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


def conflict_incident_counts(
    data: Union[str, pd.DataFrame, pl.DataFrame, io.BytesIO],
    incident_id_col: Optional[str] = None,
    date_column: Optional[str] = None,
    group_by: Optional[List[str]] = None
) -> pl.DataFrame:
    """
    Conflict Incident Counts
    ========================

    What
    ----
    Count number of conflict/security incidents.

    When
    ----
    Protection/Access monitoring and trend analysis.

    Why
    ---
    Track intensity and distribution of conflict.

    Parameters
    ----------
    data : str | pd.DataFrame | pl.DataFrame | io.BytesIO
        Input dataset of incidents.
    incident_id_col : str | None
        Unique incident id column; if None, counts rows.
    date_column : str | None
        Optional date column (string). Not used in placeholder, but kept for API.
    group_by : list[str] | None
        Optional grouping (e.g., province, district).

    Returns
    -------
    pl.DataFrame
        Placeholder count column per group or overall.
    """
    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")

    if group_by:
        # Placeholder: not aggregating to keep schema simple
        return df.with_columns(pl.lit(1).alias("incident_count_placeholder"))
    else:
        # Placeholder: add same count to each row
        count = df.height
        return df.with_columns(pl.lit(count).alias("incident_count_placeholder"))
