Benchmark: json stringify vs array map + join

Script Preparation code:

function moreData(arr, left) {
  if(left === 0) return arr;
  else {
    arr.push(Math.floor(Math.random() * 256));
  	return moreData(arr, left - 1);
  }
}
function makeTestData() { return moreData([], 4); }

Tests:

map + join
makeTestData().map(i => `${i}`).join('-')
JSON.stringify
JSON.stringify(makeTestData());

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
map + join
JSON.stringify

Fastest: N/A

Slowest: N/A

Latest run results:

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

LLMs can make mistakes. Check important info.

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

**Benchmark Definition JSON**

The provided JSON represents a benchmark definition, which is essentially a script that creates test data and defines how it should be used for the benchmark. In this case, we have two benchmark definitions:

1. `makeTestData()`: This function generates test data by recursively pushing random numbers to an array using the `moreData` function.
2. The second benchmark definition uses the result of `makeTestData()` as input and applies two operations: `map` and `join`. The `map` function applies a transformation to each element in the array, while the `join` method concatenates all elements into a single string separated by a hyphen.

**Options Compared**

The two benchmark definitions compare two different approaches to concatenate an array of numbers:

1. **`JSON.stringify()`**: This is a built-in JavaScript method that converts a value (in this case, an array) to a JSON string.
2. **`map` + `join`**: This approach uses the `map` function to transform each number in the array into a string and then concatenates these strings using the `join` method.

**Pros and Cons**

Here are some pros and cons of each approach:

**`JSON.stringify()`**

Pros:

* Fast: `JSON.stringify()` is generally faster than the `map` + `join` approach.
* Simple: This approach only requires one function call.

Cons:

* Unparsable: The resulting string is in JSON format, which might not be suitable for all use cases.
* Not human-readable: The output is not easily readable by humans.

**`map` + `join`**

Pros:

* Human-readable: The output is a string of numbers separated by hyphens, making it easy to read and understand.
* Flexible: You can customize the transformation function passed to `map`.

Cons:

* Slower: This approach involves two separate operations (`map` and `join`), which might be slower than calling `JSON.stringify()`.
* More complex: You need to handle the transformations and concatenation logic.

**Library Used**

There is no explicit library used in this benchmark definition. However, it's worth noting that if you were to use a library like Lodash or Ramda for functional programming, you might choose to use their `map` and `join` functions to achieve similar results.

**Special JS Feature/Syntax**

There are no special JavaScript features or syntaxes used in this benchmark definition. The code only uses standard JavaScript functions (`push`, `concat`) and data types (arrays, strings).

**Other Alternatives**

If you want to explore other alternatives for concatenating an array of numbers, here are a few options:

* Using a loop instead of `map` + `join`: This approach would be slower than the current benchmark but might be more readable.
* Using a library like `lodash` or `ramda` with their string-joining functions: These libraries provide efficient and flexible ways to concatenate arrays into strings.

Keep in mind that these alternatives might not change the overall performance of your application, but they can affect readability and maintainability.

Related benchmarks:

json stringify vs array map + join (version: 0)

Comparing performance of: map + join vs JSON.stringify

Created: 4 years ago by: Guest

Jump to the latest result

map + join

JSON.stringify

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

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