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"""``FeatherLocalDataSet`` is a data set used to load and save
data to local feather files. It uses the ``pandas`` implementation,
Feather is a fast, lightweight, and easy-to-use binary file format for storing data frames.
The underlying functionality is supported by pandas,
so it supports all operations the pandas supports.
Documentation on the Feather features, compatibility
list and known caveats can also be found on their official guide at:
https://github.com/wesm/feather.
"""
from pathlib import Path
from typing import Any, Dict
import pandas as pd
from kedro.io.core import AbstractVersionedDataSet, DataSetError, Version
[docs]class FeatherLocalDataSet(AbstractVersionedDataSet):
"""``FeatherLocalDataSet`` loads and saves data to a local feather file. The
underlying functionality is supported by pandas, so it supports all
allowed pandas options for loading and saving csv files.
Example:
::
>>> from kedro.contrib.io.feather import FeatherLocalDataSet
>>> import pandas as pd
>>>
>>> data = pd.DataFrame({'col1': [1, 2], 'col2': [4, 5],
>>> 'col3': [5, 6]})
>>>
>>> data_set = FeatherLocalDataSet(filepath="test.feather",
>>> load_args=None)
>>> data_set.save(data)
>>> reloaded = data_set.load()
>>>
>>> assert data.equals(reloaded)
"""
[docs] def __init__(
self, filepath: str, load_args: Dict[str, Any] = None, version: Version = None
) -> None:
"""Creates a new instance of ``FeatherLocalDataSet`` pointing to a concrete
filepath.
Args:
filepath: path to a feather file.
load_args: feather options for loading feather files.
Here you can find all available arguments:
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_feather.html#pandas.read_feather
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)
default_load_args = {} # type: Dict[str, Any]
self._load_args = (
{**default_load_args, **load_args}
if load_args is not None
else default_load_args
)
def _load(self) -> pd.DataFrame:
load_path = Path(self._get_load_path())
return pd.read_feather(load_path, **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_feather(str(save_path))
load_path = Path(self._get_load_path())
self._check_paths_consistency(load_path.absolute(), save_path.absolute())
def _exists(self) -> bool:
try:
path = self._get_load_path()
except DataSetError:
return False
return Path(path).is_file()
def _describe(self) -> Dict[str, Any]:
return dict(
filepath=self._filepath, load_args=self._load_args, version=self._version
)