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"""``JSONLocalDataSet`` encodes a given object to json and saves it to a local
file.
"""
import copy
import json
from pathlib import Path
from typing import Any, Dict
import pandas as pd
from kedro.io.core import AbstractVersionedDataSet, DataSetError, Version
[docs]class JSONLocalDataSet(AbstractVersionedDataSet):
"""``JSONLocalDataSet`` encodes data as json and saves it to a local file
or reads in and decodes an existing json file. The encoding/decoding
functionality is provided by Python's ``json`` library.
Example:
::
>>> from kedro.io import JSONLocalDataSet
>>> my_dict = {
>>> 'a_string': 'Hello, World!',
>>> 'a_list': [1, 2, 3]
>>> }
>>> data_set = JSONLocalDataSet(filepath="test.json")
>>> data_set.save(my_dict)
>>> reloaded = data_set.load()
>>> assert my_dict == reloaded
"""
DEFAULT_LOAD_ARGS = {} # type: Dict[str, Any]
DEFAULT_SAVE_ARGS = {"indent": 4} # type: Dict[str, Any]
[docs] def __init__(
self,
filepath: str,
load_args: Dict[str, Any] = None,
save_args: Dict[str, Any] = None,
version: Version = None,
) -> None:
"""Creates a new instance of ``JSONLocalDataSet`` pointing to a concrete
filepath.
Args:
filepath: path to a local json file.
load_args: Arguments passed on to ```json.load``.
See https://docs.python.org/3/library/json.html for details.
All defaults are preserved.
save_args: Arguments passed on to ```json.dump``.
See https://docs.python.org/3/library/json.html
for details. 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)
# 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 _describe(self) -> Dict[str, Any]:
return dict(
filepath=self._filepath,
load_args=self._load_args,
save_args=self._save_args,
version=self._version,
)
def _load(self) -> Any:
load_path = Path(self._get_load_path())
with load_path.open("r") as local_file:
return json.load(local_file, **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)
with save_path.open("w") as local_file:
json.dump(data, local_file, **self._save_args)
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()