Benchmark: json stringify vs object tostring number thresholds

Script Preparation code:

function makeTestDataNum() { return 0; }

function makeTestDataUndef() { return undefined; }

function makeTestDataArray() { return [0, 0.4, 0.6, 1]; }

Tests:

toString number
const d = makeTestDataNum() d ? d.toString() : "0"
JSON.stringify number
JSON.stringify(makeTestDataNum());
toString undefined
const d = makeTestDataUndef() d ? d.toString() : "0"
JSON.stringify undefined
JSON.stringify(makeTestDataUndef());
toString array
const d = makeTestDataArray() d ? d.toString() : "0"
JSON.stringify array
JSON.stringify(makeTestDataArray());

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
toString number
JSON.stringify number
toString undefined
JSON.stringify undefined
toString array
JSON.stringify array

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 29 days ago):

LLMs can make mistakes. Check important info.

Let's dive into the explanation of the provided benchmark.

**Benchmark Overview**

The MeasureThat.net website allows users to create and run JavaScript microbenchmarks, comparing different approaches to test various scenarios. The current benchmark is designed to measure the performance of `toString()` and `JSON.stringify()` methods when handling different types of data: numbers, undefined values, and arrays.

**Script Preparation Code**

The provided script preparation code defines three helper functions:

1. `makeTestDataNum()`: Returns a number (0).
2. `makeTestDataUndef()`: Returns an undefined value.
3. `makeTestDataArray()`: Returns an array `[0, 0.4, 0.6, 1]`.

These functions are used to generate test data for the benchmark.

**Individual Test Cases**

There are four test cases in total:

1. **`toString number`**: Tests the performance of `toString()` when called on a number (0).
2. **`JSON.stringify number`**: Tests the performance of `JSON.stringify()` when called on a number (0).
3. **`toString undefined`**: Tests the performance of `toString()` when called on an undefined value.
4. **`JSON.stringify undefined`**: Tests the performance of `JSON.stringify()` when called on an undefined value.
5. **`toString array`**: Tests the performance of `toString()` when called on an array.
6. **`JSON.stringify array`**: Tests the performance of `JSON.stringify()` when called on an array.

**Library Usage**

The benchmark uses two built-in JavaScript libraries:

1. `JSON`: Used for comparing the performance of `JSON.stringify()`.
2. No explicit library usage is required for the `toString()` method, as it's a native JavaScript function.

**Special JS Features or Syntax**

There are no special JavaScript features or syntax used in this benchmark that would require explanation.

**Options Compared**

The benchmark compares two options for each test case:

1. **`toString()`**: A native JavaScript function.
2. **`JSON.stringify()`**: A built-in JavaScript library function.

These two options are compared to measure their performance difference.

**Pros and Cons of Different Approaches**

Here's a brief summary of the pros and cons of using `toString()` versus `JSON.stringify()`:

**`toString()`**:

Pros:

* Lightweight: `toString()` is a lightweight function that doesn't require any additional library calls.
* Native execution: `toString()` is a native JavaScript function, meaning it's executed directly by the browser.

Cons:

* Inconsistent results: The output of `toString()` can vary depending on the data type and context.
* Limited control: `toString()` has limited control over the formatting of the output.

**`JSON.stringify()`**:

Pros:

* Consistent results: `JSON.stringify()` always produces a consistent, human-readable format for any data type.
* Control over formatting: `JSON.stringify()` provides more control over the formatting of the output, allowing for custom encoding and escaping options.

Cons:

* Heavier: `JSON.stringify()` is a heavier function that requires an additional library call.
* More CPU-intensive: `JSON.stringify()` can be more CPU-intensive than `toString()`, especially for large data sets.

**Other Considerations**

When deciding between `toString()` and `JSON.stringify()`, consider the following:

* Performance: If lightweight performance is critical, `toString()` might be a better choice. However, if you need to ensure consistent results and control over formatting, `JSON.stringify()` might be a better option.
* Readability: If readability is important, `JSON.stringify()` produces a more human-readable format for most data types.

**Alternative Approaches**

If you need to measure the performance of other functions or methods, consider alternatives such as:

1. **`Array.prototype.map()`**: Can be used to measure the performance of array processing and transformation.
2. **`Set()`**: Can be used to measure the performance of set operations and lookup.
3. **`Date.now()`**: Can be used to measure the performance of timing-related functions.

Keep in mind that these alternatives might require additional setup and testing to ensure accurate results.

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/128.0.0.0 Safari/537.36

Browser/OS: Chrome 128 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
toString number	26034676.0 Ops/sec
JSON.stringify number	8386008.0 Ops/sec
toString undefined	10100495.0 Ops/sec
JSON.stringify undefined	5602038.0 Ops/sec
toString array	5074846.5 Ops/sec
JSON.stringify array	5196670.5 Ops/sec

Related benchmarks:

json stringify vs object tostring number thresholds (version: 0)

Comparing performance of: toString number vs JSON.stringify number vs toString undefined vs JSON.stringify undefined vs toString array vs JSON.stringify array

Created: one year ago by: Registered User

Jump to the latest result

toString number

JSON.stringify number

toString undefined

JSON.stringify undefined

toString array

JSON.stringify array

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 29 days ago):