Benchmark: Two Arrays to Object #3

Script Preparation code:

keys = ["a","b","c","d"];
values = [1,2,3,4];

Tests:

forEach #1
const ob = {}; keys.forEach((key, i)=>ob[key]=values[i]);
fromEntries and map #1
const ob = Object.fromEntries( keys.map((key, i)=>[key, values[i]]) );
Object.assign and map #1
const ob = Object.assign( ...keys.map((k, i) => ({[k]: values[i]})) );
reduce #1
const ob = keys.reduce( (o, k, i) => ({...o, [k]: values[i]}), {} );
for
const ob = {}; for (let key=0; key<keys.length; key++) { ob[keys[key]] = values[key]; }
forEach #2
const ob = {}; const fn = (key, i)=>ob[key]=values[i]; keys.forEach(fn);
fromEntries and map #2
const fn = (key, i)=>[key, values[i]]; const ob = Object.fromEntries(keys.map(fn));
Object.assign and map #2
const fn = (k, i) => ({[k]: values[i]}); const ob = Object.assign( ...keys.map(fn) );
reduce #2
const fn = (o, k, i) => ({...o, [k]: values[i]}); const ob = keys.reduce(fn, {});

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
forEach #1
fromEntries and map #1
Object.assign and map #1
reduce #1
for
forEach #2
fromEntries and map #2
Object.assign and map #2
reduce #2

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

This benchmark does not have any results yet. Be the first one to run it!

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

LLMs can make mistakes. Check important info.

I'll break down the provided benchmark definition and test cases, explaining what's being tested, compared, and discussing their pros and cons.

**Benchmark Definition**

The provided JSON represents a JavaScript microbenchmark that tests various methods for creating an object from two arrays: one with keys and another with values. The test aims to determine which approach is the fastest.

**Options Compared**

Six different approaches are compared:

1. `forEach` loop
2. `fromEntries` method with `map`
3. `Object.assign` method with `map`
4. `reduce` method
5. `for` loop
6. Closure-based approach using `forEach`

**Pros and Cons of Each Approach**

1. **forEach**: The simplest approach, but potentially slow due to the function call overhead.
2. **fromEntries**: A built-in method that creates an object from key-value pairs, which is likely to be fast.
3. **Object.assign**: Another built-in method for creating objects, which might be slower than `fromEntries` due to the function call overhead.
4. **reduce**: A concise and efficient approach using a reducer function, which can be faster than other methods.
5. **for**: A basic loop that creates an object by iterating over the arrays, which is likely to be slow.
6. **Closure-based forEach**: An optimized approach using a closure to avoid the function call overhead of `forEach`, making it competitive with `reduce`.

**Libraries and Special Features**

None of the test cases use any external libraries or special JavaScript features (e.g., Promises, async/await).

**Other Alternatives**

If you're interested in exploring alternative approaches, here are some:

* Using `Array.prototype.reduce()` with a custom reducer function
* Utilizing `String.prototype.forEach()` instead of `Array.prototype.forEach()`
* Employing `Function.prototype.call()` to call the closure-based `forEach` implementation

Keep in mind that these alternatives might not be as optimized or efficient as the original test cases.

Now, if you'll excuse me, I need a deep breath...

Related benchmarks:

Two Arrays to Object #3 (version: 2)

Array with keys and Array with values into Object.

Comparing performance of: forEach #1 vs fromEntries and map #1 vs Object.assign and map #1 vs reduce #1 vs for vs forEach #2 vs fromEntries and map #2 vs Object.assign and map #2 vs reduce #2

Created: 6 years ago by: Registered User

Jump to the latest result

forEach #1

fromEntries and map #1

Object.assign and map #1

reduce #1

for

forEach #2

fromEntries and map #2

Object.assign and map #2

reduce #2

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):