The following classes are used as part of the new Pythonic resources system.
Base class for Dagster resources that utilize structured config.
This class is a subclass of both ResourceDefinition and Config.
Example definition:
class WriterResource(ConfigurableResource):
prefix: str
def output(self, text: str) -> None:
print(f"{self.prefix}{text}")
Example usage:
@asset
def asset_that_uses_writer(writer: WriterResource):
writer.output("text")
defs = Definitions(
assets=[asset_that_uses_writer],
resources={"writer": WriterResource(prefix="a_prefix")},
)
You can optionally use this class to model configuration only and vend an object of a different type for use at runtime. This is useful for those who wish to have a separate object that manages configuration and a separate object at runtime. Or where you want to directly use a third-party class that you do not control.
To do this you override the create_resource methods to return a different object.
class WriterResource(ConfigurableResource):
str: prefix
def create_resource(self, context: InitResourceContext) -> Writer:
# Writer is pre-existing class defined else
return Writer(self.prefix)
Example usage:
@asset
def use_preexisting_writer_as_resource(writer: ResourceParam[Writer]):
writer.output("text")
defs = Definitions(
assets=[use_preexisting_writer_as_resource],
resources={"writer": WriterResource(prefix="a_prefix")},
)
Core class for defining resources.
Resources are scoped ways to make external resources (like database connections) available to ops and assets during job 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 job execution.
resource_fn (Callable[[InitResourceContext], Any]) – User-provided function to instantiate
the resource, which will be made available to executions keyed on the
context.resources object.
config_schema (Optional[ConfigSchema) – The schema for the config. If set, Dagster will check that config provided for the resource matches this schema and fail if it does not. If not set, Dagster will accept any config provided for the resource.
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 ) (This parameter may break in future versions, even between dot releases.) (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.
A helper function that creates a ResourceDefinition with a hardcoded object.
value (Any) – The value that will be accessible via context.resources.resource_name.
description ([Optional[str]]) – The description of the resource. Defaults to None.
A hardcoded resource.
A helper function that creates a ResourceDefinition which wraps a mock.MagicMock.
description ([Optional[str]]) – The description of the resource. Defaults to None.
you mock existing resources.
A helper function that returns a none resource.
description ([Optional[str]]) – The description of the resource. Defaults to None.
A resource that does nothing.
Creates a ResourceDefinition which takes in a single string as configuration
and returns this configured string to any ops or assets which depend on it.
description ([Optional[str]]) – The description of the string resource. Defaults to None.
returns that string.
A human-readable description of the resource.
A set of the resource keys that this resource depends on. These keys will be made available to the resource’s init context during execution, and the resource will not be instantiated until all required resources are available.
A string which can be used to identify a particular code version of a resource definition.
The context object available as the argument to the initialization function of a dagster.ResourceDefinition.
Users should not instantiate this object directly. To construct an InitResourceContext for testing purposes, use dagster.build_init_resource_context().
Example
from dagster import resource, InitResourceContext
@resource
def the_resource(init_context: InitResourceContext):
init_context.log.info("Hello, world!")
The Dagster instance configured for the current execution context.
The Dagster log manager configured for the current execution context.
The log manager for this run of the job.
The configuration data provided by the run config. The schema
for this data is defined by the config_field argument to
ResourceDefinition.
The definition of the resource currently being constructed.
The resources that are available to the resource that we are initializing.
The id for this run of the job or pipeline. When initializing resources outside of execution context, this will be None.
A helper function that creates a ResourceDefinition to take in user-defined values.
This is useful for sharing values between ops.
**kwargs – Arbitrary keyword arguments that will be passed to the config schema of the returned resource definition. If not set, Dagster will accept any config provided for the resource.
For example:
@op(required_resource_keys={"globals"})
def my_op(context):
print(context.resources.globals["my_str_var"])
@job(resource_defs={"globals": make_values_resource(my_str_var=str, my_int_var=int)})
def my_job():
my_op()
A resource that passes in user-defined values.
Builds resource initialization context from provided parameters.
build_init_resource_context can be used as either a function or context manager. If there is a
provided resource to build_init_resource_context that is a context manager, then it must be
used as a context manager. This function can be used to provide the context argument to the
invocation of a resource.
resources (Optional[Dict[str, Any]]) – The resources to provide to the context. These can be either values or resource definitions.
config (Optional[Any]) – The resource config to provide to the context.
instance (Optional[DagsterInstance]) – The dagster instance configured for the context. Defaults to DagsterInstance.ephemeral().
Examples
context = build_init_resource_context()
resource_to_init(context)
with build_init_resource_context(
resources={"foo": context_manager_resource}
) as context:
resource_to_init(context)
Context manager that yields resources using provided resource definitions and run config.
This API allows for using resources in an independent context. Resources will be initialized with the provided run config, and optionally, dagster_run. The resulting resources will be yielded on a dictionary keyed identically to that provided for resource_defs. Upon exiting the context, resources will also be torn down safely.
resources (Mapping[str, Any]) – Resource instances or definitions to build. All required resource dependencies to a given resource must be contained within this dictionary, or the resource build will fail.
instance (Optional[DagsterInstance]) – The dagster instance configured to instantiate resources on.
resource_config (Optional[Mapping[str, Any]]) – A dict representing the config to be provided to each resource during initialization and teardown.
dagster_run (Optional[PipelineRun]) – The pipeline run to provide during resource initialization and teardown. If the provided resources require either the dagster_run or run_id attributes of the provided context during resource initialization and/or teardown, this must be provided, or initialization will fail.
log_manager (Optional[DagsterLogManager]) – Log Manager to use during resource initialization. Defaults to system log manager.
Examples
from dagster import resource, build_resources
@resource
def the_resource():
return "foo"
with build_resources(resources={"from_def": the_resource, "from_val": "bar"}) as resources:
assert resources.from_def == "foo"
assert resources.from_val == "bar"
Adds dagster resources to copies of resource-requiring dagster definitions.
An error will be thrown if any provided definitions have a conflicting resource definition provided for a key provided to resource_defs. Resource config can be provided, with keys in the config dictionary corresponding to the keys for each resource definition. If any definition has unsatisfied resource keys after applying with_resources, an error will be thrown.
definitions (Iterable[ResourceAddable]) – Dagster definitions to provide resources to.
resource_defs (Mapping[str, object]) – Mapping of resource keys to objects to satisfy resource requirements of provided dagster definitions.
resource_config_by_key (Optional[Mapping[str, Any]]) – Specifies config for provided resources. The key in this dictionary corresponds to configuring the same key in the resource_defs dictionary.
Examples
from dagster import asset, resource, with_resources
@resource(config_schema={"bar": str})
def foo_resource():
...
@asset(required_resource_keys={"foo"})
def asset1(context):
foo = context.resources.foo
...
@asset(required_resource_keys={"foo"})
def asset2(context):
foo = context.resources.foo
...
asset1_with_foo, asset2_with_foo = with_resources(
[asset1, asset2],
resource_defs={
"foo": foo_resource
},
resource_config_by_key={
"foo": {
"config": {"bar": ...}
}
}
)
Class used to represent an environment variable in the Dagster config system.
This class is intended to be used to populate config fields or resources. The environment variable will be resolved to a string value when the config is loaded.
To access the value of the environment variable, use the get_value method.
The following classes are used as part of the legacy resource system.
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.
config_schema (Optional[ConfigSchema]) – The schema for the config. Configuration data available in init_context.resource_config. If not set, Dagster will accept any config provided.
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.