Benchmark: memoize-one vs fast-memoize not-repeating--previous

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/npm/memoize-one@5.2.1/dist/memoize-one.cjs.min.js"></script>
<script src="https://cdn.jsdelivr.net/npm/fast-memoize@2.5.2/src/index.min.js"></script>

Script Preparation code:

var getData = async function(query) {
  await new Promise(r => setTimeout(r, 100));
  return query; 
}

var repeat = function(limit, callback) {
  for(var i = 0; i < limit; i++) {
    callback();
  }
}

var memoizeOneFn = memoizeOne(getData);
var fastMemoizeFn = memoize(getData);

Tests:

memoizeOne
repeat(100, () => { memoizeOneFn('hello'); memoizeOneFn('world'); });
fastMemoize
repeat(100, () => { fastMemoizeFn('hello'); fastMemoizeFn('world'); });

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
memoizeOne
fastMemoize

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/124.0.0.0 Safari/537.36

Browser/OS: Chrome 124 on Windows

View result in a separate tab

Test name	Executions per second
memoizeOne	1771.2 Ops/sec
fastMemoize	8444.8 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.

**Overview**

The provided JSON represents a benchmark test on MeasureThat.net, which compares the performance of two memoization libraries: `memoize-one` and `fast-memoize`. The test is designed to measure the execution time of these libraries when called multiple times with different inputs.

**Benchmark Definition**

The benchmark definition consists of two parts:

1. **Script Preparation Code**: This code defines a few functions:
	* `getData`: an asynchronous function that returns a query string after a 100ms delay.
	* `repeat`: a function that calls another function `limit` times.
	* Two memoization functions: `memoizeOneFn` and `fastMemoizeFn`, which wrap the `getData` function with memoization using the `memoize-one` and `fast-memoize` libraries, respectively.
2. **Html Preparation Code**: This code includes links to the `memoize-one` and `fast-memoize` libraries.

**Options Compared**

The two memoization libraries being compared are:

1. **memoize-one**: a library that provides a simple way to memoize functions using a caching mechanism.
2. **fast-memoize**: a library that provides an optimized version of memoization, likely with some performance enhancements or trade-offs.

**Pros and Cons**

Here's a brief summary of the pros and cons of each approach:

1. **memoize-one**:
	* Pros: simple to use, easy to understand.
	* Cons: might have performance overhead due to caching mechanisms.
2. **fast-memoize**:
	* Pros: potentially optimized for better performance.
	* Cons: might be more complex to understand or use.

**Library Descriptions**

1. **memoize-one**: a lightweight JavaScript library that provides a simple way to memoize functions using a caching mechanism. Its purpose is to optimize function calls by storing the results of expensive computations so they can be reused instead of recalculated.
2. **fast-memoize**: a more advanced memoization library that likely uses various optimizations and techniques to improve performance. Its exact implementation details are not publicly available, but it's designed to provide better performance than traditional memoization libraries.

**Special JS Features/Syntax**

The benchmark test doesn't explicitly use any special JavaScript features or syntax, such as async/await, Promises, or ES6 modules. However, the `getData` function uses an asynchronous delay (`setTimeout`) and a Promise-like behavior, which might be relevant to some readers.

**Alternative Approaches**

If you're interested in exploring alternative memoization libraries or approaches, here are a few options:

1. **LRU Cache**: a popular JavaScript library that provides a Least Recently Used (LRU) caching mechanism.
2. **ObjectCache**: another caching library for JavaScript that uses a more advanced caching strategy.
3. **Memoize using WeakMap**: an approach that uses the `WeakMap` data structure to create a memoization cache, which can be more efficient than traditional caching mechanisms.

Keep in mind that these alternatives might have different performance characteristics, trade-offs, or use cases compared to `memoize-one` and `fast-memoize`.

Related benchmarks:

memoize-one vs fast-memoize not-repeating--previous (version: 3)

Comparing the performance of memoize-one to fast-memoize

Comparing performance of: memoizeOne vs fastMemoize

Created: 4 years ago by: Registered User

Jump to the latest result

memoizeOne

fastMemoize

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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