#10 good reasons to invest your time in FP

Humberto Streb @humbertostreb

Joel Corrêa @joelcorrea_

#1 Learn

#2 Parallel collections

Multicore powered Parallel collections

F#

Collection operations: Map - Reduce

Map –> Applies a given fn to each element

Reduce –> Combine / Accumulate /

fold / compress results though combining operation

Higher order functions

Sample

Map

20 18 41 25 29 32 30 38

age

Map

Reduce

20 18

236

25 44 29 32 …

Combining fn: a+b (operation = +)

+ Data

Map age Map age Map age Map age

map in parallel

reduce in parallel

filter in parallel

#3 Focus

Boilerplate code

REPL

#4 Troubleshooting

Same result value given the same

arguments

Troubleshooting in FP

Consistency

Once wrong, always wrong

Arguments only

No global state

Referential transparency

#5 State discipline

Side effects…

Pure function

Immutable It is highly recommended that value objects be immutable. They are created with a constructor, and never modified during their life time. Eric Evans

Immutable

Immutable

#6 Built-ins

Non-Blocking

Futures

Parallel

Null checks

Optionals

Explicit

Interoperability

#8 Simplicity

#7 Simplicity

#8 Simplicity

Salesmen…

#8 Simplicity

#8 Composition

# Building blocks

Inheritance

Polymorphism

HOFs

Composition

OOP = Objects

FP = Functions

Real world / Complex scenarios  

# HOFs

Receives fn

# Partially applied

Returns fn

# Composition

#9 Testability

if($player->getScore() > 0) {!!$player->setSwizzle(7);!

} else {!!$player->setSwizzle(!! !$player->getSwizzle() + 1;!!);!

}!

Hard to test

#10 Principles

FP in non-FP languages

Guidelines

Side effects

Immutability

Referen'al  transparency  

FP in non-FP languages

functools

LuaFun

# Challenges ahead

Readability / Expressiveness

Learning curve

Samples

https://github.com/jjcorrea/TenGoodReasonsToInvestYourTimeInFP

Resources

http://twitter.github.io/scala_school/ http://twitter.github.io/effectivescala http://coursera.org/course/progfun