content stringlengths 1 1.04M | input_ids listlengths 1 774k | ratio_char_token float64 0.38 22.9 | token_count int64 1 774k |
|---|---|---|---|
import insightconnect_plugin_runtime
from .schema import IsolateEndpointInput, IsolateEndpointOutput, Input, Output, Component
# Custom imports below
from insightconnect_plugin_runtime.exceptions import PluginException
from time import sleep
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... | 4.357143 | 56 |
#!/usr/bin/env python
try:
import Tkinter as tk # Python 2
except:
import tkinter as tk # Python 3
root = tk.Tk()
# all functions put here
root.mainloop()
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19... | 2.356164 | 73 |
from google.appengine.ext import ndb
from google.appengine.ext import vendor
context = ndb.get_context()
context.set_cache_policy(lambda key: False)
context.set_memcache_policy(lambda key: False)
vendor.add('backend/lib') | [
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import os
import sys
from pathlib import Path
from janus import Queue
import aiofiles
from loguru import logger
from .decorator import producer
if getattr("sys", "frozen", False):
app_path = sys._MEIPASS
else:
app_path = Path(os.path.dirname(os.path.abspath(__file__))).parent
@producer
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import random
def find_shortest(array: list[int]) -> int:
""" Find the shortest element in an array.
find_shortest
=============
The `find_shortest` function takes an array and finds the shortest element
in it.
Parameters
----------
array: list[int]
An array/list of integers
Returns
-------
index: int
Index of the shortest element is in the array
"""
index = 0 # Stores the index of the shortestvalue
# value
shortest = array[index] # Stores the shortest value
for i in range(len(array)):
if array[i] < shortest:
shortest = array[i]
index = i
return index
def selection_sort(array: list[int]) -> list:
""" Sort the given array elements.
selection_sort
=============
The `selection_sort` function takes an array and returns a new array with
sorted elements in ascending manner.
Parameters
----------
array: list[int]
An array/list of integers
Returns
-------
new_array: list[int]
A sorted array/list
"""
new_array = []
for i in range(len(array)):
shortest_index = find_shortest(array) # Finds the shortest value in the
new_array.append(array.pop(shortest_index)) # array, and adds it to the new array
return new_array
if __name__ == '__main__':
array = [random.randint(0, int(random.random() * 100)) for i in range(10)] # Generating an array of random values
print("Array:", array)
sorted_array = selection_sort(array)
print("Sorted array:", sorted_array)
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... | 2.300761 | 788 |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
__author__ = 'Christian Heider Nielsen'
__doc__ = r'''
Created on 17-12-2020
'''
import os
import numpy
import soundfile
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from django.core.files.storage import FileSystemStorage
from less.settings import LESS_ROOT
class LessFileStorage(FileSystemStorage):
"""
Standard file system storage for files handled by django-less.
The default for ``location`` is ``LESS_ROOT``
"""
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# The MIT License (MIT)
# Copyright (c) 2014 Halit Alptekin
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
# EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
# MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
# IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM,
# DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR
# OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE
# OR OTHER DEALINGS IN THE SOFTWARE.
import random
import string
import logging
def random_data(size):
"""
:param size:
:return:
"""
alpha_list = string.ascii_letters + "".join(map(str, range(10)))
return "".join(random.sample(alpha_list, size))
def random_number(size):
"""
:param size:
:return:
"""
return "".join(random.sample(map(str, range(10)), size))
def random_port(*args):
"""
:return:
"""
return random.randint(1, 65536)
def random_tag(*args):
"""
:return:
"""
return random_data(8) + "-" + random_data(4) + "-" + random_data(4) + "-" + random_data(4) + "-" + random_data(12)
def random_ip(*args):
"""
:return:
"""
return ".".join(map(str, (random.randint(0, 255) for _ in range(4))))
def random_headers_from(*args):
"""
:param args:
:return:
"""
return '"{0}" <sip:{1}@{2}>;tag={3}'.format(random_data(10),
random_data(20),
random_data(15),
random_tag())
def random_headers_call_id(*args):
"""
:param args:
:return:
"""
return random_tag(*args)
def random_headers_max_forwards(*args):
"""
:param args:
:return:
"""
return random_data(2)
def random_headers_to(*args):
"""
:param args:
:return:
"""
return '<sip:{0}@{1}>'.format(random_data(20), random_data(15))
def random_headers_via(*args):
"""
:param args:
:return:
"""
return 'SIP/2.0/UDP {0}:{1};branch={2};rport'.format(random_ip(), random_port(), random_tag())
def random_headers_user_agent(*args):
"""
:param args:
:return:
"""
return '{0}'.format(random_data(30))
def random_headers_contact(*args):
"""
:param args:
:return:
"""
return '<sip:{0}@{1}:{2};' \
'transport=UDP>;' \
'q=1.00;' \
'agentid="{3}";' \
'methods="INVITE,NOTIFY,MESSAGE,ACK,BYE,CANCEL";' \
'expires={4}'.format(random_data(20), random_ip(), random_data(20), random_tag(), random_number(2))
def random_headers_invite_cseq(*args):
"""
:param args:
:return:
"""
return '{0} {1}'.format(random_number(1), 'INVITE')
def random_headers_register_cseq(*args):
"""
:param args:
:return:
"""
return '{0} {1}'.format(random_number(1), 'REGISTER')
def print_message_set(msg_set):
"""
:param msg:
:return:
"""
if isinstance(msg_set, set):
for msg in msg_set:
print "# Sip Message: name='{0}', type='{1}'".format(msg.name, msg.msg_type)
elif isinstance(msg_set, list):
for i, msg in enumerate(msg_set):
print "# History {0}: '{1}'".format(i, msg)
else:
logging.getLogger("isip.runtime").error("Variable set is invalid. {0}".format(__file__))
def print_message(msg):
"""
:param msg:
:return:
"""
print "# Info: {0}".format(msg)
def show_sip_message(msg):
"""
:param msg:
:return:
"""
print "###[ SIP ]###"
print " method = {0}".format(msg.message.method)
print " uri = {0}".format(msg.message.uri)
print " version = {0}".format(msg.message.version)
print " headers ="
for header_key, header_value in msg.message.headers.items():
print " {0}: {1}".format(header_key, header_value)
print " body = {0}".format(msg.message.body)
print " data = {0}".format(msg.message.body)
def control_arg(var):
"""
:param var:
:return:
"""
if var.isdigit():
return int(var)
else:
return var
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1... | 2.177461 | 2,316 |
import unittest
from ansiblelint import Runner, RulesCollection
from ansiblelint.rules.UsingBareVariablesIsDeprecatedRule import UsingBareVariablesIsDeprecatedRule
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from logger import LOGGER
import re
import calendar
from datetime import datetime
from contextlib import suppress
import pytz
from config import Config
from youtube_search import YoutubeSearch
from youtube_dl import YoutubeDL
from pyrogram import(
Client,
filters
)
from pyrogram.types import (
InlineKeyboardButton,
InlineKeyboardMarkup
)
from utils import (
delete_messages,
is_admin,
sync_to_db,
is_audio,
chat_filter,
scheduler
)
from pyrogram.types import (
InlineKeyboardButton,
InlineKeyboardMarkup
)
from pyrogram.errors import (
MessageIdInvalid,
MessageNotModified
)
IST = pytz.timezone(Config.TIME_ZONE)
admin_filter=filters.create(is_admin)
@Client.on_message(filters.command(["schedule", f"schedule@{Config.BOT_USERNAME}"]) & chat_filter & admin_filter)
@Client.on_message(filters.command(["slist", f"slist@{Config.BOT_USERNAME}"]) & admin_filter & chat_filter)
@Client.on_message(filters.command(["cancel", f"cancel@{Config.BOT_USERNAME}"]) & admin_filter & chat_filter)
@Client.on_message(filters.command(["cancelall", f"cancelall@{Config.BOT_USERNAME}"]) & admin_filter & chat_filter)
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import time
import zmq
context = zmq.Context()
socket = context.socket(zmq.REQ)
socket.connect("tcp://localhost:5000")
print("Client started")
i = 0
while True:
socket.send_string(f"Current iteration is: {i}")
msg = socket.recv_string()
print("Received message %s" % msg)
time.sleep(1)
i += 1
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import json
import os
import re
import shutil
from string import Template
from ..base import Downloader, Recipe, Configure, Make, MakeInstall
from ..base import TarballRecipe, GnuRecipe, GetVersionMixin
from hardhat.util import run, read_url, Object
from hardhat.urls import Urls
from hardhat.version import Versions, extension_regex
# Unused - trial code
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... | 3.62 | 100 |
from .state_aggregation import *
from .box_discretization import *
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import torch
from torch import nn
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
from overrides import overrides
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from typing import Generator, Dict, Iterable, List
import time
from openpyxl.styles.cell_style import StyleArray
from openpyxl.worksheet.worksheet import Worksheet, Cell
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# Unless explicitly stated otherwise all files in this repository are licensed
# under the Apache License Version 2.0.
# This product includes software developed at Datadog (https://www.datadoghq.com/).
# Copyright 2018 Datadog, Inc.
import pytest
import utils.process
ORIGINAL_SUBPROC_OUTPUT = utils.process.get_subprocess_output
AIX_LPARSTATS_MEMORY = '''
System configuration: lcpu=4 mem=7936MB mpsz=0.00GB iome=7936.00MB iomp=16 ent=0.20
physb hpi hpit pmem iomin iomu iomf iohwm iomaf %entc vcsw
----- ----- ----- ----- ------ ------ ------ ------ ----- ----- -----
0.63 0 0 7.75 46.8 - - - 0 4.1 1249045057
'''
AIX_LPARSTATS_MEMORY_PAGE = '''
System configuration: lcpu=4 mem=7936MB mpsz=0.00GB iome=7936.00MB iomp=16 ent=0.20
physb hpi hpit pmem iomin iomu iomf iohwm iomaf pgcol mpgcol ccol %entc vcsw
----- ----- ----- ----- ------ ------ ------ ------ ----- ------ ------ ---- ----- -----
0.63 0 0 7.75 46.8 23.8 - 23.9 0 0.0 0.0 0.0 4.1 1249055296
'''
AIX_LPARSTATS_MEMORY_ENTITLEMENTS = '''
System configuration: lcpu=4 mem=7936MB mpsz=0.00GB iome=7936.00MB iomp=16 ent=0.20
physb hpi hpit pmem iomin iomu iomf iohwm iomaf %entc vcsw
----- ----- ----- ----- ------ ------ ------ ------ ----- ----- -----
0.64 0 0 7.75 46.8 - - - 0 4.1 1250974887
iompn: iomin iodes iomu iores iohwm iomaf
ent1.txpool 2.12 16.00 2.00 2.12 2.00 0
ent1.rxpool__4 4.00 16.00 3.50 4.00 3.50 0
ent1.rxpool__3 4.00 16.00 2.00 16.00 2.00 0
ent1.rxpool__2 2.50 5.00 2.00 2.50 2.00 0
ent1.rxpool__1 0.84 2.25 0.75 0.84 0.75 0
ent1.rxpool__0 1.59 4.25 1.50 1.59 1.50 0
ent1.phypmem 0.10 0.10 0.09 0.10 0.09 0
ent0.txpool 2.12 16.00 2.00 2.12 2.00 0
ent0.rxpool__4 4.00 16.00 3.50 4.00 3.50 0
ent0.rxpool__3 4.00 16.00 2.00 16.00 2.00 0
ent0.rxpool__2 2.50 5.00 2.00 2.50 2.00 0
ent0.rxpool__1 0.84 2.25 0.75 0.84 0.75 0
ent0.rxpool__0 1.59 4.25 1.50 1.59 1.50 0
ent0.phypmem 0.10 0.10 0.09 0.10 0.09 0
vscsi0 16.50 16.50 0.13 16.50 0.18 0
sys0 0.00 0.00 0.00 0.00 0.00 0
'''
AIX_LPARSTATS_HYPERVISOR = '''
System configuration: type=Shared mode=Uncapped smt=On lcpu=4 mem=7936MB psize=16 ent=0.20
Detailed information on Hypervisor Calls
Hypervisor Number of %Total Time %Hypervisor Avg Call Max Call
Call Calls Spent Time Spent Time(ns) Time(ns)
remove 15 0.0 0.4 1218 1781
read 0 0.0 0.0 0 0
nclear_mod 0 0.0 0.0 0 0
page_init 316 0.0 9.7 1452 6843
clear_ref 0 0.0 0.0 0 0
protect 0 0.0 0.0 0 0
put_tce 0 0.0 0.0 0 0
h_put_tce_indirect 0 0.0 0.0 0 0
xirr 75 0.1 0.5 1823 10062
eoi 73 0.0 0.3 1032 4437
ipi 0 0.0 0.0 0 0
cppr 40 0.0 0.1 690 3375
asr 0 0.0 0.0 0 0
others 91 0.1 1.2 3294 33906
cede 354 11.9 95.1 67328 39936500
enter 72 0.0 0.2 695 2531
migrate_dma 0 0.0 0.0 0 0
put_rtce 0 0.0 0.0 0 0
confer 0 0.0 0.0 0 0
prod 0 0.0 0.0 0 3843
get_ppp 7 0.2 1.2 43901 107937
set_ppp 0 0.0 0.0 0 0
purr 0 0.0 0.0 0 0
pic 7 0.0 0.0 517 3125
bulk_remove 0 0.0 0.0 0 5187
send_crq 1 0.0 0.0 8593 8593
copy_rdma 0 0.0 0.0 0 0
get_tce 0 0.0 0.0 0 0
send_logical_lan 9 0.1 0.5 12809 34093
add_logical_lan_buf 81 0.1 0.7 2307 7625
h_remove_rtce 0 0.0 0.0 0 0
h_ipoll 20 0.0 0.0 459 2062
h_stuff_tce 0 0.0 0.0 0 0
h_get_mpp 0 0.0 0.0 0 0
h_get_mpp_x 0 0.0 0.0 0 0
h_get_em_parms 8 0.0 0.0 625 1656
h_vpm_pstat 0 0.0 0.0 0 0
h_hfi_start_interface 0 0.0 0.0 0 0
h_hfi_stop_interface 0 0.0 0.0 0 0
h_hfi_query_interface 0 0.0 0.0 0 0
h_hfi_query_window 0 0.0 0.0 0 0
h_hfi_open_window 0 0.0 0.0 0 0
h_hfi_close_window 0 0.0 0.0 0 0
h_hfi_dump_info 0 0.0 0.0 0 0
h_hfi_adapter_attach 0 0.0 0.0 0 0
h_hfi_modify_rcxt 0 0.0 0.0 0 0
h_hfi_route_info 0 0.0 0.0 0 0
h_cau_write_index 0 0.0 0.0 0 0
h_cau_read_index 0 0.0 0.0 0 0
h_nmmu_start 0 0.0 0.0 0 0
h_nmmu_stop 0 0.0 0.0 0 0
h_nmmu_allocate_resource 0 0.0 0.0 0 0
h_nmmu_free_resource 0 0.0 0.0 0 0
h_nmmu_modify_resource 0 0.0 0.0 0 0
h_confer_adjunct 0 0.0 0.0 0 0
h_adjunct_mode 0 0.0 0.0 0 0
h_get_ppp_x 0 0.0 0.0 0 0
h_cop_op 0 0.0 0.0 0 0
h_stop_cop_op 0 0.0 0.0 0 0
h_random 0 0.0 0.0 0 0
h_enter_decomp 0 0.0 0.0 0 0
h_remove_comp 0 0.0 0.0 0 0
h_xirr_x 0 0.0 0.0 0 0
h_get_perf_info 0 0.0 0.0 0 0
h_block_remove 0 0.0 0.0 0 0
--------------------------------------------------------------------------------
'''
AIX_LPARSTATS_SPURR = '''
System configuration: type=Shared mode=Uncapped smt=On lcpu=4 mem=7936MB ent=0.20 Power=Disabled
Physical Processor Utilisation:
--------Actual-------- ------Normalised------
user sys wait idle freq user sys wait idle
---- ---- ---- ---- --------- ---- ---- ---- ----
0.008 0.012 0.000 0.180 3.6GHz[100%] 0.008 0.012 0.000 0.180
'''
OUTPUT_MAP = {
' '.join(['lparstat', '-m', '1', '1']): AIX_LPARSTATS_MEMORY,
' '.join(['lparstat', '-m', '-pw', '1', '1']): AIX_LPARSTATS_MEMORY_PAGE,
' '.join(['lparstat', '-H', '1', '1']): AIX_LPARSTATS_HYPERVISOR,
' '.join(['lparstat', '-m', '-eR', '1', '1']): AIX_LPARSTATS_MEMORY_ENTITLEMENTS,
' '.join(['lparstat', '-E', '1', '1']): AIX_LPARSTATS_SPURR,
}
@pytest.fixture(scope="module",)
| [
2,
17486,
11777,
5081,
4306,
477,
3696,
287,
428,
16099,
389,
11971,
198,
2,
739,
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24843,
13789,
10628,
362,
13,
15,
13,
198,
2,
770,
1720,
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4166,
379,
16092,
324,
519,
357,
5450,
1378,
2503,
13,
19608,
4533,
456,
80,... | 1.384072 | 6,793 |
# -*- encoding: utf-8 -*-
import errno
import os
import shlex
import subprocess
# Root of the Git repository
ROOT = subprocess.check_output([
'git', 'rev-parse', '--show-toplevel']).decode('ascii').strip()
# Hash of the current commit
CURRENT_COMMIT = subprocess.check_output([
'git', 'rev-parse', 'HEAD']).decode('ascii').strip()
def write_release_id(project, release_id):
"""
Write a release ID to the .releases directory in the root of the repo.
"""
releases_dir = os.path.join(ROOT, '.releases')
os.makedirs(releases_dir, exist_ok=True)
release_file = os.path.join(releases_dir, project)
with open(release_file, 'w') as f:
f.write(release_id)
def compare_zip_files(zf1, zf2):
"""Return True/False if ``zf1`` and ``zf2`` have the same contents.
This ignores file metadata (e.g. creation time), and just looks at
filenames and CRC-32 checksums.
This requires zipcmp to be available.
"""
try:
subprocess.check_call(['zipcmp', '-q', zf1, zf2])
except subprocess.CalledProcessError:
return False
else:
return True
| [
2,
532,
9,
12,
21004,
25,
3384,
69,
12,
23,
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9,
12,
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3919,
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628,
198,
2,
20410,
286,
262,
15151,
16099,
198,
13252,
2394,
796,
850,
14681,
... | 2.56621 | 438 |
import warnings
from typing import Any
import numpy as np
from ..utils import message_to_binary, binary_to_message, rgb_to_gray, conv2d
__all__ = ["SobelLSB"]
class SobelLSB():
"""Edge-based LSB embedding using Sobel kernel, idea described in:
`"Edge-based image steganography", Saiful Islam, Mangat R Modi and Phalguni Gupta`
""" | [
11748,
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20500,
11,
46140,
62,
1462,
62,
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11,
3063,
17,
67,
628,... | 2.941176 | 119 |
from django.db import models
# Create your models here.
| [
6738,
42625,
14208,
13,
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1330,
4981,
198,
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2,
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] | 3.5625 | 16 |
import os
import random
import re
import requests
import discord
from discord.ext import commands
from cogs.arkhamdb import Arkhamdb
from cogs.dice import Dice
from cogs.bag import Bag
from cogs.blob import Blob
from cogs.funko import Funko
from cogs.marvelcdb import Marvelcdb
from dotenv import load_dotenv
load_dotenv()
token = os.getenv('DISCORD_TOKEN')
client = discord.Client()
bot = commands.Bot(command_prefix='!')
@bot.event
bot.add_cog(Arkhamdb(bot))
bot.add_cog(Dice(bot))
bot.add_cog(Bag(bot))
bot.add_cog(Blob(bot))
bot.add_cog(Funko(bot))
bot.add_cog(Marvelcdb(bot))
bot.run(token)
| [
11748,
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1330,
29486,
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6738,
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67,
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... | 2.576923 | 234 |
from torch.distributions import Categorical
import gym
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
gamma = 0.99
if __name__ == '__main__':
main()
| [
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28034,
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2... | 2.852941 | 68 |
gen = silly_generator()
for item in gen:
print(item)
# #Python
# #Rocks
# #So do you! | [
5235,
796,
14397,
62,
8612,
1352,
3419,
201,
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201,
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2,
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201,
198,
2,
1303,
2396... | 2.083333 | 48 |
# -*- coding: utf-8 -*-
import os,sys,shutil
import zipfile,glob,subprocess
import traceback
try:
option = {
"stdout":subprocess.PIPE,
"stderr":subprocess.PIPE
}
cwd = os.path.abspath(os.path.dirname(__file__))
print "c",cwd,__file__
if len(cwd) == 0:
cwd = "."
sys.path.append(myjoin(cwd,"..","Engine"))
from android_compile import compile_run
from android_compile import orientation_portrait
from android_compile import orientation_landscape
dist_root = myjoin(cwd,"pini_distribute")
pini_root = myjoin(cwd,"pini")
updator_root = myjoin(cwd,"updator")
if sys.platform == "darwin" :
pass
else:
os.chdir(cwd)
if os.path.exists(dist_root) :
shutil.rmtree(dist_root)
os.chdir(pini_root)
proc = subprocess.Popen(["python","setup.py","py2exe"],**option)
out, err = proc.communicate()
errcode = proc.returncode
print out,err,errcode
shutil.move(myjoin(os.curdir,"dist"), dist_root )
shutil.rmtree(myjoin(os.curdir,"build"))
shutil.copyfile(myjoin(os.curdir,"atl.so"),myjoin(dist_root,"atl.so"))
shutil.copyfile(myjoin(os.curdir,"compiler.py"),myjoin(dist_root,"compiler.py"))
shutil.copyfile(myjoin(os.curdir,"libgcc_s_dw2-1.dll"),myjoin(dist_root,"libgcc_s_dw2-1.dll"))
shutil.copyfile(myjoin(os.curdir,"libstdc++-6.dll"),myjoin(dist_root,"libstdc++-6.dll"))
shutil.copytree(myjoin(os.curdir,"resource"),myjoin(dist_root,"resource"))
shutil.copytree(myjoin(os.curdir,"imageformats"),myjoin(dist_root,"imageformats"))
shutil.copytree(myjoin(os.pardir,os.pardir,"Engine","VisNovel","src"), myjoin(dist_root,"lua"))
shutil.copytree(myjoin(os.pardir,os.pardir,"Engine","window64"), myjoin(dist_root,"window"))
try:
shutil.rmtree(myjoin(dist_root,"window","src"))
except Exception, e:
pass
try:
shutil.rmtree(myjoin(dist_root,"window","res"))
except Exception, e:
pass
shutil.copytree(myjoin(os.pardir,os.pardir,"Engine","VisNovel","src"),myjoin(dist_root,"window","src"))
shutil.copytree(myjoin(os.pardir,os.pardir,"Engine","VisNovel","res"),myjoin(dist_root,"window","res"))
# launcher lua compile - dist_root+"\\window\\src"
# launcher_lua = myjoin(dist_root,"window","src")
# luaCompileWithCocos("launcher",launcher_lua)
### tool lua compile - dist_root+"\\lua"
# tool_lua = myjoin(dist_root,"lua")
# luaCompileWithLuac("tool",tool_lua)
### cocos lua remove
# for root, dirs, files in os.walk(myjoin(dist_root,"window","src"), topdown=False):
# for name in files:
# path = os.path.join(root, name).replace("\\","/")
# p,ext= os.path.splitext(path)
# if ext == ".lua" :
# print "remove plain-lua ",path
# os.remove(path)
#################################################################
### android compile
orientation_portrait()
compile_run(False,True,False,"-portrait.apk")
orientation_landscape()
compile_run(False,True,False,"-landscape.apk",True)
#################################################################
apkdistpath = myjoin(dist_root,"resource","android")
try:
shutil.rmtree(apkdistpath)
except Exception, e:
pass
os.mkdir(apkdistpath)
srcapk1 = myjoin(dist_root,"..","..","Engine","android","PiniRemote-portrait.apk")
srcapk2 = myjoin(dist_root,"..","..","Engine","android","PiniRemote-landscape.apk")
distapk1= myjoin(apkdistpath,"PiniRemote-portrait.apk")
distapk2= myjoin(apkdistpath,"PiniRemote-landscape.apk")
shutil.copy(srcapk1,distapk1)
shutil.copy(srcapk2,distapk2)
distapk1 = myjoin(dist_root,"..","pini","resource","android","PiniRemote-portrait.apk")
distapk2 = myjoin(dist_root,"..","pini","resource","android","PiniRemote-landscape.apk")
try:
os.remove(distapk1)
except Exception, e:
pass
try:
os.remove(distapk2)
except Exception, e:
pass
shutil.copy(srcapk1,distapk1)
shutil.copy(srcapk2,distapk2)
#################################################################
os.chdir(updator_root)
proc = subprocess.Popen(["python","setup.py","py2exe"],**option)
out, err = proc.communicate()
errcode = proc.returncode
print out,err,errcode
os.chdir(myjoin(updator_root,"dist"))
#myjoin(os.pardir,os.pardir,"novel","VisNovel","src")
if os.path.exists(myjoin(os.curdir,"resource")) :
shutil.rmtree(myjoin(os.curdir,"resource"))
if os.path.exists(myjoin(os.curdir,"pygit2")) :
shutil.rmtree(myjoin(os.curdir,"pygit2"))
shutil.copytree(myjoin(os.pardir,"resource"),myjoin(os.curdir,"resource"))
shutil.copytree(myjoin(os.pardir,"pygit2"), myjoin(os.curdir,"pygit2"))
'''
_zip = zipfile.ZipFile(myjoin(os.pardir,os.pardir,"pini_launcher.zip"), 'w')
for root, dirs, files in os.walk(os.curdir, topdown=False):
for name in files:
path = os.path.join(root, name).replace("\\","/")
_zip.write(path)
_zip.close()
'''
os.chdir(updator_root)
#shutil.rmtree(myjoin(os.curdir,"dist"))
nsisMaster = myjoin(os.curdir,"nsis","Master")
if os.path.isdir(nsisMaster) :
shutil.rmtree(nsisMaster)
shutil.move(myjoin(os.curdir,"dist"),nsisMaster)
shutil.rmtree(myjoin(os.curdir,"build"))
shutil.copyfile("nsis/Master/Updator.exe","../Updator.exe")
os.rename("nsis/Master/Updator.exe",u("nsis/Master/piniengine.exe"))
shutil.copytree("../pini/imageformats","nsis/Master/imageformats")
os.system("makensis.exe nsis\\Master.nsi")
try:
os.remove("../PiniInstaller.exe")
except Exception, e:
pass
os.rename("nsis/installer.exe","../PiniInstaller.exe")
shutil.rmtree(nsisMaster)
except Exception, e:
print e
traceback.print_exc()
| [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
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11,
17597,
11,
1477,
22602,
198,
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19974,
7753,
11,
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11,
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14681,
198,
11748,
12854,
1891,
198,
198,
28311,
25,
198,
197,
18076,
796,
13... | 2.365188 | 2,344 |
from rollout import connect
from .util import get_service_name
import os
from collections import defaultdict
import subprocess as sub
from slackclient import SlackClient
| [
6738,
38180,
1330,
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764,
22602,
1330,
651,
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28686,
198,
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1330,
4277,
11600,
198,
11748,
850,
14681,
355,
850,
198,
6738,
30740,
16366,
1330,
36256,
11792,
628,
628,
198
] | 4.461538 | 39 |
from .app import app
# production specific config
app.config['DEBUG'] = False
| [
6738,
764,
1324,
1330,
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198,
198,
2,
3227,
2176,
4566,
198,
1324,
13,
11250,
17816,
30531,
20520,
796,
10352,
198
] | 3.761905 | 21 |
"""The project's utilities.
This module provides utility functions that don't fit any other module.
"""
from typing import List
def load_board_state(path_to_file: str) -> List[List[int]]:
"""Loads the initial board state from file.
Args:
path_to_file: A path to the file, preferably constructed with
os.path.join().
Returns:
A list of lists representing the board in a 2D space.
"""
with open(path_to_file) as raw_data:
read_data = raw_data.read().splitlines()
state = []
for row in read_data:
state.append([int(cell) for cell in row])
return state
| [
37811,
464,
1628,
338,
20081,
13,
198,
198,
1212,
8265,
3769,
10361,
5499,
326,
836,
470,
4197,
597,
584,
8265,
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198,
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628,
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4299,
3440,
62,
3526,
62,
5219,
7,
6978,
62,
1462,
62,
7753... | 2.623482 | 247 |
import unknownpasta
import numpy as np
import matplotlib.pyplot as plt
# call lucs_tools.formatting.joyful.joy_text to plot the string
# lucs_tools.formatting.joyful.text(
# input_string,
# 90,
# fontsize=5.5,
# weight='light',
# factor=3.,
# write_lines=True,
# )
# text = """it was a good run. A new coach to soccer that coaching rec ed would realize if you're down 3-0 in the first 25 mins of the game, you need to change your strategy. Scolari and the rest of the coaching staff including perreira will never be apart of the brasilian futbol federation again. There were so many players to choose. He chose jo and fred one of the two most lazy ass strikers to be his "offense". Then I realize that pato is 24 why not play him. How about fabiano or even coutinho or damiao. It's crazy, he made a team centered around neymar. Kaka ronaldinho or robinho should of made the team. Congrats on germany, if argentina goes to the final they better not fuck up man. Because that will be a nightmare if the argentines win in brasil. GO NEUR AND SHURLLE"""
# unknownpasta.joyful.text(text)
# standard joy division cover recreation, with multiple modes:
# ax1 = lucs_tools.formatting.joyful.lines(90, 60, size=(400,600), title='standard', mode='normal')
# ax2 = lucs_tools.formatting.joyful.lines(90, 60, size=(400,600), title='standard', mode='normal')
# # bright mode
# lucs_tools.formatting.joyful.lines(90, 60, size=(400,600), title='bright-peaks', mode='bright')
# # transparent landscape mode
# lucs_tools.formatting.joyful.lines(90, 60, size=(400,600), title='transparent_mode', mode='transparent')
# # ... inverted switch
# lucs_tools.formatting.joyful.lines(30, 50, size=(400,500), title='inverted :-0', inverted=True)
# # a bizzare combo
unknownpasta.joyful.lines(90, 1000, size=(400,600), title='weird', linewidth=0.1, inverted=True, mode='bright')
# lucs_tools.formatting.joyful.joy_text_new(text, size=(500,600), spacing=4., fontsize=9., write_lines=False, weight='normal')
# ascii formatting; returns a loooong string you can view, from an original seed string (cuts/loops if needed)
# text = """it was a good run. A new coach to soccer that coaching rec ed would realize if you're down 3-0 in the first 25 mins of the game, you need to change your strategy. Scolari and the rest of the coaching staff including perreira will never be apart of the brasilian futbol federation again. There were so many players to choose. He chose jo and fred one of the two most lazy ass strikers to be his "offense". Then I realize that pato is 24 why not play him. How about fabiano or even coutinho or damiao. It's crazy, he made a team centered around neymar. Kaka ronaldinho or robinho should of made the team. Congrats on germany, if argentina goes to the final they better not fuck up man. Because that will be a nightmare if the argentines win in brasil. GO NEUR AND SHURLLE"""
# print(lucs_tools.formatting.joyful.ascii(text, 300, 60, 0, 2))
| [
11748,
6439,
30119,
64,
201,
198,
11748,
299,
32152,
355,
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201,
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11748,
2603,
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8019,
13,
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17115,
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62,
31391,
13,
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889,
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2633,
913,
13,
2633,
62,
5239,... | 3.153766 | 956 |
# -*- coding: utf-8 -*-
import os
from setuptools import find_packages, setup
from allauth_cas import __version__
BASE_DIR = os.path.dirname(__file__)
with open(os.path.join(BASE_DIR, 'README.rst')) as readme:
README = readme.read()
setup(
name='django-allauth-cas',
version=__version__,
description='CAS support for django-allauth.',
author='Aurélien Delobelle',
author_email='aurelien.delobelle@gmail.com',
keywords='django allauth cas authentication',
long_description=README,
url='https://github.com/aureplop/django-allauth-cas',
classifiers=[
'Development Status :: 4 - Beta',
'Environment :: Web Environment',
'Framework :: Django',
'Framework :: Django :: 1.8',
'Framework :: Django :: 1.9',
'Framework :: Django :: 1.10',
'Framework :: Django :: 1.11',
'Framework :: Django :: 2.0',
'Framework :: Django :: 4.0',
'Intended Audience :: Developers',
'License :: OSI Approved :: MIT License',
'Operating System :: OS Independent',
'Programming Language :: Python',
'Programming Language :: Python :: 2',
'Programming Language :: Python :: 2.7',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3.4',
'Programming Language :: Python :: 3.5',
'Programming Language :: Python :: 3.6',
'Programming Language :: Python :: 3.7',
'Programming Language :: Python :: 3.8',
'Programming Language :: Python :: 3.9',
'Topic :: Internet :: WWW/HTTP',
],
license='MIT',
packages=find_packages(exclude=['tests']),
include_package_data=True,
install_requires=[
'django-allauth',
'python-cas',
'six',
],
extras_require={
'docs': ['sphinx'],
'tests': ['tox'],
},
)
| [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
11748,
28686,
198,
198,
6738,
900,
37623,
10141,
1330,
1064,
62,
43789,
11,
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198,
198,
6738,
477,
18439,
62,
34004,
1330,
11593,
9641,
834,
198,
198,
33,
11159,
62,... | 2.407692 | 780 |
from pwnypack.shellcode.arm import ARM
from pwnypack.target import Target
__all__ = ['ARMThumb']
class ARMThumb(ARM):
"""
Environment that targets a generic, unrestricted ARM architecture using
the Thumb instruction set.
"""
| [
6738,
279,
675,
4464,
441,
13,
29149,
8189,
13,
1670,
1330,
20359,
198,
6738,
279,
675,
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441,
13,
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1330,
12744,
628,
198,
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439,
834,
796,
37250,
33456,
817,
2178,
20520,
628,
198,
4871,
20359,
817,
2178,
7,
33456,
2599,... | 3.181818 | 77 |
#!/usr/bin/python3
# ******************************************************************************
# Copyright (c) Huawei Technologies Co., Ltd. 2021-2021. All rights reserved.
# licensed under the Mulan PSL v2.
# You can use this software according to the terms and conditions of the Mulan PSL v2.
# You may obtain a copy of Mulan PSL v2 at:
# http://license.coscl.org.cn/MulanPSL2
# THIS SOFTWARE IS PROVIDED ON AN 'AS IS' BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT, MERCHANTABILITY OR FIT FOR A PARTICULAR
# PURPOSE.
# See the Mulan PSL v2 for more details.
# ******************************************************************************/
"""
Time:
Author:
Description: default config of diagnose executor
"""
consumer = {
"KAFKA_SERVER_LIST": "90.90.64.64:9092",
"GROUP_ID": "DiagGroup",
"ENABLE_AUTO_COMMIT": "False",
"AUTO_OFFSET_RESET": "earliest",
"TIMEOUT_MS": "5",
"MAX_RECORDS": "3"
}
topic = {
"NAME": "DIAGNOSE_EXECUTE_REQ"
}
| [
2,
48443,
14629,
14,
8800,
14,
29412,
18,
198,
2,
41906,
17174,
46068,
1174,
198,
2,
15069,
357,
66,
8,
43208,
21852,
1766,
1539,
12052,
13,
33448,
12,
1238,
2481,
13,
1439,
2489,
10395,
13,
198,
2,
11971,
739,
262,
17996,
272,
6599... | 2.977208 | 351 |
'''
* Copyright 2018 Canaan Inc.
*
* 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
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
'''
import math
import tensor_list_to_layer_list
import numpy as np
| [
7061,
6,
198,
1635,
15069,
2864,
47047,
3457,
13,
198,
1635,
198,
1635,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
198,
1635,
345,
743,
407,
779,
428,
2393,
2845,
287,
11846,
351,
262,
13789,
... | 3.677596 | 183 |
#! /usr/bin/env python3
import sys
from time import sleep
import csv
import numpy as np
import subprocess
from pprint import pprint
#PATH = os.environ['HOME'] + '/Dropbox/big.Little_optimal_frequencies/data/'
main()
| [
2,
0,
1220,
14629,
14,
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14,
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21015,
18,
198,
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269,
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198,
11748,
850,
14681,
198,
6738,
279,
4798,
1330,
279,
4798,
628,
198... | 2.884615 | 78 |
import numpy as np
import pytest
from numpy.testing import assert_allclose
from mutis.correlation import Correlation
from mutis.signal import Signal
@pytest.fixture
| [
11748,
299,
32152,
355,
45941,
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12972,
9288,
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49501,
1330,
2744,
49501,
198,
6738,
4517,
271,
13,
12683,
282,
1330,
26484,
628... | 3.365385 | 52 |
from flexget import plugin
from flexget.event import event
from flexget.utils import qualities
from flexget.utils.qualities import QualityComponent
from loguru import logger
from typing import List
logger = logger.bind(name="traits")
class Traits:
"""
Override FlexGet's built-in quality requirement types with new ones.
Example:
traits:
audio:
opus:
value: 25
regexp: opus(?:[1-7]\\.[01])?
"""
schema = {
"type": "object",
"properties": {
"audio": {"$ref": "#/$defs/qualities"},
"codec": {"$ref": "#/$defs/qualities"},
"color_range": {"$ref": "#/$defs/qualities"},
"resolution": {"$ref": "#/$defs/qualities"},
"source": {"$ref": "#/$defs/qualities"},
},
"additionalProperties": False,
"$defs": {
"qualities": {
"type": "object",
"minProperties": 1,
"additionalProperties": {
"type": "object",
"properties": {
"value": {"type": "integer"},
"regexp": {"type": "string"},
"modifier": {"type": "integer"},
},
"required": ["value"],
"additionalProperties": False,
},
},
},
}
on_task_abort = on_task_exit
@event("plugin.register")
| [
6738,
7059,
1136,
1330,
13877,
198,
6738,
7059,
1136,
13,
15596,
1330,
1785,
198,
6738,
7059,
1136,
13,
26791,
1330,
14482,
198,
6738,
7059,
1136,
13,
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13,
13255,
871,
1330,
14156,
21950,
198,
6738,
2604,
14717,
1330,
49706,
198,
... | 1.94702 | 755 |
"""
Demonstrating how to undistort images.
Reads in the given calibration file, parses it, and uses it to undistort the given
image. Then display both the original and undistorted images.
To use:
python undistort.py image calibration_file
"""
import numpy as np
import cv2
import matplotlib.pyplot as plt
import argparse
import re, pdb
from scipy.interpolate import RectBivariateSpline
if __name__ == "__main__":
main()
| [
37811,
198,
35477,
2536,
803,
703,
284,
3318,
396,
419,
4263,
13,
198,
198,
5569,
82,
287,
262,
1813,
36537,
2393,
11,
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274,
340,
11,
290,
3544,
340,
284,
3318,
396,
419,
262,
1813,
198,
9060,
13,
3244,
3359,
1111,
262,
2656,
... | 3.152174 | 138 |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
from pandoc_docx_utils import ExtractBulletList
import panflute as pf
if __name__ == "__main__":
main()
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
18,
198,
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
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87,
62,
26791,
1330,
29677,
33481,
1616,
8053,
198,
11748,
3425,
2704,
1133,
355,
279,... | 2.430769 | 65 |
import os, sys
import os.path as osp
import subprocess
import shutil
from pprint import pprint
# import git
# from git import Repo
frameworks = (
"torch",
"tensorflow",
"mxnet",
"theano",
"keras",
"matlab",
"torch_c"
)
root = "test"
proj = "3D-ResNets-PyTorch"
for (dirpath, dirnames, filenames) in os.walk(root):
break
import json
word_count = {_: 0 for _ in frameworks}
for idx, proj in enumerate(dirnames):
folder = osp.join(root, proj)
w = analyse_one_repo(folder)
pprint(folder)
pprint(w)
for key, value in w.items():
if value == True:
word_count[key] += 1
with open("result.json", "r+") as fp:
json.dumps(word_count, indent=2)
print(word_count)
| [
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13,
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267,
2777,
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346,
198,
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4798,
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4798,
198,
198,
2,
1330,
17606,
198,
2,
422,
17606,
1330,
1432,
78,
198,
198,
19298,... | 2.232143 | 336 |
import threading
import pika
import time
import json
import sys
from pprint import pformat
from Queue import Empty
from ssl import CERT_REQUIRED
from pika import PlainCredentials
from pika import SelectConnection
from pika.adapters.select_connection import SelectPoller
from syncli.config import config
from syncli.logger import logger
class ExternalCredentials(PlainCredentials):
""" The PlainCredential class is extended to work with external rabbitmq
auth mechanism. Here, the rabbitmq-auth-mechanism-ssl plugin than can be
found here http://www.rabbitmq.com/plugins.html#rabbitmq_auth_mechanism_ssl
Rabbitmq's configuration must be adapted as follow :
[
{rabbit, [
{auth_mechanisms, ['EXTERNAL']},
{ssl_listeners, [5671]},
{ssl_options, [{cacertfile,"/etc/rabbitmq/testca/cacert.pem"},
{certfile,"/etc/rabbitmq/server/cert.pem"},
{keyfile,"/etc/rabbitmq/server/key.pem"},
{verify,verify_peer},
{fail_if_no_peer_cert,true}]}
]}
].
"""
TYPE = 'EXTERNAL'
# As mentioned in pika's PlainCredentials class, we need to append the new
# authentication mechanism to VALID_TYPES
pika.credentials.VALID_TYPES.append(ExternalCredentials)
@logger
| [
11748,
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198,
6738,
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1330,
33523,
198,
6738,
264,
6649,
1330,
327,
17395,
62,
2200,
10917,
378... | 2.515686 | 510 |
# Generated by Django 3.1.6 on 2021-02-27 11:58
from django.db import migrations, models
| [
2,
2980,
515,
416,
37770,
513,
13,
16,
13,
21,
319,
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12,
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25,
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198,
6738,
42625,
14208,
13,
9945,
1330,
15720,
602,
11,
4981,
628
] | 2.84375 | 32 |
# -*- coding: utf-8 -*-
import json
import time
import os
from pretty import get_pretty_json
import webbrowser
| [
2,
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9,
12,
19617,
25,
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23,
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9,
12,
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198,
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198,
11748,
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198,
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198,
6738,
2495,
1330,
651,
62,
37784,
62,
17752,
198,
11748,
3992,
40259,
628
] | 3.054054 | 37 |
from datetime import datetime
# current date and time
now = datetime.now()
timestamp = datetime.timestamp(now)
print(type(timestamp))
print("timestamp =", timestamp)
print(datetime.fromtimestamp(timestamp)) | [
198,
6738,
4818,
8079,
1330,
4818,
8079,
198,
198,
2,
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198,
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4818,
8079,
13,
2197,
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198,
198,
16514,
27823,
796,
4818,
8079,
13,
16514,
27823,
7,
2197,
8,
198,
4798,
7,
4906,
7,
16514,
27823,
4008... | 3.149254 | 67 |
# https://leetcode.com/problems/reverse-nodes-in-k-group/
# Given a linked list, reverse the nodes of a linked list k at a time and return
# its modified list.
# k is a positive integer and is less than or equal to the length of the linked
# list. If the number of nodes is not a multiple of k then left-out nodes, in the
# end, should remain as it is.
# You may not alter the values in the list's nodes, only nodes themselves may be
# changed.
################################################################################
# reverse every sub-ListNode of length k
# curr = dummy, move k steps to make curr = tail
# prev -> (head -> ... -> tail) -> next
# prev -> (tail -> ... -> head) -> next
# separate func to reverse (head, tail)
# Definition for singly-linked list.
# class ListNode:
# def __init__(self, val=0, next=None):
# self.val = val
# self.next = next
| [
2,
3740,
1378,
293,
316,
8189,
13,
785,
14,
1676,
22143,
14,
50188,
12,
77,
4147,
12,
259,
12,
74,
12,
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198,
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2,
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1351,
11,
9575,
262,
13760,
286,
257,
6692,
1351,
479,
379,
257,
640,
290,
1441,
198... | 3.357143 | 266 |
import unittest
import os
from copy import deepcopy
from subprocess import CalledProcessError
from shutil import rmtree
from openpaisdk.command_line import Engine
from openpaisdk.utils import run_command
from openpaisdk.utils import OrganizedList as ol
from openpaisdk.job import Job, Namespace, from_file
from typing import Union
| [
11748,
555,
715,
395,
198,
11748,
28686,
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6738,
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6738,
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631,
198,
6738,
1280,
8957,
9409,
74,
13,
21812,
62,
1370,
1330,
7117... | 3.67033 | 91 |
# 1. Import Flask
from flask import Flask,jsonify
import sqlalchemy
from sqlalchemy.ext.automap import automap_base
from sqlalchemy.orm import Session
from sqlalchemy import create_engine, func
import datetime as dt
engine = create_engine("sqlite:///Resources/hawaii.sqlite")
Base = automap_base()
Base.prepare(engine,reflect=True)
measurement = Base.classes.measurement
station = Base.classes.station
session = Session(engine)
app = Flask(__name__)
@app.route("/")
@app.route("/api/v1.0/precipitation")
@app.route("/api/v1.0/stations")
@app.route("/api/v1.0/tobs")
@app.route('/api/v1.0/<start>/<end>')
@app.route('/api/v1.0/<start>')
# 4. Define main behavior
if __name__ == "__main__":
app.run(debug=True)
| [
2,
352,
13,
17267,
46947,
198,
6738,
42903,
1330,
46947,
11,
17752,
1958,
198,
11748,
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282,
26599,
198,
6738,
44161,
282,
26599,
13,
2302,
13,
2306,
296,
499,
1330,
3557,
499,
62,
8692,
198,
6738,
44161,
282,
26599,
13,
579,
133... | 2.594982 | 279 |
import itertools
from enum import Enum
from graph.GraphLoader import DatasetLoader
from graph.GridSearch import GridSearch
| [
11748,
340,
861,
10141,
198,
6738,
33829,
1330,
2039,
388,
198,
198,
6738,
4823,
13,
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17401,
1330,
16092,
292,
316,
17401,
198,
6738,
4823,
13,
41339,
18243,
1330,
24846,
18243,
628
] | 3.90625 | 32 |
# Shifter, Copyright (c) 2015, The Regents of the University of California,
# through Lawrence Berkeley National Laboratory (subject to receipt of any
# required approvals from the U.S. Dept. of Energy). All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# 1. Redistributions of source code must retain the above copyright notice,
# this list of conditions and the following disclaimer.
# 2. Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation
# and/or other materials provided with the distribution.
# 3. Neither the name of the University of California, Lawrence Berkeley
# National Laboratory, U.S. Dept. of Energy nor the names of its
# contributors may be used to endorse or promote products derived from this
# software without specific prior written permission.`
#
# See LICENSE for full text.
import os
import unittest
from nersc_sdn import munge
| [
2,
911,
18171,
11,
15069,
357,
66,
8,
1853,
11,
383,
3310,
658,
286,
262,
2059,
286,
3442,
11,
198,
2,
832,
13914,
14727,
2351,
18643,
357,
32796,
284,
14507,
286,
597,
198,
2,
2672,
45818,
422,
262,
471,
13,
50,
13,
28786,
13,
... | 4.051471 | 272 |
import jax.numpy as jnp
from jax import jit
from onnx_jax.handlers.backend_handler import BackendHandler
from onnx_jax.handlers.handler import onnx_op
from onnx_jax.pb_wrapper import OnnxNode
@onnx_op("MatMul")
| [
11748,
474,
897,
13,
77,
32152,
355,
474,
37659,
198,
6738,
474,
897,
1330,
474,
270,
198,
198,
6738,
319,
77,
87,
62,
73,
897,
13,
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13,
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437,
62,
30281,
1330,
5157,
437,
25060,
198,
6738,
319,
77,
87,
62,
73,
89... | 2.45977 | 87 |
import os
config = {"dev": DevelopmentConfig, "prod": ProductionConfig, "docker": DockerDevConfig}
| [
11748,
28686,
628,
628,
628,
198,
11250,
796,
19779,
7959,
1298,
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11,
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67,
1298,
19174,
16934,
11,
366,
45986,
1298,
25716,
13603,
16934,
92,
198
] | 3.62069 | 29 |
import asyncio
import random
import time
from typing import Any, AsyncIterator
import pytest
from aioredis import Redis
from fakeredis.aioredis import FakeRedis
from pytest_mock import MockerFixture
from src.room_store.memory_room_archive import MemoryRoomArchive
from src.room_store.memory_room_store import MemoryRoomStore, MemoryRoomStorage
from src.room_store.merged_room_store import MergedRoomStore
from src.room_store.redis_room_store import RedisRoomStore, create_redis_room_store
@pytest.fixture(autouse=True)
def disable_sleep(mocker: MockerFixture) -> None:
"""Disable sleep in all tests by default"""
original_sleep = asyncio.sleep
# We don't want to actually sleep for any amount of time, but we do want to
# allow functions to yield the event loop, so convert all sleep calls to sleep(0)
mocker.patch('asyncio.sleep', sleep)
@pytest.fixture(autouse=True)
def fix_monotonic(mocker: MockerFixture) -> None:
"""Time machine does not work with time.monotonic. Use time.time in tests instead"""
mocker.patch('time.monotonic', time.time)
@pytest.fixture(autouse=True)
def fix_random() -> None:
"""Force a consistent seed so there's no randomness in tests"""
random.seed(1)
@pytest.fixture
@pytest.fixture
@pytest.fixture
@pytest.fixture
@pytest.fixture
| [
11748,
30351,
952,
198,
11748,
4738,
198,
11748,
640,
198,
6738,
19720,
1330,
4377,
11,
1081,
13361,
37787,
198,
198,
11748,
12972,
9288,
198,
6738,
257,
72,
1850,
271,
1330,
2297,
271,
198,
6738,
8390,
445,
271,
13,
1872,
1850,
271,
... | 3.050926 | 432 |
# K-Arm Optimization
########################################################################################################################################
### K_Arm_Opt functions load data based on different trigger types, then create an instance of K-Arm scanner and run optimization ###
### It returns the target-victim pair and corresponding pattern, mask and l1 norm of the mask ###
########################################################################################################################################
import torch
from torchvision import transforms
from dataset import CustomDataSet
from torch.utils.data import DataLoader
import torch.nn.functional as F
import numpy as np
from K_Arm_Scanner import *
| [
2,
509,
12,
26560,
30011,
1634,
198,
29113,
29113,
29113,
29113,
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21017,
509,
62,
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62,
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5499,
3440,
1366,
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319,
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11,
788,
2251,
281,
4554,
286,
509,
12,
26560,
27474,
290,
1057,
23989,
220,
... | 4.630952 | 168 |
from gmssl import sm3, func
from binascii import a2b_hex, b2a_hex
sm2p256v1_ecc_table = {
'n': 'FFFFFFFEFFFFFFFFFFFFFFFFFFFFFFFF7203DF6B21C6052B53BBF40939D54123',
'p': 'FFFFFFFEFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF00000000FFFFFFFFFFFFFFFF',
'g': '32c4ae2c1f1981195f9904466a39c9948fe30bbff2660be1715a4589334c74c7' +
'bc3736a2f4f6779c59bdcee36b692153d0a9877cc62a474002df32e52139f0a0',
'a': 'FFFFFFFEFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF00000000FFFFFFFFFFFFFFFC',
'b': '28E9FA9E9D9F5E344D5A9E4BCF6509A7F39789F515AB8F92DDBCBD414D940E93',
}
from flag import FLAG
if __name__ == "__main__":
password = b2a_hex(FLAG)
sk = func.random_hex(len(sm2p256v1_ecc_table['n']))
assert len(sk) >= len(password)
hashed_pwd = sm3.sm3_hash(func.bytes_to_list(password))
cipher = '%064x' % (int(sk, 16) ^ int(password, 16))
client = APAKE(hashed_pwd=hashed_pwd, sk=sk)
pk = client.public_key
kc_str = func.random_hex(len(sm2p256v1_ecc_table['n']))
A = client.send_client(kc_str)
print('A =',A)
print('Hash =', hashed_pwd)
print('PublicKey =', pk)
print('Cipher =', cipher)
B = input('B = ?')
c_prime = input('c_prime = ?')
signature = client.prove_client(password, kc_str, A, B, c_prime)
print('Signature =', signature)
| [
6738,
308,
76,
45163,
1330,
895,
18,
11,
25439,
198,
6738,
9874,
292,
979,
72,
1330,
257,
17,
65,
62,
33095,
11,
275,
17,
64,
62,
33095,
198,
198,
5796,
17,
79,
11645,
85,
16,
62,
68,
535,
62,
11487,
796,
1391,
198,
220,
220,
... | 2.097561 | 615 |
#_*_ coding: utf-8 _*_
my_func(input("이름을 입력하세요 : ")) | [
2,
62,
9,
62,
19617,
25,
3384,
69,
12,
23,
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9,
62,
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7,
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98,
47991,
246,
168,
226,
116,
168,
248,
242,
1058,
366,
4008
] | 1.2 | 45 |
from django import forms
from .models import Procurement
| [
6738,
42625,
14208,
1330,
5107,
198,
6738,
764,
27530,
1330,
31345,
495,
434,
198
] | 4.071429 | 14 |
#
# Copyright (c) nexB Inc. and others. All rights reserved.
# VulnerableCode is a trademark of nexB Inc.
# SPDX-License-Identifier: Apache-2.0
# See http://www.apache.org/licenses/LICENSE-2.0 for the license text.
# See https://github.com/nexB/vulnerablecode for support or download.
# See https://aboutcode.org for more information about nexB OSS projects.
#
import json
import os
from unittest.mock import patch
from vulnerabilities.importers.debian import DebianBasicImprover
from vulnerabilities.importers.debian import DebianImporter
from vulnerabilities.improvers.default import DefaultImprover
from vulnerabilities.tests import util_tests
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
TEST_DATA = os.path.join(BASE_DIR, "test_data")
@patch("vulnerabilities.importers.debian.DebianImporter.get_response")
@patch("vulnerabilities.importers.debian.DebianImporter.get_response")
| [
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2,
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357,
66,
8,
497,
87,
33,
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2,
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33234,
7483,
25,
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12,
1... | 3.218638 | 279 |
from tensorflow.keras.models import load_model
import numpy as np
import cv2
model = load_model('handwriting.model')
#imprimir una imagen con muestra
images = []
# seleccionar muestras aleatorias de los datos
for i in np.random.choice(np.arange(0, len(testY)), size=(64,)):
# hacer las predicciones
probs = model.predict(testX[np.newaxis, i])
prediction = probs.argmax(axis=1)
label = labelNames[prediction[0]]
#extraer imagen correspondiente de los datos
image = (testX[i] * 255).astype("uint8")
color = (0, 255, 0)
# si al prediccion es incorrecta, ponerla en rojo
if prediction[0] != np.argmax(testY[i]):
color = (0, 0, 255)
# agregar prediccion y cambiar tamaño para verlas mejor
image = cv2.merge([image] * 3)
image = cv2.resize(image, (96, 96), interpolation=cv2.INTER_LINEAR)
cv2.putText(image, label, (5, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.75,
color, 2)
# add the image to our list of output images
images.append(image)
# construct the montage for the images
montage = build_montages(images, (96, 96), (8, 8))[0]
# show the output montage
cv2.imshow("OCR Results", montage)
cv2.waitKey(0) | [
6738,
11192,
273,
11125,
13,
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16502,
13,
19849,
11537,
198,
198,
2,
320,
1050,
130... | 2.519101 | 445 |
# -*- coding: utf-8 -*-
from django.apps import AppConfig
| [
2,
532,
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9,
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6738,
42625,
14208,
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1330,
2034,
16934,
628
] | 2.565217 | 23 |
"""Flask configuration."""
import os
VERSION = '0.2'
SECRET_KEY = os.environ.get('SECRET_KEY', 'asdf1234')
SERVER_NAME = os.environ.get('ACCOUNTS_SERVER_NAME')
AWS_ACCESS_KEY_ID = os.environ.get('AWS_ACCESS_KEY_ID', 'nope')
AWS_SECRET_ACCESS_KEY = os.environ.get('AWS_SECRET_ACCESS_KEY', 'nope')
AWS_REGION = os.environ.get('AWS_REGION', 'us-east-1')
LOGFILE = os.environ.get('LOGFILE')
LOGLEVEL = os.environ.get('LOGLEVEL', 20)
REDIS_HOST = os.environ.get('REDIS_HOST', 'localhost')
REDIS_PORT = os.environ.get('REDIS_PORT', '7000')
REDIS_DATABASE = os.environ.get('REDIS_DATABASE', '0')
REDIS_TOKEN = os.environ.get('REDIS_TOKEN', None)
"""This is the token used in the AUTH procedure."""
JWT_SECRET = os.environ.get('JWT_SECRET', 'foosecret')
DEFAULT_LOGIN_REDIRECT_URL = os.environ.get(
'DEFAULT_LOGIN_REDIRECT_URL',
'https://arxiv.org/user'
)
DEFAULT_LOGOUT_REDIRECT_URL = os.environ.get(
'DEFAULT_LOGOUT_REDIRECT_URL',
'https://arxiv.org'
)
AUTH_SESSION_COOKIE_NAME = 'ARXIVNG_SESSION_ID'
AUTH_SESSION_COOKIE_SECURE = bool(int(os.environ.get('AUTH_SESSION_COOKIE_SECURE', '1')))
CLASSIC_COOKIE_NAME = os.environ.get('CLASSIC_COOKIE_NAME', 'tapir_session')
CLASSIC_PERMANENT_COOKIE_NAME = os.environ.get(
'CLASSIC_PERMANENT_COOKIE_NAME',
'tapir_permanent'
)
CLASSIC_TRACKING_COOKIE = os.environ.get('CLASSIC_TRACKING_COOKIE', 'browser')
CLASSIC_COOKIE_TIMEOUT = os.environ.get('CLASSIC_COOKIE_TIMEOUT', '86400')
CLASSIC_TOKEN_RECOVERY_TIMEOUT = os.environ.get(
'CLASSIC_TOKEN_RECOVERY_TIMEOUT',
'86400'
)
CLASSIC_SESSION_HASH = os.environ.get('CLASSIC_SESSION_HASH', 'foosecret')
CLASSIC_SESSION_TIMEOUT = os.environ.get(
'CLASSIC_SESSION_TIMEOUT',
'36000'
)
CLASSIC_DATABASE_URI = os.environ.get('CLASSIC_DATABASE_URI')
"""If not set, legacy database integrations will not be available."""
CAPTCHA_SECRET = os.environ.get('CAPTCHA_SECRET', 'foocaptcha')
"""Used to encrypt captcha answers, so that we don't need to store them."""
CAPTCHA_FONT = os.environ.get('CAPTCHA_FONT', None)
BASE_SERVER = os.environ.get('BASE_SERVER', 'arxiv.org')
URLS = [
("register", "/user/register", BASE_SERVER),
("lost_password", "/user/lost_password", BASE_SERVER),
("login", "/login", BASE_SERVER)
]
CREATE_DB = bool(int(os.environ.get('CREATE_DB', 0)))
RELEASE_NOTES_URL = "https://confluence.cornell.edu/x/wtJyFQ"
RELEASE_NOTES_TEXT = "Accounts v0.2 released 2018-09-05"
| [
37811,
7414,
2093,
8398,
526,
15931,
198,
198,
11748,
28686,
198,
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6,
198,
198,
23683,
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62,
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268,
2268,
13,
1136,
10786,
23683,
26087,
62,
20373,
3256,
705,
292,
7568,
1065,... | 2.293396 | 1,060 |
from .alternatives import Alternative
from .tools import (
str_to_timedelta,
timedelta_from_str,
)
from .helpers import text_in_range
from .speakers import Speaker
from .markers import Marker
from .segments import Segment
from .speakers import Speaker
from pathlib import Path
from datetime import timedelta
import string
import time
import logging
import typing
class Job():
"""Job objects are the foundation of transcriptor. A job holds the markers, segments, speakers, alternatives, and outputs for a transcription"""
def _check_marker_content(self, marker):
"""checks given marker for content otherwise loads segments between the
marker start and end times
"""
if marker.content:
return marker.content
else:
return text_in_range(
self.segments,
start_time=marker.start_time,
end_time=marker.end_time,
)
def _text_from_marker(self) -> typing.Generator:
"""Generate dictionaries of text for each Marker value"""
markers = []
for marker in self.markers:
markers.append({
"start_time": marker.start_time,
"end_time": marker.end_time,
"content": self._check_marker_content(marker),
"speaker": marker.speaker if marker.speaker else '',
})
return markers
| [
6738,
764,
33645,
2929,
1330,
27182,
198,
6738,
764,
31391,
1330,
357,
198,
220,
220,
220,
965,
62,
1462,
62,
16514,
276,
12514,
11,
198,
220,
220,
220,
28805,
12514,
62,
6738,
62,
2536,
11,
198,
8,
198,
6738,
764,
16794,
364,
1330,... | 2.432161 | 597 |
from urllib import request
from PyQt5.QtCore import QThread | [
6738,
2956,
297,
571,
1330,
2581,
198,
198,
6738,
9485,
48,
83,
20,
13,
48,
83,
14055,
1330,
1195,
16818
] | 3 | 20 |
#!/usr/bin/env @PYTHON_EXECUTABLE@
"""
Description: Run a pre-generated Siconos mechanics-IO HDF5 simulation file.
"""
# Lighter imports before command line parsing
from __future__ import print_function
import argparse
parser = argparse.ArgumentParser(
description = __doc__,
epilog = """This script only provides a basic interface for the most common
simulation options. For more complex options, or to specify
behaviour such as controllers, you must create a custom simulation
script. If a partially-completed simulation is found, it will be
continued from the last time step until T.
Note that most example scripts do not use this program, and simply
define and then run the simulation in the same script.""")
parser.add_argument('file', metavar='filename', type=str, nargs=1,
help = 'simulation file (HDF5)')
parser.add_argument('-T', metavar='time', type=float,
help = 'time in seconds to run until (default T=1 second)',
default=1)
parser.add_argument('-p', '--period', metavar='period', type=float,
help = 'time in seconds between frames (default p=5e-3)',
default=5e-3)
parser.add_argument('-e','--every', metavar='interval', type=int,
help = 'output every nth frame (default=1)', default=1)
parser.add_argument('-f','--frequency', metavar='Hz', type=float,
help = 'alternative to -p, specify simulation frequency in Hz'+
' (default=200 Hz)')
parser.add_argument('-V','--version', action='version',
version='@SICONOS_VERSION@')
args = parser.parse_args()
if args.frequency is not None:
args.p = 1.0 / args.frequency
# Heavier imports after command line parsing
from siconos.io.mechanics_run import MechanicsHdf5Runner
# Run the simulation from the inputs previously defined and add
# results to the hdf5 file. The visualisation of the output may be done
# with the vview command.
with MechanicsHdf5Runner(mode='r+',io_filename=args.file[0]) as io:
# By default earth gravity is applied and the units are those
# of the International System of Units.
# Because of fixed collision margins used in the collision detection,
# sizes of small objects may need to be expressed in cm or mm.
io.run(output_frequency=args.every, T=args.T, h=args.period)
| [
2,
48443,
14629,
14,
8800,
14,
24330,
2488,
47,
56,
4221,
1340,
62,
6369,
2943,
3843,
17534,
31,
198,
37811,
198,
11828,
25,
5660,
257,
662,
12,
27568,
311,
4749,
418,
12933,
12,
9399,
5572,
37,
20,
18640,
2393,
13,
198,
37811,
198,... | 2.825677 | 849 |
# Original Version: Taehoon Kim (http://carpedm20.github.io)
# + Source: https://github.com/carpedm20/DCGAN-tensorflow/blob/e30539fb5e20d5a0fed40935853da97e9e55eee8/model.py
# + License: MIT
from __future__ import division
import os
import time
from glob import glob
import tensorflow as tf
import pickle
from six.moves import xrange
from scipy.stats import entropy
from ops import *
from utils import *
| [
2,
13745,
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25,
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3609,
71,
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6502,
357,
4023,
1378,
66,
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276,
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13,
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13,
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8,
198,
2,
220,
220,
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25,
3740,
1378,
12567,
13,
785,
14,
66,
5117,
276,
76,
1238,
14,
9697,
45028,
12,
83,... | 2.77027 | 148 |
import sys
import warnings
if not sys.warnoptions:
warnings.simplefilter("ignore")
import math
from absl import app
import numpy as np
import lib.helper as helper
import lib.ops as ops
import lib.state as state
def make_f(d: int = 3, r: int = 1):
"""Construct function that will return 1 for 'solutions' bits."""
num_inputs = 2**d
answers = np.zeros(num_inputs, dtype=np.int32)
answers[r] = 1
return func
def run_experiment(nbits, r, solutions=1) -> None:
"""Run full experiment for a given flavor of f()."""
# Note that op_zero multiplies the diagonal elements of the operator by -1,
# except for element [0][0] which is for control.
zero_projector = np.zeros((2**nbits, 2**nbits))
zero_projector[0, 0] = 1
op_zero = ops.Operator(zero_projector)
# Make f and Uf
f = make_f(nbits, r)
uf = ops.OracleUf(nbits+1, f)
# Build state with 1 ancilla of |1>.
psi = state.zeros(nbits) * state.ones(1)
for i in range(nbits + 1):
psi.apply1(ops.Hadamard(), i)
# The Grover operator is the combination of:
# - phase inversion via the u unitary
# - inversion about the mean (see matrix above)
hn = ops.Hadamard(nbits)
reflection = op_zero * 2.0 - ops.Identity(nbits)
inversion = hn(reflection(hn)) * ops.Identity()
grover = inversion(uf)
# Number of Grover iterations
iterations = int(math.pi / 4 * math.sqrt(2**nbits / solutions))
for _ in range(iterations):
psi = grover(psi)
# Measurement - pick element with higher probability.
#
# Note: We constructed the Oracle with n+1 qubits, to allow
# for the 'xor-ancillary'. To check the result, we need to
# ignore this ancilla.
# Check Matrix to see if max prob is legit
# print("Probs:", [psi.prob(*bits) for bits in helper.bitprod(psi.nbits)])
maxbits, maxprob = psi.maxprob()
result = f(maxbits[:-1])
print('\n({} qubits) Search result: f(x={}) = {}, want: {}, p: {:6.4f}'
.format(nbits, maxbits[:-1], result, r, maxprob))
if result != 1:
raise AssertionError('something went wrong, measured invalid state')
if __name__ == '__main__':
app.run(main)
| [
11748,
25064,
198,
11748,
14601,
198,
361,
407,
25064,
13,
40539,
25811,
25,
198,
220,
220,
220,
14601,
13,
36439,
24455,
7203,
46430,
4943,
198,
11748,
10688,
198,
6738,
2352,
75,
1330,
598,
198,
11748,
299,
32152,
355,
45941,
198,
198... | 2.72365 | 778 |
from django.apps import AppConfig
| [
6738,
42625,
14208,
13,
18211,
1330,
2034,
16934,
628
] | 3.888889 | 9 |
'''Crie um programa que leia o nome e o preco de varios produtos. O programa devera perguntar se o usuario vai continuar.
No final mostre:
a) Qual é o total gasto na compra
b) Quantos produtos custam mais de R$1000.
c) Qual é o nome do produto mais barato. '''
sair = 'N'
compras = 0
prdcaro = 0
nomeprd = ''
precomenor = 999999
print('-'*50)
print('Mercado Popular')
print('-'*50)
while sair != 'S':
prod = str(input('Digite o nome do produto: ')).strip().upper()
preco = float(input('Digite o valor do produto: '))
while True:
cont = str(input('Continua comprando ? [S/N] ')).strip().upper()
if cont == 'S':
break
else:
sair = 'S'
break
compras += preco
if preco > 1000:
prdcaro += 1
if preco < precomenor:
nomeprd = prod
precomenor = preco
print('='*50)
print(f'O tota de compras foi: {compras}')
print(f'Foi comprado {prdcaro} produro com valor acima de R$1000.')
print(f'O nome do produto mais barato é: {nomeprd}.')
print('='*50)
| [
7061,
6,
34,
5034,
23781,
1430,
64,
8358,
443,
544,
267,
299,
462,
304,
267,
662,
1073,
390,
1401,
4267,
40426,
315,
418,
13,
440,
1430,
64,
390,
332,
64,
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283,
384,
267,
514,
84,
4982,
410,
1872,
11143,
283,
13,
1... | 2.167347 | 490 |
from . import views
from django.conf.urls import url
urlpatterns = [
url(r'', views.HomeView.as_view(), name='home'),
]
| [
6738,
764,
1330,
5009,
198,
6738,
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13,
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6371,
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82,
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685,
198,
220,
220,
220,
220,
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220,
220,
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7,
81,
6,
3256,
5009,
13,
16060,
7680,
13,
292,
62,
1177,
22... | 2.37931 | 58 |
from django.contrib.auth.models import AbstractUser
from django.db import models
from django.db.models.deletion import CASCADE
from django.core.validators import MinValueValidator
from django.core.exceptions import ValidationError
| [
6738,
42625,
14208,
13,
3642,
822,
13,
18439,
13,
27530,
1330,
27741,
12982,
198,
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42625,
14208,
13,
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1330,
4981,
198,
6738,
42625,
14208,
13,
9945,
13,
27530,
13,
2934,
1616,
295,
1330,
35106,
34,
19266,
198,
6738,
42625,
142... | 3.470588 | 68 |
import os
import numpy as np
import csv
import pandas as pd
import sys
try:
import cPickle as pickle
except:
import pickle
import matplotlib.pyplot as plt
import progressbar as pb
import interpolate as ip
| [
11748,
28686,
198,
11748,
299,
32152,
355,
45941,
198,
11748,
269,
21370,
198,
11748,
19798,
292,
355,
279,
67,
198,
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25064,
198,
28311,
25,
198,
220,
220,
1330,
269,
31686,
293,
355,
2298,
293,
198,
16341,
25,
198,
220,
220,
13... | 2.958904 | 73 |
try:
f = open("fruit.txt", "r")
a = int(f.readline())
o = int(f.readline())
g = int(f.readline())
f.close()
except:
a,o,g = 0,0,0
while True:
print("현재 재고는 사과",a,"개, 오렌지",o,"개, 포도",g,"개 입니다.")
S,t = input("변동할 재고와 갯수를 입력해주세요(저장하고 나갈때는 q 0 입력) : ").split()
t = int(t)
if S == 'apple' :
a += t
elif S == 'orange' :
o += t
elif S == 'grape' :
g += t
else:
f = open("fruit.txt", "w")
f.write(str(a))
f.write('\n')
f.write(str(o))
f.write('\n')
f.write(str(g))
f.close()
print('저장 완료')
break
| [
28311,
25,
198,
220,
220,
220,
277,
796,
1280,
7203,
34711,
13,
14116,
1600,
366,
81,
4943,
198,
220,
220,
220,
257,
796,
493,
7,
69,
13,
961,
1370,
28955,
198,
220,
220,
220,
267,
796,
493,
7,
69,
13,
961,
1370,
28955,
198,
220... | 1.333333 | 480 |
"""
Created on Sun Feb 2 13:28:48 2020
@author: matias
"""
import numpy as np
from matplotlib import pyplot as plt
from scipy.interpolate import interp1d
from scipy.constants import c as c_luz #metros/segundos
c_luz_norm = c_luz/1000
import sys
import os
from os.path import join as osjoin
from pc_path import definir_path
path_git, path_datos_global = definir_path()
os.chdir(path_git)
sys.path.append('./Software/Funcionales/')
from funciones_int import integrador
#%%
omega_m = 0.24
b = 0.1
H0 = 73.48
params_fisicos = [omega_m,b,H0]
cantidad_zs = int(10**5)
max_steps = np.linspace(0.01,0.001,100)
Hs = []
for maxs in max_steps:
zs, H_ode = integrador(params_fisicos, n=1, cantidad_zs=cantidad_zs,
max_step=maxs)
#f=interp1d(zs,H_ode)
#Hs.append(f(np.linspace(0,3,100000)))
Hs.append(H_ode)
final = np.zeros(len(Hs))
for j in range(1,len(Hs)):
aux = np.mean(Hs[j]-Hs[j-1]);
#aux = np.mean((1-Hs[j]/Hs[j-1]));
final[j]=aux;
#%%
%matplotlib qt5
plt.close()
plt.figure()
plt.grid(True)
plt.xlabel('Tamaño del paso de integración', fontsize=13)
plt.ylabel('$\Delta$H', fontsize=13)
plt.xticks(fontsize=14)
plt.yticks(fontsize=14)
plt.plot(max_steps[::-1],np.array(final)[::-1],'.-');
plt.gca().invert_xaxis()
#plt.legend(loc='best',prop={'size': 12})
plt.show()
#%%
index=np.where(abs(final)<=float(10**(-10)))[0][1]
max_steps[index+1]
final[index+1]
max_steps
final
#Delta H = 10**(-10)
#Delta h = 10**(-12/13)
| [
37811,
198,
41972,
319,
3825,
3158,
220,
362,
1511,
25,
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25,
2780,
12131,
198,
198,
31,
9800,
25,
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198,
37811,
198,
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299,
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355,
45941,
198,
6738,
2603,
29487,
8019,
1330,
12972,
29487,
355,
458,
83,
19... | 2.064698 | 711 |
import os
diccionario = []
crearArchivo()
cargarArchivo()
menu = True
while menu == True:
os.system("clear")
print "\t\t\t [DICCIONARIO]"
print "\t\t\t -------------\n"
print " 1. AGREGAR AL DICCIONARIO"
print " 2. MOSTRAR DICCIONARIO"
print " 3. BUSCAR EN EL DICCIONARIO"
print " 4. ELIMINAR TERMINO"
print " 5. SALIR\n"
opMenu = raw_input(" Opcion > ")
if opMenu == "1":
os.system("clear")
opAgregar = True
while opAgregar == True:
AgregarAlDicionario()
print
print " (v) Volver al menu"
print " (a) Agregar otro termino"
print " (s) Salir"
print
opcion = raw_input(" Opcion > ")
if opcion == 'v':
opAgregar = False
menu = True
elif opcion == 'a':
opAgregar = True
elif opcion == 's':
print "\n 'Ha salido de la diccionario' \n"
opAgregar = False
menu = False
else:
opAgregar = False
menu = True
if opMenu == "2":
MostrarDicionario()
print
print " (v) Volver al menu"
print " (s) Salir"
print
opcion = raw_input(" Opcion > ")
if opcion == 'v':
opAgregar = False
menu = True
elif opcion == 's':
print "\n 'Ha salido de la diccionario' \n"
opAgregar = False
menu = False
else:
opBuscar = False
menu = True
if opMenu == "3":
os.system("clear")
opBuscar = True
while opBuscar == True:
BuscarEnDiccionario()
print "\n (v) Volver al menu"
print " (b) Buscar otro termino"
print " (s) Salir"
print
opcion = raw_input(" Opcion > ")
if opcion == 'v':
opBuscar = False
menu = True
elif opcion == 'b':
opBuscar = True
elif opcion == 's':
print "\n 'Ha salido de la diccionario' \n"
opBuscar = False
menu = False
else:
break
if opMenu == "4":
# os.system("clear")
opEliminar = True
while opEliminar == True:
EliminarDelDiccionario()
print
print " (v) Volver al menu"
print " (e) Eliminar otro termino"
print " (s) Salir"
print
opcion = raw_input(" Opcion > ")
if opcion == 'v':
opEliminar = False
menu = True
elif opcion == 'e':
opEliminar = True
elif opcion == 's':
print "\n 'Ha salido de la diccionario' \n"
opEliminar = False
menu = False
else:
opEliminar = False
menu = True
if opMenu == "5":
print "\n 'Ha salido de la diccionario' \n"
break
| [
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628,
628,
628,
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283,
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23593,
3419,
198,
66,
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283,
19895,
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198,
198,
26272,
796,
6407,
198,
198,
4514,
6859,
6624,
6407,
25,
198,
220,
... | 1.72927 | 1,821 |
from unittest.mock import Mock
import paramiko
from blocksync.sync import (
_connect_ssh,
_do_create,
_get_block_size,
_get_blocks,
_get_range,
_get_remotedev_size,
_get_size,
_log,
)
| [
6738,
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395,
13,
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198,
198,
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5772,
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198,
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198,
220,
220,
220,
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62,
45824,
11,
198,
220,
220,
220,
4808,
4598,
62,
17953,
11,
198,
220,
... | 2.132075 | 106 |
from argparse import ArgumentParser
import numpy as np
from calculator import computeSurfaceDistance
DefaultPreFilePath = 'data/pre.data'
DefaultPostFilePath = 'data/post.data'
MetersPerPixel = 30
MetersPerHeightValue = 11
if __name__ == '__main__':
exit(main())
| [
6738,
1822,
29572,
1330,
45751,
46677,
198,
11748,
299,
32152,
355,
45941,
198,
6738,
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1330,
24061,
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45767,
198,
198,
19463,
6719,
8979,
15235,
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705,
7890,
14,
3866,
13,
7890,
6,
198,
19463,
6307,
8979,
15235,
796,
... | 3.240964 | 83 |
# -*- coding: utf-8 -*-
import datetime
from south.db import db
from south.v2 import SchemaMigration
from django.db import models
| [
2,
532,
9,
12,
19617,
25,
3384,
69,
12,
23,
532,
9,
12,
198,
11748,
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198,
6738,
5366,
13,
9945,
1330,
20613,
198,
6738,
5366,
13,
85,
17,
1330,
10011,
2611,
44,
4254,
198,
6738,
42625,
14208,
13,
9945,
1330,
4981,
198
] | 2.954545 | 44 |
#! /usr/bin/env python
import sys,os
import time
from Bio import Fasta
DEFAULT_DICT_FILE = '/project1/structure/mliang/pdb/derived_data/pdb_seqres.idx'
DEFAULT_OUTFH = sys.stdout
dict_file = DEFAULT_DICT_FILE
outfh = DEFAULT_OUTFH
start_time = time.time()
fdict = Fasta.Dictionary(dict_file)
elapse_time = time.time() - start_time
print >>sys.stderr, "Time to load dictionary:", elapse_time
start_time = time.time()
chainmap = {}
for key in fdict.keys():
chainmap.setdefault(key[:4],[]).append(key)
elapse_time = time.time() - start_time
print >>sys.stderr, "Time to build chain map:", elapse_time
start_time = time.time()
args = sys.argv[1:]
if not args:
args = sys.stdin
for field in args:
fields = field.strip().split()
for arg in fields:
if arg in chainmap:
for chain in chainmap[arg]:
outfh.write(fdict[chain])
else:
try:
outfh.write(fdict[arg])
except KeyError:
pass
elapse_time = time.time() - start_time
print >>sys.stderr, "Time to lookup entries:", elapse_time
| [
2,
0,
1220,
14629,
14,
8800,
14,
24330,
21015,
198,
198,
11748,
25064,
11,
418,
198,
11748,
640,
198,
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16024,
1330,
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64,
198,
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7206,
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62,
35,
18379,
62,
25664,
796,
31051,
16302,
16,
14,
301,
5620,
14,
4029,
154... | 2.293501 | 477 |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
http://www.zillow.com/browse/homes/
Zillow有一个页面按照层级列出了所有房产的具体地址信息:
State -> County -> Zipcode -> Street -> Address
"""
__version__ = "0.0.1"
__author__ = "Sanhe Hu"
__license__ = "MIT"
__short_description__ = "Zillow Database Crawler" | [
2,
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14,
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2586,
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57,
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... | 1.8 | 160 |
# Generated by Django 2.2 on 2019-04-27 16:33
from django.db import migrations, models
import django.db.models.deletion
| [
2,
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515,
416,
37770,
362,
13,
17,
319,
13130,
12,
3023,
12,
1983,
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198,
198,
6738,
42625,
14208,
13,
9945,
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15720,
602,
11,
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198,
11748,
42625,
14208,
13,
9945,
13,
27530,
13,
2934,
1616,
295,
628
] | 2.904762 | 42 |
# -*- coding: utf8 -*-
# Copyright (c) 2017-2018 THL A29 Limited, a Tencent company. All Rights Reserved.
#
# 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
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import json
from tencentcloud.common.exception.tencent_cloud_sdk_exception import TencentCloudSDKException
from tencentcloud.common.abstract_client import AbstractClient
from tencentcloud.monitor.v20180724 import models
| [
2,
532,
9,
12,
19617,
25,
3384,
69,
23,
532,
9,
12,
198,
2,
15069,
357,
66,
8,
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12,
7908,
2320,
43,
317,
1959,
15302,
11,
257,
9368,
1087,
1664,
13,
1439,
6923,
33876,
13,
198,
2,
198,
2,
49962,
739,
262,
24843,
13789,
11... | 3.6375 | 240 |
"""
Sequence to Sequence models with attention-based copying of input
and/or schema.
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
from pydoc import locate
import tensorflow as tf
from tensorflow.python.ops import math_ops
import numpy as np
from seq2seq import decoders
from seq2seq.models.attention_seq2seq import AttentionSeq2Seq
from seq2seq import losses as seq2seq_losses
from seq2seq import graph_utils
class BaseAttentionCopyingSeq2Seq(AttentionSeq2Seq):
"""Base class for Sequence2Sequence model with attention-based copying.
Args:
source_vocab_info: An instance of `VocabInfo`
for the source vocabulary
target_vocab_info: An instance of `VocabInfo`
for the target vocabulary
params: A dictionary of hyperparameters
"""
@staticmethod
def compute_loss(self, decoder_output, _features, labels):
"""Computes the sequence loss for this model.
seq_loss is the cross entropy loss for the output sequence.
Returns a tuple `(losses, loss)`, where `losses` are the per-batch
losses and loss is a single scalar tensor to minimize.
"""
targets, seq_len = self._targets_and_seq_len(labels)
seq_loss = seq2seq_losses.cross_entropy_sequence_loss(
logits=decoder_output.logits[:, :, :],
targets=targets,
sequence_length=seq_len)
return seq_loss
class SchemaAttentionCopyingSeq2Seq(BaseAttentionCopyingSeq2Seq):
"""Sequence2Sequence model with attention-based copying from schema.
Args:
source_vocab_info: An instance of `VocabInfo`
for the source vocabulary
target_vocab_info: An instance of `VocabInfo`
for the target vocabulary
params: A dictionary of hyperparameters
"""
def _preprocess(self, features, labels):
"""Model-specific preprocessing for features and labels:
- Creates vocabulary lookup tables for source and target vocab
- Converts tokens into vocabulary ids
- Trims copy indices to target.max_seq_len
"""
features, labels = super(SchemaAttentionCopyingSeq2Seq,
self)._preprocess(features, labels)
if not labels or not "schema_copy_indices" in labels:
return features, labels
labels = self._trim_copy_indices(labels, "schema_copy_indices")
self._set_special_vocab_ids()
return features, labels
def compute_loss(self, decoder_output, _features, labels):
"""Computes the loss for this model.
Loss = seq_loss + schema_copy_loss.
seq_loss is the cross entropy loss for the output sequence.
schema_copy_loss is zero at any time step where output is not
copy_schema, and the cross entropy loss for the schema attention
score otherwise.
Returns a tuple `(losses, loss)`, where `losses` are the per-batch
losses and loss is a single scalar tensor to minimize.
"""
seq_loss = super(SchemaAttentionCopyingSeq2Seq, self).compute_loss(
decoder_output, _features, labels)
targets, seq_length = self._targets_and_seq_len(labels)
schema_copy_loss = self._copy_loss(
targets, seq_length, decoder_output.schema_attention_copy_vals,
labels["schema_copy_indices"], self.copy_schema_id)
losses = seq_loss + schema_copy_loss
# Calculate the average log perplexity
loss = tf.reduce_sum(losses) / tf.to_float(
tf.reduce_sum(labels["target_len"] - 1))
return losses, loss
class InputAttentionCopyingSeq2Seq(BaseAttentionCopyingSeq2Seq):
"""Sequence2Sequence model with attention-based copying from input sequence.
Args:
source_vocab_info: An instance of `VocabInfo`
for the source vocabulary
target_vocab_info: An instance of `VocabInfo`
for the target vocabulary
params: A dictionary of hyperparameters
"""
def _preprocess(self, features, labels):
"""Model-specific preprocessing for features and labels:
- Creates vocabulary lookup tables for source and target vocab
- Converts tokens into vocabulary ids
- Trims copy indices to target.max_seq_len
"""
features, labels = super(InputAttentionCopyingSeq2Seq,
self)._preprocess(features, labels)
if not labels or not "source_copy_indices" in labels:
return features, labels
# Slices source copy indices to max length
labels = self._trim_copy_indices(labels, "source_copy_indices")
self._set_special_vocab_ids()
return features, labels
def compute_loss(self, decoder_output, _features, labels):
"""Computes the loss for this model.
Loss = seq_loss + word_copy_loss.
seq_loss is the cross entropy loss for the output sequence.
word_copy_loss is zero at any time step where output is not copy_word,
and the cross entropy loss for the input attention score otherwise.
Returns a tuple `(losses, loss)`, where `losses` are the per-batch
losses and loss is a single scalar tensor to minimize.
"""
seq_loss = super(InputAttentionCopyingSeq2Seq, self).compute_loss(
decoder_output, _features, labels)
targets, seq_length = self._targets_and_seq_len(labels)
word_copy_loss = self._copy_loss(targets, seq_length,
decoder_output.attention_scores,
labels["source_copy_indices"],
self.copy_word_id)
losses = seq_loss + word_copy_loss
# Calculate the average log perplexity
loss = tf.reduce_sum(losses) / tf.to_float(
tf.reduce_sum(labels["target_len"] - 1))
return losses, loss
class SchemaAndInputAttentionCopyingSeq2Seq(SchemaAttentionCopyingSeq2Seq):
"""Sequence2Sequence model with attention-based copying from schema and input.
Args:
source_vocab_info: An instance of `VocabInfo`
for the source vocabulary
target_vocab_info: An instance of `VocabInfo`
for the target vocabulary
params: A dictionary of hyperparameters
"""
def _preprocess(self, features, labels):
"""Model-specific preprocessing for features and labels:
- Creates vocabulary lookup tables for source and target vocab
- Converts tokens into vocabulary ids
- Trims copy indices to target.max_seq_len
"""
# features, labels already include schema-related
# preprocessing, since this inherits from
# SchemaAttentionCopyingSeq2Seq.
features, labels = super(SchemaAndInputAttentionCopyingSeq2Seq,
self)._preprocess(features, labels)
if not labels or not "source_copy_indices" in labels:
return features, labels
# Slices source copy indices to max length
labels = self._trim_copy_indices(labels, "source_copy_indices")
self._set_special_vocab_ids()
return features, labels
def compute_loss(self, decoder_output, _features, labels):
"""Computes the loss for this model.
Loss = seq_loss + schema_copy_loss + word_copy_loss.
seq_loss is the cross entropy loss for the output sequence.
word_copy_loss is zero at any time step where output is not copy_word,
and the cross entropy loss for the input attention score otherwise.
schema_copy_loss is like word_copy_loss, only for schema copying.
Returns a tuple `(losses, loss)`, where `losses` are the per-batch
losses and loss is a single scalar tensor to minimize.
"""
seq_and_schema_loss, _ = super(SchemaAndInputAttentionCopyingSeq2Seq,
self).compute_loss(decoder_output,
_features, labels)
targets, seq_length = self._targets_and_seq_len(labels)
word_copy_loss = self._copy_loss(targets, seq_length,
decoder_output.attention_scores,
labels["source_copy_indices"],
self.copy_word_id)
losses = seq_and_schema_loss + word_copy_loss
# Calculate the average log perplexity
loss = tf.reduce_sum(losses) / tf.to_float(
tf.reduce_sum(labels["target_len"] - 1))
return losses, loss
| [
37811,
198,
44015,
594,
284,
45835,
4981,
351,
3241,
12,
3106,
23345,
286,
5128,
198,
392,
14,
273,
32815,
13,
198,
37811,
198,
198,
6738,
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62,
11748,
198,
6738,
11593,
37443,
834,
1330,
7297,
198,
6738,
... | 2.431576 | 3,566 |
import os
from django.conf import settings
from django.db import models
from django.utils.translation import ugettext_lazy as _
from model_utils.models import TimeStampedModel
| [
11748,
28686,
198,
198,
6738,
42625,
14208,
13,
10414,
1330,
6460,
198,
6738,
42625,
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13,
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62,
75,
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355,
4808,
198,
6738,
2746,
62,
26791... | 3.632653 | 49 |
# Generated by Django 2.2.7 on 2019-12-04 20:58
from django.db import migrations, models
import django.db.models.deletion
| [
2,
2980,
515,
416,
37770,
362,
13,
17,
13,
22,
319,
13130,
12,
1065,
12,
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25,
3365,
198,
198,
6738,
42625,
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13,
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1330,
15720,
602,
11,
4981,
198,
11748,
42625,
14208,
13,
9945,
13,
27530,
13,
2934,
1616,
295,
... | 2.818182 | 44 |
# parsetab.py
# This file is automatically generated. Do not edit.
# pylint: disable=W,C,R
_tabversion = '3.10'
_lr_method = 'LALR'
_lr_signature = 'leftpuntobipuntoleftcomarightigualleftcor1cor2leftmasmenosleftasteriscodivporcentajeleftpotrightumenosumasleftpar1par2leftt_orleftt_andleftdiferenteleftmayormenormayorimenorirightt_notasterisco bipunto char coma cor1 cor2 decimal diferente diferentede div entero id igual mas mayor mayori menor menori menos par1 par2 porcentaje pot punto pyc string t_abs t_acos t_acosd t_acosh t_add t_all t_alter t_and t_as t_asc t_asin t_asind t_asinh t_atan t_atan2 t_atan2d t_atand t_atanh t_avg t_bigint t_bool t_boolean t_by t_cbrt t_ceil t_ceiling t_character t_charn t_check t_column t_constraint t_convert t_cos t_cosd t_cosh t_cot t_cotd t_count t_create t_current t_current_user t_database t_databases t_date t_decimal t_decode t_default t_degrees t_delete t_desc t_distinct t_div t_double t_drop t_encode t_enum t_exists t_exp t_factorial t_false t_first t_floor t_foreign t_from t_full t_gcd t_get_byte t_group t_having t_if t_inherits t_inner t_insert t_integer t_into t_join t_key t_last t_left t_length t_like t_limit t_ln t_log t_max t_md5 t_min t_min_scale t_mod t_mode t_money t_natural t_not t_null t_nulls t_numeric t_of t_offset t_on t_only t_or t_order t_outer t_owner t_pi t_power t_precision t_primary t_radians t_random t_real t_references t_rename t_replace t_returning t_right t_round t_scale t_select t_session_user t_set t_set_byte t_setseed t_sha256 t_show t_sign t_sin t_sind t_sinh t_smallint t_sqrt t_substr t_substring t_sum t_table t_tan t_tand t_tanh t_text t_to t_trim t_trim_scale t_true t_trunc t_type t_unique t_update t_use t_using t_values t_varchar t_varying t_where t_width_bucketSQL : Sentencias_SQLSQL : emptySentencias_SQL : Sentencias_SQL Sentencia_SQLSentencias_SQL : Sentencia_SQLSentencia_SQL : Sentencias_DMLSentencia_SQL : Sentencias_DDLSentencias_DML : t_select Lista_EXP Select_SQL Condiciones GRP ORD pyc\n | t_select asterisco Select_SQL Condiciones GRP ORD pyc\n | t_insert t_into id Insert_SQL pyc\n | t_update id t_set Lista_EXP Condiciones1 pyc\n | t_delete t_from id Condiciones1 pyc\n | t_use id pycSelect_SQL : t_from Table_ExpressionSelect_SQL : emptyTable_Expression : Alias_Tabla\n | SubqueriesAlias_Tabla : Lista_ID\n | Lista_AliasSubqueries : par1 t_select par2Insert_SQL : par1 Lista_ID par2 t_values par1 Lista_EXP par2Insert_SQL : t_values par1 Lista_EXP par2Condiciones : t_where EXP\n | emptyCondiciones1 : t_where EXP\n | emptyGRP : t_group t_by Lista_ID\n | t_group t_by Lista_ID HV\n | emptyHV : t_having EXPORD : t_order t_by LSORT\n | t_order t_by LSORT LMT\n | emptyLSORT : LSORT coma SORT\n | SORTSORT : EXP AD NFL\n | EXP AD\n | EXPAD : t_asc\n | t_descNFL : t_nulls t_first\n | t_nulls t_lastLMT : t_limit NAL t_offset entero\n | t_limit NAL\n | t_offset entero NAL : entero\n | t_all Sentencias_DDL : t_show t_databases Show_DB_Like_Char pyc\n | Enum_Type\n | t_drop Drop pyc\n | t_alter Alter pyc\n | t_create Create pycShow_DB_Like_Char : t_like char \n | empty Enum_Type : t_create t_type id t_as t_enum par1 Lista_Enum par2 pycDrop : t_database DropDB id\n | t_table id DropDB : t_if t_exists\n | emptyAlter : t_database id AlterDB\n | t_table id AlterTB AlterDB : t_rename t_to id\n | t_owner t_to SesionDB SesionDB : id\n | t_current_user\n | t_session_user AlterTB : t_add Add_Opc\n | t_drop Drop_Opc\n | t_alter t_column Alter_Column\n | t_rename t_column id t_to id Add_Opc : t_column id Tipo\n | Constraint_AlterTB t_foreign t_key par1 Lista_ID par2 t_references id par1 Lista_ID par2\n | Constraint_AlterTB t_unique par1 id par2\n | Constraint_AlterTB t_check EXP Constraint_AlterTB : t_constraint id\n | empty Drop_Opc : t_column id\n | t_constraint id Alter_Column : id t_set t_not t_null\n | Alter_Columns Alter_Columns : Alter_Columns coma Alter_Column1\n | Alter_Column1Alter_Column1 : id t_type t_varchar par1 entero par2\n | t_alter t_column id t_type t_varchar par1 entero par2Create : CreateDBCreate : CreateTB CreateDB : OrReplace_CreateDB t_database IfNotExist_CreateDB id Sesion OrReplace_CreateDB : t_or t_replace\n | empty IfNotExist_CreateDB : t_if t_not t_exists\n | empty Sesion : t_owner Op_Sesion Sesion_mode\n | t_mode Op_Mode\n | empty Op_Sesion : igual char\n | char Sesion_mode : t_mode Op_Mode\n | empty Op_Mode : igual entero\n | entero CreateTB : t_table id par1 Columnas par2 Inherits Inherits : t_inherits par1 id par2\n | empty Columnas : Columnas coma Columna\n | Columna Columna : id Tipo Cond_CreateTB\n | Constraint Cond_CreateTB : Constraint_CreateTB t_default id Cond_CreateTB\n | Constraint_CreateTB t_not t_null Cond_CreateTB\n | Constraint_CreateTB t_null Cond_CreateTB\n | Constraint_CreateTB t_unique Cond_CreateTB\n | Constraint_CreateTB t_check par1 EXP par2 Cond_CreateTB\n | Constraint_CreateTB t_primary t_key Cond_CreateTB\n | Constraint_CreateTB t_references id Cond_CreateTB\n | emptyConstraint_CreateTB : t_constraint id\n | empty Constraint : Constraint_CreateTB t_unique par1 Lista_ID par2\n | Constraint_CreateTB t_check par1 EXP par2\n | Constraint_CreateTB t_primary t_key par1 Lista_ID par2\n | Constraint_CreateTB t_foreign t_key par1 Lista_ID par2 t_references id par1 Lista_ID par2\n | empty Tipo : t_smallint\n | t_integer\n | t_bigint\n | t_decimal\n | t_numeric par1 entero par2\n | t_real\n | t_double t_precision\n | t_money\n | t_character t_varying par1 entero par2\n | t_varchar par1 entero par2\n | t_character par1 entero par2\n | t_charn par1 entero par2\n | t_text\n | t_boolean\n | t_date\n | id Valor : decimal\n | entero\n | string\n | char\n | t_true\n | t_falseValor : idempty :EXP : EXP mas EXP\n | EXP menos EXP\n | EXP asterisco EXP\n | EXP div EXP\n | EXP pot EXP\n | EXP porcentaje EXPEXP : par1 EXP par2EXP : id par1 Lista_EXP par2EXP : EXP mayor EXP\n | EXP mayori EXP\n | EXP menor EXP\n | EXP menori EXP\n | EXP igual EXP\n | EXP diferente EXP\n | EXP diferentede EXPEXP : EXP t_and EXP\n | EXP t_or EXP\n EXP : mas EXP %prec umas\n | menos EXP %prec umenos\n | t_not EXPEXP : ValorEXP : id punto idEXP : EXP t_as EXPEXP : t_avg par1 EXP par2\n | t_sum par1 EXP par2\n | t_count par1 EXP par2\n | t_count par1 asterisco par2\n | t_max par1 EXP par2\n | t_min par1 EXP par2EXP : t_abs par1 EXP par2\n | t_cbrt par1 EXP par2\n | t_ceil par1 EXP par2\n | t_ceiling par1 EXP par2\n | t_degrees par1 EXP par2\n | t_exp par1 EXP par2\n | t_factorial par1 EXP par2\n | t_floor par1 EXP par2\n | t_gcd par1 Lista_EXP par2\n | t_ln par1 EXP par2\n | t_log par1 EXP par2\n | t_pi par1 par2\n | t_radians par1 EXP par2\n | t_round par1 EXP par2\n | t_min_scale par1 EXP par2\n | t_scale par1 EXP par2\n | t_sign par1 EXP par2\n | t_sqrt par1 EXP par2\n | t_trim_scale par1 EXP par2\n | t_trunc par1 EXP par2\n | t_width_bucket par1 Lista_EXP par2\n | t_random par1 par2\n | t_setseed par1 EXP par2 EXP : t_div par1 EXP coma EXP par2\n | t_mod par1 EXP coma EXP par2\n | t_power par1 EXP coma EXP par2 EXP : t_acos par1 EXP par2\n | t_acosd par1 EXP par2\n | t_asin par1 EXP par2\n | t_asind par1 EXP par2\n | t_atan par1 EXP par2\n | t_atand par1 EXP par2\n | t_cos par1 EXP par2\n | t_cosd par1 EXP par2\n | t_cot par1 EXP par2\n | t_cotd par1 EXP par2\n | t_sin par1 EXP par2\n | t_sind par1 EXP par2\n | t_tan par1 EXP par2\n | t_tand par1 EXP par2 EXP : t_atan2 par1 EXP coma EXP par2\n | t_atan2d par1 EXP coma EXP par2 EXP : t_length par1 id par2\n | t_substring par1 char coma entero coma entero par2\n | t_trim par1 char par2\n | t_md5 par1 char par2\n | t_sha256 par1 par2\n | t_substr par1 par2\n | t_get_byte par1 par2\n | t_set_byte par1 par2\n | t_convert par1 EXP t_as Tipo par2\n | t_encode par1 par2\n | t_decode par1 par2 Lista_ID : Lista_ID coma id\n | id Lista_Enum : Lista_Enum coma char\n | char Lista_EXP : Lista_EXP coma EXP\n | EXP Lista_Alias : Lista_Alias coma Nombre_Alias\n | Nombre_Alias Nombre_Alias : id id'
_lr_action_items = 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_lr_action = {}
for _k, _v in _lr_action_items.items():
for _x,_y in zip(_v[0],_v[1]):
if not _x in _lr_action: _lr_action[_x] = {}
_lr_action[_x][_k] = _y
del _lr_action_items
_lr_goto_items = {'SQL':([0,],[1,]),'Sentencias_SQL':([0,],[2,]),'empty':([0,16,18,19,95,97,110,114,197,212,215,227,309,321,329,330,338,411,479,480,481,517,563,564,596,597,601,602,634,],[3,109,113,113,201,205,217,217,312,328,332,332,312,404,418,422,422,476,525,528,418,558,525,525,525,525,525,525,525,]),'Sentencia_SQL':([0,2,],[4,17,]),'Sentencias_DML':([0,2,],[5,5,]),'Sentencias_DDL':([0,2,],[6,6,]),'Enum_Type':([0,2,],[13,13,]),'Lista_EXP':([7,134,150,162,196,394,545,],[18,245,261,273,309,452,587,]),'EXP':([7,21,22,23,25,111,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,134,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,154,155,156,157,158,159,160,161,162,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,192,196,216,311,367,368,369,384,385,390,394,462,488,531,538,545,574,600,],[20,131,132,133,136,218,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,20,247,248,249,251,252,253,254,255,256,257,258,259,260,20,262,263,265,266,267,268,269,270,271,272,20,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,293,294,303,20,333,397,429,430,431,432,433,243,20,509,536,570,580,20,536,622,]),'Valor':([7,21,22,23,25,111,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,134,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,154,155,156,157,158,159,160,161,162,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,192,196,216,311,367,368,369,384,385,390,394,462,488,531,538,545,574,600,],[26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,]),'Drop':([14,],[96,]),'Alter':([15,],[99,]),'Create':([16,],[102,]),'CreateDB':([16,],[104,]),'CreateTB':([16,],[105,]),'OrReplace_CreateDB':([16,],[106,]),'Select_SQL':([18,19,],[110,114,]),'Show_DB_Like_Char':([95,],[199,]),'DropDB':([97,],[203,]),'Condiciones':([110,114,],[215,227,]),'Table_Expression':([112,],[219,]),'Alias_Tabla':([112,],[220,]),'Subqueries':([112,],[221,]),'Lista_ID':([112,307,423,530,546,571,572,641,643,],[222,392,489,569,588,606,607,644,645,]),'Lista_Alias':([112,],[223,]),'Nombre_Alias':([112,335,],[226,425,]),'Insert_SQL':([195,],[306,]),'Condiciones1':([197,309,],[310,395,]),'AlterDB':([208,],[317,]),'AlterTB':([209,],[320,]),'IfNotExist_CreateDB':([212,],[326,]),'GRP':([215,227,],[330,338,]),'Add_Opc':([321,],[400,]),'Constraint_AlterTB':([321,],[402,]),'Drop_Opc':([322,],[405,]),'Columnas':([329,],[414,]),'Columna':([329,481,],[415,529,]),'Constraint':([329,481,],[416,416,]),'Constraint_CreateTB':([329,479,481,563,564,596,597,601,602,634,],[417,524,417,524,524,524,524,524,524,524,]),'ORD':([330,338,],[420,428,]),'Tipo':([390,413,459,],[435,479,506,]),'SesionDB':([399,],[455,]),'Alter_Column':([408,],[467,]),'Alter_Columns':([408,],[469,]),'Alter_Column1':([408,513,],[470,551,]),'Sesion':([411,],[473,]),'Lista_Enum':([472,],[515,]),'Op_Sesion':([474,],[517,]),'Op_Mode':([475,557,],[520,595,]),'Cond_CreateTB':([479,563,564,596,597,601,602,634,],[523,598,599,620,621,623,624,639,]),'Inherits':([480,],[526,]),'LSORT':([488,],[534,]),'SORT':([488,574,],[535,608,]),'HV':([489,],[537,]),'Sesion_mode':([517,],[556,]),'LMT':([534,],[573,]),'AD':([536,],[577,]),'NAL':([575,],[609,]),'NFL':([577,],[613,]),}
_lr_goto = {}
for _k, _v in _lr_goto_items.items():
for _x, _y in zip(_v[0], _v[1]):
if not _x in _lr_goto: _lr_goto[_x] = {}
_lr_goto[_x][_k] = _y
del _lr_goto_items
_lr_productions = [
("S' -> SQL","S'",1,None,None,None),
('SQL -> Sentencias_SQL','SQL',1,'p_sql','Gramatica.py',318),
('SQL -> empty','SQL',1,'p_sql2','Gramatica.py',322),
('Sentencias_SQL -> Sentencias_SQL Sentencia_SQL','Sentencias_SQL',2,'p_Sentencias_SQL_Sentencia_SQL','Gramatica.py',326),
('Sentencias_SQL -> Sentencia_SQL','Sentencias_SQL',1,'p_Sentencias_SQL','Gramatica.py',332),
('Sentencia_SQL -> Sentencias_DML','Sentencia_SQL',1,'p_Sentencia_SQL_DML','Gramatica.py',337),
('Sentencia_SQL -> Sentencias_DDL','Sentencia_SQL',1,'p_Sentencia_SQL_DDL','Gramatica.py',346),
('Sentencias_DML -> t_select Lista_EXP Select_SQL Condiciones GRP ORD pyc','Sentencias_DML',7,'p_Sentencias_DML','Gramatica.py',352),
('Sentencias_DML -> t_select asterisco Select_SQL Condiciones GRP ORD pyc','Sentencias_DML',7,'p_Sentencias_DML','Gramatica.py',353),
('Sentencias_DML -> t_insert t_into id Insert_SQL pyc','Sentencias_DML',5,'p_Sentencias_DML','Gramatica.py',354),
('Sentencias_DML -> t_update id t_set Lista_EXP Condiciones1 pyc','Sentencias_DML',6,'p_Sentencias_DML','Gramatica.py',355),
('Sentencias_DML -> t_delete t_from id Condiciones1 pyc','Sentencias_DML',5,'p_Sentencias_DML','Gramatica.py',356),
('Sentencias_DML -> t_use id pyc','Sentencias_DML',3,'p_Sentencias_DML','Gramatica.py',357),
('Select_SQL -> t_from Table_Expression','Select_SQL',2,'p_Select_SQL','Gramatica.py',376),
('Select_SQL -> empty','Select_SQL',1,'p_Select2_SQL','Gramatica.py',382),
('Table_Expression -> Alias_Tabla','Table_Expression',1,'p_Table_Expression','Gramatica.py',388),
('Table_Expression -> Subqueries','Table_Expression',1,'p_Table_Expression','Gramatica.py',389),
('Alias_Tabla -> Lista_ID','Alias_Tabla',1,'p_Alias_Tabla','Gramatica.py',395),
('Alias_Tabla -> Lista_Alias','Alias_Tabla',1,'p_Alias_Tabla','Gramatica.py',396),
('Subqueries -> par1 t_select par2','Subqueries',3,'p_Subqueries','Gramatica.py',401),
('Insert_SQL -> par1 Lista_ID par2 t_values par1 Lista_EXP par2','Insert_SQL',7,'p_Insert_SQL','Gramatica.py',406),
('Insert_SQL -> t_values par1 Lista_EXP par2','Insert_SQL',4,'p_Insert_SQL2','Gramatica.py',411),
('Condiciones -> t_where EXP','Condiciones',2,'p_Condiciones','Gramatica.py',416),
('Condiciones -> empty','Condiciones',1,'p_Condiciones','Gramatica.py',417),
('Condiciones1 -> t_where EXP','Condiciones1',2,'p_Condiciones1','Gramatica.py',426),
('Condiciones1 -> empty','Condiciones1',1,'p_Condiciones1','Gramatica.py',427),
('GRP -> t_group t_by Lista_ID','GRP',3,'p_GRP','Gramatica.py',438),
('GRP -> t_group t_by Lista_ID HV','GRP',4,'p_GRP','Gramatica.py',439),
('GRP -> empty','GRP',1,'p_GRP','Gramatica.py',440),
('HV -> t_having EXP','HV',2,'p_HV','Gramatica.py',447),
('ORD -> t_order t_by LSORT','ORD',3,'p_ORD','Gramatica.py',451),
('ORD -> t_order t_by LSORT LMT','ORD',4,'p_ORD','Gramatica.py',452),
('ORD -> empty','ORD',1,'p_ORD','Gramatica.py',453),
('LSORT -> LSORT coma SORT','LSORT',3,'p_L_SORT','Gramatica.py',461),
('LSORT -> SORT','LSORT',1,'p_L_SORT','Gramatica.py',462),
('SORT -> EXP AD NFL','SORT',3,'p_SORT','Gramatica.py',469),
('SORT -> EXP AD','SORT',2,'p_SORT','Gramatica.py',470),
('SORT -> EXP','SORT',1,'p_SORT','Gramatica.py',471),
('AD -> t_asc','AD',1,'p_AD','Gramatica.py',480),
('AD -> t_desc','AD',1,'p_AD','Gramatica.py',481),
('NFL -> t_nulls t_first','NFL',2,'p_NFL','Gramatica.py',486),
('NFL -> t_nulls t_last','NFL',2,'p_NFL','Gramatica.py',487),
('LMT -> t_limit NAL t_offset entero','LMT',4,'p_LMT','Gramatica.py',491),
('LMT -> t_limit NAL','LMT',2,'p_LMT','Gramatica.py',492),
('LMT -> t_offset entero','LMT',2,'p_LMT','Gramatica.py',493),
('NAL -> entero','NAL',1,'p_NAL','Gramatica.py',500),
('NAL -> t_all','NAL',1,'p_NAL','Gramatica.py',501),
('Sentencias_DDL -> t_show t_databases Show_DB_Like_Char pyc','Sentencias_DDL',4,'p_Sentencias_DDL','Gramatica.py',506),
('Sentencias_DDL -> Enum_Type','Sentencias_DDL',1,'p_Sentencias_DDL','Gramatica.py',507),
('Sentencias_DDL -> t_drop Drop pyc','Sentencias_DDL',3,'p_Sentencias_DDL','Gramatica.py',508),
('Sentencias_DDL -> t_alter Alter pyc','Sentencias_DDL',3,'p_Sentencias_DDL','Gramatica.py',509),
('Sentencias_DDL -> t_create Create pyc','Sentencias_DDL',3,'p_Sentencias_DDL','Gramatica.py',510),
('Show_DB_Like_Char -> t_like char','Show_DB_Like_Char',2,'p_show_db_like_regex','Gramatica.py',530),
('Show_DB_Like_Char -> empty','Show_DB_Like_Char',1,'p_show_db_like_regex','Gramatica.py',531),
('Enum_Type -> t_create t_type id t_as t_enum par1 Lista_Enum par2 pyc','Enum_Type',9,'p_Enum_Type','Gramatica.py',540),
('Drop -> t_database DropDB id','Drop',3,'p_Drop','Gramatica.py',545),
('Drop -> t_table id','Drop',2,'p_Drop','Gramatica.py',546),
('DropDB -> t_if t_exists','DropDB',2,'p_DropDB','Gramatica.py',555),
('DropDB -> empty','DropDB',1,'p_DropDB','Gramatica.py',556),
('Alter -> t_database id AlterDB','Alter',3,'p_Alter','Gramatica.py',565),
('Alter -> t_table id AlterTB','Alter',3,'p_Alter','Gramatica.py',566),
('AlterDB -> t_rename t_to id','AlterDB',3,'p_AlterDB','Gramatica.py',575),
('AlterDB -> t_owner t_to SesionDB','AlterDB',3,'p_AlterDB','Gramatica.py',576),
('SesionDB -> id','SesionDB',1,'p_SesionDB','Gramatica.py',585),
('SesionDB -> t_current_user','SesionDB',1,'p_SesionDB','Gramatica.py',586),
('SesionDB -> t_session_user','SesionDB',1,'p_SesionDB','Gramatica.py',587),
('AlterTB -> t_add Add_Opc','AlterTB',2,'p_AlterTB','Gramatica.py',597),
('AlterTB -> t_drop Drop_Opc','AlterTB',2,'p_AlterTB','Gramatica.py',598),
('AlterTB -> t_alter t_column Alter_Column','AlterTB',3,'p_AlterTB','Gramatica.py',599),
('AlterTB -> t_rename t_column id t_to id','AlterTB',5,'p_AlterTB','Gramatica.py',600),
('Add_Opc -> t_column id Tipo','Add_Opc',3,'p_Add_Opc','Gramatica.py',615),
('Add_Opc -> Constraint_AlterTB t_foreign t_key par1 Lista_ID par2 t_references id par1 Lista_ID par2','Add_Opc',11,'p_Add_Opc','Gramatica.py',616),
('Add_Opc -> Constraint_AlterTB t_unique par1 id par2','Add_Opc',5,'p_Add_Opc','Gramatica.py',617),
('Add_Opc -> Constraint_AlterTB t_check EXP','Add_Opc',3,'p_Add_Opc','Gramatica.py',618),
('Constraint_AlterTB -> t_constraint id','Constraint_AlterTB',2,'p_Constraint_AlterTB','Gramatica.py',633),
('Constraint_AlterTB -> empty','Constraint_AlterTB',1,'p_Constraint_AlterTB','Gramatica.py',634),
('Drop_Opc -> t_column id','Drop_Opc',2,'p_Drop_Opc','Gramatica.py',643),
('Drop_Opc -> t_constraint id','Drop_Opc',2,'p_Drop_Opc','Gramatica.py',644),
('Alter_Column -> id t_set t_not t_null','Alter_Column',4,'p_Alter_Column','Gramatica.py',653),
('Alter_Column -> Alter_Columns','Alter_Column',1,'p_Alter_Column','Gramatica.py',654),
('Alter_Columns -> Alter_Columns coma Alter_Column1','Alter_Columns',3,'p_Alter_Columns','Gramatica.py',663),
('Alter_Columns -> Alter_Column1','Alter_Columns',1,'p_Alter_Columns','Gramatica.py',664),
('Alter_Column1 -> id t_type t_varchar par1 entero par2','Alter_Column1',6,'p_Alter_Colum1','Gramatica.py',674),
('Alter_Column1 -> t_alter t_column id t_type t_varchar par1 entero par2','Alter_Column1',8,'p_Alter_Colum1','Gramatica.py',675),
('Create -> CreateDB','Create',1,'p_Create','Gramatica.py',690),
('Create -> CreateTB','Create',1,'p_Create1','Gramatica.py',695),
('CreateDB -> OrReplace_CreateDB t_database IfNotExist_CreateDB id Sesion','CreateDB',5,'p_CreateDB','Gramatica.py',700),
('OrReplace_CreateDB -> t_or t_replace','OrReplace_CreateDB',2,'p_CreateDB_or_replace','Gramatica.py',705),
('OrReplace_CreateDB -> empty','OrReplace_CreateDB',1,'p_CreateDB_or_replace','Gramatica.py',706),
('IfNotExist_CreateDB -> t_if t_not t_exists','IfNotExist_CreateDB',3,'p_IfNotExist_CreateDB','Gramatica.py',715),
('IfNotExist_CreateDB -> empty','IfNotExist_CreateDB',1,'p_IfNotExist_CreateDB','Gramatica.py',716),
('Sesion -> t_owner Op_Sesion Sesion_mode','Sesion',3,'p_Sesion','Gramatica.py',725),
('Sesion -> t_mode Op_Mode','Sesion',2,'p_Sesion','Gramatica.py',726),
('Sesion -> empty','Sesion',1,'p_Sesion','Gramatica.py',727),
('Op_Sesion -> igual char','Op_Sesion',2,'p_Op_Sesion','Gramatica.py',739),
('Op_Sesion -> char','Op_Sesion',1,'p_Op_Sesion','Gramatica.py',740),
('Sesion_mode -> t_mode Op_Mode','Sesion_mode',2,'p_Sesion_mode','Gramatica.py',749),
('Sesion_mode -> empty','Sesion_mode',1,'p_Sesion_mode','Gramatica.py',750),
('Op_Mode -> igual entero','Op_Mode',2,'p_Op_Mode','Gramatica.py',759),
('Op_Mode -> entero','Op_Mode',1,'p_Op_Mode','Gramatica.py',760),
('CreateTB -> t_table id par1 Columnas par2 Inherits','CreateTB',6,'p_CreateTB','Gramatica.py',769),
('Inherits -> t_inherits par1 id par2','Inherits',4,'p_Inherits','Gramatica.py',774),
('Inherits -> empty','Inherits',1,'p_Inherits','Gramatica.py',775),
('Columnas -> Columnas coma Columna','Columnas',3,'p_Columnas','Gramatica.py',784),
('Columnas -> Columna','Columnas',1,'p_Columnas','Gramatica.py',785),
('Columna -> id Tipo Cond_CreateTB','Columna',3,'p_Columna','Gramatica.py',795),
('Columna -> Constraint','Columna',1,'p_Columna','Gramatica.py',796),
('Cond_CreateTB -> Constraint_CreateTB t_default id Cond_CreateTB','Cond_CreateTB',4,'p_Cond_CreateTB','Gramatica.py',805),
('Cond_CreateTB -> Constraint_CreateTB t_not t_null Cond_CreateTB','Cond_CreateTB',4,'p_Cond_CreateTB','Gramatica.py',806),
('Cond_CreateTB -> Constraint_CreateTB t_null Cond_CreateTB','Cond_CreateTB',3,'p_Cond_CreateTB','Gramatica.py',807),
('Cond_CreateTB -> Constraint_CreateTB t_unique Cond_CreateTB','Cond_CreateTB',3,'p_Cond_CreateTB','Gramatica.py',808),
('Cond_CreateTB -> Constraint_CreateTB t_check par1 EXP par2 Cond_CreateTB','Cond_CreateTB',6,'p_Cond_CreateTB','Gramatica.py',809),
('Cond_CreateTB -> Constraint_CreateTB t_primary t_key Cond_CreateTB','Cond_CreateTB',4,'p_Cond_CreateTB','Gramatica.py',810),
('Cond_CreateTB -> Constraint_CreateTB t_references id Cond_CreateTB','Cond_CreateTB',4,'p_Cond_CreateTB','Gramatica.py',811),
('Cond_CreateTB -> empty','Cond_CreateTB',1,'p_Cond_CreateTB','Gramatica.py',812),
('Constraint_CreateTB -> t_constraint id','Constraint_CreateTB',2,'p_Constraint_CreateTB','Gramatica.py',846),
('Constraint_CreateTB -> empty','Constraint_CreateTB',1,'p_Constraint_CreateTB','Gramatica.py',847),
('Constraint -> Constraint_CreateTB t_unique par1 Lista_ID par2','Constraint',5,'p_Constraint','Gramatica.py',856),
('Constraint -> Constraint_CreateTB t_check par1 EXP par2','Constraint',5,'p_Constraint','Gramatica.py',857),
('Constraint -> Constraint_CreateTB t_primary t_key par1 Lista_ID par2','Constraint',6,'p_Constraint','Gramatica.py',858),
('Constraint -> Constraint_CreateTB t_foreign t_key par1 Lista_ID par2 t_references id par1 Lista_ID par2','Constraint',11,'p_Constraint','Gramatica.py',859),
('Constraint -> empty','Constraint',1,'p_Constraint','Gramatica.py',860),
('Tipo -> t_smallint','Tipo',1,'p_Tipo','Gramatica.py',878),
('Tipo -> t_integer','Tipo',1,'p_Tipo','Gramatica.py',879),
('Tipo -> t_bigint','Tipo',1,'p_Tipo','Gramatica.py',880),
('Tipo -> t_decimal','Tipo',1,'p_Tipo','Gramatica.py',881),
('Tipo -> t_numeric par1 entero par2','Tipo',4,'p_Tipo','Gramatica.py',882),
('Tipo -> t_real','Tipo',1,'p_Tipo','Gramatica.py',883),
('Tipo -> t_double t_precision','Tipo',2,'p_Tipo','Gramatica.py',884),
('Tipo -> t_money','Tipo',1,'p_Tipo','Gramatica.py',885),
('Tipo -> t_character t_varying par1 entero par2','Tipo',5,'p_Tipo','Gramatica.py',886),
('Tipo -> t_varchar par1 entero par2','Tipo',4,'p_Tipo','Gramatica.py',887),
('Tipo -> t_character par1 entero par2','Tipo',4,'p_Tipo','Gramatica.py',888),
('Tipo -> t_charn par1 entero par2','Tipo',4,'p_Tipo','Gramatica.py',889),
('Tipo -> t_text','Tipo',1,'p_Tipo','Gramatica.py',890),
('Tipo -> t_boolean','Tipo',1,'p_Tipo','Gramatica.py',891),
('Tipo -> t_date','Tipo',1,'p_Tipo','Gramatica.py',892),
('Tipo -> id','Tipo',1,'p_Tipo','Gramatica.py',893),
('Valor -> decimal','Valor',1,'p_Valor','Gramatica.py',978),
('Valor -> entero','Valor',1,'p_Valor','Gramatica.py',979),
('Valor -> string','Valor',1,'p_Valor','Gramatica.py',980),
('Valor -> char','Valor',1,'p_Valor','Gramatica.py',981),
('Valor -> t_true','Valor',1,'p_Valor','Gramatica.py',982),
('Valor -> t_false','Valor',1,'p_Valor','Gramatica.py',983),
('Valor -> id','Valor',1,'p_Valor2','Gramatica.py',989),
('empty -> <empty>','empty',0,'p_empty','Gramatica.py',994),
('EXP -> EXP mas EXP','EXP',3,'p_aritmeticas','Gramatica.py',1001),
('EXP -> EXP menos EXP','EXP',3,'p_aritmeticas','Gramatica.py',1002),
('EXP -> EXP asterisco EXP','EXP',3,'p_aritmeticas','Gramatica.py',1003),
('EXP -> EXP div EXP','EXP',3,'p_aritmeticas','Gramatica.py',1004),
('EXP -> EXP pot EXP','EXP',3,'p_aritmeticas','Gramatica.py',1005),
('EXP -> EXP porcentaje EXP','EXP',3,'p_aritmeticas','Gramatica.py',1006),
('EXP -> par1 EXP par2','EXP',3,'p_parentesis','Gramatica.py',1011),
('EXP -> id par1 Lista_EXP par2','EXP',4,'p_funciones','Gramatica.py',1017),
('EXP -> EXP mayor EXP','EXP',3,'p_relacionales','Gramatica.py',1024),
('EXP -> EXP mayori EXP','EXP',3,'p_relacionales','Gramatica.py',1025),
('EXP -> EXP menor EXP','EXP',3,'p_relacionales','Gramatica.py',1026),
('EXP -> EXP menori EXP','EXP',3,'p_relacionales','Gramatica.py',1027),
('EXP -> EXP igual EXP','EXP',3,'p_relacionales','Gramatica.py',1028),
('EXP -> EXP diferente EXP','EXP',3,'p_relacionales','Gramatica.py',1029),
('EXP -> EXP diferentede EXP','EXP',3,'p_relacionales','Gramatica.py',1030),
('EXP -> EXP t_and EXP','EXP',3,'p_logicos','Gramatica.py',1035),
('EXP -> EXP t_or EXP','EXP',3,'p_logicos','Gramatica.py',1036),
('EXP -> mas EXP','EXP',2,'p_unario','Gramatica.py',1042),
('EXP -> menos EXP','EXP',2,'p_unario','Gramatica.py',1043),
('EXP -> t_not EXP','EXP',2,'p_unario','Gramatica.py',1044),
('EXP -> Valor','EXP',1,'p_EXP_Valor','Gramatica.py',1053),
('EXP -> id punto id','EXP',3,'p_EXP_Indices','Gramatica.py',1058),
('EXP -> EXP t_as EXP','EXP',3,'p_EXP_IndicesAS','Gramatica.py',1064),
('EXP -> t_avg par1 EXP par2','EXP',4,'p_exp_agregacion','Gramatica.py',1071),
('EXP -> t_sum par1 EXP par2','EXP',4,'p_exp_agregacion','Gramatica.py',1072),
('EXP -> t_count par1 EXP par2','EXP',4,'p_exp_agregacion','Gramatica.py',1073),
('EXP -> t_count par1 asterisco par2','EXP',4,'p_exp_agregacion','Gramatica.py',1074),
('EXP -> t_max par1 EXP par2','EXP',4,'p_exp_agregacion','Gramatica.py',1075),
('EXP -> t_min par1 EXP par2','EXP',4,'p_exp_agregacion','Gramatica.py',1076),
('EXP -> t_abs par1 EXP par2','EXP',4,'p_funciones_matematicas','Gramatica.py',1081),
('EXP -> t_cbrt par1 EXP par2','EXP',4,'p_funciones_matematicas','Gramatica.py',1082),
('EXP -> t_ceil par1 EXP par2','EXP',4,'p_funciones_matematicas','Gramatica.py',1083),
('EXP -> t_ceiling par1 EXP par2','EXP',4,'p_funciones_matematicas','Gramatica.py',1084),
('EXP -> t_degrees par1 EXP par2','EXP',4,'p_funciones_matematicas','Gramatica.py',1085),
('EXP -> t_exp par1 EXP par2','EXP',4,'p_funciones_matematicas','Gramatica.py',1086),
('EXP -> t_factorial par1 EXP par2','EXP',4,'p_funciones_matematicas','Gramatica.py',1087),
('EXP -> t_floor par1 EXP par2','EXP',4,'p_funciones_matematicas','Gramatica.py',1088),
('EXP -> t_gcd par1 Lista_EXP par2','EXP',4,'p_funciones_matematicas','Gramatica.py',1089),
('EXP -> t_ln par1 EXP par2','EXP',4,'p_funciones_matematicas','Gramatica.py',1090),
('EXP -> t_log par1 EXP par2','EXP',4,'p_funciones_matematicas','Gramatica.py',1091),
('EXP -> t_pi par1 par2','EXP',3,'p_funciones_matematicas','Gramatica.py',1092),
('EXP -> t_radians par1 EXP par2','EXP',4,'p_funciones_matematicas','Gramatica.py',1093),
('EXP -> t_round par1 EXP par2','EXP',4,'p_funciones_matematicas','Gramatica.py',1094),
('EXP -> t_min_scale par1 EXP par2','EXP',4,'p_funciones_matematicas','Gramatica.py',1095),
('EXP -> t_scale par1 EXP par2','EXP',4,'p_funciones_matematicas','Gramatica.py',1096),
('EXP -> t_sign par1 EXP par2','EXP',4,'p_funciones_matematicas','Gramatica.py',1097),
('EXP -> t_sqrt par1 EXP par2','EXP',4,'p_funciones_matematicas','Gramatica.py',1098),
('EXP -> t_trim_scale par1 EXP par2','EXP',4,'p_funciones_matematicas','Gramatica.py',1099),
('EXP -> t_trunc par1 EXP par2','EXP',4,'p_funciones_matematicas','Gramatica.py',1100),
('EXP -> t_width_bucket par1 Lista_EXP par2','EXP',4,'p_funciones_matematicas','Gramatica.py',1101),
('EXP -> t_random par1 par2','EXP',3,'p_funciones_matematicas','Gramatica.py',1102),
('EXP -> t_setseed par1 EXP par2','EXP',4,'p_funciones_matematicas','Gramatica.py',1103),
('EXP -> t_div par1 EXP coma EXP par2','EXP',6,'p_funciones_matematicas2','Gramatica.py',1108),
('EXP -> t_mod par1 EXP coma EXP par2','EXP',6,'p_funciones_matematicas2','Gramatica.py',1109),
('EXP -> t_power par1 EXP coma EXP par2','EXP',6,'p_funciones_matematicas2','Gramatica.py',1110),
('EXP -> t_acos par1 EXP par2','EXP',4,'p_funciones_Trigonometricas','Gramatica.py',1115),
('EXP -> t_acosd par1 EXP par2','EXP',4,'p_funciones_Trigonometricas','Gramatica.py',1116),
('EXP -> t_asin par1 EXP par2','EXP',4,'p_funciones_Trigonometricas','Gramatica.py',1117),
('EXP -> t_asind par1 EXP par2','EXP',4,'p_funciones_Trigonometricas','Gramatica.py',1118),
('EXP -> t_atan par1 EXP par2','EXP',4,'p_funciones_Trigonometricas','Gramatica.py',1119),
('EXP -> t_atand par1 EXP par2','EXP',4,'p_funciones_Trigonometricas','Gramatica.py',1120),
('EXP -> t_cos par1 EXP par2','EXP',4,'p_funciones_Trigonometricas','Gramatica.py',1121),
('EXP -> t_cosd par1 EXP par2','EXP',4,'p_funciones_Trigonometricas','Gramatica.py',1122),
('EXP -> t_cot par1 EXP par2','EXP',4,'p_funciones_Trigonometricas','Gramatica.py',1123),
('EXP -> t_cotd par1 EXP par2','EXP',4,'p_funciones_Trigonometricas','Gramatica.py',1124),
('EXP -> t_sin par1 EXP par2','EXP',4,'p_funciones_Trigonometricas','Gramatica.py',1125),
('EXP -> t_sind par1 EXP par2','EXP',4,'p_funciones_Trigonometricas','Gramatica.py',1126),
('EXP -> t_tan par1 EXP par2','EXP',4,'p_funciones_Trigonometricas','Gramatica.py',1127),
('EXP -> t_tand par1 EXP par2','EXP',4,'p_funciones_Trigonometricas','Gramatica.py',1128),
('EXP -> t_atan2 par1 EXP coma EXP par2','EXP',6,'p_funciones_Trigonometricas1','Gramatica.py',1133),
('EXP -> t_atan2d par1 EXP coma EXP par2','EXP',6,'p_funciones_Trigonometricas1','Gramatica.py',1134),
('EXP -> t_length par1 id par2','EXP',4,'p_funciones_String_Binarias','Gramatica.py',1138),
('EXP -> t_substring par1 char coma entero coma entero par2','EXP',8,'p_funciones_String_Binarias','Gramatica.py',1139),
('EXP -> t_trim par1 char par2','EXP',4,'p_funciones_String_Binarias','Gramatica.py',1140),
('EXP -> t_md5 par1 char par2','EXP',4,'p_funciones_String_Binarias','Gramatica.py',1141),
('EXP -> t_sha256 par1 par2','EXP',3,'p_funciones_String_Binarias','Gramatica.py',1142),
('EXP -> t_substr par1 par2','EXP',3,'p_funciones_String_Binarias','Gramatica.py',1143),
('EXP -> t_get_byte par1 par2','EXP',3,'p_funciones_String_Binarias','Gramatica.py',1144),
('EXP -> t_set_byte par1 par2','EXP',3,'p_funciones_String_Binarias','Gramatica.py',1145),
('EXP -> t_convert par1 EXP t_as Tipo par2','EXP',6,'p_funciones_String_Binarias','Gramatica.py',1146),
('EXP -> t_encode par1 par2','EXP',3,'p_funciones_String_Binarias','Gramatica.py',1147),
('EXP -> t_decode par1 par2','EXP',3,'p_funciones_String_Binarias','Gramatica.py',1148),
('Lista_ID -> Lista_ID coma id','Lista_ID',3,'p_Lista_ID','Gramatica.py',1158),
('Lista_ID -> id','Lista_ID',1,'p_Lista_ID','Gramatica.py',1159),
('Lista_Enum -> Lista_Enum coma char','Lista_Enum',3,'p_Lista_Enum','Gramatica.py',1168),
('Lista_Enum -> char','Lista_Enum',1,'p_Lista_Enum','Gramatica.py',1169),
('Lista_EXP -> Lista_EXP coma EXP','Lista_EXP',3,'p_Lista_EXP','Gramatica.py',1178),
('Lista_EXP -> EXP','Lista_EXP',1,'p_Lista_EXP','Gramatica.py',1179),
('Lista_Alias -> Lista_Alias coma Nombre_Alias','Lista_Alias',3,'p_Lista_Alias','Gramatica.py',1194),
('Lista_Alias -> Nombre_Alias','Lista_Alias',1,'p_Lista_Alias','Gramatica.py',1195),
('Nombre_Alias -> id id','Nombre_Alias',2,'p_Nombre_Alias','Gramatica.py',1204),
]
| [
198,
2,
13544,
316,
397,
13,
9078,
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2,
770,
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318,
6338,
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9641,
796,
705,
18,
13,
940,
6,
198,
198,
62,
14050,
6... | 1.958013 | 59,566 |
import pkg_resources
import pyglet
import pyperclip
from pyglet.window import Window
from pyglet import gl
from . import draw, initialCode, menu
from .process import Process
from .node import Node
from .field import Field
from .sub import Sub
from .codeEditor import CodeEditor
from .element import color_inverse
from .utils import font, x_y_pan_scale, point_intersect_quad, random_node_color
class PynoWindow(Window, Process):
'''
Visual interface for Process
'''
| [
11748,
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70,
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... | 3.356643 | 143 |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Copyright 2011 yinhm
import datetime
import os
import sys
import numpy as np
ROOT_PATH = os.path.join(os.path.realpath(os.path.dirname(__file__)), '..')
sys.path[0:0] = [ROOT_PATH]
from cStringIO import StringIO
from datafeed.client import Client
from datafeed.datastore import Manager
from datafeed.exchange import *
from datafeed.providers.dzh import *
var_path = os.path.join(ROOT_PATH, 'var')
client = Client()
store = Manager('/tmp/df', SH())
filename = os.path.join(var_path, "dzh/sh/MIN1.DAT")
io = DzhMinute()
for symbol, ohlcs in io.read(filename, 'SH'):
client.put_minute(symbol, ohlcs)
filename = os.path.join(var_path, "dzh/sh/MIN1.DAT")
io = DzhMinute()
for symbol, ohlcs in io.read(filename, 'SH'):
for ohlc in ohlcs:
ohlc['time'] = ohlc['time'] - 8 * 3600
print symbol
#client.put_1minute(symbol, ohlcs)
store.oneminstore.update(symbol, ohlcs)
filename = os.path.join(var_path, "dzh/sh/MIN.DAT")
io = DzhFiveMinute()
for symbol, ohlcs in io.read(filename, 'SH'):
for ohlc in ohlcs:
ohlc['time'] = ohlc['time'] - 8 * 3600
print symbol
client.put_5minute(symbol, ohlcs)
# store.fiveminstore.update(symbol, ohlcs)
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
2,
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9,
12,
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25,
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69,
12,
23,
532,
9,
12,
198,
2,
198,
2,
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2813,
331,
259,
23940,
198,
11748,
4818,
8079,
198,
11748,
28686,
198,
11748,
25064,
198,
198,
11748,... | 2.388031 | 518 |
from jd.api.base import RestApi
| [
6738,
474,
67,
13,
15042,
13,
8692,
1330,
8324,
32,
14415,
628,
628,
628,
198
] | 2.533333 | 15 |
from marshmallow import fields
from qikfiller.schemas.lists import (
BaseCollectionObject, BaseCollectionSchema, BaseSchema, register_class,
)
@register_class
| [
6738,
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11,
7308,
27054,
2611,
11,
7881,
62,
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11,
198... | 3.294118 | 51 |
from django.test import TestCase
from django.core.exceptions import ValidationError
from incomewealth.app.serializers import (serialize_get_request,
serialize_saving_capacity_request)
| [
6738,
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25927... | 2.425532 | 94 |
#!/usr/bin/env python3
from unittest import main, TestCase
from tracerface.parse_stack import parse_stack
if __name__ == '__main__':
main()
| [
2,
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21136,
62,
25558,
628,
198,
198,
361,
11593,
3672,
834,
6624,
705,
... | 2.792453 | 53 |
import onmt.io
import onmt.translate
import onmt.Models
import onmt.ViModels
import onmt.Loss
from onmt.Trainer import Trainer, Statistics
from onmt.Optim import Optim
# For flake8 compatibility
__all__ = [onmt.Loss, onmt.Models, onmt.ViModels,
Trainer, Optim, Statistics, onmt.io, onmt.translate]
| [
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1... | 2.672414 | 116 |
class Trigger:
"""
A trigger is simply a scene/action pair that can be passed in to actions
(along with other triggers if required).
Attributes:
scene (botticelli.Scene): A scene that will trigger the accompanying
action.
action (botticelli.Action): An action that will be performed if the
accompanying scene is detected.
""" | [
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611,
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628,
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220,
220,
220,
3715,
... | 3.705263 | 95 |
# https://stackoverflow.com/questions/57964626/permissions-denied-when-trying-to-invoke-go-aws-lambda-function
import zipfile
import time
| [
2,
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25558,
2502,
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12,
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12,
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12,
8818,
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198,
11748,
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7753,
... | 2.916667 | 48 |
from django.db import models
| [
6738,
42625,
14208,
13,
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1330,
4981,
628
] | 3.75 | 8 |
import sys
import gzip
import numpy as np
import scipy as sc
import pickle
from optparse import OptionParser
from sklearn.decomposition import PCA
from sklearn import preprocessing
from sklearn import linear_model
from scipy.stats import rankdata
from scipy.stats import norm
if __name__ == "__main__":
parser = OptionParser(usage="usage: %prog [-p num_PCs] input_perind.counts.gz")
parser.add_option("-p", "--pcs", dest="npcs", default = 50, help="number of PCs output")
(options, args) = parser.parse_args()
if len(args)==0:
sys.stderr.write("Error: no ratio file provided... (e.g. python leafcutter/scripts/prepare_phenotype_table.py input_perind.counts.gz\n")
exit(0)
main(args[0], int(options.npcs) )
| [
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293,
198,
198,
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2172,
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1330,
16018,
46677,
198,
220,
220,
220,
220,
198,
6738,
1341,
35720,
13,
... | 2.690391 | 281 |
"""CODEX preprocessing pipeline core logic
This is not intended to be run directly but rather used by mutliple external
interfaces to implement the core process that comprises CODEX processing.
"""
import os, logging, itertools, queue
import numpy as np
from os import path as osp
from threading import Thread
from timeit import default_timer as timer
from codex import io as codex_io
from codex import config as codex_config
from codex.ops import op
from codex.ops import tile_generator
from codex.ops import tile_crop
from codex.ops import drift_compensation
from codex.ops import best_focus
from codex.ops import deconvolution
from dask.distributed import Client, LocalCluster
logger = logging.getLogger(__name__)
# Set 1 hour time limit on tile loading/reading operations
TIMEOUT = 1 * 60 * 60
| [
37811,
34,
3727,
6369,
662,
36948,
11523,
4755,
9156,
198,
198,
1212,
318,
407,
5292,
284,
307,
1057,
3264,
475,
2138,
973,
416,
4517,
75,
2480,
7097,
198,
3849,
32186,
284,
3494,
262,
4755,
1429,
326,
28800,
327,
3727,
6369,
7587,
13... | 3.636771 | 223 |
# Copyright 2016-2021 Doug Latornell, 43ravens
# 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
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Unit tests for cli module.
"""
import argparse
from datetime import datetime
from unittest.mock import patch
import arrow
import pytest
from nemo_nowcast.cli import CommandLineInterface
class TestCommandLineInterface:
"""Unit tests for nemo_nowcast.cli.CommandLineInterface constructor.
"""
class TestBuildParser:
"""Unit tests for nemo_nowcast.cli.CommandLineInterface.build_parser method.
"""
@patch("nemo_nowcast.cli.argparse.ArgumentParser")
class TestAddArgument:
"""Unit test for nemo_nowcast.cli.CommandLineInterface.add_argument method.
"""
def test_add_argument(self, m_parser):
"""add_argument() wraps argparse.ArgumentParser.add_argument()
"""
cli = CommandLineInterface("test")
cli.parser = m_parser
cli.add_argument(
"--yesterday",
action="store_true",
help="Download forecast files for previous day's date.",
)
m_parser.add_argument.assert_called_once_with(
"--yesterday",
action="store_true",
help="Download forecast files for previous day's date.",
)
class TestAddDateOption:
"""Unit tests for nemo_nowcast.cli.CommandLineInterface.add_date_option
method.
"""
class TestArrowDate:
"""Unit tests for nemo_nowcast.cli.CommandLineInterface.arrow_date method.
"""
| [
2,
15069,
1584,
12,
1238,
2481,
15115,
5476,
1211,
695,
11,
5946,
430,
574,
82,
198,
198,
2,
49962,
739,
262,
24843,
13789,
11,
10628,
362,
13,
15,
357,
1169,
366,
34156,
15341,
198,
2,
345,
743,
407,
779,
428,
2393,
2845,
287,
11... | 2.908284 | 676 |
import datetime
import logging
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
from matplotlib.ticker import FuncFormatter
from matplotlib.ticker import FormatStrFormatter
import numpy as np
import math
logger = logging.getLogger(__name__)
| [
11748,
4818,
8079,
198,
11748,
18931,
198,
11748,
2603,
29487,
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198,
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355,
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198,
11748,
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13,
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355,
285,
19581,
198,
6738,
2603,
29487,
8019,
13,
83,
15799,
1... | 3.349398 | 83 |
##
# @file slider.py
#
# @brief A wx.Slider connected to a pex.RangeInterface node.
#
# @author Jive Helix (jivehelix@gmail.com)
# @date 06 Jun 2020
# @copyright Jive Helix
# Licensed under the MIT license. See LICENSE file.
from __future__ import annotations
from typing import Generic, Any, TypeVar
import wx
from .. import pex
from ..value import InterfaceValue
from ..range import RangeInterface, ModelNumber, InterfaceNumber
from .window import Window
from .view import View
| [
2235,
198,
2,
2488,
7753,
28982,
13,
9078,
198,
2,
198,
2,
2488,
65,
3796,
317,
266,
87,
13,
11122,
1304,
5884,
284,
257,
613,
87,
13,
17257,
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10139,
13,
198,
2,
198,
2,
2488,
9800,
449,
425,
5053,
844,
357,
73,
425,
2978,... | 3.368056 | 144 |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
__author__ = 'alberto'
# Delete rules
DO_NOTHING = 0
NULLIFY = 1
CASCADE = 2
DENY = 3
| [
2,
48443,
14629,
14,
8800,
14,
24330,
21015,
198,
2,
532,
9,
12,
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25,
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69,
12,
23,
532,
9,
12,
198,
198,
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6,
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2,
23520,
3173,
198,
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62,
11929,
39,
2751,
796,
657,
198,
... | 2.15625 | 64 |
# -*- coding: utf-8 -*-
# @Time : 2017/7/13 下午7:17
# @Author : play4fun
# @File : 1-kNN.py
# @Software: PyCharm
"""
1-kNN.py:
k 的取值最好为奇数
根据 k 个 最近邻居进行分类的方法 称为 kNN
权重
距离近的具有更高的权重， 距离远的权重更低
"""
import cv2
import numpy as np
import matplotlib.pyplot as plt
# Feature set containing (x,y) values of 25 known/training data
trainData = np.random.randint(0, 100, (25, 2)).astype(np.float32)
# Labels each one either Red or Blue with numbers 0 and 1
responses = np.random.randint(0, 2, (25, 1)).astype(np.float32)
# Take Red families and plot them
red = trainData[responses.ravel() == 0]
plt.scatter(red[:, 0], red[:, 1], 80, 'r', '^')
# Take Blue families and plot them
blue = trainData[responses.ravel() == 1]
plt.scatter(blue[:, 0], blue[:, 1], 80, 'b', 's')
plt.show()
# 测试数据被标记为绿色
# # 回值包括
# 1. 由 kNN算法计算得到的测 数据的类别标志0或1 。
# 如果你想使用最近邻算法 只需 将 k 置为 1 k 就是最近邻的数目。
# 2. k 个最近邻居的类别标志。
# 3. 每个最近邻居到测 数据的 离。
newcomer = np.random.randint(0, 100, (1, 2)).astype(np.float32)
plt.scatter(newcomer[:, 0], newcomer[:, 1], 80, 'g', 'o')
knn = cv2.ml.KNearest_create()
knn.train(trainData, cv2.ml.ROW_SAMPLE, responses)
ret, results, neighbours, dist = knn.findNearest(newcomer, 3)
print("result: ", results, "\n")
print("neighbours: ", neighbours, "\n")
print("distance: ", dist)
plt.show()
# 如果我们有大 的数据 测 可以直接传入一个数组。对应的结果 同样也是数组
# 10 new comers
newcomers = np.random.randint(0, 100, (10, 2)).astype(np.float32)
ret, results, neighbours, dist = knn.findNearest(newcomer, 3)
# The results also will contain 10 labels.
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... | 1.644708 | 926 |
from config.celery import app
from django.core.mail import send_mail
@app.task
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# coding=utf-8
import time
from poco.drivers.unity3d.test.tutorial.case import TutorialCase
if __name__ == '__main__':
from airtest.core.api import connect_device
connect_device('Android:///')
import pocounit
pocounit.main()
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