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[zack@leto ~]$ sudo tee << EOF /etc/wpa_supplicant.conf > /dev/null
ctrl_interface=/run/wpa_supplicant
EOF
[zack@leto ~]$ sudo wpa_supplicant -iwlp1s0 -Dnl80211 -c/etc/wpa_supplicant.conf -B
Successfully initialized wpa_supplicant
[zack@leto ~]$ sudo wpa_cli
wpa_cli v2.0
Copyright (c) 2004-2012, Jouni Malinen <[email protected]> and contributors

This software may be distributed under the terms of the BSD license.

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Install Arch Linux on Mac mini

We will be creating dual boot for OS X and Linux with no special boot loader. For other setup, refer to [1]. We will keep all data on an external hard drive, so we do not need huge amount of space for the linux system. We will install from an USB thumb drive (will need at least 1GB in size), newer Minis do not have CD roms.

Prepare the disk in Mac OS X (El Capitan)

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import tensorflow as tf #We need tensorflow 2.x
import numpy as np

#The hashlength in bits
hashLength = 256

def buildModel():
    #we can set the seed to simulate the fact that this network is known and doesn't change between runs
    #tf.random.set_seed(42)
    model = tf.keras.Sequential()

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if(typeof(ArrayBuffer.prototype.transfer) === "undefined") {
	ArrayBuffer.prototype.transfer = function transfer(old) {
		var dva, dvb, i, mod;
		dva = new DataView(this);
		dvb = new DataView(old);
		mod = this.byteLength%8+1;
		for(i = 0; i <= old.byteLength-mod; i+=8) dva.setFloat64(i, dvb.getFloat64(i));
		mod = this.byteLength%4+1;
		if(i < old.byteLength-mod) {
			dva.setUint32(i, dvb.getUint32(i));

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function memcpy (src, srcOffset, dst, dstOffset, length) {
	var i

	src = src.subarray || src.slice ? src : src.buffer
	dst = dst.subarray || dst.slice ? dst : dst.buffer

	src = srcOffset ? src.subarray ?
		src.subarray(srcOffset, length && srcOffset + length) :
		src.slice(srcOffset, length && srcOffset + length) : src

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// This is free and unencumbered software released into the public domain.

// Marshals a string to an Uint8Array.
function encodeUTF8(s) {
	var i = 0, bytes = new Uint8Array(s.length * 4);
	for (var ci = 0; ci != s.length; ci++) {
		var c = s.charCodeAt(ci);
		if (c < 128) {
			bytes[i++] = c;
			continue;

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// data comes from here http://stat-computing.org/dataexpo/2009/the-data.html
// download 1994.csv.bz2 and unpack by running: cat 1994.csv.bz2 | bzip2 -d > 1994.csv
// 1994.csv should be ~5.2 million lines and 500MB
// importing all rows into leveldb took ~50 seconds on my machine

// there are two main techniques at work here:
// 1: never create JS objects, leave the data as binary the entire time (binary-split does this)
// 2: group lines into 16 MB batches, to take advantage of leveldbs batch API (byte-stream does this)

var level = require('level')

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import os
import sqlite3
from hashlib import md5
from time import time
import simplejson as json
from flask import Flask
from flask.ext import restful
from flask import g
from flask import request

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// Licensed under MIT license.
// (c) Lewin Bormann 2014

# include <string>
# include <iostream>
# include <list>
# include <cstring>
# include <algorithm>

using std::string;

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git fetch upstream
git reset --hard upstream/master