Modes & Resources¶

Modes¶

class dagster.ModeDefinition(name=None, resource_defs=None, logger_defs=None, executor_defs=None, description=None, intermediate_storage_defs=None)[source]¶

Define a mode in which a pipeline can operate.

A mode provides pipelines with a set of resource implementations, loggers, system storages, and executors.

Parameters

• name (Optional[str]) – The name of the mode. Must be unique within the PipelineDefinition to which the mode is attached. (default: “default”).

• resource_defs (Optional[Dict[str, ResourceDefinition]]) – A dictionary of string resource keys to their implementations. Individual solids may require resources to be present by these keys.

• logger_defs (Optional[Dict[str, LoggerDefinition]]) – A dictionary of string logger identifiers to their implementations.

• executor_defs (Optional[List[ExecutorDefinition]]) – The set of executors available when executing in this mode. By default, this will be the ‘in_process’ and ‘multiprocess’ executors (default_executors).

• description (Optional[str]) – A human-readable description of the mode.

• intermediate_storage_defs (Optional[List[IntermediateStorageDefinition]]) – The set of intermediate storage options available when executing in this mode. By default, this will be the ‘in_memory’ and ‘filesystem’ system storages.

Resources¶

@dagster.resource(config_schema=None, description=None, required_resource_keys=None, version=None)[source]¶

Define a resource.

The decorated function should accept an InitResourceContext and return an instance of the resource. This function will become the resource_fn of an underlying ResourceDefinition.

If the decorated function yields once rather than returning (in the manner of functions decorable with @contextlib.contextmanager) then the body of the function after the yield will be run after execution resolves, allowing users to write their own teardown/cleanup logic.

Parameters

• config_schema (Optional[ConfigSchema]) – The schema for the config. Configuration data available in init_context.resource_config.

• description (Optional[str]) – A human-readable description of the resource.

• version (Optional[str]) – (Experimental) The version of a resource function. Two wrapped resource functions should only have the same version if they produce the same resource definition when provided with the same inputs.

• required_resource_keys (Optional[Set[str]]) – Keys for the resources required by this resource.

class dagster.ResourceDefinition(resource_fn=None, config_schema=None, description=None, required_resource_keys=None, version=None)[source]¶

Core class for defining resources.

Resources are scoped ways to make external resources (like database connections) available to solids during pipeline execution and to clean up after execution resolves.

If resource_fn yields once rather than returning (in the manner of functions decorable with @contextlib.contextmanager) then the body of the function after the yield will be run after execution resolves, allowing users to write their own teardown/cleanup logic.

Depending on your executor, resources may be instantiated and cleaned up more than once in a pipeline execution.

Parameters

• resource_fn (Callable[[InitResourceContext], Any]) – User-provided function to instantiate the resource, which will be made available to solid executions keyed on the context.resources object.

• config_schema (Optional[ConfigSchema]) – The schema for the config. Configuration data available in init_context.resource_config.

• description (Optional[str]) – A human-readable description of the resource.

• required_resource_keys – (Optional[Set[str]]) Keys for the resources required by this resource. A DagsterInvariantViolationError will be raised during initialization if dependencies are cyclic.

• version (Optional[str]) – (Experimental) The version of the resource’s definition fn. Two wrapped resource functions should only have the same version if they produce the same resource definition when provided with the same inputs.

configured(config_or_config_fn: Any, config_schema: Optional[Dict[str, Any]] = None, description: Optional[str] = None)¶

Wraps this object in an object of the same type that provides configuration to the inner object.

Parameters

• config_or_config_fn (Union[Any, Callable[[Any], Any]]) – Either (1) Run configuration that fully satisfies this object’s config schema or (2) A function that accepts run configuration and returns run configuration that fully satisfies this object’s config schema. In the latter case, config_schema must be specified. When passing a function, it’s easiest to use configured().

• config_schema (ConfigSchema) – If config_or_config_fn is a function, the config schema that its input must satisfy.

• description (Optional[str]) – Description of the new definition. If not specified, inherits the description of the definition being configured.

Returns (ConfigurableDefinition): A configured version of this object.

static hardcoded_resource(value, description=None)[source]¶

A helper function that creates a ResourceDefinition with a hardcoded object.

Parameters

• value (Any) – A hardcoded object which helps mock the resource.

• description ([Optional[str]]) – The description of the resource. Defaults to None.

Returns

A hardcoded resource.

Return type

[ResourceDefinition]

static mock_resource(description=None)[source]¶

A helper function that creates a ResourceDefinition which wraps a mock.MagicMock.

Parameters

description ([Optional[str]]) – The description of the resource. Defaults to None.

Returns

A resource that creates the magic methods automatically and helps

you mock existing resources.

Return type

[ResourceDefinition]

static none_resource(description=None)[source]¶

A helper function that returns a none resource.

Parameters

description ([Optional[str]]) – The description of the resource. Defaults to None.

Returns

A resource that does nothing.

Return type

[ResourceDefinition]

class dagster.InitResourceContext(resource_config: Any, resource_def: dagster.core.definitions.resource.ResourceDefinition, pipeline_run: Optional[dagster.core.storage.pipeline_run.PipelineRun] = None, log_manager: Optional[dagster.core.log_manager.DagsterLogManager] = None, resource_instance_dict: Optional[Dict[str, Any]] = None, required_resource_keys: Optional[Set[str]] = None, instance: Optional[dagster.core.instance.DagsterInstance] = None, pipeline_def_for_backwards_compat: Optional[dagster.core.definitions.pipeline.PipelineDefinition] = None)[source]¶

Resource-specific initialization context.

resource_config¶

The configuration data provided by the environment config. The schema for this data is defined by the config_field argument to ResourceDefinition.

Type

Any

resource_def¶

The definition of the resource currently being constructed.

Type

ResourceDefinition

log_manager¶

The log manager for this run of the pipeline

Type

DagsterLogManager

resources¶

The resources that are available to the resource that we are initalizing.

Type

ScopedResources

pipeline_run¶

The pipeline run to use. When initializing resources outside of execution context, this will be None.

Type

Optional[PipelineRun]

run_id¶

The id for this run of the pipeline. When initializing resources outside of execution context, this will be None.

Type

Optional[str]