Benchmark: Filter (Native vs. Generator)

Script Preparation code:

function* filter(iterable, predicate) {
    for (const item of iterable) {
        if (predicate(item)) {
            yield item;
        }
    }
}

var array = Array.from('YYYY-MM-DD HH:mm:ss.SSSZ');

Tests:

Native
var filtered = array.filter((patternToken) => patternToken.match(/\W/)); console.log(filtered);
Generator
var filtered = [...filter(array, (patternToken) => patternToken.match(/\W/))]; console.log(filtered);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Native
Generator

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

Let's dive into the provided benchmark.

The benchmark tests two approaches to filter an array of strings: one using the native `filter()` method and another using a generator function.

**Native Approach**

In the native approach, the `filter()` method is called on an array of date strings, where each string contains a pattern token (`\\W`) that matches any non-word character (e.g., `-`, `:`). The filtered array is then logged to the console.

The native approach uses built-in JavaScript functionality and is relatively simple to implement. However, it may have some limitations:

Pros:

* Easy to understand and implement
* Built-in function makes it a straightforward choice

Cons:

* May be slower due to the overhead of calling a built-in function
* Less control over the filtering process compared to a custom implementation

**Generator Approach**

In the generator approach, a custom `filter()` function is defined as a generator using the syntax `function* filter(iterable, predicate) { ... }`. This function yields each item that passes the predicate test. The filtered array is then created by spreading the yielded values into an array.

The generator approach offers more control over the filtering process and can be optimized for better performance:

Pros:

* More control over the filtering process
* Can be optimized for better performance

Cons:

* Requires a custom implementation, which may be less straightforward to understand
* May have additional overhead due to the creation of an iterator object

**Other Considerations**

Both approaches use regular expressions (`\\W`) to match non-word characters. Regular expressions can be powerful tools for pattern matching but may also introduce additional complexity.

Additionally, both approaches assume that the input array contains only date strings with a specific format (YYYY-MM-DD HH:mm:ss.SSSZ). If the input data is more varied or has different formats, the filtering process may need to be adjusted accordingly.

**Library and Custom Functionality**

In this benchmark, no libraries are explicitly used. However, the custom `filter()` function defined as a generator uses JavaScript syntax that was introduced in ECMAScript 2015 (ES6). This allows for more concise and expressive code but requires support for ES6 features.

**Alternative Approaches**

There are alternative approaches to filter an array of strings:

1. Using a library like Lodash or Ramda, which provide comprehensive sets of functional programming utilities.
2. Implementing a custom filtering function using a different data structure, such as a trie or a suffix tree.
3. Using a streaming algorithm that processes the input data in chunks rather than loading the entire array into memory.

In summary, the benchmark compares two approaches to filter an array of strings: one using the native `filter()` method and another using a custom generator function. The choice between these approaches depends on performance requirements, code complexity, and personal preference.

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/99.0.4844.51 Safari/537.36 Edg/99.0.1150.39

Browser/OS: Chrome 99 on Windows

View result in a separate tab

Test name	Executions per second
Native	102295.2 Ops/sec
Generator	84733.5 Ops/sec

Related benchmarks:

Filter (Native vs. Generator) (version: 18)

Comparing performance of: Native vs Generator

Created: 2 years ago by: Registered User

Jump to the latest result

Native

Generator

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):