pdf

To extract text and tables from scanned PDF documents, you can use OCR processing via pytesseract and pdf2image. This approach handles scanned documents by converting pages to images, allowing accurate data retrieval from non-native PDF structures.

The best way to automate filling out non-fillable PDF forms is by using coordinate-based annotation. This method utilizes pdf-lib to visually map and insert data onto specific document locations, bypassing the need for native fillable form fields.

You can merge, split, and encrypt PDF files programmatically using document manipulation libraries like pypdf and pdfplumber. These tools enable batch document manipulation, allowing you to easily modify document structures and secure content.

Yes, you can use Python libraries like pdfplumber to parse complex PDF tables. It specializes in accurate data retrieval and table parsing across various PDF structures, ensuring structured data extraction from native documents.

Automated PDF form filling works with both native and scanned documents. It supports natively fillable forms and applies OCR with coordinate-based annotation for scanned or non-fillable forms, ensuring accurate data entry across complex workflows.