ChrisPenner

Optics By Example Cheat Sheets

The following are appendices from Optics By Example, a comprehensive guide to optics from beginner to advanced! If you like the content below, there's plenty more where that came from; pick up the book!

• Operators
• Composition Guide
• Substitution Guide
• Optical Constarints and Types

Operator Cheat Sheet

mmenestret

Purity and pure FP

• purity is a syntactical property of programs, more precisely defined as referential transparency: replacing an expression for its bound value doesn't change meaning (precise definition)
• side effects are things that break referential transparency (precise definition)
• There's no direct connection between the concepts of IO, State and so on, and side effects. Traditionally, these things are side effectful (break referential transparency), but you can have abstractions that are pure (don't break ref.trans.)
• Due to the above, the term purely functional programming is not an oxymoron, it makes perfect sense.
• In haskell style pure FP, type constructors and algebras are used to represent "things that would otherwise traditionally be side effects (break ref.trans.)". We call these F[_]s effects or computational contexts for brevity. You can see for yourself how this cannot be a precise definition (especially because they could also have kind higher than * -> *, even though most famous a

dsebban

Undertsanding the Pull type from fs2

From the scaladocs

class Stream[+F[_], +O] extends AnyVal

• A stream producing output of type O
• May evaluate F effects.

Daenyth

The problem

I have some data which has adjacent entries that I want to group together and perform actions on. I know roughly that fs2.Pull can be used to "step" through a stream and do more complicated logic than the built in combinators allow. I don't know how to write one though!

In the end we should have something like

def combineAdjacent[F[_], A](
 shouldCombine: (A, A) => Boolean,

davidkaste

-- roll.hs a dice rolling shell utility
-- David Castellà 'kaste' <hola@davidcastella.com>

import Data.List.Split
import Data.List
import Data.Char
import System.Random
import Control.Monad
import Control.Arrow
import Options.Applicative

rebcabin

In https://github.com/ekmett/lens/wiki/Derivation, we see some types for
composition of compositions: (.).(.), (.).(.).(.), and so on. Let's prove that
the type of (.).(.) is (a -> b) -> (c -> d -> a) -> c -> d -> b, as stated in
the site. We'll stick with prefix notation, meaning that we want the type of
(.)(.)(.).

Recall the type of composition. This should be intuitive:

  (.) :: (b -> c) -> (a -> b) -> a -> c                                      [1]

gaga5lala

# 1. Backup image tags to text file.
#    $ docker images --format "{{.Repository}}:{{.Tag}} {{.ID}}" > img_id.txt
#
# 2. Execute clean-docker-for-mac script
#    $ bash clean-docker-for-mac.sh $(docker images --format "{{.ID}}" | xargs)
#
#    source: https://gist.github.com/MrTrustor/e690ba75cefe844086f5e7da909b35ce#file-clean-docker-for-mac-sh 
#
# 3. Execute this script to restore tags from text file.

IGI-111

Category Theory for Programmers: The Preface

Table of Contents

Part One

MrTrustor

#!/bin/bash

# Copyright 2017 Théo Chamley
# Permission is hereby granted, free of charge, to any person obtaining a copy of 
# this software and associated documentation files (the "Software"), to deal in the Software
# without restriction, including without limitation the rights to use, copy, modify, merge,
# publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons
# to whom the Software is furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all copies or

jdegoes

Applied Functional Programming with Scala - Notes

Copyright © 2016-2018 Fantasyland Institute of Learning. All rights reserved.

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