Benchmark: FlatMap vs For-Loop

HTML Preparation code:

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Script Preparation code:

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async function globalMeasureThatScriptPrepareFunction() {
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Tests:

flatMap
const input = Array.from({ length: 1000 }, (_, i) => [i, i + 1]); const result = input.flatMap(pair => pair);
for loop
const input = Array.from({ length: 1000 }, (_, i) => [i, i + 1]); const result = []; for (let i = 0; i < input.length; i++) { result.push(input[i][0], input[i][1]); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
flatMap
for loop

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 8 months ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:145.0) Gecko/20100101 Firefox/145.0

Browser/OS: Firefox 145 on Windows

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for loop

59K/s

flatMap

56K/s

View exact numbers

Test name	Executions per second
✓ for loop	58,773 Ops/sec
flatMap	56,460 Ops/sec

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

LLMs can make mistakes. Check important info.

### Benchmark Overview: FlatMap vs For-Loop

The benchmark conducted compares the performance of two different methods for flattening arrays in JavaScript: using the `flatMap()` method versus a traditional `for` loop.

#### Options Compared

1. **FlatMap**
   ```javascript
   const input = Array.from({ length: 1000 }, (_, i) => [i, i + 1]);
   const result = input.flatMap(pair => pair);
   ```
   - **Description**: This method makes use of the `flatMap()` function, which simultaneously maps each element of an array and flattens the result into a new array. In this case, each subarray `pair` is transformed into its individual elements.

2. **For Loop**
   ```javascript
   const input = Array.from({ length: 1000 }, (_, i) => [i, i + 1]);
   const result = [];
   for (let i = 0; i < input.length; i++) {
     result.push(input[i][0], input[i][1]);
   }
   ```
   - **Description**: This traditional `for` loop iterates through the input array and explicitly pushes each element of the subarray (`pair`) into a new result array.

#### Pros and Cons

- **FlatMap Pros**:
  - **Conciseness**: The code is cleaner and more expressive, which can lead to better maintainability.
  - **Built-in function**: As a built-in method, it can be optimized by the JavaScript runtime.

- **FlatMap Cons**:
  - **Performance Overhead**: For certain operations and in specific contexts, the higher-level abstraction might introduce slight performance overhead, making it slower than a straightforward loop.

- **For Loop Pros**:
  - **Explicit Control**: Developers have fine-grained control over the iteration and can customize it as needed.
  - **Potential Speed**: In some cases, especially with large datasets or complex operations, traditional loops can be faster, as they have less overhead compared to methods that abstract away the operation.

- **For Loop Cons**:
  - **Verbosity**: More code means a higher chance for errors and less readability.
  - **Manual Error Handling**: Requires extra handling of edge cases (e.g., empty arrays) which might be implicitly managed by higher-order functions like `flatMap()`.

### Library and Features
In this benchmark, not any external libraries are used. The benchmark entirely relies on JavaScript's built-in capabilities, specifically the `flatMap()` method, which is part of the Array prototype.

### Conclusion and Alternatives
The provided benchmark indicates that the `for` loop executed approximately 29,521 operations per second, while `flatMap()` executed about 17,975 operations per second. Thus, in this specific test case, the `for` loop outperformed `flatMap()`.

**Alternatives to Consider**:
- **Reduce**: Another functional approach to flatten an array could be using the `reduce()` method, providing more flexibility at the cost of complexity.
- **Spread Operator**: Developers could also utilize the spread operator in conjunction with `map()`, although it may lead to additional memory overhead.
- **TypeScript**: Consider using TypeScript for additional type safety, especially when working with complex data structures.

This benchmark is valuable for developers choosing between readability and performance, adapting their strategies based on the specific context of the application.

FlatMap vs For-Loop (version: 1)

Comparing performance of: `flatMap vs for loop`

Created: 9 months ago by: Guest

Go to the latest result

flatMap

for loop

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

FlatMap vs For-Loop (version: 1)

Comparing performance of: flatMap vs for loop

Created: 9 months ago by: Guest

Go to the latest result

flatMap

for loop

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

Related benchmarks

Comparing performance of: `flatMap vs for loop`