pdf

To extract text and tables from PDF invoices, you can programmatically parse documents using pypdf and pdfplumber to pull full-page text, detect line-item tables, and export the structured data into a centralized CSV.

You can programmatically fill native PDF form fields and add text annotations to non-fillable documents, applying validation for field IDs and page locations before writing the filled copies for your records.

For scanned PDFs requiring OCR text extraction, pypdf alone is insufficient, but you can convert pages to images using pdf2image and Pillow to process the scanned content and pull embedded data.

The best way to validate bounding boxes before annotating PDF documents is to run programmatic bounding-box intersection and size checks, creating visual validation overlays to ensure accurate placement.

You can merge, split, and manipulate PDF documents programmatically by applying pypdf and pdfplumber parsing tools to extract pages, combine multiple files, and restructure the document workflows.

Limitations of extracting embedded images from PDF files include handling complex page layouts and scanned pages, which require converting pages to images with pdf2image and applying OCR fallback for accurate retrieval.