kedro.io.PickleLocalDataSet¶

class kedro.io.PickleLocalDataSet(filepath, backend='pickle', load_args=None, save_args=None, version=None)[source]¶

Bases: kedro.io.core.AbstractVersionedDataSet

PickleLocalDataSet loads and saves a Python object to a local pickle file. The underlying functionality is supported by the pickle and joblib libraries, so it supports all allowed options for loading and saving pickle files.

Example:

from kedro.io import PickleLocalDataSet
import pandas as pd

dummy_data =  pd.DataFrame({'col1': [1, 2],
                            'col2': [4, 5],
                            'col3': [5, 6]})
data_set = PickleLocalDataSet(filepath="data.pkl",
                              backend='pickle',
                              load_args=None,
                              save_args=None)
data_set.save(dummy_data)
reloaded = data_set.load()

Attributes

`PickleLocalDataSet.BACKENDS`
`PickleLocalDataSet.DEFAULT_LOAD_ARGS`
`PickleLocalDataSet.DEFAULT_SAVE_ARGS`

Methods

`PickleLocalDataSet.__init__`(filepath[, …])	Creates a new instance of `PickleLocalDataSet` pointing to a concrete filepath.
`PickleLocalDataSet.exists`()	Checks whether a data set’s output already exists by calling the provided _exists() method.
`PickleLocalDataSet.from_config`(name, config)	Create a data set instance using the configuration provided.
`PickleLocalDataSet.get_last_load_version`()	Versioned datasets should override this property to return last loaded version
`PickleLocalDataSet.get_last_save_version`()	Versioned datasets should override this property to return last saved version.
`PickleLocalDataSet.load`()	Loads data by delegation to the provided load method.
`PickleLocalDataSet.release`()	Release any cached data.
`PickleLocalDataSet.save`(data)	Saves data by delegation to the provided save method.

BACKENDS = {'joblib': <module 'joblib' from '/home/circleci/miniconda/envs/kedro_builder/lib/python3.6/site-packages/joblib/__init__.py'>, 'pickle': <module 'pickle' from '/home/circleci/miniconda/envs/kedro_builder/lib/python3.6/pickle.py'>}¶

DEFAULT_LOAD_ARGS = {}¶

DEFAULT_SAVE_ARGS = {}¶

__init__(filepath, backend='pickle', load_args=None, save_args=None, version=None)[source]¶

Creates a new instance of PickleLocalDataSet pointing to a concrete filepath. PickleLocalDataSet can use two backends to serialise objects to disk:

pickle.dump: https://docs.python.org/3/library/pickle.html#pickle.dump

joblib.dump: https://pythonhosted.org/joblib/generated/joblib.dump.html

and it can use two backends to load serialised objects into memory:

pickle.load: https://docs.python.org/3/library/pickle.html#pickle.load

joblib.load: https://pythonhosted.org/joblib/generated/joblib.load.html

Joblib tends to exhibit better performance in case objects store NumPy arrays: http://gael-varoquaux.info/programming/new_low-overhead_persistence_in_joblib_for_big_data.html.

Parameters:	filepath (`str`) – path to a pkl file. backend (`str`) – backend to use, must be one of [‘pickle’, ‘joblib’]. load_args (`Optional`[`Dict`[`str`, `Any`]]) – Options for loading pickle files. Refer to the help file of `pickle.load` or `joblib.load` for options. save_args (`Optional`[`Dict`[`str`, `Any`]]) – Options for saving pickle files. Refer to the help file of `pickle.dump` or `joblib.dump` for options. version (`Optional`[`Version`]) – If specified, should be an instance of `kedro.io.core.Version`. If its `load` attribute is None, the latest version will be loaded. If its `save` attribute is None, save version will be autogenerated.
Raises:	`ValueError` – If ‘backend’ is not one of [‘pickle’, ‘joblib’]. `ImportError` – If ‘backend’ could not be imported.
Return type:	`None`

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.

get_last_load_version()¶

Versioned datasets should override this property to return last loaded version

Return type:	`Optional`[`str`]

get_last_save_version()¶

Versioned datasets should override this property to return last saved version.

Return type:	`Optional`[`str`]

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 exists 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`