cronitor pin to allow versions >= 5.0.1 to enable use of DayOfWeek as 7. Cronitor 4.0.0 is still disallowed. (Thanks, @joshuataylor!)checkDbReadyInitContainer to optionally disable db check initContainer.kind tags. (Thanks, @dragos-pop!)Re-executions.kind tag for display in the UI.DataprocResource now receives an optional parameter labels to be attached to Dataproc clusters. (Thanks, @thiagoazcampos!)checkDbReadyInitContainer flag to the Dagster Helm chart to allow disabling the default init container behavior. (Thanks, @easontm!)build_materialize_workbook_assets_definition which can be used to build assets that run materialize schedules for a Sigma workbook.SnowflakeResource and SnowflakeIOManager both accept additional_snowflake_connection_args config. This dictionary of arguments will be passed to the snowflake.connector.connect method. This config will be ignored if you are using the sqlalchemy connector.BackfillPolicy are now evaluated correctly during backfills. Self dependent assets no longer result in serial partition submissions or disregarded upstream dependencies.PipesCloudWatchMessageReader correctly identifies streams which are not ready yet and doesn't fail on ThrottlingException. (Thanks, @jenkoian!)FivetranWorkspace.sync_and_poll(...).fetch_column_metadata().dlt_assets API docs. (Thanks, @zilto!)dagster/run-id, dagster/code-location, dagster/user and Dagster Cloud environment variables) typically attached to external resources are now available under DagsterRun.dagster_execution_info.SensorReturnTypesUnion is now exported for typing the output of sensor functions.@fivetran_assets decorator.load_fivetran_asset_specs has been updated to accept an instance of DagsterFivetranTranslator or custom subclass.fivetran_assets decorator was added. It can be used with the FivetranWorkspace resource and DagsterFivetranTranslator translator to load Fivetran tables for a given connector as assets in Dagster. The build_fivetran_assets_definitions factory can be used to create assets for all the connectors in your Fivetran workspace.ECSPipesClient.run now waits up to 70 days for tasks completion (waiter parameters are configurable) (Thanks @jenkoian!)load_airbyte_cloud_asset_specs function has
been added. It can be used with the AirbyteCloudWorkspace resource and DagsterAirbyteTranslator translator to load your Airbyte Cloud connection streams as external assets in Dagster.icechunk kind.ConsolidatedSqliteEventLogStorage, which is mostly used for tests.1.6.0 may need to run dagster instance migrate to enable.map_asset_specs to enable modifying AssetSpecs and AssetsDefinitions in bulk.AssetSpec.replace_attributes and AssetSpec.merge_attributes to easily alter properties of an asset spec.PipesS3MessageReader now has a new parameter include_stdio_in_messages which enables log forwarding to Dagster via Pipes messages.log_external_stream has been added. It can be used to forward external logs to Dagster via Pipes messages.load_powerbi_asset_specs(..., use_workspace_scan=False).dagster-sigma snapshot command, allowing Sigma workspaces to be captured to a file for faster subsequent loading.DagsterExecutionStepNotFoundError errors when trying to execute an asset check step of a run launched by a backfill.owners added to AssetOuts when defining a @graph_multi_asset were not added to the underlying AssetsDefinition.& or | operators on AutomationConditions with labels would cause that label to be erased.SigmaFilter no longer fetch lineage information.DagsterPowerBITranslator.get_asset_key is deprecated in favor of DagsterPowerBITranslator.get_asset_spec().keyDagsterLookerApiTranslator.get_asset_key is deprecated in favor of DagsterLookerApiTranslator.get_asset_spec().keyDagsterSigmaTranslator.get_asset_key is deprecated in favor of DagsterSigmaTranslator.get_asset_spec().keyDagsterTableauTranslator.get_asset_key is deprecated in favor of DagsterTableauTranslator.get_asset_spec().keyAdded run_id to the run_tags index to improve database performance. Run dagster instance migrate to update the index. (Thanks, @HynekBlaha!)
Added icons for kind tags: Cassandra, ClickHouse, CockroachDB, Doris, Druid, Elasticsearch, Flink, Hadoop, Impala, Kafka, MariaDB, MinIO, Pinot, Presto, Pulsar, RabbitMQ, Redis, Redpanda, ScyllaDB, Starrocks, and Superset. (Thanks, @swrookie!)
Added a new icon for the Denodo kind tag. (Thanks, @tintamarre!)
Errors raised from defining more than one Definitions object at module scope now include the object names so that the source of the error is easier to determine.
[ui] Asset metadata entries like dagster/row_count now appear on the events page and are properly hidden on the overview page when they appear in the sidebar.
[dagster-aws] PipesGlueClient now attaches AWS Glue metadata to Dagster results produced during Pipes invocation.
[dagster-aws] PipesEMRServerlessClient now attaches AWS EMR Serverless metadata to Dagster results produced during Pipes invocation and adds Dagster tags to the job run.
[dagster-aws] PipesECSClient now attaches AWS ECS metadata to Dagster results produced during Pipes invocation and adds Dagster tags to the ECS task.
[dagster-aws] PipesEMRClient now attaches AWS EMR metadata to Dagster results produced during Pipes invocation.
[dagster-databricks] PipesDatabricksClient now attaches Databricks metadata to Dagster results produced during Pipes invocation and adds Dagster tags to the Databricks job.
[dagster-fivetran] Added load_fivetran_asset_specs function. It can be used with the FivetranWorkspace resource and DagsterFivetranTranslator translator to load your Fivetran connector tables as external assets in Dagster.
[dagster-looker] Errors are now handled more gracefully when parsing derived tables.
[dagster-sigma] Sigma assets now contain extra metadata and kind tags.
[dagster-sigma] Added support for direct workbook to warehouse table dependencies.
[dagster-sigma] Added include_unused_datasets field to SigmaFilter to disable pulling datasets that aren't used by a downstream workbook.
[dagster-sigma] Added skip_fetch_column_data option to skip loading Sigma column lineage. This can speed up loading large instances.
[dagster-sigma] Introduced an experimental dagster-sigma snapshot command, allowing Sigma workspaces to be captured to a file for faster subsequent loading.
dagster-airlift (experimental)#dagster-airlift is coming out of stealth. See the initial Airlift RFC here, and the following documentation to learn more:
More Airflow-related content is coming soon! We'd love for you to check it out, and post any comments / questions in the #airflow-migration channel in the Dagster slack.
monitor_all_code_locations and monitored_jobs did not raise the expected error. (Thanks, @apetryla!)AutomationCondition.any_deps_match() and AutomationCondition.all_deps_match() to render incorrectly when allow_selection or ignore_selection were set.CacheableAssetsDefinitions in code locations that contained AutomationConditionsToo many open files errors for jobs with many steps.dagster-dingtalk to the list of community supported libraries.dagster-wandb (Weights and Biases) documentation. (Thanks, @matt-weingarten!)dagster-sigma documentation.AssetOut.from_spec, that will construct an AssetOut from an AssetSpec.Column name section of the asset overview page.gcs (Google Cloud Storage) kind tag.report and semanticmodel kind tags.EcsRunLauncher. (Thanks, @zyd14!)DagsterDbtTranslator.get_code_version to customize the code version for your dbt assets. (Thanks, @Grzyblon!)PipesClientCompletedInvocation. This metadata will be attached to all materializations and asset checks stored during the pipes invocation.AutomationCondition.execution_in_progress which would cause it to evaluate to True for unpartitioned assets that were part of a run that was in progress, even if the asset itself had already been materialized.AutomationCondition.run_in_progress that would cause it to ignore queued runs.default_automation_condition_sensor to be constructed for user code servers running on dagster version < 1.9.0 even if the legacy auto_materialize: use_sensors configuration setting was set to False.0 in cases where all partitions were evaluated./ characters now work correctly with Dagster Pipes.dagster-airlift.types-sqlalchemy package is no longer included in the dagster[pyright] extra package.dagster project scaffold now has an option to create dagster projects from templates with excluded files/filepaths.parse_tableau_external_and_materializable_asset_specs is now available to parse a list of Tableau asset specs into a list of external asset specs and materializable asset specs.DagsterFivetranTranslator to customize assets loaded from Fivetran.dagster_snowflake.fetch_last_updated_timestamps now supports ignoring tables not found in Snowflake instead of raising an error.default_automation_condition_sensor to be constructed for user code servers running on dagster version < 1.9.0 even if the legacy auto_materialize: use_sensors configuration setting was set to False.dagster instance migrate on Dagster version 1.9.0 constructed a SQL query that exceeded the maximum allowed depth.ImportErrors are no longer raised when bigquery libraries are not installed [#25708]New
dagster-k8s Helm chart.dagster-k8s Helm chart.Bugfix
SourceString.dagster schedule up would fail in certain scenarios
with the SystemCronScheduler.Pandas
Dagstermill
Docs
Experimental
RetryRequested exception, was added.
This API is experimental and likely to change.Other
runtime_type to dagster_type in definitions. The following are deprecated
and will be removed in a future version.InputDefinition.runtime_type is deprecated. Use InputDefinition.dagster_type instead.OutputDefinition.runtime_type is deprecated. Use OutputDefinition.dagster_type instead.CompositeSolidDefinition.all_runtime_types is deprecated. Use
CompositeSolidDefinition.all_dagster_types instead.SolidDefinition.all_runtime_types is deprecated. Use SolidDefinition.all_dagster_types
instead.PipelineDefinition.has_runtime_type is deprecated. Use PipelineDefinition.has_dagster_type
instead.PipelineDefinition.runtime_type_named is deprecated. Use
PipelineDefinition.dagster_type_named instead.PipelineDefinition.all_runtime_types is deprecated. Use
PipelineDefinition.all_dagster_types instead.Docs
New
OutputDefinition to take is_required rather than is_optional argument. This is to
remain consistent with changes to Field in 0.7.1 and to avoid confusion
with python's typing and dagster's definition of Optional, which indicates None-ability,
rather than existence. is_optional is deprecated and will be removed in a future version.Bugfixes
Dagit
dagster_pandas
dagster_pandas dataframes.dagster_aws
s3_resource no longer uses an unsigned session by default.Bugfixes
Documentation
Breaking Changes
There are a substantial number of breaking changes in the 0.7.0 release.
Please see 070_MIGRATION.md for instructions regarding migrating old code.
Scheduler
The scheduler configuration has been moved from the @schedules decorator to DagsterInstance.
Existing schedules that have been running are no longer compatible with current storage. To
migrate, remove the scheduler argument on all @schedules decorators:
instead of:
@schedules(scheduler=SystemCronScheduler) def define_schedules(): ...
Remove the scheduler argument:
@schedules def define_schedules(): ...
Next, configure the scheduler on your instance by adding the following to
$DAGSTER_HOME/dagster.yaml:
scheduler: module: dagster_cron.cron_scheduler class: SystemCronScheduler
Finally, if you had any existing schedules running, delete the existing $DAGSTER_HOME/schedules
directory and run dagster schedule wipe && dagster schedule up to re-instatiate schedules in a
valid state.
The should_execute and environment_dict_fn argument to ScheduleDefinition now have a
required first argument context, representing the ScheduleExecutionContext
Config System Changes
In the config system, Dict has been renamed to Shape; List to Array; Optional to
Noneable; and PermissiveDict to Permissive. The motivation here is to clearly delineate
config use cases versus cases where you are using types as the inputs and outputs of solids as
well as python typing types (for mypy and friends). We believe this will be clearer to users in
addition to simplifying our own implementation and internal abstractions.
Our recommended fix is not to use Shape and Array, but instead to use our new condensed
config specification API. This allow one to use bare dictionaries instead of Shape, lists with
one member instead of Array, bare types instead of Field with a single argument, and python
primitive types (int, bool etc) instead of the dagster equivalents. These result in
dramatically less verbose config specs in most cases.
So instead of
from dagster import Shape, Field, Int, Array, String # ... code config=Shape({ # Dict prior to change 'some_int' : Field(Int), 'some_list: Field(Array[String]) # List prior to change })
one can instead write:
config={'some_int': int, 'some_list': [str]}
No imports and much simpler, cleaner syntax.
config_field is no longer a valid argument on solid, SolidDefinition, ExecutorDefintion,
executor, LoggerDefinition, logger, ResourceDefinition, resource, system_storage, and
SystemStorageDefinition. Use config instead.
For composite solids, the config_fn no longer takes a ConfigMappingContext, and the context
has been deleted. To upgrade, remove the first argument to config_fn.
So instead of
@composite_solid(config={}, config_fn=lambda context, config: {})
one must instead write:
@composite_solid(config={}, config_fn=lambda config: {})
Field takes a is_required rather than a is_optional argument. This is to avoid confusion
with python's typing and dagster's definition of Optional, which indicates None-ability,
rather than existence. is_optional is deprecated and will be removed in a future version.
Required Resources
All solids, types, and config functions that use a resource must explicitly list that
resource using the argument required_resource_keys. This is to enable efficient
resource management during pipeline execution, especially in a multiprocessing or
remote execution environment.
The @system_storage decorator now requires argument required_resource_keys, which was
previously optional.
Dagster Type System Changes
dagster.Set and dagster.Tuple can no longer be used within the config system.DagsterType, rather than a class than inherits from
RuntimeType. Instead of dynamically generating a class to create a custom runtime type, just
create an instance of a DagsterType. The type checking function is now an argument to the
DagsterType, rather than an abstract method that has to be implemented in
a subclass.RuntimeType has been renamed to DagsterType is now an encouraged API for type creation.bool in addition
to a TypeCheck object.type_check_fn on DagsterType (formerly type_check and RuntimeType, respectively) now
takes a first argument context of type TypeCheckContext in addition to the second argument of
value.define_python_dagster_type has been eliminated in favor of PythonObjectDagsterType .dagster_type has been renamed to usable_as_dagster_type.as_dagster_type has been removed and similar capabilities added as
make_python_type_usable_as_dagster_type.PythonObjectDagsterType and usable_as_dagster_type no longer take a type_check argument. If
a custom type_check is needed, use DagsterType.dagster_pyspark or
dagster_pandas and expecting Pyspark or Pandas types to work as Dagster types, e.g., in type
annotations to functions decorated with @solid to indicate that they are input or output types
for a solid, you will need to call make_python_type_usable_as_dagster_type from your code in
order to map the Python types to the Dagster types, or just use the Dagster types
(dagster_pandas.DataFrame instead of pandas.DataFrame) directly.Other
step_metadata_fn has been removed from SolidDefinition & @solid.SolidDefinition & @solid now takes tags and enforces that values are strings or
are safely encoded as JSON. metadata is deprecated and will be removed in a future version.resource_mapper_fn has been removed from SolidInvocation.New
Dagit now includes a much richer execution view, with a Gantt-style visualization of step execution and a live timeline.
Early support for Python 3.8 is now available, and Dagster/Dagit along with many of our libraries are now tested against 3.8. Note that several of our upstream dependencies have yet to publish wheels for 3.8 on all platforms, so running on Python 3.8 likely still involves building some dependencies from source.
dagster/priority tags can now be used to prioritize the order of execution for the built-in
in-process and multiprocess engines.
dagster-postgres storages can now be configured with separate arguments and environment
variables, such as:
run_storage: module: dagster_postgres.run_storage class: PostgresRunStorage config: postgres_db: username: test password: env: ENV_VAR_FOR_PG_PASSWORD hostname: localhost db_name: test
Support for RunLaunchers on DagsterInstance allows for execution to be "launched" outside of
the Dagit/Dagster process. As one example, this is used by dagster-k8s to submit pipeline
execution as a Kubernetes Job.
Added support for adding tags to runs initiated from the Playground view in Dagit.
Added @monthly_schedule decorator.
Added Enum.from_python_enum helper to wrap Python enums for config. (Thanks @kdungs!)
[dagster-bash] The Dagster bash solid factory now passes along kwargs to the underlying
solid construction, and now has a single Nothing input by default to make it easier to create a
sequencing dependency. Also, logs are now buffered by default to make execution less noisy.
[dagster-aws] We've improved our EMR support substantially in this release. The
dagster_aws.emr library now provides an EmrJobRunner with various utilities for creating EMR
clusters, submitting jobs, and waiting for jobs/logs. We also now provide a
emr_pyspark_resource, which together with the new @pyspark_solid decorator makes moving
pyspark execution from your laptop to EMR as simple as changing modes.
[dagster-pandas] Added create_dagster_pandas_dataframe_type, PandasColumn, and
Constraint API's in order for users to create custom types which perform column validation,
dataframe validation, summary statistics emission, and dataframe serialization/deserialization.
[dagster-gcp] GCS is now supported for system storage, as well as being supported with the Dask executor. (Thanks @habibutsu!) Bigquery solids have also been updated to support the new API.
Bugfix
RunStorage clean up pipeline run tags when a run
is deleted. Requires a storage migration, using dagster instance migrate.@solid and @lambda_solid decorators now correctly wrap their decorated functions, in the
sense of functools.wraps.dagster_k8s has been hardened against various failure modes and is now
compatible with Helm 2.raise_error flag in execute_pipeline now actually raises user exceptions instead
of a wrapper type.Documentation
Thank you Thank you to all of the community contributors to this release!! In alphabetical order: @habibutsu, @kdungs, @vatervonacht, @zzztimbo.
Bugfix
Documentation