Project

def configure_logging(logging_config: dict[str, Any]) -> None:
    """Configure logging according to ``logging_config`` dictionary."""
    LOGGING.configure(logging_config)

def configure_project(package_name: str, preserve_logging: bool = False) -> None:
    """Configure a Kedro project by populating its settings with values
    defined in user's settings.py and pipeline_registry.py.

    Args:
        package_name: The name of the project package.
        preserve_logging: If True, skip re-applying the logging configuration when
            setting up the project logger. Useful in long-running processes (e.g.
            FastAPI apps) where custom handlers are added at runtime and must not
            be overwritten on repeated calls to ``configure_project()``.
    """
    settings_module = f"{package_name}.settings"
    settings.configure(settings_module)

    pipelines_module = f"{package_name}.pipeline_registry"
    pipelines.configure(pipelines_module)

    # Once the project is successfully configured once, store PACKAGE_NAME as a
    # global variable to make it easily accessible. This is used by validate_settings()
    # below, and also by ParallelRunner on Windows, as package_name is required every
    # time a new subprocess is spawned.
    global PACKAGE_NAME  # noqa: PLW0603
    PACKAGE_NAME = package_name

    if PACKAGE_NAME:
        LOGGING.set_project_logging(PACKAGE_NAME, preserve_logging=preserve_logging)

def find_pipelines(  # noqa: PLR0912, PLR0915
    raise_errors: bool = False, pipelines_to_find: list[str] | None = None
) -> dict[str, Pipeline]:
    """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://docs.kedro.org/en/stable/build/pipeline_registry/

    Args:
        raise_errors: If ``True``, raise an error upon failed discovery.
        pipelines_to_find: Optional list of pipeline names to load selectively.
            If ``None`` or contains ``"__default__"``, all pipelines are loaded.

    Returns:
        A generated mapping from pipeline names to ``Pipeline`` objects.

    Raises:
        RuntimeError: When the project has not been configured (i.e.
            ``PACKAGE_NAME`` is ``None``).
        ImportError: 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.
            If ``raise_errors`` is ``False``, see Warns section instead.

    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.
            If ``raise_errors`` is ``True``, see Raises section instead.
    """
    if PACKAGE_NAME is None:
        raise RuntimeError(
            "'find_pipelines' cannot be called before the project is configured. "
            "Call 'configure_project' first."
        )

    # Determine if specific pipelines were requested
    load_all = pipelines_to_find is None or "__default__" in pipelines_to_find
    requested_pipelines: set[str] | None = None if load_all else set(pipelines_to_find)  # type: ignore[arg-type]

    pipelines_dict: dict[str, Pipeline] = {}

    if load_all:
        # Handle the simplified project structure found in several starters.
        pipeline_obj = None
        pipeline_module_name = f"{PACKAGE_NAME}.pipeline"
        try:
            pipeline_module = importlib.import_module(pipeline_module_name)
        except Exception as exc:
            if str(exc) != f"No module named '{pipeline_module_name}'":
                if raise_errors:
                    raise ImportError(
                        f"An error occurred while importing the "
                        f"'{pipeline_module_name}' module."
                    ) from exc

                warnings.warn(
                    IMPORT_ERROR_MESSAGE.format(
                        module=pipeline_module_name, tb_exc=traceback.format_exc()
                    )
                )
        else:
            pipeline_obj = _create_pipeline(pipeline_module)

        pipelines_dict["__default__"] = pipeline_obj or pipeline([])

    # Handle the case that a project doesn't have a pipelines directory.
    try:
        pipelines_package = importlib.resources.files(f"{PACKAGE_NAME}.pipelines")
    except ModuleNotFoundError as exc:
        if str(exc) == f"No module named '{PACKAGE_NAME}.pipelines'":
            if requested_pipelines is not None:
                missing_str = ", ".join(sorted(requested_pipelines))
                error_msg = f"Pipeline(s) not found: {missing_str}"
                if raise_errors:
                    raise KeyError(error_msg) from exc
                warnings.warn(error_msg)
                return {}
            return pipelines_dict

    seen: set[str] = set()
    for pipeline_dir in pipelines_package.iterdir():
        if not pipeline_dir.is_dir():
            continue

        pipeline_name = pipeline_dir.name
        if pipeline_name == "__pycache__":
            continue
        # Prevent imports of hidden directories/files
        if pipeline_name.startswith("."):
            continue

        if requested_pipelines is not None and pipeline_name not in requested_pipelines:
            continue

        seen.add(pipeline_name)
        pipeline_module_name = f"{PACKAGE_NAME}.pipelines.{pipeline_name}"
        try:
            pipeline_module = importlib.import_module(pipeline_module_name)
        except Exception as exc:
            if raise_errors:
                raise ImportError(
                    f"An error occurred while importing the "
                    f"'{pipeline_module_name}' module."
                ) from exc

            warnings.warn(
                IMPORT_ERROR_MESSAGE.format(
                    module=pipeline_module_name, tb_exc=traceback.format_exc()
                )
            )
            continue

        pipeline_obj = _create_pipeline(pipeline_module)
        if pipeline_obj is not None:
            pipelines_dict[pipeline_name] = pipeline_obj
        elif raise_errors:
            raise KeyError(f"Pipeline '{pipeline_name}' not found")

    if requested_pipelines is not None:
        for pipeline_name in requested_pipelines - seen:
            pipeline_module_name = f"{PACKAGE_NAME}.pipelines.{pipeline_name}"
            error_msg = f"An error occurred while importing the '{pipeline_module_name}' module."
            if raise_errors:
                raise ImportError(error_msg)
            warnings.warn(
                f"{error_msg} Nothing defined therein will be returned by 'find_pipelines'."
            )

    return pipelines_dict

def validate_settings() -> None:
    """Eagerly validate that the settings module is importable if it exists. 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/dynaconf/dynaconf/issues/460
    """
    if PACKAGE_NAME is None:
        raise ValueError(
            "Package name not found. Make sure you have configured the project using "
            "'bootstrap_project'. This should happen automatically if you are using "
            "Kedro command line interface."
        )
    # Check if file exists, if it does, validate it.
    if importlib.util.find_spec(f"{PACKAGE_NAME}.settings") is not None:
        importlib.import_module(f"{PACKAGE_NAME}.settings")
    else:
        logger = logging.getLogger(__name__)
        logger.warning("No 'settings.py' found, defaults will be used.")