import polars as pl
import pandas as pd
from typing import Union, Optional, List
import io


def donor_contribution_tracking(
    data: Union[str, pd.DataFrame, pl.DataFrame, io.BytesIO],
    donor_col: str,
    amount_col: str,
    group_by: Optional[List[str]] = None
) -> pl.DataFrame:
    """
    Donor Contribution Tracking
    ===========================

    What
    ----
    Summarize contributions by donor (and optional groups).

    When
    ----
    Financial tracking and reporting.

    Why
    ---
    Attribute funding and monitor top donors.

    Parameters
    ----------
    data : str | pd.DataFrame | pl.DataFrame | io.BytesIO
        Input dataset.
    donor_col : str
        Donor name column.
    amount_col : str
        Contribution amount column.
    group_by : list[str] | None
        Additional grouping (e.g., cluster, province).

    Returns
    -------
    pl.DataFrame
        Aggregated placeholder by donor.
    """
    if isinstance(data, str):
        df = pl.read_csv(data)
    elif isinstance(data, io.BytesIO):
        df = pl.read_csv(data)
    elif isinstance(data, pd.DataFrame):
        df = pl.from_pandas(data)
    elif isinstance(data, pl.DataFrame):
        df = data
    else:
        raise TypeError("Unsupported data type")

    # Placeholder: return as-is; aggregation to be implemented later
    return df
