Benchmark: reduce vs map + fromEntries + parseJson 2 "

Script Preparation code:

var data = { ...Array.from(Array(10000).keys()) };

Tests:

1
Object.entries(data).reduce((acc, [k, v]) => { acc[k] = JSON.parse('{"atj": "was here"}') return acc; }, {});
2
Object.fromEntries(Object.entries(data).map(([k, v]) => ([k, JSON.parse('{"atj": "was here"}')])));

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
1
2

Fastest: N/A

Slowest: N/A

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

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Let's break down the benchmark and explain what's being tested.

**Benchmark Overview**

The benchmark measures the performance of two approaches to process an array of objects: `reduce` vs `map + fromEntries + parseJson`.

**Approaches Being Tested**

1. **Reduce**: The first approach uses `Object.entries(data).reduce((acc, [k, v]) => { ... })`. This method iterates over the array of key-value pairs returned by `Object.entries(data)` and applies a callback function to each pair.
2. **Map + fromEntries + parseJson**: The second approach uses `Object.fromEntries(Object.entries(data).map(([k, v]) => ([k, JSON.parse('{\"atj\": \"was here\"}')]))`. This method first maps over the array of key-value pairs using `map`, creates an array of arrays by converting each pair to a new array with two elements (key and value), then uses `Object.fromEntries` to convert this array of arrays into an object.

**Comparison**

The benchmark is comparing the performance of these two approaches. The results will show which approach is faster for processing the data.

**Pros and Cons**

1. **Reduce**:
	* Pros: More concise, easier to read, and can be more efficient since it only iterates over the array once.
	* Cons: Can be less readable if not familiar with the `reduce` method, and may have performance issues for very large datasets.
2. **Map + fromEntries + parseJson**:
	* Pros: May be more intuitive for those familiar with `map`, `fromEntries`, and `parseJson`. Can also handle multiple iterations over the data.
	* Cons: More verbose, requires an extra step to create the intermediate array, and may have performance overhead due to the additional iteration.

**Library Used**

The library used in this benchmark is not explicitly mentioned. However, it's likely that the `JSON.parse` method is being used, which is a built-in JavaScript function for parsing JSON strings into JavaScript objects.

**Special JS Feature/Syntax**

The benchmark uses the `fromEntries` and `map` methods, which are part of the ECMAScript standard (ES2019). These methods were introduced to provide more concise and expressive ways of working with arrays and objects. If you're not familiar with these methods, they might make your code harder to read.

**Alternatives**

If you want to implement this benchmark in your own JavaScript environment, here are some alternatives:

1. Use `Array.prototype.forEach` instead of `reduce`.
2. Implement a custom loop using `for` or `while` loops.
3. Compare the performance of different data structures (e.g., arrays vs objects) for similar operations.

Keep in mind that these alternatives might not be as concise or expressive as the original code, and may have performance implications.

**Benchmark Preparation Code**

The benchmark preparation code creates an array of 10,000 key-value pairs using `Array.from(Array(10000).keys())` and assigns it to the `data` variable.

Related benchmarks:

reduce vs map + fromEntries + parseJson 2 " (version: 0)

Comparing performance of: 1 vs 2

Created: 5 years ago by: Guest

Jump to the latest result

1

2

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):