"""A module containing specifications for all callable hooks in the Kedro's execution timeline.
For more information about these specifications, please visit
[Pluggy's documentation](https://pluggy.readthedocs.io/en/stable/#specs)
"""
from __future__ import annotations
from typing import Any
from kedro.framework.context import KedroContext
from kedro.io import DataCatalog
from kedro.pipeline import Pipeline
from kedro.pipeline.node import Node
from .markers import hook_spec
[docs]
class DataCatalogSpecs:
"""Namespace that defines all specifications for a data catalog's lifecycle hooks."""
[docs]
@hook_spec
def after_catalog_created( # noqa: PLR0913
self,
catalog: DataCatalog,
conf_catalog: dict[str, Any],
conf_creds: dict[str, Any],
feed_dict: dict[str, Any],
save_version: str,
load_versions: dict[str, str],
) -> None:
"""Hooks to be invoked after a data catalog is created.
It receives the ``catalog`` as well as
all the arguments for ``KedroContext._create_catalog``.
Args:
catalog: The catalog that was created.
conf_catalog: The config from which the catalog was created.
conf_creds: The credentials conf from which the catalog was created.
feed_dict: The feed_dict that was added to the catalog after creation.
save_version: The save_version used in ``save`` operations
for all datasets in the catalog.
load_versions: The load_versions used in ``load`` operations
for each dataset in the catalog.
"""
pass
[docs]
class NodeSpecs:
"""Namespace that defines all specifications for a node's lifecycle hooks."""
[docs]
@hook_spec
def before_node_run( # noqa: PLR0913
self,
node: Node,
catalog: DataCatalog,
inputs: dict[str, Any],
is_async: bool,
session_id: str,
) -> dict[str, Any] | None:
"""Hook to be invoked before a node runs.
The arguments received are the same as those used by ``kedro.runner.run_node``
Args:
node: The ``Node`` to run.
catalog: A ``DataCatalog`` containing the node's inputs and outputs.
inputs: 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: Whether the node was run in ``async`` mode.
session_id: The id of the session.
Returns:
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.
"""
pass
[docs]
@hook_spec
def after_node_run( # noqa: PLR0913
self,
node: Node,
catalog: DataCatalog,
inputs: dict[str, Any],
outputs: dict[str, Any],
is_async: bool,
session_id: str,
) -> None:
"""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.
Args:
node: The ``Node`` that ran.
catalog: A ``DataCatalog`` containing the node's inputs and outputs.
inputs: The dictionary of inputs dataset.
The keys are dataset names and the values are the actual loaded input data,
not the dataset instance.
outputs: 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: Whether the node was run in ``async`` mode.
session_id: The id of the session.
"""
pass
[docs]
@hook_spec
def on_node_error( # noqa: PLR0913
self,
error: Exception,
node: Node,
catalog: DataCatalog,
inputs: dict[str, Any],
is_async: bool,
session_id: str,
) -> None:
"""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.
Args:
error: The uncaught exception thrown during the node run.
node: The ``Node`` to run.
catalog: A ``DataCatalog`` containing the node's inputs and outputs.
inputs: 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: Whether the node was run in ``async`` mode.
session_id: The id of the session.
"""
pass
[docs]
class PipelineSpecs:
"""Namespace that defines all specifications for a pipeline's lifecycle hooks."""
[docs]
@hook_spec
def before_pipeline_run(
self, run_params: dict[str, Any], pipeline: Pipeline, catalog: DataCatalog
) -> None:
"""Hook to be invoked before a pipeline runs.
Args:
run_params: The params used to run the pipeline.
Should have the following schema::
{
"session_id": str
"project_path": str,
"env": str,
"kedro_version": str,
"tags": Optional[List[str]],
"from_nodes": Optional[List[str]],
"to_nodes": Optional[List[str]],
"node_names": Optional[List[str]],
"from_inputs": Optional[List[str]],
"to_outputs": Optional[List[str]],
"load_versions": Optional[List[str]],
"extra_params": Optional[Dict[str, Any]]
"pipeline_name": str,
"namespace": Optional[str],
"runner": str,
}
pipeline: The ``Pipeline`` that will be run.
catalog: The ``DataCatalog`` to be used during the run.
"""
pass
[docs]
@hook_spec
def after_pipeline_run(
self,
run_params: dict[str, Any],
run_result: dict[str, Any],
pipeline: Pipeline,
catalog: DataCatalog,
) -> None:
"""Hook to be invoked after a pipeline runs.
Args:
run_params: The params used to run the pipeline.
Should have the following schema::
{
"session_id": str
"project_path": str,
"env": str,
"kedro_version": str,
"tags": Optional[List[str]],
"from_nodes": Optional[List[str]],
"to_nodes": Optional[List[str]],
"node_names": Optional[List[str]],
"from_inputs": Optional[List[str]],
"to_outputs": Optional[List[str]],
"load_versions": Optional[List[str]],
"extra_params": Optional[Dict[str, Any]]
"pipeline_name": str,
"namespace": Optional[str],
"runner": str,
}
run_result: The output of ``Pipeline`` run.
pipeline: The ``Pipeline`` that was run.
catalog: The ``DataCatalog`` used during the run.
"""
pass
[docs]
@hook_spec
def on_pipeline_error(
self,
error: Exception,
run_params: dict[str, Any],
pipeline: Pipeline,
catalog: DataCatalog,
) -> None:
"""Hook to be invoked if a pipeline run throws an uncaught Exception.
The signature of this error hook should match the signature of ``before_pipeline_run``
along with the error that was raised.
Args:
error: The uncaught exception thrown during the pipeline run.
run_params: The params used to run the pipeline.
Should have the following schema::
{
"session_id": str
"project_path": str,
"env": str,
"kedro_version": str,
"tags": Optional[List[str]],
"from_nodes": Optional[List[str]],
"to_nodes": Optional[List[str]],
"node_names": Optional[List[str]],
"from_inputs": Optional[List[str]],
"to_outputs": Optional[List[str]],
"load_versions": Optional[List[str]],
"extra_params": Optional[Dict[str, Any]]
"pipeline_name": str,
"namespace": Optional[str],
"runner": str,
}
pipeline: The ``Pipeline`` that will was run.
catalog: The ``DataCatalog`` used during the run.
"""
pass
[docs]
class DatasetSpecs:
"""Namespace that defines all specifications for a dataset's lifecycle hooks."""
[docs]
@hook_spec
def before_dataset_loaded(self, dataset_name: str, node: Node) -> None:
"""Hook to be invoked before a dataset is loaded from the catalog.
Args:
dataset_name: name of the dataset to be loaded from the catalog.
node: The ``Node`` to run.
"""
pass
[docs]
@hook_spec
def after_dataset_loaded(self, dataset_name: str, data: Any, node: Node) -> None:
"""Hook to be invoked after a dataset is loaded from the catalog.
Args:
dataset_name: name of the dataset that was loaded from the catalog.
data: the actual data that was loaded from the catalog.
node: The ``Node`` to run.
"""
pass
[docs]
@hook_spec
def before_dataset_saved(self, dataset_name: str, data: Any, node: Node) -> None:
"""Hook to be invoked before a dataset is saved to the catalog.
Args:
dataset_name: name of the dataset to be saved to the catalog.
data: the actual data to be saved to the catalog.
node: The ``Node`` that ran.
"""
pass
[docs]
@hook_spec
def after_dataset_saved(self, dataset_name: str, data: Any, node: Node) -> None:
"""Hook to be invoked after a dataset is saved in the catalog.
Args:
dataset_name: name of the dataset that was saved to the catalog.
data: the actual data that was saved to the catalog.
node: The ``Node`` that ran.
"""
pass
[docs]
class KedroContextSpecs:
"""Namespace that defines all specifications for a Kedro context's lifecycle hooks."""
[docs]
@hook_spec
def after_context_created(
self,
context: KedroContext,
) -> None:
"""Hooks to be invoked after a `KedroContext` is created. This is the earliest
hook triggered within a Kedro run. The `KedroContext` stores useful information
such as `credentials`, `config_loader` and `env`.
Args:
context: The context that was created.
"""
