Benchmark: reduce with object spread vs foreach with adding vs reduce without spread

Tests:

Using reduce and the spread operator
const styles = { foo: { color: 'red', }, bar: { color: 'green', '&:focus': { color: 'blue', }, }, foo2: { color: 'red', }, bar2: { color: 'green', '&:focus': { color: 'blue', }, }, foo3: { color: 'red', }, bar3: { color: 'green', '&:focus': { color: 'blue', }, }, foo4: { color: 'red', }, bar4: { color: 'green', '&:focus': { color: 'blue', }, }, }; Object .keys(styles) .reduce((classes, selector) => ({ ...classes, [selector]: selector, }), {});
Using map and adding to an object
const styles = { foo: { color: 'red', }, bar: { color: 'green', '&:focus': { color: 'blue', }, }, foo2: { color: 'red', }, bar2: { color: 'green', '&:focus': { color: 'blue', }, }, foo3: { color: 'red', }, bar3: { color: 'green', '&:focus': { color: 'blue', }, }, foo4: { color: 'red', }, bar4: { color: 'green', '&:focus': { color: 'blue', }, }, }; const obj = {}; Object .keys(styles) .forEach(style => { obj[style] = style; })
Using reduce without spread operator
const styles = { foo: { color: 'red', }, bar: { color: 'green', '&:focus': { color: 'blue', }, }, foo2: { color: 'red', }, bar2: { color: 'green', '&:focus': { color: 'blue', }, }, foo3: { color: 'red', }, bar3: { color: 'green', '&:focus': { color: 'blue', }, }, foo4: { color: 'red', }, bar4: { color: 'green', '&:focus': { color: 'blue', }, }, }; Object .keys(styles) .reduce((classes, selector) => { classes[selector] = selector; return classes; }, {});

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Using reduce and the spread operator
Using map and adding to an object
Using reduce without spread operator

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 28 days ago):

LLMs can make mistakes. Check important info.

I'll provide an in-depth explanation of the benchmark.

**Benchmark Overview**

The benchmark compares three approaches for iterating over object keys: using `reduce` with the spread operator, using `forEach` with adding to an object, and using `reduce` without the spread operator. The test case is designed to measure the performance difference between these approaches on a specific JavaScript object structure.

**Options Compared**

1. **Using `reduce` with the spread operator (`Object.keys().reduce()` + `{ ...classes }`)**
	* Pros:
		+ Efficiently creates a new object by spreading the existing object's properties.
		+ Allows for concise and expressive code.
	* Cons:
		+ May incur additional overhead due to the spread operation.
2. **Using `forEach` with adding to an object (`Object.keys().forEach()` + `{ obj[style] = style }`)**
	* Pros:
		+ Simpler and more intuitive syntax.
		+ Avoids potential performance impact of the spread operator.
	* Cons:
		+ Requires explicit looping, which can be less readable in some cases.
3. **Using `reduce` without the spread operator (`Object.keys().reduce()` + `{ classes[selector] = selector }`)**
	* Pros:
		+ Simplifies code by avoiding the need for the spread operator.
	* Cons:
		+ May result in a slower performance due to the unnecessary property assignments.

**Library and Special Features**

None of the options explicitly use any external libraries. However, it's worth noting that `Object.keys()` is a built-in method in modern JavaScript.

**Test Case Considerations**

The test case uses an object with multiple properties (e.g., `foo`, `bar`, `foo2`, etc.) to ensure that the iteration and property assignment are repeated multiple times. This helps mitigate any potential caching or optimization effects that might occur during benchmarking.

**Other Alternatives**

For similar scenarios, alternative approaches could include:

1. Using `for...in` loops instead of `forEach`.
2. Utilizing array methods like `map()` or `filter()`.
3. Leveraging functional programming techniques with `reduce()` and arrow functions.
4. Employing lazy evaluation or memoization to optimize the iteration process.

However, these alternatives may not directly address the specific performance trade-offs between `reduce` with the spread operator, `forEach` with adding to an object, and `reduce` without the spread operator.

**Benchmark Result Interpretation**

The latest benchmark results show that:

1. **Using `reduce` with the spread operator** yields the highest number of executions per second (391026).
2. **Using `forEach` with adding to an object** comes in second with approximately 1568087 executions per second.
3. **Using `reduce` without the spread operator** is the slowest, with around 390026 executions per second.

These results suggest that using `reduce` with the spread operator is likely the most efficient approach in this scenario. However, the actual performance difference may vary depending on specific use cases and optimization strategies.

Latest run results:

Run details: (Test run date: 5 years ago)

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/71.0.3578.80 Safari/537.36

Browser/OS: Chrome 71 on Linux

View result in a separate tab

Test name	Executions per second
Using reduce and the spread operator	390026.8 Ops/sec
Using map and adding to an object	1568087.5 Ops/sec
Using reduce without spread operator	1644045.4 Ops/sec

Related benchmarks:

reduce with object spread vs foreach with adding vs reduce without spread (version: 0)

Comparing performance of: Using reduce and the spread operator vs Using map and adding to an object vs Using reduce without spread operator

Created: 5 years ago by: Guest

Jump to the latest result

Using reduce and the spread operator

Using map and adding to an object

Using reduce without spread operator

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 28 days ago):