Source code for kedro.io.memory_data_set

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"""``MemoryDataSet`` is a data set implementation which handles in-memory data.
"""

import copy
from typing import Any, Dict

import numpy as np
import pandas as pd

from kedro.io.core import AbstractDataSet, DataSetError


[docs]class MemoryDataSet(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) """ def _describe(self) -> Dict[str, Any]: if self._data is not None: return dict(data="<{}>".format(type(self._data).__name__)) return dict(data=None) # pragma: no cover
[docs] def __init__(self, data: Any = None): """Creates a new instance of ``MemoryDataSet`` pointing to the provided Python object. Args: data: Python object containing the data. """ self._data = None if data is not None: self._save(data)
def _load(self) -> Any: if self._data is None: raise DataSetError("Data for MemoryDataSet has not been saved yet.") if isinstance(self._data, (pd.DataFrame, np.ndarray)): data = self._data.copy() elif type(self._data).__name__ == "DataFrame": data = self._data else: data = copy.deepcopy(self._data) return data def _save(self, data: Any): if isinstance(data, (pd.DataFrame, np.ndarray)): self._data = data.copy() elif type(data).__name__ == "DataFrame": self._data = data else: self._data = copy.deepcopy(data) def _exists(self) -> bool: if self._data is None: return False return True def _release(self): self._data = None