import yfinance as yf
import pandas as pd
import plotly.graph_objs as go
from datetime import datetime, timedelta

tickers = ['QQQ', 'TQQQ', 'SPY']
data = yf.download(tickers, start='2015-01-01', end=datetime.today().strftime('%Y-%m-%d'))['Adj Close']

initial_cash = 10000
cash = 2/3 * initial_cash
tqqq_holding = 1/3 * initial_cash / data['TQQQ'].iloc[0]
monthly_contribution = 10000
buy_dates = []

portfolio_value = [initial_cash]
cash_reserve = [cash]
tqqq_value = [tqqq_holding * data['TQQQ'].iloc[0]]
total_cash = cash
tqqq_allocation = tqqq_holding * data['TQQQ'].iloc[0]
drawdown20, drawdown30, drawdown40 = False, False, False
drawdown20_needsreset, drawdown30_needsreset, drawdown40_needsreset = False, False, False

ath = data['QQQ'].iloc[0]  # Initial All-Time High

# Initialize values for SPY, QQQ, and TQQQ with monthly contributions
spy_holding = initial_cash / data['SPY'].iloc[0]
qqq_holding = initial_cash / data['QQQ'].iloc[0]
tqqq_compare_holding = initial_cash / data['TQQQ'].iloc[0]

spy_value = [initial_cash]
qqq_value = [initial_cash]
tqqq_compare_value = [initial_cash]

for i in range(1, len(data)):

    # Update ATH
    ath = max(ath, data['QQQ'].iloc[i])

    # Reset drawdowns if ATH
    if ath == data['QQQ'].iloc[i]:
        drawdown20, drawdown30, drawdown40 = False, False, False
        drawdown20_needsreset, drawdown30_needsreset, drawdown40_needsreset = False, False, False

    # Check for buy conditions given drawdowns
    drawdown = (data['QQQ'].iloc[i] - ath) / ath
    drawdown_1 = (data['QQQ'].iloc[i-1] - ath) / ath

    if drawdown < -0.2 and drawdown_1 > -0.2 and not drawdown20_needsreset and not drawdown30_needsreset and not drawdown40_needsreset:
        drawdown20 = True
        drawdown20_needsreset = True
    if drawdown < -0.3 and drawdown_1 > -0.3 and not drawdown20_needsreset and not drawdown30_needsreset and not drawdown40_needsreset:
        drawdown30 = True
        drawdown30_needsreset = True
    if drawdown < -0.4 and drawdown_1 > -0.4 and not drawdown20_needsreset and not drawdown30_needsreset and not drawdown40_needsreset:
        drawdown40 = True
        drawdown40_needsreset = True

    # Buy TQQQ
    if (drawdown20 or drawdown30 or drawdown40) and cash > 0:

        print('****** BUY OPPORTUNITY')
        print('date = ', data.index[i])
        print('cash = ', cash)
        print('ath QQQ = ', ath)
        print('current value QQQ = ', data['QQQ'].iloc[i])
        print('prev value QQQ = ', data['QQQ'].iloc[i-1])
        print('drawdown', drawdown)
        print('drawdown_1', drawdown_1)
        print('drawdown20', drawdown20, drawdown20_needsreset)
        print('drawdown30', drawdown30, drawdown30_needsreset)
        print('drawdown40', drawdown40, drawdown40_needsreset)

        buy_amount = 1/3 * cash
        tqqq_holding += buy_amount / data['TQQQ'].iloc[i]
        cash -= buy_amount
        buy_dates.append(data.index[i])
        drawdown20, drawdown30, drawdown40 = False, False, False  # Reset drawdown indicators

    if i > 0 and data.index[i].day == 1:
        # Add monthly cash contribution
        cash += monthly_contribution

        # Add to SPY, QQQ, TQQQ for comparison
        spy_holding += monthly_contribution / data['SPY'].iloc[i]
        qqq_holding += monthly_contribution / data['QQQ'].iloc[i]
        tqqq_compare_holding += monthly_contribution / data['TQQQ'].iloc[i]

    # Calculate current portfolio value
    total_cash = cash
    tqqq_allocation = tqqq_holding * data['TQQQ'].iloc[i]
    portfolio_value.append(total_cash + tqqq_allocation)
    cash_reserve.append(cash)
    tqqq_value.append(tqqq_allocation)

    # Calculate current values for SPY, QQQ, and TQQQ with monthly contributions
    spy_value.append(spy_holding * data['SPY'].iloc[i])
    qqq_value.append(qqq_holding * data['QQQ'].iloc[i])
    tqqq_compare_value.append(tqqq_compare_holding * data['TQQQ'].iloc[i])

# Plot Portfolio Value
fig = go.Figure()

# Plot Strategy Portfolio Value
fig.add_trace(go.Scatter(x=data.index, y=portfolio_value, mode='lines', name='Portfolio'))

# Plot References with Monthly Contributions
fig.add_trace(go.Scatter(x=data.index, y=spy_value, mode='lines', name='SPY'))
fig.add_trace(go.Scatter(x=data.index, y=qqq_value, mode='lines', name='QQQ'))
fig.add_trace(go.Scatter(x=data.index, y=tqqq_compare_value, mode='lines', name='TQQQ'))

# Add Buy Markers
for date in buy_dates:
    fig.add_trace(go.Scatter(x=[date], y=[portfolio_value[data.index.get_loc(date)]], mode='markers', name='Buy', marker=dict(color='red', size=10)))

fig.update_layout(title='Portfolio vs SPY, QQQ, TQQQ with Monthly Contributions',
                  xaxis_title='Date',
                  yaxis_title='Portfolio Value',
                  showlegend=True)

fig.show()

# Display Buy Dates Table
buy_table = pd.DataFrame({'Buy Dates': buy_dates})
print(buy_table)