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Python client for MLflow REST API

Project description

status PyPI PyPI License PyPI Python Version ReadTheDocs Build Coverage

Python client for MLflow REST API.


  • Unlike MLflow Tracking client all REST API methods are exposed to user.

  • All class fields are validated with pydantic.

  • Basic and Bearer auth is supported.

  • All methods and classes are documented.


  • There is no integration with ML frameworks and libraries. You should use official MLflow client instead.

  • There is no integration with S3 or other artifact storage type. You should access it directly with boto3 or other client.

  • Only Python 3.7+ is supported. Python 3.6 and lower already reached end of life.



Contribution guide





Stable release

Stable version is released on every tag to master branch. Please use stable releases on production environment. Version example: 2.0.0

pip install mlflow-rest-client==2.0.0 # exact version

pip install mlflow-rest-client # latest release

Development release

Development version is released on every commit to dev branch. You can use them to test some new features before official release. Version example: 2.0.0.dev5

pip install mlflow-rest-client==2.0.0.dev5 # exact dev version

pip install --pre mlflow-rest-client # latest dev version


Clone repo:

git clone

cd mlflow-rest-client

Install dependencies for development:

pip install -r requirements-dev.txt

Install pre-commit hooks:

pre-commit install
pre-commit autoupdate
pre-commit install-hooks

Test pre-commit hooks run:

pre-commit run --all-files -v


Make sure you have an MLflow Tracking Server running.

from mlflow_rest_client import MLflowRESTClient

client = MLflowRESTClient("https://mlflow.domain", ignore_ssl_check=True)

experiment = client.get_or_create_experiment("experiment_name")
run = client.create_run(

See for more examples.

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