Dagster

Latest version: v1.9.5

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1.0.13

Not secure
New

- `AssetMaterialization` now has a `metadata` property, which allows accessing the materialization’s metadata as a dictionary.
- `DagsterInstance` now has a `get_latest_materialization_event` method, which allows fetching the most recent materialization event for a particular asset key.
- `RepositoryDefinition.load_asset_value` and `AssetValueLoader.load_asset_value` now work with IO managers whose `load_input` implementation accesses the `op_def` and `name` attributes on the `InputContext`.
- `RepositoryDefinition.load_asset_value` and `AssetValueLoader.load_asset_value` now respect the `DAGSTER_HOME` environment variable.
- `InMemoryIOManager`, the `IOManager` that backs `mem_io_manager`, has been added to the public API.
- The `multi_asset_sensor` (experimental) now supports marking individual partitioned materializations as “consumed”. Unconsumed materializations will appear in future calls to partitioned context methods.
- The `build_multi_asset_sensor_context` testing method (experimental) now contains a flag to set the cursor to the newest events in the Dagster instance.
- `TableSchema` now has a static constructor that enables building it from a dictionary of column names to column types.
- Added a new CLI command `dagster run migrate-repository` which lets you migrate the run history for a given job from one repository to another. This is useful to preserve run history for a job when you have renamed a repository, for example.
- [dagit] The run timeline view now shows jobs grouped by repository, with each repository section collapsible. This feature was previously gated by a feature flag, and is now turned on for everyone.
- [dagster-airbyte] Added option to specify custom request params to the Airbyte resource, which can be used for auth purposes.
- [dagster-airbyte] When loading Airbyte assets from an instance or from YAML, a filter function can be specified to ignore certain connections.
- [dagster-airflow] `DagsterCloudOperator` and `DagsterOperator` now support Airflow 2. Previously, installing the library on Airflow 2 would break due to an import error.
- [dagster-duckdb] A new integration with DuckDB allows you to store op outputs and assets in an in-process database.

Bugfixes

- Previously, if retries were exceeded when running with `execute_in_process`, no error would be raised. Now, a `DagsterMaxRetriesExceededError` will be launched off.
- [dagster-airbyte] Fixed generating assets for Airbyte normalization tables corresponding with nested union types.
- [dagster-dbt] When running assets with `load_assets_from_...(..., use_build=True)`, AssetObservation events would be emitted for each test. These events would have metadata fields which shared names with the fields added to the AssetMaterialization events, causing confusing historical graphs for fields such as Compilation Time. This has been fixed.
- [dagster-dbt] The name for the underlying op for `load_assets_from_...` was generated in a way which was non-deterministic for dbt projects which pulled in external packages, leading to errors when executing across multiple processes. This has been fixed.

Dependency changes

- [dagster-dbt] The package no longer depends on pandas and dagster-pandas.

Community Contributions

- [dagster-airbyte] Added possibility to change request timeout value when calling Airbyte. Thanks FransDel!
- [dagster-airflow] Fixed an import error in `dagster_airflow.hooks`. Thanks bollwyvl!
- [dagster-gcp] Unpin Google dependencies. `dagster-gcp` now supports google-api-python-client 2.x. Thanks amarrella!
- [dagstermill] Fixed an issue where DagsterTranslator was missing an argument required by newer versions of papermill. Thanks tizz98!

Documentation

- Added an example, underneath examples/assets_smoke_test, that shows how to write a smoke test that feeds empty data to all the transformations in a data pipeline.
- Added documentation for `build_asset_reconciliation_sensor`.
- Added documentation for monitoring partitioned materializations using the `multi_asset_sensor` and kicking off subsequent partitioned runs.
- [dagster-cloud] Added documentation for running the Dagster Cloud Docker agent with Docker credential helpers.
- [dagster-dbt] The class methods of the dbt_cli_resource are now visible in the API docs for the dagster-dbt library.
- [dagster-dbt] Added a step-by-step tutorial for using dbt models with Dagster software-defined assets

1.0.12

Not secure
New

- The `multi_asset_sensor` (experimental) now accepts an `AssetSelection` of assets to monitor. There are also minor API updates for the multi-asset sensor context.
- `AssetValueLoader`, the type returned by `RepositoryDefinition.get_asset_value_loader` is now part of Dagster’s public API.
- `RepositoryDefinition.load_asset_value` and `AssetValueLoader.load_asset_value` now support a `partition_key` argument.
- `RepositoryDefinition.load_asset_value` and `AssetValueLoader.load_asset_value` now work with I/O managers that invoke `context.upstream_output.asset_key`.
- When running Dagster locally, the default amount of time that the system waits when importing user code has been increased from 60 seconds to 180 seconds, to avoid false positives when importing code with heavy dependencies or large numbers of assets. This timeout can be configured in `dagster.yaml` as follows:

yaml
code_servers:
local_startup_timeout: 120


- [dagit] The “Status” section has been renamed to “Deployment”, to better reflect that this section of the app shows deployment-wide information.
- [dagit] When viewing the compute logs for a run and choosing a step to filter on, there is now a search input to make it easier to find the step you’re looking for.
- [dagster-aws] The EcsRunLauncher can now launch runs in ECS clusters using both Fargate and EC2 capacity providers. See the [Deploying to ECS docs](http://docs.dagster.io/deployment/guides/aws#customizing-the-launched-runs-task) for more information.
- [dagster-airbyte] Added the `load_assets_from_airbyte_instance` function which automatically generates asset definitions from an Airbyte instance. For more details, see the [new Airbyte integration guide](https://docs.dagster.io/integrations/airbyte).
- [dagster-airflow] Added the `DagsterCloudOperator` and `DagsterOperator` , which are airflow operators that enable orchestrating dagster jobs, running on either cloud or OSS dagit instances, from Apache Airflow.

Bugfixes

- Fixed a bug where if resource initialization failed for a dynamic op, causing other dynamic steps to be skipped, those skipped dynamic steps would be ignored when retrying from failure.
- Previously, some invocations within the Dagster framework would result in warnings about deprecated metadata APIs. Now, users should only see warnings if their code uses deprecated metadata APIs.
- How the daemon process manages its understanding of user code artifacts has been reworked to improve memory consumption.
- [dagit] The partition selection UI in the Asset Materialization modal now allows for mouse selection and matches the UI used for partitioned op jobs.
- [dagit] Sidebars in Dagit shrink more gracefully on small screens where headers and labels need to be truncated.
- [dagit] Improved performance for loading runs with >10,000 logs
- [dagster-airbyte] Previously, the `port` configuration in the `airbyte_resource` was marked as not required, but if it was not supplied, an error would occur. It is now marked as required.
- [dagster-dbt] A change made to the manifest.json schema in dbt 1.3 would result in an error when using `load_assets_from_dbt_project` or `load_assets_from_manifest_json`. This has been fixed.
- [dagster-postgres] connections that fail due to **`sqlalchemy.exc.TimeoutError`** now retry

Breaking Changes

- [dagster-aws] The `redshift_resource` no longer accepts a `schema` configuration parameter. Previously, this parameter would error whenever used, because Redshift connections do not support this parameter.

Community Contributions

- We now reference the correct method in the "loading asset values outside of Dagster runs" example (thank you Peter A. I. Forsyth!)
- We now reference the correct test directory in the “Create a New Project” documentation (thank you Peter A. I. Forsyth!)
- [dagster-pyspark] dagster-pyspark now contains a `LazyPysparkResource` that only initializes a spark session once it’s accessed (thank you zyd14!)

Experimental

- The new `build_asset_reconciliation_sensor` function accepts a set of software-defined assets and returns a sensor that automatically materializes those assets after their parents are materialized.
- [dagit] A new "groups-only" asset graph feature flag allows you to zoom way out on the global asset graph, collapsing asset groups into smaller nodes you can double-click to expand.

1.0.11

Not secure
New

- `RepositoryDefinition` now exposes a `load_asset_value` method, which accepts an asset key and invokes the asset’s I/O manager’s `load_input` function to load the asset as a Python object. This can be used in notebooks to do exploratory data analysis on assets.
- Methods to fetch a list of partition keys from an input/output `PartitionKeyRange` now exist on the op execution context and input/output context.
- [dagit] On the Instance Overview page, batched runs in the run timeline view will now proportionally reflect the status of the runs in the batch instead of reducing all run statuses to a single color.
- [dagster-dbt] [dagster-snowflake] You can now use the Snowflake IO manager with dbt assets, which allows them to be loaded from Snowflake into Pandas DataFrames in downstream steps.
- The dagster package’s pin of the alembic package is now much less restrictive.

Bugfixes

- The sensor daemon when using threads will no longer evaluate the next tick for a sensor if the previous one is still in flight. This resolves a memory leak in the daemon process.
- The scheduler will no longer remove tracked state for automatically running schedules when they are absent due to a workspace load error.
- The way user code severs manage repository definitions has been changed to more efficiently serve requests.
- The `multi_asset` decorator now respects its `config_schema` parameter.
- [dagit] Config supplied to `define_asset_job` is now prefilled in the modal that pops up when you click the Materialize button on an asset job page, so you can quickly adjust the defaults.
- [dagster-dbt] Previously, `DagsterDbtCliError`s produced from the dagster-dbt library would contain large serialized objects representing the raw unparsed logs from the relevant cli command. Now, these messages will contain only the parsed version of these messages.
- Fixed an issue where the `deploy_ecs` example didn’t work when built and deployed on an M1 Mac.

Community Contributions

- [dagster-fivetran] The `resync_parameters` configuration on the `fivetran_resync_op` is now optional, enabling triggering historical re\*syncs for connectors. Thanks dwallace0723!

Documentation

- Improved API documentation for the Snowflake resource.

1.0.10

Not secure
New

- Run status sensors can now monitor all runs in a Dagster Instance, rather than just runs from jobs within a single repository. You can enable this behavior by setting `monitor_all_repositories=True` in the run status sensor decorator.
- The `run_key` argument on `RunRequest` and `run_request_for_partition` is now optional.
- [dagster-databricks] A new “verbose_logs” config option on the databricks_pyspark_step_launcher makes it possible to silence non-critical logs from your external steps, which can be helpful for long-running, or highly parallel operations (thanks zyd14!)
- [dagit] It is now possible to delete a run in Dagit directly from the run page. The option is available in the dropdown menu on the top right of the page.
- [dagit] The run timeline on the Workspace Overview page in Dagit now includes ad hoc asset materialization runs.

Bugfixes

- Fixed a set of bugs in `multi_asset_sensor` where the cursor would fail to update, and materializations would be returned out of order for `latest_materialization_records_by_partition`.
- Fixed a bug that caused failures in runs with time-partitioned asset dependencies when the PartitionsDefinition had an offset that wasn’t included in the date format. E.g. a daily-partitioned asset with an hour offset, whose date format was `%Y-%m-%d`.
- An issue causing code loaded by file path to import repeatedly has been resolved.
- To align with best practices, singleton comparisons throughout the codebase have been converted from (e.g.) `foo == None` to `foo is None` (thanks chrisRedwine!).
- [dagit] In backfill jobs, the “Partition Set” column would sometimes show an internal `__ASSET_JOB` name, rather than a comprehensible set of asset keys. This has been fixed.
- [dagit] It is now possible to collapse all Asset Observation rows on the AssetDetails page.
- [dagster-dbt] Fixed issue that would cause an error when loading assets from dbt projects in which a source had a “\*” character in its name (e.g. BigQuery sharded tables)
- [dagster-k8s] Fixed an issue where the `k8s_job_op` would sometimes fail if the Kubernetes job that it creates takes a long time to create a pod.
- Fixed an issue where links to the compute logs for a run would sometimes fail to load.
- [dagster-k8s] The `k8s_job_executor` now uses environment variables in place of CLI arguments to avoid limits on argument size with large dynamic jobs.

Documentation

- Docs added to explain subsetting graph-backed assets. You can use this feature following the documentation [here](https://docs.dagster.io/concepts/assets/graph-backed-assets).
- UI updated to reflect separate version schemes for mature core Dagster packages and less mature integration libraries

1.0.9

Not secure
New

- The `multi_asset_sensor` (experimental) now has improved capabilities to monitor asset partitions via a `latest_materialization_records_by_partition` method.
- Performance improvements for the Partitions page in Dagit.

Bugfixes

- Fixed a bug that caused the op_config argument of `dagstermill.get_context` to be ignored
- Fixed a bug that caused errors when loading the asset details page for assets with time window partitions definitions
- Fixed a bug where assets sometimes didn’t appear in the Asset Catalog while in Folder view.
- [dagit] Opening the asset lineage tab no longer scrolls the page header off screen in some scenarios
- [dagit] The asset lineage tab no longer attempts to materialize source assets included in the upstream / downstream views.
- [dagit] The Instance page Run Timeline no longer commingles runs with the same job name in different repositories
- [dagit] Emitting materializations with JSON metadata that cannot be parsed as JSON no longer crashes the run details page
- [dagit] Viewing the assets related to a run no longer shows the same assets multiple times in some scenarios
- [dagster-k8s] Fixed a bug with timeouts causing errors in `k8s_job_op`
- [dagster-docker] Fixed a bug with Op retries causing errors with the `docker_executor`

Community Contributions

- [dagster-aws] Thanks Vivanov98 for adding the `list_objects` method to `S3FakeSession`!

Experimental

- [dagster-airbyte] Added an experimental function to automatically generate Airbyte assets from project YAML files. For more information, see the [dagster-airbyte docs](https://docs.dagster.io/_apidocs/libraries/dagster-airbyte).
- [dagster-airbyte] Added the forward_logs option to `AirbyteResource`, allowing users to disble forwarding of Airbyte logs to the compute log, which can be expensive for long-running syncs.
- [dagster-airbyte] Added the ability to generate Airbyte assets for [basic normalization](https://docs.airbyte.com/understanding-airbyte/basic-normalization/#nesting) tables generated as part of a sync.

Documentation

- [dagster-dbt] Added a new guide focused on the dbt Cloud integration.
- Fixed a bug that was hiding display of some public methods in the API docs.
- Added documentation for [managing full deployments in Dagster Cloud](https://docs.dagster.io/dagster-cloud/managing-deployments/managing-deployments), including a [reference for deployment configuration options](https://docs.dagster.io/dagster-cloud/developing-testing/deployment-settings-reference).

1.0.8

Not secure
New

- With the new `cron_schedule` argument to `TimeWindowPartitionsDefinition`, you can now supply arbitrary cron expressions to define time window-based partition sets.
- Graph-backed assets can now be subsetted for execution via `AssetsDefinition.from_graph(my_graph, can_subset=True)`.
- `RunsFilter` is now exported in the public API.
- [dagster-k8s] The `dagster-user-deployments.deployments[].schedulerName` Helm value for specifying custom Kubernetes schedulers will now also apply to run and step workers launched for the given user deployment. Previously it would only apply to the grpc server.

Bugfixes

- In some situations, default asset config was ignored when a subset of assets were selected for execution. This has been fixed.
- Added a pin to `grpcio` in dagster to address an issue with the recent 0.48.1 grpcio release that was sometimes causing Dagster code servers to hang.
- Fixed an issue where the “Latest run” column on the Instance Status page sometimes displayed an older run instead of the most recent run.

Community Contributions

- In addition to a single cron string, `cron_schedule` now also accepts a sequence of cron strings. If a sequence is provided, the schedule will run for the union of all execution times for the provided cron strings, e.g., `['45 23 * * 6', '30 9 * * 0]` for a schedule that runs at 11:45 PM every Saturday and 9:30 AM every Sunday. Thanks erinov1!
- Added an optional boolean config `install_default_libraries` to `databricks_pyspark_step_launcher` . It allows to run Databricks jobs without installing the default Dagster libraries .Thanks nvinhphuc!

Experimental

- [dagster-k8s] Added additional configuration fields (`container_config`, `pod_template_spec_metadata`, `pod_spec_config`, `job_metadata`, and `job_spec_config`) to the experimental `k8s_job_op` that can be used to add additional configuration to the Kubernetes pod that is launched within the op.

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