A fast, single-file PHP Markdown parser with GitHub Flavored Markdown support and no dependencies.
Parsedown is a PHP Markdown parser that converts Markdown-formatted text to HTML. It solves the problem of needing a fast, reliable way to render user-generated content or documentation written in Markdown within PHP applications. The library focuses on performance and simplicity while supporting GitHub Flavored Markdown syntax.
PHP developers building content management systems, documentation tools, blogs, forums, or any application that needs to render user-generated Markdown content. It's particularly useful for projects that prioritize performance and minimal dependencies.
Developers choose Parsedown because it offers exceptional parsing speed in a single-file package with no external dependencies. Its unique line-based parsing approach provides both performance benefits and human-readable code, while the safe mode feature makes it suitable for processing untrusted user input.
Better Markdown Parser in PHP
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The entire library is contained in one PHP file, making integration effortless without managing multiple dependencies or complex setup.
Works standalone without requiring external PHP packages, reducing bloat and minimizing compatibility issues across environments.
Uses a unique line-based algorithm optimized for speed, with benchmarks showing it significantly outperforms many other PHP Markdown parsers.
Includes safe mode for escaping untrusted user input and HTML escaping options, crucial for preventing XSS in applications like forums or CMS.
The README admits it doesn't pass all CommonMark tests, which could lead to subtle rendering differences in edge cases compared to specification-driven parsers.
Safe mode may not protect against XSS when using third-party extensions, requiring additional security audits and potentially compromising safety for custom functionality.
Tied exclusively to PHP, so it's unsuitable for projects using other server-side languages, forcing developers to seek alternatives in multi-language ecosystems.