Can I extract PDF tables into Excel or CSV?

Yes, it includes advanced examples using pdfplumber combined with pandas to extract tabular data and export it to Excel files.

Does it support command-line PDF tools?

Absolutely. It covers powerful CLI utilities like qpdf, pdftotext, and pdftk for quick document operations outside of Python.

Can this skill handle scanned PDF documents?

Yes, the skill includes specific implementation patterns using pytesseract and pdf2image to perform OCR on scanned documents.

Can I add passwords to my PDF files?

Yes, the toolkit provides code snippets for encrypting PDFs and adding user/owner passwords using the pypdf library.

Which Python libraries are featured in this toolkit?

The guide provides detailed examples for pypdf (manipulation), pdfplumber (data extraction), reportlab (creation), and pytesseract (OCR).

PDF Processing Toolkit

Name: PDF Processing Toolkit
Author: EricGrill

byEricGrill

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Content Management

Manipulates PDF documents by extracting text and tables, merging files, and programmatically generating or filling PDF forms.

About

The PDF Processing Toolkit provides Claude with a comprehensive set of patterns and best practices for advanced document management. It enables developers to automate complex workflows including structural manipulation like merging and splitting, precise data extraction from tables using pdfplumber, and programmatic generation of high-quality reports with reportlab. Additionally, it covers OCR for scanned documents, form filling, and security features like password protection, making it an essential resource for integrating robust PDF capabilities into any application.

Key Features

Process scanned documents using OCR (Optical Character Recognition)
Programmatically generate custom PDFs with text, graphics, and multiple pages
Extract structured text and complex tables with layout preservation
2 GitHub stars
Manage PDF security including encryption and password protection
Merge, split, and rotate PDF pages using Python and CLI tools

Use Cases

Programmatically filling out and generating business forms at scale
Building batch processing pipelines to merge multiple reports into unified documents
Automating the extraction of financial data from PDF invoices into structured databases

About

Key Features

Process scanned documents using OCR (Optical Character Recognition)
Programmatically generate custom PDFs with text, graphics, and multiple pages
Extract structured text and complex tables with layout preservation
2 GitHub stars
Manage PDF security including encryption and password protection
Merge, split, and rotate PDF pages using Python and CLI tools

Use Cases

Programmatically filling out and generating business forms at scale
Building batch processing pipelines to merge multiple reports into unified documents
Automating the extraction of financial data from PDF invoices into structured databases