Emrys Ingersoll wemrysi

Applied Functional Programming with Scala - Notes

1. Mastering Functions

A function is a mapping from one set, called a domain, to another set, called the codomain. A function associates every element in the domain with exactly one element in the codomain. In Scala, both domain and codomain are types.

val square : Int => Int = x => x * x

What is the appeal of dynamically-typed languages?

Kris Nuttycombe asks:

I genuinely wish I understood the appeal of unityped languages better. Can someone who really knows both well-typed and unityped explain?

I think the terms well-typed and unityped are a bit of question-begging here (you might as well say good-typed versus bad-typed), so instead I will say statically-typed and dynamically-typed.

I'm going to approach this article using Scala to stand-in for static typing and Python for dynamic typing. I feel like I am credibly proficient both languages: I don't currently write a lot of Python, but I still have affection for the language, and have probably written hundreds of thousands of lines of Python code over the years.

Git DMZ Flow

I've been asked a few times over the last few months to put together a full write-up of the Git workflow we use at RichRelevance (and at Precog before), since I have referenced it in passing quite a few times in tweets and in person. The workflow is appreciably different from GitFlow and its derivatives, and thus it brings with it a different set of tradeoffs and optimizations. To that end, it would probably be helpful to go over exactly what workflow benefits I find to be beneficial or even necessary.

Two developers working on independent features must never be blocked by each other
- No code freeze! Ever! For any reason!
A developer must be able to base derivative work on another developer's work, without waiting for any third party
Two developers working on inter-dependent features (or even the same feature) must be able to do so without interference from (or interfering with) any other parties
Developers must be able to work on multiple features simultaneously, or at lea

Introduction to scalaz-stream

Every application ever written can be viewed as some sort of transformation on data. Data can come from different sources, such as a network or a file or user input or the Large Hadron Collider. It can come from many sources all at once to be merged and aggregated in interesting ways, and it can be produced into many different output sinks, such as a network or files or graphical user interfaces. You might produce your output all at once, as a big data dump at the end of the world (right before your program shuts down), or you might produce it more incrementally. Every application fits into this model.

The scalaz-stream project is an attempt to make it easy to construct, test and scale programs that fit within this model (which is to say, everything). It does this by providing an abstraction around a "stream" of data, which is really just this notion of some number of data being sequentially pulled out of some unspecified data source. On top of this abstraction, sca

	#!/usr/bin/env bash
	#
	# Dependencies:
	# coursier ( on OSX: brew install --HEAD paulp/extras/coursier )
	# zinc ( on OSX: brew install zinc )
	#

	set -euo pipefail

	# You can compile code in different projects by overriding these, e.g.

	_hashCode java/lang/Object.hashCode()I
	_getClass java/lang/Object.getClass()Ljava/lang/Class;
	_clone java/lang/Object.clone()Ljava/lang/Object;
	_dabs java/lang/Math.abs(D)D
	_dsin java/lang/Math.sin(D)D
	_dcos java/lang/Math.cos(D)D
	_dtan java/lang/Math.tan(D)D
	_datan2 java/lang/Math.atan2(DD)D
	_dsqrt java/lang/Math.sqrt(D)D
	_dlog java/lang/Math.log(D)D

	-- A port of: http://semantic-domain.blogspot.com/2015/03/abstract-binding-trees.html

	{-# LANGUAGE DeriveFunctor #-}

	module ABT where

	import qualified Data.Foldable as Foldable
	import Data.Foldable (Foldable)
	import Data.Set (Set)
	import qualified Data.Set as Set

	(* -- mode: ocaml; -- *)

	module type FUNCTOR = sig
	type 'a t
	val map : ('a -> 'b) -> 'a t -> 'b t
	end

	type 'a monoid = {unit : 'a ; join : 'a -> 'a -> 'a}

	type var = string

	# Edit this configuration file to define what should be installed on
	# your system. Help is available in the configuration.nix(5) man page
	# and in the NixOS manual (accessible by running ‘nixos-help’).

	{ config, pkgs, ... }:

	{
	imports =
	[ # Include the results of the hardware scan.
	./hardware-configuration.nix

	keycode 97 = grave asciitilde
	keycode 132 = grave asciitilde