MongoDB PyMongoArrow
Introduction
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.
Installation
Learn how to install or upgrade PyMongoArrow, see the Install and Upgrade section.
Quick Start
Learn how to begin working with data in the Quick Start section.
What's New
For a list of new features and changes in each version, see the What's New section.
Comparing to PyMongo
For a comparison between PyMongoArrow and PyMongo, see the Comparing to PyMongo section.
Schemas
For examples of using PyMongoArrow schemas, see the Schema Examples section.
Data Types
Learn about the types of data supported with PyMongoArrow in the Data Types section.
FAQ
For answers to commonly asked questions about PyMongoArrow, see the FAQ section.
API Documentation
For detailed information about types and methods in PyMongoArrow, see the PyMongoArrow API documentation.
Getting Help
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.
Issues
Report all issues at the main MongoDB JIRA bug tracker in the PyMongoArrow project.
Feature Requests and Feedback
Use the feedback engine to send feature requests and general feedback about PyMongoArrow.
Contributing
Contributions to PyMongoArrow are encouraged. To contribute, fork the project on GitHub and send a pull request.