kedro.io.AbstractDataset

class kedro.io.AbstractDataset

AbstractDataset is the base class for all data set implementations. All data set implementations should extend this abstract class and implement the methods marked as abstract. If a specific dataset implementation cannot be used in conjunction with the ParallelRunner, such user-defined dataset should have the attribute _SINGLE_PROCESS = True. Example:

from pathlib import Path, PurePosixPath
import pandas as pd
from kedro.io import AbstractDataset


class MyOwnDataset(AbstractDataset[pd.DataFrame, pd.DataFrame]):
    def __init__(self, filepath, param1, param2=True):
        self._filepath = PurePosixPath(filepath)
        self._param1 = param1
        self._param2 = param2

    def _load(self) -> pd.DataFrame:
        return pd.read_csv(self._filepath)

    def _save(self, df: pd.DataFrame) -> None:
        df.to_csv(str(self._filepath))

    def _exists(self) -> bool:
        return Path(self._filepath.as_posix()).exists()

    def _describe(self):
        return dict(param1=self._param1, param2=self._param2)

Example catalog.yml specification:

my_dataset:
    type: <path-to-my-own-dataset>.MyOwnDataset
    filepath: data/01_raw/my_data.csv
    param1: <param1-value> # param1 is a required argument
    # param2 will be True by default

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.

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 (str | None) – 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 (str | None) – 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:

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