kedro.io.MemoryDataSet

class kedro.io.MemoryDataSet(data=<object object>)[source]

Bases: kedro.io.core.AbstractDataSet

MemoryDataSet loads and saves data from/to an in-memory Python object.

Example:

from kedro.io import MemoryDataSet
import pandas as pd

data = pd.DataFrame({'col1': [1, 2], 'col2': [4, 5],
                     'col3': [5, 6]})
data_set = MemoryDataSet(data=data)

loaded_data = data_set.load()
assert loaded_data.equals(data)

new_data = pd.DataFrame({'col1': [1, 2], 'col2': [4, 5]})
data_set.save(new_data)
reloaded_data = data_set.load()
assert reloaded_data.equals(new_data)

Methods

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

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

Parameters:data (Any) – Python object containing the data.
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