Skip to content

benji6/imlazy

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

imlazy

npm version CI/CD NPM Netlify Status

Functional programming with lazy immutable iterables

Introduction

imlazy let's you harness the power of the ES2015 iteration protocols. With it you can create infinite or circular iterables which are lazy, immutable and performant. For instance:

const { filter, range } = require("imlazy");

const isEven = (x) => x % 2 === 0;

const positiveIntegers = range(1, Infinity); // => (1 2 3 4 5 6 7 8 9 10...)
const positiveEvenIntegers = filter(isEven, positiveIntegers); // => (2 4 6 8 10 12 14 16 18 20...)

All functions are auto-curried and iterable-last (like in lodash/fp and ramda) which allows developers to build up reusable functions with partial application like so:

const { take } = require("imlazy");

const takeThree = take(3);

const oneTwoThree = takeThree(positiveIntegers); // => (1 2 3)
const twoFourSix = takeThree(positiveEvenIntegers); // => (2 4 6)

Putting iterables into an array, or set, or using them as arguments to a function call is simple (be careful with anything infinite or circular though!):

[...twoFourSix]; // => [2, 4, 6]
Array.from(twoFourSix); // => [2, 4, 6]
new Set(twoFourSix); // => Set { 2, 4, 6 }
Math.max(...twoFourSix); // => 6

Because imlazy uses the ES2015 iteration protocols it is compatible with all native iterables (including the Generator, String, Array, TypedArray, Map and Set types) and many libraries (including Immutable.js):

const { sum } = require("imlazy");
const Immutable = require("immutable");

sum(twoFourSix); // => 12
sum([2, 4, 6]); // => 12
sum(new Set(twoFourSix)); // => 12
sum(Immutable.List.of(2, 4, 6)); // => 12

const fibonacciGenerator = function* () {
  let [a, b] = [0, 1];
  while (true) yield ([a, b] = [b, a   b])[0];
};

take(8, fibonacciGenerator()); // => (1 1 2 3 5 8 13 21)

All iterables created by imlazy are frozen with Object.freeze so, not only are they lazy, they're also immutable.

If you want to find out more about the ES2015 iteration protocols this MDN article is a good place to start.

Getting Started

Installation

npm i imlazy

API Documentation

API docs are here.

Support

imlazy is written in ES2015 and will run in any environment that supports that specification. If using in Node.js use version 6 or greater.

Debugging

imlazy implements a custom toString method for the iterables it returns. Just invoke String on an iterable returned by one of imlazy's functions to see what's inside it:

String(range(1, 8)); // => (1 2 3 4 5 6 7 8)
String(range(1, Infinity)); // => (1 2 3 4 5 6 7 8 9 10...)

The custom toString method can handle nested and infinite iterables (in which case it lists the first 10 elements followed by ellipsis) and uses a LISP-like notation to differentiate iterables from arrays and other JS data structures

Static Land

This library implements the following Static Land algebraic types:

  • Functor
    • Apply
      • Applicative
      • Chain
        • Monad
  • Foldable
    • Traversable
  • Filterable
  • Semigroup
    • Monoid
  • Setoid

Performance

There is a benchmarks dir in the root of this repo. Here are the results on my machine running node 8.9.3:

benchmarks/filter.js

imlazy - filter 1x over array x 3,762 ops/sec ±0.27% (98 runs sampled)
imlazy - filter 2x over array x 3,104 ops/sec ±0.37% (96 runs sampled)
imlazy - filter 3x over array x 3,022 ops/sec ±0.18% (100 runs sampled)
native - filter 1x over array x 42,003 ops/sec ±15.10% (90 runs sampled)
native - filter 2x over array x 21,413 ops/sec ±13.20% (98 runs sampled)
native - filter 3x over array x 18,075 ops/sec ±13.47% (95 runs sampled)

benchmarks/map.js

imlazy - map 1x over array x 2,726 ops/sec ±0.24% (99 runs sampled)
imlazy - map 2x over array x 1,584 ops/sec ±0.28% (98 runs sampled)
imlazy - map 3x over array x 999 ops/sec ±0.44% (97 runs sampled)
native - map 1x over array x 60,221 ops/sec ±17.07% (96 runs sampled)
native - map 2x over array x 9,820 ops/sec ±10.96% (97 runs sampled)
native - map 3x over array x 3,899 ops/sec ±0.16% (100 runs sampled)

Influences