Create app.py

app.py

@@ -0,0 +1,91 @@
+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)