from __future__ import annotations
import pandas as pd

def ensure_cols(df: pd.DataFrame, cols: list[str]) -> None:
    missing = [c for c in cols if c not in df.columns]
    if missing:
        raise ValueError(f"DataFrame missing columns: {missing}")

def rsi(df: pd.DataFrame, price_col: str = "close", period: int = 14) -> pd.DataFrame:
    ensure_cols(df, [price_col])
    delta = df[price_col].diff()
    gain = delta.clip(lower=0)
    loss = -delta.clip(upper=0)
    avg_gain = gain.rolling(window=period, min_periods=period).mean()
    avg_loss = loss.rolling(window=period, min_periods=period).mean()
    rs = avg_gain / avg_loss
    df["RSI"] = 100 - (100 / (1 + rs))
    return df

def macd(
    df: pd.DataFrame,
    price_col: str = "close",
    short_window: int = 12,
    long_window: int = 26,
    signal_window: int = 9,
) -> pd.DataFrame:
    ensure_cols(df, [price_col])
    short_ema = df[price_col].ewm(span=short_window, adjust=False).mean()
    long_ema = df[price_col].ewm(span=long_window, adjust=False).mean()
    macd_line = short_ema - long_ema
    signal_line = macd_line.ewm(span=signal_window, adjust=False).mean()
    df["MACD_Line"] = macd_line
    df["Signal_Line"] = signal_line
    return df