pdf

Text and table extraction from PDFs uses libraries like pdfplumber and pypdf to parse document structure and pull structured content. These tools read PDF formatting and output text, tables, and metadata that you can process programmatically or export to other formats.

Automated form filling detects fillable and non-fillable PDF fields and populates them with batch data. This Skill uses reportlab and related utilities to merge datasets with form templates, processing multiple documents in one workflow without manual intervention.

Batch PDF processing combines pypdf, pdfplumber, and command-line utilities to merge, split, and extract content across document collections. A workflow handles multiple files in parallel, extracting data and manipulating pages programmatically for large-scale automation.

Scanned PDFs and image-based documents require optical character recognition (OCR). This Skill integrates pdf2image and pytesseract to convert image pages to text, enabling data extraction from documents that lack embedded text layers.

Extracted data can be transformed and written to new PDFs using reportlab or exported to structured formats. The workflow supports creating fresh documents, merging processed content, and exporting to formats compatible with downstream tools.

Complex layouts and encryption can affect extraction accuracy and form-filling capability. Standard libraries handle most PDFs, but heavily encrypted files, unusual layouts, or embedded objects may require preprocessing or specialized handling to extract content reliably.