materialize and materialize_to_memory now both accept a selection argument that allows specifying a subset of assets to materialize.MultiPartitionsDefinition is no longer marked experimental.MultiPartitionsDefinitions with a time dimension.load_assets_from_package_module and similar methods now accept a freshness_policy, which will be applied to all loaded assets.build_sensor_context and build_multi_asset_sensor_context can now take a Definitions object in place of a RepositoryDefinitions3_resource now accepts use_ssl and verify configurations.selection argument on define_asset_job.MultiPartitionsDefinition.MultiPartitionsMapping (experimental) is loaded.TimeWindowPartitionMappings to not be bubbled up to the UI.pdb stopped working when using dagster dev.AssetMaterialization objects with a null AssetKey.TimeWindowPartitionsDefinition with a non-standard cron schedule, and also provided a minute_of_hour or similar argument in build_schedule_from_partitioned_job. Dagster would silently create the wrong cron expression. It now raises an error.PartitionsDefinition. These partitions are now ignored.PersistentAirflowDatabase where versions of airflow from 2.0.0 till 2.3.0 would not use the correct connection environment variable name.poll_sync_run function ofdagster-census that prevented polling from working correctly (thanks @ldincolasmay!)run_request_for_partition method on JobDefinition and UnresolvedAssetJobDefinition is now deprecated and will be removed in 2.0.0. Instead, directly instantiate a run request with a partition key via RunRequest(partition_key=...).AssetsDefinition.to_source_assets to method convert a set of assets to SourceAsset objects.MultiPartitionsDefinitions.mlflow pin from the dagster-mlflow package.When using build_asset_reconciliation_sensor, in some cases duplicate runs could be produced for the same partition of an asset. This has been fixed.
When using Pythonic configuration for resources, aliased field names would cause an error. This has been fixed.
Fixed an issue where context.asset_partitions_time_window_for_output threw an error when an asset was directly invoked with build_op_context.
[dagster-dbt] In some cases, use of ephemeral dbt models could cause the dagster representation of the dbt dependency graph to become incorrect. This has been fixed.
[celery-k8s] Fixed a bug that caused JSON deserialization errors when an Op or Asset emitted JSON that doesn't represent a DagsterEvent.
Fixed an issue where launching a large backfill while running dagster dev would sometimes fail with a connection error after running for a few minutes.
Fixed an issue where dagster dev would sometimes hang when running Dagster code that attempted to read in input via stdin.
Fixed an issue where runs that take a long time to import code would sometimes continue running even after they were stopped by run monitoring for taking too long to start.
Fixed an issue where AssetSelection.groups() would simultaneously select both source and regular assets and consequently raise an error.
Fixed an issue where BindResourcesToJobs would raise errors encapsulating jobs which had config specified at definition-time.
Fixed Pythonic config objects erroring when omitting optional values rather than specifying None.
Fixed Pythonic config and resources not supporting Enum values.
DagsterInstance.local_temp and DagsterInstance.ephemeral now use object instance scoped local artifact storage temporary directories instead of a shared process scoped one, removing a class of thread safety errors that could manifest on initialization.
Improved direct invocation behavior for ops and assets which specify resource dependencies as parameters, for instance:
class MyResource(ConfigurableResource): pass @op def my_op(x: int, y: int, my_resource: MyResource) -> int: return x + y my_op(4, 5, my_resource=MyResource())
[dagster-azure] Fixed an issue with an AttributeError being thrown when using the async DefaultAzureCredential (thanks @mpicard)
[ui] Fixed an issue introduced in 1.2.3 in which no log levels were selected by default when viewing Run logs, which made it appear as if there were no logs at all.
environment_vars argument to ScheduleDefinition is deprecated (the argument is currently non-functional; environment variables no longer need to be whitelisted for schedules)--path-prefix can now be supplied via Helm chart (thanks @mpicard)define_asset_job now auto-infer their partitions definitions if not explicitly defined.define_asset_job. This allows putting them on a schedule/sensor.instance property to the HookContext object that is passed into Op Hook functions, which can be used to access the current DagsterInstance object for the hook.create_table_schema_metadata_from_dataframe function to generate a TableSchemaMetadataValue from a Pandas DataFrame. Thanks @AndyBys!dag_run configuration on the integration’s database resources.dagster asset wipe-partitions-status-cache to see the partitions displayed.1.1.18, users with a gRPC server that could not access the Dagster instance on user code deployments would see an error when launching backfills as the instance could not instantiate. This has been fixed.build_asset_reconciliation_sensor from kicking off runs of downstream assets. This has been fixed.build_asset_reconciliation_sensor is now much more performant in cases where unpartitioned assets are upstream or downstream of static-partitioned assets with a large number of partitions.jobNamespace field in the Dagster Helm chart when using the CeleryK8sRunLauncher.en-US browser locale. This has been fixed.Dagster is now tested on Python 3.11.
Users can now opt in to have resources provided to Definitions bind to their jobs. Opt in by wrapping your job definitions in BindResourcesToJobs. This will become the default behavior in the future.
@op(required_resource_keys={"foo"}) def my_op(context) print(context.foo) @job def my_job(): my_op() defs = Definitions( jobs=BindResourcesToJobs([my_job]) resources={"foo": foo_resource}
Added dagster asset list and dagster asset materialize commands to Dagster’s command line interface, for listing and materializing software-defined assets.
build_schedule_from_partitioned_job now accepts jobs partitioned with a MultiPartitionsDefinition that have a time-partitioned dimension.
Added SpecificPartitionsPartitionMapping, which allows an asset, or all partitions of an asset, to depend on a specific subset of the partitions in an upstream asset.
load_asset_value now supports SourceAssets.
[ui] Ctrl+K has been added as a keyboard shortcut to open global search.
[ui] Most pages with search bars now sync the search filter to the URL, so it’s easier to bookmark views of interest.
[ui] In the run logs table, the timestamp column has been moved to the far left, which will hopefully allow for better visual alignment with op names and tags.
[dagster-dbt] A new node_info_to_definition_metadata_fn to load_assets_from_dbt_project and load_assets_from_dbt_manifest allows custom metadata to be attached to the asset definitions generated from these methods.
[dagster-celery-k8s] The Kubernetes namespace that runs using the CeleryK8sRunLauncher are launched in can now be configured by setting the jobNamespace field in the Dagster Helm chart under celeryK8sRunLauncherConfig.
[dagster-gcp] The BigQuery I/O manager now accepts timeout configuration. Currently, this configuration will only be applied when working with Pandas DataFrames, and will set the number of seconds to wait for a request before using a retry.
[dagster-gcp][dagster-snowflake] [dagster-duckdb] The BigQuery, Snowflake, and DuckDB I/O managers now support self-dependent assets. When a partitioned asset depends on a prior partition of itself, the I/O managers will now load that partition as a DataFrame. For the first partition in the dependency sequence, an empty DataFrame will be returned.
[dagster-k8s] k8s_job_op now supports running Kubernetes jobs with more than one pod (Thanks @Taadas).
AssetValueLoader.load_asset_value() didn’t load transitive resource dependencies correctly.RunConfig object with optional config arguments would lead to an error.ScheduleEvaluationContext.scheduled_execution_time to not be Optional.OpExecutionContext.partition_time_window ****(thanks @elben10).InputContext.upstream_output.log is no longer None when loading a source asset.async def ops are now invoked with asyncio.run.TimeWindowPartitionDefinition now throws an error at definition time when passed an invalid cron schedule instead of at runtime.cron_schedule_timezone inside of the config for a dbt model would not result in that property being set on the generated FreshnessPolicy. This has been fixed.GCSComputeLogManager when the session does not have permissions to generate signed urls.validate_run_config no longer accepts pipeline_def or mode arguments. These arguments refer to legacy concepts that were removed in Dagster 1.0, and since then there have been no valid values for them.Added experimental support for resource requirements in sensors and schedules. Resources can be specified using required_resource_keys and accessed through the context or specified as parameters:
@sensor(job=my_job, required_resource_keys={"my_resource"}) def my_sensor(context): files_to_process = context.my_resource.get_files() ... @sensor(job=my_job) def my_sensor(context, my_resource: MyResource): files_to_process = my_resource.get_files() ...