pdf

To extract text and tables from PDF files, you can use Python libraries like pdfplumber alongside command-line tools to parse documents and return structured data for reuse. This approach reliably converts non-editable PDF content into usable formats.

Yes, you can fill non-fillable PDF forms by deriving exact page coordinates and writing text annotations directly onto the document. This allows automated form completion even when standard fillable fields are absent.

Yes, OCR for scanned documents is supported by converting PDF pages into images using pdf2image, then applying optical character recognition to produce searchable text from previously image-like formats.

The best way to merge, split, and rotate PDF pages is using deterministic Python libraries like pypdf to parse the document structure and write updated files with the desired page manipulations and appearances.

You can extract images from PDFs and validate bounding boxes using Python parsing libraries to detect page assets and coordinates accurately. This ensures extracted visual elements maintain their correct spatial dimensions.

PDF text extraction may return misaligned data when documents are scanned images rather than text-based formats, requiring OCR processing to interpret the visual content accurately before extracting usable text.