src/streamlit_app.py

import streamlit as st
import pandas as pd
import numpy as np
import yfinance as yf
import plotly.graph_objects as go
from plotly.subplots import make_subplots
import warnings
warnings.filterwarnings('ignore')
from curl_cffi import requests
session = requests.Session(impersonate="chrome")

# Import all technical indicators from your file
from technical_indicators import *

# Page configuration
st.set_page_config(
    page_title="Technical Analysis Dashboard",
    page_icon="📈",
    layout="wide",
    initial_sidebar_state="expanded"
)

# Custom CSS for better styling
st.markdown("""
<style>
    .main-header {
        font-size: 2.5rem;
        font-weight: bold;
        color: #1f77b4;
        text-align: center;
        margin-bottom: 2rem;
    }
    .sub-header {
        font-size: 1.5rem;
        font-weight: bold;
        text-align: center;
        margin-bottom: 1rem;
    }
    .metric-container {
        background-color: #f0f2f6;
        padding: 1rem;
        border-radius: 0.5rem;
        margin: 0.5rem 0;
    }
    .indicator-section {
        background-color: #ffffff;
        padding: 1.5rem;
        border-radius: 0.5rem;
        margin: 1rem 0;
        border: 1px solid #e0e0e0;
    }
</style>
""", unsafe_allow_html=True)

# Title
st.markdown('<h1 class="main-header">📈 Technical Analysis Dashboard</h1>', unsafe_allow_html=True)
st.markdown('<h3 class="sub-header">Developed By Zane Vijay Falcao</h3>', unsafe_allow_html=True)
st.divider()
# Sidebar for inputs
with st.sidebar:
    st.header("📊 Configuration")
    
    # Stock symbol input
    symbol = st.text_input("Stock Symbol", value="AAPL", help="Enter stock symbol (e.g., AAPL, GOOGL, MSFT)")
    
    # Time period selection
    period = st.selectbox(
        "Time Period",
        ["1mo", "3mo", "6mo", "1y", "2y", "5y", "max"],
        index=3
    )
    
    # Interval selection
    interval = st.selectbox(
        "Data Interval",
        ["1d", "5d", "1wk", "1mo"],
        index=0
    )
    
    st.divider()
    
    # Indicator Categories
    st.header("📈 Select Indicators")
    
    # Trend Indicators
    with st.expander("Trend Indicators", expanded=True):
        show_sma = st.checkbox("Simple Moving Average (SMA)", value=True)
        show_ema = st.checkbox("Exponential Moving Average (EMA)", value=True)
        show_hma = st.checkbox("Hull Moving Average (HMA)")
        show_wma = st.checkbox("Weighted Moving Average (WMA)")
        show_kama = st.checkbox("Kaufman Adaptive Moving Average (KAMA)")
        show_frama = st.checkbox("Fractal Adaptive Moving Average (FRAMA)")
        show_evwma = st.checkbox("Ehlers Volatility Weighted MA (EVWMA)")
        show_vwap = st.checkbox("Volume Weighted Average Price (VWAP)")
        show_dema = st.checkbox("Double Exponential Moving Average (reduces lag compared to EMA) (DEMA)", key="dema_trend")
        show_zlema = st.checkbox("Zero Lag Exponential Moving Average (ZLEMA)", key="zlema_trend")
        show_smm = st.checkbox("Simple Moving Median (SMM)")
        show_ssma = st.checkbox("Smoothed SMA (SSMA)")
        show_tema = st.checkbox("Triple Exponential Moving Average (TEMA)", key="tema_trend")
        show_trima = st.checkbox("Triangular Moving Average (TRIMA)")


    # Momentum Indicators
    with st.expander("Momentum Indicators", expanded=True):
        show_rsi = st.checkbox("Relative Strength Index (RSI)", value=True)
        show_macd = st.checkbox("MACD", value=True)
        show_stochrsi = st.checkbox("Stochastic RSI")
        show_cmo = st.checkbox("Chande Momentum Oscillator (CMO)")
        show_roc = st.checkbox("Rate of Change (ROC)")
        show_tsi = st.checkbox("True Strength Index (TSI)")
        show_kst = st.checkbox("Know Sure Thing (KST)")
        show_ppo = st.checkbox("Price Percentage Oscillator (PPO)")
        show_uo = st.checkbox("Ultimate Oscillator (UO)")
        show_mom = st.checkbox("Momentum (MOM)")
        show_dymi = st.checkbox("Dynamic Momentum Index (DYMI)")
        show_trix = st.checkbox("Triple Exponential Average (TRIX)", key="trix_momentum")

    
    # Volume Indicators
    with st.expander("Volume Indicators"):
        show_obv = st.checkbox("On-Balance Volume (OBV)")
        show_adl = st.checkbox("Accumulation/Distribution Line (ADL)")
        show_chaikin = st.checkbox("Chaikin Oscillator")
        show_efi = st.checkbox("Elder's Force Index (EFI)")
        show_emv = st.checkbox("Ease of Movement (EMV)")
        show_mfi = st.checkbox("Money Flow Index (MFI)")
        show_vpt = st.checkbox("Volume Price Trend (VPT)")
        show_fve = st.checkbox("Fractal Volume Efficiency (FVE)")
        show_vzo = st.checkbox("Volume Zone Oscillator (VZO)")
        show_wobv = st.checkbox("Weighted On-Balance Volume (WOBV)")
    
    # Volatility Indicators
    with st.expander("Volatility Indicators"):
        show_bollinger = st.checkbox("Bollinger Bands", value=True)
        show_kc = st.checkbox("Keltner Channels")
        show_dc = st.checkbox("Donchian Channels")
        show_atr = st.checkbox("Average True Range (ATR)")
        show_chandelier = st.checkbox("Chandelier Exit")
        show_psar = st.checkbox("Parabolic SAR")
        show_apz = st.checkbox("Adaptive Price Zone (APZ)")
    
    # Oscillators
    with st.expander("Oscillators"):
        show_adx = st.checkbox("Average Directional Index (ADX)")
        show_cci = st.checkbox("Commodity Channel Index (CCI)")
        show_fish = st.checkbox("Fisher Transform")
        show_ao = st.checkbox("Awesome Oscillator (AO)")
        show_mi = st.checkbox("Mass Index (MI)")
        show_wto = st.checkbox("Wave Trend Oscillator (WTO)")
        show_copp = st.checkbox("Coppock Curve")
        show_ift_rsi = st.checkbox("Inverse Fisher Transform RSI")
        show_qstick = st.checkbox("Q Stick")
        show_vbm = st.checkbox("Volatility-Based Momentum (VBM)")

    
    # Complex Indicators
    with st.expander("Complex Indicators"):
        show_ichimoku = st.checkbox("Ichimoku Cloud")
        show_pivot = st.checkbox("Pivot Points")
        show_pivot_fib = st.checkbox("Fibonacci Pivot Points")
        show_basp = st.checkbox("Buyer and Seller Pressure (BASP)")
        show_baspn = st.checkbox("Normalized BASP")
        show_dmi = st.checkbox("Directional Movement Index (DMI)")
        show_ebbp = st.checkbox("Elder Bull/Bear Power")
        show_ebbp_v = st.checkbox("Elder Bull/Bear Power Volume", key="ebbp_volume")
        show_sar = st.checkbox("Stop and Reverse (SAR)")
        show_cfi = st.checkbox("Cumulative Force Index (CFI)")

    
    st.divider()
    
    # Parameter settings
    st.header("⚙️ Parameters")
    sma_period = st.slider("SMA Period", 5, 50, 20)
    ema_period = st.slider("EMA Period", 5, 50, 20)
    rsi_period = st.slider("RSI Period", 5, 30, 14)
    bb_period = st.slider("Bollinger Bands Period", 10, 30, 20)
    bb_std = st.slider("Bollinger Bands Std Dev", 1.0, 3.0, 2.0, 0.1)


col1, col2, col3, col4, col5 = st.columns(5)
st.divider()
@st.cache_data
def fetch_data(symbol, period, interval):
    ticker = yf.Ticker(symbol.upper(), session=session)
    return ticker.history(period=period, interval=interval)

# Main content area
if col3.button("🚀 Analyze Stock", type="secondary", use_container_width=True):
    
    try:
        # Fetch data
        with st.spinner(f"Fetching data for {symbol.upper()}..."):
            
            data = fetch_data(symbol, period, interval)
            
            if data.empty:
                st.error("No data found for the given symbol. Please check the symbol and try again.")
                st.stop()
        
        # Display basic info
        col1, col2, col3, col4 = st.columns(4)
        
        with col1:
            st.metric("Current Price", f"${data['Close'].iloc[-1]:.2f}")
        
        with col2:
            price_change = data['Close'].iloc[-1] - data['Close'].iloc[-2]
            st.metric("Price Change", f"${price_change:.2f}", f"{price_change:.2f}")
        
        with col3:
            pct_change = (price_change / data['Close'].iloc[-2]) * 100
            st.metric("% Change", f"{pct_change:.2f}%", f"{pct_change:.2f}%")
        
        with col4:
            st.metric("Volume", f"{data['Volume'].iloc[-1]:,.0f}")
        
        # Calculate indicators
        indicators = {}
        
        # Trend Indicators
        if show_sma:
            indicators['SMA'] = SMA(data, sma_period)
        if show_ema:
            indicators['EMA'] = EMA(data, ema_period)
        if show_hma:
            indicators['HMA'] = HMA(data, 20)
        if show_wma:
            indicators['WMA'] = WMA(data, 20)
        if show_kama:
            indicators['KAMA'] = KAMA(data)
        if show_frama:
            indicators['FRAMA'] = FRAMA(data)
        if show_evwma:
            indicators['EVWMA'] = EVWMA(data)
        if show_vwap:
            indicators['VWAP'] = VWAP(data)
        if show_dema:
            indicators['DEMA'] = DEMA(data, ema_period)
        if show_zlema:
            indicators['ZLEMA'] = ZLEMA(data, ema_period)
        if show_smm:
            indicators['SMM'] = SMM(data)
        if show_ssma:
            indicators['SSMA'] = SSMA(data)
        if show_tema:
            indicators['TEMA'] = TEMA(data, ema_period)
        if show_trima:
            indicators['TRIMA'] = TRIMA(data, ema_period)

        # Momentum Indicators
        if show_rsi:
            indicators['RSI'] = RSI(data, rsi_period)
        if show_macd:
            indicators['MACD'] = MACD(data)
        if show_stochrsi:
            indicators['StochRSI'] = STOCHRSI(data)
        if show_cmo:
            indicators['CMO'] = CMO(data)
        if show_roc:
            indicators['ROC'] = ROC(data)
        if show_tsi:
            indicators['TSI'] = TSI(data)
        if show_kst:
            indicators['KST'] = KST(data)
        if show_ppo:
            indicators['PPO'] = PPO(data)
        if show_uo:
            indicators['UO'] = UO(data)
        if show_mom:
            indicators['MOM'] = MOM(data)
        if show_dymi:
            indicators['DYMI'] = DYMI(data)
        if show_trix:
            indicators['TRIX'] = TRIX(data, ema_period)
        
        # Volume Indicators
        if show_obv:
            indicators['OBV'] = OBV(data)
        if show_adl:
            indicators['ADL'] = ADL(data)
        if show_chaikin:
            indicators['Chaikin'] = CHAIKIN(data)
        if show_efi:
            indicators['EFI'] = EFI(data)
        if show_emv:
            indicators['EMV'] = EMV(data)
        if show_mfi:
            indicators['MFI'] = MFI(data)
        if show_vpt:
            indicators['VPT'] = VPT(data)
        if show_fve:
            indicators['FVE'] = FVE(data)
        if show_vzo:
            indicators['VZO'] = VZO(data)
        if show_wobv:
            indicators['WOBV'] = WOBV(data)
        if show_vpt:
            indicators['VPT'] = VPT(data)
        
        # Volatility Indicators
        if show_bollinger:
            indicators['Bollinger'] = BOLLINGER(data, bb_period, bb_std)
        if show_kc:
            indicators['KC'] = KC(data)
        if show_dc:
            indicators['DC'] = DC(data)
        if show_atr:
            indicators['ATR'] = ATR(data)
        if show_chandelier:
            indicators['Chandelier'] = CHANDELIER(data)
        if show_psar:
            indicators['PSAR'] = PSAR(data)
        if show_apz:
            indicators['APZ'] = APZ(data)
        
        # Oscillators
        if show_adx:
            indicators['ADX'] = ADX(data)
        if show_cci:
            indicators['CCI'] = CCI(data)
        if show_fish:
            indicators['Fisher'] = FISH(data)
        if show_ao:
            indicators['AO'] = AO(data)
        if show_mi:
            indicators['MI'] = MI(data)
        if show_wto:
            indicators['WTO'] = WTO(data)
        if show_copp:
            indicators['Coppock'] = COPP(data)
        if show_ift_rsi:
            indicators['IFT_RSI'] = IFT_RSI(data)
        if show_qstick:
            indicators['QSTICK'] = QSTICK(data)
        if show_vbm:
            indicators['VBM'] = VBM(data)
        
        # Complex Indicators
        if show_ichimoku:
            indicators['Ichimoku'] = ICHIMOKU(data)
        if show_pivot:
            indicators['Pivot'] = PIVOT(data)
        if show_pivot_fib:
            indicators['Pivot_Fib'] = PIVOT_FIB(data)
        if show_basp:
            indicators['BASP'] = BASP(data)
        if show_baspn:
            indicators['BASPN'] = BASPN(data)
        if show_dmi:
            indicators['DMI'] = DMI(data)
        if show_ebbp:
            indicators['EBBP'] = EBBP(data)
        if show_sar:
            indicators['SAR'] = SAR(data)
        if show_cfi:
            indicators['CFI'] = CFI(data)

        
        # Create main price chart
        fig = make_subplots(
                rows=4, cols=1,
                shared_xaxes=True,
                vertical_spacing=0.05,
                subplot_titles=(
                    'Price & Moving Averages / Bands',
                    'Volume-Based Indicators',
                    'Momentum Oscillators',
                    'Trend / Volatility / Other'
                ),
                row_heights=[0.5, 0.2, 0.15, 0.15]
        )

        # Add candlestick chart
        fig.add_trace(
            go.Candlestick(
                x=data.index,
                open=data['Open'],
                high=data['High'],
                low=data['Low'],
                close=data['Close'],
                name='Price'
            ),
            row=1, col=1
        )

        # Define colors for trend indicators to avoid repetition
        colors = ["red", "yellow", "green", "purple", "orange", "brown", "pink", "gray", "cyan", "magenta","teal", "navy", "darkgreen", "darkorange", "darkviolet", "darkslateblue", "darkred", "darkgoldenrod", "darkturquoise", "darkorchid", "darkcyan"]
        color_idx = 0

        # Add trend indicators to price chart (row 1)
        trend_indicators = ['SMA', 'EMA', 'HMA', 'WMA', 'KAMA', 'FRAMA', 'EVWMA', 'VWAP', 'DEMA', 'ZLEMA', 'SMM', 'SSMA', 'TEMA', 'TRIMA']
        for name in trend_indicators:
            if name in indicators:
                fig.add_trace(
                    go.Scatter(
                        x=data.index,
                        y=indicators[name].fillna(method='ffill'),  # Handle NaNs
                        mode='lines',
                        name=name,
                        line=dict(color=colors[color_idx % len(colors)])
                    ),
                    row=1, col=1
                )
                color_idx += 1

        # Add volatility indicators to price chart (row 1)
        if 'Bollinger' in indicators:
            bb = indicators['Bollinger']
            fig.add_trace(
                go.Scatter(
                    x=data.index,
                    y=bb['BB_UPPER'].fillna(method='ffill'),
                    mode='lines',
                    name='BB Upper',
                    line=dict(color='lightblue', dash='dash')
                ),
                row=1, col=1
            )
            fig.add_trace(
                go.Scatter(
                    x=data.index,
                    y=bb['BB_LOWER'].fillna(method='ffill'),
                    mode='lines',
                    name='BB Lower',
                    line=dict(color='lightblue', dash='dash'),
                    fill='tonexty',
                    fillcolor='rgba(173, 216, 230, 0.2)'
                ),
                row=1, col=1
            )
            
        if 'SAR' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['SAR'].fillna(method='ffill'), mode='markers', name='SAR', marker=dict(size=5, color='darkred')),
                row=1, col=1
            )

        if 'KC' in indicators:
            kc = indicators['KC']
            fig.add_trace(
                go.Scatter(x=data.index, y=kc['KC_UPPER'].fillna(method='ffill'), name='KC Upper', line=dict(color='orange')),
                row=1, col=1
            )
            fig.add_trace(
                go.Scatter(x=data.index, y=kc['KC_LOWER'].fillna(method='ffill'), name='KC Lower', line=dict(color='orange')),
                row=1, col=1
            )
            fig.add_trace(
                go.Scatter(x=data.index, y=kc['KC_MIDDLE'].fillna(method='ffill'), name='KC Middle', line=dict(color='gray', dash='dot')),
                row=1, col=1
            )

        if 'DC' in indicators:
            dc = indicators['DC']
            fig.add_trace(
                go.Scatter(x=data.index, y=dc['DC_U'].fillna(method='ffill'), name='DC Upper', line=dict(color='green')),
                row=1, col=1
            )
            fig.add_trace(
                go.Scatter(x=data.index, y=dc['DC_L'].fillna(method='ffill'), name='DC Lower', line=dict(color='green')),
                row=1, col=1
            )
            fig.add_trace(
                go.Scatter(x=data.index, y=dc['DC_M'].fillna(method='ffill'), name='DC Middle', line=dict(color='limegreen', dash='dot')),
                row=1, col=1
            )

        if 'Chandelier' in indicators:
            ce = indicators['Chandelier']
            fig.add_trace(
                go.Scatter(x=data.index, y=ce['CHANDELIER_Long'].fillna(method='ffill'), name='Chandelier Long', line=dict(color='darkred')),
                row=1, col=1
            )
            fig.add_trace(
                go.Scatter(x=data.index, y=ce['CHANDELIER_Short'].fillna(method='ffill'), name='Chandelier Short', line=dict(color='darkgreen')),
                row=1, col=1
            )

        if 'APZ' in indicators:
            apz = indicators['APZ']
            fig.add_trace(
                go.Scatter(x=data.index, y=apz['APZ_UPPER'].fillna(method='ffill'), name='APZ Upper', line=dict(color='orange', dash='dot')),
                row=1, col=1
            )
            fig.add_trace(
                go.Scatter(x=data.index, y=apz['APZ_LOWER'].fillna(method='ffill'), name='APZ Lower', line=dict(color='coral', dash='dot')),
                row=1, col=1
            )

        if 'Ichimoku' in indicators:
            ichimoku = indicators['Ichimoku']
            fig.add_trace(
                go.Scatter(x=data.index, y=ichimoku['TENKAN'].fillna(method='ffill'), name='Tenkan-sen', line=dict(color='blue')),
                row=1, col=1
            )
            fig.add_trace(
                go.Scatter(x=data.index, y=ichimoku['KIJUN'].fillna(method='ffill'), name='Kijun-sen', line=dict(color='red')),
                row=1, col=1
            )
            fig.add_trace(
                go.Scatter(x=data.index, y=ichimoku['SENKOU_A'].fillna(method='ffill'), name='Senkou A', line=dict(color='green')),
                row=1, col=1
            )
            fig.add_trace(
                go.Scatter(x=data.index, y=ichimoku['SENKOU_B'].fillna(method='ffill'), name='Senkou B', line=dict(color='red'), fill='tonexty', fillcolor='rgba(0, 255, 0, 0.2)'),
                row=1, col=1
            )
            fig.add_trace(
                go.Scatter(x=data.index, y=ichimoku['CHIKOU'].fillna(method='ffill'), name='Chikou Span', line=dict(color='purple')),
                row=1, col=1
            )

        if 'Pivot' in indicators:
            pivot = indicators['Pivot']
            for col in ['pivot', 'r1', 'r2', 'r3', 's1', 's2', 's3']:
                fig.add_trace(
                    go.Scatter(x=data.index, y=pivot[col].fillna(method='ffill'), name=f'Pivot {col.upper()}', line=dict(dash='dash')),
                    row=1, col=1
                )

        if 'Pivot_Fib' in indicators:
            pivot_fib = indicators['Pivot_Fib']
            for col in ['pivot', 'r1', 'r2', 'r3', 's1', 's2', 's3']:
                fig.add_trace(
                    go.Scatter(x=data.index, y=pivot_fib[col].fillna(method='ffill'), name=f'Fib Pivot {col.upper()}', line=dict(dash='dot')),
                    row=1, col=1
                )

        if 'PSAR' in indicators:
            psar = indicators['PSAR']
            fig.add_trace(
                go.Scatter(x=data.index, y=psar['psar'].fillna(method='ffill'), name='PSAR', mode='markers', marker=dict(size=5, color='blue')),
                row=1, col=1
            )
            fig.add_trace(
                go.Scatter(x=data.index, y=psar['psarbull'].fillna(method='ffill'), name='PSAR Bull', mode='markers', marker=dict(size=5, color='green')),
                row=1, col=1
            )
            fig.add_trace(
                go.Scatter(x=data.index, y=psar['psarbear'].fillna(method='ffill'), name='PSAR Bear', mode='markers', marker=dict(size=5, color='red')),
                row=1, col=1
            )
            
        if 'SMM' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['SMM'].fillna(method='ffill'), name='SMM', line=dict(color='darkcyan')),
                row=1, col=1
            )

        if 'SSMA' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['SSMA'].fillna(method='ffill'), name='SSMA', line=dict(color='indigo')),
                row=1, col=1
            )
        
        if 'TRIX' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['TRIX'].fillna(method='ffill'), name='TRIX', line=dict(color='darkorange')),
                row=4, col=1
            )

        # Add volume (row 2)
        fig.add_trace(
            go.Bar(
                x=data.index,
                y=data['Volume'],
                name='Volume',
                marker_color='lightblue'
            ),
            row=2, col=1
        )

        # Add oscillators to row 3
        if 'RSI' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['RSI'].fillna(method='ffill'), mode='lines', name='RSI', line=dict(color='purple')),
                row=3, col=1
            )
            fig.add_hline(y=70, line_dash="dash", line_color="red", row=3, col=1)
            fig.add_hline(y=30, line_dash="dash", line_color="green", row=3, col=1)

        if 'StochRSI' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['StochRSI'].fillna(method='ffill'), mode='lines', name='StochRSI', line=dict(color='orange')),
                row=3, col=1
            )
            fig.add_hline(y=80, line_dash="dash", line_color="red", row=3, col=1)
            fig.add_hline(y=20, line_dash="dash", line_color="green", row=3, col=1)

        if 'CCI' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['CCI'].fillna(method='ffill'), mode='lines', name='CCI', line=dict(color='blue')),
                row=3, col=1
            )
            fig.add_hline(y=100, line_dash="dash", line_color="red", row=3, col=1)
            fig.add_hline(y=-100, line_dash="dash", line_color="green", row=3, col=1)

        if 'ADX' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['ADX'].fillna(method='ffill'), mode='lines', name='ADX', line=dict(color='cyan')),
                row=3, col=1
            )
            fig.add_hline(y=25, line_dash="dash", line_color="gray", row=3, col=1)

        if 'Fisher' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['Fisher'].fillna(method='ffill'), mode='lines', name='Fisher Transform', line=dict(color='magenta')),
                row=3, col=1
            )

        if 'AO' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['AO'].fillna(method='ffill'), mode='lines', name='Awesome Oscillator', line=dict(color='green')),
                row=3, col=1
            )
            fig.add_hline(y=0, line_dash="dash", line_color="gray", row=3, col=1)

        if 'MI' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['MI'].fillna(method='ffill'), mode='lines', name='Mass Index', line=dict(color='purple')),
                row=3, col=1
            )
            fig.add_hline(y=27, line_dash="dash", line_color="red", row=3, col=1)

        if 'IFT_RSI' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['IFT_RSI'].fillna(method='ffill'), mode='lines', name='IFT RSI', line=dict(color='orange')),
                row=3, col=1
            )

        # Add momentum and volume indicators to row 4
        if 'MACD' in indicators:
            macd = indicators['MACD']
            macd_line = macd['MACD']
            signal_line = macd['SIGNAL']
            macd_histogram = macd_line - signal_line
            fig.add_trace(
                go.Scatter(x=data.index, y=macd_line.fillna(method='ffill'), mode='lines', name='MACD', line=dict(color='#04c6fc')),
                row=4, col=1
            )
            fig.add_trace(
                go.Scatter(x=data.index, y=signal_line.fillna(method='ffill'), mode='lines', name='MACD Signal', line=dict(color='blue', dash='dash')),
                row=4, col=1
            )
            fig.add_trace(
                go.Bar(x=data.index, y=macd_histogram.fillna(0), name='MACD Histogram', marker_color=['green' if val >= 0 else 'red' for val in macd_histogram]),
                row=4, col=1
            )
        
        if 'MOM' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['MOM'].fillna(method='ffill'), name='MOM', line=dict(color='lime')),
                row=4, col=1
            )
            
        if 'WOBV' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['WOBV'].fillna(method='ffill'), name='WOBV', line=dict(color='darkblue', dash='dot')),
                row=4, col=1
            )


        if 'DYMI' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['DYMI'].fillna(method='ffill'), name='DYMI', line=dict(color='crimson')),
                row=4, col=1
            )

        if 'TSI' in indicators:
            tsi = indicators['TSI']
            fig.add_trace(
                go.Scatter(x=data.index, y=tsi['TSI'].fillna(method='ffill'), name='TSI', line=dict(color='blue')),
                row=4, col=1
            )
            fig.add_trace(
                go.Scatter(x=data.index, y=tsi['signal'].fillna(method='ffill'), name='TSI Signal', line=dict(color='blue', dash='dash')),
                row=4, col=1
            )

        if 'KST' in indicators:
            kst = indicators['KST']
            fig.add_trace(
                go.Scatter(x=data.index, y=kst['KST'].fillna(method='ffill'), name='KST', line=dict(color='purple')),
                row=4, col=1
            )
            fig.add_trace(
                go.Scatter(x=data.index, y=kst['signal'].fillna(method='ffill'), name='KST Signal', line=dict(color='purple', dash='dot')),
                row=4, col=1
            )

        if 'PPO' in indicators:
            ppo = indicators['PPO']
            fig.add_trace(
                go.Scatter(x=data.index, y=ppo['PPO'].fillna(method='ffill'), name='PPO', line=dict(color='cyan')),
                row=4, col=1
            )
            fig.add_trace(
                go.Scatter(x=data.index, y=ppo['PPO_signal'].fillna(method='ffill'), name='PPO Signal', line=dict(color='cyan', dash='dash')),
                row=4, col=1
            )
            fig.add_trace(
                go.Bar(x=data.index, y=ppo['PPO_histo'].fillna(0), name='PPO Histogram', marker_color=['green' if val >= 0 else 'red' for val in ppo['PPO_histo']]),
                row=4, col=1
            )

        if 'CMO' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['CMO'].fillna(method='ffill'), name='CMO', line=dict(color='orange')),
                row=4, col=1
            )
            fig.add_hline(y=50, line_dash="dash", line_color="red", row=4, col=1)
            fig.add_hline(y=-50, line_dash="dash", line_color="green", row=4, col=1)

        if 'ROC' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['ROC'].fillna(method='ffill'), name='ROC', line=dict(color='green')),
                row=4, col=1
            )
            fig.add_hline(y=0, line_dash="dash", line_color="gray", row=4, col=1)

        if 'UO' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['UO'].fillna(method='ffill'), name='Ultimate Oscillator', line=dict(color='purple')),
                row=4, col=1
            )
            fig.add_hline(y=70, line_dash="dash", line_color="red", row=4, col=1)
            fig.add_hline(y=30, line_dash="dash", line_color="green", row=4, col=1)

        if 'OBV' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['OBV'].fillna(method='ffill'), name='OBV', line=dict(color='blue')),
                row=4, col=1
            )

        if 'ADL' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['ADL'].fillna(method='ffill'), name='ADL', line=dict(color='cyan')),
                row=4, col=1
            )

        if 'EFI' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['EFI'].fillna(method='ffill'), name='EFI', line=dict(color='magenta')),
                row=4, col=1
            )

        if 'EMV' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['EMV'].fillna(method='ffill'), name='EMV', line=dict(color='orange')),
                row=4, col=1
            )

        if 'MFI' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['MFI'].fillna(method='ffill'), name='MFI', line=dict(color='blue')),
                row=4, col=1
            )
            fig.add_hline(y=80, line_dash="dash", line_color="red", row=4, col=1)
            fig.add_hline(y=20, line_dash="dash", line_color="green", row=4, col=1)

        if 'VPT' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['VPT'].fillna(method='ffill'), name='VPT', line=dict(color='blue', dash='dot')),
                row=4, col=1
            )

        if 'FVE' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['FVE'].fillna(method='ffill'), name='FVE', line=dict(color='blue', dash='dot')),
                row=4, col=1
            )

        if 'VZO' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['VZO'].fillna(method='ffill'), name='VZO', line=dict(color='blue', dash='dot')),
                row=4, col=1
            )
            fig.add_hline(y=40, line_dash="dash", line_color="green", row=4, col=1)
            fig.add_hline(y=5, line_dash="dash", line_color="red", row=4, col=1)
            fig.add_hline(y=-5, line_dash="dash", line_color="red", row=4, col=1)
            fig.add_hline(y=-40, line_dash="dash", line_color="green", row=4, col=1)

        if 'WTO' in indicators:
            wto = indicators['WTO']
            fig.add_trace(
                go.Scatter(x=data.index, y=wto['WT1'].fillna(method='ffill'), name='WTO WT1', line=dict(color='cyan')),
                row=4, col=1
            )
            fig.add_trace(
                go.Scatter(x=data.index, y=wto['WT2'].fillna(method='ffill'), name='WTO WT2', line=dict(color='cyan', dash='dash')),
                row=4, col=1
            )

        if 'Coppock' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['Coppock'].fillna(method='ffill'), name='Coppock Curve', line=dict(color='purple')),
                row=4, col=1
            )
            fig.add_hline(y=0, line_dash="dash", line_color="gray", row=4, col=1)

        if 'BASP' in indicators:
            basp = indicators['BASP']
            fig.add_trace(
                go.Scatter(x=data.index, y=basp['Buy'].fillna(method='ffill'), name='BASP Buy', line=dict(color='green')),
                row=4, col=1
            )
            fig.add_trace(
                go.Scatter(x=data.index, y=basp['Sell'].fillna(method='ffill'), name='BASP Sell', line=dict(color='red')),
                row=4, col=1
            )

        if 'BASPN' in indicators:
            baspn = indicators['BASPN']
            fig.add_trace(
                go.Scatter(x=data.index, y=baspn['BASPN_Buy'].fillna(method='ffill'), name='BASPN Buy', line=dict(color='limegreen')),
                row=4, col=1
            )
            fig.add_trace(
                go.Scatter(x=data.index, y=baspn['BASPN_Sell'].fillna(method='ffill'), name='BASPN Sell', line=dict(color='coral')),
                row=4, col=1
            )

        if 'DMI' in indicators:
            dmi = indicators['DMI']
            fig.add_trace(
                go.Scatter(x=data.index, y=dmi['+DI'].fillna(method='ffill'), name='+DI', line=dict(color='blue')),
                row=4, col=1
            )
            fig.add_trace(
                go.Scatter(x=data.index, y=dmi['-DI'].fillna(method='ffill'), name='-DI', line=dict(color='red')),
                row=4, col=1
            )

        if 'EBBP' in indicators:
            ebbp = indicators['EBBP']
            fig.add_trace(
                go.Scatter(x=data.index, y=ebbp['Bull'].fillna(method='ffill'), name='Bull Power', line=dict(color='green')),
                row=4, col=1
            )
            fig.add_trace(
                go.Scatter(x=data.index, y=ebbp['Bear'].fillna(method='ffill'), name='Bear Power', line=dict(color='red')),
                row=4, col=1
            )

        if 'ATR' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['ATR'].fillna(method='ffill'), name='ATR', line=dict(color='blue')),
                row=4, col=1
            )
            
        if 'QSTICK' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['QSTICK'].fillna(method='ffill'), name='Q Stick', line=dict(color='gold')),
                row=4, col=1
            )

        if 'VBM' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['VBM'].fillna(method='ffill'), name='VBM', line=dict(color='orange')),
                row=4, col=1
            )
        
        if 'CFI' in indicators:
            fig.add_trace(
                go.Scatter(x=data.index, y=indicators['CFI'].fillna(method='ffill'), name='CFI', line=dict(color='deepskyblue')),
                row=4, col=1
            )


            
        # Update layout
        fig.update_layout(
            title=f'{symbol.upper()} - Technical Analysis',
            xaxis_rangeslider_visible=False,
            height=800,
            showlegend=True
        )
        
        st.plotly_chart(fig, use_container_width=True)
        
        # Display indicator values in tabs
        st.subheader("📊 Indicator Values")
        
        # Create tabs for different categories
        tab1, tab2, tab3, tab4, tab5 = st.tabs(["Trend", "Momentum", "Volume", "Volatility", "Oscillators"])
        
        with tab1:
            st.markdown("### Trend Indicators")
            trend_cols = st.columns(3)
            col_idx = 0
            
            for name, indicator in indicators.items():
                if name in ['SMA', 'EMA', 'HMA', 'WMA', 'KAMA', 'FRAMA', 'EVWMA', 'VWAP']:
                    with trend_cols[col_idx % 3]:
                        if isinstance(indicator, pd.Series):
                            st.metric(name, f"{indicator.iloc[-1]:.2f}")
                        col_idx += 1
        
        with tab2:
            st.markdown("### Momentum Indicators")
            momentum_cols = st.columns(3)
            col_idx = 0
            
            for name, indicator in indicators.items():
                if name in ['RSI', 'StochRSI', 'CMO', 'ROC', 'UO']:
                    with momentum_cols[col_idx % 3]:
                        if isinstance(indicator, pd.Series):
                            st.metric(name, f"{indicator.iloc[-1]:.2f}")
                        col_idx += 1
        
        with tab3:
            st.markdown("### Volume Indicators")
            volume_cols = st.columns(3)
            col_idx = 0
            
            for name, indicator in indicators.items():
                if name in ['OBV', 'ADL', 'EFI', 'EMV', 'MFI', 'VPT', 'FVE', 'VZO']:
                    with volume_cols[col_idx % 3]:
                        if isinstance(indicator, pd.Series):
                            st.metric(name, f"{indicator.iloc[-1]:.2f}")
                        col_idx += 1
        
        with tab4:
            st.markdown("### Volatility Indicators")
            volatility_cols = st.columns(3)
            col_idx = 0
            
            for name, indicator in indicators.items():
                if name in ['ATR', 'PSAR']:
                    with volatility_cols[col_idx % 3]:
                        if isinstance(indicator, pd.Series):
                            st.metric(name, f"{indicator.iloc[-1]:.2f}")
                        col_idx += 1
        
        with tab5:
            st.markdown("### Oscillators")
            osc_cols = st.columns(3)
            col_idx = 0
            
            for name, indicator in indicators.items():
                if name in ['ADX', 'CCI', 'Fisher', 'AO', 'MI']:
                    with osc_cols[col_idx % 3]:
                        if isinstance(indicator, pd.Series):
                            st.metric(name, f"{indicator.iloc[-1]:.2f}")
                        col_idx += 1
        
        # Raw data section
        with st.expander("📋 Raw Data"):
            st.dataframe(data.tail(50))
        
        # Download section
        st.subheader("💾 Download Data")
        
        # Combine all indicators into one DataFrame
        combined_df = data.copy()
        for name, indicator in indicators.items():
            if isinstance(indicator, pd.Series):
                combined_df[name] = indicator
            elif isinstance(indicator, pd.DataFrame):
                for col in indicator.columns:
                    combined_df[f"{name}_{col}"] = indicator[col]
        
        csv = combined_df.to_csv()
        st.download_button(
            label="Download CSV",
            data=csv,
            file_name=f'{symbol}_technical_analysis.csv',
            mime='text/csv'
        )
        
    except Exception as e:
        st.error(f"An error occurred: {str(e)}")
        st.error("Please check your internet connection and try again.")

# Instructions
else:
    st.markdown("""
    ## 🚀 How to Use This Dashboard
    
    1. **Enter a stock symbol** in the sidebar (e.g., AAPL, GOOGL, MSFT) for Indian Stocks, use NSE symbols like RELIANCE.NS
    or BHEL.NS.
    2. **Select time period and interval** for the data
    3. **Choose technical indicators** you want to analyze
    4. **Adjust parameters** for the indicators
    5. **Click "Analyze Stock"** to generate the analysis
    
    ### 📈 Available Indicators
    
    This dashboard includes **50+ technical indicators** across multiple categories:
    
    - **Trend Indicators**: SMA, EMA, HMA, WMA, KAMA, FRAMA, EVWMA, VWAP
    - **Momentum Indicators**: RSI, MACD, Stochastic RSI, CMO, ROC, TSI, KST, PPO, UO
    - **Volume Indicators**: OBV, ADL, Chaikin Oscillator, EFI, EMV, MFI, VPT, FVE, VZO
    - **Volatility Indicators**: Bollinger Bands, Keltner Channels, Donchian Channels, ATR, Chandelier Exit, Parabolic SAR
    - **Oscillators**: ADX, CCI, Fisher Transform, Awesome Oscillator, Mass Index, Wave Trend Oscillator
    - **Complex Indicators**: Ichimoku Cloud, Pivot Points, Fibonacci Pivots, BASP, DMI, Elder Bull/Bear Power
    
    ### 💡 Tips
    
    - Use multiple indicators together for better analysis
    - Adjust parameters based on your trading timeframe
    - Download the data for further analysis
    - Check different time periods to understand trends
    """)

# Footer
st.markdown("---")
st.markdown("**Technical Analysis Dashboard** | Built with Streamlit & Python | Data from Yahoo Finance")
st.markdown("---")
st.markdown("**Made By Zane Vijay Falcao**")