kedro.io.PickleLocalDataSet

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

Bases: kedro.io.core.AbstractDataSet, kedro.io.core.FilepathVersionMixIn

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

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.load() Loads data by delegation to the provided load method.
PickleLocalDataSet.save(data) Saves data by delegation to the provided save method.
BACKENDS = {'joblib': <module 'joblib' from '/home/circleci/.conda/envs/kedro_builder/lib/python3.6/site-packages/joblib/__init__.py'>, 'pickle': <module 'pickle' from '/home/circleci/.conda/envs/kedro_builder/lib/python3.6/pickle.py'>}
__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.load 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.

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.
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