Benchmark: Lodash FP vs. Ramda 10,000

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/npm/ramda@0.26.1/dist/ramda.min.js"></script>
<script src="https://cdn.jsdelivr.net/npm/lodash@4.17.11/lodash.fp.min.js"></script>

Script Preparation code:

var array = Array(10000).fill().map(Math.random);

Tests:

Ramda.filter
R.filter(Math.round, array);
Lodash.filter
_.filter(Math.round, array);
Ramda.map
R.map(Math.round, array);
Lodash.map
_.map(Math.round, array);
Ramda.sortBy
R.sortBy(val => val, array);
Lodash.sortBy
_.sortBy(val => val, array);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Ramda.filter
Lodash.filter
Ramda.map
Lodash.map
Ramda.sortBy
Lodash.sortBy

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 5 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_14_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.100 Safari/537.36

Browser/OS: Chrome 75 on Mac OS X 10.14.5

View result in a separate tab

Test name	Executions per second
Ramda.filter	7726.1 Ops/sec
Lodash.filter	1008591.2 Ops/sec
Ramda.map	8541.8 Ops/sec
Lodash.map	854921.7 Ops/sec
Ramda.sortBy	180.3 Ops/sec
Lodash.sortBy	396.7 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's dive into the benchmark.

**Benchmark Definition**
The benchmark is designed to compare the performance of two popular functional programming libraries in JavaScript: Lodash and Ramda. The comparison is done by running a series of microbenchmarks on a large array of 10,000 random numbers using the `filter` and `map` operations.

**Options Compared**

There are four options being compared:

1. **Ramda**: A functional programming library that provides a set of utility functions for working with data.
2. **Lodash**: A popular JavaScript utility library that includes functional programming features.
3. **Ramda.filter**: The filtering operation in Ramda, which takes an array and a predicate function as input and returns a new array containing only the elements that pass the test.
4. **Lodash.filter**: The filtering operation in Lodash, which is similar to Ramda's filter but has some additional features.

**Pros and Cons**

* **Ramda and Lodash**: Both libraries are well-maintained and widely used, but they have different design philosophies and use cases. Ramda is generally considered more concise and expressive, while Lodash is often preferred for its sheer breadth of functionality.
	+ Pros: Higher performance in some cases, more concise code.
	+ Cons: Steeper learning curve, less comprehensive than Lodash.
* **Filter vs Map**: Both operations are useful, but they have different use cases. Filter is used to remove elements from an array that don't meet a certain condition, while map is used to transform each element of an array into something new.
	+ Pros: Different approaches can lead to more efficient code in some cases.
	+ Cons: Requires careful consideration of the use case to choose the right approach.

**Other Considerations**

* **Benchmarking**: The benchmarking process involves running a series of identical tests on multiple browsers and platforms to determine which library performs better. This helps to identify performance regressions and ensure that the libraries are optimized for different environments.
* **Library Features**: Lodash includes additional features beyond functional programming, such as string manipulation and utility functions like `_.forEach`. Ramda is more focused on functional programming.

**Library Use**

In this benchmark, both libraries are used to perform the filtering and mapping operations. The `filter` function in Ramda takes an array of random numbers and a predicate function that returns `true` for numbers that meet some condition (in this case, `Math.round`). The resulting array is then logged to the console.

Similarly, Lodash's `filter` function is used with the same input data and a similar predicate function. However, Lodash also includes additional features like memoization, which can affect performance in certain cases.

**Special JS Features or Syntax**

None of the libraries use any special JavaScript features or syntax that are not already covered by the standard ECMAScript language specification.

In summary, this benchmark compares the performance of Ramda and Lodash for filtering and mapping operations on a large array of random numbers. The results indicate that Ramda and Lodash have different performance characteristics, with Ramda generally performing better in some cases. However, both libraries have their strengths and weaknesses, and the choice between them depends on the specific use case and requirements.

**Alternatives**

Other functional programming libraries for JavaScript include:

* **Immutable.js**: A library that provides immutable data structures and a set of utility functions for working with them.
* **Cayman.js**: A library that provides a set of functional programming utilities, including `filter` and `map`.
* **Mochas**: A library that provides a set of testing utilities, including `expect` and `it`.

Each of these libraries has its own strengths and weaknesses, and the choice between them depends on the specific use case and requirements.

Related benchmarks:

Lodash FP vs. Ramda 10,000 (version: 0)

Comparing performance of: Ramda.filter vs Lodash.filter vs Ramda.map vs Lodash.map vs Ramda.sortBy vs Lodash.sortBy

Created: 5 years ago by: Guest

Jump to the latest result

Ramda.filter

Lodash.filter

Ramda.map

Lodash.map

Ramda.sortBy

Lodash.sortBy

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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