Exploring the implementation of a functional accumulator inspired by Haskell in JavaScript functions

Question

Exploring the implementation of a functional accumulator inspired by Haskell in JavaScript functions

Exploring Haskell has captivated me, particularly its end-recursive functions with an accumulator.

Curiosities:

Is there a similar construct in javascript? Is it even practical given that javascript lacks the functional nature of Haskell?
Are there any libraries like ramda or lodash that support this style of programming?

If so, how would you implement this in javascript, for instance:

 power_acc :: Double -> Int -> Double
 power_acc x y = power_acc_h x y 1

 power_acc_h :: Double -> Int -> Double -> Double
 power_acc_h x 0 acc = acc
 power_acc_h x y acc = power_acc_h x (y-1) (acc*x)

javascript haskell underscore.js lodash ramda.js

Answer 1

Answer №1

Is there a similar construct in JavaScript?

Absolutely, you can directly translate this to JS:

function calculatePower(x, y) { // Double -> Int -> Double
    y = y>>>0; // ensure positive int (prevent nontermination)
    return calculatePowerHelper(x, y, 1);
}
function calculatePowerHelper(x, y, acc) { // Double -> Int -> Double -> Double
    return y == 0
      ? acc
      : calculatePowerHelper(x, y-1, acc*x);
}

Does it make sense in terms of efficiency considering JavaScript is not as functional as Haskell?

ES6 fully supports tail recursion in JS now, offering the same efficiency as loops (potentially even better than Haskell since lazy multiplications are avoided).

Are there any libraries like ramda, lodash, etc., that facilitate this style of programming?

No need for a library. However, there may be libraries simplifying type checks or providing better notation for pattern matching.

How would you implement this concept in JavaScript?

You'd employ a while loop. All accumulation functions in Haskell follow this formula because they optimize into a loop effectively. The following concise notation using a loop is preferred in JS:

function calculatePower(x, y) { // Double -> Int -> Double
    y = y>>>0; // ensure positive int (prevent nontermination)
    var acc = 1;
    while (y != 0) {
        acc *= x;
        y -= 1;
    }
    return acc;
}

Mutating local variables doesn't harm purity. For brevity, consider using a for loop.

Answer 2

Is there a similar construct in JavaScript?

Absolutely, you can directly translate this to JS:

function calculatePower(x, y) { // Double -> Int -> Double
    y = y>>>0; // ensure positive int (prevent nontermination)
    return calculatePowerHelper(x, y, 1);
}
function calculatePowerHelper(x, y, acc) { // Double -> Int -> Double -> Double
    return y == 0
      ? acc
      : calculatePowerHelper(x, y-1, acc*x);
}

Does it make sense in terms of efficiency considering JavaScript is not as functional as Haskell?

ES6 fully supports tail recursion in JS now, offering the same efficiency as loops (potentially even better than Haskell since lazy multiplications are avoided).

Are there any libraries like ramda, lodash, etc., that facilitate this style of programming?

No need for a library. However, there may be libraries simplifying type checks or providing better notation for pattern matching.

How would you implement this concept in JavaScript?

You'd employ a while loop. All accumulation functions in Haskell follow this formula because they optimize into a loop effectively. The following concise notation using a loop is preferred in JS:

function calculatePower(x, y) { // Double -> Int -> Double
    y = y>>>0; // ensure positive int (prevent nontermination)
    var acc = 1;
    while (y != 0) {
        acc *= x;
        y -= 1;
    }
    return acc;
}

Mutating local variables doesn't harm purity. For brevity, consider using a for loop.

Answer 3

Answer №2

The translation of the Haskell code into JavaScript is as follows:

function calculatePower(x, y) {
    return operate(x, y, 1);
    function operate(x, y, result) {
        if (y === 0)
            return result;
        else
            return operate(x, y - 1, result * x);
    }
}

Are there any libraries similar to ramda or lodash that support this programming style?

You actually don't need ramda or lodash for this specific case. You can achieve the same functionality using plain JavaScript just like demonstrated above. It's important to remember that lodash is a utility library designed for consistent operations on collections in a functional manner, and may not be useful in situations like these.

Answer 4

The translation of the Haskell code into JavaScript is as follows:

function calculatePower(x, y) {
    return operate(x, y, 1);
    function operate(x, y, result) {
        if (y === 0)
            return result;
        else
            return operate(x, y - 1, result * x);
    }
}

Are there any libraries similar to ramda or lodash that support this programming style?

You actually don't need ramda or lodash for this specific case. You can achieve the same functionality using plain JavaScript just like demonstrated above. It's important to remember that lodash is a utility library designed for consistent operations on collections in a functional manner, and may not be useful in situations like these.

Answer 5

Answer №3

Adding on to Sibi's response, it is worth noting that JavaScript, specifically nodejs, does indeed allocate stack space. It performs efficiently up to exponents around 13,000, beyond which a

RangeError: Maximum call stack size exceeded

occurs. To conduct this experiment successfully, the base must be set close to 1 (e.g. 1.0001) to avoid getting Infinity.

In contrast, Haskell does not face this issue. Even an exponent 1000 times larger (i.e. 13,000,000) does not result in space problems, although it may take a few seconds to execute. The reason behind this efficiency lies in Haskell's tail call recursion, which runs in constant space.

Therefore, while Sibi's explanation resembles Haskell's elegance, there are distinct differences in their runtime behaviors. Unfortunately, there may not be a solution to reconcile these disparities.

Answer 6

Adding on to Sibi's response, it is worth noting that JavaScript, specifically nodejs, does indeed allocate stack space. It performs efficiently up to exponents around 13,000, beyond which a

RangeError: Maximum call stack size exceeded

occurs. To conduct this experiment successfully, the base must be set close to 1 (e.g. 1.0001) to avoid getting Infinity.

In contrast, Haskell does not face this issue. Even an exponent 1000 times larger (i.e. 13,000,000) does not result in space problems, although it may take a few seconds to execute. The reason behind this efficiency lies in Haskell's tail call recursion, which runs in constant space.

Therefore, while Sibi's explanation resembles Haskell's elegance, there are distinct differences in their runtime behaviors. Unfortunately, there may not be a solution to reconcile these disparities.

Answer 7

Answer №4

In my opinion, a library is not necessary nor particularly beneficial. (By the way, I am one of the creators of Ramda.)

Bergi's JavaScript translation is satisfactory, although I believe it is more idiomatic, especially in browser-side JS, to encapsulate the helper function within a local closure, similar to Sibi's suggestion.

Martin Drautzburg raises a valid point about the performance issue due to the lack of widespread implementation of tail-call optimization, despite being specified. One exception is Babel's support for direct recursion, which can provide the expected performance advantage in a Babel-transpiled version.

If you are pursuing this for its elegance and have faith that TCO will be widely implemented soon, and if current potential performance issues do not concern you, then these responses offer valuable insights. Additionally, here's another ES6 technique:

// Double -> Int -> Double -> Double
function powerAcc(x, y, acc = 1) {
    return y == 0 ? acc : powerAcc(x, y - 1, acc * x);
}

powerAcc(2, 5); //=> 32

Default function parameters can help replace some basic forms of pattern matching in this language, which lacks true pattern matching capabilities. While still dependent on TCO, this approach results in cleaner code and should perform well in Babel.

Answer 8

In my opinion, a library is not necessary nor particularly beneficial. (By the way, I am one of the creators of Ramda.)

Bergi's JavaScript translation is satisfactory, although I believe it is more idiomatic, especially in browser-side JS, to encapsulate the helper function within a local closure, similar to Sibi's suggestion.

Martin Drautzburg raises a valid point about the performance issue due to the lack of widespread implementation of tail-call optimization, despite being specified. One exception is Babel's support for direct recursion, which can provide the expected performance advantage in a Babel-transpiled version.

If you are pursuing this for its elegance and have faith that TCO will be widely implemented soon, and if current potential performance issues do not concern you, then these responses offer valuable insights. Additionally, here's another ES6 technique:

// Double -> Int -> Double -> Double
function powerAcc(x, y, acc = 1) {
    return y == 0 ? acc : powerAcc(x, y - 1, acc * x);
}

powerAcc(2, 5); //=> 32

Default function parameters can help replace some basic forms of pattern matching in this language, which lacks true pattern matching capabilities. While still dependent on TCO, this approach results in cleaner code and should perform well in Babel.

Exploring the implementation of a functional accumulator inspired by Haskell in JavaScript functions

Answer №1

Answer №2

Answer №3

Answer №4

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