code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
# created by Angus Clark 9/2/17 updated 27/2/17
# ToDo impliment traceroute function into this
# Perhaps get rid of unnecessary itemediate temp file
import socket
import os
import json
import my_traceroute
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
host = '130.56.253.43'
#print host
port = 5201 # Change ... | normal | {
"blob_id": "792f62c72f1667f651567314b062d862abbc9aa5",
"index": 6692,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ns.bind((host, port))\ns.listen(5)\n<mask token>\nwhile True:\n c, addr = s.accept()\n f = open('temp.json', 'wb')\n l = c.recv(1024)\n while l:\n f.write(l)\n l ... | [
0,
1,
2,
3,
4
] |
"""Vista de Autorizaciones (Clientes/Especialistas/Vendedores)."""
from django.shortcuts import render
from dashboard.json2table import convert
from django.utils.translation import ugettext_lazy as _
from api.connection import api
from login.utils.tools import role_admin_check
from django.utils.decorators import method... | normal | {
"blob_id": "b78ad3a55eb27fd91f89c22db07fadca297640ab",
"index": 2892,
"step-1": "<mask token>\n\n\nclass Autorization:\n <mask token>\n <mask token>\n <mask token>\n\n\nclass AutorizationClient(Autorization):\n \"\"\"\n Manejo de autorizaciones de clientes,\n se listan los clientes, en... | [
4,
5,
6,
7,
8
] |
import os,sys
parentdir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
sys.path.insert(0,parentdir)
import xmind
from xmind.core.markerref import MarkerId
xmind_name="数据结构"
w = xmind.load(os.path.dirname(os.path.abspath(__file__))+"\\"+xmind_name+".xmind")
s2=w.createSheet()
s2.setTitle("二叉树——递归套路")... | normal | {
"blob_id": "b713e38824db13f919484b071fb35afb29e26baa",
"index": 3803,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsys.path.insert(0, parentdir)\n<mask token>\ns2.setTitle('二叉树——递归套路')\n<mask token>\nr2.setTitle('二叉树——递归套路')\n<mask token>\nxmind.build(content, r2)\nxmind.save(w, os.path.dirname(os.pat... | [
0,
1,
2,
3,
4
] |
#!C:\Python27\python
print('Content-Type:text/html\n\n')
print ("""
<html>
<head>
<link href="iconTech.png" rel="icon"/>
<meta name="viewport" content="width=device-width,intial-scale=1.0"/>
<link href="../css/bootstrap.min.css" rel="stylesheet" type="text/css"/>
<link href="../css/bootstrap-theme.min.css" rel=... | normal | {
"blob_id": "968cfcfe9d31adcd3a67a88a66e5ebe7b719be8d",
"index": 2841,
"step-1": "<mask token>\n",
"step-2": "print('Content-Type:text/html\\n\\n')\nprint(\n \"\"\"\n<html>\n<head>\n<link href=\"iconTech.png\" rel=\"icon\"/>\n<meta name=\"viewport\" content=\"width=device-width,intial-scale=1.0\"/>\n<link h... | [
0,
1,
2
] |
"""Tests for Node objects."""
import numpy as np
import unittest
import optimus.core as core
import optimus.nodes as nodes
import optimus.util as util
def __relu__(x):
"Numpy Rectified Linear Unit."
return 0.5 * (np.abs(x) + x)
class NodeTests(unittest.TestCase):
def setUp(self):
pass
de... | normal | {
"blob_id": "8e74bd0c051b672bf22c2c8dfb03760805b105c5",
"index": 8799,
"step-1": "<mask token>\n\n\nclass NodeTests(unittest.TestCase):\n <mask token>\n\n def tearDown(self):\n pass\n <mask token>\n <mask token>\n\n def test_Add(self):\n x1 = core.Input(name='x1', shape=(2, 2))\n ... | [
19,
20,
23,
25,
34
] |
"""
Write a program that prompts for the user’s favorite number.
Use json.dump() to store this number in a file. Write a separate program that reads in this value and
prints the message, “I know your favorite number! It’s _____.”
"""
import json
file_name = 'supporting_files/favourite_number.json'
favourite_number = ... | normal | {
"blob_id": "7a359d4b31bd1fd35cd1a9a1de4cbf4635e23def",
"index": 7932,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open(file_name, 'a') as file_object:\n json.dump(favourite_number, file_object)\nprint(f'{favourite_number} is saved in {file_name}')\n",
"step-3": "<mask token>\nfile_name = 's... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Prestamo(models.Model):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class PrestamoInLine(admin.TabularInline):
model = Prestamo
extra = 1
class LibroA... | flexible | {
"blob_id": "86fdea2ae8e253aa4639bb3114de70c693536760",
"index": 1046,
"step-1": "<mask token>\n\n\nclass Prestamo(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\nclass PrestamoInLine(admin.TabularInline):\n model = Prestamo\n extra = 1\n\n\ncla... | [
7,
8,
12,
13,
16
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Generator:
<|reserved_special_token_0|>
@staticmethod
def generate(level):
"""
根据 level 生成指定等级的算术题
0：小学；1：初中；2：高中
"""
"""
生成操作数序列以及二元运算符序列
"""
le... | flexible | {
"blob_id": "6e3bb17696953256af6d8194128427acebf1daac",
"index": 524,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Generator:\n <mask token>\n\n @staticmethod\n def generate(level):\n \"\"\"\n 根据 level 生成指定等级的算术题\n 0：小学；1：初中；2：高中\n \"\"\"\n \"\"\"\n... | [
0,
2,
3,
4
] |
# Pose estimation and object detection: OpenCV DNN, ImageAI, YOLO, mpi, caffemodel, tensorflow
# Authors:
# Tutorial by: https://learnopencv.com/deep-learning-based-human-pose-estimation-using-opencv-cpp-python/
# Model file links collection (replace .sh script): Twenkid
# http://posefs1.perception.cs.cmu.edu/OpenPose/... | normal | {
"blob_id": "c80ae9d2eb07fd716a80a5e2d7b5237925fda02c",
"index": 5861,
"step-1": "<mask token>\n\n\ndef yolo():\n root = 'Z:\\\\'\n name = '23367640.png'\n execution_path = os.getcwd()\n yolo_path = 'Z:\\\\yolo.h5'\n localdir = False\n detector = ObjectDetection()\n detector.setModelTypeAsYO... | [
2,
3,
4,
5,
6
] |
''' mock_proto.py '''
from heron.common.src.python import constants
import heron.proto.execution_state_pb2 as protoEState
import heron.proto.physical_plan_pb2 as protoPPlan
import heron.proto.tmaster_pb2 as protoTmaster
import heron.proto.topology_pb2 as protoTopology
# pylint: disable=no-self-use, missing-docstring
c... | normal | {
"blob_id": "002ef36bd132f1ac258b3f8baf8098accbd8a8f2",
"index": 6839,
"step-1": "<mask token>\n\n\nclass MockProto(object):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def create_mock_spout(self, spout_name, output_streams, spout_parallelism):\n spout ... | [
9,
10,
12,
13,
14
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
parser.add_argument('--rs', type=str, nargs='+')
<|reserved_special_token_0|>
for f in args.rs:
df = ss.read.json(f).select('id', 'subreddit', 'subreddit_id', 'title')
post_df = df if post_df is None else post_df.union(df)... | flexible | {
"blob_id": "e6b3def6ed6f2523d88912832a876caf2742b786",
"index": 7572,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nparser.add_argument('--rs', type=str, nargs='+')\n<mask token>\nfor f in args.rs:\n df = ss.read.json(f).select('id', 'subreddit', 'subreddit_id', 'title')\n post_df = df if post_df... | [
0,
1,
2,
3
] |
import subprocess
from whoosh.index import create_in
from whoosh.fields import *
import os
import codecs
from whoosh.qparser import QueryParser
import whoosh.index as index
import json
from autosub.autosub import autosub
from azure.storage.blob import AppendBlobService
vedio_formats = ['mp4','avi','wmv','mov'] # 1
aud... | normal | {
"blob_id": "7b5a16fdc536eb4ae3fdc08f827663613560187a",
"index": 8642,
"step-1": "import subprocess\nfrom whoosh.index import create_in\nfrom whoosh.fields import *\nimport os\nimport codecs\nfrom whoosh.qparser import QueryParser\nimport whoosh.index as index\nimport json\nfrom autosub.autosub import autosub\nf... | [
0
] |
#!/usr/bin/python
try:
fh = open('testfile','w')
try:
fh.write('This is my test file for this exception')
finally:
print "Going to close file"
fh.close()
except IOError:
print" Error: can\'t find file or read data"
| normal | {
"blob_id": "a538c6d8c9f99bc37def5817a54c831393c051f3",
"index": 7395,
"step-1": "#!/usr/bin/python\n\n\ntry:\n fh = open('testfile','w')\n try:\n fh.write('This is my test file for this exception')\n finally:\n print \"Going to close file\"\n fh.close()\n\nexcept IOError:\n prin... | [
0
] |
# -*- coding: utf-8 -*-
"""
Created on Tue Sep 23 10:16:40 2014
@author: Yusuke
"""
import math
result = []
for i in range(6 * 9**5):
sum_num = 0
for j_digit in str(i):
sum_num += int(j_digit) ** 5
if sum_num == i:
print i
result.append(i)
print math.fsum(result)
| normal | {
"blob_id": "08ccc58fe139db3f4712aa551b80f6ea57e0ad76",
"index": 1888,
"step-1": "# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Tue Sep 23 10:16:40 2014\n\n@author: Yusuke\n\"\"\"\nimport math\n\nresult = []\nfor i in range(6 * 9**5):\n sum_num = 0\n for j_digit in str(i):\n sum_num += int(j_digit) **... | [
0
] |
#!/usr/bin/env python
import re
pdfs_file = './pdf_names_2017.txt'
sessions_file = './session_names_2017.txt'
with open(pdfs_file) as f:
pdf_names = f.read().splitlines()
with open(sessions_file) as f:
session_names = f.read().splitlines()
#for i in xrange(0,len(pdf_names)):
# print str(i+1).zfill(3) +... | normal | {
"blob_id": "e686d8617360c5a3ce35bd4d2bdeb2376b33f53a",
"index": 9726,
"step-1": "#!/usr/bin/env python\n\nimport re\n\n\npdfs_file = './pdf_names_2017.txt'\nsessions_file = './session_names_2017.txt'\n\nwith open(pdfs_file) as f:\n pdf_names = f.read().splitlines()\n\nwith open(sessions_file) as f:\n sess... | [
0
] |
<|reserved_special_token_0|>
def _func(filename, label):
image_string = tf.io.read_file(filename)
decode_image = tf.image.decode_jpeg(image_string, channels=3)
decode_image = tf.image.resize(decode_image, [FLAGS.img_size - 8, FLAGS
.img_size - 8]) / 255.0
if random() > 0.5:
decode_imag... | flexible | {
"blob_id": "9ffe350ff9a568111620ef7dafef83d341f6f01e",
"index": 9409,
"step-1": "<mask token>\n\n\ndef _func(filename, label):\n image_string = tf.io.read_file(filename)\n decode_image = tf.image.decode_jpeg(image_string, channels=3)\n decode_image = tf.image.resize(decode_image, [FLAGS.img_size - 8, F... | [
7,
8,
9,
10,
12
] |
# -*- coding: utf-8 -*-
import pickle
import pathlib
from pathlib import Path
from typing import List, Tuple, Dict
import numpy as np
import torch
import torch.nn as nn
from torch.optim import SGD, Adam
from torch.utils.data import Dataset, DataLoader
from torchtext.data import get_tokenizer
from matplotlib import py... | normal | {
"blob_id": "9c653719ea511d78de9ddcc19442d9f9f7dc11dc",
"index": 4560,
"step-1": "<mask token>\n\n\nclass Vocabulary:\n \"\"\"\n Helper class that maps words to unique indices and the other way around\n \"\"\"\n\n def __init__(self, tokens: List[str]):\n self.word_to_idx = {'<PAD>': 0}\n ... | [
20,
23,
25,
30,
31
] |
'''
Can you print numbers from 1 to 100 without using any loop.
'''
# Use Recursion | normal | {
"blob_id": "cc703690151acd17430b5a9715e71a694fdeca10",
"index": 2116,
"step-1": "<mask token>\n",
"step-2": "'''\nCan you print numbers from 1 to 100 without using any loop.\n'''\n\n# Use Recursion",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
from django.contrib import admin
from pharma_models.personas.models import Persona
admin.site.register(Persona)
| normal | {
"blob_id": "59d04ebd9a45c6a179a2da1f88f728ba2af91c05",
"index": 590,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nadmin.site.register(Persona)\n",
"step-3": "from django.contrib import admin\nfrom pharma_models.personas.models import Persona\nadmin.site.register(Persona)\n",
"step-4": null,
"ste... | [
0,
1,
2
] |
from handler.auth import provider_required
from handler.provider import ProviderBaseHandler
from forms.provider import ProviderAddressForm, ProviderVanityURLForm
import logging
from data import db
from util import saved_message
class ProviderEditAddressHandler(ProviderBaseHandler):
@provider_required
def get(s... | normal | {
"blob_id": "454f885e2254295ce6508e70c0348f5cbe855520",
"index": 5071,
"step-1": "<mask token>\n\n\nclass ProviderEditAddressHandler(ProviderBaseHandler):\n <mask token>\n <mask token>\n\n\nclass ProviderChangeURLHandler(ProviderBaseHandler):\n\n @provider_required\n def post(self, vanity_url=None):\... | [
3,
4,
5,
6,
7
] |
# 다이얼
dial = ['ABC', 'DEF', 'GHI','JKL','MNO','PQRS','TUV','WXYZ']
cha = input()
num = 0
for i in range(len(cha)):
for j in dial:
if cha[i] in j:
num = num + dial.index(j) + 3
print(num) | normal | {
"blob_id": "774e607c693fa2d5199582302e466674f65b6449",
"index": 6213,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(len(cha)):\n for j in dial:\n if cha[i] in j:\n num = num + dial.index(j) + 3\nprint(num)\n",
"step-3": "dial = ['ABC', 'DEF', 'GHI', 'JKL', 'MNO', '... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class UnknownResponseFormat(Exception):
pass
| flexible | {
"blob_id": "e5e460eb704e2ab5f747d1beee05e012ea95fbd2",
"index": 3871,
"step-1": "<mask token>\n",
"step-2": "class UnknownResponseFormat(Exception):\n pass\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
from pptx import Presentation
import csv
prs = Presentation()
slide_layout = prs.slide_layouts[1]
slide = prs.slides.add_slide(slide_layout)
shapes = slide.shapes
title_shape = shapes.title
body_shape = shapes.placeholders[1]
title_shape.text = "Tekst"
tf = body_shape.text_frame
tf.text = "Zawartość tekst frame"
wi... | normal | {
"blob_id": "e1f003b6a687e5654a1ee6c595e789ced02cd6c3",
"index": 7086,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('report.csv') as csvfile:\n data = csv.reader(csvfile, delimiter=',')\n for row in data:\n p = tf.add_paragraph()\n p.text = row[0]\n p.level = 1\n ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def alt(h, dt):
t = 0
while True:
t = t + 1
a = -6 * t ** 4 + h * t ** 3 + 2 * t ** 2 + t
if a <= 0:
print('The balloon first touches ground at hour:')
print(t)
break
elif t == dt:
... | flexible | {
"blob_id": "592f29f08637e511bd7d49a3b58f69b700721d89",
"index": 8083,
"step-1": "<mask token>\n",
"step-2": "def alt(h, dt):\n t = 0\n while True:\n t = t + 1\n a = -6 * t ** 4 + h * t ** 3 + 2 * t ** 2 + t\n if a <= 0:\n print('The balloon first touches ground at hour:')... | [
0,
1,
2,
3
] |
# Generated by Django 3.0.8 on 2020-07-29 18:30
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('scenario', '0005_auto_20200729_1149'),
]
operations = [
migrations.RemoveField(
model_name='weapon',
name='vehicle',
... | normal | {
"blob_id": "b99093fb13c59d4b9bb0a4f32fb62423d6752118",
"index": 6480,
"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 = [('scenario', ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def take_second(element):
return element[1]
<|reserved_special_token_0|>
def get_random_name():
name = ''
for i in range(random.randint(5, 15)):
name += random.choice(string.ascii_letters)
return name
<|reserved_special_token_0|>
<|reserved_special_token_1|... | flexible | {
"blob_id": "21ef8103a5880a07d8c681b2367c2beef727260f",
"index": 6536,
"step-1": "<mask token>\n\n\ndef take_second(element):\n return element[1]\n\n\n<mask token>\n\n\ndef get_random_name():\n name = ''\n for i in range(random.randint(5, 15)):\n name += random.choice(string.ascii_letters)\n r... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for i in range(count):
print('Enter details for student', i + 1, 'below:')
rollNo = int(input('Rollno: '))
name = input('Name: ')
marks = float(input('Marks: '))
records = str(rollNo) + ',' + name + ',' + str(m... | flexible | {
"blob_id": "74cb06ffa41748af431b46c9ff98eb91771a5015",
"index": 537,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(count):\n print('Enter details for student', i + 1, 'below:')\n rollNo = int(input('Rollno: '))\n name = input('Name: ')\n marks = float(input('Marks: '))\n r... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
print('Content-Type: text/html')
print()
<|reserved_special_token_0|>
cgitb.enable()
<|reserved_special_token_0|>
print('Name of the user is:', name)
<|reserved_special_token_0|>
cursor.execute(name)
<|reserved_special_token_0|>
print(name)
db.close()
<|res... | flexible | {
"blob_id": "cb28e8bb98cbeed0b703fbfcf7cf30ebca52aa25",
"index": 4247,
"step-1": "<mask token>\n",
"step-2": "print('Content-Type: text/html')\nprint()\n<mask token>\ncgitb.enable()\n<mask token>\nprint('Name of the user is:', name)\n<mask token>\ncursor.execute(name)\n<mask token>\nprint(name)\ndb.close()\n",... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def CALCB2(NVAC, KGAS, LGAS, ELECEN, ISHELL, L1):
global ELEV
global NSDEG
global AA
global BB
global SCR, SCR1
global PRSH
global ESH
global AUG
global RAD
global PRSHBT
global IZ
global INIOCC
global ISHLMX
global AMZ
global NO... | flexible | {
"blob_id": "09698649510348f92ea3b83f89ffa1c844929b8f",
"index": 3332,
"step-1": "<mask token>\n\n\ndef CALCB2(NVAC, KGAS, LGAS, ELECEN, ISHELL, L1):\n global ELEV\n global NSDEG\n global AA\n global BB\n global SCR, SCR1\n global PRSH\n global ESH\n global AUG\n global RAD\n global... | [
3,
4,
5,
6,
7
] |
from logupload import *
log = LogUpload()
log.uploadLogs(4)
| normal | {
"blob_id": "421837698b7fc188c84a3221271f11a40d1625d9",
"index": 7280,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nlog.uploadLogs(4)\n",
"step-3": "<mask token>\nlog = LogUpload()\nlog.uploadLogs(4)\n",
"step-4": "from logupload import *\nlog = LogUpload()\nlog.uploadLogs(4)\n",
"step-5": null,
... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
print(
'¡hola! te invito a jugar mi juego trivia, trataremos temas como termux xd y entre otras cosas'
)
<|reserved_special_token_0|>
print('\nmucho gusto', n1, ',empecemos')
<|reserved_special_token_0|>
print(
'me puedes decir con que comando en ... | flexible | {
"blob_id": "0c297e6f79682896e98c7a2933a4da6d9af7d7fe",
"index": 9060,
"step-1": "<mask token>\n",
"step-2": "print(\n '¡hola! te invito a jugar mi juego trivia, trataremos temas como termux xd y entre otras cosas'\n )\n<mask token>\nprint('\\nmucho gusto', n1, ',empecemos')\n<mask token>\nprint(\n 'm... | [
0,
1,
2,
3
] |
from django.conf.urls import url
from . import views
urlpatterns = [
url(r'^class/([^/]+)/?$', views.puppet_class, name='puppet-class'),
url(r'^edit-host/(?P<fqdn>[^/]+)?/?$', views.edit_host, name='edit-host'),
url(r'^add-host/(?P<fqdn>[^/]+)?/?$', views.add_host, name='add-host'),
url(r'^delete/([^/... | normal | {
"blob_id": "add56d52f3c88f814a166d12c3bc5a5906268864",
"index": 484,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [url('^class/([^/]+)/?$', views.puppet_class, name=\n 'puppet-class'), url('^edit-host/(?P<fqdn>[^/]+)?/?$', views.edit_host,\n name='edit-host'), url('^add-host/(?P<fq... | [
0,
1,
2,
3
] |
#!/usr/bin/python
# Developed by Hector Cobos
import sys
import csv
import datetime
def mapper():
# Using a reader in order to read the whole file
reader = csv.reader(sys.stdin, delimiter='\t')
# Jump to the next line. We want to avoid the line with the name of the fields
reader.next()
# loop
for line in reade... | normal | {
"blob_id": "d959ed49a83fb63e0bce31b5c81c013f0986706b",
"index": 4314,
"step-1": "#!/usr/bin/python\n\n# Developed by Hector Cobos\n\nimport sys\nimport csv\nimport datetime\n\ndef mapper():\n\t# Using a reader in order to read the whole file\n\treader = csv.reader(sys.stdin, delimiter='\\t')\n\t# Jump to the ne... | [
0
] |
<|reserved_special_token_0|>
class task_NER:
def __init__(self):
self.name = 'NER_task_bio'
self.controller_size = 128
self.controller_layers = 1
self.num_read_heads = 1
self.num_write_heads = 1
self.num_inputs = 200
self.num_outputs = 7
self.memory... | flexible | {
"blob_id": "eb99def75404bc3b674bcb633714009149f2d50d",
"index": 5097,
"step-1": "<mask token>\n\n\nclass task_NER:\n\n def __init__(self):\n self.name = 'NER_task_bio'\n self.controller_size = 128\n self.controller_layers = 1\n self.num_read_heads = 1\n self.num_write_heads... | [
12,
20,
26,
27,
29
] |
<|reserved_special_token_0|>
class Net(torch.nn.Module):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Net(torch.nn.Module):
def __init__(self, layer_sizes=[256, 128, 2], dropout_prob=None, device
=None):
sup... | flexible | {
"blob_id": "4711adcc7c95993ec13b9d06fa674aa064f79bfd",
"index": 314,
"step-1": "<mask token>\n\n\nclass Net(torch.nn.Module):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Net(torch.nn.Module):\n\n def __init__(self, layer_sizes=[256, 128, 2], dropout_prob=None, device\n ... | [
1,
2,
3,
4,
5
] |
import ordenador
import pytest
import contatempo
class TestaOrdenador:
@pytest.fixture
def ordenad(self):
return ordenador.Ordenador()
@pytest.fixture
def list_quase_ord(self):
c = contatempo.ContaTempos()
return c.lista_quase_ordenada(100)
@pytest.fixture
def list_al... | normal | {
"blob_id": "32bb6d5ad0a1398c9ab89190c087fe3916631878",
"index": 7750,
"step-1": "<mask token>\n\n\nclass TestaOrdenador:\n\n @pytest.fixture\n def ordenad(self):\n return ordenador.Ordenador()\n <mask token>\n <mask token>\n <mask token>\n\n def test_selecao_bolha_melhorada_aleatoria(se... | [
5,
6,
8,
9,
11
] |
from datetime import datetime, timezone, timedelta
import json
import urllib.request
from mysql_dbcon import Connection
from model import SlackChannel, SlackUser, SlackMessage
# TODO set timezone at config
jst = timezone(timedelta(hours=+9), 'JST')
def get_new_message_list(channel_id: int):
with Connection() a... | normal | {
"blob_id": "2b141f12bec2006e496bf58a3fcb0167c95ab3b6",
"index": 2530,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_new_message_list(channel_id: int):\n with Connection() as cn:\n token, channel = cn.s.query(SlackChannel.token, SlackChannel.channel\n ).filter(SlackChann... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def swap(arr, first, second):
"""
Swaps the first index with the second.
arr: an input array
first: an index in the array
second: an index in the array
This function has the side effect mentioned above.
"""
arr[first], arr[second] = arr[second], arr[first... | flexible | {
"blob_id": "1262d41be3bf873d003464cb23998dde20fde318",
"index": 8115,
"step-1": "<mask token>\n\n\ndef swap(arr, first, second):\n \"\"\"\n Swaps the first index with the second.\n\n arr: an input array\n first: an index in the array\n second: an index in the array\n\n This function has the si... | [
5,
7,
8,
10
] |
<|reserved_special_token_0|>
class Renderable:
def __init__(self, material_name: str, attributes: Dict[str, np.ndarray
], model_mat=np.eye(4), uv_scale=1.0):
self.model_mat = model_mat
self.material_name = material_name
self._attributes = attributes
self._uv_scale = uv_sca... | flexible | {
"blob_id": "061c287d5f0a5feeeaedc80eea6b3fc4ff02286e",
"index": 7191,
"step-1": "<mask token>\n\n\nclass Renderable:\n\n def __init__(self, material_name: str, attributes: Dict[str, np.ndarray\n ], model_mat=np.eye(4), uv_scale=1.0):\n self.model_mat = model_mat\n self.material_name = ma... | [
10,
11,
13,
16,
17
] |
import socket
import time
class FileTransProgram(object):
def __init__(self, ADDR, file_name):
self.ADDR = ADDR
self.sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
self.sock.connect(ADDR)
self.file_name = file_name
def recv(self):
self.sock.send(bytes("Connec... | normal | {
"blob_id": "231a07e63e40f2e4d204cde76c52e64b922da1b8",
"index": 2619,
"step-1": "<mask token>\n\n\nclass FileTransProgram(object):\n\n def __init__(self, ADDR, file_name):\n self.ADDR = ADDR\n self.sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\n self.sock.connect(ADDR)\n ... | [
2,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
def __print_field_stats(tfield, field, label):
good_mask = ~field.mask
if not np.any(good_mask):
print(f'{label}: no meaningful data')
return
good_data = field[good_mask]
print(
f"""{label} {tfield}:
{good_data.min()}...{good_data.max()}
mean={good_... | flexible | {
"blob_id": "2d5e147b081283047cd044746d73d91ee2e59052",
"index": 4139,
"step-1": "<mask token>\n\n\ndef __print_field_stats(tfield, field, label):\n good_mask = ~field.mask\n if not np.any(good_mask):\n print(f'{label}: no meaningful data')\n return\n good_data = field[good_mask]\n prin... | [
3,
4,
5,
6,
7
] |
import scrapy
from scrapy.loader import ItemLoader
class BlogSpider(scrapy.Spider):
name = 'blogspider'
start_urls = ['https://blog.scrapinghub.com']
def content_title_parser(self, mystr):
return mystr[0].split(' ')[3]
def parse(self, response):
for url in response.css('ul li a::attr... | normal | {
"blob_id": "4c79dcf394acbcc9a636bcc9b0aac13a2bafc7e3",
"index": 9249,
"step-1": "<mask token>\n\n\nclass BlogSpider(scrapy.Spider):\n <mask token>\n <mask token>\n <mask token>\n\n def parse(self, response):\n for url in response.css('ul li a::attr(\"href\")').re('.*/category/.*'):\n ... | [
4,
5,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(x)
<|reserved_special_token_1|>
x = 'Programming is like building a multilingual puzzle\n'
print(x)
<|reserved_special_token_1|>
#!/usr/bin/env python3
x = "Programming is like building a multilingual puzzle\n"
prin... | flexible | {
"blob_id": "95c0ba757b7561ef6cc0ad312034e2695f8420c3",
"index": 3933,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(x)\n",
"step-3": "x = 'Programming is like building a multilingual puzzle\\n'\nprint(x)\n",
"step-4": "#!/usr/bin/env python3\n\nx = \"Programming is like building a multilingua... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def f(h):
Vw = 4 * pi * r ** 3 / 3 - pi * h ** 2 / 3 * (3 * r - h)
Vs = 4 * pi * r ** 3 / 3
return ρw * Vw - ρs * Vs
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
r = 1.0... | flexible | {
"blob_id": "3e7d2bacb15c39658ef5044685b73068deb1c145",
"index": 6060,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef f(h):\n Vw = 4 * pi * r ** 3 / 3 - pi * h ** 2 / 3 * (3 * r - h)\n Vs = 4 * pi * r ** 3 / 3\n return ρw * Vw - ρs * Vs\n\n\n<mask token>\n",
"step-3": "<mask token>\nr ... | [
0,
1,
2,
3,
4
] |
#Script start
print"This is the two number subtraction python program."
a = 9
b = 2
c = a - b
print c
# Scrip close
| normal | {
"blob_id": "a045423edd94d985dfc9660bcfe4a88c61bf4574",
"index": 20,
"step-1": "#Script start\nprint\"This is the two number subtraction python program.\"\na = 9\nb = 2\nc = a - b\nprint c\n\n# Scrip close\n",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
} | [
0
] |
import os
import numpy as np
import pycuda
import pycuda.driver as driver
import cudasim.solvers.cuda.Simulator_mg as sim
import cudasim
class Lsoda(sim.SimulatorMG):
_param_tex = None
_step_code = None
_runtimeCompile = True
_lsoda_source_ = """
extern "C"{
#include <stdio.h>
... | normal | {
"blob_id": "e9754530bef7614c16cdba0e818c1fa188e2d9a2",
"index": 9940,
"step-1": "<mask token>\n\n\nclass Lsoda(sim.SimulatorMG):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def _compile(self, step_code):\n self._beta = 1\n fc = open(os.path.join(os.path.split(os.... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
def getChromosome(str):
if str == '*' or str[3:] == 'X':
return -1
try:
return int(str[3:])
except:
return -1
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def parseFile(file, frequency_tree):
readnumber = re.compile('[r]+\\d+')
... | flexible | {
"blob_id": "227b71cb6d4cde8f498ad19c1c5f95f7fc572752",
"index": 6995,
"step-1": "<mask token>\n\n\ndef getChromosome(str):\n if str == '*' or str[3:] == 'X':\n return -1\n try:\n return int(str[3:])\n except:\n return -1\n",
"step-2": "<mask token>\n\n\ndef parseFile(file, freque... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class ProyectoSistemaViewSet(viewsets.ModelViewSet):
queryset = ProyectoSistema.objects.all()
serializer_class = ProyectoSistemaSerializer
class UsuarioProyectoSistemaViewSet(viewsets.ModelViewSet):
queryset = UsuarioProyectoSistema.objects.all()
serializer_class = Usuar... | flexible | {
"blob_id": "bedae2621bfcc64deb0d13d7cbce3cfb89720245",
"index": 4346,
"step-1": "<mask token>\n\n\nclass ProyectoSistemaViewSet(viewsets.ModelViewSet):\n queryset = ProyectoSistema.objects.all()\n serializer_class = ProyectoSistemaSerializer\n\n\nclass UsuarioProyectoSistemaViewSet(viewsets.ModelViewSet):... | [
6,
8,
9,
12,
14
] |
<|reserved_special_token_0|>
@api(canonical_alias='nncf.torch.create_compressed_model')
@tracked_function(NNCF_PT_CATEGORY, [CompressionStartedFromConfig(argname=
'config')])
def create_compressed_model(model: Module, config: NNCFConfig,
compression_state: Optional[Dict[str, Any]]=None, dummy_forward_fn:
... | flexible | {
"blob_id": "cd1ada2d7979fffc17f707ed113efde7aa134954",
"index": 3036,
"step-1": "<mask token>\n\n\n@api(canonical_alias='nncf.torch.create_compressed_model')\n@tracked_function(NNCF_PT_CATEGORY, [CompressionStartedFromConfig(argname=\n 'config')])\ndef create_compressed_model(model: Module, config: NNCFConfi... | [
2,
3,
5,
6,
7
] |
DEFAULT_SIZE = 512
class DataEncoding:
@staticmethod
def segment_decode(segment):
arr = bytearray(segment)
ack_binary = bytearray([arr[i] for i in range(4)])
tip_binary = bytearray([arr[4]])
len_binary = bytearray([arr[i] for i in (5,6)])
ack = int.from... | normal | {
"blob_id": "47c5375816ab35e8225e5f3695f7ee2ab5336076",
"index": 4312,
"step-1": "<mask token>\n\n\nclass DataEncoding:\n\n @staticmethod\n def segment_decode(segment):\n arr = bytearray(segment)\n ack_binary = bytearray([arr[i] for i in range(4)])\n tip_binary = bytearray([arr[4]])\n ... | [
6,
8,
9,
10,
11
] |
<|reserved_special_token_0|>
class TestFileReadingFunctions(unittest.TestCase):
def setUp(self):
self.data_dir = os.path.join(os.path.dirname(os.path.realpath(
__file__)), 'data')
self.one_word_per_line_path = os.path.join(self.data_dir,
'one_word_per_line.txt')
se... | flexible | {
"blob_id": "7c3798aa9cc5424656572dfaa87f7acb961613eb",
"index": 8715,
"step-1": "<mask token>\n\n\nclass TestFileReadingFunctions(unittest.TestCase):\n\n def setUp(self):\n self.data_dir = os.path.join(os.path.dirname(os.path.realpath(\n __file__)), 'data')\n self.one_word_per_line_p... | [
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": "bf160bd2fc924a11d340bd466b4a879d1cdcd86e",
"index": 7639,
"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 = [('restapp', '... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
import numpy as np
import matplotlib.pyplot as plt
from sklearn.ensemble import (
StackingClassifier,
RandomForestClassifier
)
import pandas as pd
from sklearn.metrics import f1_score
# feel free to import any sklearn model here
from sklearn.linear_model import LogisticRegression
from ... | normal | {
"blob_id": "cf65966f5daf88bdefc7a8aa2ff80835cff0d0b6",
"index": 4627,
"step-1": "<mask token>\n\n\ndef load_data():\n \"\"\"\n Helper function for loading in the data\n\n ------\n # of training samples: 419\n # of testing samples: 150\n ------\n \"\"\"\n df = pd.read_csv('../../Data/brea... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Brokerage(models.Model):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>... | flexible | {
"blob_id": "174f744b641ee20272713fa2fe1991cb2c76830a",
"index": 99,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Brokerage(models.Model):\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... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
@ddt
class ApiTest(unittest.TestCase):
@classmethod
def setUpClass(cls) ->None:
cls.keyword = Keyword()
cls.cookie = None
cls.confData = LoadIni('config.ini')
logger.info('----------用例开始执行----------')
<|reserved_special_token_0|>
<|reserved_s... | flexible | {
"blob_id": "b28bada020ac593783ac62994bb45311ebb78813",
"index": 9055,
"step-1": "<mask token>\n\n\n@ddt\nclass ApiTest(unittest.TestCase):\n\n @classmethod\n def setUpClass(cls) ->None:\n cls.keyword = Keyword()\n cls.cookie = None\n cls.confData = LoadIni('config.ini')\n logge... | [
2,
3,
4,
5,
6
] |
<|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": "7e11a33d82926ed544640a0192e905d373f575da",
"index": 2766,
"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 = [('main_app', ... | [
0,
1,
2,
3,
4
] |
# -*- coding:utf-8 -*-
# Author: washing
# DateTime: 2022/5/18 10:28
# File: 0668.py
# Desc: CV
class Solution:
def findKthNumber(self, m: int, n: int, k: int) -> int:
return bisect_left(range(m * n), k, key=lambda x: x // n * n + sum(x // i for i in range(x // n + 1, m + 1)))
| normal | {
"blob_id": "ec9efeca7eef7b8ee25c1e089e675bdb1e53413b",
"index": 417,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n",
"step-3": "class Solution:\n\n def findKthNumber(self, m: int, n: int, k: int) ->int:\n return bisect_left(range(m * n), k, key=lambda x: x // n * n + s... | [
0,
1,
2,
3
] |
import json
import sys
from pkg_resources import resource_string
# Load a package data file resource as a string. This
_conf = json.loads(resource_string(__name__, 'conf.json'))
# Load a data file specified in "package_data" setup option for this pkg.
_pkg_data = resource_string(__name__, 'data/pkg1.dat')
# Load a d... | normal | {
"blob_id": "4689ee7f7178cef16ac1f5375481a9ee8a48f924",
"index": 3780,
"step-1": "<mask token>\n\n\ndef hello():\n print(_conf['greeting'])\n print(_pkg_data)\n print(_sys_data)\n\n\n<mask token>\n",
"step-2": "<mask token>\ntry:\n _sys_data = open(sys.prefix + '/data/data1.dat').read()\nexcept Exc... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
while True:
content = f.read(num + '.txt').decode('utf-8')
print(content)
comments.append(f.getinfo(num + '.txt').comment.decode('utf-8'))
match = re.search('Next nothing is (\\d+)', content)
if match == None:
... | flexible | {
"blob_id": "b883e63c70f3dfeac3294989fab93c1331b6329c",
"index": 7990,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile True:\n content = f.read(num + '.txt').decode('utf-8')\n print(content)\n comments.append(f.getinfo(num + '.txt').comment.decode('utf-8'))\n match = re.search('Next noth... | [
0,
1,
2,
3,
4
] |
"""------------------------------------------------------------------------
MODULE
FContactRegulatoryInfoBase -
DESCRIPTION:
This file provides the custom instance of RegulatoryInfo on the Contact which has all the RegulatoryInfo related methods
VERSION: 1.0.25(0.25.7)
RESTRICTIONS/ LIMITATIONS:
1. Any modi... | normal | {
"blob_id": "d4e62950f10efeb27d19c3d9c672969342ef8c7c",
"index": 3095,
"step-1": "<mask token>\n\n\nclass FContactRegulatoryInfoBase(object):\n\n def __init__(self, contact=None):\n \"\"\"class that maintains all data related to the regulatory on the FContact\"\"\"\n try:\n self.__con... | [
13,
15,
18,
20,
23
] |
# coding=utf-8
# --------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
#
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes ... | normal | {
"blob_id": "0719448e7eb8d48e636be1332c904beebf27e02d",
"index": 4163,
"step-1": "<mask token>\n\n\nclass PredictionQueryToken(Model):\n <mask token>\n <mask token>\n\n def __init__(self, session=None, continuation=None, max_count=None,\n order_by=None, tags=None, iteration_id=None, start_time=No... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class PhoneSerializer(serializers.ModelSerializer):
class Meta:
model = Phones
fields = 'id', 'number', 'area_code', 'country_code'
<|reserved_special_token_1|>
from rest_framework import serializers
fro... | flexible | {
"blob_id": "e3ba6395a8d7272fc7e5a8be37e6b0b18c355e14",
"index": 9272,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass PhoneSerializer(serializers.ModelSerializer):\n\n\n class Meta:\n model = Phones\n fields = 'id', 'number', 'area_code', 'country_code'\n",
"step-3": "from re... | [
0,
1,
2,
3
] |
# coding=utf-8
from datetime import datetime, timedelta
from flask import current_app as app
from flask_script import Command
from main import db
from models.payment import Payment
from models.product import ProductGroup, Product, PriceTier, Price, ProductView, ProductViewProduct
from models.purchase import Purchase
... | normal | {
"blob_id": "1de46ee2818b4cb2ae68ef5870581c341f8d9b04",
"index": 4020,
"step-1": "<mask token>\n\n\nclass CancelReservedTickets(Command):\n\n def run(self):\n payments = Purchase.query.filter(Purchase.state == 'reserved', \n Purchase.modified < datetime.utcnow() - timedelta(days=3), ~\n ... | [
6,
7,
9,
10,
11
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
@main.app_errorhandler(404)
def page_not_found(e):
return render_template('404.html'), 404
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
@main.app_errorhandler(404)
def page_no... | flexible | {
"blob_id": "021cbd1bd22f9ec48db2e52b2a98be169bbfdbbd",
"index": 5979,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@main.app_errorhandler(404)\ndef page_not_found(e):\n return render_template('404.html'), 404\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\n@main.app_errorhandler(404)\ndef ... | [
0,
1,
2,
3,
4
] |
from os import environ as env
import json
import utils
import utils.aws as aws
import utils.handlers as handlers
def put_record_to_logstream(event: utils.LambdaEvent) -> str:
"""Put a record of source Lambda execution in LogWatch Logs."""
log_group_name = env["REPORT_LOG_GROUP_NAME"]
utils.Log.info("Fet... | normal | {
"blob_id": "01d545e77c211201332a637a493d27608721aad5",
"index": 7004,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef put_record_to_logstream(event: utils.LambdaEvent) ->str:\n \"\"\"Put a record of source Lambda execution in LogWatch Logs.\"\"\"\n log_group_name = env['REPORT_LOG_GROUP_NAM... | [
0,
1,
2,
3,
4
] |
import botocore
class s3Obj:
def __init__(self, name, bucket_name, size, last_modified, storage_class):
self.name = name
self.size = size
self.last_modified = last_modified
self.storage_class = storage_class
self.bucket_name = bucket_name
self.acl = []
... | normal | {
"blob_id": "b3f376f4aec81cae853f996a74062e32bb4a8fa3",
"index": 2569,
"step-1": "<mask token>\n\n\nclass s3Obj:\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass s3Obj:\n <mask token>\n\n def getACL(self, client_s3):\n \"\"\"\n get ACL info and update the object\n ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
urc.run(beam_neutrons_path, instrument, samplexmlpath, psi, hkl2Q, pixel,
t_m2p, Q, E, hkl_projection, Nbuffer=100000)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
beam_neutrons_path = (
'/SNS/users/p63/ORN... | flexible | {
"blob_id": "de286b94e09db477e3d920a9eff1a299474baf20",
"index": 2614,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurc.run(beam_neutrons_path, instrument, samplexmlpath, psi, hkl2Q, pixel,\n t_m2p, Q, E, hkl_projection, Nbuffer=100000)\n",
"step-3": "<mask token>\nbeam_neutrons_path = (\n '/SN... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def find_square_sum(num):
_sum = 0
while num > 0:
digit = num % 10
_sum += digit * digit
num //= 10
return _sum
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def find_happy_nu... | flexible | {
"blob_id": "60b5e515c7275bfa0f79e22f54302a578c2f7b79",
"index": 728,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef find_square_sum(num):\n _sum = 0\n while num > 0:\n digit = num % 10\n _sum += digit * digit\n num //= 10\n return _sum\n\n\n<mask token>\n",
"step-... | [
0,
1,
2,
3,
4
] |
# Overview file
#import python classes
import numpy as np
import random as rn
import math
import matplotlib.pyplot as plt
import pylab
from mpl_toolkits.mplot3d import Axes3D
#import self produced classes
import forcemodule as fm
import init_sys
# independent parameters
dt = 0.004
N=2048
lpnum = 1000
density = 0.... | normal | {
"blob_id": "63c214d9e831356345ba2eee68634af36964dcff",
"index": 550,
"step-1": "# Overview file\n\n#import python classes\nimport numpy as np\nimport random as rn\nimport math\nimport matplotlib.pyplot as plt\nimport pylab\nfrom mpl_toolkits.mplot3d import Axes3D\n\n\n\n#import self produced classes\nimport for... | [
0
] |
# -*- coding:utf-8 -*-
from odoo import api, fields, _, models
Type_employee = [('j', 'Journalier'), ('m', 'Mensuel')]
class HrCnpsSettings(models.Model):
_name = "hr.cnps.setting"
_description = "settings of CNPS"
name = fields.Char("Libellé", required=True)
active = fields.Boolean("Ac... | normal | {
"blob_id": "4f7b689c06383673b510092932b051c644306b84",
"index": 3500,
"step-1": "<mask token>\n\n\nclass HrCnpsSettings(models.Model):\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\nclass HrCnpsCotisationLineTe... | [
3,
4,
5,
6,
7
] |
#!/usr/bin/python
import glob
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import time
import seaborn as sns
import os
from pathlib import Path
#import math
#functions related to elasticity of WLC
def f1(l,lp, kbt):
return kbt/lp*(1./(4*(1.-l)*(1.-l))-.25+l)
def derf1(l,lp,kbt):
return k... | normal | {
"blob_id": "9817600759bc01e89f6c48bdc2d256651aedf74d",
"index": 1788,
"step-1": "<mask token>\n\n\ndef derf1(l, lp, kbt):\n return kbt / lp * (0.5 / ((1.0 - l) * (1.0 - l) * (1.0 - l)) + 1.0)\n\n\ndef xdefWLC(kbt, l, p, f):\n l0 = 0.9999\n lnew = l0 - (f1(l0, p, kbt) - f) / derf1(l0, p, kbt)\n if ab... | [
4,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
urlpatterns = [path('<int:id>', api_photo_detail_view, name='user_detail'),
path('', api_photos_view, name='users')]
<|reserved_special_token_1|>
from django.urls import path
from photo.api.views import api_photo_detail_vie... | flexible | {
"blob_id": "ab4145ccc0b360dcca9b9aa6ebe919bdddac65a2",
"index": 3962,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('<int:id>', api_photo_detail_view, name='user_detail'),\n path('', api_photos_view, name='users')]\n",
"step-3": "from django.urls import path\nfrom photo.api.vie... | [
0,
1,
2
] |
"""
Client component of the Quartjes connector. Use the ClientConnector to create
a connection to the Quartjes server.
Usage
-----
Create an instance of this object with the host and port to connect to.
Call the start() method to establish the connection.
Now the database and the stock_exchange variable can be used to... | normal | {
"blob_id": "a8f200e0ae1252df4ad6560e5756347cd0e4c8ba",
"index": 5034,
"step-1": "<mask token>\n\n\nclass ClientConnector(object):\n <mask token>\n\n def __init__(self, host=None, port=None):\n self._host = host\n if port:\n self._port = port\n else:\n from quartj... | [
12,
16,
19,
20,
21
] |
a=[i for i in range(10)]
del a[0]
print a
del a[-1]
print a
del a[1]
print a
del a[0:2]
print a
del a[1:3:1]
print a
#test del all
del a[:]
print a
a.append(1)
print a
# Make sure that del's work correctly in sub-scopes:
x = 1
def f1():
x = range(5)
def f2():
del x[1]
return f2
f1()()
| normal | {
"blob_id": "d0e5cfc7b619c2eaec19248619d7d59e41503c89",
"index": 4302,
"step-1": "a=[i for i in range(10)]\ndel a[0]\nprint a\ndel a[-1]\nprint a\ndel a[1]\nprint a\n\ndel a[0:2] \nprint a \ndel a[1:3:1]\nprint a\n#test del all\ndel a[:]\nprint a\na.append(1)\nprint a\n\n# Make sure that del's work correctly in ... | [
0
] |
<|reserved_special_token_0|>
def lambda_handler(event, context):
products = list(Product.scan(Product.do_crawl == True))
for product in products:
product.search_lowest_price()
print('{} product(s) crawled'.format(len(products)))
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if not D... | flexible | {
"blob_id": "76905171602cbeb53903a4b0259685288da3a083",
"index": 6365,
"step-1": "<mask token>\n\n\ndef lambda_handler(event, context):\n products = list(Product.scan(Product.do_crawl == True))\n for product in products:\n product.search_lowest_price()\n print('{} product(s) crawled'.format(len(p... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
def formatName(name):
arr = re.split(' |-', name)
print(arr)
gweight = ''
gname = []
gnumber = ''
for word in arr:
if any(str.isdigit(c) for c in word):
for weight in weights:
pos = word.find(weight)
if pos != -1:... | flexible | {
"blob_id": "b808daf8d1fbe3cc585db57e1049a502d3ca46f5",
"index": 857,
"step-1": "<mask token>\n\n\ndef formatName(name):\n arr = re.split(' |-', name)\n print(arr)\n gweight = ''\n gname = []\n gnumber = ''\n for word in arr:\n if any(str.isdigit(c) for c in word):\n for weigh... | [
5,
6,
7,
8,
9
] |
import xarray as xr
def precip_stats_to_climatology(fili, start_year=1981, end_year=2015):
"""
Calculates average climatology for annual data - either Jan to Dec or accummulation period
"""
nyear = end_year - start_year + 1
ds = xr.open_dataset(fili)
year = ds['time'].dt.year
#dsMsk ... | normal | {
"blob_id": "eb403fbb307332c18ffdcdf52589c714f0719960",
"index": 3052,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef precip_stats_to_climatology(fili, start_year=1981, end_year=2015):\n \"\"\"\n Calculates average climatology for annual data - either Jan to Dec or accummulation period\n ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def Geocode(address, apiKey):
URL = 'https://geocode.search.hereapi.com/v1/geocode'
params = {'q': address, 'apiKey': apiKey}
import pdb
pdb.set_trace()
response = requests.get(URL, params=params).json()
... | flexible | {
"blob_id": "d32496c9bce86f455b24cd9c6dc263aee1bf82af",
"index": 3552,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef Geocode(address, apiKey):\n URL = 'https://geocode.search.hereapi.com/v1/geocode'\n params = {'q': address, 'apiKey': apiKey}\n import pdb\n pdb.set_trace()\n respo... | [
0,
2,
3,
4,
5
] |
from secrets import randbelow
print(randbelow(100))
| normal | {
"blob_id": "18ae982c7fac7a31e0d257f500da0be0851388c2",
"index": 8985,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(randbelow(100))\n",
"step-3": "from secrets import randbelow\nprint(randbelow(100))\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
} | [
0,
1,
2
] |
from django import forms
from .models import Project
from user.models import User
from assets.models import Assets
class CreateProjectForm(forms.ModelForm):
project_name = forms.CharField(
label='项目名',
widget=forms.TextInput(
attrs={"class": "form-control"}
)
)
project_... | normal | {
"blob_id": "599c5c02397f283eb00f7343e65c5cb977442e38",
"index": 3848,
"step-1": "<mask token>\n\n\nclass CreateProjectForm(forms.ModelForm):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\n class Meta:\n model = Project\n fields = ['project_name', 'project_desc', 'a... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
parser.add_argument('-d', type=str, help='dataset')
parser.add_argument('-o', type=str, default='dataset', help='output directory')
parser.add_argument('-f', type=str, default='mp4', help='format')
parser.add_argument('-c', type=s... | flexible | {
"blob_id": "479411727de14e8032b6d01cdb844632111af688",
"index": 5275,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nparser.add_argument('-d', type=str, help='dataset')\nparser.add_argument('-o', type=str, default='dataset', help='output directory')\nparser.add_argument('-f', type=str, default='mp4', he... | [
0,
1,
2,
3
] |
import math
import numpy as np
class incStat:
def __init__(self, Lambda, isTypeJitter=False): # timestamp is creation time
self.CF1 = 0 # linear sum
self.CF2 = 0 # sum of squares
self.w = 0 # weight
self.isTypeJitter = isTypeJitter
self.Lambda = Lambda # Decay Factor
... | normal | {
"blob_id": "7b2ca3db44c5f71c2975bd8af701dafca3b3d081",
"index": 5492,
"step-1": "<mask token>\n\n\nclass windowed_incStat:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\nclass windowed_incStat_2D:\n\n def __init__(self, L):\n self.incSt... | [
18,
32,
35,
44,
46
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def get_link():
parser = optparse.OptionParser()
parser.add_option('-l', '--link', dest='url', help=
'direct link of file to download .pdf')
url, argument = parser.parse_args()
return url
def download(u... | flexible | {
"blob_id": "22ddae977afd2a1b0a729cf0d56783eaaca3b0a0",
"index": 9813,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_link():\n parser = optparse.OptionParser()\n parser.add_option('-l', '--link', dest='url', help=\n 'direct link of file to download .pdf')\n url, argument = pa... | [
0,
2,
3,
4,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
logging.basicConfig(level='DEBUG')
<|reserved_special_token_0|>
client.sendto(message.encode('utf-8'), (serverName, serverPort))
<|reserved_special_token_0|>
print(modifiedMessage.decode('utf-8'))
client.close()
<|reserved_speci... | flexible | {
"blob_id": "4d388c912915c3f1f9e433f1342289f0864b3a11",
"index": 409,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nlogging.basicConfig(level='DEBUG')\n<mask token>\nclient.sendto(message.encode('utf-8'), (serverName, serverPort))\n<mask token>\nprint(modifiedMessage.decode('utf-8'))\nclient.close()\n",... | [
0,
1,
2,
3,
4
] |
import os
_basedir = os.path.abspath(os.path.dirname(__file__))
DEBUG = True
SECRET_KEY = '06A52C5B30EC2960310B45E4E0FF21C5D6C86C47D91FE19FA5934EFF445276A0'
SQLALCHEMY_DATABASE_URI = 'sqlite:///' + os.path.join(_basedir, 'app.db')
SQLALCHEMY_ECHO = True
DATABASE_CONNECT_OPTIONS = {}
THREADS_PER_PAGE = 8
CSRF_ENABL... | normal | {
"blob_id": "6ee71cf61ae6a79ec0cd06f1ddc7dc614a76c7b9",
"index": 6547,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n_basedir = os.path.abspath(os.path.dirname(__file__))\nDEBUG = True\nSECRET_KEY = '06A52C5B30EC2960310B45E4E0FF21C5D6C86C47D91FE19FA5934EFF445276A0'\nSQLALCHEMY_DATABASE_URI = 'sqlite:///... | [
0,
1,
2,
3
] |
from django.db import models
# Create your models here.
class Advertisement(models.Model):
title = models.CharField(max_length=1500, db_index=True, verbose_name='Заголовок')
description = models.TextField(blank=True)
created_at = models.DateTimeField(auto_now_add=True)
update_at = models.DateTimeFiel... | normal | {
"blob_id": "c5bdbcc8ba38b02e5e5cf8b53362e87ba761443d",
"index": 8654,
"step-1": "<mask token>\n\n\nclass AdvertisementStatus(models.Model):\n name = models.CharField(max_length=100)\n\n def __str__(self):\n return self.name\n\n\nclass Authors(models.Model):\n name = models.CharField(max_length=2... | [
6,
7,
8,
10,
11
] |
'''
config -- config manipulator module for share
@author: shimarin
@copyright: 2014 Walbrix Corporation. All rights reserved.
@license: proprietary
'''
import json,argparse
import oscar,groonga
def parser_setup(parser):
parser.add_argument("base_dir")
parser.add_argument("operations", nargs="*")
... | normal | {
"blob_id": "8b4590cf2d8c040b6ab31c63baff0d83ab818641",
"index": 5423,
"step-1": "'''\nconfig -- config manipulator module for share\n\n@author: shimarin\n\n@copyright: 2014 Walbrix Corporation. All rights reserved.\n\n@license: proprietary\n'''\n\nimport json,argparse\nimport oscar,groonga\n\ndef parser... | [
0
] |
from locations.storefinders.stockinstore import StockInStoreSpider
class ScooterHutAUSpider(StockInStoreSpider):
name = "scooter_hut_au"
item_attributes = {"brand": "Scooter Hut", "brand_wikidata": "Q117747623"}
api_site_id = "10112"
api_widget_id = "119"
api_widget_type = "product"
api_origin... | normal | {
"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
] |
import os
import z5py
from shutil import copytree, copyfile
ROOT = '/g/kreshuk/pape/Work/data/mito_em/data'
SCRATCH = '/scratch/pape/mito_em/data'
def create_file(out_path, ref_path):
os.makedirs(out_path, exist_ok=True)
copyfile(
os.path.join(ref_path, 'attributes.json'),
os.path.join(out_pa... | normal | {
"blob_id": "9d3db4ca5bf964c68e9778a3625c842e74bf9dbd",
"index": 1228,
"step-1": "<mask token>\n\n\ndef create_file(out_path, ref_path):\n os.makedirs(out_path, exist_ok=True)\n copyfile(os.path.join(ref_path, 'attributes.json'), os.path.join(\n out_path, 'attributes.json'))\n\n\ndef copy_to_scratch... | [
3,
5,
6,
7,
8
] |
# Generated by Django 3.0.5 on 2020-04-25 15:35
from django.db import migrations, models
import lots.models
class Migration(migrations.Migration):
dependencies = [
('lots', '0012_auto_20200425_1720'),
]
operations = [
migrations.AlterField(
model_name='lots',
nam... | normal | {
"blob_id": "b36f3ffed888edaa7716f712f1549dc205799caf",
"index": 6338,
"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 = [('lots', '001... | [
0,
1,
2,
3,
4
] |
from ortools.sat.python import cp_model
import os
import math
import csv
import sys
def ortoolsSolverReduceVar(num, cap, refill, fun, goal):
model = cp_model.CpModel()
token = [model.NewIntVar(-2147483648, 2147483647, 't%i' % i)
for i in range(1, num + 1)]
play = [model.NewIntVar(-2147483648, ... | normal | {
"blob_id": "da98835e48a759cbe7bd29ddba1fac20c006827d",
"index": 4996,
"step-1": "<mask token>\n\n\ndef ortoolsSolverRange(num, cap, refill, fun, goal):\n model = cp_model.CpModel()\n token = [model.NewIntVar(1, cap, 't%i' % i) for i in range(1, num + 1)]\n play = [model.NewIntVar(1, cap, 'q%i' % i) for... | [
2,
4,
5,
6,
7
] |
# -*- coding: utf-8
# @paidatocandeira
# Acessa arquivo do CADASTRO NACIONAL DE EMPRESAS INIDÔNEAS E SUSPENSAS (CEIS) que está no portal da Transparência
#
import pandas as pd
# Parte 2 - pode rodar no Jupyter para ver resultados
# Método lendo direto o arquivo disponível para download (http://www.portaltransparencia... | normal | {
"blob_id": "d2325b07d11e64df0b26d0de9992a6f496e92a30",
"index": 2879,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nceis_arquivo.reset_index()\nceis_arquivo.info()\n<mask token>\nceis_sp.to_csv('ceis_sp.csv')\n",
"step-3": "<mask token>\nceis_arquivo = pd.read_csv('20180225_CEIS.csv', sep=';', encodi... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Stack(object):
def __init__(self):
self.arr = []
def push(self, val):
self.arr.append(val)
def pop(self):
if len(self.arr):
return self.arr.pop()
def inc(self, e, k):
count = min(len(self.arr), e)
for i in range... | flexible | {
"blob_id": "5ed439a2a7cfb9c941c40ea0c5eba2851a0f2855",
"index": 24,
"step-1": "<mask token>\n\n\nclass Stack(object):\n\n def __init__(self):\n self.arr = []\n\n def push(self, val):\n self.arr.append(val)\n\n def pop(self):\n if len(self.arr):\n return self.arr.pop()\n\... | [
5,
6,
7,
8,
10
] |
#!/usr/bin/env python
# encoding: utf-8
from tree import *
def findKthNode(root, k):
if not root:
return None
if root.number < k or k <= 0:
return None
if k == 1:
return root
if root.left and root.left.number >= k-1:
return findKthNode(root.left, k - 1)
else:
... | normal | {
"blob_id": "b9675bc65e06624c7f039188379b76da8e58fb19",
"index": 1623,
"step-1": "<mask token>\n\n\ndef findKthNode(root, k):\n if not root:\n return None\n if root.number < k or k <= 0:\n return None\n if k == 1:\n return root\n if root.left and root.left.number >= k - 1:\n ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class PR:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_... | flexible | {
"blob_id": "606a6e7ecc58ecbb11aa53602599e671514bc537",
"index": 3890,
"step-1": "<mask token>\n\n\nclass PR:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def init(self, d... | [
7,
8,
9,
11,
14
] |
<|reserved_special_token_0|>
class UserViewSet(viewsets.ModelViewSet):
queryset = User.objects.all()
model = User
serializer_class = UserSerializer
def get_permissions(self):
return (AllowAny() if self.request.method == 'POST' else
permissions.IsStaffOrTargetUser(),)
class Group... | flexible | {
"blob_id": "cce85d8a34fd20c699b7a87d402b34231b0d5dbb",
"index": 3186,
"step-1": "<mask token>\n\n\nclass UserViewSet(viewsets.ModelViewSet):\n queryset = User.objects.all()\n model = User\n serializer_class = UserSerializer\n\n def get_permissions(self):\n return (AllowAny() if self.request.m... | [
9,
11,
14,
16,
18
] |
from openvino.inference_engine import IENetwork, IECore
import numpy as np
import time
from datetime import datetime
import sys
import os
import cv2
class MotionDetect:
# Klasse zur Erkennung von Bewegung
def __init__(self):
self.static_back = None
def detect_motion(self, frame, reset=False):
... | normal | {
"blob_id": "fbd7868a37a2270e5dc86843adff50a94436404d",
"index": 5899,
"step-1": "<mask token>\n\n\nclass MotionDetect:\n\n def __init__(self):\n self.static_back = None\n <mask token>\n <mask token>\n\n\nclass InferenceModel:\n\n def __init__(self, device='MYRIAD'):\n self.ie = IECore(... | [
9,
10,
11,
12,
13
] |
import os
import flask_sqlalchemy as sqlalchemy
from flask import Flask, jsonify, request,render_template,redirect,url_for,json,flash
from flask_uploads import UploadSet, configure_uploads, IMAGES, patch_request_class
from flask_cors import CORS
import datetime
from flask_bootstrap import Bootstrap
from flask_login i... | normal | {
"blob_id": "5dc17db0aca109720d1ba62d65b86d9b81714063",
"index": 6622,
"step-1": "<mask token>\n\n\n@login_manager.user_loader\ndef load_user(id):\n user = Student.query.get(int(id))\n if user is not None:\n return user\n else:\n return Instructor.query.get(int(id))\n\n\n<mask token>\n\n\n... | [
9,
10,
13,
17,
18
] |
<|reserved_special_token_0|>
def fileWrite(content):
""" write result to result.txt """
file = open('./result.txt', 'w')
file.write(content)
file.close()
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def get_data(query):
""" fetch data from database ... | flexible | {
"blob_id": "612a3d168a09fc26530b95d258cbb4de6728419d",
"index": 3721,
"step-1": "<mask token>\n\n\ndef fileWrite(content):\n \"\"\" write result to result.txt \"\"\"\n file = open('./result.txt', 'w')\n file.write(content)\n file.close()\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_d... | [
1,
2,
5,
6,
7
] |
# coding: utf-8
from korean.morphophonemics.phonology import Syllable
from notes.old_morphology import Noun, Verb
class Case (object):
pass
class Nominative (Case):
def apply(self, noun):
if noun.has_tail():
noun.syllables.append(Syllable(u'이'))
else:
noun.syl... | normal | {
"blob_id": "1077efaa4379ff0e114a0b8d4d3b7156758e070f",
"index": 9861,
"step-1": "# coding: utf-8\n\nfrom korean.morphophonemics.phonology import Syllable\nfrom notes.old_morphology import Noun, Verb\n\n\nclass Case (object):\n pass \n\nclass Nominative (Case):\n def apply(self, noun):\n if n... | [
0
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.