GroupDocs.Metadata for Python via .NET Overview Leave feedback

GroupDocs.Metadata for Python via .NET is a native Python library that reads, edits, removes, and exports metadata across documents, images, audio, video, and many other formats. It works with the most notable metadata standards — XMP, EXIF, IPTC, Image Resource Blocks, and ID3 — as well as format-specific and built-in document properties, and exposes them all through one unified, predicate-driven API regardless of file format. It runs entirely on-premise, requires no Microsoft Office installation, and ships as a pre-built wheel on Windows, Linux, and macOS.

Typical uses include:

• Privacy and compliance — strip author, GPS location, comments, and hidden data from files before they leave your organization.
• Digital asset management — read and edit EXIF, IPTC, and XMP fields on images to drive search, tagging, and cataloguing.
• AI / content preprocessing — extract metadata as structured data (JSON, CSV) to enrich search indexes and LLM context. See Agents and LLM Integration.
• Auditing — inspect documents for format, MIME type, encryption state, and statistics without modifying them.
• Batch normalization — set or update properties (titles, dates, copyright) across many files with a single predicate.

With its powerful and straightforward API, you can:

• Work with the most popular metadata standards: XMP, EXIF, IPTC, Image Resource Blocks, ID3, document properties, etc.
• Manage audio metadata: ID3 tags (ID3v1, ID3v2), Lyrics3 tag, APE.
• Create, modify, and remove metadata with a few lines of code.
• Identify built-in, custom, and hidden metadata.
• Work with password-protected documents.
• Detect the format and MIME type of a loaded file by its internal structure.
• Use predefined tags to manipulate metadata properties in a unified way across all supported formats.
• Detect and remove digital signatures associated with a loaded file.
• Inspect office documents to extract user comments, form fields, hidden pages, etc.
• Manage metadata in e-books, torrent files, archives, electronic business cards, saved emails, and more.

GroupDocs.Metadata runs across multiple platforms and operating systems: Windows, Linux, and macOS (Intel and Apple Silicon).

from groupdocs.metadata import Metadata


def quick_example():
    """Read every metadata property from a document."""
    with Metadata("./input.docx") as metadata:
        # `lambda p: True` matches every property in the file
        for prop in metadata.find_properties(lambda p: True):
            print(f"{prop.name} = {prop.value}")


if __name__ == "__main__":
    quick_example()

from groupdocs.metadata import License, Metadata


def remove_all_metadata():
    """Strip every property and save a clean copy (saving requires a license)."""
    License().set_license("./GroupDocs.Metadata.lic")

    with Metadata("./input.pdf") as metadata:
        removed = metadata.sanitize()
        print(f"Removed {removed} properties")
        metadata.save("./clean.pdf")


if __name__ == "__main__":
    remove_all_metadata()

1. Install the package — Installation walks through PyPI and offline wheel installation for Windows, Linux, and macOS.
2. Run your first example — the Quick Start Guide reads and removes metadata in a few minutes.
3. Explore the examples — How to Run Examples clones the runnable repository and runs every documented scenario locally or in Docker.
4. Use it in depth — the Developer Guide covers reading, editing, removing, standards, loading, saving, and exporting.
5. Plug it into AI pipelines — Agents and LLM Integration explains the MCP server and the AGENTS.md shipped inside the wheel.

If you encounter an issue while using GroupDocs.Metadata or have a technical question, feel free to create a post in our Free Support Forum. If free support is not sufficient, you can submit a ticket to our Paid Support Helpdesk.