flytekit.extras.sqlite3.task.SQLite3Task#
- class flytekit.extras.sqlite3.task.SQLite3Task(*args, **kwargs)[source]#
Run client side SQLite3 queries that optionally return a FlyteSchema object.
Note
This is a pre-built container task. That is, your user container will not be used at task execution time. Instead the image defined in this task definition will be used instead.
sql_task = SQLite3Task( "test", query_template="select TrackId, Name from tracks limit {{.inputs.limit}}", inputs=kwtypes(limit=int), output_schema_type=FlyteSchema[kwtypes(TrackId=int, Name=str)], task_config=SQLite3Config( uri=EXAMPLE_DB, compressed=True, ), )
See the integrations guide for additional usage examples and the base class
flytekit.extend.PythonCustomizedContainerTask
as well.- Parameters
name – unique name for the task, usually the function’s module and name.
task_config – Configuration object for Task. Should be a unique type for that specific Task
container_image – This is the external container image the task should run at platform-run-time.
executor – This is an executor which will actually provide the business logic.
task_resolver – Custom resolver - if you don’t make one, use the default task template resolver.
task_type – String task type to be associated with this Task.
requests – custom resource request settings.
limits – custom resource limit settings.
environment – Environment variables you want the task to have when run.
secret_requests (List[Secret]) –
Secrets that are requested by this container execution. These secrets will be mounted based on the configuration in the Secret and available through the SecretManager using the name of the secret as the group Ideally the secret keys should also be semi-descriptive. The key values will be available from runtime, if the backend is configured to provide secrets and if secrets are available in the configured secrets store. Possible options for secret stores are
Methods
- compile(ctx, *args, **kwargs)#
Generates a node that encapsulates this task in a workflow definition.
- Parameters
- Return type
Optional[Union[Tuple[flytekit.core.promise.Promise], flytekit.core.promise.Promise, flytekit.core.promise.VoidPromise]]
- construct_node_metadata()#
Used when constructing the node that encapsulates this task as part of a broader workflow definition.
- Return type
flytekit.models.core.workflow.NodeMetadata
- dispatch_execute(ctx, input_literal_map)#
This function is largely similar to the base PythonTask, with the exception that we have to infer the Python interface before executing. Also, we refer to
self.task_template
rather than justself
similar to task classes that derive from the basePythonTask
.- Parameters
input_literal_map (flytekit.models.literals.LiteralMap) –
- Return type
Union[flytekit.models.literals.LiteralMap, flytekit.models.dynamic_job.DynamicJobSpec]
- get_command(settings)#
- Parameters
settings (flytekit.configuration.SerializationSettings) –
- Return type
- get_config(settings)#
Returns the task config as a serializable dictionary. This task config consists of metadata about the custom defined for this task.
- Parameters
settings (flytekit.configuration.SerializationSettings) –
- Return type
- get_container(settings)#
Returns the container definition (if any) that is used to run the task on hosted Flyte.
- Parameters
settings (flytekit.configuration.SerializationSettings) –
- Return type
flytekit.models.task.Container
- get_custom(settings)[source]#
Return additional plugin-specific custom data (if any) as a serializable dictionary.
- Parameters
settings (flytekit.configuration.SerializationSettings) –
- Return type
- get_extended_resources(settings)#
Returns the extended resources to allocate to the task on hosted Flyte.
- Parameters
settings (flytekit.configuration.SerializationSettings) –
- Return type
Optional[flyteidl.core.tasks_pb2.ExtendedResources]
- get_input_types()#
Returns the names and python types as a dictionary for the inputs of this task.
- get_k8s_pod(settings)#
Returns the kubernetes pod definition (if any) that is used to run the task on hosted Flyte.
- Parameters
settings (flytekit.configuration.SerializationSettings) –
- Return type
Optional[flytekit.models.task.K8sPod]
- get_sql(settings)#
Returns the Sql definition (if any) that is used to run the task on hosted Flyte.
- Parameters
settings (flytekit.configuration.SerializationSettings) –
- Return type
Optional[flytekit.models.task.Sql]
- get_type_for_input_var(k, v)#
Returns the python type for an input variable by name.
- get_type_for_output_var(k, v)#
Returns the python type for the specified output variable by name.
- classmethod interpolate_query(query_template, **kwargs)#
This function will fill in the query template with the provided kwargs and return the interpolated query. Please note that when SQL tasks run in Flyte, this step is done by the task executor.
- Return type
- local_execute(ctx, **kwargs)#
This function is used only in the local execution path and is responsible for calling dispatch execute. Use this function when calling a task with native values (or Promises containing Flyte literals derived from Python native values).
- Parameters
- Return type
Optional[Union[Tuple[flytekit.core.promise.Promise], flytekit.core.promise.Promise, flytekit.core.promise.VoidPromise, Coroutine]]
- local_execution_mode()#
- post_execute(_, rval)#
This function is a stub, just here to keep dispatch_execute compatibility between this class and PythonTask.
- Parameters
_ (Optional[flytekit.core.context_manager.ExecutionParameters]) –
rval (Any) –
- Return type
- pre_execute(user_params)#
This function is a stub, just here to keep dispatch_execute compatibility between this class and PythonTask.
- Parameters
user_params (Optional[flytekit.core.context_manager.ExecutionParameters]) –
- Return type
- sandbox_execute(ctx, input_literal_map)#
Call dispatch_execute, in the context of a local sandbox execution. Not invoked during runtime.
- Parameters
input_literal_map (flytekit.models.literals.LiteralMap) –
- Return type
flytekit.models.literals.LiteralMap
- serialize_to_model(settings)#
- Parameters
settings (flytekit.configuration.SerializationSettings) –
- Return type
flytekit.models.task.TaskTemplate
Attributes
- SERIALIZE_SETTINGS = SerializationSettings(image_config=ImageConfig(default_image=Image(name='custom_container_task', fqn='flyteorg.io/placeholder', tag='image'), images=None), project='PLACEHOLDER_PROJECT', domain='LOCAL', version='PLACEHOLDER_VERSION', env=None, git_repo=None, python_interpreter='/opt/venv/bin/python3', flytekit_virtualenv_root='/opt/venv', fast_serialization_settings=None, source_root=None)
- container_image
- disable_deck
If true, this task will not output deck html file
- docs
- environment
Any environment variables that supplied during the execution of the task.
- executor
- executor_type
- instantiated_in
- interface
- lhs
- location
- metadata
- name
Return the name of the underlying task.
- output_columns
- python_interface
Returns this task’s python interface.
- query_template
- resources
- security_context
- task_config
Returns the user-specified task config which is used for plugin-specific handling of the task.
- task_resolver
- task_template
Override the base class implementation to serialize on first call.
- task_type
- task_type_version