isaacs

echo 'export PATH=$HOME/local/bin:$PATH' >> ~/.bashrc
. ~/.bashrc
mkdir ~/local
mkdir ~/node-latest-install
cd ~/node-latest-install
curl http://nodejs.org/dist/node-latest.tar.gz | tar xz --strip-components=1
./configure --prefix=~/local
make install # ok, fine, this step probably takes more than 30 seconds...
curl https://www.npmjs.org/install.sh | sh

rdegges

sudo aptitude -y install nginx
cd /etc/nginx/sites-available
sudo rm default
sudo cat > jenkins
upstream app_server {
    server 127.0.0.1:8080 fail_timeout=0;
}

server {
    listen 80;

pauldix

# Optimized for writes, sort on read

# LVC
redis.hset("bonds|1", "bid_price", 96.01)
redis.hset("bonds|1", "ask_price", 97.53)
redis.hset("bonds|2", "bid_price", 95.50)
redis.hset("bonds|2", "ask_price", 98.25)
redis.sadd("bond_ids", 1)
redis.sadd("bond_ids", 2)

jacqui

# Optimized for writes, sort on read

# LVC
redis.hset("bonds|1", "bid_price", 96.01)
redis.hset("bonds|1", "ask_price", 97.53)
redis.hset("bonds|2", "bid_price", 95.50)
redis.hset("bonds|2", "ask_price", 98.25)
redis.sadd("bond_ids", 1)
redis.sadd("bond_ids", 2)

pksunkara

# vi: ft=dosini
[user]
	name = Pavan Kumar Sunkara
	email = [email protected]
	username = pksunkara
[core]
	editor = nvim
	whitespace = fix,-indent-with-non-tab,trailing-space,cr-at-eol
	pager = delta
[column]

mikeyk

#! /usr/bin/env python

import redis
import random
import pylibmc
import sys

r = redis.Redis(host = 'localhost', port = 6389)
mc = pylibmc.Client(['localhost:11222'])

entaroadun

Movies Recommendation:

• MovieLens - Movie Recommendation Data Sets http://www.grouplens.org/node/73
• Yahoo! - Movie, Music, and Images Ratings Data Sets http://webscope.sandbox.yahoo.com/catalog.php?datatype=r
• Jester - Movie Ratings Data Sets (Collaborative Filtering Dataset) http://www.ieor.berkeley.edu/~goldberg/jester-data/
• Cornell University - Movie-review data for use in sentiment-analysis experiments http://www.cs.cornell.edu/people/pabo/movie-review-data/

Music Recommendation:

• Last.fm - Music Recommendation Data Sets http://www.dtic.upf.edu/~ocelma/MusicRecommendationDataset/index.html

sgmurphy

/**
 * Create a web friendly URL slug from a string.
 *
 * Requires XRegExp (http://xregexp.com) with unicode add-ons for UTF-8 support.
 *
 * Although supported, transliteration is discouraged because
 *     1) most web browsers support UTF-8 characters in URLs
 *     2) transliteration causes a loss of information
 *
 * @author Sean Murphy <[email protected]>

nikic

Why objects (usually) use less memory than arrays in PHP

This is just a small post in response to [this tweet][tweet] by Julien Pauli (who by the way is the release manager for PHP 5.5). In the tweet he claims that objects use more memory than arrays in PHP. Even though it can be like that, it's not true in most cases. (Note: This only applies to PHP 5.4 or newer.)

The reason why it's easy to assume that objects are larger than arrays is because objects can be seen as an array of properties and a bit of additional information (like the class it belongs to). And as array + additional info > array it obviously follows that objects are larger. The thing is that in most cases PHP can optimize the array part of it away. So how does that work?

The key here is that objects usually have a predefined set of keys, whereas arrays don't:

klovadis

-- sets all fields for a hash from a dictionary 
local hmset = function (key, dict)
  if next(dict) == nil then return nil end
	local bulk = {}
	for k, v in pairs(dict) do
		table.insert(bulk, k)
		table.insert(bulk, v)
	end
	return redis.call('HMSET', key, unpack(bulk))
end