kedro.framework.hooks.specs.NodeSpecs

class documentation

class NodeSpecs: (source)

Namespace that defines all specifications for a node's lifecycle hooks.

Method	`after_node_run`	Hook to be invoked after a node runs. The arguments received are the same as those used by `kedro.runner.run_node` as well as the `outputs` of the node run.
Method	`before_node_run`	Hook to be invoked before a node runs. The arguments received are the same as those used by `kedro.runner.run_node`
Method	`on_node_error`	Hook to be invoked if a node run throws an uncaught error. The signature of this error hook should match the signature of `before_node_run` along with the error that was raised.

@hook_spec
def after_node_run(self, node: Node, catalog: DataCatalog, inputs: Dict[str, Any], outputs: Dict[str, Any], is_async: bool, session_id: str): (source) ¶

Hook to be invoked after a node runs. The arguments received are the same as those used by kedro.runner.run_node as well as the outputs of the node run.

Parameters
node:`Node`	The `Node` that ran.
catalog:`DataCatalog`	A `DataCatalog` containing the node's inputs and outputs.
inputs:`Dict[str, Any]`	The dictionary of inputs dataset. The keys are dataset names and the values are the actual loaded input data, not the dataset instance.
outputs:`Dict[str, Any]`	The dictionary of outputs dataset. The keys are dataset names and the values are the actual computed output data, not the dataset instance.
is_async:`bool`	Whether the node was run in `async` mode.
session_id:`str`	The id of the session.

@hook_spec
def before_node_run(self, node: Node, catalog: DataCatalog, inputs: Dict[str, Any], is_async: bool, session_id: str) -> Optional[Dict[str, Any]]: (source) ¶

Hook to be invoked before a node runs. The arguments received are the same as those used by kedro.runner.run_node

Parameters
node:`Node`	The `Node` to run.
catalog:`DataCatalog`	A `DataCatalog` containing the node's inputs and outputs.
inputs:`Dict[str, Any]`	The dictionary of inputs dataset. The keys are dataset names and the values are the actual loaded input data, not the dataset instance.
is_async:`bool`	Whether the node was run in `async` mode.
session_id:`str`	The id of the session.
Returns
`Optional[Dict[str, Any]]`	Either None or a dictionary mapping dataset name(s) to new value(s). If returned, this dictionary will be used to update the node inputs, which allows to overwrite the node inputs.

@hook_spec
def on_node_error(self, error: Exception, node: Node, catalog: DataCatalog, inputs: Dict[str, Any], is_async: bool, session_id: str): (source) ¶

Hook to be invoked if a node run throws an uncaught error. The signature of this error hook should match the signature of before_node_run along with the error that was raised.

Parameters
error:`Exception`	The uncaught exception thrown during the node run.
node:`Node`	The `Node` to run.
catalog:`DataCatalog`	A `DataCatalog` containing the node's inputs and outputs.
inputs:`Dict[str, Any]`	The dictionary of inputs dataset. The keys are dataset names and the values are the actual loaded input data, not the dataset instance.
is_async:`bool`	Whether the node was run in `async` mode.
session_id:`str`	The id of the session.