "<mask token>\n\n\nclass DepartmentAdmin(admin.ModelAdmin):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def save_model(self, request, obj, form, change):\n if obj.code == '':\n obj... | [
17,
23,
24,
27,
29
] |
import csv
import boto3
import pytz
import time
from datetime import datetime, timedelta
# current_time = int(datetime.now())
from boto3.dynamodb.conditions import Key, Attr
def lambda_handler(event, context):
current_date = datetime.now(pytz.timezone('US/Central'))
yesterday_date = current_date - timedleta(... | normal | {
"blob_id": "64d955d568a6bfec50aad36c9c4f1e36998e4d74",
"index": 7467,
"step-1": "<mask token>\n\n\ndef lambda_handler(event, context):\n current_date = datetime.now(pytz.timezone('US/Central'))\n yesterday_date = current_date - timedleta(days=1)\n yesterday_date_string = yesterday_date.strftime('%Y-%m-... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
dependencies = [(... | flexible | {
"blob_id": "a6cc0078fb37f9c63e119046193f521290c9fb21",
"index": 4634,
"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 = [('app', '0006... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class EchoHandler(StreamRequestHandler):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class EchoHandler(StreamRequestHandler):
def __init__(self, *args, ack, **kwargs):
... | flexible | {
"blob_id": "7819e41d567daabe64bd6eba62461d9e553566b3",
"index": 5393,
"step-1": "<mask token>\n\n\nclass EchoHandler(StreamRequestHandler):\n <mask token>\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass EchoHandler(StreamRequestHandler):\n\n def __init__(self, *args, ack, **kw... | [
1,
3,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def findWord(word):
return re.compile('\\b({0})\\b'.format(word), flags=re.IGNORECASE).search
async def managePunishment(ctx, punishment, reason):
await ctx.message.delete()
user: discord.Member = ctx.author
ms... | flexible | {
"blob_id": "10c9566503c43e806ca89e03955312c510092859",
"index": 5346,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef findWord(word):\n return re.compile('\\\\b({0})\\\\b'.format(word), flags=re.IGNORECASE).search\n\n\nasync def managePunishment(ctx, punishment, reason):\n await ctx.message... | [
0,
2,
3,
4,
5
] |
from collections import Counter, defaultdict
import pandas as pd
from glob import glob
import subsamplex
files = glob('outputs.txt/*.unique.txt.gz')
files.sort()
biome = pd.read_table('cold/biome.txt', squeeze=True, index_col=0)
duplicates = set(line.strip() for line in open('cold/duplicates.txt'))
counts = defaultdi... | normal | {
"blob_id": "74eea67b8640a03e616bebdadba49891017b921d",
"index": 8914,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfiles.sort()\n<mask token>\nfor i, fname in enumerate(files):\n sample = fname.split('/')[1].split('.')[0]\n if sample in duplicates:\n skipped += 1\n if skipped % 100... | [
0,
1,
2,
3,
4
] |
import math
# 计算像素点属于哪个中心点
from utils.util import distance
def attenuation(color, last_mean):
return 1 - math.exp(((distance(color, last_mean) / 80) ** 2) * -1)
def get_Count_By_distance(centers, pixel_use,d):
# d_min设置过低会产生多的中心点,许多很相似但是没有归到一类中
# d_min设置过高产生少的中心点,不相似的归到一类中
d_min = 1;
d_b = d;
... | normal | {
"blob_id": "918db455fc50b49ca2b40dd78cecdec4ba08dcb8",
"index": 6013,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_Count_By_distance(centers, pixel_use, d):\n d_min = 1\n d_b = d\n count_use = 0\n for i in range(len(centers)):\n d = attenuation(centers[i], pixel_use)\n ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(vector)
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
vector = np.zeros((8, 8))
vector[1::2, ::2] = 1
vector[::2, 1::2] = 1
print(vector)
<|reserved_special_token_0|>
<|reserved_... | flexible | {
"blob_id": "10d3ee459a296c26429659a202833a9570cf9454",
"index": 9639,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(vector)\n<mask token>\n",
"step-3": "<mask token>\nvector = np.zeros((8, 8))\nvector[1::2, ::2] = 1\nvector[::2, 1::2] = 1\nprint(vector)\n<mask token>\n",
"step-4": "import num... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def preprocess_data(train, test):
global train_features, test_features, train_target, categorical, numerical
train_features = train.drop(['Sales', 'Customers'], axis=1)
train_target = train[['Sales']]
test_features = test.drop(['Id'], axis=1)
try:
train_feature... | flexible | {
"blob_id": "dc51ca86a49dbec6f714753782494f21d4b1591d",
"index": 9091,
"step-1": "<mask token>\n\n\ndef preprocess_data(train, test):\n global train_features, test_features, train_target, categorical, numerical\n train_features = train.drop(['Sales', 'Customers'], axis=1)\n train_target = train[['Sales'... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
driver.get('F:\\BaiduYunDownload\\webdriverspace\\sources\\注册实例.html')
driver.maximize_window()
sleep(2)
driver.find_element_by_link_text('注册A网页').click()
<|reserved_special_token_0|>
print('当前敞口句柄：', current_handle)
<|reserved_sp... | flexible | {
"blob_id": "f73a316b6020908472e35a7b78959a9bda6e8e56",
"index": 7810,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ndriver.get('F:\\\\BaiduYunDownload\\\\webdriverspace\\\\sources\\\\注册实例.html')\ndriver.maximize_window()\nsleep(2)\ndriver.find_element_by_link_text('注册A网页').click()\n<mask token>\nprint(... | [
0,
1,
2,
3,
4
] |
import logging
from common.loghdl import getLogHandler
from datastore.dbutil import DBSQLLite, getDSConnStr
#from utils.generator import random_password
#from datastore.dbadmin import DBAdmin
#from datastore.initevaldb import *
############################ TESTING TO BE REMOVED
# md = cfg
#def test_spetest(c... | normal | {
"blob_id": "c3970ad8bddb1ca136724f589ff9088024157662",
"index": 7942,
"step-1": "\nimport logging\n\nfrom common.loghdl import getLogHandler\nfrom datastore.dbutil import DBSQLLite, getDSConnStr\n\n\n#from utils.generator import random_password\n#from datastore.dbadmin import DBAdmin\n#from datastore.initeva... | [
0
] |
"""
Python shell for Diofant.
This is just a normal Python shell (IPython shell if you have the
IPython package installed), that adds default imports and run
some initialization code.
"""
import argparse
import ast
import atexit
import code
import os
import readline
import rlcompleter
from diofant.interactive.sessio... | normal | {
"blob_id": "80e395715d3ae216beb17e7caed1d8d03c5c56de",
"index": 9943,
"step-1": "<mask token>\n\n\ndef main():\n args, ipython_args = parser.parse_known_args()\n lines = ['from diofant import *', 'init_printing()',\n \"a, b, c, d, t, x, y, z = symbols('a:d t x:z')\",\n \"k, m, n = symbols('k... | [
1,
2,
3,
4,
5
] |
class Solution:
"""
https://leetcode.com/problems/game-of-life/
289. Game of Life
Medium
--------------------
According to the Wikipedia's article: "The Game of Life, also known simply as Life, is a cellular automaton devised by the British mathematician John Horton Conway in 1970."
Given a ... | normal | {
"blob_id": "5b6ed75279b39a1dad1bf92535c4b129bb599350",
"index": 3612,
"step-1": "class Solution:\n <mask token>\n\n def gameOfLife(self, board):\n \"\"\"\n Do not return anything, modify board in-place instead.\n \"\"\"\n self.gameOfLife_2(board)\n\n def gameOfLife_1(self, b... | [
4,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(slicedString)
<|reserved_special_token_1|>
str = 'mama'
stringlength = len(str)
slicedString = str[stringlength::-1]
print(slicedString)
<|reserved_special_token_1|>
str="mama"
stringlength=len(str)
slicedString=str[... | flexible | {
"blob_id": "5c80561a3344c0240e59500e5dadc1f1ef7f380e",
"index": 7687,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(slicedString)\n",
"step-3": "str = 'mama'\nstringlength = len(str)\nslicedString = str[stringlength::-1]\nprint(slicedString)\n",
"step-4": "str=\"mama\"\r\nstringlength=len(str... | [
0,
1,
2,
3
] |
# this is for the 12/30/2015 experiments
# varied over 1, 10, 25, 50, 100 repeat particles per particle
# 10000 particles total per filter
# bias is at 0.8 in both the "real" world (realWorld.cpp)
files = ['data0Tue_Dec_30_20_37_34_2014.txt',
'data0Tue_Dec_30_20_37_49_2014.txt',
'data0Tue_Dec_30_20_38_04_2014.txt',
'd... | normal | {
"blob_id": "b63221af86748241fdce34052819569a06d37afe",
"index": 6965,
"step-1": "<mask token>\n",
"step-2": "files = ['data0Tue_Dec_30_20_37_34_2014.txt',\n 'data0Tue_Dec_30_20_37_49_2014.txt',\n 'data0Tue_Dec_30_20_38_04_2014.txt',\n 'data0Tue_Dec_30_20_38_19_2014.txt',\n 'data0Tue_Dec_30_20_38_3... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def partition(pred: Callable[[T], bool], it: Iterable[T]) ->Tuple[List[T],
List[T]]:
...
<|reserved_special_token_1|>
<|reserved_special_token_0|>
T = TypeVar('T')
def partition(pred: Callable[[T], bool], it: Iterab... | flexible | {
"blob_id": "8e443d136a4e9fcdd18a106192f9c097928b8c99",
"index": 7340,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef partition(pred: Callable[[T], bool], it: Iterable[T]) ->Tuple[List[T],\n List[T]]:\n ...\n",
"step-3": "<mask token>\nT = TypeVar('T')\n\n\ndef partition(pred: Callable[[T... | [
0,
1,
2,
3,
4
] |
from gamesim import GameSim
from network import Network
from player import RemotePlayer
from mutator import Mutator
from random import *
import copy
game = GameSim()
game.make_players(10)
base = "networks/"
dir = ""
name = "203964_85377"
gens = 2000
game.players[0].import_player(base + dir + name + ".network")
game... | normal | {
"blob_id": "1aace7b9385aefdc503ce0e43e0f7f0996fe112a",
"index": 4284,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ngame.make_players(10)\n<mask token>\ngame.players[0].import_player(base + dir + name + '.network')\ngame.train(gens)\nif gens % 500 != 0:\n game.players[0].export_player()\n",
"step-... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import logging
lgr = logging.getLogger(__name__)
lgr.log("hello")
import database
import csv
import codecs
class Stop(object):
"""docstring for Stop"""
def __init__(self, arg):
self.fields = [
'stop_id',
'stop_name',
'stop... | normal | {
"blob_id": "39ecbf914b0b2b25ce4290eac4198199b90f95e0",
"index": 5384,
"step-1": "<mask token>\n\n\nclass Stop(object):\n \"\"\"docstring for Stop\"\"\"\n\n def __init__(self, arg):\n self.fields = ['stop_id', 'stop_name', 'stop_lat', 'stop_lon',\n 'stop_calle', 'stop_numero', 'stop_entre... | [
9,
10,
12,
13,
14
] |
<|reserved_special_token_0|>
def balanco(img, ar, ag, ab):
nova = Imagem((img.altura, img.largura))
for y in range(img.altura):
for x in range(img.largura):
r, g, b = img[y][x]
R = int(ar * r)
G = int(ar * g)
B = int(ar * b)
nova[y][x] = R, G... | flexible | {
"blob_id": "1f7007fcea490a8b28bd72163f99b32e81308878",
"index": 4834,
"step-1": "<mask token>\n\n\ndef balanco(img, ar, ag, ab):\n nova = Imagem((img.altura, img.largura))\n for y in range(img.altura):\n for x in range(img.largura):\n r, g, b = img[y][x]\n R = int(ar * r)\n ... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
def max_heapity(arr, start, end):
root = start
while True:
child = 2 * root + 1
if child > end:
break
if child + 1 <= end and arr[child] < arr[child + 1]:
child += 1
if arr[root] < arr[child]:
arr[root], arr[child... | flexible | {
"blob_id": "2ffe4b0eb7af9b3a4d5724442b5409d27bfa92a1",
"index": 6130,
"step-1": "<mask token>\n\n\ndef max_heapity(arr, start, end):\n root = start\n while True:\n child = 2 * root + 1\n if child > end:\n break\n if child + 1 <= end and arr[child] < arr[child + 1]:\n ... | [
2,
3,
4,
5,
6
] |
#!/usr/bin/env python
import os
from distutils.core import setup, Extension
import distutils.util
setup (name = 'pybanery',
version= '1.0',
description='Python interface for Kanbanery',
author = 'Pablo Lluch',
author_email = 'pablo.lluch@gmail.com',
py_modules = ['pybanery'],
... | normal | {
"blob_id": "60c862accbb9cda40ed4c45491f643f065e2868a",
"index": 6467,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsetup(name='pybanery', version='1.0', description=\n 'Python interface for Kanbanery', author='Pablo Lluch', author_email=\n 'pablo.lluch@gmail.com', py_modules=['pybanery'], script... | [
0,
1,
2,
3
] |
#!/usr/bin/python
# Original code found at:
# https://github.com/zzeromin/raspberrypi/tree/master/i2c_lcd
# requires I2C_LCD_driver.py
import I2C_LCD_driver
from time import *
import os
mylcd = I2C_LCD_driver.lcd()
mylcd.lcd_clear()
mylcd.lcd_display_string("RAS Hi-Pi shutdown", 1)
mylcd.lcd_display_string(" See yo... | normal | {
"blob_id": "df60d3b829c5702385f59fdefaea04f569fb7db2",
"index": 9058,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nmylcd.lcd_clear()\nmylcd.lcd_display_string('RAS Hi-Pi shutdown', 1)\nmylcd.lcd_display_string(' See you again ~', 2)\nmylcd.lcd_display_string('http://rasplay.org', 3)\nmylcd.lcd_displa... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if settings.DEBUG:
urlpatterns += static(settings.STATIC_URL, document_root=settings.
STATIC_ROOT)
urlpatterns += static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT
)
<|reserved_special_token_1|... | flexible | {
"blob_id": "a35e86e474883d892a6ce8eb191a3a5f8a9558c8",
"index": 1105,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif settings.DEBUG:\n urlpatterns += static(settings.STATIC_URL, document_root=settings.\n STATIC_ROOT)\n urlpatterns += static(settings.MEDIA_URL, document_root=settings.MEDI... | [
0,
1,
2,
3,
4
] |
'''Mock classes that imitate idlelib modules or classes.
Attributes and methods will be added as needed for tests.
'''
from idlelib.idle_test.mock_tk import Text
class Editor:
'''Minimally imitate EditorWindow.EditorWindow class.
'''
def __init__(self, flist=None, filename=None, key=None, root=None):
... | normal | {
"blob_id": "3b7c30718838a164eaf3aa12cd7b6a68930346f8",
"index": 8604,
"step-1": "<mask token>\n\n\nclass UndoDelegator:\n <mask token>\n\n def undo_block_start(*args):\n pass\n\n def undo_block_stop(*args):\n pass\n",
"step-2": "<mask token>\n\n\nclass Editor:\n <mask token>\n\n d... | [
3,
7,
8,
9,
10
] |
with open('dwarfs.txt') as fh:
i = 1
for line in fh:
print("[%d] %s" % (i, line))
i += 1
| normal | {
"blob_id": "18c4c1e1ee0df835895397488b270a47b1620c30",
"index": 8032,
"step-1": "<mask token>\n",
"step-2": "with open('dwarfs.txt') as fh:\n i = 1\n for line in fh:\n print('[%d] %s' % (i, line))\n i += 1\n",
"step-3": "with open('dwarfs.txt') as fh:\n i = 1\n for line in fh:\n ... | [
0,
1,
2
] |
<|reserved_special_token_0|>
@serious12.route('/')
def home():
return 'HOME'
@serious12.route('/user/<username>')
def user(username):
user = {'trung': {'name': 'Trung', 'age': 19, 'birthplace': 'Hanoi'},
'nguyenvana': {'name': 'A', 'age': 69, 'birthplace': 'Trai Dat'}}
return render_template('us... | flexible | {
"blob_id": "db1b6c545555116a334061440614e83e62994838",
"index": 4440,
"step-1": "<mask token>\n\n\n@serious12.route('/')\ndef home():\n return 'HOME'\n\n\n@serious12.route('/user/<username>')\ndef user(username):\n user = {'trung': {'name': 'Trung', 'age': 19, 'birthplace': 'Hanoi'},\n 'nguyenvana'... | [
2,
3,
4,
5,
6
] |
#!/usr/bin/env python3
import warnings
import config
import numpy as np
from latplan.model import ActionAE, default_networks
from latplan.util import curry
from latplan.util.tuning import grid_search, nn_task
import keras.backend as K
import tensorflow as tf
float_formatter = lambda x: "%.3f" % x
np.set_printo... | normal | {
"blob_id": "f1c6340880b52ba86856913f74c7d589d9b49f49",
"index": 5179,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nnp.set_printoptions(formatter={'float_kind': float_formatter})\n<mask token>\nif __name__ == '__main__':\n import numpy.random as random\n import sys\n if len(sys.argv) == 1:\n ... | [
0,
1,
2,
3,
4
] |
from flask import jsonify
from flask_restful import Resource
from flask_apispec.views import MethodResource
import pandas as pd
import jellyfish
df = pd.read_csv('data/trancotop1m.csv')
df_dict = df.to_dict('records')
class StrComparison(MethodResource,Resource):
# @requires_auth
def get(self, domain):
... | normal | {
"blob_id": "6d974580ff546bda17caa1e61e2621b4bc705f3f",
"index": 2952,
"step-1": "<mask token>\n\n\nclass StrComparison(MethodResource, Resource):\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass StrComparison(MethodResource, Resource):\n\n def get(self, domain):\n domain_found = ''\n ... | [
1,
2,
3,
4,
5
] |
h = 160
xorg = 0
yoff = 400
xcount = 0
xvel = 2
def setup():
size(800, 800)
colorMode(HSB, 360, 1, 1, 1)
background(140, 0.49, 0.75)
frameRate(30)
noStroke()
def draw():
global h, xorg, yoff, xcount, xvel
if frameCount % 10 == 0:
fill(140, 0.49, 0.75, 0.2)
square(0,0,width)... | normal | {
"blob_id": "2257494dec9fccc4e8bd4acf0aff31a73c252a61",
"index": 616,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef draw():\n global h, xorg, yoff, xcount, xvel\n if frameCount % 10 == 0:\n fill(140, 0.49, 0.75, 0.2)\n square(0, 0, width)\n pushMatrix()\n translate(xorg... | [
0,
1,
2,
3,
4
] |
"""insta URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/2.0/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: path('', views.home, name='home')
Class-based v... | normal | {
"blob_id": "63c0786d277c5576822d6e521f65850762ab5eb0",
"index": 9198,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns += static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT)\n",
"step-3": "<mask token>\nurlpatterns = [path('admin/', admin.site.urls), path('post/', post_views.\n ... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
from django.apps import AppConfig
class AcademyConfig(AppConfig):
name = 'academy'
verbose_name = u"Академия"
| normal | {
"blob_id": "619d2df45d0823930484f030a9a78e71ec718cb7",
"index": 6661,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass AcademyConfig(AppConfig):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass AcademyConfig(AppConfig):\n name = 'academy'\n verbose_name = u'Акад... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def main():
N = int(input())
A = tuple(map(int, input().split()))
c = Counter(A).most_common()
if c[0][0] == 0 and c[0][1] == N:
print('Yes')
elif len(c) == 2 and c[0][1] == 2 * N // 3 and c[1][0] == ... | flexible | {
"blob_id": "7c6ada250770e04b395dda774a78042da69e2854",
"index": 8681,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main():\n N = int(input())\n A = tuple(map(int, input().split()))\n c = Counter(A).most_common()\n if c[0][0] == 0 and c[0][1] == N:\n print('Yes')\n elif le... | [
0,
1,
2,
3,
4
] |
# -*- python -*-
# ex: set syntax=python:
# vim: set syntax=python:
import os
import re
from collections import defaultdict, namedtuple
from enum import Enum
from pathlib import Path
import buildbot.www.authz.endpointmatchers as ems
from buildbot.changes.filter import ChangeFilter
from buildbot.changes.gitpoller impo... | normal | {
"blob_id": "4abcca52095a169b71d2527ce52b8367534c42a4",
"index": 5989,
"step-1": "<mask token>\n\n\nclass Purpose(Enum):\n halide_nightly = 1\n halide_testbranch = 2\n llvm_nightly = 3\n\n\nclass BuildSystem(Enum):\n make = 0\n cmake = 1\n\n\nclass BuilderType:\n \"\"\"A class to encapsulate th... | [
45,
55,
62,
69,
80
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from operation import *
import math
class InsertWord(Operation):
@classmethod
def getValue(cls, t, h, w, b, arg=None):
return math.log(arg["prob"]) * w[cls]
@classmethod
def getKBest(cls, t, h , args, w, b, k):
valueList = []
for ... | normal | {
"blob_id": "355e3932c8bd9105e0c1ce9259e3b7416997523c",
"index": 3668,
"step-1": "<mask token>\n\n\nclass InsertWord(Operation):\n\n @classmethod\n def getValue(cls, t, h, w, b, arg=None):\n return math.log(arg['prob']) * w[cls]\n <mask token>\n <mask token>\n\n @classmethod\n def transF... | [
3,
4,
5,
6,
7
] |
a = float(input('Digite um valor: '))
b = float(input('Digite outro valor: '))
c = float(input('Digite mais um valor: '))
if a == b or b == c:
print('Com os números digitados, formam um triângulo EQUILATERO.')
elif a <> b and b <> c and c == a and b == c:
print('Com os números digitados, formam um triângulo ISO... | normal | {
"blob_id": "81233eb12b8447d017b31f200ab7902dcce45496",
"index": 1649,
"step-1": "a = float(input('Digite um valor: '))\nb = float(input('Digite outro valor: '))\nc = float(input('Digite mais um valor: '))\nif a == b or b == c:\n print('Com os números digitados, formam um triângulo EQUILATERO.')\nelif a <> b ... | [
0
] |
'''
Applies the mish function element-wise:
.. math::
mish(x) = x * tanh(softplus(x)) = x * tanh(ln(1 + e^{x}))
'''
# import pytorch
import torch
from torch import nn
# import activation functions
import echoAI.Activation.Torch.functional as Func
class Mish(nn.Module):
'''
Applies the mish function ele... | normal | {
"blob_id": "2deb73c7d2588ea1a5b16eb1ed617583d41f0130",
"index": 2846,
"step-1": "<mask token>\n\n\nclass Mish(nn.Module):\n <mask token>\n <mask token>\n\n def forward(self, input):\n \"\"\"\n Forward pass of the function.\n \"\"\"\n return Func.mish(input, inplace=self.inpl... | [
2,
3,
4,
5,
6
] |
from __future__ import print_function
import tensorflow as tf
# from keras.callbacks import ModelCheckpoint
from data import load_train_data
from utils import *
import os
create_paths()
log_file = open(global_path + "logs/log_file.txt", 'a')
X_train, y_train = load_train_data()
labeled_index = np.arange(0, nb_labeled... | normal | {
"blob_id": "d36552cc589b03008dc9edab8d7e4a003e26bd21",
"index": 5046,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ncreate_paths()\n<mask token>\nif os.path.exists(initial_weights_path):\n model.load_weights(initial_weights_path)\nif initial_train:\n model_checkpoint = tf.keras.callbacks.ModelChe... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class States:
INIT = -1
GET_READY = 1
FIND_BAR = 2
WALK_2_BAR = 3
WALK_SIDEWAYS = 4
PICK_BAR = 5
WALK_WITH_BAR = 6
LIFT_BAR = 7
WALK_2_FINISH = 8
END = 99
<|reserved_special_token_0|>
def init():
robot.setGeneralControlModule('action_module'... | flexible | {
"blob_id": "b3a2db38e2074b02c8837bfce85d06598a7b194d",
"index": 5701,
"step-1": "<mask token>\n\n\nclass States:\n INIT = -1\n GET_READY = 1\n FIND_BAR = 2\n WALK_2_BAR = 3\n WALK_SIDEWAYS = 4\n PICK_BAR = 5\n WALK_WITH_BAR = 6\n LIFT_BAR = 7\n WALK_2_FINISH = 8\n END = 99\n\n\n<ma... | [
3,
4,
5,
6,
7
] |
import re
import sys
import zipfile
import pathlib
from typing import IO, Any
from collections.abc import Mapping
import numpy.typing as npt
import numpy as np
from numpy.lib._npyio_impl import BagObj
if sys.version_info >= (3, 11):
from typing import assert_type
else:
from typing_extensions import assert_typ... | normal | {
"blob_id": "e2f134f5ff00405396b8bbf4edc263b70ef5d972",
"index": 2435,
"step-1": "<mask token>\n\n\nclass BytesWriter:\n <mask token>\n\n\nclass BytesReader:\n\n def read(self, n: int=...) ->bytes:\n ...\n\n def seek(self, offset: int, whence: int=...) ->int:\n ...\n\n\n<mask token>\n",
... | [
4,
5,
6,
7,
8
] |
from django.conf.urls import url, include
from . import views
explore_patterns = [
url(r'^$', views.explore),
url(r'^(?P<model_type>\w+)/$', views.get_by_model_type),
url(r'^(?P<model_type>\w+)/(?P<id>\w+)/$', views.get_by_model_id),
url(r'^(?P<model_type>\w+)/(?P<id>\w+)/download$', views.download_me... | normal | {
"blob_id": "89078ddd7dad3a2727b66566457b9ac173abe607",
"index": 8506,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nexplore_patterns = [url('^$', views.explore), url('^(?P<model_type>\\\\w+)/$',\n views.get_by_model_type), url('^(?P<model_type>\\\\w+)/(?P<id>\\\\w+)/$',\n views.get_by_model_id), ... | [
0,
1,
2,
3
] |
import time
import numpy as np
import matplotlib.pyplot as plt #tutorial: http://pybonacci.org/2012/05/19/manual-de-introduccion-a-matplotlib-pyplot-ii-creando-y-manejando-ventanas-y-configurando-la-sesion/
import threading
from random import shuffle
T = 1
eps = 0.000000001
agilityMin = 1/T
'''------------GOVERMENT'... | normal | {
"blob_id": "ab0c3cf3e43f34874dd94629b746ca1237c3349a",
"index": 7494,
"step-1": "<mask token>\n\n\nclass Map:\n <mask token>\n\n def __init__(self, size, num_feeds):\n self.size = size\n self.map_cells = np.zeros((self.size, self.size))\n <mask token>\n <mask token>\n\n def createCe... | [
21,
26,
27,
32,
34
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.... | flexible | {
"blob_id": "b308d81fb8eab9f52aa0ad4f88e25d6757ef703a",
"index": 1761,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Migration(migrations.Migration):\n <mask token>\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Migration(migrations.Migration):\n initial = T... | [
0,
1,
2,
3,
4
] |
"""
Copyright (c) 2017 - Philip Paquette
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribu... | normal | {
"blob_id": "9a183b1f81681b3dec1132a27b17e389438ab725",
"index": 6045,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef set_seed(n):\n global seed, py_rng, np_rng, t_rng\n seed = n\n py_rng = Random(seed)\n np_rng = np.random.RandomState(seed)\n\n\n<mask token>\n",
"step-3": "<mask to... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def upgrade():
op.add_column('Gifs', sa.Column('personal_collections', sa.Integer(),
nullable=True))
op.create_foreign_key(None, 'Gifs', 'PersonalGifCollections', [
'personal_collections'], ['id'])
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|re... | flexible | {
"blob_id": "21bdf315c98a4cf69482cc7db41bc30d44781596",
"index": 816,
"step-1": "<mask token>\n\n\ndef upgrade():\n op.add_column('Gifs', sa.Column('personal_collections', sa.Integer(),\n nullable=True))\n op.create_foreign_key(None, 'Gifs', 'PersonalGifCollections', [\n 'personal_collections... | [
1,
2,
3,
4,
5
] |
# coding: utf-8
## ROC for CLEF-IP2010 patents
####### ROC for clef-ip2010 patents
# In[ ]:
def vectorize_corpus(corpus,tokenizer,vocabulary,max_ngram_size):
# tokenize text
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.feature_extraction.text import TfidfTransformer
from... | normal | {
"blob_id": "08e5e8515528eae400a59bfc0c58b8d7b4affd7e",
"index": 5921,
"step-1": "\n# coding: utf-8\n\n## ROC for CLEF-IP2010 patents\n\n####### ROC for clef-ip2010 patents\n\n# In[ ]:\n\ndef vectorize_corpus(corpus,tokenizer,vocabulary,max_ngram_size):\n # tokenize text\n from sklearn.feature_extraction.t... | [
0
] |
<|reserved_special_token_0|>
def handle_request(user, data):
results = []
resultsByTag = {}
api = Api(user, data.get('createdIds', None))
for capability in data['using']:
CAPABILITIES[capability].register_methods(api)
for cmd, kwargs, tag in data['methodCalls']:
t0 = monotonic()
... | flexible | {
"blob_id": "aac3b2478980d3a5453451cb848afcfd6aca1743",
"index": 1680,
"step-1": "<mask token>\n\n\ndef handle_request(user, data):\n results = []\n resultsByTag = {}\n api = Api(user, data.get('createdIds', None))\n for capability in data['using']:\n CAPABILITIES[capability].register_methods(... | [
6,
7,
8,
9,
10
] |
import numpy as np
import matplotlib.pyplot as plt
from scipy import stats
def fit(x, iters=1000, eps=1e-6):
"""
Fits a 2-parameter Weibull distribution to the given data using maximum-likelihood estimation.
:param x: 1d-ndarray of samples from an (unknown) distribution. Each value must satisfy x ... | normal | {
"blob_id": "b10d3d8d0ded0d2055c1abdaf40a97abd4cb2cb8",
"index": 1631,
"step-1": "<mask token>\n\n\ndef fit(x, iters=1000, eps=1e-06):\n \"\"\"\n Fits a 2-parameter Weibull distribution to the given data using maximum-likelihood estimation.\n :param x: 1d-ndarray of samples from an (unknown) distributio... | [
1,
2,
3,
4,
5
] |
"""
First run in samples:
mogrify -format png -density 150 input.pdf -quality 90 -- *.pdf
"""
import cv2
import os
import numpy as np
from matplotlib import pylab
def peakdetect(v, delta, x=None):
"""
Converted from MATLAB script at http://billauer.co.il/peakdet.html
Returns two arrays
fun... | normal | {
"blob_id": "9887e001f13ed491331c79c08450299afcc0d7cd",
"index": 4279,
"step-1": "\"\"\"\nFirst run in samples: \nmogrify -format png -density 150 input.pdf -quality 90 -- *.pdf\n\"\"\"\n\nimport cv2\nimport os\nimport numpy as np\nfrom matplotlib import pylab\n\ndef peakdetect(v, delta, x=None):\n \"\"\"\n ... | [
0
] |
<|reserved_special_token_0|>
class ConditionWrapper:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class MonitorBase(object, metaclass=MonitorMeta):
_monitor_counter = 0
_variable_counter = 0
_condition_counter = 0
def __new__(cls, *args, **kwarg... | flexible | {
"blob_id": "80d49b24a2233569a340cee918393b1663c3d55d",
"index": 4598,
"step-1": "<mask token>\n\n\nclass ConditionWrapper:\n <mask token>\n <mask token>\n <mask token>\n\n\nclass MonitorBase(object, metaclass=MonitorMeta):\n _monitor_counter = 0\n _variable_counter = 0\n _condition_counter = 0... | [
16,
17,
18,
23,
26
] |
#!/usr/bin/python
__author__ = "morganlnance"
'''
Analysis functions using PyRosetta4
'''
def get_sequence(pose, res_nums=None):
# type: (Pose, list) -> str
"""
Return the sequence of the <pose>, or, return the sequence listed in <res_nums>
:param pose: Pose
:param res_nums: list() of Pose residu... | normal | {
"blob_id": "876e9f03c908338a247b6bf1f23011e609bbc2a5",
"index": 8739,
"step-1": "<mask token>\n\n\ndef write_fasta_file(pdb_names, pdb_sequences, filename, dump_dir=''):\n \"\"\"\n Use a list of <pdb_names> and their corresponding <pdb_sequences> to write out a FASTA formatted file\n Need a <filename> ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
app_name = 'produce'
urlpatterns = [url('^sms/$', views.sms, name='sms'), url('^list/', views.
SeasonalView.as_view(), name='list'), url('^(?P<pk>[0-9]+)/$', views.
ProduceDetailView.as_view(), name='produce_detail'), url(... | flexible | {
"blob_id": "f7d0d7dda955acd07b6da010d21dc5f02254e1ed",
"index": 5821,
"step-1": "<mask token>\n",
"step-2": "<mask token>\napp_name = 'produce'\nurlpatterns = [url('^sms/$', views.sms, name='sms'), url('^list/', views.\n SeasonalView.as_view(), name='list'), url('^(?P<pk>[0-9]+)/$', views.\n ProduceDeta... | [
0,
1,
2,
3
] |
'''
tag名だけで変えてもいいよね？？
ただし，置換するときは，「代表参照表現（参照表現）」のように，元の参照表現が分かるように配慮せよ．→何を言いたい！？
もしかして:
<mention> -> <mention representative="false"> 欲しい??「元の参照表現が分かる」とは <mention representative="true"> と区割りできればいいよね？
'''
from bs4 import BeautifulSoup, element
soup = BeautifulSoup(open("nlp.txt.xml"),"lxml")
mentions = soup.find_all('me... | normal | {
"blob_id": "04938e14f22c44437188469b53dfb05d2ecd4a5c",
"index": 4481,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor m in mentions:\n if m.has_attr('representative') == False:\n print('before: =>\\n{}'.format(m))\n m['representative'] = 'false'\n print('after: =>\\n{}'.format... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
__all__ = ['AddonsRepository', 'Addon', 'Addons', 'Utils']
<|reserved_special_token_1|>
__all__ = ["AddonsRepository", "Addon", "Addons", "Utils"] | flexible | {
"blob_id": "054d7e4bd51110e752a18a5c0af4432a818ef3b8",
"index": 7974,
"step-1": "<mask token>\n",
"step-2": "__all__ = ['AddonsRepository', 'Addon', 'Addons', 'Utils']\n",
"step-3": "__all__ = [\"AddonsRepository\", \"Addon\", \"Addons\", \"Utils\"]",
"step-4": null,
"step-5": null,
"step-ids": [
... | [
0,
1,
2
] |
class Queue(object):
def __init__(self, val_list=None):
self.stack_one = []
self.stack_two = []
if val_list:
for item in val_list:
self.stack_one.append(item)
def push(self, val=None):
if val:
self.stack_one.append(val)
def pop(self)... | normal | {
"blob_id": "d4d8d800b81a50f2c520f0394412935738d1a8ee",
"index": 2986,
"step-1": "class Queue(object):\n\n def __init__(self, val_list=None):\n self.stack_one = []\n self.stack_two = []\n if val_list:\n for item in val_list:\n self.stack_one.append(item)\n\n d... | [
3,
4,
5,
6
] |
import optparse
from camera import apogee_U2000
if __name__ == "__main__":
parser = optparse.OptionParser()
group1 = optparse.OptionGroup(parser, "General")
group1.add_option('--s', action='store', default=1, dest='mode', help='set cooler on/off')
args = parser.parse_args()
options, args = parser.par... | normal | {
"blob_id": "60c849d213f6266aeb0660fde06254dfa635f10f",
"index": 3383,
"step-1": "import optparse\n\nfrom camera import apogee_U2000\t\t\t\n\nif __name__ == \"__main__\":\n parser = optparse.OptionParser()\n group1 = optparse.OptionGroup(parser, \"General\") \n group1.add_option('--s', action='store', defau... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Solution(object):
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Solution(object):
def longestSubsequence(self, arr, difference):
dp = dict()
mx =... | flexible | {
"blob_id": "fa4ab3ed5c653633879b5ba2c078c896aa3eb0c6",
"index": 2838,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Solution(object):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Solution(object):\n\n def longestSubsequence(self, arr, difference):\n dp = dict()\n ... | [
0,
1,
2,
3
] |
print(180 / 4)
| normal | {
"blob_id": "509129052f97bb32b4ba0e71ecd7b1061d5f8da2",
"index": 38,
"step-1": "<mask token>\n",
"step-2": "print(180 / 4)\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
from django.shortcuts import render, redirect
from .models import League, Team, Player
from django.db.models import Count
from . import team_maker
def index(request):
baseball = League.objects.filter(name__contains='Baseball')
women_league = League.objects.filter(name__contains='women')
hockey_league = ... | normal | {
"blob_id": "49703775da87e8cbbe78a69c91a68128c3fd78e1",
"index": 3363,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef index(request):\n baseball = League.objects.filter(name__contains='Baseball')\n women_league = League.objects.filter(name__contains='women')\n hockey_league = League.obje... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class AlipayInsSceneEcommerceInsureCheckModel(object):
def __init__(self):
self._insure_admit_dto_list = None
self._partner_org_id = None
self._product_code = None
self._scene_code = None
self._user_client = None
@property
def insure_a... | flexible | {
"blob_id": "e616d14827beaa08ab08219421cbf7990cf163fd",
"index": 242,
"step-1": "<mask token>\n\n\nclass AlipayInsSceneEcommerceInsureCheckModel(object):\n\n def __init__(self):\n self._insure_admit_dto_list = None\n self._partner_org_id = None\n self._product_code = None\n self._s... | [
8,
10,
11,
12,
16
] |
# Copyright (c) 2016, Xilinx, Inc.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice,
# this list of ... | normal | {
"blob_id": "15514d5636471b1a311641a40b6a00b81703cd2b",
"index": 6488,
"step-1": "<mask token>\n\n\nclass Grove_PIR(Pmod_IO):\n <mask token>\n\n def __init__(self, mb_info, gr_pin):\n \"\"\"Return a new instance of a PIR object. \n \n Parameters\n ----------\n mb_info : d... | [
3,
4,
5,
6,
7
] |
'''
Created on Mar 19, 2019
@author: malte
'''
import gc
import pickle
from hyperopt import tpe, hp
from hyperopt.base import Trials
from hyperopt.fmin import fmin
from config.globals import BASE_PATH
from domain.features import FEATURES
from evaluate import evaluate
from featuregen.create_set import create_set
fro... | normal | {
"blob_id": "daf070291bbf59a7a06b129bbde5fd79b5cd46ad",
"index": 6715,
"step-1": "<mask token>\n\n\ndef objective(params):\n train = create_set(base_path=BASE_PATH + SET, conf=CONF, key=DSKEY,\n redo=False)\n test = train.query('train == 0')\n train.query('train == 1', inplace=True)\n X = trai... | [
2,
3,
4,
5,
6
] |
#!/usr/bin/env python
"""
.. module:: convert
:synopsis: used to create info.txt and the <txname>.txt files.
"""
import sys
import os
import argparse
argparser = argparse.ArgumentParser(description =
'create info.txt, txname.txt, twiki.txt and sms.py')
argparser.add_argument ('-utilsPath', '--utilsPath',
help ... | normal | {
"blob_id": "c80b31bc154d5c1c8f9fc0ac226295160f2f9473",
"index": 4249,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nargparser.add_argument('-utilsPath', '--utilsPath', help=\n 'path to the package smodels_utils', type=str)\nargparser.add_argument('-smodelsPath', '--smodelsPath', help=\n 'path to ... | [
0,
1,
2,
3,
4
] |
import os
import subprocess
import discord
import asyncio
import traceback
import sys
import ast
from discord.ext import commands
# Import Cogs
from cogs.misc import Miscellaneous
from cogs.serversettings import ServerSettings
from cogs.mod import Moderator
from cogs.automod import AutoMod
from cogs.google import Goo... | normal | {
"blob_id": "4f9729e396e01cb3d6c9011f79a1ebe618a8e762",
"index": 7787,
"step-1": "<mask token>\n\n\ndef insert_returns(body):\n if isinstance(body[-1], ast.Expr):\n body[-1] = ast.Return(body[-1].value)\n ast.fix_missing_locations(body[-1])\n if isinstance(body[-1], ast.If):\n insert_r... | [
1,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def findSubset(s0, s, t):
mys0 = s0.copy()
mys = s.copy()
if t == 0 and mys0:
return mys0
elif t == 0:
return True
elif len(mys) > 0:
p = mys.pop()
mys1 = mys0.copy()
mys1.add(p)
if t - p < 0... | flexible | {
"blob_id": "079610f2aaebec8c6e46ccf21a9d5728df1be8de",
"index": 4155,
"step-1": "<mask token>\n",
"step-2": "def findSubset(s0, s, t):\n mys0 = s0.copy()\n mys = s.copy()\n if t == 0 and mys0:\n return mys0\n elif t == 0:\n return True\n elif len(mys) > 0:\n p = mys.pop()\n... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
@unittest.skipIf(not _HAS_SKLEARN, 'Missing sklearn. Skipping tests.')
class ImputerTestCase(unittest.TestCase):
<|reserved_special_token_0|>
@classmethod
def setUpClass(self):
"""
Set up the unit test by loading the dataset and training a model.
"""
... | flexible | {
"blob_id": "d3d90b8ccd0ec449c84ac0316c429b33353f4518",
"index": 8900,
"step-1": "<mask token>\n\n\n@unittest.skipIf(not _HAS_SKLEARN, 'Missing sklearn. Skipping tests.')\nclass ImputerTestCase(unittest.TestCase):\n <mask token>\n\n @classmethod\n def setUpClass(self):\n \"\"\"\n Set up th... | [
4,
5,
6,
7,
8
] |
import FWCore.ParameterSet.Config as cms
class StageOneCustomize():
"""
Customizaton class for STXS stage 1 analysis
"""
def __init__(self, process, customize, metaConditions):
self.process = process
self.customize = customize
self.metaConditions = metaConditions
se... | normal | {
"blob_id": "ce12ede15f4ca4a085e38e455515d8a028da8fd2",
"index": 2115,
"step-1": "<mask token>\n\n\nclass StageOneCustomize:\n <mask token>\n\n def __init__(self, process, customize, metaConditions):\n self.process = process\n self.customize = customize\n self.metaConditions = metaCond... | [
6,
7,
8,
9,
10
] |
<|reserved_special_token_0|>
class Optimizer(object):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
@staticmethod
def fromXml(xmlDoc, plant, orderList, simulator, evaluator):
"""
Loads the optimizer configuration and parameters from an XML tree.
"""
optimizer = Optimiz... | flexible | {
"blob_id": "8ce2e9cd9ceed6c79a85682b8bc03a3ffb5131c4",
"index": 3817,
"step-1": "<mask token>\n\n\nclass Optimizer(object):\n <mask token>\n <mask token>\n\n @staticmethod\n def fromXml(xmlDoc, plant, orderList, simulator, evaluator):\n \"\"\"\n\t\tLoads the optimizer configuration and parame... | [
10,
11,
12,
13,
16
] |
#!/usr/bin/env python3
import os
import fileinput
project = input("Enter short project name: ")
if os.path.isdir(project):
print("ERROR: Project exists")
exit()
os.mkdir(project)
os.chdir(project)
cmd = "virtualenv env -p `which python3` --prompt=[django-" + project + "]"
os.system(cmd)
# Install django wi... | normal | {
"blob_id": "c700af6d44cd036212c9e4ae4932bc60630f961e",
"index": 6930,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif os.path.isdir(project):\n print('ERROR: Project exists')\n exit()\nos.mkdir(project)\nos.chdir(project)\n<mask token>\nos.system(cmd)\n<mask token>\nwith open('requirements.txt',... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python
"""
haxor
Unofficial Python wrapper for official Hacker News API
@author avinash sajjanshetty
@email hi@avi.im
"""
from __future__ import absolute_import
from __future__ import unicode_literals
import datetime
import json
import sys
import requests
from .settings import supported_api_versions... | normal | {
"blob_id": "e14c7eb11c06d6de5c2f9f8adfb8b742fcb432e1",
"index": 8073,
"step-1": "<mask token>\n\n\nclass HackerNews(object):\n <mask token>\n\n def _get(self, url):\n \"\"\"Internal method used for GET requests\n\n Args:\n url (string): URL to send GET.\n\n Returns:\n ... | [
11,
16,
17,
20,
29
] |
import os
import base64
from binascii import hexlify
from cryptography.hazmat.primitives.ciphers import Cipher, algorithms, modes
from cryptography.hazmat.primitives import hashes, hmac
from cryptography.hazmat.backends import default_backend
backend = default_backend()
# Llave falsa
key = key = b"vcOqXPg==lz3M0IH4s... | normal | {
"blob_id": "c33aedbd5aaa853131c297a9382b72c3c646a319",
"index": 4006,
"step-1": "<mask token>\n\n\ndef decrypt(message):\n message = base64.urlsafe_b64decode(message)\n iv = message[:16]\n signed_data = message[16:36]\n encrypted_data = message[36:]\n cipher = Cipher(algorithms.AES(key), modes.CB... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(
'Έχουμε ένα τριώνυμο ax²+bx+c. Δώστε μία θετική ή αρνητική τιμή σε κάθε σταθερά!'
)
<|reserved_special_token_0|>
print('Η Διακρίνουσα ειναι: ' + str(D))
if D > 0:
x1 = (-b + math.sqrt(D)) / (2 * a)
print('Η ... | flexible | {
"blob_id": "b80deec4d3d3ab4568f37cc59e098f1d4af5504c",
"index": 6503,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(\n 'Έχουμε ένα τριώνυμο ax²+bx+c. Δώστε μία θετική ή αρνητική τιμή σε κάθε σταθερά!'\n )\n<mask token>\nprint('Η Διακρίνουσα ειναι: ' + str(D))\nif D > 0:\n x1 = (-b + math... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import sys
import json
import requests
BASE_URL = 'http://www.omdbapi.com/'
def rating_msg(rating):
if rating > 80:
return 'You should watch this movie right now!\n'
elif rating < 50:
return 'Avoid this movie at all cost!\n'
else:
re... | normal | {
"blob_id": "7f33effa86fc3a80fce0e5e1ecf97ab4ca80402d",
"index": 1833,
"step-1": "<mask token>\n\n\ndef rating_msg(rating):\n if rating > 80:\n return 'You should watch this movie right now!\\n'\n elif rating < 50:\n return 'Avoid this movie at all cost!\\n'\n else:\n return ''\n\n\... | [
1,
2,
3,
4,
5
] |
from flask import current_app
def get_logger():
return current_app.logger
def debug(msg, *args, **kwargs):
get_logger().debug(msg, *args, **kwargs)
def info(msg, *args, **kwargs):
get_logger().info(msg, *args, **kwargs)
def warn(msg, *args, **kwargs):
get_logger().warning(msg, *args, **kwargs)
... | normal | {
"blob_id": "355e2799e89dfea4f775480ea7d829a075f92473",
"index": 4241,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_logger():\n return current_app.logger\n\n\n<mask token>\n\n\ndef info(msg, *args, **kwargs):\n get_logger().info(msg, *args, **kwargs)\n\n\n<mask token>\n",
"step-3": ... | [
0,
2,
3,
4,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
with open('Grainger_Library.csv', newline='') as f:
reader = csv.reader(f)
data = list(reader)
del data[0]
<|reserved_special_token_0|>
data.sort(key=lambda x: x[1])
for i in range(0, len(data)):
gld.append((data[i][1]... | flexible | {
"blob_id": "79ff164c36cc5f0a2382a571ec183952a03e66cc",
"index": 9570,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('Grainger_Library.csv', newline='') as f:\n reader = csv.reader(f)\n data = list(reader)\ndel data[0]\n<mask token>\ndata.sort(key=lambda x: x[1])\nfor i in range(0, len(d... | [
0,
1,
2,
3,
4
] |
if __name__ == '__main__':
print('--------------------------------------')
query = 'user=pilgrim&database=master&password=PapayaWhip'
a_list = query.split('&')
print(a_list)
print('--------------------------------------')
a_list_of_lists = [v.split('=', 1) for v in a_list if '=' in v]
print(... | normal | {
"blob_id": "5c3bf49f88dec429ec85cceb8130cccf2691363b",
"index": 1538,
"step-1": "<mask token>\n",
"step-2": "if __name__ == '__main__':\n print('--------------------------------------')\n query = 'user=pilgrim&database=master&password=PapayaWhip'\n a_list = query.split('&')\n print(a_list)\n pr... | [
0,
1
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for i in range(0, n):
reg = int(input('Enter RegNo: '))
student_reg.append(reg)
marks = int(input('Enter marks: '))
student_marks.append(marks)
<|reserved_special_token_0|>
gplt.title('RegNo. V/S Marks')
gplt.xlabe... | flexible | {
"blob_id": "dcbbc7098410d771a7151af7c43ac4d0e4d46f18",
"index": 9135,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(0, n):\n reg = int(input('Enter RegNo: '))\n student_reg.append(reg)\n marks = int(input('Enter marks: '))\n student_marks.append(marks)\n<mask token>\ngplt.tit... | [
0,
1,
2,
3,
4
] |
"""
Django settings for hauki project.
"""
import logging
import os
import subprocess
import environ
import sentry_sdk
from django.conf.global_settings import LANGUAGES as GLOBAL_LANGUAGES
from django.core.exceptions import ImproperlyConfigured
from sentry_sdk.integrations.django import DjangoIntegration
CONFIG_FILE... | normal | {
"blob_id": "5ed34ada35dfb2f783af4485bf9d31aa42712b9a",
"index": 4480,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_git_revision_hash() ->str:\n \"\"\"\n Retrieve the git hash for the underlying git repository or die trying\n\n We need a way to retrieve git revision hash for sentry... | [
0,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
for i in range(-10, 0):
print(i, end=' ')
<|reserved_special_token_1|>
for i in range(-10,0):
print(i,end=" ") | flexible | {
"blob_id": "8d0fcf0bf5effec9aa04e7cd56b4b7098c6713cb",
"index": 70,
"step-1": "<mask token>\n",
"step-2": "for i in range(-10, 0):\n print(i, end=' ')\n",
"step-3": "for i in range(-10,0):\n print(i,end=\" \")",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
} | [
0,
1,
2
] |
## PURPOSE: get reads for certain motifs across certain tumors
## INPUT: manifest data all-tumor-manifest.csv
## collapsed fastq files sample.converted.unpaired.fastq.collapsed
## OUTPUT: table containing reads for specific motif across samples motif.tumor.common.reads.fastq.collapsed.summary.tsv
import... | normal | {
"blob_id": "ddabceb223f4e457a0f69af5abf793ae72e5f432",
"index": 1465,
"step-1": "<mask token>\n\n\ndef getCollapsedFastqDataframe(file):\n df = pd.read_table(file, header=None, delim_whitespace=True)\n df = df.dropna(axis=1, how='all')\n sample = file.split('/')\n sample = sample[len(sample) - 1]\n ... | [
2,
3,
4,
5,
6
] |
import io
from PIL import Image
def bytes_from_file(path, size, quality=15):
img = Image.open(path)
img = img.resize(size)
img_byte_arr = io.BytesIO()
img.save(img_byte_arr, format="JPEG", quality=quality)
return img_byte_arr.getvalue()
| normal | {
"blob_id": "3344eb5b3e5b5eaee7b08d0991be732dae62c7fc",
"index": 7137,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef bytes_from_file(path, size, quality=15):\n img = Image.open(path)\n img = img.resize(size)\n img_byte_arr = io.BytesIO()\n img.save(img_byte_arr, format='JPEG', qualit... | [
0,
1,
2,
3
] |
from django.contrib import admin
from orders.models import OrderModel
@admin.register(OrderModel)
class OrderAdmin(admin.ModelAdmin):
list_display = ['first_name', 'phone']
| normal | {
"blob_id": "a238175c94764137bfc8fac1ce67436016b1591a",
"index": 1519,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@admin.register(OrderModel)\nclass OrderAdmin(admin.ModelAdmin):\n <mask token>\n",
"step-3": "<mask token>\n\n\n@admin.register(OrderModel)\nclass OrderAdmin(admin.ModelAdmin):\... | [
0,
1,
2,
3
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.