Major features and improvements

• Added documentation with a focus on single machine and distributed environment deployment; the series includes Docker, Argo, Prefect, Kubeflow, AWS Batch, AWS Sagemaker and extends our section on Databricks
• Added kedro-starter-spaceflights alias for generating a project: kedro new --starter spaceflights.

Bug fixes and other changes

• Fixed TypeError when converting dict inputs to a node made from a wrapped partial function.
• PartitionedDataSet improvements:
  • Supported passing arguments to the underlying filesystem.
• Improved handling of non-ASCII word characters in dataset names.
  • For example, a dataset named jalapeño will be accessible as DataCatalog.datasets.jalapeño rather than DataCatalog.datasets.jalape__o.
• Fixed kedro install for an Anaconda environment defined in environment.yml.
• Fixed backwards compatibility with templates generated with older Kedro versions <0.16.5. No longer need to update .kedro.yml to use kedro lint and kedro jupyter notebook convert.
• Improved documentation.
• Added documentation using MinIO with Kedro.
• Improved error messages for incorrect parameters passed into a node.
• Fixed issue with saving a TensorFlowModelDataset in the HDF5 format with versioning enabled.
• Added missing run_result argument in after_pipeline_run Hooks spec.
• Fixed a bug in IPython script that was causing context hooks to be registered twice. To apply this fix to a project generated with an older Kedro version, apply the same changes made in this PR to your 00-kedro-init.py file.

Thanks for supporting contributions

Deepyaman Datta, Bhavya Merchant, Lovkush Agarwal, Varun Krishna S, Sebastian Bertoli, noklam, Daniel Petti, Waylon Walker