Benchmark: Ramda's `where` vs. my `whereAll` - Part 3 - Nested Spec

HTML Preparation code:

<script src="https://unpkg.com/ramda@0.23.0/dist/ramda.js"></script>

Script Preparation code:

// Sort of like a recursive version of Ramda's `where` (http://ramdajs.com/docs/#where).
var whereAll = R.curry((spec, obj) => {
  if (typeof obj === "undefined") {
    if (spec === null || typeof spec === "boolean") {
      return !spec
    }
    return false
  } else if (spec === false) {
    return false
  }
  var output = true
  R.forEachObjIndexed((v, k) => {
    if (v === null || typeof v === "boolean" || R.keys(v).length) {
      if (!whereAll(v, obj[k])) {
        output = false
      }
    } else if (!v(obj[k])) {
      output = false
    }
  }, spec)
  return output
})

// -----------------------------------------------------------------------------

var data1 = {
  a: {
    h: [
      { i: 5 },
      [
        { j: 6, k: 7 },
        { j: 8, k: "nine" },
      ],
      10,
      { l: { m: { n: false } } },
    ],
  },
}

var data2 = {
  a: {
    h: [
      { i: 5 },
      [
        { j: 8, k: "nine" },
      ],
    ],
  },
}

var detect1 = R.where({
  a: R.where({
    h: R.where([
      R.always(true),
      Array.isArray,
      R.complement(R.identical(undefined)),
      R.where({ l: R.where({ m: R.where({ n: R.complement(R.identical(undefined)) }) }) }),
    ]),
  }),
})

var detect2 = whereAll({
  a: {
    h: [
      R.always(true),
      Array.isArray,
      R.complement(R.identical(undefined)),
      { l: { m: { n: R.complement(R.identical(undefined)) } } },
    ],
  },
})

var detect3 = whereAll({
  a: {
    h: [
      null,
      Array.isArray,
      true,
      { l: { m: { n: true } } },
    ],
  },
})

Tests:

Using `R.where`
detect1(data1) detect1(data2)
Using `whereAll`
detect2(data1) detect2(data2)
Using `whereAll` (alternate)
detect3(data1) detect3(data2)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Using `R.where`
Using `whereAll`
Using `whereAll` (alternate)

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

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

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**Overview**

MeasureThat.net is a website that allows users to create and run JavaScript microbenchmarks. The provided benchmark measures the performance difference between Ramda's `where` function and a custom implementation called `whereAll`. We will break down what is being tested, compare different approaches, discuss pros and cons, and explore alternative libraries.

**Benchmark Definition**

The benchmark definition is a JSON object that contains the script preparation code, HTML preparation code, individual test cases, and latest benchmark results. The script preparation code defines two custom functions: `whereAll` and `R.where`, which are implementations of Ramda's `where` function. The `whereAll` function checks if all properties in an object match a certain condition.

**Individual Test Cases**

There are three test cases:

1. **Using `R.where`**: This test case uses Ramda's `where` function with the same conditions as the `whereAll` function.
2. **Using `whereAll`**: This test case uses the custom `whereAll` function defined in the script preparation code.
3. **Using `whereAll` (alternate)**: This test case uses another implementation of `whereAll`, which is different from the first one.

**What is being tested?**

The benchmark tests the performance difference between three implementations:

* Ramda's `where` function
* Two custom implementations of `whereAll`

**Options Compared**

The options compared are:

1. **Ramda's `where` function**: A built-in implementation of the `where` function from the Ramda library.
2. **Custom implementation 1 (whereAll)**: The first custom implementation of `whereAll`, defined in the script preparation code.
3. **Custom implementation 2 (whereAll alternate)**: Another custom implementation of `whereAll`, which is different from the first one.

**Pros and Cons**

Here are some pros and cons for each option:

1. **Ramda's `where` function**
	* Pros:
		+ Built-in, optimized implementation
		+ Easy to use and understand
	* Cons:
		+ Might be slower than custom implementations due to overhead of the Ramda library
2. **Custom implementation 1 (whereAll)**
	* Pros:
		+ Optimized for specific use cases (nested objects with arrays)
		+ Customizable to fit specific requirements
	* Cons:
		+ Requires manual handling of edge cases and potential issues with array manipulation
3. **Custom implementation 2 (whereAll alternate)**
	* Pros:
		+ Might be faster than the first custom implementation due to different optimizations
	* Cons:
		+ Unknown performance characteristics, as it's a different implementation

**Library: Ramda**

Ramda is a popular JavaScript library for functional programming. The `where` function in this benchmark is part of Ramda's API and provides a concise way to filter objects based on conditions.

**Special JS Features or Syntax (None)**

There are no special JavaScript features or syntax used in this benchmark, except for the use of Ramda's `curry` method to create higher-order functions.

**Other Alternatives**

If you need to implement a similar filtering mechanism, consider using:

* Lodash's `filterBy` function
* A simple recursive function implementation
* A library like Immutable.js or MobX for state management and filtering

In conclusion, the benchmark measures the performance difference between Ramda's `where` function and two custom implementations of `whereAll`. The choice of implementation depends on specific requirements, optimization needs, and familiarity with functional programming.

Related benchmarks:

Ramda's `where` vs. my `whereAll` - Part 3 - Nested Spec (version: 14)

Comparing performance of: Using `R.where` vs Using `whereAll` vs Using `whereAll` (alternate)

Created: 9 years ago by: Registered User

Jump to the latest result

Using `R.where`

Using `whereAll`

Using `whereAll` (alternate)

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):