luizhenriquefbb

# see gist of LogManager (https://gist.github.com/luizhenriquefbb/040124818a5c56ffba81d91929801be5)

def timeit(logger:LogManager=None):
    def decorator(function):
        def wrapper(*args, **kwargs):
            ts = time.time()
            result = function(*args, **kwargs)
            te = time.time()

            log_string = f'func:{function.__name__} args:[{args}, {kwargs}] took: {"{:.2f}".format(te-ts)} sec'

luizhenriquefbb

def lambda_handler(event, context):
    from concurrent.futures import ThreadPoolExecutor, as_completed

    def task(data):
        print(f"computing data {data}")

    with ThreadPoolExecutor(max_workers = 5) as executor:
        future_to_data = { executor.submit(task, data) : data for data in list(range(100)) }

        response = []

luizhenriquefbb

import functools
import threading
import time

def timed_memoized(time_to_reset: int = 300):
    """
    Decorator that caches a function's return value each time it is called.
    If called later with the same arguments, the cached value is returned, and
    not re-evaluated.

luizhenriquefbb

#!/usr/bin/python
# -*- coding: utf-8 -*-

import logging
import os
from logging.handlers import RotatingFileHandler


class LogManager:
    def __init__(self, log_name,

luizhenriquefbb

/**
 * This script expects the global variables 'refresh_token' and 'firebase_api_key' to be set. 'firebase_api_key' can be found
 * in the Firebase console under project settings then 'Web API Key'.
 * 'refresh_token' as to be gathered from watching the network requests to https://securetoken.googleapis.com/v1/token from 
 * your Firebase app, look for the formdata values
 * 
 * If all the data is found it makes a request to get a new token and sets a 'auth_jwt' environment variable and updates the 
 * global 'refresh_token'.
 * 
 * Requests that need authentication should have a header with a key of 'Authentication' and value of '{{auth_jwt}}'

luizhenriquefbb

Git deploy

English 🇺🇸

Deploy with Git

That is it! You read right. If you are building small applications and don't need to prepare a super complex environment to deploy it and just want to keep the code on an updated server, you can set up a bare repository on your remote machine and "listen" changes on the master. So, with a push, you can always update the code on the remote machine.

Step 1: Create the repository that will listen to the pushes on GIT and the folder where the files will be stored

luizhenriquefbb

Git deploy

English 🇺🇸

Deploy with Git

That is it! You read right. If you are building small applications and don't need to prepare a super complex environment to deploy it and just want to keep the code on an updated server, you can set up a bare repository on your remote machine and "listen" changes on the master. So, with a push, you can always update the code on the remote machine.

Step 1: Create the repository that will listen to the pushes on GIT and the folder where the files will be stored

luizhenriquefbb

import numpy as np

# Variável onde seu índice representa a posíção no labirinto
# E seu valor representa os possíveis lugares para se mover
# em outras palavras, a tabela de adjacencia
NOS = [
    [1],#nó 0
    [0, 2, 4, 3],#nó 1
    [1],#nó 2
    [1, 5],#nó 3

luizhenriquefbb

Install

yarn global add pm2

edit the file ~/.bashrc and add the following line in the end

export PATH=$(yarn global bin):$PATH

luizhenriquefbb

[MASTER]

# A comma-separated list of package or module names from where C extensions may
# be loaded. Extensions are loading into the active Python interpreter and may
# run arbitrary code.
extension-pkg-whitelist=

# Add files or directories to the blacklist. They should be base names, not
# paths.
ignore=CVS