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MongoDB PyMongoArrow

PyMongoArrow is a PyMongo extension containing tools for loading MongoDB query result-sets as Apache Arrow tables, NumPy arrays, and Pandas or Polars DataFrames. PyMongoArrow is the recommended way to materialize MongoDB query result-sets as contiguous-in-memory typed arrays suited for in-memory analytical processing applications.

Learn how to install or upgrade PyMongoArrow, see the Install and Upgrade section.

Learn how to begin working with data in the Quick Start section.

For a list of new features and changes in each version, see the What's New section.

For a comparison between PyMongoArrow and PyMongo, see the Comparing to PyMongo section.

For examples of using PyMongoArrow schemas, see the Schema Examples section.

Learn about the types of data supported with PyMongoArrow in the Data Types section.

For answers to commonly asked questions about PyMongoArrow, see the FAQ section.

For detailed information about types and methods in PyMongoArrow, see the PyMongoArrow API documentation.

If you're having trouble or have questions about PyMongoArrow, ask your question on the MongoDB Community Forum. Once you get an answer, it'd be great if you could work it back into this documentation and contribute.

Report all issues at the main MongoDB JIRA bug tracker in the PyMongoArrow project.

Use the feedback engine to send feature requests and general feedback about PyMongoArrow.

Contributions to PyMongoArrow are encouraged. To contribute, fork the project on GitHub and send a pull request.

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