flytekitplugins.sqlalchemy.task

Directory

Classes

flytekitplugins.sqlalchemy.task.SQLAlchemyConfig

Use this configuration to configure task. String should be standard sqlalchemy connector format ( https://docs.sqlalchemy.org/en/14/core/engines.html#database-urls). Database can be found:

• within the container
• or from a publicly accessible source

class SQLAlchemyConfig(
    uri: str,
    connect_args: typing.Optional[typing.Dict[str, typing.Any]],
    secret_connect_args: typing.Optional[typing.Dict[str, flytekit.models.security.Secret]],
)

Methods

secret_connect_args_to_dicts()

def secret_connect_args_to_dicts()

flytekitplugins.sqlalchemy.task.SQLAlchemyDefaultImages

Default images for the sqlalchemy flytekit plugin.

Methods

default_image()

def default_image()

find_image_for()

def find_image_for(
    python_version: typing.Optional[flytekit.configuration.default_images.PythonVersion],
    flytekit_version: typing.Optional[str],
) -> str

get_version_suffix()

def get_version_suffix()

flytekitplugins.sqlalchemy.task.SQLAlchemyTask

Makes it possible to run client side SQLAlchemy queries that optionally return a FlyteSchema object

class SQLAlchemyTask(
    name: str,
    query_template: str,
    task_config: flytekitplugins.sqlalchemy.task.SQLAlchemyConfig,
    inputs: typing.Optional[typing.Dict[str, typing.Type]],
    output_schema_type: typing.Optional[typing.Type[flytekit.types.schema.types.FlyteSchema]],
    container_image: str,
    kwargs,
)

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

Properties

flytekitplugins.sqlalchemy.task.SQLAlchemyTaskExecutor

Please see the notes for the metaclass above first.

This functionality has two use-cases currently,

• Keep track of naming for non-function PythonAutoContainerTasks. That is, things like the :py:class:flytekit.extras.sqlite3.task.SQLite3Task task.
• Task resolvers, because task resolvers are instances of :py:class:flytekit.core.python_auto_container.TaskResolverMixin classes, not the classes themselves, which means we need to look on the left hand side of them to see how to find them at task execution time.

class SQLAlchemyTaskExecutor(
    args,
    kwargs,
)

Methods

execute_from_model()

def execute_from_model(
    tt: flytekit.models.task.TaskTemplate,
    kwargs,
) -> n: Python native output values from the task.

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()

Properties