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To extract text and tables from a PDF while preserving layout and formatting, you can automate the workflow using libraries like pdfplumber and pypdf to accurately read and isolate the document content.

Automating PDF form filling programmatically involves using a Python library to map structured data into the form fields of documents like tax returns, saving the populated output as a new PDF file.

Yes, you can perform OCR on scanned PDFs to convert them into searchable text by utilizing pytesseract alongside pdf2image and poppler_utils to process the document images and extract the underlying text.

Merging and splitting PDFs primarily requires Python libraries like pypdf, but advanced manipulation, OCR, and image extraction require external dependencies including poppler_utils, imagemagick, qpdf_tool, and pdftk_tool.

Adding watermarks and encrypting PDF files in an automated workflow is achieved by applying Python scripts that leverage pypdf and reportlab to overlay security layers and visual markers onto the document.

PDF data extraction often fails on scanned documents because they lack embedded text, requiring OCR processing, or on secured documents that need decryption via qpdf_tool before text and table extraction can proceed.