Benchmark: curryChain - MeasureThat.net

Script Preparation code:

window.round = (value, decimalScale) => {
  const scale = Math.pow(10, decimalScale);
  return Math.round(value * scale) / scale;
}

window.snap = (value, increment) => {
  return Math.round(value / increment) * increment;
}

window.clamp = (value, min, max) => {
  return Math.min(Math.max(value, min), max);
}

const noop = () => {};

const curry = (fn, right) => (...args) => right ? v => fn(...args, v) : v => fn(v, ...args);

const chain = fn => (...args) => {
  const result = fn(...args);
  return new Proxy(noop, {
    apply: (_, __, [value]) => result(value),
    get: (_, prop) => chain((...nextArgs) => {
      const nextResult = utils[prop](...nextArgs);
      return value => nextResult(result(value));
    })
  });
}

const makeChainable = (fn, right = 0) => (...args) => (args.length < fn.length ? chain(curry(fn, right)) : fn)(...args);

window.utils = {
  round: makeChainable(round),
  snap: makeChainable(snap),
  clamp: makeChainable(clamp),
};

const randomNumber = Math.random();
window.cachedRaw = v => round(clamp(snap(v, 10.2222), 20.5555, 40.5555), 2);
window.cachedDirect = v => utils.round(utils.clamp(utils.snap(v, 10.2222), 20.5555, 40.5555), 2);
window.cachedChain = utils.snap(10.2222).clamp(20.5555, 40.5555).round(2);

Tests:

Raw
cachedRaw(Math.random() * 100);
Direct
cachedDirect(Math.random() * 100);
Chain
cachedChain(Math.random() * 100);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Raw
Direct
Chain

Fastest: N/A

Slowest: N/A

Latest run results:

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Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

LLMs can make mistakes. Check important info.

Let's break down the provided JSON and explain what is tested on the benchmark.

**Benchmark Definition**

The benchmark definition provides a JavaScript function that defines several utility functions: `round`, `snap`, and `clamp`. These functions are used to manipulate numbers. The `curry` and `chain` functions are used to create chainable versions of these utilities.

* `round`: rounds a number to a specified decimal scale.
* `snap`: returns the nearest multiple of an increment value.
* `clamp`: limits a value within a specified range.

**Options Compared**

The benchmark compares three different approaches to perform the same calculation:

1. **Raw**: The original implementation that calls `cachedRaw` directly.
2. **Direct**: An implementation that uses `cachedDirect` to calculate the result.
3. **Chain**: An implementation that uses `cachedChain` to calculate the result.

**Pros and Cons of Each Approach**

* **Raw**:
	+ Pros: Simple, straightforward implementation.
	+ Cons: May not be optimized for performance.
* **Direct**:
	+ Pros: Can potentially be faster than Raw since it avoids the overhead of `utils`.
	+ Cons: Requires more function calls, which can increase overhead.
* **Chain**:
	+ Pros: Can potentially be faster and more efficient due to lazy evaluation.
	+ Cons: May require more memory allocation and deallocation.

**Library**

The benchmark uses a custom library called `utils` that provides the `round`, `snap`, and `clamp` functions. This library is created using the `makeChainable` function, which creates chainable versions of these utilities.

* `utils`: A custom library that provides utility functions for rounding, snapping, and clamping numbers.
* `makeChainable`: A function that takes a utility function and returns a chainable version of it.

**Special JS Feature**

The benchmark uses the `Proxy` object to create a proxy around the `noop` function. This is not a special JavaScript feature per se, but rather a common technique for implementing lazy evaluation.

* `Proxy`: A built-in JavaScript object that allows creating proxies around other objects or functions.

Now, let's discuss the test cases and benchmark results:

The benchmark consists of three test cases: Raw, Direct, and Chain. Each test case calls one of the utility functions (`cachedRaw`, `cachedDirect`, or `cachedChain`) with a random number.

The benchmark results show that the Chain approach is the fastest, followed by Direct, and then Raw. This suggests that lazy evaluation using the `chain` function can lead to significant performance improvements in this specific use case.

Related benchmarks:

curryChain (version: 0)

Comparing performance of: Raw vs Direct vs Chain

Created: 2 years ago by: Registered User

Jump to the latest result

Raw

Direct

Chain

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):