ohanhi

Learning FP the hard way: Experiences on the Elm language

by Ossi Hanhinen, @ohanhi

with the support of Futurice 💚.

Licensed under CC BY 4.0.

Editorial note

14427

use std::rc::Rc;

trait HKT<U> {
    type C; // Current type
    type T; // Type with C swapped with U
}

macro_rules! derive_hkt {
    ($t:ident) => {
        impl<T, U> HKT<U> for $t<T> {

mpasternacki

FreeBSD on a MacBook Pro

Since 2008 or 2009 I work on Apple hardware and OS: back then I grew tired of Linux desktop (which is going to be MASSIVE NEXT YEAR, at least since 2001), and switched to something that Just Works. Six years later, it less and less Just Works, started turning into spyware and nagware, and doesn't need much less maintenance than Linux desktop — at least for my work, which is system administration and software development, probably it is better for the mythical End User person. Work needed to get software I need running is not less obscure than work I'd need to do on Linux or othe Unix-like system. I am finding myself turning away from GUI programs that I used to appreciate, and most of the time I use OSX to just run a terminal, Firefox, and Emacs. GUI that used to be nice and unintrusive, got annoying. Either I came full circle in the last 15 years of my computer usage, or the OSX experience degraded in last 5 years. Again, this is from a sysadmin/developer ki

sloria

The Best of the Best Practices (BOBP) Guide for Python

A "Best of the Best Practices" (BOBP) guide to developing in Python.

In General

Values

• "Build tools for others that you want to be built for you." - Kenneth Reitz
• "Simplicity is alway better than functionality." - Pieter Hintjens

ragingwind

Backend Architectures

Twitter

ror, scala, jetty, erlang, thrift, mongrel, comet server, my-sql, memchached, varnish, kestrel(mq), starling, gizzard, cassandra, hadoop, vertica, munin, nagios, awstats

• Introduce Gizzard of Twitter - 트위터의 새로운 분산 관리 라이브러리 Gizzard를 소개합니다.
• The Architecture Twitter Uses to Deal with 150M Active Users, 300K QPS, a 22 MB/S Firehose, and Send Tweets in Under 5 Seconds
• Scaling Twitter: Making Twitter 10000 Percent Faster

hellerbarde

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

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