hdf_local.py

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"""``HDFLocalDataSet`` loads and saves data to a local hdf file. The
underlying functionality is supported by pandas, so it supports all
allowed pandas options for loading and saving hdf files.
"""
import copy
from pathlib import Path
from typing import Any, Dict

import pandas as pd
from pandas.io.pytables import HDFStore

from kedro.io.core import AbstractVersionedDataSet, DataSetError, Version


class HDFLocalDataSet(AbstractVersionedDataSet):
    """``HDFLocalDataSet`` loads and saves data to a local hdf file. The
    underlying functionality is supported by pandas, so it supports all
    allowed pandas options for loading and saving hdf files.

    Example:
    ::

        >>> from kedro.io import HDFLocalDataSet
        >>> import pandas as pd
        >>>
        >>> data = pd.DataFrame({'col1': [1, 2], 'col2': [4, 5],
        >>>                      'col3': [5, 6]})
        >>> data_set = HDFLocalDataSet(filepath="test.hdf",
        >>>                            key="test_hdf_key",
        >>>                            load_args=None,
        >>>                            save_args=None)
        >>> data_set.save(data)
        >>> reloaded = data_set.load()
        >>>
        >>> assert data.equals(reloaded)

    """

    DEFAULT_LOAD_ARGS = {}  # type: Dict[str, Any]
    DEFAULT_SAVE_ARGS = {}  # type: Dict[str, Any]

    # pylint: disable=too-many-arguments
    def __init__(
        self,
        filepath: str,
        key: str,
        load_args: Dict[str, Any] = None,
        save_args: Dict[str, Any] = None,
        version: Version = None,
    ) -> None:
        """Creates a new instance of ``HDFLocalDataSet`` pointing to a concrete
        filepath.

        Args:
            filepath: Path to an hdf file.
            key: Identifier to the group in the HDF store.
            load_args: Pandas options for loading hdf files.
                Here you can find all available arguments:
                https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_hdf.html
                All defaults are preserved.
            save_args: Pandas options for saving hdf files.
                Here you can find all available arguments:
                https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.to_hdf.html
                All defaults are preserved.
            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.

        """
        super().__init__(Path(filepath), version)
        self._key = key

        # Handle default load and save arguments
        self._load_args = copy.deepcopy(self.DEFAULT_LOAD_ARGS)
        if load_args is not None:
            self._load_args.update(load_args)
        self._save_args = copy.deepcopy(self.DEFAULT_SAVE_ARGS)
        if save_args is not None:
            self._save_args.update(save_args)

    def _load(self) -> pd.DataFrame:
        load_path = Path(self._get_load_path())
        return pd.read_hdf(load_path, key=self._key, **self._load_args)

    def _save(self, data: pd.DataFrame) -> None:
        save_path = Path(self._get_save_path())
        save_path.parent.mkdir(parents=True, exist_ok=True)
        data.to_hdf(str(save_path), key=self._key, **self._save_args)

        load_path = Path(self._get_load_path())
        self._check_paths_consistency(load_path.absolute(), save_path.absolute())

    def _describe(self) -> Dict[str, Any]:
        return dict(
            filepath=self._filepath,
            key=self._key,
            load_args=self._load_args,
            save_args=self._save_args,
            version=self._version,
        )

    def _exists(self) -> bool:
        try:
            path = self._get_load_path()
        except DataSetError:
            return False
        if Path(path).is_file():
            with HDFStore(Path(path), mode="r") as hdfstore:
                key_with_slash = (
                    self._key if self._key.startswith("/") else "/" + self._key
                )
                if key_with_slash in hdfstore.keys():
                    return True
        return False