iaindooley

<?php
    /****
    * This script presents an "algorithmic" way of doing a cohort analysis
    * on your eCommerce customer database.
    *
    * This can be useful if you want to automate a lifetime value calculation
    * based on some data available from a CSV file, database or API.
    *
    * The specifics of how your eCommerce system stores this information is
    * abstracted out to a couple of objects with methods such as 

keyurdg

package main

import (
    "bufio"
	"bytes"
	_ "github.com/Go-SQL-Driver/MySQL"
	"database/sql"
	"flag"
	"fmt"
	"io"

binarybana

javascript:(function(e,a,g,h,f,c,b,d)%7Bif(!(f=e.jQuery)%7C%7Cg%3Ef.fn.jquery%7C%7Ch(f))%7Bc=a.createElement(%22script%22);c.type=%22text/javascript%22;c.src=%22http://ajax.googleapis.com/ajax/libs/jquery/%22+g+%22/jquery.min.js%22;c.onload=c.onreadystatechange=function()%7Bif(!b&&(!(d=this.readyState)%7C%7Cd==%22loaded%22%7C%7Cd==%22complete%22))%7Bh((f=e.jQuery).noConflict(1),b=1);f(c).remove()%7D%7D;a.documentElement.childNodes%5B0%5D.appendChild(c)%7D%7D)(window,document,%221.3.2%22,function($,L)%7B$('%23header,%20.pagehead,%20.breadcrumb,%20.commit,%20.meta,%20%23footer,%20%23footer-push,%20.wiki-actions,%20%23last-edit,%20.actions,%20.header').remove();%20$('%23files,%20.file').css(%7B%22background%22:%22none%22,%20%22border%22:%22none%22%7D);%20$('link').removeAttr('media');%7D);

tomnomnom

<?php
// An experiment: using traits for dependency injection

// A trait provides a way to inject a Logger and a way to use it
trait aLogger {
  protected $logger = null;
  public function setLogger(Logger $logger){
    $this->logger = $logger;
  }
  public function log($msg){

extraordinaire

<?php
class ReconnectingPDO
{
    protected $dsn, $username, $password, $pdo, $driver_options;
    
    public function __construct($dsn, $username = "", $password = "", $driver_options = array())
    {
        $this->dsn = $dsn;
        $this->username = $username;
        $this->password = $password;

morphizer

#!/usr/bin/env python

# Processes the files in the incoming directory for query analysis in anemometer
# Supply the db user/pass/host

import glob, os, shutil, sys
from subprocess import Popen

db_user = "anemometer"
db_pass = "password"

mardix

#!/usr/bin/php
<?php
/**
 * .git/hooks/pre-commit
 * 
 * This pre-commit hooks will check for PHP error (lint), and make sure the code
 * is PSR compliant.
 * 
 * Dependecy: PHP-CS-Fixer (https://github.com/fabpot/PHP-CS-Fixer)
 * 

liutaihua

#!/usr/bin/env python
# -*-mode: python; coding: iso-8859-1 -*-
#
# Copyright (c) Liu taihua <defage@gmail.com>

"""
Usage:
    [-h|--help] [-t interval=60] [-c cluster=Nanhui] [-H prefer=hostname|IP] [-v|--verbose True|False]

Example:

perusio

## From a post on the ML, apropos this: 
## http://lowlatencyweb.wordpress.com/2012/03/20/500000-requestssec-modern-http-servers-are-fast.
## For sysctl.conf

net.ipv4.tcp_slow_start_after_idle = 0


  echo "2048 64512" > /proc/sys/net/ipv4/ip_local_port_range
  echo "1" > /proc/sys/net/ipv4/tcp_tw_recycle
  echo "1" > /proc/sys/net/ipv4/tcp_tw_reuse

dspezia

OBJ = genload.o
BINS = genload

CC=g++
OPTIMIZATION?=-O3
CFLAGS?=$(OPTIMIZATION) $(ARCH) $(PROF) -I ../hiredis
CCLINK?=-pthread
LDFLAGS?=-L../hiredis -lhiredis -lm

OBJ = example.o