Dagster

New

- Performance improvements when evaluating time-partitioned run requests within sensors and schedules.
- [ui] Performance improvements when loading the asset catalog and launchpad for deployments with many time-partitioned assets.

Bugfixes

- Fixed an issue where loading a Definitions object that included sensors attached to multiple jobs would raise an error.
- Fixed a bug in which Pythonic resources would produce underlying resource values that would fail reference equality checks. This would lead to a conflicting resource version error when using the same Pythonic resource in multiple places.

**Major Changes since 1.2.0 (core) / 0.18.0 (libraries)**

Core

- **Auto-materialize policies replace the asset reconciliation sensor** - We significantly renovated the APIs used for specifying which assets are scheduled declaratively. Compared to `build_asset_reconciliation_sensor`s , `AutoMaterializePolicy` works across code locations, as well as allow you to customize the conditions under which each asset is auto-materialized. [[docs](https://docs.dagster.io/concepts/assets/asset-auto-execution)]
- **Asset backfill page** - A new page in the UI for monitoring asset backfills shows the progress of each asset in the backfill.
- **Clearer labels for tracking changes to data and code** - Instead of the opaque “stale” indicator, Dagster’s UI now indicates whether code, upstream data, or dependencies have changed. When assets are in violation of their `FreshnessPolicy`s, Dagster’s UI now marks them as “overdue” instead of “late”.
- **Auto-materialization and observable source assets** - Assets downstream of an observable source asset now use the source asset observations to determine whether upstream data has changed and assets need to be materialized.
- **Pythonic Config and Resources** - The set of APIs introduced in 1.2 is no longer experimental [[community memo](https://dagster.io/blog/pythonic-config-and-resources)]. Examples, integrations, and documentation have largely ported to the new APIs. Existing resources and config APIs will continue to be supported for the foreseeable future. Check out [migration guide](https://docs.dagster.io/guides/dagster/migrating-to-pythonic-resources-and-config) to learn how to incrementally adopt the new APIs.

Docs

- **Improved run concurrency docs** - You asked (in support), and we answered! This [new guide](https://docs.dagster.io/guides/limiting-concurrency-in-data-pipelines) is a one-stop-shop for understanding and implementing run concurrency, whether you’re on Dagster Cloud or deploying to your own infrastructure.
- **Additions to the Intro to Assets tutorial** - We’ve added two new sections to the assets tutorial, focused on [scheduling](https://docs.dagster.io/tutorial/scheduling-your-pipeline) and [I/O](https://docs.dagster.io/tutorial/saving-your-data). While we’re close to wrapping things up for the tutorial revamp, we still have a few topics to cover - stay tuned!
- **New guide about building machine learning pipelines** - Many of our users learn best by example - [this guide](https://docs.dagster.io/guides/dagster/ml-pipeline) is one way we’re expanding our library of examples. In this guide, we walk you through building a simple machine learning pipeline using Dagster.
- **Re-organized Dagster Cloud docs** - We overhauled how the Dagster Cloud docs are organized, bringing them more in line with the UI.

**Since 1.2.7 (core) / 0.18.7 (libraries)**

New

- Long-running runs can now be terminated after going over a set runtime. See the [run termination docs](https://docs.dagster.io/deployment/run-monitoring#general-run-timeouts) to learn more.
- Adds a performance improvement to partition status caching for multi-partitioned assets containing a time dimension.
- [ui] Asset groups are now included in global search.
- [ui] Assets in the asset catalog have richer status information that matches what is displayed on the asset graph.
- [dagster-aws] New `AthenaClientResource`, `ECRPublicResource`, `RedshiftClientResource`, `S3Resource`, `S3FileManagerResource`, `ConfigurablePickledObjectS3IOManager`, `SecretsManagerResource` follow Pythonic resource system. The existing APIs remain supported.
- [dagster-datadog] New `DatadogResource` follows Pythonic resource system. The existing `datadog_resource` remains supported.
- [dagster-ge] New `GEContextResource` follows Pythonic resource system. The existing `ge_context_resource` remains supported.
- [dagster-github] New `GithubResource` follows Pythonic resource system. The existing `github_resource` remains supported.
- [dagster-msteams] New `MSTeamsResource` follows Pythonic resource system. The existing `msteams_resource` remains supported.
- [dagster-slack] New `SlackResource` follows Pythonic resource system. The existing `slack_resource` remains supported.

Bugfixes

- Fixed an issue where using `pdb.set_trace` no longer worked when running Dagster locally using `dagster dev` or `dagit`.
- Fixed a regression where passing custom metadata on `asset` or `Out` caused an error to be thrown.
- Fixed a regression where certain states of the asset graph would cause GQL errors.
- [ui] Fixed a bug where assets downstream of source assets would sometimes incorrectly display a “New data” (previously “stale”) tag for assets with materializations generated from ops (as opposed to SDA materializations).
- [ui] Fixed a bug where URLs for code locations named `pipelines` or `jobs` could lead to blank pages.
- [ui] When configuring a partition-mapped asset backfill, helpful context no longer appears nested within the “warnings” section
- [ui] For observable source assets,the asset sidebar now shows a “latest observation” instead of a “latest materialization”

Breaking Changes

- By default, resources defined on `Definitions` are now automatically bound to jobs. This will only result in a change in behavior if you a) have a job with no "io_manager" defined in its `resource_defs` and b) have supplied an `IOManager` with key "io_manager" to the `resource_defs` argument of your `Definitions`. Prior to 1.3.0, this would result in the job using the default filesystem-based `IOManager` for the key "io_manager". In 1.3.0, this will result in the "io_manager" supplied to your `Definitions` being used instead. The `BindResourcesToJobs` wrapper, introduced in 1.2 to simulate this behavior, no longer has any effect.
- [dagster-celery-k8s] The default kubernetes namespace for run pods when using the Dagster Helm chart with the `CeleryK8sRunLauncher` is now the same namespace as the Helm chart, instead of the `default` namespace. To restore the previous behavior, you can set the `celeryK8sRunLauncher.jobNamespace` field to the string `default`.
- [dagster-snowflake-pandas] Due to a longstanding issue storing Pandas Timestamps in Snowflake tables, the `SnowflakePandasIOManager` has historically converted all timestamp data to strings before storing it in Snowflake. Now, it will instead ensure that timestamp data has a timezone, and if not, attach the UTC timezone. This allows the timestamp data to be stored as timestamps in Snowflake. If you have been storing timestamp data using the `SnowflakePandasIOManager` you can set the `store_timestamps_as_strings=True` configuration to continue storing timestamps as strings. For more information, and instructions for migrating Snowflake tables to use timestamp types, see the Migration Guide.

**Changes to experimental APIs**

- Pythonic Resources and Config
- Enabled passing `RunConfig` to many APIs which previously would only accept a config dictionary.
- Enabled passing raw Python objects as resources to many APIs which previously would only accept `ResourceDefinition`.
- Added the ability to pass `execution` config when constructing a `RunConfig` object.
- Introduced more clear error messages when trying to mutate state on a Pythonic config or resource object.
- Improved direct invocation experience for assets, ops, schedules and sensors using Pythonic config and resources. Config and resources can now be passed directly as args or kwargs.
- The `minutes_late` and `previous_minutes_late` properties on the experimental `FreshnesPolicySensorContext` have been renamed to `minutes_overdue` and `previous_minutes_overdue`, respectively.

**Removal of deprecated APIs**

- [previously deprecated, 0.15.0] `metadata_entries` arguments to event constructors have been removed. While `MetadataEntry` still exists and will only be removed in 2.0, it is no longer passable to any Dagster public API — users should always pass a dictionary of metadata values instead.

Experimental

- Adds a performance improvement to the multi-asset sensor context’s `latest_materialization_records_by_key` function.

Documentation

- The Google BigQuery [tutorial](https://docs.dagster.io/integrations/bigquery/using-bigquery-with-dagster) and [reference](https://docs.dagster.io/integrations/bigquery/reference) pages have been updated to use the new `BigQueryPandasIOManager` and `BigQueryPySparkIOManager`.
- The Snowflake [tutorial](https://docs.dagster.io/integrations/snowflake/using-snowflake-with-dagster) and [reference](https://docs.dagster.io/integrations/snowflake/reference) pages have been updated to use the new `SnowflakePandasIOManager` and `SnowflakePySparkIOManager`.

Dagster Cloud

- Previously, when deprovisioning an agent, code location servers were cleaned up in serial. Now, they’re cleaned up in parallel.

New

- Resource access (via both `required_resource_keys` and Pythonic resources) are now supported in observable source assets.
- [ui] The asset graph now shows how many partitions of each asset are currently materializing, and blue bands appear on the partition health bar.
- [ui] Added a new page to monitor an asset backfill.
- [ui] Performance improvement for Runs page for runs that materialize large numbers of assets.
- [ui] Performance improvements for Run timeline and left navigation for users with large numbers of jobs or assets.
- [ui] In the run timeline, consolidate “Ad hoc materializations” rows into a single row.
- [dagster-aws] The `EcsRunLauncher` now allows you to customize volumes and mount points for the launched ECS task. See [the API docs](https://docs.dagster.io/_apidocs/libraries/dagster-aws#dagster_aws.ecs.EcsRunLauncher) for more information.
- [dagster-duckdb, dagster-duckdb-pandas, dagster-duckdb-pyspark] New `DuckDBPandasIOManager` and `DuckDBPySparkIOManager` follow Pythonic resource system. The existing `duckdb_pandas_io_manager` and `duckdb_pyspark_io_manager` remain supported.
- [dagster-gcp, dagster-gcp-pandas, dagster-gcp-pyspark] New `BigQueryPandasIOManager` and `BigQueryPySparkIOManager` follow Pythonic resource system. The existing `bigquery_pandas_io_manager` and `bigquery_pyspark_io_manager` remain supported.
- [dagster-gcp] The BigQuery resource now accepts authentication credentials as configuration. If you pass GCP authentication credentials to `gcp_crentials` , a temporary file to store the credentials will be created and the `GOOGLE_APPLICATION_CREDENTIALS` environment variable will be set to the temporary file. When the BigQuery resource is garbage collected, the environment variable will be unset and the temporary file deleted.
- [dagster-snowflake, dagster-snowflake-pandas, dagster-snowflake-pyspark] New `SnowflakePandasIOManager` and `SnowflakePySparkIOManager` follow Pythonic resource system. The existing `snowflake_pandas_io_manager` and `snowflake_pyspark_io_manager` remain supported.

Bugfixes

- Fixed an issue where `dagster dev` would periodically emit a harmless but annoying warning every few minutes about a gRPC server being shut down.
- Fixed a schedule evaluation error that occurred when schedules returned a `RunRequest(partition_key=...)` object.
- Fixed a bug that caused errors in the asset reconciliation sensor when the event log includes asset materializations with partitions that aren’t part of the asset’s `PartitionsDefinition`.
- Fixed a bug that caused errors in the asset reconciliation sensor when a partitioned asset is removed.
- Fixed an issue where `run_request_for_partition` would incorrectly raise an error for a job with a `DynamicPartitionsDefinition` that was defined with a function.
- Fixed an issue where defining a partitioned job with unpartitioned assets via `define_asset_job` would raise an error.
- Fixed a bug where source asset observations could not be launched from dagit when the asset graph contained partitioned assets.
- Fixed a bug that caused **`__ASSET_JOB has no op named ...`** errors when using automatic run retries.
- [ui] The asset partition health bar now correctly renders partial failed partitions of multi-dimensional assets in a striped red color.
- [ui] Fixed an issue where steps that were skipped due to an upstream dependency failure were incorrectly listed as “Preparing” in the right-hand column of the runs timeline.
- [ui] Fixed markdown base64 image embeds.
- [ui] Guard against localStorage quota errors when storing launchpad config tabs.
- [dagster-aws] Fixed an issue where the `EcsRunLauncher` would fail to launch runs if the `use_current_ecs_task_config` field was set to `False` but no `task_definition` field was set.
- [dagster-k8s] Fixed an issue introduced in 1.2.6 where older versions of the kubernetes Python package were unable to import the package.

Community Contributions

- The `EcsRunLauncher` now allows you to set a capacity provider strategy and customize the ephemeral storage used for launched ECS tasks. See [the docs](https://docs.dagster.io/deployment/guides/aws#customizing-the-launched-runs-task) for details. Thanks [AranVinkItility](https://github.com/AranVinkItility)!
- Fixed an issue where freshness policies were not being correctly applied to assets with key prefixes defined via `AssetsDefinition.from_op`. Thanks tghanken for the fix!
- Added the `minimum_interval_seconds` parameter to enable customizing the evaluation interval on the slack run failure sensor, thanks ldnicolasmay!
- Fixed a docs example and updated references, thanks NicolasPA!

Experimental

- The `Resource` annotation for Pythonic resource inputs has been renamed to `ResourceParam` in preparation for the release of the feature in 1.3.
- When invoking ops and assets that request resources via parameters directly, resources can now be specified as arguments.
- Improved various error messages related to Pythonic config and resources.
- If the Resources Dagit feature flag is enabled, they will now show up in the overview page and search.

Documentation

- Learn how to [limit concurrency in your data pipelines](https://docs.dagster.io/guides/limiting-concurrency-in-data-pipelines) with our new guide!
- Need some help managing a run queue? Check out the new [customizing run queue priority guide](https://docs.dagster.io/guides/customizing-run-queue-priority).
- New tutorial section that adds I/O managers to the tutorial project.

Bugfixes

- Fixed a GraphQL resolution error which occurred when retrieving metadata for step failures in the event log.

New

- `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.
- Context methods to access time window partition information now work for `MultiPartitionsDefinition`s with a time dimension.
- Improved the performance of the asset reconciliation sensor when a non-partitioned asset depends on a partitioned asset.
- `load_assets_from_package_module` and similar methods now accept a `freshness_policy`, which will be applied to all loaded assets.
- When the asset reconciliation sensor is scheduling based on freshness policies, and there are observable source assets, the observed versions now inform the data time of the assets.
- `build_sensor_context` and `build_multi_asset_sensor_context` can now take a `Definitions` object in place of a `RepositoryDefinition`
- [UI] Performance improvement for loading asset partition statuses.
- [dagster-aws] `s3_resource` now accepts `use_ssl` and `verify` configurations.

Bugfixes

- Fixed a bug that caused an error to be raised when passing a multi-asset into the `selection` argument on `define_asset_job`.
- Fixes a graphQL error that displays on Dagit load when an asset’s partitions definition is change from a single-dimensional partitions definition to a `MultiPartitionsDefinition`.
- Fixed a bug that caused backfills to fail when spanning assets that live in different code locations.
- Fixed an error that displays when a code location with a `MultiPartitionsMapping` (experimental) is loaded.
- Fixed a bug that caused errors with invalid `TimeWindowPartitionMapping`s to not be bubbled up to the UI.
- Fixed an issue where the scheduler would sometimes incorrectly handle spring Daylight Savings Time transitions for schedules running at 2AM in a timezone other than UTC.
- Fixed an issue introduced in the 1.2.4 release where running `pdb` stopped working when using dagster dev.
- Fixed an issue where it is was possible to create `AssetMaterialization` objects with a null `AssetKey`.
- Previously, if you had a `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.
- The asset reconciliation sensor now no longer fails when the event log contains materializations that contain partitions that aren’t contained in the asset’s `PartitionsDefinition`. These partitions are now ignored.
- Fixed a regression that prevented materializing dynamically partitioned assets from the UI (thanks [planvin](https://github.com/planvin)!)
- [UI] On the asset graph, the asset health displayed in the sidebar for the selected asset updates as materializations and failures occur.
- [UI] The asset partitions page has been adjusted to make materialization and observation event metadata more clear.
- [UI] Large table schema metadata entries now display within a modal rather than taking up considerable space on the page.
- [UI] Launching a backfill of a partitioned asset with unpartitioned assets immediately upstream no longer shows the “missing partitions” warning.
- [dagster-airflow] fixed a bug in the `PersistentAirflowDatabase` where versions of airflow from 2.0.0 till 2.3.0 would not use the correct connection environment variable name.
- [dagster-census] fixed a bug with the `poll_sync_run` function of`dagster-census` that prevented polling from working correctly (thanks [ldincolasmay](https://github.com/ldnicolasmay)!)

Deprecations

- The `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=...)`.

Documentation

- Added a missing link to next tutorial section (Thanks Mike Kutzma!)

New

- Further performance improvements to the asset reconciliation sensor.
- Performance improvements to asset backfills with large numbers of partitions.
- New `AssetsDefinition.to_source_assets` to method convert a set of assets to `SourceAsset` objects.
- (experimental) Added partition mapping that defines dependency relationships between different `MultiPartitionsDefinitions`.
- [dagster-mlflow] Removed the `mlflow` pin from the `dagster-mlflow` package.
- [ui] Syntax highlighting now supported in rendered markdown code blocks (from metadata).

Bugfixes

- 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](https://docs.dagster.io/deployment/run-monitoring#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:

python
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](https://github.com/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.

Deprecations

- The `environment_vars` argument to `ScheduleDefinition` is deprecated (the argument is currently non-functional; environment variables no longer need to be whitelisted for schedules)

Community Contributions

- Typos fixed in [CHANGES.md](http://CHANGES.md) (thanks [fridiculous](https://github.com/fridiculous))
- Links to telemetry docs fixed (thanks [Abbe98](https://github.com/Abbe98))
- `--path-prefix` can now be supplied via Helm chart (thanks [mpicard](https://github.com/mpicard))

Documentation

- New machine learning pipeline with Dagster guide
- New example of multi-asset conditional materialization
- New tutorial section about scheduling
- New images on the Dagster README