code stringlengths 13 1.2M | order_type stringclasses 1
value | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
#coding=utf-8
import requests,sys
result_url=[]
def main():
counts=open(sys.argv[1]).readlines()
for line in open(sys.argv[1]):
line=line.strip("\n")
url=line
try:
#url="http://s6000.sgcc.com.cn/WebContent/s6000/main/index.jsp#no-back"
r=requests.get(u... | normal | {
"blob_id": "96a4659f03879e051af95b5aa9c1e1364015fb86",
"index": 8723,
"step-1": "<mask token>\n\n\ndef main():\n counts = open(sys.argv[1]).readlines()\n for line in open(sys.argv[1]):\n line = line.strip('\\n')\n url = line\n try:\n r = requests.get(url, verify=True, timeo... | [
1,
2,
3,
4,
5
] |
# Copyright (C) 2020 Francis Sun, all rights reserved.
"""A copyright utility"""
import datetime
import argparse
import os
import os.path
class Copyright:
_file_type = {
'c/c++': ['h', 'c', 'cpp', 'cc'],
'python': ['py'],
'cmake': ['cmake'],
'vim': ['vim'],
... | normal | {
"blob_id": "dc05a441c21a67fbb3a1975b3fccb865a32731c8",
"index": 4642,
"step-1": "<mask token>\n\n\nclass Copyright:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def _c_cpp_formater(self):\n return '/* ' + self.declaration + ' */'\n for ft in _file_type['c/c++']:\n ... | [
5,
7,
11,
12,
13
] |
#!/usr/bin/env python
# @HEADER
# ************************************************************************
#
# TriBITS: Tribal Build, Integrate, and Test System
# Copyright 2013 Sandia Corporation
#
# Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
# the U.S. Govern... | normal | {
"blob_id": "550f5ad4fef77d5795db0393ae0701f679143e72",
"index": 221,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif os.environ.get('MOCKPROGRAM_INOUT_FILE_OVERRIDE'):\n mockProgramInOutFilePath = os.environ.get('MOCKPROGRAM_INOUT_FILE_OVERRIDE'\n )\nelse:\n mockProgramInOutFilePath = '.m... | [
0,
1,
2,
3,
4
] |
"""
USERS MODEL
"""
from www import app
import mongoengine
import datetime
class User(mongoengine.Document):
username = mongoengine.StringField(required=True)
password = mongoengine.StringField(required=True)
email = mongoengine.StringField(required=True)
active_hash = mongoengine.StringField(re... | normal | {
"blob_id": "51cdb41836415c08609ee6a6bcc3adbaf2533da4",
"index": 3697,
"step-1": "<mask token>\n\n\nclass User(mongoengine.Document):\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>... | [
2,
3,
4,
5,
6
] |
from dateutil import parser
from datetime import datetime
from backend.crawler import calender_crawler
from backend.logic.schedule_by_time.schedule_utils import get_weeks_of_subject
from backend.logic.schedule_by_time.schedule_utils import get_time_str
# e.g. hôm nay, hôm qua, ngày mai, thứ 2, thứ tư, chủ nhật, thứ ... | normal | {
"blob_id": "6339f5c980ab0c0fb778870196493ddd83963ae7",
"index": 9203,
"step-1": "<mask token>\n\n\ndef filter_by_session(schedule_table, time_entity):\n subjects_of_day = filter_by_weekday(schedule_table, time_entity)\n start_session_hour = parser.parse(time_entity['value']['from']).hour\n schedule = [... | [
5,
6,
7,
10,
11
] |
# -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'KPS_RevisitBusinessEvents.ui'
#
# Created: Sun May 18 14:50:49 2014
# by: PyQt4 UI code generator 4.10.4
#
# WARNING! All changes made in this file will be lost!
from PyQt4 import QtCore, QtGui, QtSql
import sqlite3
try:
_fromUtf... | normal | {
"blob_id": "8339113fd6b0c286cc48ec04e6e24978e2a4b44e",
"index": 9991,
"step-1": "<mask token>\n\n\nclass Ui_Form(object):\n\n def setupUi(self, Form):\n Form.setObjectName(_fromUtf8('Form'))\n Form.resize(666, 538)\n palette = QtGui.QPalette()\n self.eventSkip = 0\n self.db... | [
8,
10,
11,
12,
13
] |
from helper import *
tree_type = TREE_TYPE_SPLIT
file_name = ''
file_path = ''
split_scalars = {}
visited = {}
adjacency = {}
pairs = {}
index_map = {}
postorder_map = {}
preorder_map = {}
birth = {}
death = {}
string = ''
class Tree(object):
def __init__(self):
self.index = None
self.children = []
self.p... | normal | {
"blob_id": "4daab8b8db1e394e3132ab5550fe0236b67074d8",
"index": 5527,
"step-1": "from helper import *\n\ntree_type = TREE_TYPE_SPLIT\n\nfile_name = ''\nfile_path = ''\n\nsplit_scalars = {}\nvisited = {}\nadjacency = {}\npairs = {}\n\nindex_map = {}\npostorder_map = {}\npreorder_map = {}\n\nbirth = {}\ndeath = {... | [
0
] |
#!/usr/bin/python
'''
** dmcalc **
Estimates the Dispersion Measure (DM) from the data in psrfits file format.
Returns the DM value with its uncertainty and reduced chi-square from tempo2
DM fit.
Dependencies
-------------
PSRCHIVE with python interface: http://psrchive.sourceforge.ne... | normal | {
"blob_id": "e464b465c4bc90c250c0ea02c17b7398d975964b",
"index": 1163,
"step-1": "<mask token>\n\n\ndef main():\n args = parser.parse_args()\n quiet = False\n if args.quiet:\n quiet = True\n tempo2 = True\n ptoa = False\n if args.print_toas:\n ptoa = True\n if not quiet:\n ... | [
4,
5,
6,
7,
8
] |
from django import forms
class LoginForm(forms.Form):
usuario=forms.CharField(label="Usuario",max_length=20, required=True, widget=forms.TextInput(
attrs={'class':'form-control'}
))
contraseña=forms.CharField(label="Contraseña",max_length=20, widget=forms.PasswordInput(
attrs={'class':'for... | normal | {
"blob_id": "7da5a7476c807619bed805cb892774c23c04c6f7",
"index": 4917,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass LoginForm(forms.Form):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass LoginForm(forms.Form):\n usuario = forms.CharField(label='Usuario', max_le... | [
0,
1,
2,
3,
4
] |
class NlpUtility():
"""
Utility methods to get particular parts of speech from a token set
"""
def get_nouns(self, tokens):
nouns = []
for word, pos in tokens:
if pos == "NN":
nouns.push(word)
def get_verbs(self, tokens):
verbs = []
for word, pos in tokens:
if pos == "VB":
nouns.push(word)
... | normal | {
"blob_id": "c6502ea2b32ad90c76b6dfaf3ee3218d029eba15",
"index": 56,
"step-1": "class NlpUtility:\n <mask token>\n\n def get_nouns(self, tokens):\n nouns = []\n for word, pos in tokens:\n if pos == 'NN':\n nouns.push(word)\n <mask token>\n <mask token>\n\n d... | [
4,
5,
6,
7,
8
] |
from catalyst_rl.contrib.registry import (
Criterion, CRITERIONS, GRAD_CLIPPERS, Model, MODELS, Module, MODULES,
Optimizer, OPTIMIZERS, Sampler, SAMPLERS, Scheduler, SCHEDULERS, Transform,
TRANSFORMS
)
from catalyst_rl.core.registry import Callback, CALLBACKS
from catalyst_rl.utils.tools.registry import Reg... | normal | {
"blob_id": "09d13fe6b090850782feb601412cf135d497136f",
"index": 6206,
"step-1": "<mask token>\n\n\ndef _callbacks_loader(r: Registry):\n from catalyst_rl.dl import callbacks as m\n r.add_from_module(m)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef _callbacks_loader(r: Registry):\n from catal... | [
1,
2,
3,
4,
5
] |
# -*- utf-8 -*-
from django.db import models
class FieldsTest(models.Model):
pub_date = models.DateTimeField()
mod_date = models.DateTimeField()
class BigS(models.Model):
s = models.SlugField(max_length=255)
class Foo(models.Model):
a = models.CharField(max_length=10)
d = models.DecimalField(... | normal | {
"blob_id": "d6cfe7132855d832d8fd1ea9ca9760bd22109a92",
"index": 1893,
"step-1": "<mask token>\n\n\nclass Bar(models.Model):\n b = models.CharField(max_length=10)\n a = models.ForeignKey(Foo, related_name='bars', on_delete=models.CASCADE)\n\n\nclass DTModel(models.Model):\n name = models.CharField(max_l... | [
5,
6,
8,
10,
13
] |
# import visual_servoing_utils_main as utils
from autolab_core import rigid_transformations as rt
from yumipy import YuMiState
class YumiConstants:
T_gripper_gripperV = rt.RigidTransform(rotation=[[-1, 0, 0], [0, 1, 0], [0, 0, -1]],
from_frame='gripper', to_frame='obj')
... | normal | {
"blob_id": "34c81b9318d978305748d413c869a86ee6709e2c",
"index": 996,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass YumiConstants:\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... | [
0,
1,
2,
3,
4
] |
from math import sqrt, ceil
def encode_s(s):
encoded_s = ''
s_with_no_spaces = s.replace(' ', '')
step = ceil(sqrt(len(s_with_no_spaces)))
for j in range(0, step):
i = j
while i < len(s_with_no_spaces):
encoded_s = encoded_s + s_with_no_spaces[i]
i += step
... | normal | {
"blob_id": "a3ed47c285b26dca452fa192eb354a21a78b8424",
"index": 4632,
"step-1": "<mask token>\n\n\ndef TheRabbitsFoot(s, encode):\n if encode:\n return encode_s(s)\n return decode_s(s)\n",
"step-2": "<mask token>\n\n\ndef decode_s(s):\n arr = s.split(' ')\n decoded_s = ''\n for j in rang... | [
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
"""
A customised logger for this project for logging to the file and console
Created on 29/07/2022
@author: PNimbhore
"""
# imports
import os
import logging
class Logger:
"""
A custom logger which will take care
of logging to console and file.
"""
def __init__(self, filepat... | normal | {
"blob_id": "45d57f8392b89776f9349c32b4bb2fa71a4aaa83",
"index": 8610,
"step-1": "<mask token>\n\n\nclass Logger:\n <mask token>\n\n def __init__(self, filepath):\n \"\"\"\n Constructor\n :param filepath:\n \"\"\"\n self.filepath = filepath\n self.logger = logging.... | [
2,
3,
4,
5,
6
] |
#-*- coding: utf-8 -*-
s = "123"
try:
print(int(s) + 1)
print(int(s) / 1)
except ValueError as ve:
print("ValueError occurs!!!", ve)
except ZeroDivisionError as e:
print("ValueError occurs!!!", e)
except :
print("Error occurs!!!")
else:
print("elseeeeeeeeeeeeeee")
finally:
print("ABCDE... | normal | {
"blob_id": "1bf79319613ca1454f3a9ed21068bd899616395c",
"index": 624,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ntry:\n print(int(s) + 1)\n print(int(s) / 1)\nexcept ValueError as ve:\n print('ValueError occurs!!!', ve)\nexcept ZeroDivisionError as e:\n print('ValueError occurs!!!', e)\ne... | [
0,
1,
2,
3
] |
""" [BBC] Web Scraper """
import os
from .abstract_crawler import AbstractWebCrawler
class BBCCrawler(AbstractWebCrawler):
""" [BBC] Web Scraper """
# Spider Properties
name = "web_bbc"
# Crawler Properties
resource_link = 'http://www.bbc.com/news/topics/cz4pr2gd85qt/cyber-security'
resourc... | normal | {
"blob_id": "3c22fbfd7d83ff3ecacabc3c88af2169fa5906b9",
"index": 5190,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass BBCCrawler(AbstractWebCrawler):\n <mask token>\n name = 'web_bbc'\n resource_link = (\n 'http://www.bbc.com/news/topics/cz4pr2gd85qt/cyber-security')\n resour... | [
0,
2,
3,
4,
5
] |
from django import forms
from django.core.validators import RegexValidator
from dashboard.validators import validate_domainonly_email
class addUserForm(forms.Form):
username = forms.CharField(label='User Name', required="required", disabled="", min_length=6, max_length=128,
help_tex... | normal | {
"blob_id": "39b6ca21b8d4856e2b2edfcbd00b75fbce6dfff7",
"index": 1407,
"step-1": "<mask token>\n\n\nclass addUserForm(forms.Form):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass addUserForm(for... | [
1,
2,
3,
4,
5
] |
from discord.ext import commands
def is_owner():
async def predicate(ctx):
return ctx.author.id == 98208218022428672
return commands.check(predicate)
class Staff(commands.Cog):
def __init__(self, bot):
self.bot = bot
@commands.command(
name='stop',
aliases=['shutdow... | normal | {
"blob_id": "23b2cc5b561a11ae7757a281a141491d5b7e23ca",
"index": 2683,
"step-1": "<mask token>\n\n\nclass Staff(commands.Cog):\n <mask token>\n\n @commands.command(name='stop', aliases=['shutdown'], description=\n 'This is a command for staff only to stop the bot')\n @is_owner()\n async def st... | [
1,
2,
3,
4,
5
] |
# Author: BeiYu
# Github: https://github.com/beiyuouo
# Date : 2021/2/21 21:57
# Description:
__author__ = "BeiYu"
from utils.init_env import set_seed
from utils.options import *
import os
import logging
import torch
from torch import nn
from torch import optim
from torch.optim.lr_scheduler import MultiStepLR
from ... | normal | {
"blob_id": "75e6554ea3c327c87a2a65710a7f1d55e9933bb0",
"index": 276,
"step-1": "<mask token>\n\n\ndef train():\n args = get_args()\n os.makedirs(args.model_path, exist_ok=True)\n set_seed(args.seed)\n \"\"\"\n To follow this training routine you need a DataLoader that yields the tuples of the... | [
1,
3,
4,
5,
6
] |
import discord
from discord.ext import commands
class TestCommands(commands.Cog, description="Unstable test commands", command_attrs=dict(hidden=True, description="Can only be used by an Owner")):
def __init__(self, bot):
self.bot = bot
self.hidden = True
print("Loaded", __name__)
as... | normal | {
"blob_id": "d5a5c6f9d483b2998cd0d9e47b37ab4499fa1c2a",
"index": 6279,
"step-1": "<mask token>\n\n\nclass TestCommands(commands.Cog, description='Unstable test commands',\n command_attrs=dict(hidden=True, description='Can only be used by an Owner')\n ):\n <mask token>\n\n async def cog_check(self, ct... | [
1,
2,
3,
4,
5
] |
from django.urls import path,include
from Income import views
urlpatterns = [
path('IncomeHome/',views.IncomeHome,name='IncomeHome'),
path('IncomeCreate/',views.IncomeCreate.as_view(),name='IncomeCreate'),
path('IncomeUpdate/<int:pk>',views.IncomeUpdate.as_view(),name='IncomeUpdate'),
path('IncomeDel... | normal | {
"blob_id": "ad3a7221883a847fc9d26097c3801973cbbda38e",
"index": 355,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('IncomeHome/', views.IncomeHome, name='IncomeHome'),\n path('IncomeCreate/', views.IncomeCreate.as_view(), name='IncomeCreate'\n ), path('IncomeUpdate/<int:pk>', ... | [
0,
1,
2,
3
] |
__author__ = 'jjpr'
import pyrr
import barleycorn as bc
def test_xyz123():
cone_x = bc.primitives.Cone(1.0, 1.0)
| normal | {
"blob_id": "e6af221f1d6397d0fc52671cdd27d43549d0aecb",
"index": 513,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef test_xyz123():\n cone_x = bc.primitives.Cone(1.0, 1.0)\n",
"step-3": "__author__ = 'jjpr'\n<mask token>\n\n\ndef test_xyz123():\n cone_x = bc.primitives.Cone(1.0, 1.0)\n",
... | [
0,
1,
2,
3
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# jan 2014 bbb garden shield attempt
# AKA
'''
Sensors:
analog level sensor, pin AIN0
TMP102 i2c temperature sensor, address 0x48
(if add0 is grounded) or 0x49 (if pulled up)
Outputs:
Analog RGB LED strip
I2C display(?)
Pump Activate/Deactivate (GPIO pin)
Some measurem... | normal | {
"blob_id": "06992263599fe3290c87ec00c6cb8af3748920c8",
"index": 5497,
"step-1": "\n#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n# jan 2014 bbb garden shield attempt\n# AKA\n\n'''\nSensors:\nanalog level sensor, pin AIN0\nTMP102 i2c temperature sensor, address 0x48\n(if add0 is grounded) or 0x49 (if pulled up... | [
0
] |
# apport hook for oem-config; adds log file
import os.path
def add_info(report):
if os.path.exists('/var/log/oem-config.log'):
report['OemConfigLog'] = ('/var/log/oem-config.log',)
| normal | {
"blob_id": "74b1cdcb1aaf6cde7e8ce3eeb73cd82689719b00",
"index": 6404,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef add_info(report):\n if os.path.exists('/var/log/oem-config.log'):\n report['OemConfigLog'] = '/var/log/oem-config.log',\n",
"step-3": "import os.path\n\n\ndef add_info... | [
0,
1,
2,
3
] |
'''
"MAIN" module
All operations are added to the defaultgraph.
Network functions are found in module network_functions_2
Display graph in tensorboard by opening a new terminal and write "tensorboard --logdir=tensorbaord/debug/01/" where
the last number depends on which directory the current graph is saved in (see l... | normal | {
"blob_id": "8a2cf1d550a593beae579104413b424e007d511f",
"index": 9048,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith tf.name_scope('input_data'):\n (iterate_data, sub_images, sub_depths, sub_images_placeholder,\n sub_depths_placeholder) = rd.read_debug_data()\n sub_images_coarse = tf.c... | [
0,
1,
2,
3,
4
] |
import sys
from collections import defaultdict
sys.setrecursionlimit(1200)
def dfs(G, v, prev):
t = []
s = 0
for x in G[v]:
if x == prev: continue
tmp = dfs(G, x, v)
s += tmp[1]
t.append(tmp[0] - tmp[1])
t.sort()
t = t[:2]
if len(t) < 2:
return (s... | normal | {
"blob_id": "efa06d929e76a255afd9923b5340252c291a325c",
"index": 3615,
"step-1": "import sys\nfrom collections import defaultdict\nsys.setrecursionlimit(1200)\n\ndef dfs(G, v, prev):\n t = []\n s = 0\n for x in G[v]:\n if x == prev: continue\n tmp = dfs(G, x, v)\n s += tmp[1]\n ... | [
0
] |
from typing import Type
from sqlalchemy.exc import IntegrityError
from src.main.interface import RouteInterface as Route
from src.presenters.helpers import HttpRequest, HttpResponse
from src.presenters.errors import HttpErrors
def flask_adapter(request: any, api_route: Type[Route]) -> any:
"""Adapter pattern for ... | normal | {
"blob_id": "3212bb7df990ad7d075b8ca49a99e1072eab2a90",
"index": 595,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef flask_adapter(request: any, api_route: Type[Route]) ->any:\n \"\"\"Adapter pattern for Flask\n :param - Flask Request\n :api_route: Composite Routes\n \"\"\"\n try:\... | [
0,
1,
2,
3
] |
# -*- coding: utf-8 -*-
"""Part of speech mapping constants and functions for NLPIR/ICTCLAS.
This module is used by :mod:`pynlpir` to format segmented words for output.
"""
import logging
logger = logging.getLogger("pynlpir.pos_map")
#: A dictionary that maps part of speech codes returned by NLPIR to
#: human-read... | normal | {
"blob_id": "093b2afef7cdfb7070eb5e94e84624afe495db66",
"index": 1948,
"step-1": "<mask token>\n\n\ndef get_pos_name(code, name='parent', english=True, pos_tags=POS_MAP):\n \"\"\"Gets the part of speech name for *code*.\n\n :param str code: The part of speech code to lookup, e.g. ``'nsf'``.\n :param str... | [
1,
2,
3,
4,
5
] |
# -*- coding: utf-8 -*-
from django.shortcuts import get_object_or_404
from rest_framework import serializers
from tandlr.core.api.serializers import ModelSerializer
from tandlr.users.models import DeviceUser, User, UserSettings
from tandlr.utils.refresh_token import create_token
class LoginSerializer(serializers.S... | normal | {
"blob_id": "01900c1d14a04ee43553c8602a07e0c6ecfabded",
"index": 1803,
"step-1": "<mask token>\n\n\nclass LogoutSerializer(ModelSerializer):\n <mask token>\n <mask token>\n\n\n class Meta:\n model = DeviceUser\n fields = ['device_user_token', 'device_os', 'is_active']\n <mask token>\n ... | [
9,
11,
15,
17,
19
] |
"""Given an integer array arr and an integer difference, return the length of
the longest subsequence in arr which is an arithmetic sequence such that the
difference between adjacent elements in the subsequence equals difference."""
class Solution(object):
def longestSubsequence(self, arr, difference):
... | normal | {
"blob_id": "fa4ab3ed5c653633879b5ba2c078c896aa3eb0c6",
"index": 2838,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Solution(object):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Solution(object):\n\n def longestSubsequence(self, arr, difference):\n dp = dict()\n ... | [
0,
1,
2,
3
] |
#alds13c
from collections import deque
d_stack=deque()
res_stack=deque()
s = input()
for i in range(len(s)):
#print(d_stack,res_stack)
if s[i]=="\\":
d_stack.append(i)
elif s[i]=="/":
if len(d_stack)==0:
continue
left = d_stack.pop()
area = i-left
#res_s... | normal | {
"blob_id": "48e3259698788904e000eb15b5443067b0c3e791",
"index": 5968,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(len(s)):\n if s[i] == '\\\\':\n d_stack.append(i)\n elif s[i] == '/':\n if len(d_stack) == 0:\n continue\n left = d_stack.pop()\n ... | [
0,
1,
2,
3,
4
] |
import smtplib
import requests
import datetime
import json
import time
from datetime import date
from urllib.request import Request,urlopen
today = date.today().strftime("%d-%m-%y")
count = 0
pincodes = ["784164","781017","784161","787001"]
date = 0
temp = str(14) + "-05-21"
while True:
for... | normal | {
"blob_id": "7c60ae58b26ae63ba7c78a28b72192373cc05a86",
"index": 1211,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile True:\n for i in range(0, 8):\n temp = str(23 + i) + '-05-21'\n for pincode in pincodes:\n req = Request(\n 'https://cdn-api.co-vin.in/api... | [
0,
1,
2,
3,
4
] |
import datetime
def year_choices():
return [(r, r) for r in range(1984, datetime.date.today().year + 1)]
def current_year():
return datetime.date.today().year
| normal | {
"blob_id": "90bb70b0a97c7872c8581a176ebacc50df8e1f72",
"index": 464,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef year_choices():\n return [(r, r) for r in range(1984, datetime.date.today().year + 1)]\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef year_choices():\n return [(r, ... | [
0,
1,
2,
3
] |
import warnings
from re import *
from pattern import collection
warnings.filterwarnings("ignore")
def test():
raw_text = "通化辉南县经济适用房_通化辉南县经适房_通化辉南县经济适用房转让_通化去114网通化切换城市var googlequerykey ='二手经适房 二手房买卖 二手房地产公司' ; var AdKeyWords = 'j... | normal | {
"blob_id": "488d20a86c5bddbca2db09b26fb8df4b6f87a1dc",
"index": 2354,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef test():\n raw_text = (\n \"通化辉南县经济适用房_通化辉南县经适房_通化辉南县经济适用房转让_通化去114网通化切换城市var googlequerykey ='二手经适房 二手房买卖 二手房地产公司' ; ... | [
0,
1,
2,
3,
4
] |
import os, sys, datetime, csv, platform
####FUNCTIONS####
#Get Creation Time
def get_lastupdate_date(path):
return os.path.getmtime(path)
#Get Date From String
def convertIntToTimestamp(timeint):
return str(datetime.datetime.fromtimestamp(timeint))
#Get Filename
def getFilename(name):
return os.path... | normal | {
"blob_id": "e83b6b1f4cb12fe3b932903eddddfb0dc0e7d98d",
"index": 2765,
"step-1": "<mask token>\n\n\ndef get_lastupdate_date(path):\n return os.path.getmtime(path)\n\n\ndef convertIntToTimestamp(timeint):\n return str(datetime.datetime.fromtimestamp(timeint))\n\n\ndef getFilename(name):\n return os.path.... | [
5,
8,
9,
11,
12
] |
#!/usr/bin/python
# -*- coding:utf-8 -*-
import epd2in7
import time
from PIL import Image,ImageDraw,ImageFont
import traceback
try:
epd = epd2in7.EPD()
epd.init()
epd.Clear(0xFF)
time.sleep(2)
epd.sleep()
except:
print 'traceback.format_exc():\n%s' % traceback.format_exc... | normal | {
"blob_id": "14cac4f11830511923ee1ce0d49ec579aec016fd",
"index": 4720,
"step-1": "#!/usr/bin/python\n# -*- coding:utf-8 -*-\n\nimport epd2in7\nimport time\nfrom PIL import Image,ImageDraw,ImageFont\nimport traceback\n\ntry:\n epd = epd2in7.EPD()\n epd.init()\n epd.Clear(0xFF)\n \n time.sleep(2)\n ... | [
0
] |
# print all cards with even numbers.
cards = ["2", "3", "4", "5", "6", "7", "8", "9", "10", "J", "Q", "K", "A"]
for card in cards:
try:
number = int(card)
if number % 2 == 0: # modulo operator
print(card, "is an even card.")
except ValueError:
print (card, "can not be divi... | normal | {
"blob_id": "b5180a2dbe1f12e1bbc92874c67ea99c9a84a9ed",
"index": 19,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor card in cards:\n try:\n number = int(card)\n if number % 2 == 0:\n print(card, 'is an even card.')\n except ValueError:\n print(card, 'can not be d... | [
0,
1,
2,
3
] |
### Global parameters ###
seconds_per_unit_time = 0.01
#########################
pars_spont = {
"tau_p": 2.5,
"tau_d": 5.0,
"amp_p": 0.08,
"amp_d": -0.0533,
"rho": 0.0015,
"N": 50,
"w_max": 0.05,
"mu": 0.07,
"seed": None,
"tend": 50_000_000,
"r_in": 0.04,
"w_in": 0.05,... | normal | {
"blob_id": "8f17c1ed0cb273a88b986cd7fe7a45439211d536",
"index": 8641,
"step-1": "<mask token>\n",
"step-2": "seconds_per_unit_time = 0.01\npars_spont = {'tau_p': 2.5, 'tau_d': 5.0, 'amp_p': 0.08, 'amp_d': -0.0533,\n 'rho': 0.0015, 'N': 50, 'w_max': 0.05, 'mu': 0.07, 'seed': None, 'tend':\n 50000000, 'r_... | [
0,
1,
2
] |
from functions.service_funcs.get_data import get_data_character
def clean_room(update):
char, db_sess = get_data_character(update, return_sess=True)
# удаляем старую комнату и всю инфу о ней
if char and char.room:
if char.room.mobs:
for mob in char.room.mobs:
db_sess.de... | normal | {
"blob_id": "4d57fa22282d7b3f8adabedd7a04e32767181890",
"index": 5693,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef clean_room(update):\n char, db_sess = get_data_character(update, return_sess=True)\n if char and char.room:\n if char.room.mobs:\n for mob in char.room.mob... | [
0,
1,
2,
3
] |
from .Buzzer import BuzzerController
from .Card import CardScanner
from .RFID import RFIDController
from .Servo import ServoController
__all__ = ["BuzzerController", "CardScanner", "RFIDController", "ServoController"]
| normal | {
"blob_id": "8fa78824a38a3b0c1f51aceacab671f987ea2705",
"index": 9635,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n__all__ = ['BuzzerController', 'CardScanner', 'RFIDController',\n 'ServoController']\n",
"step-3": "from .Buzzer import BuzzerController\nfrom .Card import CardScanner\nfrom .RFID im... | [
0,
1,
2,
3
] |
from __future__ import division
import random as rnd
import math
from collections import Counter
from matplotlib import pyplot as plt
import ds_library
import ds_algebra
import ds_probability
import ds_gradient_descent
def normal_pdfs_visualization():
xs = [x/10.0 for x in range(-50, 50)]
plt.plot(xs... | normal | {
"blob_id": "c0adc0032a2647a19d3540c057fa9762906e5f62",
"index": 4439,
"step-1": "<mask token>\n\n\ndef normal_pdfs_visualization():\n xs = [(x / 10.0) for x in range(-50, 50)]\n plt.plot(xs, [ds_probability.normal_pdf(x, sigma=1) for x in xs], '-',\n label='mu=0-sigma=1')\n plt.plot(xs, [ds_prob... | [
3,
4,
6,
7,
8
] |
from django.shortcuts import resolve_url as r
from django.test import TestCase
class coreGetHome(TestCase):
def setUp(self):
self.resp = self.client.get(r('core:core_home'))
def test_template_home(self):
self.assertTemplateUsed(self.resp, 'index.html')
def test_200_template_home(self):
... | normal | {
"blob_id": "d20e41dd7054ff133be264bebf13e4e218710ae5",
"index": 933,
"step-1": "<mask token>\n\n\nclass coreGetHome(TestCase):\n <mask token>\n <mask token>\n\n def test_200_template_home(self):\n self.assertEqual(200, self.resp.status_code)\n",
"step-2": "<mask token>\n\n\nclass coreGetHome(T... | [
2,
3,
4,
5
] |
import praw
import pickle
import copy
class histogram:
def __init__(self, dictionary=None):
self.frequencies = {}
if dictionary is not None:
self.frequencies = copy.deepcopy(dictionary)
def get_sum(self):
the_sum = 0
for e in self.frequencies:
the_sum +=... | normal | {
"blob_id": "f135d52e4d5e49f96869c4209b84f30ff72f6780",
"index": 876,
"step-1": "import praw\nimport pickle\nimport copy\n\nclass histogram:\n def __init__(self, dictionary=None):\n self.frequencies = {}\n if dictionary is not None:\n self.frequencies = copy.deepcopy(dictionary)\n\n ... | [
0
] |
# Error using ncdump - NetCDF4 Python
ncdump -h filename
| normal | {
"blob_id": "12f0eeeb81fe611d88e33fd2e8df407e289fb582",
"index": 1255,
"step-1": "# Error using ncdump - NetCDF4 Python\nncdump -h filename\n",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
} | [
0
] |
#!/usr/bin/python
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
import os
try:
import Image
except ImportError:
from PIL import Image
import sys
sys.path.append(os.path.abspath(os.path.join(__file__, os.pardir, os.pardir, 'DropPy.Common')))
from file_tools import get_file_paths_from_director... | normal | {
"blob_id": "df3208a00f7a5dd1ddd76542ac0de85762cc45ab",
"index": 7236,
"step-1": "<mask token>\n\n\nclass Task(object):\n <mask token>\n <mask token>\n\n @staticmethod\n def rotate_file(input_file, output_dir, degrees, expand):\n output_file_name = os.path.basename(input_file)\n output_... | [
2,
3,
4,
6,
7
] |
import os
import pandas as pd
import time
import sys
from tqdm import tqdm
sys.path.append(os.path.join(os.environ['HOME'],'Working/interaction/'))
from src.make import exec_gjf
from src.vdw import vdw_R, get_c_vec_vdw
from src.utils import get_E
import argparse
import numpy as np
from scipy import signal
i... | normal | {
"blob_id": "961bda96e433bb66d592ad1e99c92db0a9ab9fe9",
"index": 8545,
"step-1": "<mask token>\n\n\ndef init_process(args):\n auto_dir = args.auto_dir\n monomer_name = args.monomer_name\n os.makedirs(os.path.join(auto_dir, 'gaussian'), exist_ok=True)\n os.makedirs(os.path.join(auto_dir, 'gaussview'),... | [
3,
7,
9,
10,
12
] |
from starter2 import *
from collections import defaultdict
import scipy
import colors
import hair_dryer
reload(hair_dryer)
import three_loopers_u500 as TL
import movie_frames
def GE_pearson(this_looper,core_list=None):
if core_list is None:
core_list = np.unique(this_looper.tr.core_ids)
name = th... | normal | {
"blob_id": "0762c5bec2d796bb7888e3de45e29fb20f88f491",
"index": 392,
"step-1": "<mask token>\n\n\ndef GE_pearson(this_looper, core_list=None):\n if core_list is None:\n core_list = np.unique(this_looper.tr.core_ids)\n name = this_looper.sim_name\n thtr = this_looper.tr\n mask = movie_frames.q... | [
1,
2,
3,
4,
5
] |
class StartStateImpl:
start_message = "Для продолжения мне необходим ваш корпоративный E-mail"\
"Адрес вида: <адрес>@edu.hse.ru (без кавычек)"
thank_you = "Спасибо за ваш адрес. Продолжаем."
def __init__(self):
pass
def enter_state(self, message, user):
user.send_message(StartS... | normal | {
"blob_id": "3741e44178375f351278cb17c2bf8f11c69e1262",
"index": 4009,
"step-1": "class StartStateImpl:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def exit_state(self, message, user):\n user.send_message(StartStateImpl.thank_you)\n <mask token>\n\n\nclass StartState(... | [
5,
6,
7,
8,
10
] |
"""This module will serve the api request."""
import json
from bson.json_util import dumps
from flask import abort, request, Response, jsonify
from api import app, collection
@app.route("/api/v1/users", methods=['POST'])
def create_user():
"""
Function to create new users.
"""
try:
# Creat... | normal | {
"blob_id": "0f4bb65b93df997ca1a9b7945ebcec53a2f43822",
"index": 3636,
"step-1": "<mask token>\n\n\n@app.route('/api/v1/users', methods=['POST'])\ndef create_user():\n \"\"\"\n Function to create new users.\n \"\"\"\n try:\n try:\n body = request.get_json()\n except:\n ... | [
3,
4,
5,
6,
7
] |
import tensorflow as tf
import blood_model
import os
import numpy as np
FLAGS = tf.app.flags.FLAGS
RUN = 'new_test_hm'
tf.app.flags.DEFINE_string('checkpoint_dir', RUN+'/checkpoints',
"""Directory where to write event logs and checkpoint.""")
tf.app.flags.DEFINE_string('summaries_dir', RUN+... | normal | {
"blob_id": "f653e906d3026de4bb1e705162f4321bb75e8705",
"index": 4166,
"step-1": "<mask token>\n\n\ndef check_filesystem():\n \"\"\"\n either start a new checkpoint or continue from existing checkpoint folder\n \"\"\"\n if FLAGS.continue_run:\n if not tf.gfile.Exists(FLAGS.summaries_dir):\n ... | [
3,
5,
6,
7,
8
] |
import json
from django.core.management import call_command
from django.http import JsonResponse
from django.test import TestCase
from django.urls import reverse
URLS = ['api_v1:categories', 'api_v1:main_categories', 'api_v1:articles']
class GetJsonData(TestCase):
def test_post_not_login_no_pk(self):
f... | normal | {
"blob_id": "676caabb103f67c631bc191b11ab0d2d8ab25d1e",
"index": 5803,
"step-1": "<mask token>\n\n\nclass UnLoginGetArticleJsonTestCase(TestCase):\n\n @classmethod\n def setUpClass(cls):\n super().setUpClass()\n call_command('loaddata', 'fixtures/auth.json', verbosity=0)\n call_command... | [
5,
7,
8,
9,
11
] |
from slistener import SListener
from slistener import track
import datetime
import time, tweepy, sys
import json
import re
#def tweet_collector():
consumer_key='qpUR91PwjvChszV0VFgrc4Hje'
consumer_secret='q9mPUZE2OsFbaqKUF32ZsY1ry4anZ1k8pNSne56wc3HInmERFu'
access_token='2845943577-R0g6YRlrdEqSFb2mKy5HXuByQPdpq4TLGrPkm... | normal | {
"blob_id": "606e40dd073c3efc95ef01a08466fd536a28f140",
"index": 324,
"step-1": "from slistener import SListener\nfrom slistener import track\nimport datetime\nimport time, tweepy, sys\nimport json\nimport re\n\n#def tweet_collector():\nconsumer_key='qpUR91PwjvChszV0VFgrc4Hje'\nconsumer_secret='q9mPUZE2OsFbaqKUF... | [
0
] |
from setuptools import setup
from os import path
this_directory = path.abspath(path.dirname(__file__))
with open(path.join(this_directory, 'README.md'), encoding='utf-8') as f:
long_description = f.read()
setup(
name='SumoSound',
packages=['SumoSound'],
version='1.0.2',
license='MIT',
description='A pyt... | normal | {
"blob_id": "81c9cabaa611f8e884708d535f0b99ff83ec1c0d",
"index": 8319,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open(path.join(this_directory, 'README.md'), encoding='utf-8') as f:\n long_description = f.read()\nsetup(name='SumoSound', packages=['SumoSound'], version='1.0.2', license=\n ... | [
0,
1,
2,
3,
4
] |
#read file
my_file=open("file.txt","r")
#print(my_file.read())
#print(my_file.readline())
#print(my_file.read(3))#read 3 caracteres
"""
for line in my_file:
print(line)
my_file.close()
"""
print(my_file.readlines())#list
#close file
my_file.close()
#create new file and writing
new_file=open("newfile.txt",mode="w",... | normal | {
"blob_id": "d44f8a2dee35d76c152695d49d73f74e9c25bfa9",
"index": 3015,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(my_file.readlines())\nmy_file.close()\n<mask token>\nfor i in range(5):\n new_file.write('new line ' + str(i + 1) + '\\n')\nnew_file.close()\n<mask token>\nnew_file.writelines(a)... | [
0,
1,
2,
3
] |
from robotcar import RobotCar
import pdb
class RobotCar_Stub(RobotCar):
def forward(self):
print("Forward")
def backward(self):
print("Backward")
def left(self):
print("Left")
def right(self):
print("Right")
def stop(self):
print("Stop")
if __name__ == '__main__':
... | normal | {
"blob_id": "09b2c1e69203f440754e82506b42e7856c94639a",
"index": 8623,
"step-1": "<mask token>\n\n\nclass RobotCar_Stub(RobotCar):\n <mask token>\n\n def backward(self):\n print('Backward')\n\n def left(self):\n print('Left')\n\n def right(self):\n print('Right')\n\n def stop(... | [
5,
6,
7,
8,
9
] |
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] == s[i]:
j += 1
if j == len(wo... | normal | {
"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
] |
import requests
import json
data = json.load(open("dummy_data/data.json"))
for one in data:
print(one)
r = requests.post("http://localhost:8080/sumari", json=one)
print(r.text)
| normal | {
"blob_id": "8bc40ed4fe1091ecdb40cd55ff9cf53010078823",
"index": 361,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor one in data:\n print(one)\n r = requests.post('http://localhost:8080/sumari', json=one)\n print(r.text)\n",
"step-3": "<mask token>\ndata = json.load(open('dummy_data/data.j... | [
0,
1,
2,
3,
4
] |
"""
Exercise 3 from the Python tutorial Part 1 on:
https://codeandwork.github.io/courses/prep/pythonTutorial1.html
"""
import math
print("Give the length of each side in order to compute the area of a triangle.")
lenA = float(input("Give the length of side A:"))
lenB = float(input("Give the length of side B:"))
len... | normal | {
"blob_id": "398cb05218a9772a0b62fdfbacc465b26427827d",
"index": 2854,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(\n 'Give the length of each side in order to compute the area of a triangle.')\n<mask token>\nprint('The triangle area is:', triangleArea)\n",
"step-3": "<mask token>\nprint(\n... | [
0,
1,
2,
3,
4
] |
import sys
n=int(input().strip())
a=list(input().strip().split(' '))
H=list(input().strip().split(' '))
a = [int(i) for i in a]
m=int(H[0])
hmin=int(H[1])
hmax=int(H[2])
pos=0
found = 0
d=a[-1]-a[0]
if(d==m):
print(a[0])
elif(0<d<m):
for i in range(hmin, hmax+1):
fin1 = a[0]-i+m
if(hmin<=fin1-... | normal | {
"blob_id": "3da82bcff0a4f91c1245892bc01e9f743ea354a8",
"index": 4484,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif d == m:\n print(a[0])\nelif 0 < d < m:\n for i in range(hmin, hmax + 1):\n fin1 = a[0] - i + m\n if hmin <= fin1 - a[-1] <= hmax or fin1 == a[-1]:\n prin... | [
0,
1,
2,
3,
4
] |
from .base import *
import os
SECRET_KEY = os.environ['SECRET_KEY']
ALLOWED_HOSTS = ['demo.pythonic.nl']
DEBUG = False
| normal | {
"blob_id": "e5607d9893b775b216d1790897124a673b190c26",
"index": 2085,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nSECRET_KEY = os.environ['SECRET_KEY']\nALLOWED_HOSTS = ['demo.pythonic.nl']\nDEBUG = False\n",
"step-3": "from .base import *\nimport os\nSECRET_KEY = os.environ['SECRET_KEY']\nALLOWED_... | [
0,
1,
2
] |
#library
import pandas as pd
import numpy as np
import sys
from tqdm import tqdm # appear the precess of running situation.
import time
from scipy.spatial.distance import pdist, squareform
#0. Data Load
data = pd.read_csv(sys.argv[1], delimiter='\t') # Load train (input text file)
#1. Data Preprocessing
all_element... | normal | {
"blob_id": "267695555e876dc2fe5820dc194490aad9e5e344",
"index": 1361,
"step-1": "<mask token>\n\n\ndef avg_dissim_within_group_element(node, element_list):\n max_diameter = -np.inf\n sum_dissm = 0\n for i in element_list:\n sum_dissm += dissimilarity_matrix[node][i]\n if dissimilarity_mat... | [
4,
5,
6,
8,
9
] |
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
] |
import json
import os
from six import iteritems
from ..exceptions import ColinConfigException
from ..constant import CONFIG_DIRECTORY, JSON
from ..loader import load_check_implementation
from ..target import is_compatible
class Config(object):
def __init__(self, name=None):
"""
Load config for ... | normal | {
"blob_id": "7bb9455e6f0c15ab0be6963cff06ff41df73e6e0",
"index": 2583,
"step-1": "<mask token>\n\n\nclass Config(object):\n\n def __init__(self, name=None):\n \"\"\"\n Load config for colin.\n\n :param name: str (name of the config file (without .json), default is \"default\"\n \"\... | [
6,
7,
8,
9,
11
] |
from flask import Flask, render_template, request, url_for, redirect,jsonify,json,request
from pymongo import MongoClient
#conexão bd
app = Flask(__name__)
conexao = MongoClient('localhost',27017)
db = conexao['teste_db']
#inserindo contatos iniciais
contato1 = {'nome': 'Lucas', 'email': 'lucas@gmail.com', 'telefone... | normal | {
"blob_id": "05ca16303d0eb962249793164ac91795c45cc3c2",
"index": 9974,
"step-1": "<mask token>\n\n\n@app.route('/')\ndef showMachineList():\n return render_template('list.html')\n\n\n@app.route('/insert_records', methods=['POST'])\ndef insert_records():\n json_data = request.json['info']\n nome = json_d... | [
3,
4,
5,
6,
7
] |
from scipy.io import wavfile
import numpy
from matplotlib import pyplot as plt
import librosa
import noisereduce
def loadWavFile(fileName, filePath, savePlot, maxAudioLength, reduceNoise = True):
# Read file
# rate, data = wavfile.read(filePath)
# print(filePath, rate, data.shape, "audio length", data.shap... | normal | {
"blob_id": "07ac061d7d1eaf23b6c95fbcbf6753f25e568188",
"index": 157,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef loadWavFile(fileName, filePath, savePlot, maxAudioLength, reduceNoise=True\n ):\n data, rate = librosa.load(filePath, sr=None)\n if reduceNoise:\n noiseRemovedData ... | [
0,
1,
2,
3
] |
from sklearn.preprocessing import RobustScaler
from statsmodels.tsa.arima.model import ARIMA
from sklearn.metrics import mean_squared_error, r2_score, mean_absolute_error
from math import sqrt
import tensorflow as tf
import pandas as pd
import numpy as np
import os
import random
# set random seed
random.seed(1)
np.ra... | normal | {
"blob_id": "d78ac5188cad104ee1b3e214898c41f843b6d8c0",
"index": 5185,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nrandom.seed(1)\nnp.random.seed(1)\ntf.random.set_random_seed(1)\n<mask token>\nfor i in range(1, 6):\n df = pd.read_csv(random_sample_save_folder_path + \n 'power_demand_sample%... | [
0,
1,
2,
3,
4
] |
from flask_restful import Api, Resource, reqparse
class HelloApiHandler(Resource):
def get(self):
return {
'resultStatus': 'SUCCESS',
'message': "Hello Api Handler"
}
def post(self):
print(self)
parser = reqparse.RequestParser()
parser.add_argument('type', type=str)
parser.ad... | normal | {
"blob_id": "80c3d9165c1b592122fabf6382e265465604989c",
"index": 1450,
"step-1": "<mask token>\n\n\nclass HelloApiHandler(Resource):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass HelloApiHandler(Resource):\n\n def get(self):\n return {'resultStatus': 'SUCCESS', 'message':... | [
1,
2,
3,
4,
5
] |
from game import BaseGame
class First(BaseGame):
key = 'F'
code = 'FIRST'
short_description = 'Vinci se esce 1 o 2. x2.8'
long_description = (
'Si lancia un unico dado, se esce 1 o 2 vinci 2.8 volte quello che hai'
' puntato.')
min_bet = 20
multiplier = 2.8
def has_won(sel... | normal | {
"blob_id": "81fa3129d971fe8296a89a7b772d61ff50a8b9f7",
"index": 9284,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass First(BaseGame):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def has_won(self, draws):\n return dra... | [
0,
2,
3,
4,
5
] |
import speech_recognition as sr
import pyttsx3
import pywhatkit
import datetime
listner = sr.Recognizer()
engine = pyttsx3.init()
#change voices
voices = engine.getProperty('voices')
engine.setProperty('voice',voices[10].id)
rate = engine.getProperty('rate')
engine.setProperty('rate', 150)
#for machine to say
def t... | normal | {
"blob_id": "c4f437e6f5aaeccb6dd0948c3ed1f1d465bb29ce",
"index": 1200,
"step-1": "<mask token>\n\n\ndef talk(text):\n engine.say(text)\n engine.runAndWait()\n\n\ndef takeCommand():\n try:\n with sr.Microphone() as sc:\n print('Listening......')\n vc = listner.listen(sc)\n ... | [
3,
4,
5,
6,
7
] |
from collections import Counter
import pandas as pd
import string
from collections import namedtuple, defaultdict
import csv
import sys
import torch
import numpy as np
from sklearn.preprocessing import LabelEncoder
from scipy.sparse import coo_matrix
from tqdm import tqdm
device = torch.device('cuda' if torch.cuda.is_... | normal | {
"blob_id": "613b060ee50b49417342cfa70b36f77d112dcc58",
"index": 2951,
"step-1": "<mask token>\n\n\ndef get_data():\n df = pd.read_csv('./data/filteredCorpus.csv')\n df_filt = df[df['outcome'] == True]\n df_filt = df_filt[df_filt['role'] == 'speaker']\n df_filt = df_filt[df_filt['source'] == 'human']... | [
4,
5,
6,
7,
8
] |
from unittest.case import TestCase
from datetime import datetime
from src.main.domain.Cohort import Cohort
from src.main.domain.Group import Group
from src.main.util.TimeFormatter import TimeFormatter
__author__ = 'continueing'
class CohortTest(TestCase):
def testAnalyzeNewGroups(self):
cohort = Cohort(... | normal | {
"blob_id": "f12bdfc054e62dc244a95daad9682790c880f20d",
"index": 5367,
"step-1": "<mask token>\n\n\nclass CohortTest(TestCase):\n\n def testAnalyzeNewGroups(self):\n cohort = Cohort(aStartDate=TimeFormatter.toDatetime(\n '2014-05-05 00:00:00'), aEndDate=TimeFormatter.toDatetime(\n ... | [
2,
3,
4,
5,
6
] |
import re
pattern1 = r"[:]{2}[A-Z][a-z]{2,}[:]{2}|[\*]{2}[a-zA-Z]{3,}[\*]{2}"
pattern2 = r"([0-9]+)"
data = input()
valid_emojis = re.findall(pattern1, data)
numbers_ascii = re.findall(pattern2, data)
numbers_total = ""
for num in numbers_ascii:
numbers_total += num
cool_threshold = 1
for i in numbers_total:
... | normal | {
"blob_id": "c2201a281ccd0833b0d7d2219d97ce3175fb012b",
"index": 2042,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor num in numbers_ascii:\n numbers_total += num\n<mask token>\nfor i in numbers_total:\n i = int(i)\n cool_threshold *= i\nprint(f'Cool threshold: {cool_threshold}')\n<mask toke... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.test import TestCase
from collections import Counter
import generator.resume_parser as resume_parser
import os
import json
class TestResumeParser(TestCase):
def load_resume(self, resume_name):
path_to_directory = "generator/fixtures/{... | normal | {
"blob_id": "4bbfb35e4b03e2bfd46dd0fe5bfd54fb01ba11df",
"index": 1996,
"step-1": "<mask token>\n\n\nclass TestResumeParser(TestCase):\n <mask token>\n <mask token>\n\n def generate_counter(self, resume_name):\n json_file = self.load_resume(resume_name)\n return self.convert_to_counter(json... | [
10,
22,
24,
25,
26
] |
import os
from google.cloud import bigquery
def csv_loader(data, context):
client = bigquery.Client()
dataset_id = os.environ['DATASET']
dataset_ref = client.dataset(dataset_id)
job_config = bigquery.LoadJobConfig()
job_config.schema = [
bigquery.SchemaField('id'... | normal | {
"blob_id": "01467a4dad3255a99025c347469881a71ffbae7c",
"index": 8179,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef csv_loader(data, context):\n client = bigquery.Client()\n dataset_id = os.environ['DATASET']\n dataset_ref = client.dataset(dataset_id)\n job_config = bigquery.LoadJob... | [
0,
1,
2,
3
] |
# -*- coding: utf-8 -*-
{
'name': 'EDC Analytic Entry',
'depends': [
'stock_account',
'purchase_stock',
'account_accountant',
],
"description": """
""",
'author': "Ejaftech",
'data': [
'views/account_move_view.xml',
],
}
| normal | {
"blob_id": "797e7c1b3e8b41a167bfbedfb6a9449e6426ba22",
"index": 8570,
"step-1": "<mask token>\n",
"step-2": "{'name': 'EDC Analytic Entry', 'depends': ['stock_account',\n 'purchase_stock', 'account_accountant'], 'description': '\\n ',\n 'author': 'Ejaftech', 'data': ['views/account_move_view.xml']}\n"... | [
0,
1,
2
] |
#!/usr/bin/env python
import sys
total = 0
for line in sys.stdin:
edges = [int(x) for x in line.split("x")]
edges.sort()
ribbon = sum(x * 2 for x in edges[:2])
l, w, h = edges
bow = l * w * h
total += bow + ribbon
print(total)
| normal | {
"blob_id": "ed85cb61f4bc8bf758dafb10ffbabf87fb4521d0",
"index": 9281,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor line in sys.stdin:\n edges = [int(x) for x in line.split('x')]\n edges.sort()\n ribbon = sum(x * 2 for x in edges[:2])\n l, w, h = edges\n bow = l * w * h\n total +=... | [
0,
1,
2,
3,
4
] |
import datetime
with open('D:\Documents\PythonDocs\ehmatthes-pcc-f555082\chapter_10\programming.txt') as f_obj:
lines = f_obj.readlines()
m_lines = []
for line in lines:
m_line = line.replace('python', 'C#')
m_lines.append(m_line)
with open('D:\Documents\PythonDocs\ehmatthes-pcc-f555082\chapter_10\prog... | normal | {
"blob_id": "03da813650d56e7ab92885b698d4af3a51176903",
"index": 3878,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open(\n 'D:\\\\Documents\\\\PythonDocs\\\\ehmatthes-pcc-f555082\\\\chapter_10\\\\programming.txt'\n ) as f_obj:\n lines = f_obj.readlines()\n<mask token>\nfor line in lines:... | [
0,
1,
2,
3,
4
] |
'''
Created on 13 Dec 2016
@author: hpcosta
'''
# https://www.hackerrank.com/challenges/backreferences-to-failed-groups
regex = r"^\d{2}(-?)\d{2}\1\d{2}\1\d{2}$" # Do not delete 'r'.
import re
print(str(bool(re.search(regex, raw_input()))).lower())
# Task
#
# You have a test string S.
# Your task is to write... | normal | {
"blob_id": "e884ce5878de75afe93085e2310b4b8d5953963a",
"index": 337,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(str(bool(re.search(regex, raw_input()))).lower())\n",
"step-3": "<mask token>\nregex = '^\\\\d{2}(-?)\\\\d{2}\\\\1\\\\d{2}\\\\1\\\\d{2}$'\n<mask token>\nprint(str(bool(re.search(re... | [
0,
1,
2,
3,
4
] |
# Generated by Django 3.0.1 on 2020-01-11 19:59
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('users', '0004_auto_20191230_2037'),
]
operations = [
migrations.AddField(
model_name='user',
name='cir... | normal | {
"blob_id": "6aa762165dba891a3638d13862019dd342a7e05a",
"index": 7644,
"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 = [('users', '00... | [
0,
1,
2,
3,
4
] |
from django import forms
class photoForm(forms.Form):
iso = forms.ChoiceField(label='ISO', choices=[("100", 100),
("200", 200),
("300", 300),
("400", 400),
... | normal | {
"blob_id": "19b55b2de3d2ed16275cef572e3518fbb2457f84",
"index": 8293,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass photoForm(forms.Form):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass photoForm(forms.Form):\n iso = forms.ChoiceField(label='ISO', choices=[('1... | [
0,
1,
2,
3,
4
] |
#-------------------------------------------------------------------------------
# rtlconverter.py
#
# PyCoRAM RTL Converter
#
# Copyright (C) 2013, Shinya Takamaeda-Yamazaki
# License: Apache 2.0
#-------------------------------------------------------------------------------
import sys
import os
import subprocess
im... | normal | {
"blob_id": "55ffcf5e6120cc07da461e30979dd8a36a599bee",
"index": 8353,
"step-1": "<mask token>\n\n\nclass RtlConverter(object):\n\n def __init__(self, filelist, topmodule='userlogic', include=None,\n define=None, single_clock=False):\n self.filelist = filelist\n self.topmodule = topmodule... | [
7,
8,
9,
10,
11
] |
#!/usr/bin/python2
# -*- coding: UTF-8 -*-
# coding: utf-8
#!/usr/bin/env python
'''
发布轨迹信息
path.x; path.y; c_speed;
'''
import numpy as np
import matplotlib.pyplot as plt
import copy
import math
from cubic_spline import Spline2D
from polynomials import QuarticPolynomial, QuinticPolynomial
import time
import... | normal | {
"blob_id": "4647a7d0996ceeef4f39cf3182ac3944d25cb349",
"index": 8197,
"step-1": "<mask token>\n\n\nclass FrenetPath:\n\n def __init__(self):\n self.t = []\n self.d = []\n self.d_d = []\n self.d_dd = []\n self.d_ddd = []\n self.s = []\n self.s_d = []\n s... | [
20,
21,
24,
25,
27
] |
#--------------------------------------------------------
# File------------project2.py
# Developer-------Paige Weber
# Course----------CS1213-03
# Project---------Project #1
# Due-------------September 26, 2017
#
# This program uses Gregory-Leibniz series to compute
# an approximate value of pi.
#---------------------... | normal | {
"blob_id": "466148395a4141793b5f92c84513fd093876db76",
"index": 9964,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif number_of_terms >= 1:\n add_approximation = 0\n for count in range(1, number_of_terms):\n approximation = (-1) ** (count + 1) / (2 * count - 1)\n add_approximation ... | [
0,
1,
2,
3
] |
from django.contrib.auth.models import User
from django.core import validators
from django.db import models
from django.db.models.signals import post_save
from django.dispatch import receiver
from django.contrib.auth.models import Group
from django.conf import settings
@receiver(post_save, sender=settings.AUTH_USER_... | normal | {
"blob_id": "a139042d0c6fa4941b7149a33b0a48018e9f511b",
"index": 9003,
"step-1": "<mask token>\n\n\nclass Category(models.Model):\n \"\"\"Категории\"\"\"\n name = models.CharField('Категория', max_length=150)\n url = models.SlugField(max_length=160, unique=True)\n\n def __str__(self):\n return... | [
8,
9,
10,
14,
15
] |
from golem import actions
from projects.golem_gui.pages import common
from projects.golem_gui.pages import api
from projects.golem_gui.pages import test_builder_code
description = 'Verify the user can edit test code and save it'
tags = ['smoke']
def setup(data):
common.access_golem(data.env.url, data.env.admin)
... | normal | {
"blob_id": "d4cdc4f1995eab7f01c970b43cb0a3c5ed4a2711",
"index": 3673,
"step-1": "<mask token>\n\n\ndef setup(data):\n common.access_golem(data.env.url, data.env.admin)\n api.project.using_project('test_builder_code')\n data.test = api.test.create_access_test_code(data.project)\n\n\n<mask token>\n",
"... | [
1,
2,
3,
4
] |
from sklearn import svm, metrics, tree
from sklearn.ensemble import AdaBoostClassifier
from sklearn.neighbors import KNeighborsClassifier
import numpy as np
my_data = np.loadtxt('edited_data/dataset_regression_edited.csv',delimiter=',', dtype='str')
training_data = my_data[:, 0:6]
validation_data = my_data[:, 6]
... | normal | {
"blob_id": "3024359710148bfbb15677973555f214b1f878b7",
"index": 1521,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor classifier in classifiers:\n classifier.fit(training_data[:1500], validation_data[:1500])\n expected = validation_data[681:]\n predicted = classifier.predict(training_data[68... | [
0,
1,
2,
3,
4
] |
#GUIcal.py
from tkinter import *
from tkinter import ttk
import math
GUI=Tk()
GUI.title('My Cal Program')
GUI.geometry('500x500')
def calc():
height=v_height.get()
base=v_base.get()#ดึงค่ามาจากv_base
print(f'height is {height}')
print(f'Basal length is {base}')
length= math.isqrt((height*height)+(b... | normal | {
"blob_id": "77d7fb49ed4c3e78b148cd446e9a5c6a0e6fac8b",
"index": 835,
"step-1": "<mask token>\n\n\ndef calc():\n height = v_height.get()\n base = v_base.get()\n print(f'height is {height}')\n print(f'Basal length is {base}')\n length = math.isqrt(height * height + base * base)\n print('Lenght i... | [
1,
2,
3,
4,
5
] |
# -*- coding:utf-8 -*-
import requests
from lxml import etree
import codecs
from transfrom import del_extra
import re
MODIFIED_TEXT = [r'一秒记住.*?。', r'(看书.*?)', r'纯文字.*?问', r'热门.*?>', r'最新章节.*?新',
r'は防§.*?e', r'&.*?>', r'r.*?>', r'c.*?>',
r'复制.*?>', r'字-符.*?>', r'最新最快，无.*?。',
... | normal | {
"blob_id": "7539042b92a5188a11f625cdfc0f341941f751f0",
"index": 6937,
"step-1": "<mask token>\n\n\ndef crawl_urls(u):\n response = requests.get(u, headers=HEADER)\n body = etree.HTML(response.content)\n content_urls = body.xpath('//div[@class=\"box_con\"]/div/dl//dd/a/@href')\n for pk_id, u in enume... | [
4,
5,
6,
7,
8
] |
from yoloPydarknet import pydarknetYOLO
import cv2
import imutils
import time
yolo = pydarknetYOLO(obdata="../darknet/cfg/coco.data", weights="yolov3.weights",
cfg="../darknet/cfg/yolov3.cfg")
video_out = "yolo_output.avi"
start_time = time.time()
if __name__ == "__main__":
VIDEO_IN = cv2.VideoCapture(0)
... | normal | {
"blob_id": "669eb2e898c3a127ae01e0ee3020a3674e5e340d",
"index": 1091,
"step-1": "from yoloPydarknet import pydarknetYOLO\nimport cv2\nimport imutils\nimport time\n\nyolo = pydarknetYOLO(obdata=\"../darknet/cfg/coco.data\", weights=\"yolov3.weights\", \n cfg=\"../darknet/cfg/yolov3.cfg\")\nvideo_out = \"yolo_... | [
0
] |
# Copyright 2018 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
import datetime
import json
import logging
import mock
from parameterized import parameterized
from buildbucket_proto import common_pb2
from buildbucket_pr... | normal | {
"blob_id": "325efe65030ad3488a7fc45c0d4a289eb0b17196",
"index": 1311,
"step-1": "<mask token>\n\n\nclass StepUtilTest(wf_testcase.WaterfallTestCase):\n\n def testGetLowerBoundBuildNumber(self):\n self.assertEqual(5, step_util._GetLowerBoundBuildNumber(5, 100))\n self.assertEqual(50, step_util._... | [
26,
32,
43,
49,
55
] |
import datetime
import matplotlib.pyplot as plt
import numpy as np
import statsmodels.api as sm
import xlrd
from pandas import *
from xlrd import xldate
#since I messed up when first scraping the data, I have the dates and viewcounts in separate files
#need to create a dictionary of 'author-title':[viewcount, date]
... | normal | {
"blob_id": "6ece524c82521b175cc7791e22c8249dd24dc714",
"index": 2281,
"step-1": "import datetime\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport statsmodels.api as sm\nimport xlrd\nfrom pandas import *\nfrom xlrd import xldate\n\n\n#since I messed up when first scraping the data, I have the dates a... | [
0
] |
# Generated by Django 3.0.1 on 2020-02-01 16:38
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('shopUser', '0024_order_contact'),
]
operations = [
migrations.AddField(
model_name='order',
name='location',
... | normal | {
"blob_id": "0a5570ef17efa26ef6317930df616c8326f83314",
"index": 2936,
"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 = [('shopUser', ... | [
0,
1,
2,
3,
4
] |
import requests,cv2,numpy,time,imutils
class imageAnalyzer():
def __init__(self,
roverName="Rover03",
url="http://192.168.1.10:5000/api/",
temp_img_path = "./temp",
):
self.url = url + roverName
self.temp_img_path = ... | normal | {
"blob_id": "7d3264e9a90ebd72439f77983cbf4f9755048a85",
"index": 4300,
"step-1": "<mask token>\n\n\nclass imageAnalyzer:\n <mask token>\n\n def getImage(self, img_number):\n temp = open(self.temp_img_path + str(img_number) + '.jpeg', 'wb')\n img = requests.get(self.url + '/image')\n te... | [
6,
8,
9,
10,
11
] |
#!/usr/bin/python
import socket
import sys
host = '10.211.55.5'
port = 69
try:
s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
except:
print "socket() failed"
sys.exit(1)
filename = "Aa0Aa1Aa2Aa3Aa4Aa5Aa6Aa7Aa8Aa9Ab0Ab1Ab2Ab3Ab4Ab5Ab6Ab7Ab8Ab9Ac0Ac1Ac2Ac3Ac4Ac5Ac6Ac7Ac8Ac9Ad0Ad1Ad2Ad3Ad4Ad5Ad6Ad7... | normal | {
"blob_id": "b318f5d443dbf8e4442707839649149e75653295",
"index": 5917,
"step-1": "#!/usr/bin/python \nimport socket \nimport sys\n\nhost = '10.211.55.5' \nport = 69\ntry:\n s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) \nexcept:\n print \"socket() failed\" \n sys.exit(1)\nfilename = \"Aa0Aa1Aa2Aa... | [
0
] |
class Solution(object):
def findDisappearedNumbers(self, nums):
"""
:type nums: List[int]
:rtype: List[int]
"""
ns = [0]*len(nums)
for i in range(0, len(nums), 1):
ns[nums[i]-1] = 1
ret = []
for j in range(0, len(ns), 1):
... | normal | {
"blob_id": "87504fb88cbbf810ad8bab08bc59284d2cf37cce",
"index": 850,
"step-1": "<mask token>\n\n\nclass Solution(object):\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Solution(object):\n\n def findDisappearedNumbers(self, nums):\n \"\"\"\n :type nums: List[int]\n :rtype: Li... | [
1,
2,
3,
4,
5
] |
import cv2
import numpy as np
import matplotlib
matplotlib.use('agg')
import matplotlib.pyplot as plt
from keras.preprocessing.image import ImageDataGenerator
from keras.models import Sequential
from keras.layers import SeparableConv2D, Conv2D, MaxPooling2D
from keras.layers import BatchNormalization, Activation, Dropo... | normal | {
"blob_id": "e47d6b5d46f2dd84569a2341178b2ea5e074603a",
"index": 7361,
"step-1": "<mask token>\n\n\ndef layer_to_visualize(layer):\n inputs = [K.learning_phase()] + model.inputs\n _convout1_f = K.function(inputs, [layer.output])\n\n def convout1_f(X):\n return _convout1_f([0] + [X])\n convolut... | [
1,
2,
3,
4,
5
] |
#!/usr/bin/python
import os
from subprocess import Popen, PIPE, STDOUT
import time
import re
import telnetlib
from get_sys_info import get_node_list, get_spec_node_list, get_active_tcu, get_ru_list, is_active_ru
g_rg_list = [
'/SGWNetMgr',
'/SS7SGU',
'/MGW_CMRG',
'/MGW_OMURG',
'/Directory',
]
status_dic... | normal | {
"blob_id": "603d904404ace88205a524d8bfbe3e621b65f425",
"index": 8750,
"step-1": "#!/usr/bin/python\nimport os\nfrom subprocess import Popen, PIPE, STDOUT\nimport time\nimport re\nimport telnetlib\nfrom get_sys_info import get_node_list, get_spec_node_list, get_active_tcu, get_ru_list, is_active_ru\ng_rg_list = ... | [
0
] |
# Kai Joseph
# Loop Practice
# Since I worked on my own, I did not have to complete all 25 challenges (with Ms. Healey's permission). I completed a total of 14 challenges.
import sys
import random
''' 1.
Write a for loop that will print out all the integers from 0-4 in ascending order.
'''
if sys.argv[1] == '... | normal | {
"blob_id": "eda8bde048f3d4c4af4bd1c296e4cc02b92eaa17",
"index": 4727,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif sys.argv[1] == '1':\n for x in range(5):\n print(str(x))\n<mask token>\nif sys.argv[1] == '2':\n for x in range(5):\n print(str(4 - x))\n<mask token>\nif sys.argv[1... | [
0,
1,
2,
3
] |
#
# Author:: Noah Kantrowitz <noah@coderanger.net>
#
# Copyright 2014, Noah Kantrowitz
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unles... | normal | {
"blob_id": "a1e563f94044ff7cd7e0e55542bc4ca2db81df28",
"index": 9749,
"step-1": "<mask token>\n\n\nclass TestUnwrap(object):\n\n @pytest.fixture\n def fn(self):\n\n def fn():\n pass\n return fn\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask toke... | [
14,
15,
20,
25,
26
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.