λFunctional Programming

Who am I?• Ryan Riley• Catapult Systems Houston• Blog: http://wizardsofsmart.net• GitHub: http://github.com/panesofglass• Twitter: @panesofglass

Agenda1. Functional Programming Concepts2. Func’y C#3. Resources

1. Functional Programming Concepts

Functional programmin

g is just a style.

Treat functions as

values.

What is a function?

A function, as in math.(In particular, as in lambda calculus.)

((Ask Jeff Odell.))

Follow the Arrows

• add x y has a type of int -> int -> int• In C#, this could be Func<int, int,

int>

• (Actually, that’s Func<int,<Func<int, int>>>. We’ll see why in a moment….)

Functions are values, too.

• .NET 1.0 => delegates• .NET 2.0 => anonymous delegates

+ generics• .NET 3.0 => lambdas• Higher-order functions accept a

function as a parameter.

ImmutabilityFunctions take an input and return a result

NO side effects!

NO state!

NO I/O!

Imag

e f

rom

One Y

ear

Bib

le B

log

Implications• Recursion• Persistent data structures

What?

How?

Paradigm-shift

Declarativevs.

Imperative

Advantages• Very easy to reason about• Concurrency friendly• Easy to compose:

doubleSq x = square(double(x))doubleSq = double . square

• Foundation of Domain Specific Languages

Disadvantages

• Too much recursion can overflow the stack (without tail-call optimization, or TCO)

• High memory consumption from creating so many objects …

However,

Referential transparency• Replace a function with its value• Efficiency with caching (a.k.a.

memoization)

• Easier for programmers to understand• ∴ Easier to reuse and test

So what?• Moore’s Law is failing.• Multiple CPUs / cores is the future.• Controlling mutable state in

concurrency is very hard …unless you have no mutable state!

Also,“Mock objects and dependency injection are just for people who don’t know math.”

*~ Erik Meijer, Microsoft

* See the Silverlight Toolkit for test examples.

2. Play that Func’y Music

C#

Func & Action

• Define your functions.• Generics are important.• Type-safety over many types.

Lists everywhere!• Functional languages like Lisp build

entirely on lists and maps (i.e. Dictionaries).

• Feel like you’ve seen this before?

Als

o

by

Eri

k M

eijer

!

LINQ!• Implementation of common functional

programming functions over lists via IEnumerable.

• Select => map• Where => filter• Aggregate => fold / reduce• SelectMany => bind / fmap, or “map then

flatten”

This means you are probably already using

FP!

Take it further

• Functions as data• Closures => Capture external state

for later• Currying + Partial application =>

Reduce dependencies• Memoization => Run it again later

DemoCurrying and Partial application

Make it concurrent

• Task Parallel Library (PFx)• Reactive Extensions (Rx)• PLinq => Parallel LINQ

DemoConcurrency

What didn’t we cover?

• Many more functional operators (LINQ)• Managing mutable state from the

environment• LINQ to Observables, Continuations, etc.• The “M” word

3. Resources

Books ‘n Blogs

• Real-World Functional Programming• PFx Team Blog• Rx Team Blog• Matthew Podwysocki’s Weblog

Libraries• Functional C#• Reactive Extensions (Rx)

Videos• Functional Programming Fundament

als

(Channel 9 Lecture Series)

Languages

More F# => http://c4fsharp.groups.live.comMore Clojure and IronScheme =>

http://hdlug.groups.live.com

Questions?