kedro.framework.project

package documentation

(source)

kedro.framework.project module provides utitlity to configure a Kedro project and access its settings.

From __init__.py:

Function	`configure_logging`	Configure logging according to `logging_config` dictionary.
Function	`configure_project`	Configure a Kedro project by populating its settings with values defined in user's settings.py and pipeline_registry.py.
Function	`find_pipelines`	Automatically find modular pipelines having a `create_pipeline` function. By default, projects created using Kedro 0.18.3 and higher call this function to autoregister pipelines upon creation/addition.
Function	`validate_settings`	Eagerly validate that the settings module is importable. This is desirable to surface any syntax or import errors early. In particular, without eagerly importing the settings module, dynaconf would silence any import error (e...
Constant	`IMPORT_ERROR_MESSAGE`	Undocumented
Constant	`LOGGING`	Undocumented
Constant	`PACKAGE_NAME`	Undocumented
Variable	`pipelines`	Undocumented
Variable	`settings`	Undocumented
Class	`_HasSharedParentClassValidator`	A validator to check that the parent of the default class is an ancestor of the settings value.
Class	`_IsSubclassValidator`	A validator to check if the supplied setting value is a subclass of the default class
Class	`_ProjectLogging`	No class docstring; 0/1 instance variable, 2/2 methods documented
Class	`_ProjectPipelines`	A read-only lazy dictionary-like object to hold the project pipelines. On configure it will store the pipelines module. On first data access, e.g. through __getitem__, it will load the registered pipelines and merge them with pipelines defined from hooks.
Class	`_ProjectSettings`	Define all settings available for users to configure in Kedro, along with their validation rules and default values. Use Dynaconf's LazySettings as base.
Function	`_create_pipeline`	Undocumented
Function	`_get_default_class`	Undocumented
Function	`_load_data_wrapper`	Wrap a method in _ProjectPipelines so that data is loaded on first access. Taking inspiration from dynaconf.utils.functional.new_method_proxy

IMPORT_ERROR_MESSAGE: str = (source) ¶

Undocumented

Value

'''An error occurred while importing the \'{module}\' module. Nothing defined th↵
erein will be returned by \'find_pipelines\'.

{tb_exc}'''

def _get_default_class(class_import_path): (source) ¶

Undocumented

def _load_data_wrapper(func): (source) ¶

Wrap a method in _ProjectPipelines so that data is loaded on first access. Taking inspiration from dynaconf.utils.functional.new_method_proxy

PACKAGE_NAME = (source) ¶

Undocumented

Value

None

LOGGING = (source) ¶

Undocumented

Value

_ProjectLogging()

settings = (source) ¶

Undocumented

pipelines = (source) ¶

Undocumented

def configure_project(package_name: str): (source) ¶

Configure a Kedro project by populating its settings with values defined in user's settings.py and pipeline_registry.py.

def configure_logging(logging_config: Dict[str, Any]): (source) ¶

Configure logging according to logging_config dictionary.

def validate_settings(): (source) ¶

Eagerly validate that the settings module is importable. This is desirable to surface any syntax or import errors early. In particular, without eagerly importing the settings module, dynaconf would silence any import error (e.g. missing dependency, missing/mislabelled pipeline), and users would instead get a cryptic error message Expected an instance of `ConfigLoader`, got `NoneType` instead. More info on the dynaconf issue: https://github.com/rochacbruno/dynaconf/issues/460

def _create_pipeline(pipeline_module: types.ModuleType) -> Optional[Pipeline]: (source) ¶

Undocumented

def find_pipelines() -> Dict[str, Pipeline]: (source) ¶

Automatically find modular pipelines having a create_pipeline function. By default, projects created using Kedro 0.18.3 and higher call this function to autoregister pipelines upon creation/addition.

Projects that require more fine-grained control can still define the pipeline registry without calling this function. Alternatively, they can modify the mapping generated by the find_pipelines function.

For more information on the pipeline registry and autodiscovery, see https://kedro.readthedocs.io/en/latest/nodes_and_pipelines/pipeline_registry.html

Returns
`Dict[str, Pipeline]`	A generated mapping from pipeline names to `Pipeline` objects.
Warns
UserWarning	When a module does not expose a `create_pipeline` function, the `create_pipeline` function does not return a `Pipeline` object, or if the module import fails up front.