pdfboss

A PDF engine written from scratch in Rust — parse, extract text, rasterize to PNG. One core, a CLI, and pythonic bindings.

Motivation

Reading a PDF shouldn't mean linking a C library. pdfboss is a clean-room reader built straight from the ISO 32000 specification: no C dependencies, no bindings to anyone else's engine — just safe Rust with a small, obvious API. The same core powers a CLI and a native Python extension, so a script and a service share one implementation.

It is a lenient reader: real-world files are damaged, and pdfboss recovers rather than refuses — reconstructing broken cross-reference tables, tolerating wrong stream lengths, and skipping garbage operators instead of erroring out.

Install

Python

pip install pdfboss

Prebuilt abi3 wheels (CPython ≥ 3.12) for Linux and macOS; no toolchain required.

Rust

cargo add pdfboss-core pdfboss-text pdfboss-render   # library crates
cargo install pdfboss-cli                            # the `pdfboss` binary

Usage

CLI

pdfboss info    report.pdf                 # version, page count, sizes, metadata
pdfboss text    report.pdf --page 2        # extract text (omit --page for all)
pdfboss render  report.pdf --page 1 -o page.png --scale 2.0
pdfboss obj     report.pdf 5               # pretty-print object 5

Python

import pdfboss

doc = pdfboss.Document("report.pdf")       # or Document(data=raw_bytes)
print(doc.page_count, doc.version, doc.metadata)

page = doc[0]
print(page.width, page.height, page.rotation)
text = page.extract_text()                 # or doc.extract_text() for all pages
png  = page.render(scale=2.0)              # PNG bytes

Rust

use pdfboss_core::Document;

let doc = Document::open("report.pdf")?;
let page = doc.page(0)?;

let text = pdfboss_text::extract_text(&doc, &page)?;
let pixmap = pdfboss_render::render_page(&doc, &page, 2.0)?;
pixmap.save_png("page.png")?;

What's inside

Supported: classic, stream, and hybrid cross-references with recovery scanning · object streams · FlateDecode, LZWDecode, ASCII85Decode, ASCIIHexDecode, RunLengthDecode + PNG/TIFF predictors · DCTDecode (JPEG) images · Standard-handler decryption — RC4 and AES-128/256 (empty user password) · page-tree attribute inheritance · text extraction with ToUnicode and WinAnsi/MacRoman/Standard encodings · rasterization of paths, fills (nonzero & even-odd), strokes, transforms, clipping, image/form XObjects, and embedded-TrueType glyph outlines.

Benchmarks

Against other Python PDF libraries over 40 real-world PDFs (best-of-3 per file, aggregated over the files every library handled; pages/sec, higher is faster):

pdfboss is the fastest library measured on both operations — including against the C-backed PyMuPDF. On text extraction it reaches 3,184 pages/s versus PyMuPDF's 460 (≈7×), and 30–170× the pure-Python readers. On open + parse it reaches 280,873 pages/s versus PyMuPDF's 102,576 (≈2.7×): lazy page-tree loading means opening a document reads only its declared page count instead of parsing every page dictionary up front. Rendering is not compared — pdfboss's rasterizer does not yet paint every glyph, so timing it against full renderers would be misleading.

Numbers are machine-dependent; reproduce with benchmarks/bench.py.

Limitations

Rendered pages paint the outlines of embedded TrueType glyphs (Type0/CIDFontType2 under Identity, and simple /TrueType fonts via their cmap). Text in other fonts (CFF/Type1 programs, the standard 14, subset fonts without a usable cmap) is still positioned but not drawn.

Not yet supported in v0.1 (they error or degrade gracefully, and are on the roadmap): password-protected documents (the empty user password is handled for both RC4 and AES) · non-TrueType glyph outlines (CFF/Type1) · shadings and tiling patterns · JPXDecode (JPEG 2000).

Development

cargo test --workspace          # Rust test suite
cargo clippy --workspace --all-targets -- -D warnings
maturin develop                 # build the Python extension into your venv
pytest                          # Python integration tests

License

Dual-licensed under either of

• MIT license (LICENSE-MIT)
• Apache License, Version 2.0 (LICENSE-APACHE)

at your option. Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you shall be dual-licensed as above, without any additional terms or conditions.