Benchmark: requests2 - MeasureThat.net

Script Preparation code:

function getUser(userId) {		
	return fetch(`https://api.tvmaze.com/people/${userId}`)	
	.then((res) => res.json())	
    .then(data => console.log(data))
}

Tests:

1
getUser(1) getUser(2)
2
Promise.all([getUser(10), getUser(11)])
3
const arr = [getUser(10), getUser(11)] Promise.all(arr)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
1
2
3

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 break down the provided benchmark and explain what's being tested.

**Benchmark Definition**

The benchmark is defined by a JSON object that contains information about the test case, including:

* `Script Preparation Code`: This code snippet defines a function named `getUser` that makes an API request to fetch data from `https://api.tvmaze.com/people/{userId}`. The function returns the fetched data as JSON.
* `Html Preparation Code`: This field is empty in this benchmark definition.

**Individual Test Cases**

There are three test cases defined, each with a unique name and a "Benchmark Definition" that specifies how to run the `getUser` function:

1. **Test Case 1**: `getUser(1)` is called twice.
2. **Test Case 2**: A promise chain is created using `Promise.all([getUser(10), getUser(11)])`. This tests the performance of fetching two API requests concurrently.
3. **Test Case 3**: An array containing two calls to `getUser` is created and passed to `Promise.all()`, which tests the performance of fetching multiple API requests concurrently.

**Comparison of Options**

The benchmark uses different approaches to test the performance of these test cases:

* **Sequential Execution**: Test Cases 1 and 3 use sequential execution, where each call is executed one after the other. This approach tests the overhead of function calls, but it may not accurately reflect real-world scenarios.
* **Concurrent Execution**: Test Case 2 uses concurrent execution, where multiple API requests are sent simultaneously. This approach tests the performance benefits of fetching data in parallel.

**Pros and Cons**

The pros and cons of each approach are:

* **Sequential Execution**:
	+ Pros: Easy to understand, allows for precise control over test conditions.
	+ Cons: May not accurately reflect real-world scenarios where concurrency is common.
* **Concurrent Execution**:
	+ Pros: Simulates real-world scenarios where data is often fetched concurrently.
	+ Cons: Requires careful consideration of potential errors and edge cases.

**Library Usage**

The `fetch` API is used in the `getUser` function to make an HTTP request. The `fetch` API is a modern JavaScript library that provides an easy-to-use way to perform HTTP requests.

**Special JS Feature/Syntax**

There are no special JavaScript features or syntax used in this benchmark, except for the use of `Promise.all()` and array methods like `map()`. These features are widely supported by most modern browsers and JavaScript engines.

**Alternatives**

Other alternatives for testing performance include:

* **Using a different benchmarking library**: Some popular benchmarking libraries include [Benchmark.js](https://benchmarkjs.com/) or [Koa-benchmarks](https://github.com/koajs/benchmarks).
* **Using a different programming paradigm**: Instead of using JavaScript, the test could be written in another language like C++ or Java.
* **Using a cloud-based benchmarking service**: Some services, like [Google Benchmark](https://google.github.io/benchmark/) or [Benchmark.NET](https://benchmarkdotnet.org/), provide pre-built benchmarks and tools for comparing performance.

Related benchmarks:

requests2 (version: 0)

Comparing performance of: 1 vs 2 vs 3

Created: 3 years ago by: Guest

Jump to the latest result

1

2

3

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):