ferrum 1.4.0

Ferrum

Features from the rust language in javascript: Provides Traits/Type classes & an advanced library for working with sequences/iterators in js.

Github
API Documentation

Table of Contents

  1. Introduction
  2. Table of Contents
  3. Status
  4. Usage & Features
    1. Sequence/Iterators
      1. Objects as Sequences
      2. Reverse Currying
      3. Pipelining
      4. Lazy Evaluation
    2. Traits/Typeclasses
    3. Operators as functions
    4. Typing utilities
    5. Functional utilities
  5. Change Log
  6. Development
    1. Build
    2. Test
    3. Lint

Status

CircleCI codecov GitHub license GitHub issues LGTM Code Quality Grade: JavaScript semantic-release

Usage & Features

$ npm add ferrum

Sequence/Iterators

Feature Ferrum Underscore Lodash wu.js
Objects as Sequences yes no no no
Reverse Currying yes no no no
Lazy Evaluation yes no no yes
Pipelining yes no no no

Ferrum provides a library for transforming lists & iterables; it provides all the functions you would expect like map, filter, foldl and many others. In this regard it is very similar to libraries like wu.js, lodash or underscore. Ferrum has been written to remedy some of the issues in these libraries.

Objects as Sequences

Ferrum/Sequence has been designed with full iterator support in mind. Generally all functions can take iterables/iterators and returns iterators.

const {map, assertSequenceEquals} = require('ferrum');

const a = map([1,2,3,4], x => x+2); // a is an iterator
const b = map(a, x => x*2); // b is also an iterator
assertSequenceEquals(b, [6, 8, 10, 12]);

In addition to supporting iterables & iterators, Ferrum/Sequence can take objects as input:

const {map,  iter, assertEquals, assertSequenceEquals} = require('ferrum');

const a = map({a: 42, b: 43}, ([k, v]) => v+2); // a is an iterator
const b = map(a, x => x*2); // b is also an iterator
assertSequenceEquals(b, [88, 90]);

const obj = {foo: 23, bar: 24};
const log = [];
for (const [key, value] in iter(obj)) {
  log.push(`${key} | ${value}`);
}
assertEquals(log, [
  'foo | 23',
  'bar | 24',
]);

Ferrum/Sequence uses lodash.isPlainObject and always tries to use the iterator protocol to make sure object iteration is only used if it really should.

const {map, assertSequenceEquals} = require('ferrum');

const obj = {};
obj[Symbol.iterator] = function*() {
  yield 2;
  yield 3;
};

assertSequenceEquals(map(obj, x => x*2), [4, 6]);

Lodash and Underscore only support arrays as input & output; wu.js supports iterators as input & output but has no support for plain objects.

Reverse Currying

Ferrum/Sequence provides many higher order functions. These are functions that take other functions as parameters, like map() or filter().

const {map, filter, assertSequenceEquals} = require('ferrum');

// Map is used to change each value in a list/iterable
assertSequenceEquals(map([1,2,3,4], x => x*2), [2,4,6,8]);

// Filter removes elements in a list/iterable
assertSequenceEquals(filter([1,2,3,4], x => x%2 === 0), [2 4]);

Sometimes it can be useful to create an intermediate function with just a few arguments instead of calling the function right away:

const myList = [
  [1,2,3],
  [4,5,6],
  [7,8,9]
];

// Add 2 to each number in a two dimensional list
// This example uses currying twice: in the `plus(2)`
// and in the `map()`
const a = map(myList, map(plus(2)));
assertSequenceEquals(a, [
  [3,4,5],
  [6,7,8],
  [9,10,11]
]);

// This is what the code would look like without currying:
// A lot less convenient and harder to read
const b = map(myList, (sublist) => map(sublist, (b) => plus(b, 2)));
assertSequenceEquals(b, [
  [3,4,5],
  [6,7,8],
  [9,10,11]
]);

You may have noticed, that when currying is used, the arguments are given in reverse order; this is why we call it reverse currying. We have decided to use currying this way, because there should nevery be extra arguments after the function (otherwise you end up with dangling arguments multiple lines below) while the function is usually also the first parameter you want to supply when currying:

const {each} = require('ferrum');

// This is much more handy
each([1,2,3], () => {
  ...
});

// This is not very handy because you might need to scroll down to find the last
// argument; you will also need to scroll down to determine whether the call to
// each is using currying
each(() => {
  ...
}, [1,2,3]);

Underscore.js does not support currying at all; lodash provides curryied variants of their functions in an extra module (not very handy either because it is often useful to mix curried and non currying invocations) while lodash has opted to make the function the first parameter, delivering good support for currying and not so good support for normal function invocation.

Pipelining

Ferrum provides a function called pipe() which – together with currying – can be used to build complex data processing pipelines. Pipelines are conceptually the same as the highly successful pipes in bash; the feature is currently being introduced into the javascript standard library in the form of the |> operator.

const {sqrt} = Math;
const {pipe, filter, uniq, map, mul, mapSort, identity, pipe,
       prepend, takeWhile, all, range} = require('ferrum');

const a = pipe(
  [5,1,6,7,10,11,1,3,4],
  filter(x => x%2 === 1), // Get rid of even number
  uniq,                   // Get rid of duplicates
  map(mul(3)),            // Multiply each element by three
  mapSort(identity));     // Sort all numbers
assertSequenceEquals(q, [3,9,12,15,18,21,30,33]);

// Very simple primality test
const isPrime = (v) => v > 1 && pipe(
  // Build the list of candidate factors
  range(0, Infinity), // List of all even integers >0
  takeWhile(x => x<=sqrt(v)), // Cut of the list at the square root of our input
  // Perform the division test
  map(x => v % x === 0),
  all); // NOTE: Due to lazy evaluation, dividing will stop at the first factor found

// Sequence of all prime numbers (calculated slowly)
const primes = () => pipe(
  range(0, Infinity), // List of all positive integers
  filter(isPrime));

Learning to write algorithms in this way is not always easy, but it can be very rewarding as the pipe form is often a lot more readable. To illustrate this, let's take a look how our code of the prime sequence example changes as we take a way features from Ferrum; let's first take away currying and the pipe() function itself:

const {sqrt} = Math;
const {all, map, takeWhile, filter, range} = require('ferrum');

const isPrime = (v) => v > 1 && all(map(takeWhile(range(2, Infinity), x => x<=sqrt(v)), x => v % x === 0));
const primes = () => filter(range(0, Infinity), isPrime);

One way to work around the lack of currying and pipe() is to just put all our filter stages into one expression. Due to this, our code has become much shorter and much harder to read. Look at how the dataflow jumps around, see how distant the map function and it's argument are from each other and it does not help that subexpression cannot be properly documented any more. Let's try another way to write down these functions:

const {sqrt} = Math;
const {all, map, takeWhile, filter, range} = require('ferrum');

const positiveIntegers = () => range(1, Infinity);
const isPrime = (v) => {
  const fromTwo = range(2, Infinity);
  const candidates = takeWhile(fromTwo, x => x<=sqrt(v));
  return v > 1 && all(map(x => v % x === 0));
}
const primes = () => filter(positiveIntegers(), isPrime);

This is much better! The data flow is more clear and substeps can be documented again. In this version we used temporary variables to get around not having pipe() and currying; this is much better than just putting everything into one line.

Note how positiveIntegers became it's own function while fromTwo and candidates became just local variables. Also note how all and map are still in the same expression. Sometimes this is the more readable variant. We have to decide each time.

This variant still has disadvantages though; first of all the code still looks more cluttered and the dataflow still jumps around more than the pipe variant. You also have to come up with a lot of names for temporary variables and take care not to reuse them (since they are lazily evaluated they must only be used once). This is one of the things you communicate by using pipe() over local variables: "This variable will never be used again" – knowing this & limiting the number of variables in a scope can be very useful, especially in large functions.

Finally, let's implement this in classic imperative style:

const {sqrt} = Math;

const isPrime = (v) => {
  if (v < 2) {
    return false;
  }

  for (let i=2; i <= sqrt(v); i++) {
    if (v % i !== 0) {
      return false;
    }
  }

  return true;
}

const primes = function *primes() {
  for (let i=2; true; i++) {
    if (isPrime(i)) {
      yield i;
    }
  }
}

The first thing that becomes noticeable in this version is that it is more than twice as long as our variant using pipe() (not counting comment lines); this version also uses two levels of nesting, while our pipelined version uses just one level of nesting. The imperative version also contains two for loops and three if statements; for loops are notoriously hard to read as well. Finally, the imperative version forces us to think in imperative terms – to consider what happens in each step of the for loop one by one and then come to the conclusion: Ah, this for loop just gets rid of all those integers that are not prime. In the imperative version this intention must be deduced, in the pipelined version it is plain to see.

To sum it up, using pipe() and currying the functions from Ferrum has a number of advantages; you end up with fewer levels of nesting, can avoid a lot of branching (if statements) and hard to write for loops; pipelining let's you break apart your problem into multiple clearly defined transformation steps with obvious data flow and obvious intention.

Underscore, lodash and wu all allow you to do something similar with chaining which does work quite well. They do require a bit more boilerplate since values need to be wrapped before chaining and unwrapped after chaining has finished. Pipelining will have even less boilerplate when the |> becomes available and pipelining can be used with arbitrary transformation functions, while chaining can only be used with functions supported by the library, thus pipelining is much more generic & extensible.

Lazy Evaluation

Like python iterators, sequences support lazy evaluation. They support it, because lazy evaluation is a core feature of javascript es6 iterators.

This means that the values in iterators/sequences are only evaluated only once they are needed:

const {map, plus} = require('ferrum');
const a = map([1,2,3], plus(2)); // At this point, no calculations have been performed
const b = list(a); // This will actually cause the values of the a iterator to be calculated

Try the above example with a couple of console.log statements and see what happens.

The practical upshot of this property is that it becomes possible to work with infinite sequences, like the primes() sequence above. It can be more efficient as well, since values that are not needed are not computed.

const {take, list, assertEquals} = require('ferrum');

// Even though primes() is infinite, this just works because only the
// first five primes are actually calculated.
// Note that just list(primes()) would crash the program since that would
// require infinite memory and infinite time
assertEquals(list(take(5, primes())), [2, 3, 5, 7, 11]);

Underscore and lodash use arrays instead of iterators, so they have no lazy evaluation support. wu uses iterators and thus has full lazy evaluation support.

Traits/Typeclasses

Sequence/Traits is the second big feature this library provides; it is a concept borrowed from the Rust language. They let you declare & document a generic interface; like the sequence concept above they are not an entirely new concept; while sequence is a library designed to make working with the javascript iteration protocols easier, traits standardize the creation of javascript protocols itself, thereby reducing boilerplate. Indeed the Sequence Trait is just a wrapper over the Iterable protocol of javascript.

const {Trait} = require('ferrum');

// Declaring a trait
/**
 * The Size trait is used for any containers that have a known size, like
 * arrays, strings, Maps…
 * Size should be used only for sizes that are relatively quick to compute, O(1) optimally…
 * @interface
 */
const Size = new Trait('Size');

// Using it
const size = (what) => Size.invoke(what);
const empty = (what) => size(what) === 0;

// Providing implementations for own types; this implementation will be
// inherited by subclasses
class MyType {
  [Size.sym]() {
    return 42;
  }
}

// Providing implementations for third party types. These won't be inherited
// by subclasses
Size.impl(Array, (x) => x.length); // Method of type Array
Size.impl(String, (x) => x.length);
Size.impl(Map, (x) => x.size);
Size.impl(Set, (x) => x.size);

// This implementation just applies to plain objects.
Size.impl(Object, (x) => {
  let cnt = 0;
  for (const _ in x) cnt++;
  return cnt;
});

// Note: The two following examples would be a bad idea in reality,
// they are just here toshow the mechanism
Size.implStatic(null, (_) => 0); // Static implementation (for a value and not a type)

Some of the advantages of using Traits are illustrated for the code above: First of all, using traits saves us a bit of boilerplate code; by having an actual variable representing the trait, we have a good place to document the trait; the @interface jsdoc feature can be used for this. We can also use this documentation to specify laws that implementations of the trait should abide by, like the (soft) law that Size implementations should be quick to compute.

Trait also features machinery to implement traits for third party types and even built in types like Array, Object, null or undefined. The classic way to implement protocols does not work in these cases:

const Size = Symbol('Size');

// Using just Symbols works perfectly for your own types
class MyType {
  [Size]() {
    return 42;
  }
}

// Using symbols for third party types is suboptimal,
// since we have to modify the type's prototype which
// could lead to weirdness
Array.prototype[Size] = () => this.length;

// Using symbols for Object, is a very bad idea as the implementation
// will be inheritaed by all other classes…this implementation obviously
// is the wrong one for Set for instance.
// This also illustrates why it is generally a bad idea to enable inheritance
// for third party types
Object.prototype[Size] = () => {
  let cnt = 0;
  for (const _ in this) cnt++;
  return cnt;
}

// Using symbols on values like null or undefined will just lead to a TypeError
// being thrown
null[Size] = () => 0;

The oldest pre-es6 way of implementing just used method names; this strategy is very problematic, since two different interfaces may use the same method name:

class MyDbTable {
  size() {
    return request(`https://mydb.com/${this._tableName}/size`);
  }
};

class MyLocalTable {
  size() {
    return this._payload.length;
  }
}

In the hypothetical example above, one size() method returns an integer, while the other returns a promise resolving an integer (which makes total sense since it's the size of some database table). Even though each method makes sense for itself, there is no way distinguishing; they developer may write a function, expecting an integer…

Since the method name size() is already taken, we cannot even implement the async size interface for MyLocalTable.

Using traits we can actually encapsulate this relationship well:

// dbtable.js
const { Trait } = require('ferrum');
const Size = new Trait('Size');

class DbTable {
  [Size.sym]() {
    return request(`https://mydb.com/${this._tableName}/size`);
  }
};

module.exports = {Size, DbTable};
// localtable.js
const { Trait } = require('ferrum');
const {Size: AsyncSize} = require('./dbtable.js')

const Size = new Trait('Size');

class MyLocalTable {
  [Size.sym]() {
    return this._payload.length;
  }
}

AsyncSize.implDerived([Size], ([size], v) => Promise.resolve(size(v)));

This example above illustrates how – using traits – we can not only deal with name collisions by just renaming traits on the fly, we where also able to write a generic adapter that automatically implements AsyncSize for all types supporting Size.

To sum up, using Traits provides a number of advantages: Traits let you avoid some boilerplate code, they allow you to specify and implement generic interfaces without the danger of name collisions; they let you provide implementations for third party types, built in types and even null, undefined and plain objects without modifying these types. They even let you write generic adapters, implementing traits for entire groups of traits at once.

Operators as functions

Ferrum/Ops provides all of the JS operators and some extra boolean operators as curryable functions.

const {plus, and, not, is, xor, map, list} = require('ferrum');

list(map([1,2,3], plus(2))); // => [3,4,5]
and(True, False);  // => False
not(1); // => False
is(2, 2); // => True
xor(True, False); // => True

Typing utilities

Ferrum provides utilities for working with types that can be safely used with null and undefined.

class {isdef, type, typename} = require('ferrum');

isdef(0); // => true
isdef(null); // => false
isdef(undefined); // => false

type(22); // => Number
type(null); // => null
type(undefined); // => undefined

typename(type(22)); // => "Number"
typename(type(null)); // => "null"
typename(type(undefined)); // => "undefined"

The usual strategy of using value.constructor and value.constructor.name yields errors for null & undefined.

Functional Utilities

const {curry, pipe, filter, isdef, uniq, map, plus} = require('ferrum');

// Using pipe() + auto currying instead of chaining
pipe(
  [0,1,2,null,3,4,null,5,1,3,2,null,1,4],
  filter(isdef), // Filter out every null & undefined
  uniq,          // Remove duplicates
  map(plus(2))); // Add two to each element
// => [2,3,4,5,6,7]

// Auto currying
const pair = curry('pair', (a, b) => [a, b]);
pair(1,2); // => [1,2]
pair(2)(1); // => [1,2]

Change Log

1.4.0

1.3.0

  • Add function repeatFn() (81de232)
  • Provide chunkify functions (9ff9603)
  • Provide takeShort() & takeWithFallback() (bafa834)
  • slidingWindow now returns an empty sequence if no=0 (533cff4)

1.2.0

  • Bugfix: Support for objects with Symbol keys – Before this change most functions would disregard Symbol keys in objects. E.g. size({[Symbol()]: 42}) would return zero. Now the functions pairs(), keys(), values(), size(), empty(), shallowclone(), deepclone(), iter(), each(), replace(), setdefault(), del(), assign(), has(), get(), eq, uneq, assertEquals, assertUneq are explicitly tested and with objects containing symbol keys.

Development

Build

$ npm install

Test

$ npm test

Lint

$ npm run lint