kedro.io.LambdaDataSet¶

class kedro.io.LambdaDataSet(load, save, exists=None, release=None)[source]¶

Bases: kedro.io.core.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 kedro.io import LambdaDataSet
import pandas as pd

file_name = "test.csv"
def load() -> pd.DataFrame:
    raise FileNotFoundError("'{}' csv file not found."
                            .format(file_name))
data_set = LambdaDataSet(load, None)

Methods

`LambdaDataSet.__init__`(load, save[, exists, …])	Creates a new instance of `LambdaDataSet` with references to the required input/output data set methods.
`LambdaDataSet.exists`()	Checks whether a data set’s output already exists by calling the provided _exists() method.
`LambdaDataSet.from_config`(name, config[, …])	Create a data set instance using the configuration provided.
`LambdaDataSet.load`()	Loads data by delegation to the provided load method.
`LambdaDataSet.release`()	Release any cached data.
`LambdaDataSet.save`(data)	Saves data by delegation to the provided save method.

__init__(load, save, exists=None, release=None)[source]¶

Creates a new instance of LambdaDataSet with references to the required input/output data set methods.

Parameters:	load (`Optional`[`Callable`[[], `Any`]]) – Method to load data from a data set. save (`Optional`[`Callable`[[`Any`], `None`]]) – Method to save data to a data set. exists (`Optional`[`Callable`[[], `bool`]]) – Method to check whether output data already exists. release (`Optional`[`Callable`[[], `None`]]) – Method to release any cached information.
Raises:	`DataSetError` – If a method is specified, but is not a Callable.

exists()¶

Checks whether a data set’s output already exists by calling the provided _exists() method.

Return type:	`bool`
Returns:	Flag indicating whether the output already exists.
Raises:	`DataSetError` – when underlying exists method raises error.

classmethod from_config(name, config, load_version=None, save_version=None)¶

Create a data set instance using the configuration provided.

Parameters:	name (`str`) – Data set name. config (`Dict`[`str`, `Any`]) – Data set config dictionary. load_version (`Optional`[`str`]) – Version string to be used for `load` operation if the data set is versioned. Has no effect on the data set if versioning was not enabled. save_version (`Optional`[`str`]) – Version string to be used for `save` operation if the data set is versioned. Has no effect on the data set if versioning was not enabled.
Return type:	`AbstractDataSet`
Returns:	An instance of an `AbstractDataSet` subclass.
Raises:	`DataSetError` – When the function fails to create the data set from its config.

load()¶

Loads data by delegation to the provided load method.

Return type:	`Any`
Returns:	Data returned by the provided load method.
Raises:	`DataSetError` – When underlying load method raises error.

release()¶

Release any cached data.

Raises:	`DataSetError` – when underlying release method raises error.
Return type:	`None`

save(data)¶

Saves data by delegation to the provided save method.

Parameters:	data (`Any`) – the value to be saved by provided save method.
Raises:	`DataSetError` – when underlying save method raises error.
Return type:	`None`