dagster-io/dagster 0.8.6

on GitHub

Breaking Changes

• The dagster-celery module has been broken apart to manage dependencies more coherently. There are now three modules: dagster celery, dagster-celery-k8s, and dagster-celery-docker.
• Related to above, the dagster-celery worker start command now takes a required -A parameter which must point to the app.py file within the appropriate module. E.g if you are using the celery_k8s_job_executor then you must use the -A dagster_celery_k8s.app option when using the celery or dagster-celery cli tools. Similar for the celery_docker_executor: -A dagster_celery_docker.app must be used.
• Renamed the input_hydration_config and output_materialization_config decorators to dagster_type_ and dagster_type_materializer respectively. Renamed DagsterType's input_hydration_config and output_materialization_config arguments to loader and materializer respectively.

New

• New pipeline scoped runs tab in Dagit

• Add the following Dask Job Queue clusters: moab, sge, lsf, slurm, oar (thanks @DavidKatz-il!)

• K8s resource-requirements for run coordinator pods can be specified using the dagster-k8s/resource_requirements tag on pipeline definitions:

  @pipeline(
      tags={
          'dagster-k8s/resource_requirements': {
              'requests': {'cpu': '250m', 'memory': '64Mi'},
              'limits': {'cpu': '500m', 'memory': '2560Mi'},
          }
      },
  )
  def foo_bar_pipeline():

• Added better error messaging in dagit for partition set and schedule configuration errors

• An initial version of the CeleryDockerExecutor was added (thanks @mrdrprofuroboros!). The celery workers will launch tasks in docker containers.

• Experimental: Great Expectations integration is currently under development in the new library dagster-ge. Example usage can be found here