import numpy as np
import pandas as pd

def calculate_rsi(data: pd.DataFrame, period: int = 21) -> pd.Series:
    """
    Calculate the RSI for a given period and return it as a Series.
    """
    delta = data['Close'].diff()    
    gain = np.where(delta > 0, delta, 0)
    loss = np.where(delta < 0, -delta, 0)

    alpha = 1 / period
    avg_gain = pd.Series(gain).ewm(alpha = alpha, adjust = False).mean()
    avg_loss = pd.Series(loss).ewm(alpha = alpha, adjust = False).mean()

    rs = avg_gain / avg_loss
    return 100 - (100 / (1 + rs))

def calculate_ibs(data: pd.DataFrame) -> pd.Series:
    """
    Calculate the IBS and return it as a Series.
    """
    return (data['Close'] - data['Low']) / (data['High'] - data['Low'])

def signals(data: pd.DataFrame) -> pd.Series:
    """
    Generate swing trading signals based on the IBS + RSI strategy.

    Returns a Series with 'L' for long signals and 'N' otherwise.
    """
    ibs = calculate_ibs(data)
    rsi_21 = calculate_rsi(data, period = 21)

    conditions = (ibs < 0.25) & (rsi_21 < 45)
    return pd.Series(np.where(conditions, 'L', 'N'), index = data.index)