# PyMuPDF for Text PDF extraction

Text PDF ingestion uses PyMuPDF (`fitz`) so Heading Reconstruction can read font size/weight, text blocks, and outline bookmarks — the same structural signals `python-docx` gives us for DOCX. We rejected flat string extractors (`pypdf`), table-first libraries as the primary path (`pdfplumber`), and LibreOffice PDF→DOCX conversion (lossy styles, slow, fights ADR 0006’s “prefer native structure”).

## Considered Options

- **PyMuPDF** — chosen; best fit for Heading Reconstruction; AGPL acceptable while this stays an internal benchmarker
- **pdfplumber** — strong tables, weaker hierarchy; deferred to backlog if tables are a measured failure
- **pypdf** — too little layout/font signal
- **LibreOffice PDF→DOCX → existing parser** — reuses DOCX path but conversion quality is unreliable

## Consequences

- Add `pymupdf` dependency; keep a single PDF code path in the documents parser seam
- If we later ship the parser as a distributed service, revisit AGPL vs a permissive alternative
- Table-heavy and Scanned PDF work stays out of this ADR (see `backlog/`)