Benchmark: qwertyuiop - MeasureThat.net

Tests:

Number
var number = Number("a"+Math.random().toString());
Unary +
var unary = +("a"+Math.random().toString());
parseFloat
var parse = parseFloat("a"+Math.random().toString());

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Number
Unary +
parseFloat

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/114.0.0.0 Safari/537.36

Browser/OS: Chrome 114 on Windows

View result in a separate tab

Test name	Executions per second
Number	2365879.0 Ops/sec
Unary +	3169824.8 Ops/sec
parseFloat	1646132.4 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks on MeasureThat.net.

**Benchmark Definition**

The provided benchmark definition is a simple JSON object that defines a script and its purpose. In this case, there are no custom libraries or special JavaScript features used in the script preparation code. The `Script Preparation Code` and `Html Preparation Code` fields are both empty, which means that MeasureThat.net will not perform any additional setup or execution of HTML code before running the benchmark.

**Individual Test Cases**

There are three test cases defined:

1. **Number**: This test case creates a variable `number` using the `Number()` function and assigns it a value generated by concatenating a string with a random number.
2. **Unary +**: This test case uses the unary plus operator (`+`) to convert a string to a number. The string is created by concatenating "a" with a random number, similar to the Number() test case.
3. **parseFloat**: This test case creates a variable `parse` using the `parseFloat()` function and assigns it a value generated by concatenating a string with a random number.

**Options Compared**

MeasureThat.net compares different approaches for performing arithmetic operations on strings:

1. **Number() vs. Unary +**: These two options convert a string to a number. The main difference is that `Number()` performs implicit type conversion, while the unary plus operator (`+`) performs explicit type coercion.
2. **parseFloat vs. Number() and Unary +**: These three options parse a string as a floating-point number. The order of evaluation matters here: first, the string is converted to a number using one of the two methods mentioned above; then, that result is passed to `parseFloat()`.

**Pros and Cons**

Here are some pros and cons of each approach:

* **Number() vs. Unary +**:
	+ Pros: More readable code (e.g., `var number = Number("a" + Math.random().toString());`), less error-prone.
	+ Cons: May have performance overhead due to implicit type conversion.
* **parseFloat vs. Number() and Unary +**:
	+ Pros: More accurate results, as it handles NaN values correctly.
	+ Cons: Requires careful handling of the converted value to avoid errors.

**Other Considerations**

When choosing between these options, consider the following factors:

* Performance: If you're optimizing for speed, using the unary plus operator (`+`) might be a better choice.
* Code readability and maintainability: Using `Number()` or explicit type coercion with the unary plus operator can lead to more readable code.
* Error handling: When working with strings as input, it's essential to handle potential errors and edge cases.

**Library Usage**

None of the provided benchmark definitions use any external libraries. However, MeasureThat.net might use internal libraries for its own purposes, such as parsing or executing JavaScript code.

If you have any specific questions about these options or want further clarification on any aspect, feel free to ask!

Related benchmarks:

qwertyuiop (version: 0)

qwertyuiop

Comparing performance of: Number vs Unary + vs parseFloat

Created: one year ago by: Guest

Jump to the latest result

Number

Unary +

parseFloat

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):