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|>
def content_loss(content_layer, generated_layer):
return tf.scalar_mul(0.5, tf.nn.l2_loss(content_layer - generated_layer))
<|reserved_special_token_0|>
def get_gram_matrix(matrix, num_filters):
matrix_vectorized = t... | flexible | {
"blob_id": "f92b939bf9813e5c78bc450ff270d5fb6171792a",
"index": 4810,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef content_loss(content_layer, generated_layer):\n return tf.scalar_mul(0.5, tf.nn.l2_loss(content_layer - generated_layer))\n\n\n<mask token>\n\n\ndef get_gram_matrix(matrix, num... | [
0,
2,
3,
4,
5
] |
from rest_framework import serializers
from .models import Twit, Comment, Message
from django.contrib.auth.models import User
class TwitSerializer(serializers.ModelSerializer):
class Meta:
model = Twit
fields = '__all__'
class CommentSerializer(serializers.ModelSerializer):
class Meta:
... | normal | {
"blob_id": "536a67935527eb99bc0424613c9b931401db0b06",
"index": 6461,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass CommentSerializer(serializers.ModelSerializer):\n\n\n class Meta:\n model = Comment\n fields = '__all__'\n\n\nclass MessageSerializer(serializers.ModelSerialize... | [
0,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class BasicMC(commands.Cog):
<|reserved_special_token_0|>
@commands.command(name='stealskin', aliases=['skinsteal', 'skin'])
@commands.cooldown(1, 4, commands.BucketType.user)
async def skinner(self, ctx, gamertag: str):
response = await self.session.get(
... | flexible | {
"blob_id": "a6f242a0443ffbad835f86098b70ede41c03515b",
"index": 7652,
"step-1": "<mask token>\n\n\nclass BasicMC(commands.Cog):\n <mask token>\n\n @commands.command(name='stealskin', aliases=['skinsteal', 'skin'])\n @commands.cooldown(1, 4, commands.BucketType.user)\n async def skinner(self, ctx, ga... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
def process_the_source(fname, dest=None, host_ip=None, verbose=False):
assert os.path.exists(fname) and os.path.isfile(fname
), 'Cannot proceed without the fname in process_the_source().'
the_lines = []
with open(fname, 'r') as fIn:
for line in fIn:
... | flexible | {
"blob_id": "d6af9a75fbe8bdf1a81a352cee71ac81fb373b86",
"index": 9926,
"step-1": "<mask token>\n\n\ndef process_the_source(fname, dest=None, host_ip=None, verbose=False):\n assert os.path.exists(fname) and os.path.isfile(fname\n ), 'Cannot proceed without the fname in process_the_source().'\n the_li... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def solve(dpArr, list, box, i):
global boxes
global ans
if box == boxes:
s = 0
for j in list:
s += len(j)
if s == len(dpArr):
mx = 0
for j in list:
... | flexible | {
"blob_id": "883b4de18dddede97f850e3a184a0e1072bda99e",
"index": 814,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef solve(dpArr, list, box, i):\n global boxes\n global ans\n if box == boxes:\n s = 0\n for j in list:\n s += len(j)\n if s == len(dpArr):\n ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def register_cccmacms(cmap='all'):
"""create my personal colormaps with discrete colors and register them.
default is to register all of them. can also specify which one.
(@@ input arg cmap not im... | flexible | {
"blob_id": "31a5bf0b275238e651dcb93ce80446a49a4edcf4",
"index": 6561,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef register_cccmacms(cmap='all'):\n \"\"\"create my personal colormaps with discrete colors and register them.\n \n \n default is to register all of them. can also specif... | [
0,
1,
2,
3,
4
] |
alias_macro = {
"class": "Application",
"method": "alias_macro",
"doc": """
Returns or modifies the macro of a command alias.
""",
"syntax": """
Rhino.AliasMacro (strAlias [, strMacro])
""",
"params": {
0: {
"name": "alias",
"... | normal | {
"blob_id": "1574f034ff9b6ddb785e4c54758b2057009198ed",
"index": 7587,
"step-1": "<mask token>\n",
"step-2": "alias_macro = {'class': 'Application', 'method': 'alias_macro', 'doc':\n \"\"\"\n Returns or modifies the macro of a command alias.\n \"\"\",\n 'syntax': \"\"\"\n Rhino.AliasMacr... | [
0,
1,
2
] |
import unittest
def is_multiple(value, base):
return 0 == (value % base)
def fizz_buzz(value):
if is_multiple(value, 5) and is_multiple(value, 3):
return "FizzBuzz"
if is_multiple(value, 3):
return "Fizz"
if is_multiple(value, 5):
return "Buzz"
return str(value)
class F... | normal | {
"blob_id": "59d543ed443c156ac65f9c806ba5bada6bcd0c21",
"index": 6891,
"step-1": "<mask token>\n\n\nclass FizzBuzzTest(unittest.TestCase):\n\n def check_fizz_buzz(self, value, expected):\n result = fizz_buzz(value)\n self.assertEqual(expected, result)\n <mask token>\n\n def test_fizz_buzz_... | [
7,
10,
11,
12,
14
] |
<|reserved_special_token_0|>
class Test(unittest.TestCase):
<|reserved_special_token_0|>
def tearDown(self):
pass
def test_these_should_win_for_x(self):
self.assertEqual(TicTacToe_Board.IsWinningBoard_static([['x', 'x',
'x'], ['o', 'x', 'o'], ['o', 'x', 'o']]), 'x', 'should r... | flexible | {
"blob_id": "1968923cd923e68dc5ff2148802f18e40a5e6c33",
"index": 939,
"step-1": "<mask token>\n\n\nclass Test(unittest.TestCase):\n <mask token>\n\n def tearDown(self):\n pass\n\n def test_these_should_win_for_x(self):\n self.assertEqual(TicTacToe_Board.IsWinningBoard_static([['x', 'x',\n ... | [
9,
12,
13,
14,
16
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def bfs(start_nodes, g):
dq = deque()
dq.extend(start_nodes)
for i, j in start_nodes:
g[i][j] = -1
while dq:
y, x = dq.popleft()
for k in range(4):
b, a = dy[k] + y, dx[k] + x
... | flexible | {
"blob_id": "0e3bf0ddd654b92b2cd962a2f3935c639eeb0695",
"index": 2155,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef bfs(start_nodes, g):\n dq = deque()\n dq.extend(start_nodes)\n for i, j in start_nodes:\n g[i][j] = -1\n while dq:\n y, x = dq.popleft()\n for k i... | [
0,
1,
2,
3,
5
] |
#Takes - Contact Name(Must be saved in phone's contact list), Message, Time as input
# and sends message to the given contact at given time
# Accuracy Level ~ Seconds. (Also depends on your network speed)
from selenium import webdriver
PATH = 'C:\Program Files (x86)\chromedriver.exe'
driver = webdriver.Chrome(PATH)
f... | normal | {
"blob_id": "1811c0c5aca9d209638e2221cad2c30e80ee5199",
"index": 3116,
"step-1": "<mask token>\n\n\ndef send_msg():\n global nameofcontact, msg\n css_path = 'span[title=\"' + nameofcontact + '\"]'\n nameofcontact = driver.find_element_by_css_selector(css_path)\n nameofcontact.click()\n chatbox = d... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class VolttronWebRPC(object):
def __init__(self, url, username='admin', password='admin'):
"""
:param url: Jsonrpc endpoint for posting data.
:param username:
:param password:
"""
self._url = url
self._username = username
... | flexible | {
"blob_id": "6fdfcbcfdf2b680a1fbdb74f77fd5d1a9f7eac0b",
"index": 6105,
"step-1": "<mask token>\n\n\nclass VolttronWebRPC(object):\n\n def __init__(self, url, username='admin', password='admin'):\n \"\"\"\n :param url: Jsonrpc endpoint for posting data.\n :param username:\n :param p... | [
11,
12,
14,
15,
18
] |
"""
Given two strings A and B of lowercase letters, return true
if and only if we can swap two letters in A so that the result
equals B.
Example 1:
Input: A = "ab", B = "ba"
Output: true
"""
class Solution:
def buddyStrings(self, A: str, B: str) -> bool:
if len(A) != len(B):
return False... | normal | {
"blob_id": "dd902f99ee8dc23f56641b8e75544a2d4576c19a",
"index": 4437,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Solution:\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Solution:\n\n def buddyStrings(self, A: str, B: str) ->bool:\n if len(A) != len(B):\n r... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def job_spider(jid='1913e38066dd3c8e1Hd40t--FVE~', ka='search_list_1', i=0):
job_url = 'https://www.zhipin.com/job_detail/' + jid + '.html'
headers = {'cache-control': 'no-cache', 'user-agent':
'Mozilla/5.0 (Wind... | flexible | {
"blob_id": "5b894eac93bff44931df4ef8d845c23071a03227",
"index": 3461,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef job_spider(jid='1913e38066dd3c8e1Hd40t--FVE~', ka='search_list_1', i=0):\n job_url = 'https://www.zhipin.com/job_detail/' + jid + '.html'\n headers = {'cache-control': 'no-c... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def swap(arr, start, end):
while start < end:
arr[start], arr[end] = arr[end], arr[start]
start += 1
end -= 1
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def swap(arr, start, end):
while start < end:
... | flexible | {
"blob_id": "2180146da7ea745f5917ee66fd8c467437b5af4c",
"index": 6761,
"step-1": "<mask token>\n",
"step-2": "def swap(arr, start, end):\n while start < end:\n arr[start], arr[end] = arr[end], arr[start]\n start += 1\n end -= 1\n\n\n<mask token>\n",
"step-3": "def swap(arr, start, end... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
from odoo import fields, models
class LunchWizard(models.TransientModel):
_name = "lunch.wizard"
_description = "LunchWizard"
lun_type = fields.Char(string="Set New Lunch Type")
lunch_id = fields.Many2one('lunch.lunch', string="Lunch Id")
def action_process_lunch(self):... | normal | {
"blob_id": "85e5bf57f7eba2cbee0fbb8a4d37b5180208f9b7",
"index": 3830,
"step-1": "<mask token>\n\n\nclass LunchWizard(models.TransientModel):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass LunchWizard(models.TransientModel):\n ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class DotProductTest(simtest):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def _check(self, c, d):
d = numpy.array(d)
ds = d.copy()
ds[d > 511] = d[d > 511] - 1024
c = numpy.array(c)
cq = self._set_coeff(c)
cs = cq... | flexible | {
"blob_id": "53110d6e7923cf65c514d54950a0be165582e9a0",
"index": 4909,
"step-1": "<mask token>\n\n\nclass DotProductTest(simtest):\n <mask token>\n <mask token>\n\n def _check(self, c, d):\n d = numpy.array(d)\n ds = d.copy()\n ds[d > 511] = d[d > 511] - 1024\n c = numpy.arra... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def treeCounter(moveRight, moveDown):
row = 0
index = 0
trees = 0
finished = False
while not finished:
row += moveDown
if len(data) > row:
index = (index + moveRight) % len(data[ro... | flexible | {
"blob_id": "c22651437094723b711a959e031f1c7f928f735a",
"index": 7645,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef treeCounter(moveRight, moveDown):\n row = 0\n index = 0\n trees = 0\n finished = False\n while not finished:\n row += moveDown\n if len(data) > row:\n... | [
0,
1,
2,
3,
4
] |
import cv2
print(cv2.__version__)
image = cv2.imread("download.jpeg", 1)
print(image)
print(image.shape)
print(image[0])
print("~~~~~~~~~~~~~~~")
print(image.shape[0])
print("~~~~~~~~~~~~~~~")
print(len(image)) | normal | {
"blob_id": "0b0ae6101fd80bdbcf37b935268f3e49230599fb",
"index": 5715,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(cv2.__version__)\n<mask token>\nprint(image)\nprint(image.shape)\nprint(image[0])\nprint('~~~~~~~~~~~~~~~')\nprint(image.shape[0])\nprint('~~~~~~~~~~~~~~~')\nprint(len(image))\n",
... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
@log.route('/login', methods=['GET', 'POST'])
def login():
print(request.path)
if request.method == 'GET':
return render_template('exec/login.html')
else:
username = request.form.get('username')
... | flexible | {
"blob_id": "763e2db4eb9ad5953273fb310c8e9714964a39e6",
"index": 9576,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@log.route('/login', methods=['GET', 'POST'])\ndef login():\n print(request.path)\n if request.method == 'GET':\n return render_template('exec/login.html')\n else:\n ... | [
0,
1,
2,
3,
4
] |
import math
def math_builtins():
assert abs(-123) == 123
assert abs(-123.456) == 123.456
assert abs(2+3j) == math.sqrt(2**2 + 3**2)
assert divmod(5, 2) == (2, 1)
assert max(1, 2, 3, 4) == 4
assert min(1, 2, 3, 4) == 1
a = 2
b = 3
c = 7
assert pow(a, b) == a ** b
assert po... | normal | {
"blob_id": "c77db71844c65eb96946ac0cc384de43ad49ca99",
"index": 6007,
"step-1": "<mask token>\n\n\ndef math_builtins():\n assert abs(-123) == 123\n assert abs(-123.456) == 123.456\n assert abs(2 + 3.0j) == math.sqrt(2 ** 2 + 3 ** 2)\n assert divmod(5, 2) == (2, 1)\n assert max(1, 2, 3, 4) == 4\n ... | [
2,
3,
4,
5,
6
] |
from django.conf.urls import url
from django.contrib import admin
from comments.api.views import CommentListAPIView, CommentDetailAPIView
urlpatterns = [
url(r'^$', CommentListAPIView.as_view(), name='list'),
url(r'^(?P<pk>\d+)/$', CommentDetailAPIView, name='detail'),
]
| normal | {
"blob_id": "e08820ff4fb35a3770fcb110ef7181aad1abbae5",
"index": 8778,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [url('^$', CommentListAPIView.as_view(), name='list'), url(\n '^(?P<pk>\\\\d+)/$', CommentDetailAPIView, name='detail')]\n",
"step-3": "from django.conf.urls import url... | [
0,
1,
2,
3
] |
no=int(input("enter no:"))
rev=0
while no!=0:
r=no%10
no=no//10
rev=rev*10+r
print("reverse no is:",rev)
| normal | {
"blob_id": "b2371f9c774c605a52ff1a4fae2dd44a856076aa",
"index": 5522,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile no != 0:\n r = no % 10\n no = no // 10\n rev = rev * 10 + r\nprint('reverse no is:', rev)\n",
"step-3": "no = int(input('enter no:'))\nrev = 0\nwhile no != 0:\n r = no... | [
0,
1,
2,
3
] |
from flask import Flask, render_template, flash, request
import pandas as pd
from wtforms import Form, TextField, TextAreaField, validators, StringField, SubmitField
df = pd.read_csv('data1.csv')
try:
row = df[df['District'] == 'Delhi'].index[0]
except:
print("now city found")
DEBUG = True
app = Flask(__name_... | normal | {
"blob_id": "8240e6483f47abbe12e7bef02493bd147ad3fec6",
"index": 6998,
"step-1": "from flask import Flask, render_template, flash, request\nimport pandas as pd\nfrom wtforms import Form, TextField, TextAreaField, validators, StringField, SubmitField\n\ndf = pd.read_csv('data1.csv')\ntry:\n row = df[df['Distri... | [
0
] |
<|reserved_special_token_0|>
def get_copy_var_ops(src_scope_name: str, dest_scope_name: str) ->list:
holder = []
src_vars = tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES, scope=
src_scope_name)
dest_vars = tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES, scope=
dest_scope_name)
... | flexible | {
"blob_id": "9a40861239268aa62075b77b3ed452f31bb14fac",
"index": 2458,
"step-1": "<mask token>\n\n\ndef get_copy_var_ops(src_scope_name: str, dest_scope_name: str) ->list:\n holder = []\n src_vars = tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES, scope=\n src_scope_name)\n dest_vars = tf.get_... | [
4,
5,
6,
7,
8
] |
<|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": "1eb5df463bbd39002c5dbc3f88459e2f26d4b465",
"index": 8505,
"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 = [('produksi', ... | [
0,
1,
2,
3,
4
] |
AuthorPath = 'data/Author.csv'
PaperPath = 'buff/Paper.TitleCut.csv'
PaperAuthorPath = 'data/PaperAuthor.csv'
AffilListPath = 'buff/AffilList2.csv'
StopwordPath = 'InternalData/en.lst'
| normal | {
"blob_id": "690e7cc9047b3a445bf330524df52e2b359f1f13",
"index": 958,
"step-1": "<mask token>\n",
"step-2": "AuthorPath = 'data/Author.csv'\nPaperPath = 'buff/Paper.TitleCut.csv'\nPaperAuthorPath = 'data/PaperAuthor.csv'\nAffilListPath = 'buff/AffilList2.csv'\nStopwordPath = 'InternalData/en.lst'\n",
"step-3... | [
0,
1
] |
from rest_framework.urlpatterns import format_suffix_patterns
from django.urls import path
from external_api import views
urlpatterns = [path('darksky/', views.DarkSkyView.as_view())]
urlpatterns = format_suffix_patterns(urlpatterns)
| normal | {
"blob_id": "e40f0a25d0c02f36c254e630133dc1fb11f29d4d",
"index": 8156,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('darksky/', views.DarkSkyView.as_view())]\nurlpatterns = format_suffix_patterns(urlpatterns)\n",
"step-3": "from rest_framework.urlpatterns import format_suffix_patt... | [
0,
1,
2
] |
<|reserved_special_token_0|>
def getLectures(name, url):
urlprefix = 'http://www.ocw.titech.ac.jp'
response = requests.get(url)
soup = BeautifulSoup(response.content, 'lxml')
table = soup.find('table', class_='ranking-list').tbody
for item in table.find_all('tr'):
code = item.find('td', cl... | flexible | {
"blob_id": "24274dddbeb1be743cfcac331ee688d48c9a46dd",
"index": 8647,
"step-1": "<mask token>\n\n\ndef getLectures(name, url):\n urlprefix = 'http://www.ocw.titech.ac.jp'\n response = requests.get(url)\n soup = BeautifulSoup(response.content, 'lxml')\n table = soup.find('table', class_='ranking-list... | [
1,
2,
3,
4,
5
] |
# We will try to implement add noise to audio file and filter it using Mean and Median Filters.
import numpy as np
import scipy
import matplotlib.pyplot as plt
from scipy.io.wavfile import read
from scipy.io.wavfile import write
rate,audio_original = read('Audio_Original.wav')
audio = audio_original[:,0]
write("Audi... | normal | {
"blob_id": "844b8e2d4f05a51282b356c995f2733d6935a5d6",
"index": 5552,
"step-1": "<mask token>\n\n\ndef Plot_Audio(audio):\n s = audio.shape[0]\n time = np.arange(s)\n plt.plot(time, audio)\n plt.show()\n\n\ndef Add_Noise(audio, mu=0, sigma=1):\n \"\"\"\n\tAdding Gaussian Noise\n\t\"\"\"\n gaus... | [
4,
5,
6,
7,
8
] |
import numpy as np
class nearest(svm):
name="MLLKM2"
def __init__(self):
svm.__init__(self)
def fit(self,x,y):
self.x=x
self.y=y
def predict(self,x):
diff=np.subtract(x,self.x)
distance=np.linalg.norm(diff,axis=1)
dmin= np.argmin( distance )
... | normal | {
"blob_id": "7d1ca15129b1bf6b713e1d5eda4436d4a8539ad1",
"index": 5939,
"step-1": "<mask token>\n\n\nclass nearest(svm):\n <mask token>\n\n def __init__(self):\n svm.__init__(self)\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass nearest(svm):\n <mask token>\n\n def ... | [
2,
3,
5,
6,
7
] |
import argparse # for handling command line arguments
import collections # for container types like OrderedDict
import configparser
import hashlib # for SHA-1
import os
import re
import sys
import zlib # git compresses everything using zlib
argparser = argparse.ArgumentParser(description="The stupid content tracker")
... | normal | {
"blob_id": "1c8145007edb09d77a3b15de5c34d0bc86c0ba97",
"index": 8343,
"step-1": "import argparse # for handling command line arguments\nimport collections # for container types like OrderedDict\nimport configparser\nimport hashlib # for SHA-1\nimport os\nimport re\nimport sys\nimport zlib # git compresses every... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class ScooterHutAUSpider(StockInStoreSpider):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_sp... | flexible | {
"blob_id": "e37f4422c1063df50453f7abf72a0a9a31156d8b",
"index": 899,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass ScooterHutAUSpider(StockInStoreSpider):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class ReplaceCornersAtCertainAngles(object):
def __init__(self):
windowWidth = 250
windowHeight = 140
windowWidthResize = 100
windowHeightResize = 0
self.w = vanilla.FloatingWindow((windowWidth, windowHeight),
'Replace Corners At Ce... | flexible | {
"blob_id": "540ae4be6a41d52d9c803f829fc8b13b523b31bc",
"index": 116,
"step-1": "<mask token>\n\n\nclass ReplaceCornersAtCertainAngles(object):\n\n def __init__(self):\n windowWidth = 250\n windowHeight = 140\n windowWidthResize = 100\n windowHeightResize = 0\n self.w = vani... | [
8,
9,
10,
11,
12
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
while True:
if c0 % 2 == 0:
c0 //= 2
if c0 != 1:
step += 1
print(' New value is ', c0, ':', 'step', step)
continue
elif c0 == 1:
step += 1
pri... | flexible | {
"blob_id": "e7db3390d30f86e19eee930c48e5f848f41cc579",
"index": 645,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile True:\n if c0 % 2 == 0:\n c0 //= 2\n if c0 != 1:\n step += 1\n print(' New value is ', c0, ':', 'step', step)\n continue\n el... | [
0,
1,
2,
3
] |
import datetime
import discord
def getTeams(reign, uprising, hunters, fuel, mayhem, gladiators, charge, outlaws, spark,
spitfire, excelsior, eternal, fusion, dynasty, shock, dragons, defiant, valiant, titans,
justice) :
teamList = discord.Embed(
title="Overwatch League Teams",
description="2021 Sea... | normal | {
"blob_id": "9a02e09cbfe2c9b6ebb9d20ba6cea639871f0838",
"index": 7647,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef getTeams(reign, uprising, hunters, fuel, mayhem, gladiators, charge,\n outlaws, spark, spitfire, excelsior, eternal, fusion, dynasty, shock,\n dragons, defiant, valiant, tit... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
featureProvider.add(shapeFeatureProvider)
featureProvider.add(statisticsFeatureProvider)
<|reserved_special_token_0|>
featureExtractor.extractFeatures(nodeFeatures, edgeFeatures, featureProvider)
<|reserved_special_token_1|>
<|... | flexible | {
"blob_id": "37d817436ce977339594867ef917177e7371a212",
"index": 6847,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfeatureProvider.add(shapeFeatureProvider)\nfeatureProvider.add(statisticsFeatureProvider)\n<mask token>\nfeatureExtractor.extractFeatures(nodeFeatures, edgeFeatures, featureProvider)\n",
... | [
0,
1,
2,
3,
4
] |
import sys
import os
import unittest
from wireless.trex_wireless_manager import APMode
from wireless.trex_wireless_manager_private import *
class APInfoTest(unittest.TestCase):
"""Tests methods for the APInfo class."""
def test_init_correct(self):
"""Test the __init__ method when parameters are corr... | normal | {
"blob_id": "ae5dfa7fa6a0d7349d6ae29aeac819903facb48f",
"index": 3518,
"step-1": "<mask token>\n\n\nclass APInfoTest(unittest.TestCase):\n <mask token>\n <mask token>\n <mask token>\n\n def test_init_no_ip(self):\n \"\"\"Test the __init__ method when parameter 'ip' is None.\n Since the ... | [
10,
11,
13,
14,
16
] |
<|reserved_special_token_0|>
class MouseButton:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class MouseButton:
Left = 0
Right = 1
Middle = 2
<|reserved_special_token_1|>
class ClickActi... | flexible | {
"blob_id": "cabebeb5ca02da2505df4a138e8b28f74dd108fa",
"index": 4362,
"step-1": "<mask token>\n\n\nclass MouseButton:\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass MouseButton:\n Left = 0\n Right = 1\n Middle = 2\n",
"step-3": "class ClickAction:\n ... | [
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
cassandra = {'nodes': ['localhost'], 'keyspace': 'coffee'}
| flexible | {
"blob_id": "0738fc48bc367f1df75567ab97ce20d3e747dc18",
"index": 8897,
"step-1": "<mask token>\n",
"step-2": "cassandra = {'nodes': ['localhost'], 'keyspace': 'coffee'}\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
from bs4 import BeautifulSoup
import requests
import pymongo
client = pymongo.MongoClient('localhost', 27017)
ku = client['ku']
url_list1 = ku['url_list_index']
start_url="http://news.ccsu.cn/index.htm"
url_host="http://news.ccsu.cn/"
def get_channel_urls(url):
wb_data = requests.get(url)
wb_data.encoding = 'ut... | normal | {
"blob_id": "4791b210f328dff5d48ff5afc381a98a5a1a2b7b",
"index": 1969,
"step-1": "<mask token>\n\n\ndef get_channel_urls(url):\n wb_data = requests.get(url)\n wb_data.encoding = 'utf-8'\n soup = BeautifulSoup(wb_data.text, 'lxml')\n links = soup.select('body > div.navWrap.clearfix > div > ul > li > a... | [
1,
2,
3,
4,
5
] |
# -*- coding: utf-8 -*-
import requests
import json
url = "http://39.108.188.34:9090/spider/zhongdengdengji.go"
# url = "http://localhost:9090/spider/zhongdengdengji.go"
input = {
"timelimit": "1年",
"title": "GD20190305001",
"maincontractno": "YT20181228001",
"maincontractcurrency": "人民币",
"mainc... | normal | {
"blob_id": "ad024a2001dc6a6fa3a2a9c1b51f79132e914897",
"index": 7592,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(response.text)\n",
"step-3": "<mask token>\nurl = 'http://39.108.188.34:9090/spider/zhongdengdengji.go'\ninput = {'timelimit': '1年', 'title': 'GD20190305001', 'maincontractno':\n ... | [
0,
1,
2,
3,
4
] |
import json
import requests
import random
import boto3
from email.parser import BytesParser, Parser
from email.policy import default
##################################
endpoint = 'https://5295t8jcs0.execute-api.us-east-1.amazonaws.com/Prod'
##################################
def get_msg_body(msg):
type = msg.get_... | normal | {
"blob_id": "cc99811321083147540a00e8029b792c8afc2ada",
"index": 3233,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_msg_body(msg):\n type = msg.get_content_maintype()\n if type == 'multipart':\n for part in msg.get_payload():\n if part.get_content_maintype() == 'text... | [
0,
2,
3,
4,
5
] |
# -*- coding: cp1251 -*-
import arcpy as a
from arcpy import AddMessage as msg, AddWarning as warning, AddError as error
from os import mkdir, walk
from os.path import join, dirname, basename, splitext
from glob import glob as get_files
from shutil import copy
from collections import OrderedDict
input_folder = a.GetP... | normal | {
"blob_id": "409e0fc0b1c1d86c5526d33ba271a8387eecf748",
"index": 9872,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nmsg(\"\"\"\nПроверка на наличие подпапок исходной папки в выходной:\"\"\")\nfor folder in input_folders:\n if folder in output_folders:\n warning(' ' + folder)\n else:\n ... | [
0,
1,
2,
3,
4
] |
# -*- coding:utf-8 -*-
import re
# 普通字符串 匹配本身
re_str = r'abc'
result = re.fullmatch(re_str, 'abc')
print(result)
# 匹配任意字符 一个.只能匹配一个字符
re_str = r'a.c'
result = re.fullmatch(re_str, 'abc')
print(result)
# \w匹配字母数字或下划线
# 匹配一个长度是5的字符串并且字符串的前两位是数字字母或者下划线后面是三个任意字符串 \w中文也能匹配
re_str = r'\w\w...'
result = re.fullmatch(re_str, ... | normal | {
"blob_id": "e0e00688a75021c2f8b608d4c942f5e68f6a6a48",
"index": 6282,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(result)\n<mask token>\nprint(result)\n<mask token>\nprint(result)\n<mask token>\nprint(result)\n<mask token>\nprint(result)\n<mask token>\nprint(result)\n<mask token>\nprint(result)... | [
0,
1,
2,
3,
4
] |
import input_data
import tensorflow as tf
from infogan import InfoGAN
if __name__ == '__main__':
# get input data
mnist_data = input_data.load_mnist_dataset('../../dataset/mnist_data', one_hot=True)
num_sample = mnist_data.train.num_examples
dataset = 'mnist'
if dataset == 'mnist':
input_di... | normal | {
"blob_id": "02a28b61ad9d664c89829df019f4887c2c869f91",
"index": 6046,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n mnist_data = input_data.load_mnist_dataset('../../dataset/mnist_data',\n one_hot=True)\n num_sample = mnist_data.train.num_examples\n dataset ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def crawl_bitcoin_price():
print('start crawling!')
bitcoin_prices = get_web_content(COIN_MARKET_CAP_URL)
bitcoin_prices = filter_invalid_records(bitcoin_prices)
if crawl_enabled:
Timer(BITCOIN_CRAWLING_PERIOD_SEC, crawl_bitcoin_price).start()
else:
pri... | flexible | {
"blob_id": "ebbc6f9115e6b4ca7d1050a59cf175d123b6f3aa",
"index": 4871,
"step-1": "<mask token>\n\n\ndef crawl_bitcoin_price():\n print('start crawling!')\n bitcoin_prices = get_web_content(COIN_MARKET_CAP_URL)\n bitcoin_prices = filter_invalid_records(bitcoin_prices)\n if crawl_enabled:\n Time... | [
3,
4,
5,
6,
8
] |
# -*- coding: utf-8 -*-
import datetime
from south.db import db
from south.v2 import SchemaMigration
from django.db import models
class Migration(SchemaMigration):
def forwards(self, orm):
# Adding field 'PhoneUser.last_contacted'
db.add_column(u'smslink_phoneuser', 'last_contacted',
... | normal | {
"blob_id": "2c1de638ac25a9f27b1af94fa075b7c1b9df6884",
"index": 993,
"step-1": "<mask token>\n\n\nclass Migration(SchemaMigration):\n\n def forwards(self, orm):\n db.add_column(u'smslink_phoneuser', 'last_contacted', self.gf(\n 'django.db.models.fields.DateTimeField')(null=True, blank=True)... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
@pytest.fixture(scope='session')
def me(api):
return api.people.me()
<|reserved_special_token_1|>
<|reserved_special_token_0|>
import pytest
import ciscosparkapi
from tests.utils import create_string
@pytest.fixture(sco... | flexible | {
"blob_id": "9b7ffa2bb62a8decbec51c6bdea38b4338726816",
"index": 1891,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@pytest.fixture(scope='session')\ndef me(api):\n return api.people.me()\n",
"step-3": "<mask token>\nimport pytest\nimport ciscosparkapi\nfrom tests.utils import create_string\n\... | [
0,
1,
2,
3
] |
import json
import nltk
with open('posts.json', 'r') as infile:
posts = []
for line in infile:
posts.append(json.loads(line[0:len(line)-2]))
for post in posts:
print '\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n'
print '~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~... | normal | {
"blob_id": "2f15814d97708e33585ea6b45e89b5a5e69d82fe",
"index": 5694,
"step-1": "import json\nimport nltk\n\nwith open('posts.json', 'r') as infile:\n\tposts = []\n\tfor line in infile:\n\t\tposts.append(json.loads(line[0:len(line)-2]))\n\nfor post in posts:\n print '\\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~... | [
0
] |
import pandas as pd
import numpy as np
#from ctaFunction import std_normalized
def barStdNormal(bars, timeperiod=5):
'''Std Normal '''
close = bars['close']
result = close.rolling(timeperiod).apply(std_normalized)
return result | normal | {
"blob_id": "6fa0e1dabd178507c32c62146b404bb42f8445d4",
"index": 9860,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef barStdNormal(bars, timeperiod=5):\n \"\"\"Std Normal \"\"\"\n close = bars['close']\n result = close.rolling(timeperiod).apply(std_normalized)\n return result\n",
"s... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
for _ in range(int(input())):
n = int(input())
s = input()
cur = 0
for i in s[::-1]:
if i == ')':
cur += 1
else:
break
print('Yes') if cur > n // 2 else print('No')
<|reserved_special_token_1|>
fo... | flexible | {
"blob_id": "31b420adebbe0d3ee6da2ed8236ece1526bdb063",
"index": 6290,
"step-1": "<mask token>\n",
"step-2": "for _ in range(int(input())):\n n = int(input())\n s = input()\n cur = 0\n for i in s[::-1]:\n if i == ')':\n cur += 1\n else:\n break\n print('Yes') ... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
urlpatterns = patterns('', ('^admin/', include('django.contrib.admin.urls')
), ('^polls/', include('goimcommunity.polls.urls')), ('^league/',
include('goimcommunity.leaguesystem.urls')), ('^board/', include(
'sphene.sp... | flexible | {
"blob_id": "f44ff7488ae8fc64bc1785fb6cbe80c4cc011fbe",
"index": 6808,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = patterns('', ('^admin/', include('django.contrib.admin.urls')\n ), ('^polls/', include('goimcommunity.polls.urls')), ('^league/',\n include('goimcommunity.leaguesystem... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class Keychains(DeviceFeature):
<|reserved_special_token_0|>
class DeviceAttributes(genie.conf.base.attributes.DeviceSubAttributes):
class KeyChainAttributes(KeyedSubAttributes):
def __init__(self, parent, key):
self.key_chain = key
... | flexible | {
"blob_id": "6d2581b83a2839dcbc644ca572b05b158d80b58d",
"index": 2479,
"step-1": "<mask token>\n\n\nclass Keychains(DeviceFeature):\n <mask token>\n\n\n class DeviceAttributes(genie.conf.base.attributes.DeviceSubAttributes):\n\n\n class KeyChainAttributes(KeyedSubAttributes):\n\n def __in... | [
4,
6,
7,
8,
9
] |
from django.urls import path
from . import views
urlpatterns = [
# @app.route("/")
path('', views.home),
path("teams", views.showTeams),
path("teams/new", views.new),
path("teams/<teamname>", views.showSpecificTeam),
# path("allfood", views.showAllFoodItems),
# path("team/<teamname>",... | normal | {
"blob_id": "e267108177841110493061a4f84ae3d29850d028",
"index": 1853,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('', views.home), path('teams', views.showTeams), path(\n 'teams/new', views.new), path('teams/<teamname>', views.showSpecificTeam)]\n",
"step-3": "from django.url... | [
0,
1,
2,
3
] |
import itertools
def permutations(string):
return list("".join(p) for p in set(itertools.permutations(string))) | normal | {
"blob_id": "3d49d03dbc38ee37eadd603b4b464b0e2e1a33d5",
"index": 5280,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef permutations(string):\n return list(''.join(p) for p in set(itertools.permutations(string)))\n",
"step-3": "import itertools\n\n\ndef permutations(string):\n return list('... | [
0,
1,
2,
3
] |
#Exercise 5
#Define with names stair1, stair2, and stair3 (from bottom up to top), and insert within the building model, the 3 stair models of the building. | normal | {
"blob_id": "4c42bad4197b51be0e9d18307c7b954a29281fe1",
"index": 3259,
"step-1": "#Exercise 5\n#Define with names stair1, stair2, and stair3 (from bottom up to top), and insert within the building model, the 3 stair models of the building.",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,... | [
1
] |
<|reserved_special_token_0|>
def test_keywordbid_rule_init(kwb_rule, account):
assert kwb_rule.get_max_bid_display() == kwb_rule.max_bid * 1000000
assert kwb_rule.get_bid_increase_percentage_display(
) == kwb_rule.bid_increase_percentage / 100
assert kwb_rule.get_target_bid_diff_display(
)... | flexible | {
"blob_id": "e0435b0b34fc011e7330ab8882865131f7f78882",
"index": 922,
"step-1": "<mask token>\n\n\ndef test_keywordbid_rule_init(kwb_rule, account):\n assert kwb_rule.get_max_bid_display() == kwb_rule.max_bid * 1000000\n assert kwb_rule.get_bid_increase_percentage_display(\n ) == kwb_rule.bid_increa... | [
3,
4,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(dataset.info())
<|reserved_special_token_0|>
regressor.fit(features, labels)
<|reserved_special_token_0|>
regressor.predict(x)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
dataset = pd.read_csv('University_da... | flexible | {
"blob_id": "94e8f0532da76c803b23fe2217b07dc8cf285710",
"index": 950,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(dataset.info())\n<mask token>\nregressor.fit(features, labels)\n<mask token>\nregressor.predict(x)\n",
"step-3": "<mask token>\ndataset = pd.read_csv('University_data.csv')\nprint(... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def extractPatternOccurrence(songName, inStart, inEnd, useTies, songs):
"""
given song name, occurrence start, occurrence end, and the database of score files,
return the notes of the associated pattern occurrence
useTies is a boolean determining whether or not tied notes ... | flexible | {
"blob_id": "eb9135c6bcf89a62534cfc8480e5d44a089fe5a8",
"index": 1216,
"step-1": "<mask token>\n\n\ndef extractPatternOccurrence(songName, inStart, inEnd, useTies, songs):\n \"\"\"\n given song name, occurrence start, occurrence end, and the database of score files,\n return the notes of the associated ... | [
3,
8,
9,
10,
11
] |
from pandas_datareader import data as pdr
from datetime import date
class YahooHelper:
"""
Class to fetch Yahoo data
"""
def __init__(self):
"""
Default constructor which initiates object
"""
pass
def get_data(self, symbol):
"""
Function to collect... | normal | {
"blob_id": "b4b4dad5cf630dc1a627e323ea63577583d1e1c3",
"index": 1551,
"step-1": "<mask token>\n\n\nclass YahooHelper:\n <mask token>\n\n def __init__(self):\n \"\"\"\n Default constructor which initiates object\n \"\"\"\n pass\n <mask token>\n\n def get_stock_data(symbol)... | [
4,
5,
6,
7,
8
] |
import os
import multiprocessing
import time
import psycopg2
#os.system("myproject1\\runscrapy2.py")
#from scrapy import cmdline
#os.system("scrapy crawl parts")
#cmdline.execute("cd myproject1".split())
#cmdline.execute("myproject1\\runscrapy.bat".split())
# start = time.perf_counter()
connection = psycopg2.conne... | normal | {
"blob_id": "8e0d729fa55aabede123d89a507296b7d8a45c8b",
"index": 1705,
"step-1": "<mask token>\n\n\ndef urls():\n os.system('urls.bat')\n\n\ndef urls_1():\n os.system('urls_1.bat')\n\n\n<mask token>\n\n\ndef urls_3():\n os.system('urls_3.bat')\n\n\ndef urls_4():\n os.system('urls_4.bat')\n\n\ndef url... | [
39,
53,
59,
67,
75
] |
from django.shortcuts import render
from django.views.generic import ListView, DetailView
from django.views.generic.edit import CreateView, UpdateView
from django.urls import reverse_lazy
from django.utils import timezone
from time import time
import json
from .models import Attendance, Disciple
from users.models imp... | normal | {
"blob_id": "38c78a51a50ee9844aec8b8cdcdd42b858748518",
"index": 2552,
"step-1": "<mask token>\n\n\nclass AttendanceDetailView(DetailView):\n <mask token>\n <mask token>\n\n\n<mask token>\n\n\nclass AttendanceCreateView(CreateView):\n model = Attendance\n template_name = 'attendance_new.html'\n fi... | [
5,
8,
9,
10,
11
] |
<|reserved_special_token_0|>
class Encoder(object):
def __init__(self, pin_x='P4', pin_y='P5', pin_mode=Pin.PULL_UP, scale=
1, min=0, max=100, reverse=False):
self.pin_x = pin_x if isinstance(pin_x, Pin) else Pin(pin_x, mode=
Pin.IN, pull=pin_mode)
self.pin_y = pin_y if isinst... | flexible | {
"blob_id": "1406b2ab78b52823a8f455c8e2719f6bd84bd168",
"index": 822,
"step-1": "<mask token>\n\n\nclass Encoder(object):\n\n def __init__(self, pin_x='P4', pin_y='P5', pin_mode=Pin.PULL_UP, scale=\n 1, min=0, max=100, reverse=False):\n self.pin_x = pin_x if isinstance(pin_x, Pin) else Pin(pin_x... | [
7,
9,
10,
11,
12
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(now.year, now.month, now.day, now.hour, now.minute, now.second)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
now = datetime.datetime.now()
print(now.year, now.month, now.day, now.hour, now.minute, now.second)... | flexible | {
"blob_id": "3af91de0b25f575ec9d981d7711c710a7e9695e4",
"index": 6819,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(now.year, now.month, now.day, now.hour, now.minute, now.second)\n",
"step-3": "<mask token>\nnow = datetime.datetime.now()\nprint(now.year, now.month, now.day, now.hour, now.minut... | [
0,
1,
2,
3
] |
import nltk
import A
from collections import defaultdict
from nltk.align import Alignment, AlignedSent
class BerkeleyAligner():
def __init__(self, align_sents, num_iter):
self.t, self.q = self.train(align_sents, num_iter)
# TODO: Computes the alignments for align_sent, using this model's parameters. Return... | normal | {
"blob_id": "bf40b516e202af14469cd4012597ba412e663f56",
"index": 5898,
"step-1": "import nltk\nimport A\nfrom collections import defaultdict\nfrom nltk.align import Alignment, AlignedSent\n\nclass BerkeleyAligner():\n\n def __init__(self, align_sents, num_iter):\n\tself.t, self.q = self.train(align_sents, num... | [
0
] |
<|reserved_special_token_0|>
@clockit
def analyze_cover(benchmarks, result_dir, calc_f1, append):
if not append:
print_headers(result_dir)
for benchmark in benchmarks:
count_benchmark_cover(result_dir, calc_f1, benchmark)
<|reserved_special_token_0|>
def f1_score(community, ground_truth):
... | flexible | {
"blob_id": "dc5b9600828857cc5ea434a7b010cd8aa2589d22",
"index": 6568,
"step-1": "<mask token>\n\n\n@clockit\ndef analyze_cover(benchmarks, result_dir, calc_f1, append):\n if not append:\n print_headers(result_dir)\n for benchmark in benchmarks:\n count_benchmark_cover(result_dir, calc_f1, be... | [
2,
3,
5,
6,
7
] |
import tensorflow as tf
import numpy as np
import time
import os
from sklearn.metrics import roc_curve
import matplotlib.pyplot as plt
from src.model import get_args
from src.funcs import linear
from src.youtubeface import load_ytf_data
from src.lfw import load_lfw_data
from src.facescrub import load_fs_data
from src... | normal | {
"blob_id": "459dd9302f7100ad02119cc94b735b19287f21e5",
"index": 5956,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n os.environ['CUDA_VISIBLE_DEVICES'] = '0'\n total_iteration = 300000\n m = 512\n q = 32\n lam = 0.01\n beta = 1.0\n margin = 0.5\n s = ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class LogisticRegression:
<|reserved_special_token_0|>
def __init__(self, max_iter=2000, learning_rate=0.01):
self.max_iter = max_iter
self.learning_rate = learning_rate
print('LogisticRegression Model(learning_rate={}, max_iteration={})'
.form... | flexible | {
"blob_id": "1dd62264aafe8ee745a3cfdfb994ac6a40c1af42",
"index": 1848,
"step-1": "<mask token>\n\n\nclass LogisticRegression:\n <mask token>\n\n def __init__(self, max_iter=2000, learning_rate=0.01):\n self.max_iter = max_iter\n self.learning_rate = learning_rate\n print('LogisticRegre... | [
7,
11,
13,
14,
15
] |
from Stack import Stack
from Regex import Regex
from Symbol import Symbol
class Postfix:
def __init__(self, regex):
self.__regex = regex.expression
self.__modr = Postfix.modRegex(self.__regex)
self.__pila = Stack()
self.__postfix = self.convertInfixToPostfix()
def getRegex(... | normal | {
"blob_id": "acc39044fa1ae444dd4a737ea37a0baa60a2c7bd",
"index": 4040,
"step-1": "<mask token>\n\n\nclass Postfix:\n\n def __init__(self, regex):\n self.__regex = regex.expression\n self.__modr = Postfix.modRegex(self.__regex)\n self.__pila = Stack()\n self.__postfix = self.convert... | [
4,
5,
7,
9,
11
] |
'''
Created on 14 november 2015
@author: federico
'''
import paho.mqtt.client as mosquitto
import json
import urllib,urllib2
import datetime
import threading
import time
from pygame import mixer
from datetime import timedelta
#ALARM SOUND PATH
alarm_path="/home/pi/SmartBed/Smart_Bed/src/Rooster.wav"
#DWEET&FREEBOA... | normal | {
"blob_id": "05bd95966d72dd40b9b828932b0bf70e40ddb573",
"index": 1511,
"step-1": "'''\nCreated on 14 november 2015\n\n@author: federico\n'''\n\nimport paho.mqtt.client as mosquitto\nimport json\nimport urllib,urllib2\nimport datetime\nimport threading\nimport time\nfrom pygame import mixer\nfrom datetime import ... | [
0
] |
flags =[]
sourcefiles:str = []
headerfiles:str = []
mainfile:str = ""
outfilename = "a.out"
assemblyfilename = "a.asm"
includedfilenames = []
class Variables:
size:bytes
name:str
class cstruct:
structname:string
def claprocessor():
print(sys.argv)
i=0
for stri in sys.argv:
if stri.... | normal | {
"blob_id": "24187284ff3e03cf79b8545415005c71f9355ddc",
"index": 9062,
"step-1": "<mask token>\n\n\nclass Variables:\n size: bytes\n name: str\n\n\nclass cstruct:\n structname: string\n\n\n<mask token>\n\n\ndef cpreprosscssor():\n maintokens = lexer(mainfile)\n return\n\n\ndef cprocessor():\n r... | [
4,
5,
6,
7,
8
] |
from django.conf import settings
from .base import *
import os
DEBUG = True
SECRET_KEY = os.environ['SECRET_KEY']
ROOT_URLCONF = 'floweryroad.urls.docker_production'
ALLOWED_HOSTS = [os.environ['WEB_HOST']]
CORS_ORIGIN_WHITELIST = [os.environ['CORS']]
DATABASES = {'default': {'ENGINE': 'django.db.backends.postgresql_ps... | normal | {
"blob_id": "ab35684166f07a3ab9e64f2ff98980e25a3fc576",
"index": 1643,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nDEBUG = True\nSECRET_KEY = os.environ['SECRET_KEY']\nROOT_URLCONF = 'floweryroad.urls.docker_production'\nALLOWED_HOSTS = [os.environ['WEB_HOST']]\nCORS_ORIGIN_WHITELIST = [os.environ['CO... | [
0,
1,
2
] |
import numpy as np
raw = np.load("raw_with_freq.npy").item()
for i in list(raw.keys()):
if len(i) > 8:
del(raw[i])
print(raw)
print(len(list(raw.keys())))
np.save("shorten_raw_with_freq.npy", raw)
| normal | {
"blob_id": "ffb17b370c892696b341f6d37a2cfe106a5670a5",
"index": 4265,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in list(raw.keys()):\n if len(i) > 8:\n del raw[i]\nprint(raw)\nprint(len(list(raw.keys())))\nnp.save('shorten_raw_with_freq.npy', raw)\n",
"step-3": "<mask token>\nraw ... | [
0,
1,
2,
3,
4
] |
g7 = int(input())
h7 = g7 / 2
i = g7 - 1
print(int(h7 * i))
| normal | {
"blob_id": "abb08956f55fd1e8af27ce12fa94a4137d7d908e",
"index": 7251,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(int(h7 * i))\n",
"step-3": "g7 = int(input())\nh7 = g7 / 2\ni = g7 - 1\nprint(int(h7 * i))\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
} | [
0,
1,
2
] |
import functools
import re
import nltk.data
from nltk.corpus import stopwords
from nltk.probability import FreqDist
from nltk.tokenize import RegexpTokenizer
def clean(string):
string = re.sub(r"\'s", " \'s", string)
string = re.sub(r"\'ve", " \'ve", string)
string = re.sub(r"n\'t", " n\'t", string)
s... | normal | {
"blob_id": "837e84d4a58d8fd0d0ffc24973d196ae57f9a260",
"index": 1723,
"step-1": "<mask token>\n\n\ndef reorder_sentences(output_sentences, input):\n\n def custom_sort(s1, s2):\n return input.find(s1) - input.find(s2)\n output_sentences.sort(key=functools.cmp_to_key(custom_sort))\n return output_... | [
1,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
class Documents(Base):
__tablename__ = 'documents'
id = Column(Integer, primary_key=True, index=True)
name_doc = Column(String, index=True)
exp = Column(DATE, index=True)
notif = Column(Integer)
descrip = Column(String, index=True)
owner_username = Column(Strin... | flexible | {
"blob_id": "acf69cd714f04aeceb4be39b8a7b2bc5d77cd69f",
"index": 3307,
"step-1": "<mask token>\n\n\nclass Documents(Base):\n __tablename__ = 'documents'\n id = Column(Integer, primary_key=True, index=True)\n name_doc = Column(String, index=True)\n exp = Column(DATE, index=True)\n notif = Column(In... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
api_key = '078c8443640961d5ce547c8269db5fd7'
<|reserved_special_token_1|>
# OpenWeatherMap API Key
api_key = "078c8443640961d5ce547c8269db5fd7"
| flexible | {
"blob_id": "4eb3d94a5fd22fc29000ec32475de9cbae1c183a",
"index": 5255,
"step-1": "<mask token>\n",
"step-2": "api_key = '078c8443640961d5ce547c8269db5fd7'\n",
"step-3": "# OpenWeatherMap API Key\napi_key = \"078c8443640961d5ce547c8269db5fd7\"\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
... | [
0,
1,
2
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import logging
import airflow
from airflow import DAG
from airflow.operators.python_operator import PythonOperator
from airflow.operators import BashOperator, DummyOperator
from datetime import datetime, timedelta
# -----------------------------------------------------... | normal | {
"blob_id": "49492ad1a1734be02ebefb77095fd560a7a7efd8",
"index": 7155,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ndefault_args = {'owner': 'Jaimin', 'depends_on_past': False, 'start_date':\n datetime.now(), 'email': ['airflow@airflow.com'], 'email_on_failure': \n False, 'email_on_retry': False,... | [
0,
1,
2,
3
] |
# coding=utf8
from __future__ import unicode_literals, absolute_import, division, print_function
"""This is a method to read files, online and local, and cache them"""
import os
from .Read import read as botread
from .Database import db as botdb
class BotNotes():
def __init__(self):
self.notes = botdb.... | normal | {
"blob_id": "2a062f0c2836850320cdd39eee6a354032ba5c33",
"index": 4565,
"step-1": "<mask token>\n\n\nclass BotNotes:\n\n def __init__(self):\n self.notes = botdb.get_plugin_value('SpiceBot_Release_Notes', 'notes'\n ) or dict()\n self.dir_to_scan = botread.get_config_dirs('SpiceBot_Rele... | [
3,
4,
5,
6,
7
] |
import sys
import re
import math
s=sys.stdin.read()
digits=re.findall(r"-?\d+",s)
listline= [int(e) for e in digits ]
x=listline[-1]
del(listline[-1])
n=len(listline)//2
customers=listline[:n]
grumpy=listline[n:]
maxcus=0
if x==n:
print(sum(customers))
else:
for i in range(n-x):
total=0
for j in... | normal | {
"blob_id": "24bc43c1fe035430afde05fec1330e27fb5f1d86",
"index": 8809,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ndel listline[-1]\n<mask token>\nif x == n:\n print(sum(customers))\nelse:\n for i in range(n - x):\n total = 0\n for j in range(i, i + x):\n total += custom... | [
0,
1,
2,
3,
4
] |
# coding=utf-8
# *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import copy
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
fr... | normal | {
"blob_id": "aa79d5cbe656979bf9c228f6a576f2bbf7e405ca",
"index": 2950,
"step-1": "<mask token>\n\n\n@pulumi.input_type\nclass _UserGpgKeyState:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\ncl... | [
11,
19,
22,
26,
29
] |
from django.shortcuts import render, HttpResponseRedirect, HttpResponse
from django.views.generic import View
from django.contrib.auth import login
from django.contrib.auth.models import User
class RegisterView(View):
def get(self, request):
return render(request, 'users/register.html', locals())
def... | normal | {
"blob_id": "c9191df0fc04818b4df9c93a9479f75a60688aa9",
"index": 6372,
"step-1": "<mask token>\n\n\nclass RegisterView(View):\n <mask token>\n <mask token>\n\n\nclass HomeView(View):\n\n def get(self, request):\n return HttpResponse(f'Home Page | Logged in as - {request.user}')\n",
"step-2": "<... | [
3,
4,
5,
6,
7
] |
# 4 Pillars of OOP:
# 1. Encapsulation: Encapsulation in Python is the process of wrapping up variables and methods into a single entity.In programming, a class is an example that wraps all the variables and methods defined inside it.
# 2. Abstraction: Abstraction in Python is the process of hiding the real implementat... | normal | {
"blob_id": "0e4c82d6eb77d2b6357925c9aab516bcc3310a4c",
"index": 140,
"step-1": "<mask token>\n\n\nclass House2:\n <mask token>\n <mask token>\n\n\nclass Vehicle(ABC):\n\n def __init__(self, speed, year):\n self.speed = speed\n self.year = year\n\n def start(self):\n print('Start... | [
9,
12,
13,
14,
17
] |
import os
from registration import Registration
from login import Login
def login():
""" redirect to login page"""
login_page = Login()
login_page.login_main_page()
def registration():
"""Register the new user"""
registration_page = Registration()
registration_page.registration_main_page()
... | normal | {
"blob_id": "8ebc11f4b9e28254ef40175b26744f2a5ab0c831",
"index": 2930,
"step-1": "import os\n\nfrom registration import Registration\nfrom login import Login\n\n\ndef login():\n \"\"\" redirect to login page\"\"\"\n login_page = Login()\n login_page.login_main_page()\n\n\ndef registration():\n \"\"\"... | [
0
] |
<|reserved_special_token_0|>
@app.route('/probability', methods=['POST'])
def make_probability():
try:
data = request.get_json()
except Exception as e:
raise e
if data == {}:
return bad_request()
else:
try:
lang = data['lang']
except:
try... | flexible | {
"blob_id": "b51e0ee80a2488197470627821204d1f74cd62a1",
"index": 5437,
"step-1": "<mask token>\n\n\n@app.route('/probability', methods=['POST'])\ndef make_probability():\n try:\n data = request.get_json()\n except Exception as e:\n raise e\n if data == {}:\n return bad_request()\n ... | [
7,
8,
10,
11,
12
] |
<|reserved_special_token_0|>
def calculadora(calcu):
if calcu == '1':
os.system('clear')
s1 = int(input('Ingrese un numero\n'))
s2 = int(input('Ingrese otro\n'))
os.system('clear')
print(f'{s1} + {s2} = {s1 + s2}')
input('\nPresione una tecla para continuar.')
e... | flexible | {
"blob_id": "ac033e45ea61770c302be677f4dfc95945e2cca5",
"index": 6100,
"step-1": "<mask token>\n\n\ndef calculadora(calcu):\n if calcu == '1':\n os.system('clear')\n s1 = int(input('Ingrese un numero\\n'))\n s2 = int(input('Ingrese otro\\n'))\n os.system('clear')\n print(f'{... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
def rearrange_digits(input_list):
if len(input_list) == 0:
return []
merge_sort(input_list)
first_number = ''
second_number = ''
for i in range(0, len(input_list)):
if i % 2 == 0:
first_number += str(input_list[i])
else:
... | flexible | {
"blob_id": "264b48c2b9ce4ec948ca5ba548e708848760f3dc",
"index": 8271,
"step-1": "<mask token>\n\n\ndef rearrange_digits(input_list):\n if len(input_list) == 0:\n return []\n merge_sort(input_list)\n first_number = ''\n second_number = ''\n for i in range(0, len(input_list)):\n if i ... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
class Solution(object):
<|reserved_special_token_0|>
class TestMethods(unittest.TestCase):
def test_Local(self):
self.assertEqual(1, 1)
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Solution(object):
def mergeTr... | flexible | {
"blob_id": "42371760d691eac9c3dfe5693b03cbecc13fd94d",
"index": 6066,
"step-1": "<mask token>\n\n\nclass Solution(object):\n <mask token>\n\n\nclass TestMethods(unittest.TestCase):\n\n def test_Local(self):\n self.assertEqual(1, 1)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass Solution... | [
3,
4,
7,
8,
10
] |
def primo(num):
if num < 1:
print(f"El numero {num} no es primo")
return None
else:
if num == 2:
print(f"El numero {num} es primo")
return None
else:
for i in range(2, num):
if num % i == 0:
print(f"El numer... | normal | {
"blob_id": "29eb1a1642d38160c138733e269bb3ba0c5d4bba",
"index": 9834,
"step-1": "<mask token>\n\n\ndef leerNumero():\n numer = int(input('Escribe un numero ==> '))\n primo(numer)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef leerNumero():\n numer = int(input('Escribe un numero ==> '))\n p... | [
1,
2,
3,
4,
5
] |
from django.apps import AppConfig
class EasyTechConfig(AppConfig):
name = 'easy_tech'
| normal | {
"blob_id": "0ef172ced411213c0f7daccd632f8d5ec97379c3",
"index": 5604,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass EasyTechConfig(AppConfig):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass EasyTechConfig(AppConfig):\n name = 'easy_tech'\n",
"step-4": "from django.apps import... | [
0,
1,
2,
3
] |
import numpy as np
import pandas as pd
import math
import sklearn
import sklearn.preprocessing
import datetime
import os
import matplotlib.pyplot as plt
import yfinance as yf
import math
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout
from tensorflow.keras.layers impor... | normal | {
"blob_id": "97ea837961c92b5c92a93ec33ac016de7ff1e876",
"index": 2449,
"step-1": "<mask token>\n\n\nclass simpleLSTM:\n <mask token>\n\n def create_dataset(self, dataset, look_back=4):\n dataX, dataY = [], []\n for i in range(len(dataset) - look_back - 1):\n a = dataset.iloc[i:i + ... | [
4,
7,
8,
9,
10
] |
<|reserved_special_token_0|>
def group_list(request):
groups = Group.objects.all()
return render(request, 'group_list.html', {'groups': groups})
<|reserved_special_token_0|>
def group_add(request):
if request.method == 'POST':
form = GroupForm(request.POST)
if form.is_valid():
... | flexible | {
"blob_id": "b9fe758d5fe12b5a15097c0e5a33cb2d57edfdd2",
"index": 7484,
"step-1": "<mask token>\n\n\ndef group_list(request):\n groups = Group.objects.all()\n return render(request, 'group_list.html', {'groups': groups})\n\n\n<mask token>\n\n\ndef group_add(request):\n if request.method == 'POST':\n ... | [
4,
6,
8,
10,
11
] |
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)
<|reserved_spe... | flexible | {
"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
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(dir(grok))
grok.testA()
<|reserved_special_token_1|>
from mypackage.A import grok
print(dir(grok))
grok.testA()
<|reserved_special_token_1|>
# PROBLEM: Code organized in package and want to import a submodule from one... | flexible | {
"blob_id": "ad9facb9c8e552845df9171549f886f3e9cba193",
"index": 7544,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(dir(grok))\ngrok.testA()\n",
"step-3": "from mypackage.A import grok\nprint(dir(grok))\ngrok.testA()\n",
"step-4": "# PROBLEM: Code organized in package and want to import a su... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def longest_word(s, d):
lengths = [(entry, len(entry)) for entry in d]
sorted_d = sorted(lengths, key=lambda x: (-x[1], x[0]))
for word, length in sorted_d:
j = 0
for i in range(0, len(s)):
if j < len(word) and word[j] ... | flexible | {
"blob_id": "86de5b4a72978e2c49e060eefc513e3ed61272ae",
"index": 4004,
"step-1": "<mask token>\n",
"step-2": "def longest_word(s, d):\n lengths = [(entry, len(entry)) for entry in d]\n sorted_d = sorted(lengths, key=lambda x: (-x[1], x[0]))\n for word, length in sorted_d:\n j = 0\n for i... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
''' Model package should containt all data types for the database engine,
which means that projects like PyCIM can be included within ''' | flexible | {
"blob_id": "ce3c1a7210632d0a8475fe886d514eb91d3c75ac",
"index": 7700,
"step-1": "<mask token>\n",
"step-2": "''' Model package should containt all data types for the database engine, \nwhich means that projects like PyCIM can be included within '''",
"step-3": null,
"step-4": null,
"step-5": null,
"st... | [
0,
1
] |
n =int(input("nhap gia tri"))
for i in range(1,n+1):
print(i) | normal | {
"blob_id": "21b295e28a7e4443ea116df1b22ff5074dca955a",
"index": 246,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(1, n + 1):\n print(i)\n",
"step-3": "n = int(input('nhap gia tri'))\nfor i in range(1, n + 1):\n print(i)\n",
"step-4": "n =int(input(\"nhap gia tri\"))\nfor i in... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
dependencies = [(... | flexible | {
"blob_id": "787397473c431d2560bf8c488af58e976c1864d0",
"index": 6730,
"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 = [('lkft', '002... | [
0,
1,
2,
3,
4
] |
#
#
#
##
from __future__ import print_function, unicode_literals
import inspect
import os
import pprint as pp
import time
from time import gmtime, strftime
import subprocess
from local import *
from slurm import *
class Job_status( object ):
""" Enumerate class for job statuses, this is done differently in pyt... | normal | {
"blob_id": "222a02f97df5ded6fea49e9eb201ed784a2a2423",
"index": 5037,
"step-1": "#\n# \n# \n##\n\nfrom __future__ import print_function, unicode_literals\nimport inspect\nimport os\nimport pprint as pp\nimport time\nfrom time import gmtime, strftime\nimport subprocess\n\nfrom local import *\nfrom slurm import *... | [
0
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.