kedro.io.MemoryDataset

class kedro.io.MemoryDataset(data=<object object>, copy_mode=None, metadata=None)[source]

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

exists()

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

from_config(name, config[, load_version, ...])

Create a data set instance using the configuration provided.

load()

Loads data by delegation to the provided load method.

release()

Release any cached data.

save(data)

Saves data by delegation to the provided save method.
__init__(data=<object object>, copy_mode=None, metadata=None)[source]

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

Parameters:

  • data – Python object containing the data.

  • copy_mode – 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.

  • metadata – Any arbitrary metadata. This is ignored by Kedro, but may be consumed by users or external plugins.

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 – Data set name.

  • config – Data set config dictionary.

  • load_version – 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 – 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.

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:

TypeVar(_DO)

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 (TypeVar(_DI)) – the value to be saved by provided save method.

Raises:

  • DatasetError – when underlying save method raises error.

  • FileNotFoundError – when save method got file instead of dir, on Windows.

  • NotADirectoryError – when save method got file instead of dir, on Unix.

Return type:

None