Benchmark: regex replace with and without for (long text)

Script Preparation code:

var sentence = "Lorem Ipsum is simply dummy text of the printing and typesetting industry.";
var wordList = sentence.split(' ');

var longText = "Lorem Ipsum is simply dummy text of the printing and typesetting industry."

for (let i = 0; i < 10; i += 1) {
  longText = longText + " " + longText
}

Tests:

replace with for
for (let i = 0; i < wordList.length; i += 1) { var re = new RegExp("(" + wordList[i] + ")", "gi"); longText = longText.replace( re, '<span>$1</span>' ); }
replace without for
var re = new RegExp("(" + wordList.join('|') + ")", "gi"); longText = longText.replace( re, '<span>$1</span>' );

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
replace with for
replace without for

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/110.0.0.0 Safari/537.36

Browser/OS: Chrome 110 on Linux

View result in a separate tab

Test name	Executions per second
replace with for	9.4 Ops/sec
replace without for	13.1 Ops/sec

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

LLMs can make mistakes. Check important info.

I'll break down the provided benchmark definitions and explain what's being tested, compared, and their pros and cons.

**Benchmark Definitions**

The test cases are designed to measure the performance of two approaches for replacing words in a long text using regular expressions:

1. **Replacing with a `for` loop**: This approach uses a `for` loop to create a regular expression pattern for each word in the list.
2. **Replacing without a `for` loop**: This approach creates a single regular expression pattern using the `join()` method, which concatenates all words in the list into a single string.

**Options Compared**

The two approaches differ in their implementation:

1. **Replacing with a `for` loop**:
	* Pros:
		+ More explicit and readable code.
		+ Can be modified or extended more easily.
	* Cons:
		+ May incur higher overhead due to the creation of multiple regular expression objects.
2. **Replacing without a `for` loop**:
	* Pros:
		+ More concise and efficient code.
		+ Reduces memory allocation and garbage collection overhead.
	* Cons:
		+ Less readable and maintainable code.
		+ May be less flexible or extensible.

**Library Used**

Neither of the test cases uses a specific JavaScript library. However, both examples use the `RegExp` constructor to create regular expression objects.

**Special JS Feature/Syntax**

There are no special JavaScript features or syntax used in these benchmarks. The focus is on comparing the performance of two approaches for replacing words in a text using regular expressions.

**Other Alternatives**

If you were to modify or extend these benchmarks, here are some alternative approaches you could consider:

1. **Using a library like Lodash**: Instead of creating regular expression patterns manually, you could use a library like Lodash to create and manipulate regex patterns.
2. **Using a caching mechanism**: If the text or word list remains relatively constant, you could implement a caching mechanism to store pre-compiled regular expression objects, reducing overhead on each execution.
3. **Using a parallel processing approach**: Instead of running both test cases sequentially, you could use parallel processing techniques (e.g., `worker_threads` in Node.js) to run both tests concurrently, potentially improving overall performance.

Keep in mind that the choice of alternative approach will depend on your specific requirements and constraints.

Related benchmarks:

regex replace with and without for (long text) (version: 1)

Comparing performance of: replace with for vs replace without for

Created: 2 years ago by: Registered User

Jump to the latest result

replace with for

replace without for

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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