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

def food_security_phase_classification(
    data: Union[str, pd.DataFrame, pl.DataFrame, io.BytesIO],
    indicator_columns: List[str],
    scheme: str = "IPC-like"
) -> pl.DataFrame:
    """
    Food Security Phase Classification
    ==================================

    What
    ----
    Classify areas into phases based on indicators (e.g., IPC-like scheme).

    When
    ----
    Food security assessments and response planning.

    Why
    ---
    Simple categories make complex info understandable.

    Parameters
    ----------
    data : str | pd.DataFrame | pl.DataFrame | io.BytesIO
        Input dataset.
    indicator_columns : list[str]
        Indicators used for classification.
    scheme : str, default "IPC-like"
        Classification scheme name.

    Returns
    -------
    pl.DataFrame
        Data with placeholder phase label.
    """
    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")
    return df.with_columns(pl.lit("Phase 1").alias("food_security_phase_placeholder"))
