Process and Generate PDF Documents

PDF Processing Guide collects essential document operations using Python libraries and command-line tools. It helps choose between reading and rearranging existing PDFs, extracting content, creating new documents, and processing scanned pages. The workflows address individual tasks rather than requiring one library to perform every operation.

The pypdf examples read pages, extract text, merge several documents, split a document into separate page files, inspect metadata, and rotate pages. Metadata extraction includes title, author, subject, and creator fields. Further examples apply an existing watermark page to every page in a document and write a password-protected output with user and owner passwords.

Use it for routine PDF processing, including combining documents, exporting tables, recovering text, creating reports, or automating page operations. Choose OCR when working with scanned pages that need image-based recognition rather than treating them as ordinary embedded text.

Form filling has dedicated instructions that should be read before attempting that workflow. Advanced pypdfium2 usage, JavaScript libraries such as pdf-lib, and additional troubleshooting are handled in the guide's separate reference material. Clarify missing inputs, permissions, boundaries, or success criteria rather than treating these examples as a substitute for environment-specific validation.

Inputs are PDF documents, selected pages or ranges, and task-specific content such as a watermark file or report text. Outputs include combined PDFs, individual page files, rotated documents, extracted text, images, spreadsheet tables, recognized scanned text, and newly generated reports.

pdfplumber handles text and table extraction. Its table example iterates through pages and tables; the extended example converts nonempty tables into pandas DataFrames, combines them, and writes an Excel spreadsheet. The reportlab library creates PDFs either through a canvas with positioned text and lines or through Platypus document elements such as paragraphs, spacers, and page breaks.

Scanned-document extraction uses pdf2image to convert pages into images and pytesseract to recognize each image, keeping page identifiers in the assembled text. Image extraction is also available independently through pdfimages. Password handling includes encryption with pypdf and decryption through qpdf when a password is supplied.

The command-line choices include pdftotext from poppler-utils, qpdf, and pdftk when available. The pdftotext utility supports plain extraction, layout preservation, and selected page ranges. A layout-preserving example is:

pdftotext -layout input.pdf output.txt

qpdf supports merging, selecting ranges, rotating pages, and password removal. The pdftk utility provides alternative merge, burst, and rotation operations. These complement the Python workflows, allowing the processing approach to follow the specific task and available tools.