import yfinance as yf
import pandas as pd
import matplotlib.pyplot as plt
import mplfinance as mpf

def create_beginner_friendly_candlestick_chart(ticker, period="6mo", interval="1d"):
    try:
        # Fetch stock data
        stock = yf.Ticker(ticker)
        df = stock.history(period=period, interval=interval)
        
        if df.empty:
            return "No data found for the stock", None
        
        # Ensure the index is a DatetimeIndex
        df.index = pd.to_datetime(df.index)
        
        # Prepare data for mplfinance
        df_mpl = df[['Open', 'High', 'Low', 'Close', 'Volume']]
        
        # Create a more straightforward mplfinance plot
        style = mpf.make_mpf_style(base_mpf_style='yahoo', rc={'font.size':10})
        
        # Save plot directly using mplfinance
        plot_path = f'{ticker}_candlestick_chart.png'
        mpf.plot(
            df_mpl, 
            type='candle', 
            volume=True, 
            title=f'{ticker} Stock Price - Candlestick Chart',
            style=style,
            savefig=plot_path
        )
        
        # Generate a beginner-friendly explanation
        explanation = f"""
        🕯️ Candlestick Chart Explained for {ticker}:

        What is a Candlestick?
        - Each 'candle' represents one day of trading
        - Shows four key price points: Open, Close, High, Low

        How to Read the Candles:
        🟢 Green Candle = Price Went Up
        - Bottom of candle = Opening Price
        - Top of candle = Closing Price
        
        🔴 Red Candle = Price Went Down
        - Top of candle = Opening Price
        - Bottom of candle = Closing Price

        Additional Insights:
        - Candle 'Wicks' show the highest and lowest prices of the day
        - Volume chart below shows how many shares were traded

        Recent Performance:
        - Latest Close Price: ${df['Close'][-1]:.2f}
        - Price Change: ${df['Close'][-1] - df['Close'][-2]:.2f}
        - Percentage Change: {((df['Close'][-1] / df['Close'][-2] - 1) * 100):.2f}%
        """
        
        return explanation, plot_path
    
    except Exception as e:
        return f"Error creating chart: {e}", None

# Gradio Interface for Candlestick Chart
import gradio as gr

def candlestick_interface(ticker, period, interval):
    explanation, plot_path = create_beginner_friendly_candlestick_chart(ticker, period, interval)
    return explanation, plot_path

# Create Gradio Interface
iface = gr.Interface(
    fn=candlestick_interface,
    inputs=[
        gr.Textbox(label="Stock Ticker (e.g., AAPL, MSFT)", value="AAPL"),
        gr.Textbox(label="Time Period (e.g., 6mo, 1y)", value="6mo"),
        gr.Textbox(label="Data Interval (e.g., 1d, 1h)", value="1d")
    ],
    outputs=[
        gr.Textbox(label="Candlestick Chart Explanation"),
        gr.Image(label="Candlestick Chart")
    ],
    title="Candlestick Chart Explained",
    description="Understand stock price movements with an easy-to-read candlestick chart"
)

# Launch the interface
iface.launch(share=True)