PyMongoArrow 1.3.0 Documentation#
Overview#
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. This documentation attempts to explain everything you need to know to use PyMongoArrow.
- Installing / Upgrading
Instructions on how to get the distribution.
- Quick Start
Start here for a quick overview.
- Data Types
Data type support with PyMongoArrow.
- Comparing to PyMongo
Comparison of using PyMongoArrow versus using PyMongo directly.
- Frequently Asked Questions
Frequently asked questions.
- pymongoarrow – Tools for working with MongoDB and PyArrow
The complete API documentation, organized by module.
- Schema Examples
Important notes about the usage of PyMongoArrow Schemas.
Getting Help#
If you’re having trouble or have questions about PyMongoArrow, ask your question on our MongoDB Community Forum. Once you get an answer, it’d be great if you could work it back into this documentation and contribute!
Issues#
All issues should be reported (and can be tracked / voted for / commented on) at the main MongoDB JIRA bug tracker, in the “Python Driver” project.
Feature Requests / Feedback#
Use our feedback engine to send us 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.
See also Developer Guide.
Changes#
See the Changelog for a full list of changes to PyMongoArrow.
About This Documentation#
This documentation is generated using the Sphinx documentation generator. The source files for the documentation are located in the docs/ directory of the PyMongoArrow distribution. To generate the docs locally run the following command from the root directory of the PyMongoArrow source:
$ cd docs && make html