Source code for

"""``LambdaDataset`` is an implementation of ``AbstractDataset`` which allows for
providing custom load, save, and exists methods without extending
from __future__ import annotations

from typing import Any, Callable

from import AbstractDataset, DatasetError

[docs] class LambdaDataset(AbstractDataset): """``LambdaDataset`` loads and saves data to a data set. It relies on delegating to specific implementation such as csv, sql, etc. ``LambdaDataset`` class captures Exceptions while performing operations on composed ``Dataset`` implementations. The composed data set is responsible for providing information on how to resolve the issue when possible. This information should be available through str(error). Example: :: >>> from import LambdaDataset >>> import pandas as pd >>> >>> file_name = "test.csv" >>> def load() -> pd.DataFrame: >>> raise FileNotFoundError("'{}' csv file not found." >>> .format(file_name)) >>> dataset = LambdaDataset(load, None) """ def _describe(self) -> dict[str, Any]: def _to_str(func: Any) -> str | None: if not func: return None try: return f"<{func.__module__}.{func.__name__}>" except AttributeError: # pragma: no cover return str(func) descr = { "load": _to_str(self.__load), "save": _to_str(self.__save), "exists": _to_str(self.__exists), "release": _to_str(self.__release), } return descr def _save(self, data: Any) -> None: if not self.__save: raise DatasetError( "Cannot save to data set. No 'save' function " "provided when LambdaDataset was created." ) self.__save(data) def _load(self) -> Any: if not self.__load: raise DatasetError( "Cannot load data set. No 'load' function " "provided when LambdaDataset was created." ) return self.__load() def _exists(self) -> bool: if not self.__exists: return super()._exists() return self.__exists() def _release(self) -> None: if not self.__release: super()._release() else: self.__release()
[docs] def __init__( # noqa: PLR0913 self, load: Callable[[], Any] | None, save: Callable[[Any], None] | None, exists: Callable[[], bool] | None = None, release: Callable[[], None] | None = None, metadata: dict[str, Any] | None = None, ): """Creates a new instance of ``LambdaDataset`` with references to the required input/output data set methods. Args: load: Method to load data from a data set. save: Method to save data to a data set. exists: Method to check whether output data already exists. release: Method to release any cached information. metadata: Any arbitrary metadata. This is ignored by Kedro, but may be consumed by users or external plugins. Raises: DatasetError: If a method is specified, but is not a Callable. """ for name, value in [ ("load", load), ("save", save), ("exists", exists), ("release", release), ]: if value is not None and not callable(value): raise DatasetError( f"'{name}' function for LambdaDataset must be a Callable. " f"Object of type '{value.__class__.__name__}' provided instead." ) self.__load = load self.__save = save self.__exists = exists self.__release = release self.metadata = metadata