import pandas as pd

from src.display.formatting import make_clickable_model


def _normalize_columns(df: pd.DataFrame) -> pd.DataFrame:
    rename_map = {
        "model type": "model_type",
        "overall f1": "overall_f1",
        "overall accuracy": "overall_accuracy",
        "accuracy": "accuracy",
        "tier i": "tier_i_f1",
        "tier ii": "tier_ii_f1",
        "tier iii": "tier_iii_f1",
        "tier i accuracy": "tier_i_accuracy",
        "tier ii accuracy": "tier_ii_accuracy",
        "tier iii accuracy": "tier_iii_accuracy",
        "start time": "start_time",
        "end time": "end_time",
    }

    normalized = {}
    for col in df.columns:
        cleaned = col.strip().lower()
        normalized[col] = rename_map.get(cleaned, cleaned.replace(" ", "_"))

    return df.rename(columns=normalized)


def get_leaderboard_df(
    results_path: str,
    _requests_path: str,
    _cols: list,
    _benchmark_cols: list,
    sort_by: str = "overall_f1",
) -> pd.DataFrame:
    """Creates a dataframe from a static CSV leaderboard file."""
    df = pd.read_csv(results_path)
    df = _normalize_columns(df)

    if "model" in df.columns:
        df["model"] = df["model"].apply(make_clickable_model)

    if sort_by in df.columns:
        df = df.sort_values(by=[sort_by], ascending=False)

    return df


def get_evaluation_queue_df(save_path: str, cols: list) -> list[pd.DataFrame]:
    """Creates empty dataframes for evaluation queues since we're using
    static data"""
    # Return empty dataframes for the queue system
    empty_df = pd.DataFrame(columns=cols)
    return empty_df, empty_df, empty_df