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# Apache License, Version 2.0 (the "License"); you may not use this file except in
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#
#     http://www.apache.org/licenses/LICENSE-2.0
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"""Module houses class that implements ``PandasDataframe``."""

from modin.core.dataframe.pandas.dataframe.dataframe import PandasDataframe

from ..partitioning.partition_manager import PandasOnDaskDataframePartitionManager


class PandasOnDaskDataframe(PandasDataframe):
    """
    The class implements the interface in ``PandasDataframe``.

    Parameters
    ----------
    partitions : np.ndarray
        A 2D NumPy array of partitions.
    index : sequence
        The index for the dataframe. Converted to a pandas.Index.
    columns : sequence
        The columns object for the dataframe. Converted to a pandas.Index.
    row_lengths : list, optional
        The length of each partition in the rows. The "height" of
        each of the block partitions. Is computed if not provided.
    column_widths : list, optional
        The width of each partition in the columns. The "width" of
        each of the block partitions. Is computed if not provided.
    dtypes : pandas.Series, optional
        The data types for the dataframe columns.
    """

    _partition_mgr_cls = PandasOnDaskDataframePartitionManager

    @classmethod
    def reconnect(cls, address, attributes):  # noqa: GL08
        # The main goal is to configure the client for the worker process
        # using the address passed by the custom `__reduce__` function
        try:
            from distributed import default_client

            default_client()
        except ValueError:
            from distributed import Client

            # setup `default_client` for worker process
            _ = Client(address)
        obj = cls.__new__(cls)
        obj.__dict__.update(attributes)
        return obj

    def __reduce__(self):  # noqa: GL08
        from distributed import default_client

        address = default_client().scheduler_info()["address"]
        return self.reconnect, (address, self.__dict__)
