AI Agents · Lesson

PDF Parsing with PyMuPDF and pdfplumber

Extracting text, tables, and metadata from PDFs programmatically.

Why PDF Parsing Is Non-Trivial

PDFs are a presentation format, not a data format. Text is stored as positioned glyphs, not logical paragraphs. Extracting meaningful text requires understanding layout, reading order, font properties, and handling edge cases like multi-column layouts, headers/footers, and embedded images.

Two libraries dominate: PyMuPDF (speed) and pdfplumber (table extraction).

PyMuPDF Basics

PyMuPDF (imported as fitz) is the fastest Python PDF library. It handles text extraction, metadata, images, and rendering. Install with pip install pymupdf.

import fitz  # PyMuPDF

# Open a PDF
doc = fitz.open('document.pdf')

print(f'Pages: {len(doc)}')
print(f'Metadata: {doc.metadata}')

# Extract text from all pages
full_text = ''
for page_num in range(len(doc)):
    page = doc[page_num]
    text = page.get_text()  # plain text extraction
    full_text += f'--- Page {page_num + 1} ---\n{text}\n'

doc.close()
print(full_text[:500])

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