pdf

To extract text and tables from a PDF, this Skill uses pdfplumber and pypdf to parse document content programmatically, enabling automated text extraction and structured table data retrieval from both native and processed files.

Yes, you can perform OCR on scanned PDFs using pytesseract and pdf2image. This process converts scanned document images into searchable and editable text, allowing you to extract data from image-based PDF files programmatically.

Automating PDF form filling is handled by pypdf and pdfplumber, which support both fillable and non-fillable forms. This workflow programmatically injects data into form fields and annotates documents to finalize inputs without manual entry.

To merge, split, or rotate PDF pages, pypdf provides the necessary programmatic operations. This allows you to manipulate document structures, combine multiple files, extract specific page ranges, and reorient pages within your automated workflow.

You need Python environments with pypdf to encrypt, decrypt, or add watermarks to PDFs. While the core workflow is script-based, the Skill also supports guidance for non-script usage to apply document protections and overlays.

Yes, this PDF processing approach works for batch processing invoices by extracting line items and compiling them into a CSV. It automates reading text and tables across multiple files to prepare structured archival data.