Function application for curried functions in JavaScript and ES6 - javascript

I love that ECMAScript 6 allows you to write curried functions like this:
var add = x => y => z => x + y + z;
However, I hate that we need to parenthesize every argument of a curried function:
add(2)(3)(5);
I want to be able to apply curried functions to multiple arguments at once:
add(2, 3, 5);
What should I do? I don't care about performance.

Currying and the application of curried functions are controversial issues in Javascript. In simple terms, there are two opposing views, which I illustrate both briefly.
- Use of a separate curry function only when necessary
The adaptation of concepts from other languages or paradigms is in principle a good thing. This adaptation though, should be done with the elementary means of the target language. What does that mean for currying in javascript?
curried functions are called as a sequence of unary functions:add3(1)(2)(3); // 6
own functions are manually curried with arrows const add3 = x => y => z => x + y + z;
third party functions or methods are curried by a separate curry function
- Use of a separate curry implementation by default
There's a problem with the proposed $/uncurry function:
const $ = (func, ...args) => args.reduce((f, x) => f(x), func);
const sum = x => y => z => x + y + z;
$(sum, 1, 2, 3); // 6
$(sum, 1, 2)(3); // 6
$(sum, 1)(2, 3); // z => x + y + z
In this way uncurried functions can only once be applied with an unlimited number of arguments. Any subsequent calls must be made unary. The function does exactly what it promises. However, it does not allow application of curried functions, such as JavaScript developers are used to. Most of the current curry implementations are more flexible. Here's an extended implementation:
const uncurry = f => (...args) => args.reduce(
(g, x) => (g = g(x), typeof g === "function" && g.length === 1
? uncurry(g)
: g), f
);
const sum = uncurry(x => y => z => x + y + z);
sum(1, 2, 3); // 6
sum(1, 2)(3); // 6
sum(1)(2, 3); // 6
This implementation works, if you like auto-uncurrying: Once a uncurried function itself produces a curried function as a return value, this returned function is automatically uncurried. If you prefer more control, the following implementation might be more appropriate.
The final uncurry implementation
const partial = arity => f => function _(...args) {
return args.length < arity
? (...args_) => _(...args.concat(args_))
: f(args);
};
const uncurry = arity => f => partial(arity)(args => args.reduce((g, x) => g(x), f));
const sum = uncurry(3)(x => y => z => x + y + z);
sum(1, 2, 3); // 6
sum(1, 2)(3); // 6
sum(1)(2, 3); // 6
This tiny arity parameter brings us the desired control. I think it's worth it.
A curry solution for the rest
What do we do with functions that are beyond our control and hence haven't been manually curried?
const curryN = uncurry(2)(arity => f => partial(arity)(args => f(...args)));
const add = curryN(2, (x, y) => x + y);
const add2 = add(2);
add2(4); // 6
Fortunately, we were able to reuse partial and keep curryN concise. With this solution also variadic functions or such with optional parameters can be curried.
Bonus: "Funcualizing" and currying Methods
To curry methods, we need to transform this nasty, implicit this property in an explicit parameter. It turns out that we can reuse partial for an adequate implementation once again:
const apply = uncurry(2)(arity => key => {
return arity
? partial(arity + 1)(args => args[arity][key](...args.slice(0, arity)))
: o => o[key]();
});
apply(0, "toLowerCase")("A|B|C"); // "a|b|c"
apply(0, "toLowerCase", "A|B|C"); // "a|b|c"
apply(1, "split")("|")("A|B|C"); // ["A", "B", "C"]
apply(1, "split")("|", "A|B|C"); // ["A", "B", "C"]
apply(1, "split", "|", "A|B|C"); // ["A", "B", "C"]
apply(2, "includes")("A")(0)("A|B|C"); // true
apply(2, "includes", "A", 0, "A|B|C"); // true
In this blog post currying is discussed in detail.

Most people write curried functions like this:
var add = curry(function (x, y, z) {
return x + y + z;
});
add(2, 3, 5);
Mostly because they don't want to write this:
var add = function (x) {
return function (y) {
return function (z) {
return x + y + z;
};
};
};
add(2)(3)(5);
However, nobody agrees on how to implement curry.
Then, ECMAScript 6 solved the first problem for us:
var add = x => y => z => x + y + z;
But, we still have to solve the second problem ourselves:
add(2)(3)(5);
It's high time that we solve this problem:
var $ = (func, ...args) => args.reduce((f, x) => f(x), func);
I hope you like Lisp syntax:
$(add, 2, 3, 5);
Sorry jQuery. Function application is more fundamental.
Also, Bergi's solution is awesome:
const uncurry = func => (...args) => {
var result = func;
for (let arg of args)
result = result(arg);
return result;
}
var add = uncurry(x => y => z => x + y + z);
add(2, 3, 5);
However, I still prefer using $.

You can easily write a function that applies multiple arguments to such a curried function:
const uncurry = fn => (...args) => args.reduce((f, x) => f(x), fn);
// or alternatively:
const uncurry = fn => (...args) => {
let f = fn;
for (const x of args) f = f(x);
return f;
}
Now you can invoke add like so:
uncurry(add)(2, 3, 4)
and if you still hate that you could also use
const $ = uncurry(uncurry);
$(add, 2, 3, 4)

Related

Similar curry functions producing different results

I am learning functional javascript and I came across two different implementations of the curry function. I am trying to understand the difference between the two they seem similar yet one works incorrectly for some cases and correctly for other cases.
I have tried interchanging the functions the one defined using es6 'const'
works for simple cases but when using 'filter' to filter strings the results are incorrect, but with integers it produces the desired results.
//es6
//Does not work well with filter when filtering strings
//but works correctly with numbers
const curry = (fn, initialArgs=[]) => (
(...args) => (
a => a.length === fn.length ? fn(...a) : curry(fn, a)
)([...initialArgs, ...args])
);
//Regular js
//Works well for all cases
function curry(fn) {
const arity = fn.length;
return function $curry(...args) {
if (args.length < arity) {
return $curry.bind(null, ...args);
}
return fn.call(null, ...args);
};
}
const match = curry((pattern, s) => s.match(pattern));
const filter = curry((f, xs) => xs.filter(f));
const hasQs = match(/q/i);
const filterWithQs = filter(hasQs);
console.log(filterWithQs(["hello", "quick", "sand", "qwerty", "quack"]));
//Output:
//es6:
[ 'hello', 'quick', 'sand', 'qwerty', 'quack' ]
//regular:
[ 'quick', 'qwerty', 'quack' ]
If you change filter to use xs.filter(x => f(x)) instead of xs.filter(f) it will work -
const filter = curry((f, xs) => xs.filter(x => f(x)))
// ...
console.log(filterWithQs(["hello", "quick", "sand", "qwerty", "quack"]))
// => [ 'quick', 'qwerty', 'quack' ]
The reason for this is because Array.prototype.filter passes three (3) arguments to the "callback" function,
callback - Function is a predicate, to test each element of the array. Return true to keep the element, false otherwise. It accepts three arguments:
element - The current element being processed in the array.
index (Optional) - The index of the current element being processed in the array.
array (Optional) - The array filter was called upon.
The f you are using in filter is match(/q/i), and so when it is called by Array.prototype.filter, you are getting three (3) extra arguments instead of the expected one (1). In the context of curry, that means a.length will be four (4), and since 4 === fn.length is false (where fn.length is 2), the returned value is curry(fn, a), which is another function. Since all functions are considered truthy values in JavaScript, the filter call returns all of the input strings.
// your original code:
xs.filter(f)
// is equivalent to:
xs.filter((elem, index, arr) => f(elem, index, arr))
By changing filter to use ...filter(x => f(x)), we only allow one (1) argument to be passed to the callback, and so curry will evaluate 2 === 2, which is true, and the return value is the result of evaluating match, which returns the expected true or false.
// the updated code:
xs.filter(x => f(x))
// is equivalent to:
xs.filter((elem, index, arr) => f(elem))
An alternative, and probably better option, is to change the === to >= in your "es6" curry -
const curry = (fn, initialArgs=[]) => (
(...args) => (
a => a.length >= fn.length ? fn(...a) : curry(fn, a)
)([...initialArgs, ...args])
)
// ...
console.log(filterWithQs(["hello", "quick", "sand", "qwerty", "quack"]))
// => [ 'quick', 'qwerty', 'quack' ]
This allows you to "overflow" function parameters "normally", which JavaScript has no problem with -
const foo = (a, b, c) => // has only three (3) parameters
console.log(a + b + c)
foo(1,2,3,4,5) // called with five (5) args
// still works
// => 6
Lastly here's some other ways I've written curry over the past. I've tested that each of them produce the correct output for your problem -
by auxiliary loop -
const curry = f => {
const aux = (n, xs) =>
n === 0 ? f (...xs) : x => aux (n - 1, [...xs, x])
return aux (f.length, [])
}
versatile curryN, works with variadic functions -
const curryN = n => f => {
const aux = (n, xs) =>
n === 0 ? f (...xs) : x => aux (n - 1, [...xs, x])
return aux (n, [])
};
// curry derived from curryN
const curry = f => curryN (f.length) (f)
spreads for days -
const curry = (f, ...xs) => (...ys) =>
f.length > xs.length + ys.length
? curry (f, ...xs, ...ys)
: f (...xs, ...ys)
homage to the lambda calculus and Howard Curry's fixed-point Y-combinator -
const U =
f => f (f)
const Y =
U (h => f => f (x => U (h) (f) (x)))
const curryN =
Y (h => xs => n => f =>
n === 0
? f (...xs)
: x => h ([...xs, x]) (n - 1) (f)
) ([])
const curry = f =>
curryN (f.length) (f)
and my personal favourites -
// for binary (2-arity) functions
const curry2 = f => x => y => f (x, y)
// for ternary (3-arity) functions
const curry3 = f => x => y => z => f (x, y, z)
// for arbitrary arity
const partial = (f, ...xs) => (...ys) => f (...xs, ...ys)
Lastly a fun twist on #Donat's answer that enables anonymous recursion -
const U =
f => f (f)
const curry = fn =>
U (r => (...args) =>
args.length < fn.length
? U (r) .bind (null, ...args)
: fn (...args)
)
The main difference here is not the es6 syntax but how the arguments are partially applied to the function.
First version: curry(fn, a)
Second versison: $curry.bind(null, ...args)
It works for only one step of currying (as needed in your example) if you change first version (es6) to fn.bind(null, ...args)
The representation of the "Regular js" version in es6 syntax would look like this (you need the constant to have a name for the function in the recursive call):
curry = (fn) => {
const c = (...args) => (
args.length < fn.length ? c.bind(null, ...args) : fn(...args)
);
return c;
}

How to share intermediate results of continuations?

Please note that even though the example in this question is encoded in Javascript, the underlying concepts are common in Haskell and I while I prefer to express myself in Javascript I also appreciate answers in Haskell.
In Javascript I use CPS to handle asynchronous computations according to monadic principles. For the sake of simplicity, however, I will use the normal continuation monad for this question.
As soon as my continuation compositions grow, I keep finding myself in a situation where I need access to intermediate results of these compositions. Since Javascript is imperative it is easy to store such results in variables and access them later. But since we're talking about continuations accessing intermediate results means calling functions and accessing them several times means a lot of re-evaluation.
This seems to be well suited for memoization. But how can I memoize a function's return value if that very function doesn't return anything but merely calls its continuation (and btw. as I mentioned before I use asynchronous functions that also don't return anything in the current cycle of Javascript's event loop).
It seems as if I have to extract the right continuation. Maybe this is possible with delimited continuations through shift/reset, but I don't know how to apply these combinators. This issue is probably not that hard to solve and I'm just confused by the magical land of continuation passing style...so please be indulgent with me.
Here is a simplified example of Cont without memoization in Javascript:
const taggedLog = tag => s =>
(console.log(tag, s), s);
const id = x => x;
const Cont = k => ({
runCont: k,
[Symbol.toStringTag]: "Cont"
});
const contAp = tf => tx =>
Cont(k => tf.runCont(f => tx.runCont(x => k(f(x)))));
const contLiftA2 = f => tx => ty =>
contAp(contMap(f) (tx)) (ty);
const contOf = x => Cont(k => k(x));
const contMap = f => tx =>
Cont(k => tx.runCont(x => k(f(x))));
const contReset = tx => // delimited continuations
contOf(tx.runCont(id));
const contShift = f => // delimited continuations
Cont(k => f(k).runCont(id));
const inc = contMap(x => taggedLog("eval inc") (x + 1));
const inc2 = inc(contOf(2));
const inc3 = inc(contOf(3));
const add = contLiftA2(x => y => taggedLog("eval add") (x + y));
const mul = contLiftA2(x => y => taggedLog("eval mul") (x * y));
const intermediateResult = add(inc2) (inc3);
mul(intermediateResult) (intermediateResult).runCont(id);
/*
should only log four lines:
eval inc 3
eval inc 4
eval add 7
eval mul 49
*/
Your problems seems to be that your Cont has no monad implementation yet. With that, it's totally simple to access previous results - they're just in scope (as constants) of nested continuation callbacks:
const contChain = tx => f =>
Cont(k => tx.runCont(r => f(r).runCont(k)));
contChain( add(inc2) (inc3), intermediateResult => {
const intermediateCont = contOf(intermediateResult);
return mul(intermediateCont) (intermediateCont);
}).runCont(id);
(Of course it's a little weird that all your functions are already lifted and take Cont values as arguments - they shouldn't do that and simply be functions that return Cont values)
Your code in Haskell:
import Control.Monad.Cont
import Control.Applicative
let inc = liftA (+1)
let inc2 = inc $ return 2
let inc3 = inc $ return 3
let add = liftA2 (+)
let mul = liftA2 (*)
(`runCont` id) $ add inc2 inc3 >>= \intermediateResult ->
let intermediateCont = return intermediateResult
in mul intermediateCont intermediateCont
-- 49
{- or with do notation: -}
(`runCont` id) $ do
intermediateResult <- add inc2 inc3
let intermediateCont = return intermediateResult
mul intermediateCont intermediateCont
-- 49
(I haven't used monad transformers to make a taggedLog side effect)
It seems that I can't avoid getting impure to obtain the desired behavior. The impurity is only local though, because I just replace the continuation chain with its result value. I can do this without changing the behavior of my program, because this is exactly what referential transparency guarantees us.
Here is the transformation of the Cont constructor:
const Cont = k => ({
runCont: k,
[Symbol.toStringTag]: "Cont"
});
// becomes
const Cont = k => thisify(o => { // A
o.runCont = (res, rej) => k(x => { // B
o.runCont = l => l(x); // C
return res(x); // D
}, rej); // E
o[Symbol.toStringTag] = "Cont";
return o;
});
thisify in line A merely mimics this context, so that the Object to be constructed is aware of itself.
Line B is the decisive change: Instead of just passing res to the continuation k I construct another lambda that stores the result x wrapped in a continuation under the runTask property of the current Task object (C), before it calls res with x (D).
In case of an error rej is just applied to x, as usual (E).
Here is the runnning example from above, now working as expected:
const taggedLog = pre => s =>
(console.log(pre, s), s);
const id = x => x;
const thisify = f => f({}); // mimics this context
const Cont = k => thisify(o => {
o.runCont = (res, rej) => k(x => {
o.runCont = l => l(x);
return res(x);
}, rej);
o[Symbol.toStringTag] = "Cont";
return o;
});
const contAp = tf => tx =>
Cont(k => tf.runCont(f => tx.runCont(x => k(f(x)))));
const contLiftA2 = f => tx => ty =>
contAp(contMap(f) (tx)) (ty);
const contOf = x => Cont(k => k(x));
const contMap = f => tx =>
Cont(k => tx.runCont(x => k(f(x))));
const inc = contMap(x => taggedLog("eval inc") (x + 1));
const inc2 = inc(contOf(2));
const inc3 = inc(contOf(3));
const add = contLiftA2(x => y => taggedLog("eval add") (x + y));
const mul = contLiftA2(x => y => taggedLog("eval mul") (x * y));
const intermediateResult = add(inc2) (inc3);
mul(intermediateResult) (intermediateResult).runCont(id);
/* should merely log
eval inc 3
eval inc 4
eval add 7
eval add 49
*/

How to implement a coroutine based on multi-shot delimited continuations?

I recently implemented delimited continuations in CPS with reset/shift:
// reset :: ((a -> a) -> a) -> (a -> r) -> r
reset = k => f => f(k(id));
// shift :: ((a -> r) -> (r -> r) -> r) -> (a -> r) -> r
shift = f => k => f(k) (id);
Studying the theory I realized the following connections:
reset ~ function* // scope of the generator function
shift ~ yield
reset ~ async // scope of the asyn function
shift ~ await
As far as I understand the theory, Javascript's generators are a asymmetric, stackless, one-shot and first class coroutines.
asymmetric means that the called generator can only yield to its caller
stackless means a generator cannot yield from within nested functions
one-shot means that a generator can only resume from a specific position once
first class means a generator object can be passed around like normal data
Now I want to implement a coroutine based on reset/shift with the following traits:
asymmetric
stackful
multi-shot
first class
When looking at the following contrived example
const id = x => x;
const mul = x => y => x * y;
const add = x => y => x + y;
const sub = x => y => x - y;
const reset = k => f => f(k(id));
const shift = f => k => f(k) (id);
const of = x => k => k(x);
const lift2 = f => tx => ty => k => tx(x => ty(y => k(f(x) (y))));
const k0 = lift2(sub)
(reset
(lift2(add) (of(3))
(shift
(k => of(mul(5) (2))))))
(of(1)); // 9
const k1 = lift2(sub)
(reset
(lift2(add) (of(3))
(shift
(k => of(k(mul(5) (2)))))))
(of(1)); // 12
const k2 = lift2(sub)
(reset
(lift2(add) (of(3))
(shift
(k => of(k(k(mul(5) (2))))))))
(of(1)); // 15
console.log(k0(id));
console.log(k1(id));
console.log(k2(id));
it seems that reset/shift already meet the last two criteria, because delimited continuations are just first class, composable functions and I can invoke the continuation k as often as required.
To answer the why, I want to bypass the following limitation in connection with the list monad.
Are these assumptions correct?
Even if I haven't make any mistakes so far I am overwhelmed by the complexity of the task at this point. I have no clue how to implement the desired coroutine or even where to begin. I didn't found an example implementation either. I don't expect a complete implementation but maybe some guidance to achieve my goal.
Goal
I want to bypass the following limitation of coroutines implemented by Javascript's generators:
const arrMap = f => xs =>
xs.map(x => f(x));
const arrAp = fs => xs =>
fs.reduce((acc, f) =>
acc.concat(xs.map(x => f(x))), []);
const arrChain = xs => fm =>
xs.reduce((acc, x) => acc.concat(fm(x)), []);
const arrOf = x => [x];
const do_ = (of, chain) => it => {
const loop = ({done, value}) =>
done
? value
: chain(value) (x => loop(it.next(x)));
return loop(it.next());
};
const z = function*() {
const x = yield [1,2,3]
return [x, x];
}
console.log(
arrChain([1,2,3]) (x => [x, x]));
console.log(
do_(arrOf, arrChain) (z()));

Compose method in recompose Library

I was looking at the compose function in recompose library by #acdlite to compose boundary conditions for Higher Order Components and this is what it looks the compose function looks like
const compose = (...funcs) => funcs.reduce((a, b) => (...args) => a(b(...args)), arg => arg);
However, I tried Eric-Elliott's one liner approach to compose, from https://medium.com/javascript-scene/reduce-composing-software-fe22f0c39a1d, specifically, this piece of code.
const compose = (...fns) => x => fns.reduceRight((v, f) => f(v), x);
I tried using both these variants, in my react component like so,
const ListWithConditionalRendering = compose(
withLoadingIndicator,
withDataNull,
withListEmpty
)(Users);
and they both seem to work fine. I am unable to understand if there is any difference in the way the above functions work, if so, what are they.
There's a few differences for very niche scenarios that might be helpful to be aware of.
The first one precomposes a function, which means it calls reduce() when it is composed rather than when it will be called. In contrast, the second approach returns a scoped function that calls reduceRight() when it is called, rather than when it was composed.
The first method accepts multiple arguments to the last function in the array, while the second method only accepts one argument:
const compose1 = (...funcs) => funcs.reduce((a, b) => (...args) => a(b(...args)), arg => arg);
const compose2 = (...fns) => x => fns.reduceRight((v, f) => f(v), x);
const f = s => (...args) => (console.log('function', s, 'length', args.length), args);
compose1(f(1), f(2), f(3))(1, 2, 3);
compose2(f(4), f(5), f(6))(1, 2, 3);
The first method may result in a stack overflow if the array of functions is very large because it is pre-composed, whereas the second method is (relatively)† stack safe:
const compose1 = (...funcs) => funcs.reduce((a, b) => (...args) => a(b(...args)), arg => arg);
const compose2 = (...fns) => x => fns.reduceRight((v, f) => f(v), x);
const f = v => v;
try {
compose1.apply(null, Array.from({ length: 1e5 }, () => f))();
console.log('1 is safe');
} catch (e) {
console.log('1 failed');
}
try {
compose2.apply(null, Array.from({ length: 1e5 }, () => f))();
console.log('2 is safe');
} catch (e) {
console.log('2 failed');
}
† The second method will still result in a stack overflow if ...fns is too large because arguments are also allocated on the stack.
If you are interested in what structure the reduce-composition actually builds, you can visualize it as follows:
/* original:
const compose = (...funcs) =>
funcs.reduce((a, b) => (...args) => a(b(...args)), arg => arg);
*/
const compose = (...funcs) =>
funcs.reduce((a, b) => `((...args) => ${a}(${b}(...args)))`, $_("id"));
const $_ = name =>
`${name}`;
const id = x => x;
const inc = x => x + 1;
const sqr = x => x * x;
const neg = x => -x;
const computation = compose($_("inc"), $_("sqr"), $_("neg"));
console.log(computation);
/* yields:
((...args) => ((...args) => ((...args) =>
id(inc(...args))) (sqr(...args))) (neg(...args)))
*/
console.log(eval(computation) (2)); // 5 (= id(inc(sqr(neg(2))))
So what is going on here? I replaced the inner function (...args) => a(b(...args)) with a Template-String and arg => arg with the $_ helper function. Then I wrapped the Template-String in parenthesis, so that the resulting String represents an IIFE. Last but not least I pass $_ helper functions with proper names to compose.
$_ is a bit odd but it is really helpful to visualize unapplied/partially applied functions.
You can see from the computational structure that the reduce-composition builds a nested structure of anonymous functions and rest/spread operations are scattered throughout the code.
Visualizing and interpreting partially applied functions is hard. We can simplify it by omitting the inner anonymous function:
const compose = (...funcs) =>
funcs.reduce($xy("reducer"), $_("id"));
const $_ = name =>
`${name}`;
const $xy = name => (x, y) =>
`${name}(${x}, ${y})`;
const id = x => x;
const inc = x => x + 1;
const sqr = x => x * x;
const neg = x => -x;
console.log(
compose($_("inc"), $_("sqr"), $_("neg"))
// reducer(reducer(reducer(id, inc), sqr), neg)
);
We can further simplify by actually running the composition:
const compose = (...funcs) =>
funcs.reduce((a, b) => (...args) => a(b(...args)), $x("id"));
const $x = name => x =>
`${name}(${x})`;
console.log(
compose($x("inc"), $x("sqr"), $x("neg")) (2) // id(inc(sqr(neg(2))))
);
I believe that the visualization of complex computations like this is a powerful technique to comprehend them correctly and to gain a better understanding of nested/recursive computational structures.
Implementation show and tell? Okay -
const identity = x =>
x
const compose = (f = identity, ...fs) => x =>
f === identity
? x
: compose (...fs) (f (x))
const add1 = x =>
x + 1
console .log
( compose () (0) // 0
, compose (add1) (0) // 1
, compose (add1, add1) (0) // 2
, compose (add1, add1, add1) (0) // 3
)
Or instead of using compose in-line ...
const ListWithConditionalRendering = compose(
withLoadingIndicator,
withDataNull,
withListEmpty
)(Users);
You could make a sort of "forward composition" function where the argument comes first -
const $ = x => k =>
$ (k (x))
const add1 = x =>
x + 1
const double = x =>
x * 2
$ (0) (add1) (console.log)
// 1
$ (2) (double) (double) (double) (console.log)
// 16
$ (2) (double) (add1) (double) (console.log)
// 10
$ is useful when you can maintain a pattern of -
$ (value) (pureFunc) (pureFunc) (pureFunc) (...) (effect)
Above, $ puts a value into a sort of "pipeline", but there's no way to take the value out. A small adjustment allows us write very flexible variadic expressions. Below, we use $ as a way of delimiting the beginning and ending of a pipeline expression.
const $ = x => k =>
k === $
? x
: $ (k (x))
const double = x =>
x * 2
const a =
$ (2) (double) ($)
const b =
$ (3) (double) (double) (double) ($)
console .log (a, b)
// 4 24
This variadic interface gives you the ability to write expressions similar to the coveted |> operator found in other more function-oriented languages -
value
|> pureFunc
|> pureFunc
|> ...
|> pureFunc
5 |> add1
|> double
|> double
// 24
Using $, that translates to -
$ (value) (pureFunc) (pureFunc) (...) (pureFunc) ($)
$ (5) (add1) (double) (double) ($) // 24
The technique also mixes nicely with curried functions -
const $ = x => k =>
$ (k (x))
const add = x => y =>
x + y
const mult = x => y =>
x * y
$ (1) (add (2)) (mult (3)) (console.log)
// 9
Or with a slightly more interesting example -
const $ = x => k =>
$ (k (x))
const flatMap = f => xs =>
xs .flatMap (f)
const join = y => xs =>
xs .join (y)
const twice = x =>
[ x, x ]
$ ('mississippi')
(([...chars]) => chars)
(flatMap (twice))
(join (''))
(console.log)
// 'mmiissssiissssiippppii'

function composition with rest operator, reducer and mapper

I'm following an article about Transducers in JavaScript, and in particular I have defined the following functions
const reducer = (acc, val) => acc.concat([val]);
const reduceWith = (reducer, seed, iterable) => {
let accumulation = seed;
for (const value of iterable) {
accumulation = reducer(accumulation, value);
}
return accumulation;
}
const map =
fn =>
reducer =>
(acc, val) => reducer(acc, fn(val));
const sumOf = (acc, val) => acc + val;
const power =
(base, exponent) => Math.pow(base, exponent);
const squares = map(x => power(x, 2));
const one2ten = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10];
res1 = reduceWith(squares(sumOf), 0, one2ten);
const divtwo = map(x => x / 2);
Now I want to define a composition operator
const more = (f, g) => (...args) => f(g(...args));
and I see that it is working in the following cases
res2 = reduceWith(more(squares,divtwo)(sumOf), 0, one2ten);
res3 = reduceWith(more(divtwo,squares)(sumOf), 0, one2ten);
which are equivalent to
res2 = reduceWith(squares(divtwo(sumOf)), 0, one2ten);
res3 = reduceWith(divtwo(squares(sumOf)), 0, one2ten);
The whole script is online.
I don't understand why I can't concatenate also the last function (sumOf) with the composition operator (more). Ideally I'd like to write
res2 = reduceWith(more(squares,divtwo,sumOf), 0, one2ten);
res3 = reduceWith(more(divtwo,squares,sumOf), 0, one2ten);
but it doesn't work.
Edit
It is clear that my initial attempt was wrong, but even if I define the composition as
const compose = (...fns) => x => fns.reduceRight((v, fn) => fn(v), x);
I still can't replace compose(divtwo,squares)(sumOf) with compose(divtwo,squares,sumOf)
Finally I've found a way to implement the composition that seems to work fine
const more = (f, ...g) => {
if (g.length === 0) return f;
if (g.length === 1) return f(g[0]);
return f(more(...g));
}
Better solution
Here it is another solution with a reducer and no recursion
const compose = (...fns) => (...x) => fns.reduceRight((v, fn) => fn(v), ...x);
const more = (...args) => compose(...args)();
usage:
res2 = reduceWith(more(squares,divtwo,sumOf), 0, one2ten);
res3 = reduceWith(more(divtwo,squares,sumOf), 0, one2ten);
full script online
Your more operates with only 2 functions. And the problem is here more(squares,divtwo)(sumOf) you execute a function, and here more(squares,divtwo, sumOf) you return a function which expects another call (fo example const f = more(squares,divtwo, sumOf); f(args)).
In order to have a variable number of composable functions you can define a different more for functions composition. Regular way of composing any number of functions is compose or pipe functions (the difference is arguments order: pipe takes functions left-to-right in execution order, compose - the opposite).
Regular way of defining pipe or compose:
const pipe = (...fns) => x => fns.reduce((v, fn) => fn(v), x);
const compose = (...fns) => x => fns.reduceRight((v, fn) => fn(v), x);
You can change x to (...args) to match your more definition.
Now you can execute any number of functions one by one:
const pipe = (...fns) => x => fns.reduce((v, fn) => fn(v), x);
const compose = (...fns) => x => fns.reduceRight((v, fn) => fn(v), x);
const inc = x => x + 1;
const triple = x => x * 3;
const log = x => { console.log(x); return x; } // log x, then return x for further processing
// left to right application
const pipe_ex = pipe(inc, log, triple, log)(10);
// right to left application
const compose_ex = compose(log, inc, log, triple)(10);
I still can't replace compose(divtwo,squares)(sumOf) with compose(divtwo,squares,sumOf)
Yes, they are not equivalent. And you shouldn't try anyway! Notice that divtwo and squares are transducers, while sumOf is a reducer. They have different types. Don't build a more function that mixes them up.
If you insist on using a dynamic number of transducers, put them in an array:
[divtwo, squares].reduceRight((t, r) => t(r), sumOf)

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