Source code for kedro.io.pickle_s3

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"""``PickleS3DataSet`` loads and saves a Python object to a pickle file on S3.
The underlying functionality is supported by the ``pickle`` library, so
it supports all allowed options for loading and saving pickle files.
"""
import copy
import pickle
from pathlib import PurePosixPath
from typing import Any, Dict

from s3fs.core import S3FileSystem

from kedro.io.core import (
    AbstractVersionedDataSet,
    DataSetError,
    Version,
    deprecation_warning,
)


[docs]class PickleS3DataSet(AbstractVersionedDataSet): """``PickleS3DataSet`` loads and saves a Python object to a pickle file on S3. The underlying functionality is supported by the pickle library, so it supports all allowed options for loading and saving pickle files. Example: :: >>> from kedro.io import PickleS3DataSet >>> import pandas as pd >>> >>> dummy_data = pd.DataFrame({'col1': [1, 2], >>> 'col2': [4, 5], >>> 'col3': [5, 6]}) >>> data_set = PickleS3DataSet(filepath="data.pkl", >>> bucket_name="test_bucket", >>> load_args=None, >>> save_args=None) >>> data_set.save(dummy_data) >>> reloaded = data_set.load() """ DEFAULT_LOAD_ARGS = {} # type: Dict[str, Any] DEFAULT_SAVE_ARGS = {} # type: Dict[str, Any] # pylint: disable=too-many-arguments
[docs] def __init__( self, filepath: str, bucket_name: str = None, credentials: Dict[str, Any] = None, load_args: Dict[str, Any] = None, save_args: Dict[str, Any] = None, version: Version = None, s3fs_args: Dict[str, Any] = None, ) -> None: """Creates a new instance of ``PickleS3DataSet`` pointing to a concrete file on S3. ``PickleS3DataSet`` uses pickle backend to serialise objects to disk: pickle.dumps: https://docs.python.org/3/library/pickle.html#pickle.dumps and to load serialised objects into memory: pickle.loads: https://docs.python.org/3/library/pickle.html#pickle.loads Args: filepath: path to a pkl file. May contain the full path in S3 including bucket and protocol, e.g. `s3://bucket-name/path/to/file.pkl`. bucket_name: S3 bucket name. Must be specified **only** if not present in ``filepath``. credentials: Credentials to access the S3 bucket, such as ``aws_access_key_id``, ``aws_secret_access_key``. load_args: Pickle options for loading pickle files. You can find all available arguments at: https://docs.python.org/3/library/pickle.html#pickle.loads All defaults are preserved. save_args: Pickle options for saving pickle files. You can see all available arguments at: https://docs.python.org/3/library/pickle.html#pickle.dumps 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. s3fs_args: S3FileSystem options. You can see all available arguments at: https://s3fs.readthedocs.io/en/latest/api.html#s3fs.core.S3FileSystem """ deprecation_warning(self.__class__.__name__) _credentials = copy.deepcopy(credentials) or {} _s3fs_args = copy.deepcopy(s3fs_args) or {} _s3 = S3FileSystem(client_kwargs=_credentials, **_s3fs_args) path = _s3._strip_protocol(filepath) path = PurePosixPath("{}/{}".format(bucket_name, path) if bucket_name else path) super().__init__( path, version, exists_function=_s3.exists, glob_function=_s3.glob ) # 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) self._s3 = _s3
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 = str(self._get_load_path()) with self._s3.open(load_path, mode="rb") as s3_file: return pickle.loads(s3_file.read(), **self._load_args) def _save(self, data: Any) -> None: save_path = str(self._get_save_path()) try: bytes_object = pickle.dumps(data, **self._save_args) except Exception: # pylint: disable=broad-except # Checks if the error is due to serialisation or not try: pickle.dumps(data) except Exception: raise DataSetError( "{} cannot be serialized. {} can only be used with " "serializable data".format( str(data.__class__), str(self.__class__.__name__) ) ) else: raise # pragma: no cover with self._s3.open(save_path, mode="wb") as s3_file: s3_file.write(bytes_object) def _exists(self) -> bool: load_path = str(self._get_load_path()) return self._s3.isfile(load_path)