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}; });
Lazy with one function
_(array).reduce(function(acc, n) { if(n > 998) acc.push({test: n}); return acc; }, []);
Strict with one function
_.reduce(array, function(acc, n) { if(n > 998) acc.push({test: n}); return acc; }, []);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Strict
Lazy
Lazy with one function
Strict with one function

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

I'd be happy to explain what's being tested in the provided JSON benchmark.

**Benchmark Overview**

The test cases measure the performance of two approaches for filtering and mapping an array using Lodash, a popular JavaScript utility library. The two approaches are:

1. **Strict**: Directly using Lodash's `map` function with a filter callback.
2. **Lazy**: Using Lodash's `_` alias (a shorthand for Lodash) to create a pipeline of operations, where the filtering and mapping are performed lazily.

**Lodash Library**

Lodash is a utility library that provides a wide range of functions for working with arrays, objects, and more. In this benchmark, Lodash's `map`, `filter`, and `_` alias are used. The `_` alias is used to create a pipeline of operations, which is the "lazy" approach.

**Test Cases**

The test cases measure the performance of each approach:

1. **Strict**: Directly using `_.map(_.filter(array, function(n) { return n > 998; }), function(n) { return {test: n}; });`
	* This approach uses `_.map` to apply a transformation function to each element in the filtered array.
2. **Lazy**:
	* **Lazy with one function**: `_([1,2,...])_.filter(function(n) { return n > 998; }).map(function(n) { return {test: n}; });`
		+ This approach uses Lodash's `_` alias to create a pipeline of operations.
		+ The `filter` operation is performed lazily on the original array, reducing its size dynamically.
	* **Strict with one function**: `_.reduce(array, function(acc, n) { if(n > 998) acc.push({test: n}); return acc; }, []);`
		+ This approach uses Lodash's `reduce` method to iterate over the array and perform an accumulation operation.

**Performance Comparison**

The benchmark measures the execution speed of each approach, which is reported as `ExecutionsPerSecond`. The results show that:

* The **Lazy with one function** approach is the fastest, with a higher executions per second value.
* The **Strict** approach is slower than both lazy approaches.
* The **Strict with one function** approach is faster than the direct `_.map` approach but still slower than the lazy approaches.

**Pros and Cons**

Here are some pros and cons of each approach:

1. **Lazy with one function**:
	* Pros: Faster execution speed, less memory allocation, and better cache locality.
	* Cons: May be more complex to understand and maintain due to pipeline operations.
2. **Lazy (using _)**:
	* Pros: Simplifies code and reduces boilerplate, can be more readable and maintainable.
	* Cons: May incur additional overhead due to the pipeline operation.
3. **Strict**:
	* Pros: Easy to understand and maintain, no unnecessary complexity.
	* Cons: Slower execution speed, more memory allocation.

**Special Features**

In this benchmark, we're using some special JavaScript features:

* `_` alias for Lodash functions (e.g., `_.map`, `_.filter`)
* Arrow functions (`function(n) { return {test: n}; }`)
* Reduced function calls and pipeline operations

Overall, the lazy approaches are faster due to reduced memory allocation and better cache locality. However, they can be more complex to understand and maintain. The strict approach is easier to understand but slower.

Latest run results:

Run details: (Test run date: 7 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; WOW64; rv:50.0) Gecko/20100101 Firefox/50.0

Browser/OS: Firefox 50 on Windows

View result in a separate tab

Test name	Executions per second
Strict	888044.8 Ops/sec
Lazy	511662.9 Ops/sec
Lazy with one function	111609.8 Ops/sec
Strict with one function	112092.5 Ops/sec

Related benchmarks:

Test lodash v2 (version: 0)

Comparing performance of: Strict vs Lazy vs Lazy with one function vs Strict with one function

Created: 8 years ago by: Guest

Jump to the latest result

Strict

Lazy

Lazy with one function

Strict with one function

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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