Filetype.pdf: Agnibina

count = 0 for i in range(doc.embfile_count()): info = doc.embfile_info(i) fname = clean_filename(info["filename"]) data = doc.embfile_get(i) (att_dir / fname).write_bytes(data) count += 1 doc.close() print(f"📦 Extracted count embedded file(s).")

# ------------------- Bookmarks / Outline ------------------- # def extract_bookmarks(pdf_path: Path, out_dir: Path): """Export the PDF's outline (bookmarks) as a JSON hierarchy.""" doc = fitz.open(str(pdf_path)) toc = doc.get_toc(simple=False) # list of [level, title, page, ...] # Turn into a nested dict for readability def build_tree(toc_entries): tree = [] stack = [(0, tree)] # (level, container) for level, title, page, *_ in toc_entries: while level <= stack[-1][0]: stack.pop() node = "title": title, "page": page, "children": [] stack[-1][1].append(node) stack.append((level, node["children"])) return tree agnibina filetype.pdf

# Optionally re-run the extraction on the OCR’d file # (You could replace the original path with ocr_output for downstream steps) count = 0 for i in range(doc

import pdfplumber import fitz # pymupdf from tqdm import tqdm tree)] # (level