pdf_oxide 0.3.9

The fastest Rust PDF library with text extraction: 0.8ms mean, 100% pass rate on 3,830 PDFs. 5× faster than pdf_extract, 17× faster than oxidize_pdf. Extract, create, and edit PDFs.
Documentation
# 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.

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[![Build Status](https://github.com/yfedoseev/pdf_oxide/workflows/CI/badge.svg)](https://github.com/yfedoseev/pdf_oxide/actions)
[![License: MIT OR Apache-2.0](https://img.shields.io/badge/License-MIT%20OR%20Apache--2.0-blue.svg)](https://opensource.org/licenses)

## Quick Start

### Python
```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)
```

```bash
pip install pdf_oxide
```

### Rust
```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())?;
```

```toml
[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). 18 libraries tested, single-thread, 60s timeout, no warm-up.

### Python Libraries

| Library | Mean | p99 | Pass Rate | License |
|---------|------|-----|-----------|---------|
| **PDF Oxide** | **0.8ms** | **9ms** | **100%** | **MIT** |
| unstructured | 478.4ms | 1,477ms | 99.6% | Apache-2.0 |
| PyMuPDF | 4.6ms | 28ms | 99.3% | AGPL-3.0 |
| pypdfium2 | 4.1ms | 42ms | 99.2% | Apache-2.0 |
| kreuzberg | 7.2ms | 49ms | 99.1% | MIT |
| pymupdf4llm | 55.5ms | 280ms | 99.1% | AGPL-3.0 |
| pdftext | 7.3ms | 82ms | 99.0% | GPL-3.0 |
| extractous | 112.0ms | 165ms | 98.9% | Apache-2.0 |
| pdfminer | 16.8ms | 124ms | 98.8% | MIT |
| pdfplumber | 23.2ms | 189ms | 98.8% | MIT |
| markitdown | 108.8ms | 378ms | 98.6% | MIT |
| pypdf | 12.1ms | 97ms | 98.4% | BSD-3 |

### Rust Libraries

| Library | Mean | p99 | Pass Rate | Text Extraction |
|---------|------|-----|-----------|-----------------|
| **PDF Oxide** | **0.8ms** | **9ms** | **100%** | **Built-in** |
| oxidize_pdf | 13.5ms | 11ms | 99.1% | Basic |
| unpdf | 2.8ms | 10ms | 95.1% | Basic |
| pdf_extract | 4.08ms | 37ms | 91.5% | Basic |
| lopdf | 0.3ms | 2ms | 80.2% | No built-in extraction |

### Text Quality

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

### Corpus

| Suite | PDFs | Pass Rate |
|-------|-----:|----------:|
| veraPDF (PDF/A compliance) | 2,907 | 100% |
| Mozilla pdf.js | 897 | 99.2% |
| SafeDocs (targeted edge cases) | 26 | 100% |
| **Total** | **3,830** | **100%** |

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

| Extract | Create | Edit |
|---------|--------|------|
| Text & Layout | Documents | Annotations |
| Images | Tables | Form Fields |
| Forms | Graphics | Bookmarks |
| Annotations | Templates | Links |
| Bookmarks | Images | Content |

## Python API

```python
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)
```

## Rust API

```rust
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(())
}
```

## Installation

### Python

```bash
pip install pdf_oxide
```

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

### Rust

```toml
[dependencies]
pdf_oxide = "0.3"
```

## Building from Source

```bash
# 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)]docs/getting-started-rust.md** - Complete Rust guide
- **[Getting Started (Python)]docs/getting-started-python.md** - Complete Python guide
- **[API Docs]https://docs.rs/pdf_oxide** - Full Rust API reference
- **[Full Documentation]https://pdf.oxide.fyi** - Complete documentation site
- **[Performance Benchmarks]https://pdf.oxide.fyi/docs/performance** - 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](LICENSE-MIT) or [Apache-2.0](LICENSE-APACHE) 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](CONTRIBUTING.md) for guidelines.

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

## Citation

```bibtex
@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** | MIT/Apache-2.0 | 100% pass rate on 3,830 PDFs | 0.8ms mean | 5× faster than PyMuPDF | v0.3.9