• Functional programming is a programming paradigm

programming paradigm: a style of building and structuring code

• Other examples of programming paradigms:

  • object-oriented: code is grouped together with the state it modifies (e.g. all methods relating to a car's functionality are grouped with the properties of the car)
  • imperative: describe what the computer should do (like a recipe - first do this, then do that)
  • declarative: describe what should happen, and let the compiler figure out how to do it (e.g. SQL: select * from orders where order_type in ("EQUITY", "FIXED_INCOME"))

As you can see, these are hard to define, and not mutually exclusive.

• C++ and Java are both imperative and object oriented
• OCaml is both object oriented and functional
• C is imperative but not object oriented

Examples of functional programming languages:

• the LISP family (lisp, scheme, Clojure, ClojureScript)
• the ML family (Standard ML, OCaml)
• Haskell
• Erlang
• Elixir
• Elm
• Rust

Many programming languages are multi-paradigm and support functional programming:

• Scala
• Java 8
• C++11
• F#
• Python
• JavaScript!

1. First class functions

• can be used the same way you would use any other value
• e.g. bind them to variables, pass them as arguments to other functions

2. Immutability

• application state cannot be mutated
• e.g. if you want to update the contents of an array, you have to reassign it to a new variable

3. Expression-oriented programming

• preferences for expressions vs statements:

  • expressions evaluate to a value
  • i.e., have a non-null return type
  • e.g. const sortedList = sort(unsortedList);

• statements do not evaluate to a value

  • Consider this line of code: list.sort();
  • it sorts the list and updates the state internally, but the result of the computation is not returned
  • this is called a side effect

• In functional programming, we try to eliminate side effects as much as possible

  • as much as possible, we try to write pure functions
  • pure function: a function in which the return value is wholly determined by its input values

• Of course, this isn't always possible. Sometimes we have side effects:

  • AJAX requests
  • printing to the console
  • manipulating the DOM

1. Scalability

• Moore's law is faltering
  • Prediction: the number of transistors on a chip will double every two years
  • Implication: computational speed can double every two years
  • Physics puts a limit on these trends, and we're running up against this limit

Ref: Herb Sutter

• Implication: the need to scale horizontally

  • Multi-core processors
  • Distributed computing

• Algorithms need to be able to scale across multiple processors or even multiple servers

  • Shared state makes this difficult!
  • Functional programming is well-suited to this
  • E.g. Hadoop

2. Easier to read and debug

"Code is read more often than it is written."

~ Guido Van Rossum, Creator of Python

• Functional programs are easier for human beings to read
  • no need to mentally keep track of state changes
  • fewer bugs, more effective code reviews

"You can’t pay people enough to carefully debug boring boilerplate code. I’ve tried"

~ Yaron Minsky, Chief Architect, Jane Street

3. Easier to unit test

• Pure functions require the output to be wholly determined by the inputs
• No complex object structures to mock
• This is simple to unit test!

4. Allows us to implement reactive programming

• Well suited to the pattern of When x happens, do y
• More on this in the future

5. JavaScript is functional!

"JavaScript is LISP in C's Clothing"

~ Douglas Crockford, co-architect of JavaScript

1. Map
2. Filter
3. Reduce
4. Partial Functions