Benchmark: Array loop vs foreach vs map -forky

Script Preparation code:

   var arr = [];
    for (var i = 0; i < 100000; i++) {
      arr[i] = i;
    }
  
    function someFn(i) {
      return i * 3 * 8;
    }

Tests:

foreach
arr.forEach(function (item){ someFn(item); })
for
for (var i = 0, len = arr.length; i < len; i++) { someFn(arr[i]); }
map
arr.map(item => someFn(item))

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
foreach
for
map

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

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

LLMs can make mistakes. Check important info.

**Overview of the Benchmark**

The provided JSON represents a JavaScript microbenchmark that compares the performance of three different approaches for iterating over an array: `forEach`, `for`, and `map`. The benchmark is designed to test which approach is the fastest.

**Options Compared**

The benchmark compares the following three options:

1. **`arr.forEach(function (item){someFn(item);})`**: This option uses the `forEach` method of the Array prototype, which executes a callback function for each element in the array.
2. **`for (var i = 0, len = arr.length; i < len; i++) {someFn(arr[i]);}`** : This option uses a traditional `for` loop to iterate over the array elements.
3. **`arr.map(item => someFn(item))`**: This option uses the `map` method of the Array prototype, which creates a new array with the results of applying a function to each element in the original array.

**Pros and Cons**

Here are the pros and cons of each approach:

1. **`forEach`**:
	* Pros: Easy to read and write, no need to worry about indexing.
	* Cons: Can be slower than traditional loops or `map`, especially for large arrays.
2. **`for`**:
	* Pros: Generally the fastest option, provides direct access to array elements without using a callback function.
	* Cons: Requires manual indexing, can be harder to read and write for complex logic.
3. **`map`**:
	* Pros: Creates a new array with the results, allows for easy transformation of data.
	* Cons: Can be slower than traditional loops or `forEach`, creates an extra memory allocation.

**Library and Special JS Features**

The benchmark uses the following libraries:

1. **`someFn`**: A simple function that takes an integer as input and returns its multiplied by 3 and 8.
2. **`map`**: The Array.prototype `map` method is used to create a new array with the results of applying `someFn` to each element.

There are no special JS features used in this benchmark, other than the use of arrow functions (`=>`) in the `map` option.

**Other Considerations**

When writing benchmarks like this one, it's essential to consider the following:

1. **Micro-optimizations**: Small changes can significantly impact performance, so ensure that any optimizations are accurate and relevant.
2. **Edge cases**: Be aware of edge cases that may affect performance, such as array lengths or element types.
3. **Browser and device differences**: Consider how different browsers and devices might perform under the same benchmarking conditions.

**Alternatives**

If you're interested in exploring other alternatives for iterating over arrays in JavaScript, consider:

1. **`reduce`**: Another method on the Array prototype that can be used to iterate over an array.
2. **`every`, `some`, or `filter`**: Methods that can be used with callback functions to perform operations on individual elements.
3. **Custom loops**: Implementing custom loops using techniques like `while` or `do-while` statements.

Keep in mind that these alternatives may have different performance characteristics and trade-offs compared to the options tested in this benchmark.

Related benchmarks:

Array loop vs foreach vs map -forky (version: 0)

Comparing performance of: foreach vs for vs map

Created: 4 years ago by: Guest

Jump to the latest result

foreach

for

map

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):