Rename Gradio to app.py

Gradio → app.py

@@ -5,47 +5,35 @@ import matplotlib.pyplot as plt
 import gradio as gr
 import io
 
-def test_function(name):
-    return f"Hello, {name}!"
-
-app = gr.Interface(fn=test_function, inputs="text", outputs="text")
-app.launch()
-
-
-print("Starting app...")
-
-try:
-    import pandas as pd
-    print("Pandas imported.")
-    import yfinance as yf
-    print("yfinance imported.")
-    import numpy as np
-    print("NumPy imported.")
-    import matplotlib.pyplot as plt
-    print("Matplotlib imported.")
-    import gradio as gr
-    print("Gradio imported.")
-except Exception as e:
-    print(f"Error importing libraries: {e}")
-    raise
-
+print("App is starting...")
 
+# Define the SMA Crossover Trading Strategy Function
 def sma_crossover_strategy(initial_budget, start_date, end_date, ticker):
+    print(f"Fetching data for {ticker} from {start_date} to {end_date}...")
     try:
+        # Fetch stock data
         df = yf.download(ticker, start=start_date, end=end_date, progress=False)
         if df.empty:
+            print("No data fetched. Returning error message.")
             return None, "No data available for the specified ticker and date range.", None
     except Exception as e:
+        print(f"Error fetching data: {str(e)}")
         return None, f"Error fetching data: {str(e)}", None
 
+    # Calculate SMAs
+    print("Calculating SMAs...")
     df = df[['Close']]
     df['SMA_50'] = df['Close'].rolling(window=50).mean()
     df['SMA_150'] = df['Close'].rolling(window=150).mean()
+
+    # Define signals
     df['Signal'] = 0
     df['Signal'][df['SMA_50'] > df['SMA_150']] = 1
     df['Signal'][df['SMA_50'] < df['SMA_150']] = -1
     df['Position'] = df['Signal'].diff()
 
+    # Initialize portfolio simulation
+    print("Simulating portfolio...")
     cash = initial_budget
     shares = 0
     portfolio_values = []
@@ -53,18 +41,23 @@ def sma_crossover_strategy(initial_budget, start_date, end_date, ticker):
     for index, row in df.iterrows():
         if pd.isna(row['Close']):
             continue
-        if row['Position'] == 1 and cash > 0:
+        if row['Position'] == 1 and cash > 0:  # Buy signal
             shares = cash / row['Close']
             cash = 0
-        elif row['Position'] == -1 and shares > 0:
+        elif row['Position'] == -1 and shares > 0:  # Sell signal
             cash = shares * row['Close']
             shares = 0
+
+        # Calculate current portfolio value
         portfolio_value = cash + (shares * row['Close'])
         portfolio_values.append(portfolio_value)
 
+    # Handle missing data at the start
     df = df.iloc[149:]
     df['Portfolio Value'] = portfolio_values[149:]
 
+    # Generate plot
+    print("Generating plot...")
     plt.figure(figsize=(14, 8))
     plt.plot(df['Portfolio Value'], label='Portfolio Value', color='purple')
     plt.xlabel('Date')
@@ -74,11 +67,13 @@ def sma_crossover_strategy(initial_budget, start_date, end_date, ticker):
     plt.grid()
     plt.tight_layout()
 
+    # Save plot to in-memory buffer
     plot_file = io.BytesIO()
     plt.savefig(plot_file, format='png')
     plot_file.seek(0)
     plt.close()
 
+    # Final portfolio summary
     final_value = portfolio_values[-1]
     profit_loss = final_value - initial_budget
     percentage_return = (profit_loss / initial_budget) * 100
@@ -94,10 +89,13 @@ def sma_crossover_strategy(initial_budget, start_date, end_date, ticker):
 
     return plot_file, results, None
 
+# Create Gradio Interface
+print("Setting up Gradio app...")
 with gr.Blocks() as app:
     gr.Markdown("# SMA Crossover Trading Strategy Simulator")
 
     with gr.Tabs():
+        # SMA Strategy Simulator Tab
         with gr.Tab("SMA Strategy Simulator"):
             with gr.Row():
                 initial_budget = gr.Number(label="Initial Investment ($)", value=100, interactive=True)
@@ -113,6 +111,7 @@ with gr.Blocks() as app:
                 portfolio_graph = gr.Image(label="Portfolio Value Over Time")
                 summary_text = gr.Textbox(label="Simulation Summary", lines=8)
 
+        # Instructions Tab
         with gr.Tab("Instructions"):
             gr.Markdown("""
             ## How to Use:
@@ -122,11 +121,14 @@ with gr.Blocks() as app:
             4. Click "Run Simulation" to visualize the portfolio value over time and view a summary of results.
             """)
 
+    # Connect simulation function to Gradio app
     run_button.click(
         sma_crossover_strategy,
         inputs=[initial_budget, start_date, end_date, ticker],
         outputs=[portfolio_graph, summary_text],
     )
 
+print("Launching Gradio app...")
 app.launch()
 
+