Benchmark: JSON Perf - MeasureThat.net

Tests:

JSON
JSON.parse("42.001")
parseInt
parseInt("42.001", 10)
parseFloat
parseFloat("42.001")

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
JSON
parseInt
parseFloat

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 5 days ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/134.0.0.0 Safari/537.36

Browser/OS: Chrome 134 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
JSON	32270174.0 Ops/sec
parseInt	231998096.0 Ops/sec
parseFloat	55567128.0 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):

LLMs can make mistakes. Check important info.

Let's break down the benchmark test cases and explain what's being tested.

**Benchmark Test Cases**

The provided JSON represents three individual test cases:

1. `JSON.parse("42.001")`: This test case is testing the performance of the `JSON.parse()` function, which is used to parse a JSON string into a JavaScript object.
2. `parseInt("42.001", 10)`: This test case is testing the performance of the `parseInt()` function, which is used to convert a string to an integer value. The second argument (base 10 in this case) specifies the radix (number system) of the input string.
3. `parseFloat("42.001")`: This test case is testing the performance of the `parseFloat()` function, which is similar to `parseInt()`, but converts a string to a floating-point number instead.

**Comparison of Options**

The three functions being tested are part of the standard JavaScript API:

* `JSON.parse()` is used for parsing JSON strings into JavaScript objects.
* `parseInt()` is used for converting strings to integers.
* `parseFloat()` is used for converting strings to floating-point numbers.

Each function has its own pros and cons:

* `JSON.parse()`:
	+ Pros: It's specifically designed for parsing JSON strings, which can be beneficial for security reasons (e.g., preventing XSS attacks).
	+ Cons: It may introduce additional overhead due to the complexity of JSON parsing.
* `parseInt()`: 
	+ Pros: It's a simple and efficient way to convert strings to integers.
	+ Cons: It may not work correctly with non-numeric input strings, which can lead to incorrect results.
* `parseFloat()`:
	+ Pros: It's similar to `parseInt()` but provides more flexibility by allowing for decimal values.
	+ Cons: It also has limitations when dealing with non-numeric input strings.

**Library Usage**

There is no explicit library usage mentioned in the provided JSON. However, it's worth noting that these functions are part of the standard JavaScript API and don't require any external libraries to be used.

**Special JS Features or Syntax**

None of the benchmark test cases explicitly use special JavaScript features or syntax (e.g., async/await, Promises, etc.). If there were any specific features being tested, they might have been mentioned in the `Benchmark Definition` section or in additional context not provided here.

**Other Alternatives**

If you needed to benchmark similar functions or alternatives, some examples could include:

* Using a different library or implementation of JSON parsing (e.g., `json5`, `json3`) versus the standard JavaScript `JSON.parse()` function.
* Benchmarking alternative methods for converting strings to integers or floating-point numbers, such as using `Number()` instead of `parseInt()` or `parseFloat()`.
* Comparing performance of different algorithms or data structures for parsing or processing JSON strings.

However, for these specific test cases (`JSON.parse()`, `parseInt()`, and `parseFloat()`), the standard JavaScript API is already being used.

Related benchmarks:

JSON Perf (version: 0)

Comparing performance of: JSON vs parseInt vs parseFloat

Created: 2 years ago by: Guest

Jump to the latest result

JSON

parseInt

parseFloat

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):