"""Amazon S3 Excel Read Module (PRIVATE)."""

from __future__ import annotations

import logging
from typing import Any

import boto3

import awswrangler.pandas as pd
from awswrangler import exceptions
from awswrangler.s3._fs import open_s3_object

_logger: logging.Logger = logging.getLogger(__name__)


def read_excel(
    path: str,
    version_id: str | None = None,
    use_threads: bool | int = True,
    boto3_session: boto3.Session | None = None,
    s3_additional_kwargs: dict[str, Any] | None = None,
    **pandas_kwargs: Any,
) -> pd.DataFrame:
    """Read EXCEL file(s) from a received S3 path.

    Note
    ----
    This function accepts any Pandas's read_excel() argument.
    https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_excel.html

    Note
    ----
    Depending on the file extension ('xlsx', 'xls', 'odf'...), an additional library
    might have to be installed first.

    Note
    ----
    In case of `use_threads=True` the number of threads
    that will be spawned will be gotten from os.cpu_count().

    Parameters
    ----------
    path
        S3 path (e.g. ``s3://bucket/key.xlsx``).
    version_id
        Version id of the object.
    use_threads
        True to enable concurrent requests, False to disable multiple threads.
        If enabled os.cpu_count() will be used as the max number of threads.
        If given an int will use the given amount of threads.
        If integer is provided, specified number is used.
    boto3_session
        Boto3 Session. The default boto3 session will be used if boto3_session receive None.
    s3_additional_kwargs
        Forward to botocore requests, only "SSECustomerAlgorithm" and "SSECustomerKey" arguments will be considered.
    pandas_kwargs:
        KEYWORD arguments forwarded to pandas.read_excel(). You can NOT pass `pandas_kwargs` explicit, just add valid
        Pandas arguments in the function call and awswrangler will accept it.
        e.g. wr.s3.read_excel("s3://bucket/key.xlsx", na_rep="", verbose=True)
        https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_excel.html

    Returns
    -------
        Pandas DataFrame.

    Examples
    --------
    Reading an EXCEL file

    >>> import awswrangler as wr
    >>> df = wr.s3.read_excel('s3://bucket/key.xlsx')

    """
    if "pandas_kwargs" in pandas_kwargs:
        raise exceptions.InvalidArgument(
            "You can NOT pass `pandas_kwargs` explicit, just add valid "
            "Pandas arguments in the function call and awswrangler will accept it."
            "e.g. wr.s3.read_excel('s3://bucket/key.xlsx', na_rep='', verbose=True)"
        )
    with open_s3_object(
        path=path,
        mode="rb",
        version_id=version_id,
        use_threads=use_threads,
        s3_block_size=-1,  # One shot download
        s3_additional_kwargs=s3_additional_kwargs,
        boto3_session=boto3_session,
    ) as f:
        _logger.debug("pandas_kwargs: %s", pandas_kwargs)
        return pd.read_excel(f, **pandas_kwargs)