PDFOxide - The Fastest PDF Toolkit for 20 Languages

June 27, 2026 · View on GitHub

New in v0.3.69 — eleven new language bindings. PDFOxide now ships idiomatic bindings for C++, Swift, Kotlin, Dart, R, Julia, Zig, Scala, Clojure, Objective-C, and Elixir, each built over the stable C ABI with its own CI workflow, api-coverage tests, and runnable examples. That brings the toolkit to 20 languages (Rust core + 19 bindings). Want another language? Open an issue and tell us.

The fastest PDF library for text extraction, image extraction, and markdown conversion. A Rust core with bindings for 19 languages — Python, Go, JavaScript / TypeScript, C# / .NET, Java, Kotlin, Scala, Clojure, Ruby, PHP, C++, Objective-C, Swift, Dart, R, Julia, Zig, Elixir, and WASM — plus a CLI tool and MCP server for AI assistants. 0.8ms mean per document, 5× faster than PyMuPDF, 15× faster than pypdf. 100% pass rate on 3,830 real-world PDFs. MIT licensed.

Crates.io PyPI PyPI Downloads npm Documentation Build Status License: MIT OR Apache-2.0

Quick Start

Python

from pdf_oxide import PdfDocument

with PdfDocument("paper.pdf") as doc:
    print(len(doc))                          # number of pages
    for page in doc:
        text = page.text                     # lazy property
        chars = page.chars                   # lazy property
        md = page.markdown(detect_headings=True)

# Direct page access by index
doc = PdfDocument("paper.pdf")
page = doc[0]
text = page.text
pip install pdf_oxide

Rust

use pdf_oxide::PdfDocument;

let mut doc = PdfDocument::open("paper.pdf")?;
let text = doc.extract_text(0)?;
let images = doc.extract_images(0)?;
let markdown = doc.to_markdown(0, Default::default())?;
[dependencies]
pdf_oxide = "0.3"

CLI

pdf-oxide text document.pdf
pdf-oxide markdown document.pdf -o output.md
pdf-oxide search document.pdf "pattern"
pdf-oxide merge a.pdf b.pdf -o combined.pdf
brew install yfedoseev/tap/pdf-oxide

MCP Server (for AI assistants)

# Install
brew install yfedoseev/tap/pdf-oxide   # includes pdf-oxide-mcp

# Configure in Claude Desktop / Claude Code / Cursor
{
  "mcpServers": {
    "pdf-oxide": { "command": "crgx", "args": ["pdf_oxide_mcp@latest"] }
  }
}

Why PDFOxide?

  • Fast — 0.8ms mean per document, 5× faster than PyMuPDF, 15× faster than pypdf, 29× faster than pdfplumber
  • Reliable — 100% pass rate on 3,830 test PDFs, zero panics, zero timeouts
  • Complete — Text extraction, image extraction, PDF creation, and editing in one library
  • Multi-platform — 20 languages (Rust core + 19 bindings: Python, Go, JS/TS, C#/.NET, Java, Kotlin, Scala, Clojure, Ruby, PHP, C++, Objective-C, Swift, Dart, R, Julia, Zig, Elixir, WASM), plus a CLI and MCP server for AI assistants
  • Permissive license — MIT / Apache-2.0 — use freely in commercial and open-source projects

Performance

Benchmarked on 3,830 PDFs from three independent public test suites (veraPDF, Mozilla pdf.js, DARPA SafeDocs). Text extraction libraries only (no OCR). Single-thread, 60s timeout, no warm-up.

Python Libraries

LibraryMeanp99Pass RateLicense
PDFOxide0.8ms9ms100%MIT
PyMuPDF4.6ms28ms99.3%AGPL-3.0
pypdfium24.1ms42ms99.2%Apache-2.0
pymupdf4llm55.5ms280ms99.1%AGPL-3.0
pdftext7.3ms82ms99.0%GPL-3.0
pdfminer16.8ms124ms98.8%MIT
pdfplumber23.2ms189ms98.8%MIT
markitdown108.8ms378ms98.6%MIT
pypdf12.1ms97ms98.4%BSD-3

Rust Libraries

LibraryMeanp99Pass RateText Extraction
PDFOxide0.8ms9ms100%Built-in
oxidize_pdf13.5ms11ms99.1%Basic
unpdf2.8ms10ms95.1%Basic
pdf_extract4.08ms37ms91.5%Basic
lopdf0.3ms2ms80.2%No built-in extraction

Text Quality

99.5% text parity vs PyMuPDF and pypdfium2 across the full corpus. PDFOxide extracts text from 7–10× more "hard" files than it misses vs any competitor.

Corpus

SuitePDFsPass Rate
veraPDF (PDF/A compliance)2,907100%
Mozilla pdf.js89799.2%
SafeDocs (targeted edge cases)26100%
Total3,830100%

100% pass rate on all valid PDFs — the 7 non-passing files across the corpus are intentionally broken test fixtures (missing PDF header, fuzz-corrupted catalogs, invalid xref streams).

Features

ExtractCreateEdit
Text & LayoutDocumentsAnnotations
ImagesTablesForm Fields
FormsGraphicsBookmarks
AnnotationsTemplatesLinks
BookmarksImagesContent

Python API

Page-oriented API

from pdf_oxide import PdfDocument

with PdfDocument("report.pdf") as doc:
    print(len(doc))          # page count
    print(doc.version())

    # Iterate or index pages
    for page in doc:
        text   = page.text                      # str, lazy
        chars  = page.chars                     # list[TextChar], lazy
        words  = page.words                     # list[Word], lazy
        lines  = page.lines                     # list[TextLine], lazy
        tables = page.tables                    # list[Table], lazy
        images = page.images                    # list[Image], lazy
        md     = page.markdown(detect_headings=True)
        html   = page.html()
        print(f"Page {page.index}: {page.width:.0f}×{page.height:.0f} pts")

    # Direct index access (supports negative indices)
    first = doc[0]
    last  = doc[-1]

Scoped extraction

# Extract from a region: (x, y, width, height) in PDF points
header = doc.within(0, (0, 700, 612, 92)).extract_text()
region = doc.within(0, (50, 400, 500, 200))
region_words  = region.extract_words()
region_images = region.extract_images()

Extraction profiles

from pdf_oxide import ExtractionProfile

# Pre-tuned profiles for different document types
words = doc.extract_words(0, profile=ExtractionProfile.form())
lines = doc.extract_text_lines(0, profile=ExtractionProfile.academic())

# Override adaptive thresholds (in PDF points)
words = doc.extract_words(0, word_gap_threshold=2.5)
lines = doc.extract_text_lines(0, word_gap_threshold=2.5, line_gap_threshold=4.0)
params = doc.page_layout_params(0)
print(f"word gap: {params.word_gap_threshold:.1f}")

Form Fields

# Extract form fields
fields = doc.get_form_fields()
for f in fields:
    print(f"{f.name} ({f.field_type}) = {f.value}")

# Fill and save
doc.set_form_field_value("employee_name", "Jane Doe")
doc.set_form_field_value("wages", "85000.00")
doc.save("filled.pdf")

Rust API

use pdf_oxide::PdfDocument;

fn main() -> Result<(), Box<dyn std::error::Error>> {
    let mut doc = PdfDocument::open("paper.pdf")?;

    // Extract text
    let text = doc.extract_text(0)?;

    // Character-level extraction
    let chars = doc.extract_chars(0)?;

    // Extract images
    let images = doc.extract_images(0)?;

    // Vector graphics
    let paths = doc.extract_paths(0)?;

    Ok(())
}

Form Fields (Rust)

use pdf_oxide::editor::{DocumentEditor, EditableDocument, SaveOptions};
use pdf_oxide::editor::form_fields::FormFieldValue;

let mut editor = DocumentEditor::open("w2.pdf")?;
editor.set_form_field_value("employee_name", FormFieldValue::Text("Jane Doe".into()))?;
editor.save_with_options("filled.pdf", SaveOptions::incremental())?;

Installation

Python

pip install pdf_oxide

Wheels available for Linux, macOS, and Windows. Python 3.8–3.14.

Rust

[dependencies]
pdf_oxide = "0.3"

JavaScript/WASM

npm install pdf-oxide-wasm
const { WasmPdfDocument } = require("pdf-oxide-wasm");

CLI

brew install yfedoseev/tap/pdf-oxide    # Homebrew (macOS/Linux)
cargo install pdf_oxide_cli             # Cargo
cargo binstall pdf_oxide_cli            # Pre-built binary via cargo-binstall

MCP Server

brew install yfedoseev/tap/pdf-oxide    # Included with CLI in Homebrew
cargo install pdf_oxide_mcp             # Cargo

Other languages

Established bindings:

  • Gogo get github.com/yfedoseev/pdf_oxide/go — see go/README.md
  • JavaScript / TypeScript (Node.js)npm install pdf-oxide — see js/README.md
  • C# / .NETdotnet add package PdfOxide — see csharp/README.md
  • Java (JDK 11+) — Maven coords fyi.oxide:pdf-oxide:0.3.69 — see java/README.md
  • Rubygem install pdf_oxide — see ruby/README.md
  • PHPcomposer require oxide/pdf-oxide — see php/README.md

New in v0.3.69 (all over the stable C ABI):

<!-- Java (Maven) -->
<dependency>
  <groupId>fyi.oxide</groupId>
  <artifactId>pdf-oxide</artifactId>
  <version>0.3.69</version>
</dependency>
// Kotlin (Gradle, Kotlin DSL)
implementation("fyi.oxide:pdf-oxide-kotlin:0.3.69")

Every binding shares the same Rust core, so a bug fix in one lands in all of them — everything you read in this README applies, just with each language's native naming conventions. Publishing details for each registry are in docs/RELEASING-bindings.md.

CLI

22 commands for PDF processing directly from your terminal:

pdf-oxide text report.pdf                      # Extract text
pdf-oxide markdown report.pdf -o report.md     # Convert to Markdown
pdf-oxide html report.pdf -o report.html       # Convert to HTML
pdf-oxide info report.pdf                      # Show metadata
pdf-oxide search report.pdf "neural.?network"  # Search (regex)
pdf-oxide images report.pdf -o ./images/       # Extract images
pdf-oxide merge a.pdf b.pdf -o combined.pdf    # Merge PDFs
pdf-oxide split report.pdf -o ./pages/         # Split into pages
pdf-oxide watermark doc.pdf "DRAFT"            # Add watermark
pdf-oxide forms w2.pdf --fill "name=Jane"      # Fill form fields

Run pdf-oxide with no arguments for interactive REPL mode. Use --pages 1-5 to process specific pages, --json for machine-readable output.

MCP Server

pdf-oxide-mcp lets AI assistants (Claude, Cursor, etc.) extract content from PDFs locally via the Model Context Protocol.

Add to your MCP client configuration:

{
  "mcpServers": {
    "pdf-oxide": { "command": "crgx", "args": ["pdf_oxide_mcp@latest"] }
  }
}

The server exposes an extract tool that supports text, markdown, and HTML output formats with optional page ranges and image extraction. All processing runs locally — no files leave your machine.

Building from Source

# Clone and build
git clone https://github.com/yfedoseev/pdf_oxide
cd pdf_oxide
cargo build --release

# Run tests
cargo test

# Build Python bindings
maturin develop

# Build the shared library for Go, JS/TS, and C# bindings
cargo build --release --lib
# Output: target/release/libpdf_oxide.{so,dylib} or pdf_oxide.dll

Documentation

Use Cases

  • RAG / LLM pipelines — Convert PDFs to clean Markdown for retrieval-augmented generation with LangChain, LlamaIndex, or any framework
  • AI assistants — Give Claude, Cursor, or any MCP-compatible tool direct PDF access via the MCP server
  • Document processing at scale — Extract text, images, and metadata from thousands of PDFs in seconds
  • Data extraction — Pull structured data from forms, tables, and layouts
  • Academic research — Parse papers, extract citations, and process large corpora
  • PDF generation — Create invoices, reports, certificates, and templated documents programmatically
  • PyMuPDF alternative — MIT licensed, 5× faster, no AGPL restrictions

Why I built this

I needed PyMuPDF's speed without its AGPL license, and I needed it in more than one language. Nothing existed that ticked all three boxes — fast, MIT, multi-language — so I wrote it. The Rust core is what does the real work; the bindings for Python, Go, JS/TS, C#, and WASM are thin shells around the same code, so a bug fix in one lands in all of them. It now passes 100% of the veraPDF + Mozilla pdf.js + DARPA SafeDocs test corpora (3,830 PDFs) on every platform I've tested.

If it's useful to you, a star on GitHub genuinely helps. If something's broken or missing, open an issue — I read all of them.

— Yury

License

Dual-licensed under MIT or Apache-2.0 at your option. Unlike AGPL-licensed alternatives, PDFOxide can be used freely in any project — commercial or open-source — with no copyleft restrictions.

Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines.

cargo build && cargo test && cargo fmt && cargo clippy -- -D warnings

Citation

@software{pdf_oxide,
  title = {PDFOxide: Fast Multi-Language PDF Toolkit (Rust core, 19 language bindings)},
  author = {Yury Fedoseev},
  year = {2025},
  url = {https://github.com/yfedoseev/pdf_oxide}
}

20 languages (Rust + Python + Go + JS/TS + C# + Java + Kotlin + Scala + Clojure + Ruby + PHP + C++ + Objective-C + Swift + Dart + R + Julia + Zig + Elixir + WASM) + CLI + MCP | MIT/Apache-2.0 | 100% pass rate on 3,830 PDFs | 0.8ms mean | 5× faster than the industry leaders