tmm1

##
# sync api: return values and exceptions

begin
  images = []

  results = RestClient.get('http://google.com/search?q=ruby')
  Hpricot(results).find('a').each{ |link|
    page = RestClient.get(link)
    begin

adamwiggins

module Heroku
class StaticAssetsMiddleware
	def initialize(app)
		@app = app
	end

	def call(env)
		# call returns an array containing [response code, header, Rack::Response]
		reply = @app.call(env)

gilles

#trace mongo in RPM
Mongo::Collection.class_eval do
  include NewRelic::Agent::MethodTracer
  add_method_tracer :find
  add_method_tracer :find_one
  add_method_tracer :find_and_modify
  add_method_tracer :update
  add_method_tracer :insert
  add_method_tracer :save
  add_method_tracer :remove

pivotalneutron

# When resque workers are no longer around, but records of them are still sitting around in Redis...

def remove_resque_workers worker, ips
  ips.each do |ip|
    eval("
      def worker.to_s
        '#{ip}:*'
      end
    ")
    worker.unregister_worker

PatrickTulskie

# inspired by http://ariejan.net/2010/08/23/resque-how-to-requeue-failed-jobs

# retry all failed Resque jobs except the ones that have already been retried
# This is, for instance, useful if you have already retried some jobs via the web interface.
Resque::Failure.count.times do |i|
  Resque::Failure.requeue(i) unless Resque::Failure.all(i, 1)['retried_at'].present?
end

# retry all :)
Resque::Failure.count.times do |i|

igor-alexandrov

class Settings < Settingslogic
  source "#{Rails.root}/config/application.yml"
  
  if Rails.env == 'development'
    namespace 'development-' + Socket.gethostname.gsub(/\W/, '-').gsub(/[-]{2,}/, '-')
  else
    namespace Rails.env
  end
      
  # load local settings

coldnebo

  { "keys": ["home"], "command": "move_to", "args": {"to": "bol"} },
  { "keys": ["end"], "command": "move_to", "args": {"to": "eol"} }

jboner

Latency Comparison Numbers (~2012)
----------------------------------
L1 cache reference                           0.5 ns
Branch mispredict                            5   ns
L2 cache reference                           7   ns                      14x L1 cache
Mutex lock/unlock                           25   ns
Main memory reference                      100   ns                      20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy             3,000   ns        3 us
Send 1K bytes over 1 Gbps network       10,000   ns       10 us
Read 4K randomly from SSD*             150,000   ns      150 us          ~1GB/sec SSD

czarneckid

Zero downtime deploys with unicorn + nginx + runit + rvm + chef

Below are the actual files we use in one of our latest production applications at Agora Games to achieve zero downtime deploys with unicorn. You've probably already read the GitHub blog post on Unicorn and would like to try zero downtime deploys for your application. I hope these files and notes help. I am happy to update these files or these notes if there are comments/questions. YMMV (of course).

Other application notes:

• Our application uses MongoDB, so we don't have database migrations to worry about as with MySQL or postgresql. That does not mean that we won't have to worry about issues with the database with indexes being built in MongoDB or what have you.
• We use capistrano for deployment.

Salient points for each file:

dopiaza

#!/bin/bash

# Usage: slackpost <token> <channel> <message>

# Enter the name of your slack host here - the thing that appears in your URL:
# https://slackhost.slack.com/
slackhost=PUT_YOUR_HOST_HERE

token=$1