pdf

To extract text and tables from scanned PDFs, you can apply OCR processing to make the content searchable before parsing it. This workflow integrates pdfplumber for structured table extraction and pdf2image with Pillow to render and process scanned pages.

Automating PDF form filling for both fillable and non-fillable forms is achieved by manipulating document elements directly. The workflow uses pypdf to populate interactive fields and Pillow to overlay text onto static document images.

You can merge, split, rotate, and watermark PDF files within a single automated workflow. The process utilizes pypdf to manipulate document structures and apply watermarks, consolidating repetitive document archiving and reporting tasks.

This PDF processing approach handles document encryption and decryption natively. By leveraging pypdf, the workflow applies password protection to secure sensitive documents or removes encryption to allow downstream text extraction and editing.

Reading and extracting data from PDFs for automated archiving involves parsing text and tables using pdfplumber and pypdf. This extracts structured content and metadata, enabling programmatic document routing and end-to-end report generation.

Processing PDF files programmatically requires the pypdf, pdfplumber, pdf2image, and Pillow Python dependencies. These libraries collectively enable text extraction, page rendering, image processing, and OCR on scanned documents.