Benchmark: String split date vs parse date 2

Script Preparation code:

var dateStrings = Array(10000).fill(null).map(() => (new Date()).toISOString());
var padDate = date => (date < 10 ? `0${date}` : date);

Tests:

Parse Date
dateStrings.map((d) => { const date = new Date(d); return `${padDate(date.getDate())}.${padDate(date.getMonth() + 1)}.${padDate(date.getYear())}`; });
String split
dateStrings.map((d) => { const [date, time] = d.split('T') const [year, month, day] = date.split('-'); return `${day}.${month}.${year}`; });

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Parse Date
String split

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 27 days ago):

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks!

**What is being tested?**

The provided benchmark is designed to compare the performance of two approaches for processing date strings:

1. **String Split**: This approach splits the date string into its constituent parts (year, month, and day) using the `T` separator in ISO 8601 format.
2. **Date Parsing**: This approach converts the date string from a string representation to a Date object using JavaScript's built-in Date parsing functionality.

**Comparison of options**

There are two main approaches being compared:

* **String Split**: This approach is faster because it avoids the overhead of converting a string to a Date object and then extracting the individual parts. However, it requires splitting the date string into its constituent parts, which can be less readable and less efficient than using the built-in Date parsing functionality.
* **Date Parsing**: This approach is more readable and easier to maintain because it uses JavaScript's built-in Date parsing functionality, which is well-tested and optimized. However, it may be slower due to the overhead of converting a string to a Date object.

**Pros and Cons**

Here are some pros and cons of each approach:

* **String Split**:
	+ Pros: Faster execution time
	+ Cons: Less readable, requires splitting date string into individual parts
* **Date Parsing**:
	+ Pros: More readable, easier to maintain
	+ Cons: Slower execution time due to conversion overhead

**Library and purpose**

The `padDate` function is a custom utility function that pads the day, month, and year values with leading zeros if necessary. This is used in both benchmark definitions to ensure consistent output.

**Special JS feature or syntax**

There is no special JavaScript feature or syntax being used in this benchmark.

**Alternatives**

If you're looking for alternative approaches, here are a few options:

* **Use a dedicated date parsing library**: There are libraries like Moment.js that provide efficient and readable date parsing functionality.
* **Use a regex pattern**: You can use a regular expression to extract the individual parts of the date string. However, this approach may be less readable and more error-prone than using JavaScript's built-in Date parsing functionality.

Overall, the choice of approach depends on your specific requirements and priorities. If you need high performance and are willing to sacrifice readability, the String Split approach may be suitable. Otherwise, the Date Parsing approach may provide better performance and maintainability.

Latest run results:

Run details: (Test run date: 3 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/89.0.4389.90 Safari/537.36

Browser/OS: Chrome 89 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Parse Date	85.4 Ops/sec
String split	127.1 Ops/sec

Related benchmarks:

String split date vs parse date 2 (version: 0)

Comparing performance of: Parse Date vs String split

Created: 3 years ago by: Guest

Jump to the latest result

Parse Date

String split

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 27 days ago):