Diego Lanciotti cosme12

Hardware specs

Chinese Brand "ITworks" , Model TW891, distributed in France and Belgium by Darty

CPU: Intel(R) Atom(TM) CPU Z3735F @ 1.33GHz
Video: Intel® HD Graphics for Intel Atom® Processor Z3700 Series
Screen: 1280x800
WiFi + BT: Realtek RTL8723BS_BT
Disks: mmcblk1: mmc1:0001 DF4032 29.1 GiB
RAM: 2GB DDR3 @ 1333 MHz

We played generals.io over the weekend. It gives some solid adrenaline rushes but we are prob going to take a break from it due to that and other priorities.

Quick tips:

Use click + WASD to queue up traversals quickly (on your own squares you can chain it multiple times)
Cities repopulate if not fully captured, be sure to have +2 to city count (1 for wipe out, 1 for move in)

Here is what we learned as some strategies:

In 1v1, maps are set up with generals at 2 sides (e.g. North/South, East/West, Northwest/Southeast)

	"""
	helloevolve.py implements a genetic algorithm that starts with a base
	population of randomly generated strings, iterates over a certain number of
	generations while implementing 'natural selection', and prints out the most fit
	string.

	The parameters of the simulation can be changed by modifying one of the many
	global variables. To change the "most fit" string, modify OPTIMAL. POP_SIZE
	controls the size of each generation, and GENERATIONS is the amount of
	generations that the simulation will loop through before returning the fittest

	import gym
	import numpy as np
	import random
	import math
	from time import sleep


	## Initialize the "Cart-Pole" environment
	env = gym.make('CartPole-v0')

	import requests
	import subprocess
	import json
	import sys
	import threading
	import time
	from Queue import Queue
	import urllib3
	import urllib3.contrib.pyopenssl

	from flask import Flask, request
	from nameko.standalone.rpc import ServiceRpcProxy

	app = Flask(__name__)


	@app.route('/')
	def task_list():
	return """
	<html>

	--3demo
	--simple 3d demo

	-- Here is the data for the 3d model
	-- The first section is the 3d location
	-- of each point on the cube, and the
	-- second section is the lines that
	-- connect the points
	cube = {{{-1,-1,-1}, -- points
	{-1,-1,1},

	'''
	You should try libtorrent (rasterbar). http://libtorrent.org
	If you want to write your client in python, on linux, install it with:

	sudo apt-get install python-libtorrent

	A very simple example of python code to use it to download a torrent:
	'''

	import libtorrent as lt

	<?php
	/**
	* Plugin Name: My Facebook Tags
	* Plugin URI: http://danielpataki.com
	* Description: This plugin adds some Facebook Open Graph tags to our single posts.
	* Version: 1.0.0
	* Author: Daniel Pataki
	* Author URI: http://danielpataki.com
	* License: GPL2
	*/