Benchmark: fight to the death - for loop vs chained arr (10)

Script Preparation code:

const randomStDate = () => {
    const randD = new Date(new Date("2021-12-05").getTime() + Math.random() * (new Date("2026-12-05").getTime() - new Date("2023-12-05").getTime()))
    let month = '' + (randD.getMonth() + 1);
    let day = '' + randD.getDate();
    let year = randD.getFullYear();
    if (month.length < 2) month = '0' + month;
    if (day.length < 2) day = '0' + day;
    return [year, month, day].join('-');

};

const rndId = Math.floor(Math.random() * (100000000 - 1 + 1) + 1)

const createArr = () => {
    let workArr = []
    for (let i = 0; i < 10; i++) {
        const pl = {
            tisId: rndId,
            startDate: randomStDate(),
            endDate: "2026-12-05",
            site: "Liverpool",
        }
        workArr.push(pl)

    }
    return workArr
}

var workArr = createArr()
var today = new Date().toISOString().slice(0, 10)

Tests:

for loop
let pastArr = []; let futureArr = []; for (let i = 0; i < workArr.length; i++) { const pl = workArr[i]; switch(true){ case pl.startDate <= today : pastArr.push(pl); break; case futureArr.length < 1 && pl.startDate > today : futureArr = [pl]; break; case futureArr.length > 0 && pl.startDate < futureArr[0].startDate : futureArr = [pl]; break; case futureArr.length > 0 && pl.startDate === futureArr[0].startDate : futureArr.push(pl); break; } } return [...pastArr, ...futureArr]
chained arr
const today = new Date().toISOString().slice(0,10) const firstFutureWorks = workArr .filter(w => w.startDate > today) .sort((a, b) => (a.startDate > b.startDate ? 1 : -1)); const nextFutureDate = firstFutureWorks[0] ? firstFutureWorks[0].startDate : today; return workArr.filter(w => w.startDate <= nextFutureDate);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
for loop
chained arr

Fastest: N/A

Slowest: N/A

Latest run results:

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

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Let's break down the benchmark and its test cases.

**Benchmark Definition**

The benchmark is defined by two test cases: "for loop" and "chained arr". The benchmark measures the performance of two approaches to filter an array of objects based on their `startDate` property.

**Test Cases**

1. **For Loop**
	* Test Name: for loop
	* Benchmark Definition: A simple for loop that iterates over the `workArr` array and pushes each object to either `pastArr` or `futureArr` based on its `startDate`.
	* Purpose: This test case measures the performance of a traditional for loop approach.
2. **Chained Arr**
	* Test Name: chained arr
	* Benchmark Definition: A more modern approach using the `filter()` and `sort()` methods to filter the `workArr` array.
	* Purpose: This test case measures the performance of a chained array approach.

**Options Compared**

The two test cases compare two different approaches:

1. **For Loop**: A traditional loop-based approach that iterates over the array using a for loop, checks each element's condition, and pushes it to either `pastArr` or `futureArr`.
2. **Chained Arr**: A modern, chained array approach that uses `filter()` and `sort()` methods to filter the array.

**Pros and Cons**

Here are some pros and cons of each approach:

1. **For Loop**
	* Pros:
		+ Easy to understand and implement for beginners.
		+ Can be optimized with early returns or caching.
	* Cons:
		+ Less efficient than chained array approaches due to the overhead of loop iteration.
2. **Chained Arr**
	* Pros:
		+ More concise and readable code.
		+ Often more efficient than traditional loops, especially for large datasets.
	* Cons:
		+ May have a higher memory footprint due to the creation of intermediate arrays.

**Library Used**

There is no explicit library mentioned in the benchmark definition. However, it appears that the `filter()` and `sort()` methods are used, which are native JavaScript methods.

**Special JS Feature or Syntax**

The benchmark uses the following special features:

1. **Arrow functions**: The `randomStDate` function and the callback functions in the `for loop` test case use arrow functions.
2. **Spread operator (`...`)**: The `return [...pastArr, ...futureArr]` statement in the `for loop` test case uses the spread operator to concatenate arrays.

**Other Alternatives**

If you're looking for alternative approaches or optimizations, consider the following:

1. **Using a more efficient sorting algorithm**: If you need to sort the array based on multiple conditions, consider using a more efficient algorithm like quicksort or mergesort.
2. **Caching intermediate results**: If you're filtering large datasets, caching intermediate results can help reduce performance overhead.
3. **Parallelizing the loop**: If you have a multi-core processor, parallelizing the loop can take advantage of multiple CPU cores to speed up execution.

Keep in mind that these alternatives will depend on your specific use case and requirements.

Related benchmarks:

fight to the death - for loop vs chained arr (10) (version: 0)

Comparing performance of: for loop vs chained arr

Created: 3 years ago by: Registered User

Jump to the latest result

for loop

chained arr

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):