Galileo-Galilei/kedro-mlflow 0.3.0 on GitHub

[0.3.0] - 2020-10-11

Add dataset MlflowMetricsDataSet for metrics logging (#9) and update documentation for metrics.
Add CI workflow create-release to ensure release consistency and up-to-date CHANGELOG. (#57, #68)
Add templates for issues and pull requests (#57, #68)

Versioned datasets artifacts logging are handled correctly (#41)
MlflowDataSet handles correctly datasets which are inherited from AbstractDataSet (#45)
Change the test in _generate_kedro_command to accept both empty Iterables(default in CLI mode) and None values (default in interactive mode) (#50)
Force to close all mlflow runs when a pipeline fails. It prevents further execution of the pipeline to be logged within the same mlflow run_id as the failing pipeline. (#10)
Fix various documentation typos (#34, #35, #36 and more)
Update README (add badges for readibility, add a "main contributors" section to give credit, fix typo in install command, link to milestones for more up-to-date priorities) (#57, #68)
Fix bug in CI deployment workflow and rename it to publish (#57, #68)
Fix a bug in MlflowDataSet which sometimes failed to log on remote storage (S3, Azure Blob storage) with underlying log_artifacts when the kedro's AbstractDataset._filepath was a pathlib.PurePosixPath object instead of a string (#74).
Add a CI for release candidate creation and use actions to enforce semantic versioning and Keep a Changelog format.

Remove conda_env and model_name arguments from MlflowPipelineHook and add them to PipelineML and pipeline_ml. This is necessary for incoming hook auto-discovery in future release and it enables having multiple PipelineML in the same project (#58). This mechanically fixes #54 by making conda_env path absolute for airflow suppport.
flatten_dict_params, recursive and sep arguments of the MlflowNodeHook are moved to the mlflow.yml config file to prepare plugin auto registration. This also modifies the run.py template (to remove the args) and the mlflow.yml keys to add a hooks entry. (#59)
Rename CI workflow to test (#57, #68)
The input_name attributes of PipelineML is now a python property and makes a check at setting time to prevent setting an invalid value. The check ensures that input_name is a valid input of the inference pipeline.

Deprecate MlflowDataSet which is renamed as MlflowArtifactDataSet for consistency with the other datasets. It will raise a DeprecationWarning in this realease, and will be totally supressed in next minor release. Please update your catalog.yml entries accordingly as soon as possible. (#63)
Deprecate pipeline_ml which is renamed as pipeline_ml_factory to avoid confusion between a PipelineML instance and the helper function to create PipelineMl instances from Kedro Pipelines.

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