pdf

To extract text and tables from a scanned PDF using OCR, you need a searchable OCR conversion process. This involves rasterizing PDF pages into images and applying optical character recognition to transform them into usable digital text and structured table data.

To programmatically fill PDF form fields, you map target field values to detected fillable areas using a JSON configuration. For non-fillable PDFs, you apply precise coordinate handling to add text annotations directly onto the document pages.

The best way to merge, split, and rotate PDF pages programmatically is through document transformation operations. These functions modify PDF structures directly, allowing you to reorganize, extract, or alter page orientations without manual editing.

Yes, Python supports generating new PDFs and applying watermarks to existing documents. By utilizing dedicated PDF generation and transformation libraries, you can create documents from scratch or overlay watermark images and text onto existing pages.

Extracting structured tables from complex PDF documents faces limitations regarding coordinate handling and layout detection. Tables merged across multiple pages, lack clear bounding boxes, or feature nested structures often require manual boundary correction to achieve accurate extraction.