Benchmark: Filter vs for - MeasureThat.net

Script Preparation code:

window.parentObj = [];

for (let i = 0; i < 1000; i++) {
  window.parentObj.push(Math.floor(Math.random() * 4294967295));
}

Tests:

Filter
const newObj = window.parentObj.filter(n => n % 2);
for of
const newObj = []; for (const n of window.parentObj) { if ((n % 2) === 0) { newObj.push(n); } }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Filter
for of

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated 9 days ago):

LLMs can make mistakes. Check important info.

The benchmark provided compares two different approaches for filtering an array of numbers: using the `Array.prototype.filter` method versus a traditional `for...of` loop. This evaluation is useful for software engineers as it highlights the performance implications of using modern JavaScript features compared to classical iterations.

### Overview of the Benchmarked Approaches

1. **Filter Method:**
   - **Benchmark Definition:** `const newObj = window.parentObj.filter(n => n % 2);`
   - **Test Name:** "Filter"
   - **Description:** This uses the `filter` function to create a new array containing all elements from `window.parentObj` that pass the test implemented by the provided callback function (in this case, it includes odd numbers).
   - **Pros:**
     - Conciseness: The code is simpler and more readable, which can enhance maintainability.
     - Expressiveness: The intent of filtering is clear immediately due to the function's name and structure.
   - **Cons:**
     - Performance: As shown in the benchmark results, it may be slightly slower (190,415 executions per second) than the `for...of` loop, especially when processing large arrays.
     - Memory Usage: Since `filter` returns a new array, if the input array is large, it could increase memory consumption, possibly impacting overall performance.

2. **For...of Loop:**
   - **Benchmark Definition:** 
     ```javascript
     const newObj = [];
     for (const n of window.parentObj) {
         if ((n % 2) === 0) {
             newObj.push(n);    
         }
     }
     ```
   - **Test Name:** "for of"
   - **Description:** This approach employs a `for...of` loop to iterate over each number in `window.parentObj`, checking if it's even (i.e., divisible by 2). If so, it pushes that number into a new array.
   - **Pros:**
     - Performance: This method recorded a marginally higher performance (189,184.66 executions per second).
     - Flexibility: Provides more control over the logic within the loop, which can be beneficial for more complex filtering conditions that don't fit well into a single function call.
   - **Cons:**
     - Verbosity: The code is longer and may be harder to read or maintain, especially if the filtering logic is complex.
     - Clarity: Less expressiveness around the action of filtering compared to the `filter` method.

### Performance and Other Considerations
- **Results Interpretation:** The benchmark results indicate that both methods perform similarly, with the `filter` method having a slight edge in actual execution speed. However, the difference may not be significant for smaller datasets.
- **Use Cases:** The choice between these methods can be situational. If performance is critical and you're dealing with large datasets, the `for...of` loop may be beneficial. However, for cleaner and more understandable code, `filter` is often preferred in modern JavaScript.

### Alternative Approaches
- **For Loop:** Instead of using `for...of`, a traditional `for` loop can also be employed, which can result in comparable performance. 
- **While Loop:** An alternate control structure that could be considered for more complex iterations.
- **Map-Filter-Reduce:** Depending on needs, chaining methods like `map` followed by `filter` can produce powerful results, but often at a performance tradeoff.

### Conclusion
Understanding the implications of using `Array.prototype.filter` versus a `for...of` loop is essential for optimizing JavaScript applications. The performance differences can be critical based on the dataset size and context in which the code is executed. Ultimately, the choice should balance performance needs with code readability and maintainability.

Latest run results:

Run details: (Test run date: 9 days ago)

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36

Browser/OS: Chrome 130 on Linux

View result in a separate tab

Test name	Executions per second
Filter	72989.7 Ops/sec
for of	66474.1 Ops/sec

Related benchmarks:

Filter vs for (version: 1)

Comparing performance of: Filter vs for of

Created: 9 days ago by: Registered User

Jump to the latest result

Filter

for of

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated 9 days ago):