0.8.0 - 2024-05-09
- Added support for python 3.11 by @em-pe
- Added support for pydantic v2 and bumped minimal required pydantic version to
2.6.4
by @froessler - Added support for
metadata
argument in Azure ML datasets by @tomasvanpottelbergh - Fixed azureml-fsspec version update changed return type of
_infer_storage_options
and pinned fsspec version to patch only @froessler
0.7.0 - 2023-11-15
-
[💔 Breaking change] Renamed all
*DataSet
classes to*Dataset
to follow Kedro's naming convention which will be introduced in 0.19. -
Upgraded minimal requirements for MLflow to
>=2.0.0,<3.0.0
to be compatible withazureml-mlflow
-
Added
--on-job-scheduled
argument tokedro azureml run
to plug-in custom behaviour after Azure ML job is scheduled @Gabriel2409
0.6.0 - 2023-09-01
- Added ability to mark a node as deterministic (enables caching on Azure ML) by @tomasvanpottelbergh
- Explicitly disabled support for
AzureMLAssetDataSet
outputs ofuri_file
type by @tomasvanpottelbergh - Made
AzureMLAssetDataSet
local and downloadable by default allowing their use in kedro sessions outside of pipeline runs e.g.kedro ipython/jupyterlab
by @froessler - Fixed FileNotFoundError for local runs (using
kedro run
) when usingAzureMLAssetDataSet
of typeuri_file
by @Gabriel2409 - [❗️ Old datasets removal ] All datasets based on Azure ML SDK v1 (azureml-core) are removed, with only importable stubs left which raise a deprecation warning.
- ARM macOS support should work again 🎉 (v1 SDKs are removed)
0.5.0 - 2023-08-11
- [🚀 New dataset] Added support for
AzureMLAssetDataSet
based on Azure ML SDK v2 (fsspec) by @tomasvanpottelbergh & @froessler - [📝 Docs] Updated datasets docs with sections
- Bumped minimal required Kedro version to `0.18.11
- [
⚠️ Deprecation warning] - starting from0.4.0
the plugin is not compatible with ARM macOS versions due to internal azure dependencies (v1 SDKs). V1 SDK-based datasets will be removed in the future
0.4.1 - 2023-05-04
- [📝 Docs] Revamp the quickstart guide in documentation
- Refactor
kedro azureml init
command to be more user-friendly - Add dependency on
kedro-datasets
to prepare for Kedro0.19.0
; Removekedro.datasets.*
imports
0.4.0 - 2023-04-28
- [🧑🔬 Experimental ] Added support for pipeline-native data passing (allows to preview intermediate data in AzureML Studio UI) by @tomasvanpottelbergh
- New
AzureMLFileDataSet
andAzureMLPandasDataSet
by @asafalinadsg & @eliorc - E2E tests for
AzureMLPandasDataSet
dataset - Bumped minimal required Kedro version to
0.18.5
- Added support for
OmegaConfigLoader
0.3.6 - 2023-03-08
0.3.5 - 2023-02-20
- Ability to pass extra environment variables to the Kedro nodes using
--env-var
option - Default configuration for docker-flow adjusted for the latest kedro-docker plugin
- Fix authorization issues on AzureML Compute Instance (getindata#47) by @j0rd1smit
0.3.4 - 2022-12-30
- Add lazy initialization and cache to Kedro's context in the
KedroContextManager
class to prevent re-loading
0.3.3 - 2022-12-08
- Upgrade
azure-ai-ml
to>=1.2.0
to adress code upload file ignore issues (see Azure/azure-sdk-for-python#27338 (comment) and getindata#33).
0.3.2 - 2022-12-02
- Add a control gate for Kedro environments before starting the pipeline in Azure ML (getindata#33)
0.3.1 - 2022-11-18
- Fix default configuration, to make code upload as default
- Improved documentation and quickstart related to the code upload feature
0.3.0 - 2022-11-16
- Added support for execution via code upload for faster development cycles getindata#15
- Quickstart documentation improvements
0.2.2 - 2022-10-26
- Added sychronization of automatic datasets for distributed training use case
- Ability to overwrite the compute target at a Node level using a Node tag that references a compute alias defined in the compute section of
azureml.yaml
. - Improvements in build process, synchronised with getindata
python-opensource-template
- Add support for distributed training in PyTorch, TensorFlow and MPI via native Azure ML integration
0.1.0 - 2022-07-28
- Initial plugin release