Benchmark: marktyTOML Vs toml-node (classic_config)

HTML Preparation code:

<script type="text/javascript" src="https://unpkg.com/markty-toml@0.1.0/dist/marktytoml.umd.js"></script>
<script type="text/javascript" src="https://binarymuse.github.io/toml-node/js/toml.js"></script>

Script Preparation code:

var data = 'key = "value"\n\n[owner]\nname = "Tom Preston-Werner"\norganization = "GitHub"\nbio = "GitHub Cofounder & CEO Likes tater tots and beer"\n\n[database]\nserver = "192.168.1.1"\nports = [ 8001, 8001, 8003 ]\nconnection_max = 5000\nconnection_min = -2\nmax_temp = 87.1\nmin_temp = -17.76\nenabled = true\n\n[servers]\n\n\n  [servers.alpha]\n  ip = "10.0.0.1"\n  dc = "eqdc10"\n  [servers.beta]\n  ip = "10.0.0.2"\n  dc = "eqdc10"'

Tests:

marktyTOML
marktytoml(data)
toml-node
toml.parse(data)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
marktyTOML
toml-node

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 5 years ago)

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Ubuntu Chromium/71.0.3578.98 Chrome/71.0.3578.98 Safari/537.36

Browser/OS: Chromium 71 on Ubuntu

View result in a separate tab

Test name	Executions per second
marktyTOML	19358.8 Ops/sec
toml-node	395.5 Ops/sec

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

LLMs can make mistakes. Check important info.

**Benchmark Overview**

The provided benchmark is designed to compare the performance of two libraries: `markty-toml` and `toml-node`. The benchmark uses a JSON data string that represents a TOML (Tom's Obvious, Minimal Language) configuration file. The goal is to measure which library can parse this data faster.

**Options Being Compared**

The two options being compared are:

1. **markty-toml**: A JavaScript library for parsing TOML files.
2. **toml-node**: A lightweight, fast, and pure Node.js implementation of the TOML parser.

**Pros and Cons of Each Approach**

* **markty-toml**:
	+ Pros: Easy to use, well-documented, and has a simple syntax.
	+ Cons: May not be as fast as other parsers due to its JavaScript nature and potential overhead.
* **toml-node**:
	+ Pros: Fast, lightweight, and optimized for Node.js environments.
	+ Cons: Requires additional setup and may have a steeper learning curve.

**Library Descriptions**

1. **markty-toml**: A JavaScript library that provides a simple and intuitive API for parsing TOML files. It's designed to be easy to use and has a small footprint.
2. **toml-node**: A pure Node.js implementation of the TOML parser, optimized for performance and minimal dependencies.

**Special JS Features**

This benchmark does not utilize any special JavaScript features or syntax beyond standard ES6+ functionality.

**Other Considerations**

When choosing between these two libraries, consider the trade-off between ease of use and performance. If you prioritize simplicity and ease of use, `markty-toml` might be a better fit. However, if you require fast parsing performance in a Node.js environment, `toml-node` is likely a better choice.

**Alternative Options**

If neither of these libraries meets your requirements, consider the following alternatives:

1. **toml-java**: A Java implementation of the TOML parser that can be used in Node.js environments via a polyfill.
2. **toml-python**: A Python implementation of the TOML parser that can be used in JavaScript environments via a transpiler or runtime environment like V8.
3. **Custom Implementation**: You can also consider implementing your own TOML parser from scratch, which would give you complete control over performance and syntax.

Keep in mind that each alternative has its pros and cons, and the choice ultimately depends on your specific use case and requirements.

Related benchmarks:

marktyTOML Vs toml-node (classic_config) (version: 0)

Comparing performance of: marktyTOML vs toml-node

Created: 5 years ago by: Guest

Jump to the latest result

marktyTOML

toml-node

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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