import streamlit as st
import os
import pandas as pd
from dotenv import load_dotenv

# ==============================
# Utility Functions
# ==============================

def load_env_variables():
    """Load environment variables from a .env file."""
    load_dotenv()

def fetch_data(symbol):
    """Fetch data for a given symbol (placeholder logic)."""
    try:
        # Replace with actual data fetching logic if needed
        return {"symbol": symbol, "data": "sample data"}
    except Exception as e:
        raise ValueError(f"Error fetching data for {symbol}: {e}")

# ==============================
# Page Functions
# ==============================

def render_home():
    st.title("ICT Core Toolkit v6")
    st.write("A comprehensive technical analysis tool for modern traders.")
    st.write("Developer: Makori Brian | Support the developer by [link]")
    st.subheader("Mission Statement")
    st.write(
        "The ICT Core Toolkit v6 aims to empower traders with advanced technical analysis tools, real-time alerts, and automated trading capabilities."
    )

def render_profile():
    st.title("User Profile")
    
    # Retrieve or initialize favorite assets in session state
    favorite_assets = st.session_state.get("favorite_assets", [])
    
    # Add favorite assets
    asset = st.text_input("Add Favorite Asset")
    if st.button("Add"):
        if asset:
            favorite_assets.append(asset)
            st.session_state["favorite_assets"] = favorite_assets
            st.success(f"{asset} added to favorites!")
    
    # Display favorite assets
    if favorite_assets:
        st.subheader("Your Favorite Assets")
        for asset in favorite_assets:
            st.write(asset)
    else:
        st.info("No favorite assets added yet.")
    
    # Public/Private sharing option
    visibility = st.radio("Set Visibility", ["Private", "Public"])
    if visibility == "Public":
        st.success("Your analysis is now visible to others.")
    else:
        st.info("Your analysis is private.")

def render_analysis():
    st.title("Technical Analysis")
    st.write("Perform advanced technical analysis on your favorite assets.")
    
    # Example: Load and display data
    try:
        # Replace 'example_data.csv' with your actual data source if available
        data = pd.read_csv("example_data.csv")
        st.line_chart(data)
        
        # Export functionality
        export_format = st.selectbox("Export Format", ["CSV", "Excel", "JSON"])
        if st.button("Export"):
            if export_format == "CSV":
                data.to_csv("exported_data.csv", index=False)
                st.success("Data exported to CSV!")
            elif export_format == "Excel":
                data.to_excel("exported_data.xlsx", index=False)
                st.success("Data exported to Excel!")
            elif export_format == "JSON":
                data.to_json("exported_data.json", orient="records")
                st.success("Data exported to JSON!")
    except Exception as e:
        st.error(f"Error loading data: {e}")

def render_automation():
    st.title("Automated Trading")
    st.write("Configure automated trading with Binance, Pepperstone, and cTrader.")
    
    broker = st.selectbox("Select Broker", ["Binance", "Pepperstone", "cTrader"])
    
    if broker == "Binance":
        api_key = st.text_input("Binance API Key", type="password")
        api_secret = st.text_input("Binance API Secret", type="password")
        if st.button("Connect", key="binance_connect"):
            # Here you would add connection logic using the API key/secret.
            st.success("Connected to Binance!")
    
    elif broker == "Pepperstone":
        client_id = st.text_input("Pepperstone Client ID")
        access_token = st.text_input("Pepperstone Access Token", type="password")
        if st.button("Connect", key="pepperstone_connect"):
            # Add connection logic for Pepperstone.
            st.success("Connected to Pepperstone!")
    
    elif broker == "cTrader":
        fix_endpoint = st.text_input("cTrader FIX Endpoint")
        if st.button("Connect", key="ctrader_connect"):
            # Add connection logic for cTrader.
            st.success("Connected to cTrader!")

def render_community():
    st.title("Community Analysis")
    st.write("Share your analysis and copy trades from other users.")
    
    public_private = st.radio("Set Visibility", ["Public", "Private"])
    if public_private == "Public":
        st.success("Your analysis is now visible to others.")
    else:
        st.info("Your analysis is private.")
    
    # Example: Display shared trades
    shared_trades = [
        {"user": "Trader1", "asset": "BTCUSD", "action": "Buy"},
        {"user": "Trader2", "asset": "NFLX", "action": "Sell"},
    ]
    if shared_trades:
        st.subheader("Shared Trades")
        for trade in shared_trades:
            st.write(f"{trade['user']} - {trade['asset']} - {trade['action']}")
    else:
        st.info("No shared trades available.")

# ==============================
# Main Application
# ==============================

def main():
    # Load environment variables
    load_env_variables()
    
    # Set page configuration
    st.set_page_config(page_title="ICT Core Toolkit v6", layout="wide")
    
    # Sidebar navigation
    pages = {
        "Home": render_home,
        "Profile": render_profile,
        "Analysis": render_analysis,
        "Automation": render_automation,
        "Community": render_community,
    }
    
    selection = st.sidebar.radio("Navigate", list(pages.keys()))
    
    # Render the selected page
    pages[selection]()

if __name__ == "__main__":
    main()