PDF Oxide - The Fastest PDF Library for Python and Rust

The fastest Python PDF library for text extraction, image extraction, and markdown conversion. Built on a Rust core — 0.8ms mean per document, 5× faster than PyMuPDF, 15× faster than pypdf. 100% pass rate on 3,830 real-world PDFs. MIT licensed.

Quick Start

Python

from pdf_oxide import PdfDocument

doc = PdfDocument("paper.pdf")
text = doc.extract_text(0)
chars = doc.extract_chars(0)
markdown = doc.to_markdown(0, detect_headings=True)

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"

Why pdf_oxide?

• 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
• Dual-language — First-class Rust API and Python bindings via PyO3
• 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

Rust Libraries

Text Quality

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

Corpus

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

Python API

from pdf_oxide import PdfDocument

doc = PdfDocument("report.pdf")
print(f"Pages: {doc.page_count}")
print(f"Version: {doc.version}")

# Extract text from each page
for i in range(doc.page_count):
    text = doc.extract_text(i)
    print(f"Page {i}: {len(text)} chars")

# Character-level extraction with positions
chars = doc.extract_chars(0)
for ch in chars:
    print(f"'{ch.char}' at ({ch.x:.1f}, {ch.y:.1f})")

# Password-protected PDFs
doc = PdfDocument("encrypted.pdf")
doc.authenticate("password")
text = doc.extract_text(0)

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");

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

Documentation

• Getting Started (Rust) - Complete Rust guide
• Getting Started (Python) - Complete Python guide
• Getting Started (WASM) - Browser and Node.js guide
• API Docs - Full Rust API reference
• Full Documentation - Complete documentation site
• Performance Benchmarks - Full benchmark methodology and results

Use Cases

• RAG / LLM pipelines — Convert PDFs to clean Markdown for retrieval-augmented generation with LangChain, LlamaIndex, or any framework
• 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

License

Dual-licensed under MIT or Apache-2.0 at your option. Unlike AGPL-licensed alternatives, pdf_oxide 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 = {PDF Oxide: Fast PDF Toolkit for Rust and Python},
  author = {Yury Fedoseev},
  year = {2025},
  url = {https://github.com/yfedoseev/pdf_oxide}
}

Rust + Python + WASM | MIT/Apache-2.0 | 100% pass rate on 3,830 PDFs | 0.8ms mean | 5× faster than PyMuPDF | v0.3.10