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 wrappedpartial
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 asDataCatalog.datasets.jalapeño
rather thanDataCatalog.datasets.jalape__o
.
- For example, a dataset named
- Fixed
kedro install
for an Anaconda environment defined inenvironment.yml
. - Fixed backwards compatibility with templates generated with older Kedro versions <0.16.5. No longer need to update
.kedro.yml
to usekedro lint
andkedro 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 inafter_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