Update app.py

app.py

@@ -2,46 +2,26 @@ import pandas as pd
 import yfinance as yf
 import numpy as np
 import matplotlib.pyplot as plt
-import io
 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("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 = []
@@ -49,23 +29,18 @@ 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:  # Buy signal
+        if row['Position'] == 1 and cash > 0:
             shares = cash / row['Close']
             cash = 0
-        elif row['Position'] == -1 and shares > 0:  # Sell signal
+        elif row['Position'] == -1 and shares > 0:
             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')
@@ -75,13 +50,11 @@ 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
@@ -97,46 +70,28 @@ 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 ($)", value=100, interactive=True)
-                start_date = gr.Text(label="Start Date (YYYY-MM-DD)", value="1993-01-01", interactive=True)
-                end_date = gr.Text(label="End Date (YYYY-MM-DD)", value="2023-12-31", interactive=True)
-                ticker = gr.Dropdown(
-                    label="Stock Ticker Symbol",
-                    choices=["SPY", "TSLA", "GOOGL", "AAPL", "MSFT"],
-                    value="SPY",
-                )
-            run_button = gr.Button("Run Simulation")
-            with gr.Row():
-                portfolio_graph = gr.Image(label="Portfolio Value Over Time")
-                summary_text = gr.Textbox(label="Simulation Summary", lines=8)
-
-        # Instructions Tab
-        with gr.Tab("Instructions"):
-            gr.Markdown("""
-            ## How to Use:
-            1. Enter your initial investment amount.
-            2. Specify the trading period (start and end dates).
-            3. Select a stock ticker symbol (e.g., SPY, TSLA, GOOGL).
-            4. Click "Run Simulation" to visualize the portfolio value over time and view a summary of results.
-            """)
-
-    # Connect simulation function to Gradio app
+    with gr.Row():
+        initial_budget = gr.Number(label="Initial Investment ($)", value=100)
+        start_date = gr.Text(label="Start Date (YYYY-MM-DD)", value="1993-01-01")
+        end_date = gr.Text(label="End Date (YYYY-MM-DD)", value="2023-12-31")
+        ticker = gr.Dropdown(
+            label="Stock Ticker Symbol",
+            choices=["SPY", "TSLA", "GOOGL", "AAPL", "MSFT"],
+            value="SPY",
+        )
+    run_button = gr.Button("Run Simulation")
+    portfolio_graph = gr.Image(label="Portfolio Value Over Time")
+    summary_text = gr.Textbox(label="Simulation Summary", lines=8)
+
     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()