Skip to main content

The fastest Python PDF library: 0.8ms mean, 5× faster than PyMuPDF. Text extraction, markdown conversion, PDF creation. 100% pass rate on 3,830 PDFs.

Project description

PDF Oxide - The Fastest PDF Toolkit for Python, Rust, Go, JS/TS, C#, Java, WASM, CLI & AI

New in v0.3.54 — text-extraction fidelity pass (Hebrew / RTL visual-vs-logical detection, ToUnicode CMap fallback for bullet & ligature decode, multi-column prose reading order, reference-style two-column reading order). Java is the 8th binding (fyi.oxide:pdf-oxide:0.3.54 on Maven Central, JDK 11+, free Kotlin interop via the same JAR). Ruby, PHP, and Swift are next on the roadmap. Want another language? Open an issue and tell us.

The fastest PDF library for text extraction, image extraction, and markdown conversion. Rust core with bindings for Python, Go, JavaScript / TypeScript, C# / .NET, Java (JDK 11+, Kotlin-compatible), 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

New in v0.3.24 — now available in Go, JavaScript / TypeScript, and C# / .NET, alongside the existing Python, Rust, and WASM bindings. Same Rust core, same 0.8 ms extraction speed, same 100% pass rate. See the language guides: Python · Go · JavaScript / TypeScript · C# / .NET · Java / Kotlin · WASM

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 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
  • Multi-platform — Rust, Python, Go, JavaScript/TypeScript, C#/.NET, Java/Kotlin, WASM, 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

Library Mean p99 Pass Rate License
PDF Oxide 0.8ms 9ms 100% MIT
PyMuPDF 4.6ms 28ms 99.3% AGPL-3.0
pypdfium2 4.1ms 42ms 99.2% Apache-2.0
pymupdf4llm 55.5ms 280ms 99.1% AGPL-3.0
pdftext 7.3ms 82ms 99.0% GPL-3.0
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 and pypdfium2 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

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

  • 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 / Kotlin (JDK 11+) — Maven coords fyi.oxide:pdf-oxide:0.3.60 — see java/README.md

    <dependency>
      <groupId>fyi.oxide</groupId>
      <artifactId>pdf-oxide</artifactId>
      <version>0.3.60</version>
    </dependency>
    
    // Gradle (Kotlin DSL)
    implementation("fyi.oxide:pdf-oxide:0.3.60")
    

All four share the same Rust core as the Python and WASM bindings, so everything you read in this README applies to them as well — just with each language's native naming conventions.

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, 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, Python, Go, JavaScript, and C#},
  author = {Yury Fedoseev},
  year = {2025},
  url = {https://github.com/yfedoseev/pdf_oxide}
}

Rust + Python + Go + JS/TS + C# + WASM + CLI + MCP | MIT/Apache-2.0 | 100% pass rate on 3,830 PDFs | 0.8ms mean | 5× faster than the industry leaders

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

pdf_oxide_fips-0.3.64-cp38-abi3-win_amd64.whl (11.4 MB view details)

Uploaded CPython 3.8+Windows x86-64

pdf_oxide_fips-0.3.64-cp38-abi3-manylinux_2_28_x86_64.whl (11.7 MB view details)

Uploaded CPython 3.8+manylinux: glibc 2.28+ x86-64

pdf_oxide_fips-0.3.64-cp38-abi3-manylinux_2_28_aarch64.whl (11.1 MB view details)

Uploaded CPython 3.8+manylinux: glibc 2.28+ ARM64

pdf_oxide_fips-0.3.64-cp38-abi3-macosx_11_0_arm64.whl (10.7 MB view details)

Uploaded CPython 3.8+macOS 11.0+ ARM64

pdf_oxide_fips-0.3.64-cp38-abi3-macosx_10_12_x86_64.whl (11.8 MB view details)

Uploaded CPython 3.8+macOS 10.12+ x86-64

File details

Details for the file pdf_oxide_fips-0.3.64-cp38-abi3-win_amd64.whl.

File metadata

File hashes

Hashes for pdf_oxide_fips-0.3.64-cp38-abi3-win_amd64.whl
Algorithm Hash digest
SHA256 38879a30b2984e89364d3ce40ad1328ab2e7742381a77ed173bca5ce4598bd94
MD5 a73cd373a8cf8b37b1014769715893f3
BLAKE2b-256 cfb8b07705c993cdc5204fd4046b76fe66d3693bf2d85f047a4bd8156488af30

See more details on using hashes here.

File details

Details for the file pdf_oxide_fips-0.3.64-cp38-abi3-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for pdf_oxide_fips-0.3.64-cp38-abi3-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 d03d4fca51cf26d1758a0c97b26eb0e3a80db1955f9c2343014d72e06a2e2bf5
MD5 17c38c980382e9b8fd35a27d34e87e07
BLAKE2b-256 56ee28acbf368115d5d7b00ba94cccb04288ce8174791554ec62bb2c11379bfd

See more details on using hashes here.

File details

Details for the file pdf_oxide_fips-0.3.64-cp38-abi3-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for pdf_oxide_fips-0.3.64-cp38-abi3-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 d5db3b7c147313791a1d5fb7673fabb35c7f9a40d0b7d5886855d261402c2889
MD5 8f892aae52ed98b3e53f56322b676c68
BLAKE2b-256 558c559ad4e95a0fd479f119c7777a980a8fb2f4bd9ac23d586685bbcf56f77d

See more details on using hashes here.

File details

Details for the file pdf_oxide_fips-0.3.64-cp38-abi3-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for pdf_oxide_fips-0.3.64-cp38-abi3-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 b77dc746c1245f085b4e6bc0ffefcbd6f7ab294d22e3c331338509bf7e774cd7
MD5 52ebd61c05ba248069085b0dc5a8aaa3
BLAKE2b-256 57addc113fd41ed4208bb234c6883aa7148488346237a0787cfe8ff331e02815

See more details on using hashes here.

File details

Details for the file pdf_oxide_fips-0.3.64-cp38-abi3-macosx_10_12_x86_64.whl.

File metadata

File hashes

Hashes for pdf_oxide_fips-0.3.64-cp38-abi3-macosx_10_12_x86_64.whl
Algorithm Hash digest
SHA256 b282d05a8448ed84ab13185a1d0521544e1a5c05b6c1eac0361d7a0e1c2e40c2
MD5 57940b144a04b2a2747d007db72968c3
BLAKE2b-256 6e87eaccba1699f745a58958707010830abed43c9dc07989b425977aa4700b25

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page