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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 copy import deepcopy
from pathlib import PurePosixPath
from typing import Any, Dict, Optional

from s3fs.core import S3FileSystem

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


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 PickleLocalDataSet
            >>> 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
    def __init__(
        self,
        filepath: str,
        bucket_name: str,
        credentials: Optional[Dict[str, Any]] = None,
        load_args: Optional[Dict[str, Any]] = None,
        save_args: Optional[Dict[str, Any]] = None,
        version: Version = 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.
            bucket_name: S3 bucket name.
            credentials: Credentials to access the S3 bucket, such as
                ``aws_access_key_id``, ``aws_secret_access_key``.
            load_args: Options for loading pickle files. Refer to the help
                file of ``pickle.loads`` for options.
            save_args: Options for saving pickle files. Refer to the help
                file of ``pickle.dumps`` for options.
            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.
        """
        _credentials = deepcopy(credentials) or {}
        _s3 = S3FileSystem(client_kwargs=_credentials)
        super().__init__(
            PurePosixPath("{}/{}".format(bucket_name, filepath)),
            version,
            exists_function=_s3.exists,
            glob_function=_s3.glob,
        )
        self._bucket_name = bucket_name
        self._credentials = _credentials

        # 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,
            bucket_name=self._bucket_name,
            load_args=self._load_args,
            save_args=self._save_args,
            version=self._version,
        )

    def _load(self) -> Any:
        load_path = PurePosixPath(self._get_load_path())

        with self._s3.open(str(load_path), mode="rb") as s3_file:
            return pickle.loads(s3_file.read(), **self._load_args)

    def _save(self, data: Any) -> None:
        save_path = PurePosixPath(self._get_save_path())
        bytes_object = pickle.dumps(data, **self._save_args)

        with self._s3.open(str(save_path), mode="wb") as s3_file:
            s3_file.write(bytes_object)

        load_path = PurePosixPath(self._get_load_path())
        self._check_paths_consistency(load_path, save_path)

    def _exists(self) -> bool:
        try:
            load_path = self._get_load_path()
        except DataSetError:
            return False
        return self._s3.isfile(str(PurePosixPath(load_path)))
