No one in the brief history of computing has ever written a piece of perfect software. It's unlikely that you'll be the first

Andy Hunt

Programming Safely With types

Ian Thomas | @anatomic

Does JavaScript Have Types?

(And can they be safe?)

JavaScript's Types

  • Undefined
  • Null
  • Boolean
  • String
  • Number
  • Object
  • Symbol

What is safety?

What are the most frequently reported errors in JavaScript applications?

In computer science, type safety is the extent to which a programming language discourages or prevents type errors.

Wikipedia

The behaviours classified as type errors [..] are usually those that result from attempts to perform operations on values that are not of the appropriate data type

Wikipedia

Static vs Dynamic; Strong vs weak

Spot the difference

const a = null;
a.prop; // #1

const b = undefined;
b.prop; // #2

What happens at 1 and 2?

  1. πŸ’₯ TypeError: Cannot read property 'prop' of null πŸ’₯
  2. Silently fails, returns undefined

Which is Interesting because...

> typeof null
'object'

πŸ™ˆ

Getting the first item from an array

What should we return...

  • When the input is an array of > 0 items?
  • When the input is an empty array?
  • When the input is not an array?

the happy path is obvious, but what about the failure branch(es)?

Null, undefined or false?

accessing data nested in objects

const a = { a: { b: { c: [1, 2, 3] } } };
const b = { a: { b: { c: undefined } } };

const sumC = data => {
  // what goes in here?
};
const a = { a: { b: { c: [1, 2, 3] } } };
const b = { a: { b: { c: undefined } } };

const add = (a, b) => a + b;
const sumC = data => data.a.b.c.reduce(add, 0);

sumC(a); // 6
sumC(b); // ?

A naive approach

TypeError: Cannot read property 'reduce' of null

How can we improve this code?

const a = { a: { b: { c: [1, 2, 3] } } };
const b = { a: { b: { c: undefined } } };

const add = (a, b) => a + b;
const sumC = data => {
    if (data.a.b.c && Array.isArray(data.a.b.c)) {
        return data.a.b.c.reduce(add, 0);
    }

    // What do we return here?
}

Add a guard clause

How do we represent the failure branch in this function?

// Option 1
return false;
// Option 2
return null;
// Option 3
throw new Error("An array is required to sum");
// Option 4
throw new CannotSumError("C should be an array");

😬

If we are regularly accessing nested properties, how can we formalise this approach and make it reusable?

There has to be a better way!?

pure functions

Consistent return types

immutable data structures

introducing

ADTS

The data types provided in Crocks allow you to remove large swaths of imperative boilerplate, allowing you to think of your code in terms of what it does and not how it does it.​

Crocks

Sum types to the rescue

First, a quick intro to haskell-like type signatures

data Bool = True | False

User defined types

type EventId = Int

Type aliases / Synonyms

add :: Int -> Int -> Int

Function signatures

Introducing Maybe

data Maybe a = Just a | Nothing

Maybe is well suited for capturing disjunction when the cause of the "error" case does not need to be communicated. For example, providing default values on specific conditions.

const a = { a: { b: { c: [1, 2, 3] } } };
const b = { a: { b: { c: undefined } } };

const add = (a, b) => a + b;
const sumC = data => {
    if (data.a.b.c && Array.isArray(data.a.b.c)) {
        return Just(data.a.b.c.reduce(add, 0));
    }

    return Nothing();
}

A solution using ADTs

const prop = require("crocks/Maybe/prop");
const propPath = require("crocks/Maybe/propPath");

const data = { a: { b: { c: [1, 1, 2, 3, 5] } } };

const a = prop("a", data); // Just { b: { c: [1, 1, 2, 3, 5] } }
const b = prop("b", data); // Nothing

const c = propPath(["a", "b", "c"], data); // Just [1, 1, 2, 3, 5]
const d = propPath(["a", "b", "d"], data); // Nothing

safely getting properties from objects

This is great, but how do we work with the value inside a Maybe?

Maybe is a Functor

A value which has a functor must provide a map method. The map method takes one argument

map :: Functor f => f a ~> (a -> b) -> f b
Just.prototype.map = function(fn) { return Just(fn(this.value)) };

What happens When You Get a nothing?

Nothing.prototype.map = function(fn) { return this; };
const a = { a: { b: { c: [1, 2, 3] } } };
const b = { a: { b: { c: undefined } } };

const sumC = data =>
    propPath(["a", "b", "c"], data)
       .map(vals => vals.reduce(add, 0));

sumC(a); // Just 6
sumC(b); // Nothing

We can re-write our solution using the new helper functions

Currying, Composition and Point-free style

propPath :: Foldable f => f (String | Integer) -> a -> Maybe b

Currying, Composition and point-free style

Arrows indicate currying

Value is only returned when all other arguments are provided

"f" has to be an ADT which implements the foldable typeclass (i.e. an array or List)

propPath :: Foldable f => f (String | Integer) -> a -> Maybe b

map :: (a -> b) -> m a -> m b

reduce :: (b -> a -> b) -> b -> m a -> b

compose :: ((y -> z), ..., (a -> b)) -> a -> z

pipe :: ((a -> b), ..., (y -> z)) -> a -> z

Currying, Composition and point-free style

// getC :: a -> Maybe b
const getC = propPath(["a", "b", "c"]);

// sum :: Foldable f => f Number -> Number
const sum = reduce(add, 0);

// sumC :: a -> Maybe Number
const sumC = pipe(getC, map(sum));

Currying, Composition and point-free style

const sum = reduce(add, 0);

Taking a closer look at our reduction

"empty" value (aka identity)

Combines two values together (aka concat)

We could use a monoid

any ADT that provides both an empty and a concat function can be used as a Monoid

Each Monoid provides a means to represent a binary operation and is usually locked down to a specific type. These are great when you need to combine a list of values down to one value.

// Instead of this
const add = (a, b) => a + b;
const sum1 = reduce(add, 0);

// We can use the built in behaviours of the Sum Monoid
const sum2 = mreduce(Sum);

Using a Monoid

πŸ’‘Note that sum1 and sum2 are equivalent - both take an array of numbers and return a number

// sumC :: a -> Maybe Number
const sumC = pipe(
    propPath(["a", "b", "c"]), 
    map(mreduce(Sum));

Our final implementation

Our program has been completely built from generic, reusable library code

mreduce vs mconcat vs mreduceMap vs mconcatMap

mconcat :: Monoid m, Foldable f => m -> f a -> m a

mconcatMap :: Monoid m, Foldable f => m -> (b -> a) -> f b -> m a

mreduce :: Monoid m, Foldable f => m -> f a -> a

mreduceMap :: Monoid m, Foldable f => m -> (b -> a) -> f b -> a

mreduce vs mconcat vs mreduceMap vs mconcatMap

Getting the first item from an array

Jumping back...

// head :: Foldable f => f a -> Maybe a
const head = xs => (Array.isArray(xs) && xs.length > 0 ? Just(xs[0]) : Nothing();)

Getting the first item from an array

// head :: Foldable f => f a -> Maybe a
function head(xs) {
  if (Array.isArray(xs) && xs.length > 0) {
    return Just(xs[0]);
  }

  return Nothing();
}

What if we need to represent more than Nothing?

Maybe is just the start of this adventure...

data Either e a = Left e | Right a

data Result e a = Err e | Ok a

data Async e a = Rejected e | Resolved a

data RemoteData e a = NotAsked | Loading | Error e | Success a

type Pair a b = (a, b)

This all sounds great, but why the crazy names!?

The specifications in this list do not derive from goals such as trying to write rules for lists and maps. Instead, they start by noticing rules that apply in common to disparate structures.

Aside, Why Fantasy Land?

Yeah this is really not happening. It totally ignores reality in favor of typed-language fantasy land, making a more awkward and less useful API just to satisfy some peoples' aesthetic preferences that aren't even applicable to JavaScript.

Where to learn more

Programming Safely With types

Ian Thomas | @anatomic

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