kedro-org/kedro 1.3.0 on GitHub

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 existing pipelines by modifying the pipeline registry.
The CLI --checkout flag can now be used on a new Kedro project from the default template, without a starter.
Added SESSION_CLASS as a configurable project setting, allowing users to define a custom KedroSession subclass

DataCatalog.load() and DataCatalog.save() now raise a DatasetError that includes the dataset name for easier debugging.
Aligned the run data passed to before_pipeline_run, after_pipeline_run, and on_pipeline_error and the schema specified in the hooks specs.
Fixed a path traversal vulnerability in versioned dataset loading that could allow unauthorized file access via unsanitized version strings.
Fixed remote code execution vulnerability in the logging configuration.
Removed the cachetools dependency and replaced it with a lightweight internal caching implementation.
Added a warning when a node returns a value but is defined with outputs=None, clarifying that the return value is ignored.
Added preserve_logging flag to configure_project() to prevent runtime-added logging handlers from being overwritten when configure_project() is called after custom handlers have been attached (e.g. in a long-running server process such as FastAPI).
Added util method find_config_file() to handle different config file extensions (.yml, .yaml)
Added reusable suggestion functionality for mistyped pipeline names using kedro run
Added a fix for CatalogConfigResolver splitting sqlalchemy URL during pattern resolution.

Added parameter validation documentation covering Pydantic model and dataclass support for typed parameters.