pdf

To extract text and tables from a PDF, use pdfplumber and pypdf. pdfplumber pulls structured table data, while pypdf reads standard text and metadata, enabling comprehensive data extraction from research papers and reports.

You can fill both fillable and non-fillable PDF forms automatically. By leveraging pypdf for interactive form fields and overlaying text using reportlab for non-fillable documents, the process accurately populates standardized application forms with provided data.

The best way to perform OCR on scanned PDFs is using pytesseract combined with pdf2image. This approach converts scanned document pages into images, applies optical character recognition, and makes previously unsearchable scanned text searchable and extractable.

qpdf supports merging, splitting, and rotating PDF files. As a command-line tool integrated into the workflow, it handles structural PDF manipulation alongside Python libraries like pypdf, allowing you to reorganize and modify document structures efficiently.

To extract data from a batch of PDF forms into a structured format, automate the process using pypdf and pdfplumber. This reads multiple files iteratively, pulls field values and text, and outputs organized data suitable for databases or spreadsheets.

You need poppler-utils installed because pdf2image depends on it to render PDF pages into images for OCR. While pypdf and pdfplumber handle direct text extraction without it, poppler-utils is strictly required for processing scanned documents via pytesseract.