Benchmark: Compare the new ES6 spread operator with Ramda assoc using reduce

HTML Preparation code:

<script src="https://cdnjs.cloudflare.com/ajax/libs/ramda/0.25.0/ramda.js"></script>

Script Preparation code:

var translations = [...Array(500).keys()].map((key) => ({term: ''+Math.random(), translation: '' + Math.random()}));
var data = {iso: 'foof', translations};

Tests:

reduce + spread operator
JSON.stringify( data.translations.reduce((acc, x) => ({ ...acc, [x.term]: x.translation }), {}), null, 4, )
for
var trans = {}; for (const x of data.translations) { trans[x.term] = x.translation; } JSON.stringify(translations, null, 4)
assoc + reduce
JSON.stringify( data.translations.reduce((acc, x) => R.assoc(x.term, x.translation, acc), {}), null, 4, )

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
reduce + spread operator
for
assoc + reduce

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

This benchmark does not have any results yet. Be the first one to run it!

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

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks on MeasureThat.net.

The benchmark is designed to compare three different approaches for transforming an array of objects into an object with nested properties:

1. Using the `reduce()` method with the spread operator (`{ ...acc, [x.term]: x.translation }`)
2. Using a traditional `for` loop
3. Using Ramda's `assoc()` function

The benchmark is testing how fast each approach can serialize an object created by reducing the array of objects.

**Options being compared:**

1. **Reduce + Spread Operator**: This approach uses the `reduce()` method to iterate over the array of objects, creating a new object with nested properties using the spread operator (`{ ...acc, [x.term]: x.translation }`). The resulting object is then serialized.
2. **For Loop**: This traditional approach uses a `for` loop to iterate over the array of objects, assigning each property to the target object (`trans[x.term] = x.translation;`) before serializing the result.
3. **Assoc + Reduce**: This approach uses Ramda's `assoc()` function to create an object with nested properties from the array of objects.

**Pros and Cons:**

* **Reduce + Spread Operator**:
	+ Pros: concise, expressive code; efficient use of spread operator for creating new objects.
	+ Cons: may be less readable for those unfamiliar with reduce() or spread operator; can be slower due to object creation overhead.
* **For Loop**:
	+ Pros: well-established, familiar syntax; can be more readable for those accustomed to traditional loops.
	+ Cons: verbose code; slower than reduce() or assoc() due to loop overhead.
* **Assoc + Reduce (with Ramda)**:
	+ Pros: concise and expressive code; leverages the power of functional programming with Ramda.
	+ Cons: requires familiarity with Ramda library; may introduce additional dependencies.

**Libraries and Special JS Features:**

The benchmark uses Ramda's `assoc()` function, which is a higher-order function that creates an object with a nested property. This function relies on Ramda's immutability model and its internal implementation details to optimize performance.

**Test Case Breakdown:**

Each test case follows the same structure:

* The **Benchmark Definition** specifies the code being tested (e.g., `JSON.stringify(data.translations.reduce((acc, x) => ({ ...acc, [x.term]: x.translation }), {}), null, 4)`)
* The **Test Name** identifies the specific test case (e.g., "reduce + spread operator")

**Alternatives:**

For those interested in exploring alternative approaches, you can consider:

1. Using a different serialization library or method (e.g., JSON.stringify with custom replacer function)
2. Implementing your own reduce() or assoc() functions
3. Investigating other functional programming libraries or utilities (e.g., Lodash) for similar tasks

When evaluating these alternatives, keep in mind the trade-offs between performance, readability, and maintainability.

I hope this explanation helps you navigate the JavaScript microbenchmark on MeasureThat.net!

Related benchmarks:

Compare the new ES6 spread operator with Ramda assoc using reduce (version: 0)

Comparing performance of: reduce + spread operator vs for vs assoc + reduce

Created: 4 years ago by: Guest

Jump to the latest result

reduce + spread operator

for

assoc + reduce

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):