Metadata-Version: 2.1
Name: mlflow-deploy-cli
Version: 1.0.1
Summary: CLI for deployment of [MLFlow](https://mlflow.org/) with support for backend and artifact stores.
License: MIT
Author: Aleksandar Ivanovski
Author-email: aleksandar.ivanovski@codechem.com
Requires-Python: >=3.9,<4.0
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.9
Requires-Dist: prompt-toolkit (>=3.0.30,<4.0.0)
Description-Content-Type: text/markdown

# mlflow-deployment

CLI for deployment of [MLFlow](https://mlflow.org/) with support for backend and artifact stores.

Deploy MLFlow with support for PostgreSQL, Azure Blobs, Amazon S3 and Google Cloud Platform with ease.

# Usage

1. [`pip install mlflow-deploy-cli`](https://pypi.org/project/mlflow-deploy-cli/)

2. `python -m mlflow_deploy_cli --artifact-store '<desired_store>'` _can be [`azure`](https://www.mlflow.org/docs/latest/tracking.html#azure-blob-storage), [`s3`](https://www.mlflow.org/docs/latest/tracking.html#id82), [`gcp`](https://www.mlflow.org/docs/latest/tracking.html#id84) or `local`_

3. `cd build`

4. `docker build . -t mlflow`

5. `docker-compose up -f docker-compose.yml up`

MLFlow is up and running 🚀.
