coatl

=begin
endless.rb is a pre-processor for ruby which allows you to use python-ish 
indentation to delimit scopes, instead of having to type 'end' every time.

Basically, this makes the end keyword optional. If you leave off the
end, the preprocessor inserts an end for you at the next line indented
at or below the level of indentation of the line which started the scope.

End is optional, so you can still write things like this:
  begin

gus

For each Ruby module/class, we have Ruby methods on the left and the equivalent
Clojure functions and/or relevant notes are on the right.

For clojure functions, symbols indicate existing method definitions, in the 
clojure namespace if none is explicitly given.  clojure.contrib.*/* functions can
be obtained from http://github.com/kevinoneill/clojure-contrib/tree/master,
ruby-to-clojure.*/* functions can be obtained from the source files in this
gist.

If no method symbol is given, we use the following notation:

eculver

// origin: http://www.google.com/support/forum/p/Chrome/thread?tid=1a37ccbdde5902fd&hl=en

javascript:
timeout=prompt("Set timeout [s]");
current=location.href;
if(timeout>0)
  setTimeout('reload()',1000*timeout);
else
  location.replace(current);
function reload(){

DmitrySoshnikov

# "Understanding Python's closures".
#
# Tested in Python 3.1.2
#
# General points:
#
#    1. Closured lexical environments are stored
#       in the property __closure__ of a function
#
#    2. If a function does not use free variables

nyuichi

(use srfi-13)

(define (token type data)
  (cons type data))

(define (normalize source)
  (let loop ([acc ()]
	     [dat (string-split source #\newline)])
    (cond [(null? dat)
	   (string-join (reverse acc) #\newline)]

kennethreitz

#!/usr/bin/env python
# -*- coding: utf-8 -*-

import urllib2

gh_url = 'https://api.github.com'

req = urllib2.Request(gh_url)

password_manager = urllib2.HTTPPasswordMgrWithDefaultRealm()

kmizu

フォローしておいた方がいいようなScalaエンジニア(海外勢/日本人)のTwitterアカウント

概要

海外勢/日本人のScala(エンジニア/ユーザ)の中で、特にフォローしておくといい方のTwitterアカウントを集めてみました。作成途中なので、突っ込み歓迎。fork歓迎。

海外

• @robey Twitterの中の人。ScalaによるメッセージキューKestrelを作ったのもこの人。
• @n8han 今話題のhttpツールキットUnfilteredの作者。NYのScalaエンジニアの中でも有名人。他にも、conscriptを初めとして、多数のプログラムを開発している。詳細は彼のgithub アカウント 参照。

chitchcock

Stevey's Google Platforms Rant

I was at Amazon for about six and a half years, and now I've been at Google for that long. One thing that struck me immediately about the two companies -- an impression that has been reinforced almost daily -- is that Amazon does everything wrong, and Google does everything right. Sure, it's a sweeping generalization, but a surprisingly accurate one. It's pretty crazy. There are probably a hundred or even two hundred different ways you can compare the two companies, and Google is superior in all but three of them, if I recall correctly. I actually did a spreadsheet at one point but Legal wouldn't let me show it to anyone, even though recruiting loved it.

I mean, just to give you a very brief taste: Amazon's recruiting process is fundamentally flawed by having teams hire for themselves, so their hiring bar is incredibly inconsistent across teams, despite various efforts they've made to level it out. And their operations are a mess; they don't real

matope

#NoSQLデータモデリング技法

原文：NoSQL Data Modeling Techniques « Highly Scalable Blog

I translated this article for study. contact matope[dot]ono[gmail] if any problem.

NoSQLデータベースはスケーラビリティ、パフォーマンス、一貫性といった様々な非機能要件から比較される。NoSQLのこの側面は実践と理論の両面からよく研究されている。ある種の非機能特性はNoSQLを利用する主な動機であり、NoSQLシステムによく適用されるCAP定理がそうであるように分散システムの基本的原則だからだ。一方で、NoSQLデータモデリングはあまり研究されておらず、リレーショナルデータベースに見られるようなシステマティックな理論に欠けている。本稿で、私はデータモデリングの視点からのNoSQLシステムファミリーの短い比較といくつかの共通するモデリングテクニックの要約を解説したい。

本稿をレビューして文法を清書してくれたDaniel Kirkdorfferに感謝したいと思う

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