mlflow-cratedb 3.1.4

MLflow adapter for CrateDB

MLflow adapter for CrateDB

About

An adapter for MLflow to use CrateDB as a storage database for MLflow Tracking. MLflow is an open source platform to manage the whole ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry.

Install

Install the most recent version of the mlflow-cratedb package.

uv pip install --upgrade mlflow-cratedb

To verify if the installation worked, you can inspect the version numbers of the software components you just installed.

mlflow-cratedb --version
mlflow-cratedb cratedb --version

Documentation

The MLflow Tracking subsystem is about recording and querying experiments, across code, data, config, and results.

The MLflow adapter for CrateDB can be used in different ways. Please refer to the handbook, and the documentation about container usage.

For more general information, see Machine Learning with CrateDB and examples about MLflow and CrateDB.

Development

For joining the development, or for making changes to the software, read about how to install a development sandbox.

Project Information

Resources

• Source code
• Documentation
• Python Package Index (PyPI)

Contributions

This library is an open source project, and is managed on GitHub. Every kind of contribution, feedback, or patch, is much welcome. Create an issue or submit a patch if you think we should include a new feature, or to report or fix a bug.

Development

In order to set up a development environment on your workstation, please head over to the development sandbox documentation. When you see the software tests succeed, you should be ready to start hacking.

License

The project is licensed under the terms of the Apache License 2.0, like MLflow and CrateDB, see LICENSE.

Acknowledgements

Siddharth Murching, Corey Zumar, Harutaka Kawamura, Ben Wilson, and all other contributors for conceiving and maintaining MLflow.

Andreas Nigg for contributing the tracking_merlion.py and tracking_pycaret.py ML experiment programs, using Merlion and PyCaret.