Benchmark: JSON Stringify Speed Test 0

Tests:

1
const a = {"name":"koreq.publish.process_response","spanId":"7bd4aae996347e18","traceId":"4c1c06b603354025a6ef5f3ff4cfa0e8","startTimeUnixMilli":1715972358893,"attributes":{"flowName":"process_response","cc":["respond_to_user"],"pid":1744551},"kind":"producer","parentSpanId":"e9b12c2049994151","endTimeUnixMilli":1715972358898,"status":{"code":1},"isWritten":false,"eventName":"endSpan"}; JSON.strigify(a);
2
const a = {}; for (let i = 0; i < 100; i++) { a[i] = i; } JSON.stringify(a);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
1
2

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/126.0.0.0 Safari/537.36 Edg/126.0.0.0

Browser/OS: Chrome 126 on Windows

View result in a separate tab

Test name	Executions per second
1	0.0 Ops/sec
2	177284.1 Ops/sec

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!

**Benchmark Definition:**

The provided JSON defines a benchmark called "JSON Stringify Speed Test 0." This benchmark is designed to test whether the speed of `JSON.stringify()` changes with object size.

In essence, this benchmark is comparing two approaches:

1. **Serialized Object**: The first test case uses an object with a fixed structure and nested objects. It creates an object `a` with specific properties, including some numeric values and strings.
2. **Array Creation**: The second test case generates an array of 100 objects, where each object has a single property (`i`) assigned to it.

**Options Compared:**

The benchmark is comparing the execution speed of `JSON.stringify()` when applied to these two different data structures:

*   Serialized Object (Test Case 1)
*   Array Creation (Test Case 2)

**Pros and Cons:**

*   **Serialized Object:**
    *   Pros:
        *   This approach allows for a more controlled environment, making it easier to analyze the impact of object structure on JSON stringification performance.
        *   It can help identify issues related to nested objects or complex data structures.
    *   Cons:
        *   This approach might not accurately reflect real-world usage patterns, where objects are often created dynamically or have varying structures.
*   **Array Creation:**
    *   Pros:
        *   This approach simulates a common scenario in JavaScript development, where arrays are frequently used to store data.
        *   It can help identify performance issues related to large array sizes or complex data structures.
    *   Cons:
        *   This approach may not accurately capture the impact of object structure on JSON stringification performance.

**Library and Purpose:**

There is no specific library mentioned in the provided benchmark definition. However, it's worth noting that `JSON.stringify()` is a built-in JavaScript function that can be used to serialize objects into a JSON-compatible format.

**Special JS Features or Syntax:**

None are explicitly mentioned in the provided benchmark definition.

**Other Alternatives:**

If you're interested in exploring alternative approaches or modifying this benchmark, here are some ideas:

*   Test the impact of different `JSON.stringify()` options, such as the `replacer` function or `space` parameter.
*   Compare the performance of other serialization libraries or implementations, like `json-stringify-safe`.
*   Experiment with different object structures or data sizes to see how they affect JSON stringification performance.

Keep in mind that when modifying benchmarks, it's essential to ensure that any changes are relevant and accurately reflect the behavior you're trying to measure.

Related benchmarks:

JSON Stringify Speed Test 0 (version: 0)

This benchmark tests whether the speed or JSON.stringify changes with object size

Comparing performance of: 1 vs 2

Created: one year ago by: Guest

Jump to the latest result

1

2

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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