Corey Reece corey

Clojure Destructuring Tutorial and Cheat Sheet

Simply put, destructuring in Clojure is a way extract values from a datastructure and bind them to symbols, without having to explicitly traverse the datstructure. It allows for elegant and concise Clojure code.

Vectors and Sequences

Channels Are Not Enough

... or Why Pipelining Is Not That Easy

Golang Concurrency Patterns for brave and smart.

By @kachayev

Intro

Mac OS X 10.10 Yosemite

Custom recipe to get OS X 10.10 Yosemite running from scratch, setup applications and developer environment. I use this gist to keep track of the important software and steps required to have a functioning system after a semi-annual fresh install. On average, I reinstall each computer from scratch every 6 months, and I do not perform upgrades between distros.

This keeps the system performing at top speeds, clean of trojans, spyware, and ensures that I maintain good organizational practices for my content and backups. I highly recommend this.

You are encouraged to fork this and modify it to your heart's content to match your own needs.

Install Software

2015-01-29 Unofficial Relay FAQ

Compilation of questions and answers about Relay from React.js Conf.

Disclaimer: I work on Relay at Facebook. Relay is a complex system on which we're iterating aggressively. I'll do my best here to provide accurate, useful answers, but the details are subject to change. I may also be wrong. Feedback and additional questions are welcome.

What is Relay?

Relay is a new framework from Facebook that provides data-fetching functionality for React applications. It was announced at React.js Conf (January 2015).

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

Regular Expression Engine Comparison Chart

Many different applications claim to support regular expressions. But what does that even mean?

Well there are lots of different regular expression engines, and they all have different feature sets and different time-space efficiencies.

The information here is just copied from: http://regular-expressions.mobi/refflavors.html

This document has moved!

It's now here, in The Programmer's Compendium. The content is the same as before, but being part of the compendium means that it's actively maintained.

Since it has come up a few times, I thought I’d write up some of the basic ideas around domain modeling in Clojure, and how they relate to keyword names and Specs. Firmly grasping these concepts will help us all write code that is simpler, cleaner, and easier to understand.

Clojure is a data-oriented language: we’re all familiar with maps, vectors, sets, keywords, etc. However, while data is good, not all data is equally good. It’s still possible to write “bad” data in Clojure.

“Good” data is well defined and easy to read; there is never any ambiguity about what a given data structure represents. Messy data has inconsistent structure, and overloaded keys that can mean different things in different contexts. Good data represents domain entities and a logical model; bad data represents whatever was convenient for the programmer at a given moment. Good data stands on its own, and can be reasoned about without any other knowledge of the codebase; bad data is deeply and tightly coupled to specific generating and

	(defmulti transmogrify
	"Rewrites the last form of a thread-last to use transducer (if possible)."
	(fn [f xform src & args] f))

	(defmacro transmogrify->>
	"Like ->> but uses transducers"
	([x] x)
	([src & xs]
	(let [end (last xs)
	xforms (butlast xs)