kedro.io.CachedDataSet

class kedro.io.CachedDataSet(dataset, version=None, copy_mode=None)[source]

Bases: kedro.io.core.AbstractDataSet

CachedDataSet is a dataset wrapper which caches in memory the data saved, so that the user avoids io operations with slow storage media.

You can also specify a CachedDataSet in catalog.yml:

test_ds:
   type: CachedDataSet
   versioned: true
   dataset:
      type: pandas.CSVDataSet
      filepath: example.csv

Please note that if your dataset is versioned, this should be indicated in the wrapper class as shown above.

Methods

CachedDataSet.__init__(dataset[, version, …]) Creates a new instance of CachedDataSet pointing to the provided Python object.
CachedDataSet.exists() Checks whether a data set’s output already exists by calling the provided _exists() method.
CachedDataSet.from_config(name, config[, …]) Create a data set instance using the configuration provided.
CachedDataSet.load() Loads data by delegation to the provided load method.
CachedDataSet.release() Release any cached data.
CachedDataSet.save(data) Saves data by delegation to the provided save method.
__init__(dataset, version=None, copy_mode=None)[source]

Creates a new instance of CachedDataSet pointing to the provided Python object.

Parameters:
  • dataset (Union[AbstractDataSet, Dict[~KT, ~VT]]) – A Kedro DataSet object or a dictionary to cache.
  • 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.
  • copy_mode (Optional[str]) – The copy mode used to copy the data. Possible values are: “deepcopy”, “copy” and “assign”. If not provided, it is inferred based on the data type.
Raises:

ValueError – If the provided dataset is not a valid dict/YAML representation of a dataset or an actual dataset.

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