app.py

import streamlit as st
import yfinance as yf
import plotly.graph_objects as go
import plotly.express as px
from datetime import datetime, timedelta
import pandas as pd
import numpy as np
from utils.database import init_db

# Configure the page
st.set_page_config(
    page_title="Stock Market Analysis",
    page_icon="📈",
    layout="wide",
    initial_sidebar_state="expanded"
)

# Initialize database
if 'db_initialized' not in st.session_state:
    st.session_state.db_initialized = init_db()

# Main page content
st.title("📈 Stock Market Analysis Dashboard")
st.markdown("---")

# Introduction
st.markdown("""
### Welcome to the Stock Market Analysis Dashboard

This comprehensive platform provides:
- **Real-time stock data** and historical analysis
- **Interactive charts** with multiple timeframes
- **Technical indicators** (Moving Averages, RSI, MACD, etc.)
- **Portfolio tracking** and performance monitoring
- **Stock comparison** tools

Navigate through the sidebar to explore different features.
""")

# Quick market overview
st.subheader("📊 Market Overview")

# Mixed portfolio for global overview
popular_stocks = ['AAPL', 'GOOGL', 'MSFT', 'RELIANCE.NS', 'TCS.NS', 'HDFCBANK.NS', 'TSLA', 'NVDA']

try:
    with st.spinner("Loading market overview..."):
        # Create columns for displaying stock cards
        cols = st.columns(4)
        
        for i, symbol in enumerate(popular_stocks[:8]):
            with cols[i % 4]:
                try:
                    stock = yf.Ticker(symbol)
                    info = stock.info
                    hist = stock.history(period="2d")
                    
                    if len(hist) >= 2:
                        current_price = hist['Close'].iloc[-1]
                        prev_price = hist['Close'].iloc[-2]
                        change = current_price - prev_price
                        change_pct = (change / prev_price) * 100
                        
                        # Color based on performance
                        color = "green" if change >= 0 else "red"
                        arrow = "↗️" if change >= 0 else "↘️"
                        
                        # Format currency based on market
                        currency_symbol = "₹" if ".NS" in symbol else "$"
                        
                        st.metric(
                            label=f"{symbol}",
                            value=f"{currency_symbol}{current_price:.2f}",
                            delta=f"{change_pct:.2f}%"
                        )
                except Exception as e:
                    st.error(f"Error loading {symbol}: {str(e)}")
                    
except Exception as e:
    st.error(f"Error loading market overview: {str(e)}")

st.markdown("---")

# Quick stock lookup
st.subheader("🔍 Quick Stock Lookup")

col1, col2 = st.columns([2, 1])

with col1:
    symbol_input = st.text_input(
        "Enter a stock symbol (e.g., AAPL, GOOGL, MSFT):",
        placeholder="AAPL"
    ).upper()

with col2:
    st.write("")  # Spacing
    lookup_button = st.button("🔍 Lookup Stock", type="primary")

if lookup_button and symbol_input:
    try:
        with st.spinner(f"Fetching data for {symbol_input}..."):
            stock = yf.Ticker(symbol_input)
            info = stock.info
            hist = stock.history(period="1mo")
            
            if not hist.empty:
                col1, col2, col3 = st.columns(3)
                
                with col1:
                    # Format currency for quick lookup
                    current_lookup_price = hist['Close'].iloc[-1]
                    prev_lookup_price = hist['Close'].iloc[-2] if len(hist) > 1 else current_lookup_price
                    lookup_change_pct = ((current_lookup_price - prev_lookup_price) / prev_lookup_price * 100) if prev_lookup_price != 0 else 0
                    lookup_currency = "₹" if ".NS" in symbol_input else "$"
                    
                    st.metric(
                        "Current Price",
                        f"{lookup_currency}{current_lookup_price:.2f}",
                        f"{lookup_change_pct:.2f}%"
                    )
                
                with col2:
                    st.metric("Volume", f"{hist['Volume'].iloc[-1]:,}")
                
                with col3:
                    st.metric("Market Cap", info.get('marketCap', 'N/A'))
                
                # Simple price chart
                fig = go.Figure()
                fig.add_trace(go.Scatter(
                    x=hist.index,
                    y=hist['Close'],
                    mode='lines',
                    name='Close Price',
                    line=dict(color='#1f77b4', width=2)
                ))
                
                fig.update_layout(
                    title=f"{symbol_input} - 1 Month Price Chart",
                    xaxis_title="Date",
                    yaxis_title="Price ($)",
                    height=400,
                    showlegend=False
                )
                
                st.plotly_chart(fig, use_container_width=True)
                
                # Company info
                if 'longName' in info:
                    st.write(f"**Company:** {info['longName']}")
                if 'sector' in info:
                    st.write(f"**Sector:** {info['sector']}")
                if 'industry' in info:
                    st.write(f"**Industry:** {info['industry']}")
            else:
                st.error(f"No data found for symbol: {symbol_input}")
                
    except Exception as e:
        st.error(f"Error fetching data for {symbol_input}: {str(e)}")

st.markdown("---")

# Navigation guide
st.subheader("🧭 Navigation Guide")

nav_col1, nav_col2 = st.columns(2)

with nav_col1:
    st.markdown("""
    **📈 Stock Analysis**
    - View detailed stock information
    - Interactive price charts
    - Multiple timeframes
    - Company fundamentals
    - Support for US and NSE stocks
    
    **📊 Technical Indicators**
    - Moving Averages (SMA, EMA)
    - RSI, MACD, Bollinger Bands
    - Volume analysis
    - Custom indicator settings
    """)

with nav_col2:
    st.markdown("""
    **💼 Portfolio Tracker**
    - Track your investments
    - Portfolio performance
    - Profit/Loss calculations
    - Diversification analysis
    
    **🔍 Stock Comparison**
    - Compare multiple stocks
    - Side-by-side analysis
    - Performance correlation
    - Relative strength
    
    **🔮 Price Prediction**
    - AI-powered weekly forecasts
    - Machine learning analysis
    - Confidence intervals
    - Technical factor insights
    
    **🇮🇳 NSE Stocks**
    - Indian stock market analysis
    - NSE-specific features
    - Currency in Indian Rupees
    - Major Indian companies
    """)

# Footer
st.markdown("---")
st.markdown("""
<div style='text-align: center; color: #666;'>
    <p>📊 Stock Market Analysis Dashboard | Built with Streamlit & yfinance</p>
    <p><small>⚠️ This is for educational purposes only. Not financial advice.</small></p>
</div>
""", unsafe_allow_html=True)