GroupDocs.Search for Python via .NET is a full-text search API: build an index over a folder of documents, then search it with keyword, phrase, wildcard, regular-expression, boolean, fuzzy, synonym, homophone and faceted queries, and highlight what was found. It indexes the text and metadata of more than 80 formats, including Word processing, spreadsheets, presentations, PDF, email, eBooks, archives and images, with no MS Office or OpenOffice installation required.
Quick example
fromgroupdocs.searchimportIndex# Create an index in a folder, index a folder of documents, and search itwithIndex("./index")asindex:index.add("./documents")result=index.search("relativity")print("Documents found:",result.document_count)
Features
Persistent index: Index files, folders and streams into an index on disk or in memory, and reopen it on the next run; update() reindexes only the documents that changed.
Rich queries: Keyword, phrase, wildcard, regular-expression, boolean, faceted, date-range and numeric-range search, written as text or built as objects.
Find what was meant: Fuzzy search tolerates typos and OCR noise, and synonym, homophone and word-form search, spell checking and keyboard layout correction widen a query.
Highlighting: Mark the found words in the whole document or in short fragments, as HTML or plain text.
Events and Python callbacks: Follow indexing, skip documents and supply passwords from Python handlers, and plug in your own text extractors, OCR engine and logger.
Index maintenance: Merge, optimize and check indexes, delete and rename documents, and update an index made by an older version.
Images: Reverse image search, and the text of images through an OCR engine you connect.
For practical code examples and explanations of the index-and-search workflow, see the Developer Guide section. It covers creating and updating indexes, every search type, search results and highlighting, dictionaries, events and Python callbacks, and search networks.
AI Agents and LLM Integration
The package ships an AGENTS.md reference for AI coding assistants, and the documentation is available to them through an MCP server and as machine-readable text. See AI agents and LLM integration.
Technical Support
If you experience any issues or have suggestions, please refer to the Technical Support topic. This topic provides multiple support channels tailored to your needs.
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