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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
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