| Crates.io | html-to-markdown-rs |
| lib.rs | html-to-markdown-rs |
| version | 2.23.4 |
| created_at | 2025-10-10 16:15:22.199082+00 |
| updated_at | 2026-01-20 18:37:12.584989+00 |
| description | High-performance HTML to Markdown converter using the astral-tl parser. Part of the Kreuzberg ecosystem. |
| homepage | https://github.com/kreuzberg-dev/html-to-markdown |
| repository | https://github.com/kreuzberg-dev/html-to-markdown |
| max_upload_size | |
| id | 1877146 |
| size | 1,180,979 |
High-performance HTML to Markdown converter built with Rust.
This crate is the core engine compiled into the Python wheels, Ruby gem, Node.js NAPI bindings, WebAssembly package, and CLI, ensuring identical Markdown output across every language.
Fast, reliable HTML to Markdown conversion with full CommonMark compliance. Built with html5ever for correctness and a DOM-based filter for safe preprocessing.
[dependencies]
html-to-markdown-rs = "2.3"
use html_to_markdown_rs::{convert, ConversionOptions};
fn main() -> Result<(), Box<dyn std::error::Error>> {
let html = r#"
<h1>Welcome</h1>
<p>This is <strong>fast</strong> conversion!</p>
<ul>
<li>Built with Rust</li>
<li>CommonMark compliant</li>
</ul>
"#;
let markdown = convert(html, None)?;
println!("{}", markdown);
Ok(())
}
Conversion returns a Result<String, ConversionError>. Inputs that look like binary data are rejected with
ConversionError::InvalidInput to prevent runaway allocations. Table colspan/rowspan values are also clamped
internally to keep output sizes bounded.
use html_to_markdown_rs::{
convert, ConversionOptions, HeadingStyle, ListIndentType,
PreprocessingOptions, PreprocessingPreset,
};
let options = ConversionOptions {
heading_style: HeadingStyle::Atx,
list_indent_width: 2,
list_indent_type: ListIndentType::Spaces,
bullets: "-".to_string(),
strong_em_symbol: '*',
escape_asterisks: false,
escape_underscores: false,
newline_style: html_to_markdown_rs::NewlineStyle::Backslash,
code_block_style: html_to_markdown_rs::CodeBlockStyle::Backticks,
..Default::default()
};
let markdown = convert(html, Some(options))?;
The preserve_tags option allows you to keep specific HTML tags in their original form instead of converting them to Markdown. This is useful for complex elements like tables that may not convert well:
use html_to_markdown_rs::{convert, ConversionOptions};
let html = r#"
<p>Before table</p>
<table class="data">
<tr><th>Name</th><th>Value</th></tr>
<tr><td>Item 1</td><td>100</td></tr>
</table>
<p>After table</p>
"#;
let options = ConversionOptions {
preserve_tags: vec!["table".to_string()],
..Default::default()
};
let markdown = convert(html, Some(options))?;
// Result: "Before table\n\n<table class=\"data\">...</table>\n\nAfter table\n"
You can preserve multiple tag types and combine with strip_tags:
let options = ConversionOptions {
preserve_tags: vec!["table".to_string(), "form".to_string()],
strip_tags: vec!["script".to_string(), "style".to_string()],
..Default::default()
};
use html_to_markdown_rs::{convert, ConversionOptions, PreprocessingOptions};
let mut options = ConversionOptions::default();
options.preprocessing.enabled = true;
options.preprocessing.preset = html_to_markdown_rs::PreprocessingPreset::Aggressive;
options.preprocessing.remove_navigation = true;
options.preprocessing.remove_forms = true;
let markdown = convert(scraped_html, Some(options))?;
use html_to_markdown_rs::convert;
// hOCR documents (from Tesseract, etc.) are detected automatically.
// Tables and spatial layout are reconstructed without additional options.
let markdown = convert(hocr_html, None)?;
use html_to_markdown_rs::{convert_with_inline_images, InlineImageConfig};
let config = InlineImageConfig::new(5 * 1024 * 1024) // 5MB max
.with_infer_dimensions(true)
.with_filename_prefix("img_".to_string());
let extraction = convert_with_inline_images(html, None, config)?;
println!("{}", extraction.markdown);
for (i, img) in extraction.inline_images.iter().enumerate() {
println!("Image {}: {} ({} bytes)", i, img.format, img.data.len());
}
This is the core Rust library. For other languages:
10-30x faster than pure Python/JavaScript implementations, delivering 150-210 MB/s throughput.
MIT