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Haskell Design Patterns

By : Lemmer

4.1 (9)

Haskell Design Patterns

4.1 (9)

By: Lemmer

Overview of this book

Design patterns and idioms can widen our perspective by showing us where to look, what to look at, and ultimately how to see what we are looking at. At their best, patterns are a shorthand method of communicating better ways to code (writing less, more maintainable, and more efficient code) This book starts with Haskell 98 and through the lens of patterns and idioms investigates the key advances and programming styles that together make "modern Haskell". Your journey begins with the three pillars of Haskell. Then you'll experience the problem with Lazy I/O, together with a solution. You'll also trace the hierarchy formed by Functor, Applicative, Arrow, and Monad. Next you'll explore how Fold and Map are generalized by Foldable and Traversable, which in turn is unified in a broader context by functional Lenses. You'll delve more deeply into the Type system, which will prepare you for an overview of Generic programming. In conclusion you go to the edge of Haskell by investigating the Kind system and how this relates to Dependently-typed programming

Preface

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Free Chapter

1. Functional Patterns – the Building Blocks

1. Functional Patterns – the Building Blocks

Higher-order functions

Currying functions

Recursion

Types, pattern matching, and polymorphism

Lazy evaluation

Monads

Summary

2. Patterns for I/O

2. Patterns for I/O

I/O as a first class citizen

Imperative I/O

Lazy I/O

The problems with lazy I/O

Resource management with bracket

Iteratee I/O

Summary

3. Patterns of Composition

3. Patterns of Composition

Functor

Applicative functor

Monad

Monad transformers

Arrows

Summary

4. Patterns of Folding and Traversing

4. Patterns of Folding and Traversing

Folding over lists

Summary

5. Patterns of Type Abstraction

5. Patterns of Type Abstraction

Abstracting function types: RankNTypes

Abstracting datatypes

Abstracting type-classes

Summary

6. Patterns of Generic Programming

6. Patterns of Generic Programming

Patterns of generic programming

The sum of products style

Origami programming

Scrap your boilerplate

Summary

7. Patterns of Kind Abstraction

7. Patterns of Kind Abstraction

Higher-order kinds

Higher-kinded polymorphism

Associated type synonyms

Type (synonym) families

Kind polymorphism

Type promotion

Type-level programming

Dependently-typed programming

Summary

Epilogue

Index

Index

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Abstracting function types: RankNTypes

Consider the higher order function that maps the argument function to each tuple element:

  tupleF elemF (x, y) = (elemF x, elemF y)

Left to its own devices, the Haskell 98 compiler will infer this type for a tupleF function:

  tupleF :: (a -> b) -> (a, a) -> (b, b)

As elemF is applied to x and y, the compiler assumes that x and y must be of the same type, hence the inferred tuple type (a,a). This allows us to do the following:

  tupleF length ([1,2,3], [3,2,1])
  tupleF show (1, 2)
  tupleF show (True, False)

However, not this:

  tupleF show (True, 2)
  tupleF length ([True, False, False], [1, 2, 4])

RankNTypes allow us to enforce parametric polymorphism explicitly. We want tupleF to accept a polymorphic function of arguments; in other words, we want our function to have a "higher rank type", in this case Rank 2:

{-# LANGUAGE Rank2Types #-}

tupleF' :: (Show a1, Show a2) => 
  (forall a . Show a => a -> b) -- elemF
    -&gt...

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