Skip to main content

MLflow adapter for CrateDB

Project description

MLflow adapter for CrateDB

Tests Test coverage Python versions

License Status PyPI Downloads

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.

Setup

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

pip install --upgrade 'mlflow-cratedb[examples]'

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

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.

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mlflow_cratedb-2.13.1.tar.gz (49.8 kB view details)

Uploaded Source

Built Distribution

mlflow_cratedb-2.13.1-py3-none-any.whl (17.4 kB view details)

Uploaded Python 3

File details

Details for the file mlflow_cratedb-2.13.1.tar.gz.

File metadata

  • Download URL: mlflow_cratedb-2.13.1.tar.gz
  • Upload date:
  • Size: 49.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.7

File hashes

Hashes for mlflow_cratedb-2.13.1.tar.gz
Algorithm Hash digest
SHA256 fb6725411c2c99dc6ce5de70e9d4e3aeba1935241e31aaf93f74db0f07115a4e
MD5 5100cf6e7f5e7320b83778d1ecec581b
BLAKE2b-256 3caf2ee2bb499633a8457cb2da55d8540b4d9d5cc624266b7a4c637e69637a46

See more details on using hashes here.

Provenance

File details

Details for the file mlflow_cratedb-2.13.1-py3-none-any.whl.

File metadata

File hashes

Hashes for mlflow_cratedb-2.13.1-py3-none-any.whl
Algorithm Hash digest
SHA256 6ee21ffa426dd1a4479e5e7301d9134c90848e7ce5bc0d5f3aa102cadb910d84
MD5 413067d8c6c6a8a6975254cf65f3e15b
BLAKE2b-256 505eae1c426e67c23db6cc3b2417624e71a6af898678c5105d42f9b89bb68dfb

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page