pdf

Text and table extraction from PDFs uses libraries like pdfplumber to parse page content into structured formats. pdfplumber identifies table boundaries and extracts rows and columns into formats like JSON or Excel, handling both simple and complex layouts across multiple pages.

Fillable PDF forms can be populated programmatically by reading form field metadata and writing values using pypdf or reportlab. For non-fillable forms, the Skill analyzes bounding boxes to place text annotations precisely, enabling batch form completion from external data sources.

Document operations like merging, splitting, and rotating PDFs are handled through pypdf and command-line tools like qpdf. These operations process multiple files in batch workflows, enabling large-volume transformations without manual intervention.

Scanned PDFs require OCR processing via pytesseract and pdf2image to convert document images into searchable text. The Skill converts PDF pages to images, applies optical character recognition, and outputs extracted text for further analysis or data extraction.

Batch PDF processing is designed for high-volume scenarios using Python libraries and command-line tools integrated into programmatic workflows. The Skill supports processing hundreds of documents, applying transformations like extraction, merging, or form filling across the entire batch consistently.

Extracted PDF data can be exported to Excel, JSON, and other structured formats for downstream analysis or integration. Format conversion occurs after text and table extraction, enabling data to flow into reporting systems, databases, or analytical tools.