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getindata / kedro-kubeflow

Kedro Plugin to support running workflows on Kubeflow Pipelines
https://kedro-kubeflow.readthedocs.io
Apache License 2.0
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build(deps): bump kedro from 0.18.2 to 0.18.3 #192

Closed dependabot[bot] closed 1 year ago

dependabot[bot] commented 1 year ago

Bumps kedro from 0.18.2 to 0.18.3.

Release notes

Sourced from kedro's releases.

0.18.3

Release 0.18.3

Major features and improvements

  • Implemented autodiscovery of project pipelines. A pipeline created with kedro pipeline create <pipeline_name> can now be accessed immediately without needing to explicitly register it in src/<package_name>/pipeline_registry.py, either individually by name (e.g. kedro run --pipeline=<pipeline_name>) or as part of the combined default pipeline (e.g. kedro run). By default, the simplified register_pipelines() function in pipeline_registry.py looks like:

    def register_pipelines() -> Dict[str, Pipeline]:
    """Register the project's pipelines.

    Returns:
    A mapping from pipeline names to ``Pipeline`` objects.
&quot;&quot;&quot;
pipelines = find_pipelines()
pipelines[&quot;__default__&quot;] = sum(pipelines.values())
return pipelines

  • The Kedro IPython extension should now be loaded with %load_ext kedro.ipython.

  • The line magic %reload_kedro now accepts keywords arguments, e.g. %reload_kedro --env=prod.

  • Improved resume pipeline suggestion for SequentialRunner, it will backtrack the closest persisted inputs to resume.

Bug fixes and other changes

  • Changed default False value for rich logging show_locals, to make sure credentials and other sensitive data isn't shown in logs.
  • Rich traceback handling is disabled on Databricks so that exceptions now halt execution as expected. This is a workaround for a bug in rich.
  • When using kedro run -n [some_node], if some_node is missing a namespace the resulting error message will suggest the correct node name.
  • Updated documentation for rich logging.
  • Updated Prefect deployment documentation to allow for reruns with saved versioned datasets.
  • The Kedro IPython extension now surfaces errors when it cannot load a Kedro project.
  • Relaxed delta-spark upper bound to allow compatibility with Spark 3.1.x and 3.2.x.
  • Added gdrive to list of cloud protocols, enabling Google Drive paths for datasets.
  • Added svg logo resource for ipython kernel.

Upcoming deprecations for Kedro 0.19.0

  • The Kedro IPython extension will no longer be available as %load_ext kedro.extras.extensions.ipython; use %load_ext kedro.ipython instead.
  • kedro jupyter convert, kedro build-docs, kedro build-reqs and kedro activate-nbstripout will be deprecated.
Changelog

Sourced from kedro's changelog.

Release 0.18.3

Major features and improvements

  • Implemented autodiscovery of project pipelines. A pipeline created with kedro pipeline create <pipeline_name> can now be accessed immediately without needing to explicitly register it in src/<package_name>/pipeline_registry.py, either individually by name (e.g. kedro run --pipeline=<pipeline_name>) or as part of the combined default pipeline (e.g. kedro run). By default, the simplified register_pipelines() function in pipeline_registry.py looks like:

    def register_pipelines() -> Dict[str, Pipeline]:
    """Register the project's pipelines.

    Returns:
    A mapping from pipeline names to ``Pipeline`` objects.
&quot;&quot;&quot;
pipelines = find_pipelines()
pipelines[&quot;__default__&quot;] = sum(pipelines.values())
return pipelines

  • The Kedro IPython extension should now be loaded with %load_ext kedro.ipython.

  • The line magic %reload_kedro now accepts keywords arguments, e.g. %reload_kedro --env=prod.

  • Improved resume pipeline suggestion for SequentialRunner, it will backtrack the closest persisted inputs to resume.

Bug fixes and other changes

  • Changed default False value for rich logging show_locals, to make sure credentials and other sensitive data isn't shown in logs.
  • Rich traceback handling is disabled on Databricks so that exceptions now halt execution as expected. This is a workaround for a bug in rich.
  • When using kedro run -n [some_node], if some_node is missing a namespace the resulting error message will suggest the correct node name.
  • Updated documentation for rich logging.
  • Updated Prefect deployment documentation to allow for reruns with saved versioned datasets.
  • The Kedro IPython extension now surfaces errors when it cannot load a Kedro project.
  • Relaxed delta-spark upper bound to allow compatibility with Spark 3.1.x and 3.2.x.
  • Added gdrive to list of cloud protocols, enabling Google Drive paths for datasets.
  • Added svg logo resource for ipython kernel.

Upcoming deprecations for Kedro 0.19.0

  • The Kedro IPython extension will no longer be available as %load_ext kedro.extras.extensions.ipython; use %load_ext kedro.ipython instead.
  • kedro jupyter convert, kedro build-docs, kedro build-reqs and kedro activate-nbstripout will be deprecated.
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dependabot[bot] commented 1 year ago

Superseded by #217.