import numpy as np

from pandas import DataFrame, Series

from daily_data import get_daily_data

def calculate_rsi(data: DataFrame, period: int = 2) -> Series:
    """
    Calculate the RSI and return it as a Series without modifying the original DataFrame.
    """
    delta = data['Close'].diff()
    gain = np.where(delta > 0, delta, 0)
    loss = np.where(delta < 0, -delta, 0)

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

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

def signals(data: DataFrame) -> Series:
    """
    Generate long signals based on the TRIN strategy with the following rules:
    1. SPY is above its 200-day moving average
    2. 2-period RSI is below 50
    3. TRIN closes above 1
    
    Returns a Series with 'L' for long signals and 'N' for no signal.
    """
    ma_200 = data['Close'].rolling(window = 200).mean()

    rsi_2 = calculate_rsi(data, period = 2)

    start_date = data['Date'].min()
    end_date = data['Date'].max()
    trin_data = get_daily_data(symbol = 'RINT.Z', start_date = start_date, end_date = end_date)

    trin_above_1 = trin_data['Close'] > 1

    above_200_ma = data['Close'] > ma_200
    rsi_below_50 = rsi_2 < 50

    signals = Series('N', index = data.index)
    signals[above_200_ma & rsi_below_50 & trin_above_1] = 'L'
    return signals