Benchmark: Test lodash v2 - MeasureThat.net

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/lodash/4.16.0/lodash.min.js"></script>

Script Preparation code:

var array = _.range(1000);

Tests:

Strict
_.map(_.filter(array, function(n) { return n > 998; }), function(n) { return {test: n}; });
Lazy
_(array).filter(function(n) { return n > 998; }).map(function(n) { return {test: n}; });

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Strict
Lazy

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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I'd be happy to help explain the JavaScript benchmark on MeasureThat.net.

**Overview**

The benchmark measures the performance of two ways of using the Lodash library, which is a popular utility library for JavaScript. The test cases compare the execution speed of two different approaches: "Strict" and "Lazy".

**What's being tested?**

In the first test case, "_map(_.filter(array, function(n) { return n > 998; }), function(n) { return {test: n}; });", we have a strict pipeline:

1. `_.filter(array, ...)` applies the filter function to the entire array and returns a new array with only the elements that pass the test.
2. `_()` is an alias for Lodash's `_` function, which returns the value returned by the function passed as its argument.
3. `.map(...)` applies the mapping function to each element of the filtered array.

In contrast, the second test case uses a lazy approach: "_(array).filter(...) .map(...)_". This pipeline is executed in two steps:

1. `_(array)` returns an object that can be used as a cache, so subsequent calls to this object with the same arguments will return the cached result.
2. `.filter(...)` applies the filter function to the array.
3. `.map(...)` applies the mapping function to each element of the filtered array.

**Pros and Cons**

**Strict approach:**

* Pros:
	+ May be easier to understand for some developers, as it's a more straightforward pipeline.
	+ Can be faster if the cache is not hit often enough (i.e., the filter function takes too long to execute).
* Cons:
	+ If the filter function is slow, it can significantly impact performance.
	+ The cache may not always be effective, especially if the filter function has side effects or returns new values.

**Lazy approach:**

* Pros:
	+ Reduces overhead by avoiding unnecessary calculations and intermediate results.
	+ May be faster when the filter function is fast and doesn't produce a lot of side effects.
* Cons:
	+ Can lead to more complex code, making it harder to understand for some developers.
	+ The cache may not always be effective, especially if the filter function has side effects or returns new values.

**Lodash library**

The Lodash library provides several aliases and utility functions that simplify common tasks. In this benchmark, `_.map` and `_.filter` are used as aliases for `Array.prototype.map` and `Array.prototype.filter`, respectively.

**Other alternatives**

There are other ways to achieve the same result without using Lodash:

* Using vanilla JavaScript: `array.filter(function(n) { return n > 998; }).map(function(n) { return {test: n}; })`
* Using a different utility library (e.g., Ramda)

In conclusion, this benchmark compares two approaches to applying filter and map functions in Lodash. The strict approach can be faster if the cache is not hit often enough, while the lazy approach reduces overhead by avoiding unnecessary calculations and intermediate results.

Related benchmarks:

Test lodash v2 (version: 0)

Comparing performance of: Strict vs Lazy

Created: 9 years ago by: Guest

Jump to the latest result

Strict

Lazy

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):