flytekit.extras.sqlite3.task

Directory

Classes

Methods

Methods

unarchive_file()

def unarchive_file(
    local_path: str,
    to_dir: str,
)

Unarchive given archive and returns the unarchived file name. It is expected that only one file is unarchived. More than one file or 0 files will result in a RuntimeError

flytekit.extras.sqlite3.task.SQLite3Config

Use this configuration to configure if sqlite3 files that should be loaded by the task. The file itself is considered as a database and hence is treated like a configuration The path to a static sqlite3 compatible database file can be

• within the container
• or from a publicly downloadable source

class SQLite3Config(
    uri: str,
    compressed: bool,
)

flytekit.extras.sqlite3.task.SQLite3Task

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.

<!– .. literalinclude:: ../../../tests/flytekit/unit/extras/sqlite3/test_task.py :start-after: # sqlite3_start :end-before: # sqlite3_end :language: python :dedent: 4 –>

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 :ref:integrations guide <cookbook:integrations_sql_sqlite3> for additional usage examples and the base class {{< py_class_ref flytekit.extend.PythonCustomizedContainerTask >}} as well.

class SQLite3Task(
    name: str,
    query_template: str,
    inputs: typing.Optional[typing.Dict[str, typing.Type]],
    task_config: typing.Optional[flytekit.extras.sqlite3.task.SQLite3Config],
    output_schema_type: typing.Optional[typing.Type[ForwardRef('FlyteSchema')]],
    container_image: typing.Optional[str],
    kwargs,
)

Properties

Methods

compile()

def compile(
    ctx: flytekit.core.context_manager.FlyteContext,
    args,
    kwargs,
) -> typing.Union[typing.Tuple[flytekit.core.promise.Promise], flytekit.core.promise.Promise, flytekit.core.promise.VoidPromise, NoneType]

Generates a node that encapsulates this task in a workflow definition.

construct_node_metadata()

def construct_node_metadata()

Used when constructing the node that encapsulates this task as part of a broader workflow definition.

dispatch_execute()

def dispatch_execute(
    ctx: FlyteContext,
    input_literal_map: _literal_models.LiteralMap,
) -> Union[_literal_models.LiteralMap, _dynamic_job.DynamicJobSpec]

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 just self similar to task classes that derive from the base PythonTask.

execute()

def execute(
    kwargs,
) -> Any

Rather than running here, send everything to the executor.

find_lhs()

def find_lhs()

get_command()

def get_command(
    settings: SerializationSettings,
) -> List[str]

get_config()

def get_config(
    settings: SerializationSettings,
) -> Dict[str, str]

Returns the task config as a serializable dictionary. This task config consists of metadata about the custom defined for this task.

get_container()

def get_container(
    settings: SerializationSettings,
) -> _task_model.Container

Returns the container definition (if any) that is used to run the task on hosted Flyte.

get_custom()

def get_custom(
    settings: flytekit.configuration.SerializationSettings,
) -> typing.Dict[str, typing.Any]

Return additional plugin-specific custom data (if any) as a serializable dictionary.

get_extended_resources()

def get_extended_resources(
    settings: flytekit.configuration.SerializationSettings,
) -> typing.Optional[flyteidl.core.tasks_pb2.ExtendedResources]

Returns the extended resources to allocate to the task on hosted Flyte.

get_image()

def get_image(
    settings: SerializationSettings,
) -> str

get_input_types()

def get_input_types()

Returns the names and python types as a dictionary for the inputs of this task.

get_k8s_pod()

def get_k8s_pod(
    settings: flytekit.configuration.SerializationSettings,
) -> typing.Optional[flytekit.models.task.K8sPod]

Returns the kubernetes pod definition (if any) that is used to run the task on hosted Flyte.

get_query()

def get_query(
    kwargs,
) -> str

get_sql()

def get_sql(
    settings: flytekit.configuration.SerializationSettings,
) -> typing.Optional[flytekit.models.task.Sql]

Returns the Sql definition (if any) that is used to run the task on hosted Flyte.

get_type_for_input_var()

def get_type_for_input_var(
    k: str,
    v: typing.Any,
) -> typing.Type[typing.Any]

Returns the python type for an input variable by name.

get_type_for_output_var()

def get_type_for_output_var(
    k: str,
    v: typing.Any,
) -> typing.Type[typing.Any]

Returns the python type for the specified output variable by name.

interpolate_query()

def interpolate_query(
    query_template,
    kwargs,
) -> typing.Any

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.

local_execute()

def local_execute(
    ctx: flytekit.core.context_manager.FlyteContext,
    kwargs,
) -> typing.Union[typing.Tuple[flytekit.core.promise.Promise], flytekit.core.promise.Promise, flytekit.core.promise.VoidPromise, typing.Coroutine, NoneType]

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).

local_execution_mode()

def local_execution_mode()

post_execute()

def post_execute(
    _: Optional[ExecutionParameters],
    rval: Any,
) -> Any

This function is a stub, just here to keep dispatch_execute compatibility between this class and PythonTask.

pre_execute()

def pre_execute(
    user_params: Optional[ExecutionParameters],
) -> Optional[ExecutionParameters]

This function is a stub, just here to keep dispatch_execute compatibility between this class and PythonTask.

sandbox_execute()

def sandbox_execute(
    ctx: flytekit.core.context_manager.FlyteContext,
    input_literal_map: flytekit.models.literals.LiteralMap,
) -> flytekit.models.literals.LiteralMap

Call dispatch_execute, in the context of a local sandbox execution. Not invoked during runtime.

serialize_to_model()

def serialize_to_model(
    settings: SerializationSettings,
) -> _task_model.TaskTemplate

flytekit.extras.sqlite3.task.SQLite3TaskExecutor

class SQLite3TaskExecutor(
    args,
    kwargs,
)

Properties

Methods

execute_from_model()

def execute_from_model(
    tt: flytekit.models.task.TaskTemplate,
    kwargs,
) -> typing.Any

This function must be overridden and is where all the business logic for running a task should live. Keep in mind that you’re only working with the TaskTemplate. You won’t have access to any information in the task that wasn’t serialized into the template.

find_lhs()

def find_lhs()