Benchmark: lodash reduce vs. mapValues

HTML Preparation code:

<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.min.js'></script>

Tests:

lodash reduce
var fruits= { 'A': { 'name': 'apple', 'number': 5}, 'O': { 'name': 'orange', 'number': 10 }, 'B': { 'name': 'banana', 'number': 15 }, }; console.log( _.reduce( fruits, (acc, name, code) => { acc[code] = { name }; return acc; }, {} ) );
lodash mapValues
var fruits= { 'A': { 'name': 'apple', 'number': 5}, 'O': { 'name': 'orange', 'number': 10 }, 'B': { 'name': 'banana', 'number': 15 }, }; console.log( _.mapValues( fruits, (fruit) => ({ name: fruit.name }) ) );

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
lodash reduce
lodash mapValues

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 dive into the world of JavaScript microbenchmarks.

**What is being tested?**

The provided JSON represents two individual test cases for comparing the performance of `lodash.reduce` and `lodash.mapValues`. The test cases use an object called "fruits" with three properties ("A", "O", and "B") that contain nested objects and values. The tests measure how quickly these two functions can transform this data structure.

**Options being compared:**

1. **Lodash Reduce**: This function takes an array-like object, a callback function, and an initial value (in this case, an empty object). It iterates over the object's properties, applying the callback function to each property value, accumulating the results in the accumulator.
2. **Lodash MapValues**: This function takes an object, a mapping function, and returns a new object with the same keys but transformed values.

**Pros and Cons:**

1. **Lodash Reduce**
	* Pros:
		+ Can be used to transform nested objects by applying a callback function to each property value.
		+ Allows for easy manipulation of complex data structures.
	* Cons:
		+ May have higher overhead due to the need to iterate over properties and accumulate results.
2. **Lodash MapValues**
	* Pros:
		+ More lightweight compared to reduce, as it only requires a simple mapping function.
		+ Can be used to extract specific values from an object without modifying its structure.
	* Cons:
		+ May not be suitable for transforming complex data structures that require nested operations.

**Library and Purpose:**

Lodash (now known as Lodash.js) is a popular JavaScript utility library that provides a collection of functions for various tasks, including data manipulation, string manipulation, and more. The `mapValues` function in particular is designed to extract specific values from an object based on a given key.

**Special JS feature or syntax:**

None mentioned in the provided test cases.

**Other considerations:**

* **Performance**: Measuring performance is crucial when comparing different algorithms, as it directly affects the application's responsiveness and scalability.
* **Code readability and maintainability**: Choosing between `reduce` and `mapValues` should consider how well each option aligns with your codebase's existing architecture and readability standards.

**Other alternatives:**

1. **Vanilla JavaScript**: Instead of using Lodash, you could implement the same functionality using vanilla JavaScript's built-in methods, such as `forEach()` or `reduce()`.
2. **Other libraries**: Depending on your specific use case, other libraries like Underscore.js (a predecessor to Lodash) or even a custom implementation might be more suitable.

In conclusion, when deciding between `lodash.reduce` and `lodash.mapValues`, consider the type of data transformation you need, potential performance implications, and code readability requirements.

Related benchmarks:

lodash reduce vs. mapValues (version: 0)

Comparing performance of: lodash reduce vs lodash mapValues

Created: 4 years ago by: Guest

Jump to the latest result

lodash reduce

lodash mapValues

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):