Benchmark: Float string optimization: parseFloat() vs regex, full version

Tests:

parseFloat()
var string = parseFloat((3/2).toFixed(4)).toString();
regex
var string = (3/2).toFixed(4).replace('^[+-]?([0-9]*[.])?[0-9]+$', '');

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
parseFloat()
regex

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/128.0.0.0 Safari/537.36

Browser/OS: Chrome 128 on Windows

View result in a separate tab

Test name	Executions per second
parseFloat()	1703416.9 Ops/sec
regex	3463378.8 Ops/sec

Autogenerated LLM Summary (model llama3.1:latest, generated one year ago):

LLMs can make mistakes. Check important info.

Let's break down the provided JSON and benchmark results.

**Benchmark Definition**

The benchmark is called "Float string optimization: parseFloat() vs regex, full version". This means we're comparing two different approaches to optimize float number formatting: using `parseFloat()` and using regular expressions (regex).

**Test Cases**

We have two individual test cases:

1. **`parseFloat()`**: In this case, the JavaScript code uses `parseFloat()` to convert a string representation of a float number (`(3/2).toFixed(4)` generates a string like "0.7500") to a numeric value using `parseFloat()`. The result is then converted back to a string with `.toString()`.
2. **`regex`**: In this case, the code uses a regular expression (regex) to remove unwanted characters from the string representation of a float number (`(3/2).toFixed(4)` generates a string like "0.7500"). The regex pattern `^[+-]?([0-9]*[.])?[0-9]+$` matches and removes any leading or trailing whitespace, as well as any decimal part (leaving only the integer part).

**Library: Regular Expressions (regex)**

Regular expressions are a powerful tool in JavaScript for matching patterns in strings. In this case, we're using a regex pattern to remove unwanted characters from the string representation of a float number.

The regex pattern `^[+-]?([0-9]*[.])?[0-9]+$` is a bit complex, but here's what it does:

* `^`: Matches the start of the string.
* `[+-]?`: Matches an optional leading "+" or "-" sign (optional because it's preceded by `?`).
* `([0-9]*[.])?`: Matches an optional decimal part (either a single "." followed by optional digits, or nothing).
* `[0-9]+`: Matches one or more digits.
* `$`: Matches the end of the string.

**Pros/Cons and Considerations**

The two approaches have different pros and cons:

* **`parseFloat()`**: This approach is simple and easy to understand. However, it may not be as efficient as using regex because `parseFloat()` needs to create a new numeric value and then convert it back to a string.
	+ Pros: Simple, easy to understand.
	+ Cons: May be slower than regex.
* **`regex`**: This approach is more efficient because it only involves modifying the original string without creating new values. However, regex patterns can be complex and harder to understand.
	+ Pros: More efficient, no need to create new numeric values.
	+ Cons: Complex regex pattern may be hard to understand.

**Other Alternatives**

There are other alternatives to consider:

* **String manipulation**: You could simply remove unwanted characters from the string representation of a float number using string methods like `replace()` or slicing (`str.slice(0, -1)` to remove trailing decimal points).
	+ Pros: Simple, easy to understand.
	+ Cons: May not be as efficient as regex.

Overall, the benchmark results show that the regex approach is faster than using `parseFloat()`. However, this may depend on specific use cases and JavaScript engines.

Related benchmarks:

Float string optimization: parseFloat() vs regex, full version (version: 0)

To get a cleaned-up float number with a limited number of digits of precision, which is faster: parsefloat() or a regular expression?

Comparing performance of: parseFloat() vs regex

Created: 5 years ago by: Guest

Jump to the latest result

parseFloat()

regex

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.1:latest, generated one year ago):