wesleyit

# pip install pyscreenshot pyuserinput

import pyscreenshot
import pykeyboard
import time

X1 = 780
X2 = 785
Y1 = 410
Y2 = 420

wesleyit

"""
runner.py - This is a cron-like executor.
You can run Python files in scheduled times.
"""

import schedule
import time

# Files to run (ordered)
files_to_run = ['some_file_1.py', 'another_file_2.py']

wesleyit

#!/bin/bash

if [ "$(whoami)" != "root" ]
then
        echo "Execute este comando com sudo ou como root."
        exit 1
fi 

clear
echo '------------------------------------------------------------'

wesleyit

# Create first network with Keras
from keras.models import Sequential
from keras.layers import Dense
import numpy as np

# Define your X and y here
X = np.array([[1, 0], [1, 1], [0, 1], [0, 0]])
y = np.array([1, 1, 1, 0])

# Create model

wesleyit

#!/bin/bash
# Com este script você cria uma forma de executar comandos
# que não terão acesso à rede externa e Internet.
# Por exemplo, se você quiser forçar o Spotify a fica offline:
# offline spotify.bin

sudo groupadd offline
echo '#!/bin/bash' | sudo tee /usr/local/bin/offline
echo 'sg offline "$*"' | sudo tee -a /usr/local/bin/offline
sudo chmod a+x /usr/local/bin/offline

wesleyit

import pandas as pd
import pyodbc as odbc
import os


query = 'select * from vendas'

# Trago os dados do servidor caso não exista um cache local,
# senão apenas carrego o cache
if os.path.isfile('./dados/julho_com_sala.csv'):

wesleyit

import sys
import pyodbc as odbc
import datetime

dsn = sys.argv[1]
query_file = sys.argv[2]
csv_file = sys.argv[3]

print(f'Connecting to {dsn}')
print(f'Executing {query_file}')

wesleyit

import sys
import pyodbc as odbc
import datetime

dsn = sys.argv[1]
query_file = sys.argv[2]
csv_file = sys.argv[3]

print(f'Connecting to {dsn}')
print(f'Executing {query_file}')

wesleyit

import sys
import time
from PyQt5.QtWidgets import QApplication, QDialog
from PyQt5.uic import loadUi


class IMC(QDialog):
    def __init__(self):
        super().__init__()
        loadUi('imc.ui', self)

wesleyit

from tensorflow.python.client import device_lib

def get_available_devices():
    local_device_protos = device_lib.list_local_devices()
    return [x.name for x in local_device_protos]

print(get_available_devices())