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Changelog#

0.9.2#

Breaking Changes

  • The --env flag no longer works for the pipeline launch or pipeline execute commands. Use --config instead.
  • The pipeline execute command no longer accepts the --workspace argument. To execute pipelines in a workspace, use pipeline launch instead.

New

  • Added ResourceDefinition.mock_resource helper for magic mocking resources. Example usage can be found here
  • Remove the row_count metadata entry from the Dask DataFrame type check (thanks @kinghuang!)
  • Add orient to the config options when materializing a Dask DataFrame to json (thanks @kinghuang!)

Bugfixes

  • Fixed a bug where applying configured to a solid definition would overwrite inputs from run config.
  • Fixed a bug where pipeline tags would not apply to solid subsets.
  • Improved error messages for repository-loading errors in CLI commands.
  • Fixed a bug where pipeline execution error messages were not being surfaced in Dagit.

0.9.1#

Bugfixes

  • Fixes an issue in the dagster-k8s-celery executor when executing solid subsets

Breaking Changes

  • Deprecated the IntermediateStore API. IntermediateStorage now wraps an ObjectStore, and TypeStoragePlugin now accepts an IntermediateStorage instance instead of an IntermediateStore instance. (Noe that IntermediateStore and IntermediateStorage are both internal APIs that are used in some non-core libraries).

0.9.0 “Laundry Service”#

Breaking Changes

  • The dagit key is no longer part of the instance configuration schema and must be removed from dagster.yaml files before they can be used.
  • -d can no longer be used as a command-line argument to specify a mode. Use --mode instead.
  • Use --preset instead of --preset-name to specify a preset to the pipeline launch command.
  • We have removed the config argument to the ConfigMapping, @composite_solid, @solid, SolidDefinition, @executor, ExecutorDefinition, @logger, LoggerDefinition, @resource, and ResourceDefinition APIs, which we deprecated in 0.8.0. Use config_schema instead.

New

  • Python 3.8 is now fully supported.
  • -d or --working-directory can be used to specify a working directory in any command that takes in a -f or --python_file argument.
  • Removed the deprecation of create_dagster_pandas_dataframe_type. This is the currently supported API for custom pandas data frame type creation.
  • Removed gevent dependency from dagster
  • New configured API for predefining configuration for various definitions: https://legacy-docs.dagster.io/overview/configuration/#configured
  • Added hooks to enable success and failure handling policies on pipelines. This enables users to set up policies on all solids within a pipeline or on a per solid basis. Example usage can be found here
  • New instance level view of Scheduler and running schedules
  • dagster-graphql is now only required in dagit images.

0.8.11#

Breaking Changes

  • AssetMaterializations no longer accepts a dagster_type argument. This reverts the change billed as "AssetMaterializations can now have type information attached as metadata." in the previous release.

0.8.10#

New

  • Added new GCS and Azure file manager resources
  • AssetMaterializations can now have type information attached as metadata. See the materializations tutorial for more
  • Added verification for resource arguments (previously only validated at runtime)

Bugfixes

  • Fixed bug with order-dependent python module resolution seen with some packages (e.g. numpy)
  • Fixed bug where Airflow's context['ts'] was not passed properly
  • Fixed a bug in celery-k8s when using task_acks_late: true that resulted in a 409 Conflict error from Kubernetes. The creation of a Kubernetes Job will now be aborted if another Job with the same name exists
  • Fixed a bug with composite solid output results when solids are skipped
  • Hide the re-execution button in Dagit when the pipeline is not re-executable in the currently loaded repository

Docs

  • Fixed code example in the advanced scheduling doc (Thanks @wingyplus!)
  • Various other improvements