Benchmark: Apply array of filters to array

Tests:

Reduce
const items = [{x: 1}, {x: 2}, {x: 3}, {x: 4}, {x: 5}, {x: 6}]; const not1Filter = (item) => item.x != 1; const not2Filter = (item) => item.x != 2; const not6Filter = (item) => item.x != 6; const filters = [not1Filter, not2Filter, not6Filter]; const result = filters.reduce((acc, f)=> acc.filter(f), items);
Filter every
const items = [{x: 1}, {x: 2}, {x: 3}, {x: 4}, {x: 5}, {x: 6}]; const not1Filter = (item) => item.x != 1; const not2Filter = (item) => item.x != 2; const not6Filter = (item) => item.x != 6; const filters = [not1Filter, not2Filter, not6Filter]; const result2 = items.filter(item => filters.every((f)=>f(item)));

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Reduce
Filter every

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 explanation of what's being tested in this benchmark.

**Overview**

The provided benchmark tests two approaches to filter an array of objects: `reduce` and `filter every`. The test data consists of an array of objects with a single property "x" containing numbers from 1 to 6. Two filters, `not1Filter`, `not2Filter`, and `not6Filter`, are defined to exclude items where the value of "x" is not equal to 1, 2, or 6, respectively.

**Options being compared**

Two options are being compared:

1. **Reduce**: This approach iterates through each item in the array and applies each filter to it using a accumulator function.
2. **Filter every**: This approach applies all filters to each item in the array simultaneously.

**Pros and Cons of each approach:**

**Reduce**

* Pros:
	+ Can handle arrays with large number of elements efficiently by processing them one-by-one, reducing memory allocation.
	+ Allows for easy implementation of conditional logic using accumulator functions.
* Cons:
	+ More complex to understand and implement due to the use of accumulator function.
	+ May be slower for very large arrays since it requires multiple iterations.

**Filter every**

* Pros:
	+ Simplifies code by applying filters directly to each item, reducing cognitive load.
	+ Can be faster than `reduce` for very large arrays as it only requires a single pass through the array.
* Cons:
	+ Requires all filters to be applied simultaneously, which can lead to slower performance if multiple filters are expensive or complex.
	+ May require additional memory allocation for intermediate results.

**Libraries and Special JavaScript Features**

There is no explicit library mentioned in the provided benchmark definition. However, it's worth noting that `filter` and `reduce` methods are built-in JavaScript functions that can be used to achieve these filtering results without any additional libraries.

No special JavaScript features are being tested or utilized in this benchmark. The code only uses standard JavaScript syntax and built-in methods.

**Other Alternatives**

Alternative approaches to filtering arrays could include:

* **forEach**: Instead of using `filter` or `reduce`, you can use a loop with `forEach` to iterate through each item in the array.
* **Map**: Another alternative is to use the `map` function to create a new array with filtered items, although this might be less efficient than using `filter`.
* **Array.prototype.some**: Some might argue that `some` could be used instead of `every`, but since `every` ensures all filters are applied, replacing it wouldn't yield the same results.

Please note, while alternatives exist, some options might not be as efficient or readable as the provided implementations.

Related benchmarks:

Apply array of filters to array (version: 0)

Comparing performance of: Reduce vs Filter every

Created: 5 years ago by: Guest

Jump to the latest result

Reduce

Filter every

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):