Benchmark: Reduce vs loop321321

HTML Preparation code:

<script src="https://raw.githubusercontent.com/lodash/lodash/4.17.15-npm/core.js"></script>

Tests:

WIth loop321321
var mapping = { 'apple': 5, 'orange': 10 }; var fruits = ['apple', 'orange']; const keys = Object.keys(mapping); const rows = fruits.map((row) => { const transformed = {}; for (const key of keys) { transformed[key] = mapping[key]; } return transformed; }); console.log(rows);
With reduce23132
var mapping = { 'apple': 5, 'orange': 10 }; var fruits = ['apple', 'orange']; var keys = Object.keys(mapping); var rows = fruits.map((row) => { const transformed = {}; for (var key of keys) { transformed[key] = mapping[key]; } return transformed; }); var rows = fruits.map((row) => Object.entries(mapping).reduce((acc, [key, transform]) => { acc[key] = transform; return acc; }, {}), ); console.log(rows);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
WIth loop321321
With reduce23132

Fastest: N/A

Slowest: N/A

Latest run results:

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

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Let's dive into the explanation of the provided benchmark.

**Overview**

The test compares two approaches to transform an object mapping with JavaScript arrays: using a `for...of` loop and using the `reduce()` method.

**Options Compared**

Two options are compared:

1. **Loop-based approach**: This approach uses a `for...of` loop to iterate over the keys of the `mapping` object and assigns the corresponding values to a new object.
2. **Reduce-based approach**: This approach uses the `reduce()` method to transform the `mapping` object into a new object, where each key-value pair is created by iterating over the key-value pairs of the original object.

**Pros and Cons**

**Loop-Based Approach:**

Pros:

* Simple and easy to understand for beginners
* Can be optimized for specific use cases (e.g., caching)

Cons:

* Less efficient than the `reduce()` approach, especially for large datasets
* May not be as scalable or flexible

**Reduce-Based Approach:**

Pros:

* More efficient and scalable than the loop-based approach
* Can handle large datasets and complex transformations

Cons:

* May be less intuitive or difficult to understand for beginners
* Requires knowledge of the `reduce()` method and its usage patterns

**Library Used: Lodash**

The benchmark uses the Lodash library, specifically the `Object.keys()` and `reduce()` functions. The `Object.keys()` function returns an array of a given object's own enumerable property names, while the `reduce()` function applies a transformation to each element in an array.

**Special JS Feature or Syntax: None**

There are no special JavaScript features or syntax used in this benchmark that would require additional explanation.

**Other Alternatives**

If you're looking for alternative approaches, here are a few options:

1. **Using `forEach()`**: You can use the `forEach()` method to iterate over an array of keys and assign values to a new object.
2. **Using `map()` with a callback function**: You can use the `map()` method with a callback function to transform each key-value pair in the `mapping` object into a new object.
3. **Using a custom implementation**: Depending on your specific requirements, you may be able to implement a custom solution that optimizes performance and scalability.

In summary, the benchmark compares two approaches to transforming an object mapping: using a loop-based approach and using the `reduce()` method. The reduce-based approach is more efficient but may require more knowledge of JavaScript and its methods.

Related benchmarks:

Reduce vs loop321321 (version: 0)

Comparing performance of: WIth loop321321 vs With reduce23132

Created: 4 years ago by: Guest

Jump to the latest result

WIth loop321321

With reduce23132

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):