leepro

// $ 6g echo.go && 6l -o echo echo.6
// $ ./echo
//
//  ~ in another terminal ~
//
// $ nc localhost 3540

package main

import (

leepro

Selenium with Python

Author:	Baiju Muthukadan
Email:	baiju.m.mail AT gmail.com
Version:	0.5.0

leepro

Latency numbers every programmer should know

L1 cache reference ......................... 0.5 ns
Branch mispredict ............................ 5 ns
L2 cache reference ........................... 7 ns
Mutex lock/unlock ........................... 25 ns
Main memory reference ...................... 100 ns             
Compress 1K bytes with Zippy ............. 3,000 ns  =   3 µs
Send 2K bytes over 1 Gbps network ....... 20,000 ns  =  20 µs
SSD random read ........................ 150,000 ns  = 150 µs

Read 1 MB sequentially from memory ..... 250,000 ns = 250 µs

leepro

/*
   PC Emulator

   Copyright (c) 2011 Fabrice Bellard

   Redistribution or commercial use is prohibited without the author's
   permission.
*/
"use strict";
var aa = [1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 0, 1, 0, 0, 1];

leepro

1. General Background and Overview

• Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
• Models and Issues in Data Stream Systems
• Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
• Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
• [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep

leepro

function  elementToObject(element, o) {
    var el = $(element);
    var o =  { 
       tagName: el.tagName
    };
    var i = 0;
    for (i ; i < el.attributes.length; i++) {
        o[el.attributes[i].name] = el.attributes[i].value;
    }

leepro

#!/bin/bash

function wait4tcp () {
    local nc opt silence op host port ret failed limit tries
    local OPTIND OPTARG

    limit=100
    op="open"

    while getopts ":csw:" opt; do

leepro

from time import sleep
from tornado.httpserver import HTTPServer
from tornado.ioloop import IOLoop
from tornado.web import Application, asynchronous, RequestHandler
from multiprocessing.pool import ThreadPool

_workers = ThreadPool(10)

def run_background(func, callback, args=(), kwds={}):
    def _callback(result):

leepro

#!/usr/bin/env python

## Tiny Syslog Server in Python.
##
## This is a tiny syslog server that is able to receive UDP based syslog
## entries on a specified port and save them to a file.
## That's it... it does nothing else...
## There are a few configuration parameters.

LOG_FILE = 'youlogfile.log'

leepro

// Use Gists to store code you would like to remember later on
console.log(window); // log the "window" object to the console