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| # 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 |
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| #!/bin/bash | |
| if [ "$(whoami)" != "root" ] | |
| then | |
| echo "Execute este comando com sudo ou como root." | |
| exit 1 | |
| fi | |
| clear | |
| echo '------------------------------------------------------------' |
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| """ | |
| 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'] |
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| # pip install pyscreenshot pyuserinput | |
| import pyscreenshot | |
| import pykeyboard | |
| import time | |
| X1 = 780 | |
| X2 = 785 | |
| Y1 = 410 | |
| Y2 = 420 |
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| from multiprocessing import Pool as pool | |
| from subprocess import Popen as run | |
| from os import listdir as ls | |
| # all files begining with this will be executed | |
| PREFIX = 'python_scripts_' | |
| # set for the number of cores you have | |
| THREADS = 4 |
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| <!DOCTYPE html> | |
| <html> | |
| <head> | |
| <meta charset="utf-8" /> | |
| <meta http-equiv="X-UA-Compatible" content="IE=edge"> | |
| <title>Grammarly - Type your text</title> | |
| <meta name="viewport" content="width=device-width, initial-scale=1"> | |
| <style> | |
| textarea { | |
| font-family: 'Trebuchet MS', 'Lucida Sans Unicode', 'Lucida Grande', 'Lucida Sans', Arial, sans-serif; |
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| # pip install pyuserinput | |
| import subprocess | |
| import sys | |
| import time | |
| import pykeyboard | |
| if len(sys.argv) > 1: | |
| ubiqui = sys.argv[1] |
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| import sys | |
| import pandas as pd | |
| import numpy as np | |
| from pandas.io import sql | |
| from sqlalchemy import create_engine | |
| from multiprocessing import Pool as pool | |
| from threading import Lock as lock | |
| # Get the data from CSV into a DataFrame | |
| df = pd.read_csv('../bases/clientes.csv', sep=';') |
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| #!/bin/bash | |
| docker run -d -p 8080:80 --name target hmlio/vaas-cve-2014-6271 | |
| cat << EOF | docker exec -i target bash | |
| export EXPLOIT="() { echo 'Hello from Shell'; }; echo 'This machine is vulnerable'" | |
| bash | |
| EOF |
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| docker run --name postgres \ | |
| -e POSTGRES_USER=pgadmin \ | |
| -e POSTGRES_PASSWORD=pgpasswd \ | |
| -e POSTGRES_DB=pgdb \ | |
| -v /my/own/datadir:/var/lib/postgresql/data \ | |
| -d postgres | |
| docker run --name mysql \ | |
| -e MYSQL_USER=myadmin \ |