import streamlit as st
import pandas as pd
import plotly.graph_objects as go
from plotly.subplots import make_subplots
import yfinance as yf

# Function to calculate Moving Averages and Parabolic SAR
def calculate_indicators(data, ema_periods=[5, 25, 50]):
    for period in ema_periods:
        data[f'EMA_{period}'] = data['Close'].ewm(span=period, adjust=False).mean()
    data['high'] = data['High'].rolling(window=2).max()
    data['low'] = data['Low'].rolling(window=2).min()
    data['af'] = 0.02
    data['psar'] = data['Close'][0]
    for i in range(1, len(data)):
        if data['Close'][i] > data['psar'][i-1]:
            data['psar'][i] = data['psar'][i-1] + data['af'][i-1] * (data['high'][i-1] - data['psar'][i-1])
        else:
            data['psar'][i] = data['psar'][i-1] - data['af'][i-1] * (data['psar'][i-1] - data['low'][i-1])
        if data['psar'][i] > data['Close'][i]:
            data['psar'][i] = data['low'][i-1]
        else:
            data['psar'][i] = data['high'][i-1]
        if (data['Close'][i] > data['Close'][i-1] and data['af'][i-1] < 0.2):
            data['af'][i] = data['af'][i-1] + 0.02
        elif (data['Close'][i] < data['Close'][i-1]):
            data['af'][i] = 0.02
    return data

# Function to plot the data
def plot_data(data):
    fig = make_subplots(rows=2, cols=1, shared_xaxes=True, vertical_spacing=0.02)
    fig.add_trace(go.Candlestick(x=data.index,
                                 open=data['Open'], high=data['High'],
                                 low=data['Low'], close=data['Close'],
                                 name='Candlestick'), row=1, col=1)
    for ema in [5, 25, 50]:
        fig.add_trace(go.Scatter(x=data.index, y=data[f'EMA_{ema}'], mode='lines', name=f'EMA {ema}'), row=1, col=1)
    fig.add_trace(go.Scatter(x=data.index, y=data['psar'], mode='markers', marker_symbol='circle', name='Parabolic SAR'), row=1, col=1)
    return fig

# Streamlit app layout
st.title('Profit Parabolic Trading Strategy Visualization')

st.sidebar.header('User Input Parameters')
ticker = st.sidebar.text_input('Ticker Symbol', 'AAPL')
start_date = st.sidebar.date_input('Start Date', pd.to_datetime('2020-01-01'))
end_date = st.sidebar.date_input('End Date', pd.to_datetime('today'))
button = st.sidebar.button('Analyze')

if button:
    data = yf.download(ticker, start=start_date, end=end_date)
    data = calculate_indicators(data)
    fig = plot_data(data)
    st.plotly_chart(fig, use_container_width=True)