kedro-datasets-1.6.0

Major features and improvements

• Added support for Python 3.11.

kedro-datasets-1.5.3

Bug fixes and other changes

• Made databricks.ManagedTableDataSet read-only by default.
  • The user needs to specify write_mode to allow save on the data set.
• Fixed an issue on api.APIDataSet where the sent data was doubly converted to json
  string (once by us and once by the requests library).
• Fixed problematic kedro-datasets optional dependencies, revert to setup.py

Community contributions

kedro-datasets-1.5.2

Bug fixes and other changes

• Fixed problematic kedro-datasets optional dependencies.

kedro-telemetry-0.2.5

• Migrate all project metadata to static pyproject.toml.

kedro-datasets-1.5.1

Bug fixes and other changes

• Fixed problematic docstrings in pandas.DeltaTableDataSet causing Read the Docs builds on Kedro to fail.

kedro-airflow-0.6.0

• Change reference to kedro.pipeline.Pipeline object throughout test suite with kedro.modular_pipeline.pipeline factory.
• Migrate all project metadata to static pyproject.toml.
• Configure DAG kwargs via airflow.yml.
• The generated DAG file now contains the pipeline name.
• Included help for CLI arguments (see kedro airflow create --help).
• Added additional CLI argument --params to pass configuration to the Jinja2 template.

Community contributions

Many thanks to the following Kedroids for contributing PRs to this release:

• sbrugman

kedro-datasets-1.5.0

Major features and improvements

• Implemented lazy loading of dataset subpackages and classes.
  • Suppose that SQLAlchemy, a Python SQL toolkit, is installed in your Python environment. With this change, the SQLAlchemy library will not be loaded (for pandas.SQLQueryDataSet or pandas.SQLTableDataSet) if you load a different pandas dataset (e.g. pandas.CSVDataSet).
• Added automatic inference of file format for pillow.ImageDataSet to be passed to save().
• Added pandas.DeltaTableDataSet.

Bug fixes and other changes

• Improved error messages for missing dataset dependencies.
  • Suppose that SQLAlchemy, a Python SQL toolkit, is not installed in your Python environment. Previously, from kedro_datasets.pandas import SQLQueryDataSet or from kedro_datasets.pandas import SQLTableDataSet would result in ImportError: cannot import name 'SQLTableDataSet' from 'kedro_datasets.pandas'. Now, the same imports raise the more helpful and intuitive ModuleNotFoundError: No module named 'sqlalchemy'.

Community contributions

Many thanks to the following Kedroids for contributing PRs to this release:

• Daniel-Falk
• afaqueahmad7117
• everdark

kedro-datasets-1.4.2

Bug fixes and other changes

• Fixed documentations of GeoJSONDataSet and SparkStreamingDataSet
• Fixed problematic docstrings causing Read the Docs builds on Kedro to fail.

kedro-datasets-1.4.1

Bug fixes and other changes

• Fixed missing pickle.PickleDataSet extras in setup.py.

kedro-datasets-1.4.0

Major features and improvements

• Added SparkStreamingDataSet.

Bug fixes and other changes

• Fixed problematic docstrings of APIDataSet.