Funcker

This is my little foray into the world of functional programming. I mean, I was sold when Curry was mentioned. I called it funcker - 'func' in functional, plus getting your head around fp can be a bit of a 'funcker'.

Functional programming is one of the original paradigms of computing. Then things moved more towards a physical representation of the world - Object Oriented. Like the circle of life, we are moving back towards the past.

Functions are fast and make good use of disc space. Bruce Lee said be like water. Well, the body is 76% water, yet we are so solid. The idea then is to loosen up, to flow, to become pure and dynamic.

If you have done much TDD (please do!) you will know that as the tests get more specific, the code gets more generic. Same principle here - make the functions generic.

Benefits of fp:

• modularise code, making it more reusable
• reduce the complexity of components
• data flows along a pipeline
• things less likely to break because there is no state or side effects

Nomenclature or Terminology or Symbolic Representations of Concepts

Function(al)

An expression related to an input or inputs. Of or relating to this

Mutable

Liable to change, from latin 'to change'

Immutable

Not changing

Pure

Not mixed, sound, free of contamination

Curry

Converting 1 function with n arguments into n functions each with 1 argument

Higher order function

A function that takes other functions as parameters

Reactive programming

Using the 'observable' pattern and treating things as streams and reacting to events in them

Declarative

Opposite of imperative, not specifying the exact procedure, using expressions, more like 'map, then filter, then reduce'

Imperative

'specially ordered', opposite of declarative, procedural, writing out everything specifically 'for loop over array, put result in another array, loop again and copy certain values, then loop again and calculate total'

Side effect

Changing something outside of itself

Decomposition

Decay, but more like breaking into component parts

Referential transparency

Given parameters should always return the same values. transparency because it is clear you get the same results, referential because of the parameters used

Expression

Anything that results in a value

State

The condition something is in at a particular time

Stateless

Not in a particular condition that persists

Arity

The number of arguments passed to a function. myFunc(1, 2, 3) has an arity of 3

List comprehension

Encapsulates the functionality of map and filter into for...of syntax

Chain(ing)

Being able to chain functions like a().b().c()

:: (Has type)

Standard notation for fp: function_name :: input_type -> value

Notation

There is a standard notation for functional programming worth covering first:

f :: input -> output

The 'f' is a function, the parameters for that function come after the '::' (or sometimes a single ':'). The '::' means 'has type'. The return value of the function comes after the comma, and the '->' is a function with its returning value. So this notation:

f :: number -> number

Becomes:

const add10 = (x) => x + 10;

Higher order functions

Functions are essentially objects, first class citizens, and can move around as such. Hence we have 'higher order' functions - functions that take other functions as parameters and/or return functions.

Arity

It is best practice that the number of parameters a function takes needs to be a maximum of two. A function really should do one thing and one thing only. Imagine how many branches there would be if a function got 3, 4, 5 or more parameters? That could indicate a complex function - not good.

Functions should do one thing and one thing only. They should not modify anything other than in its own scope.

Closure

The definition of a closure is 'a function object that has a reference to the variables in the context it was created in'.

Mutability

Functions should be pure. This could lead to problems when parameters are references to an object. If that object is changed within a function then a side effect results. Not good.

Monads

A monad is an object.

Functions in the 'funker' example

.curry

If you have ever used bind, then you are half way there. Currying is the same as bind, but applied in a different way. With bind a new function is returned with the 'this' parameter of the original function set to the first parameter of the bind function. This is partial application, and that is what currying is - partial application.

Currying takes 1 function with n arguments, and converts it to n functions with 1 argument. We can then create a function that already has most of the data it needs held in a closure, and then we can reuse it.

So instead of:

add(1, 2, 3, 4, 5, 6);

it becomes:

add(1)(2)(3)(4)(5)(6)

That looks a bit weird and not very useful. So to convert a function that usually takes multiple params:

let addToFifteen = funcker.curry(add, 1, 2, 3, 4, 5);
let addToThirty = funcker.curry(add, 10, 10, 10);
console.log(addToFifteen(15));  //30
console.log(addToThirty(15));  //45

.filter

Curried Array.filter

.get

So with imperative coding, to get an attribute for each object in an array we would have to write a for loop, then access the property. Then when we need to do it somewhere else we would write another for loop ...

Not with higher order functions. We simply want to 'get' a property. So we can pass this to a map or forEach like so:

[{ name: 'Billy', age: 42 }, { name: 'Bob', age: 24 }].map(funker.get('name'));

.only

Get a new object with only the fields specified in a space delimited string.

const getNameAge = only('name age');
const userObject = { name: 'Tad', age: 40, secret: 'shhh, don\'t tell anyone' };
console.log(getNameAge(userObject)); // { name: 'Tad', age: 40 }

.compose

Function composition: s: f1 => f2 => f3 => f1(f2(f3(s)))

Takes an array of functions and applies them in reverse order to the supplied value.

compose([f1, f2, f3], value) => f1(f2(f3(value)))