Major features and improvements Added dataset validation: datasets can declare a validator in their catalog entry, and the DataCatalog enforces it on every load and save. Failures raise DataValidationError (a DatasetError subclass), reporting every failed check at once. Pandera is the built-in adapter, installed with the new kedro[pandera-pandas] or kedro[pandera-polars] extras; custom validator c…
Major features and improvements Added a new HTTP Server layer which uses the KedroServiceSession to execute pipelines from HTTP requests. It offers the following endpoints: /run to run pipelines with optional runtime parameters. /health to check the server's health status. /snapshot to retrieve the current project snapshot. Added a new CLI command kedro server start to run the server. Added select…
Major features and improvements Add official support for Python 3.14. Added the first iteration of the KedroServiceSession, a new session implementation that allows for multiple runs and data injection. NOTE: This session implementation is under active development and may occasionally contain bugs or breaking changes. We encourage users to try it out and share their feedback with us. Added inspect…
Signed-off-by: Sajid Alam sajid_alam@mckinsey.com
Bug fixes and other changes Fixed AttributeError when node functions have non-Pydantic/dataclass type hints on params: inputs. The parameter validation framework now correctly skips types it cannot validate. Documentation changes Added documentation for Optional[Model] support and multi-type union limitations in parameter validation. Improved Mermaid diagram visibility in dark mode. Community cont…
Major features and improvements Added optional parameter validation that uses type hints of parameter inputs to auto-validate and instantiate Pydantic models/dataclasses with no impact on untyped parameters. Added list_versions() method for versioned datasets to list available dataset versions. Added pipelines_to_find parameter to find_pipelines(), allowing users to selectively run a subset of exi…
Major features and improvements Added @experimental decorator to mark unstable or early-stage public APIs. Added support for running multiple pipelines in a single Kedro session run via the --pipelines CLI option and pipeline_names argument in KedroSession.run() method. Updated the spaceflights-pyspark starter to use the new SparkDatasetV2 integration, enabling local, Databricks-native, and remote…
Bug fixes and other changes Improved namespace validation efficiency to prevent significant slowdowns when creating large pipelines Made deprecation warning appear only when the deprecated --namespace flag is used
Bug fixes and other changes Fixed project version mismatch error. The error is now only raised when the major version of the project and Kedro package differ, allowing minor and patch version differences without unnecessary failures.
Major features and improvements Added the ignore_hidden parameter to the OmegaConfigLoader. Dropped support for Python 3.9 (EOL Oct 2025). Minimum supported version is now 3.10. Bug fixes and other changes Bumped click dependency to support versions 8.2.0 and above. Fixed typos in docs and docstrings. Fixed duplicate execution of the deindex-old-docs.js script on Kedro documentation pages, prevent…
Major features and improvements Data Catalog The previously experimental KedroDataCatalog has been renamed to DataCatalog and is now the default catalog implementation. It retains the dict-like interface, supports lazy dataset initialisation, and delivers improved performance. While this change is seamless for users following standard Kedro workflows, it introduces a richer API for programmatic us…