Update app.py

app.py

@@ -67,7 +67,7 @@ with demo:
         return gr.Dropdown(choices=stock_names, label='Please Select Stock from your selected index', interactive=True)
 
     d1.input(get_stocks_from_index, d1, d2)
-
+    
     def get_stock_graph(idx, stock, interval, graph_type, forecast_method):
         stock_name, ticker_name = stock.split(":")
         
@@ -75,17 +75,27 @@ with demo:
             ticker_name += '.L' if ticker_name[-1] != '.' else 'L'
         elif ticker_dict[idx] == 'CAC 40':
             ticker_name += '.PA'
-
+    
         series = yf.download(tickers=ticker_name, start=START_DATE, end=END_DATE, interval=interval)
         series = series.reset_index()
-
+    
         predictions = forecast_series(series, model=forecast_method)
-
+    
         last_date = pd.to_datetime(series['Date'].values[-1])
-        forecast_week = [last_date + timedelta(days=i) for i in range(1, FORECAST_PERIOD + 1) if is_business_day(last_date + timedelta(days=i))]
-
+        forecast_week = []
+        i = 1
+        while len(forecast_week) < FORECAST_PERIOD:
+            next_date = last_date + timedelta(days=i)
+            if is_business_day(next_date):
+                forecast_week.append(next_date)
+            i += 1
+    
+        # Ensure predictions and forecast_week have the same length
+        predictions = predictions[:len(forecast_week)]
+        forecast_week = forecast_week[:len(predictions)]
+    
         forecast = pd.DataFrame({"Date": forecast_week, "Forecast": predictions})
-
+    
         if graph_type == 'Line Graph':
             fig = go.Figure()
             fig.add_trace(go.Scatter(x=series['Date'], y=series['Close'], mode='lines', name='Historical'))
@@ -98,13 +108,12 @@ with demo:
                                                  close=series['Close'],
                                                  name='Historical')])
             fig.add_trace(go.Scatter(x=forecast['Date'], y=forecast['Forecast'], mode='lines', name='Forecast'))
-
+    
         fig.update_layout(title=f"Stock Price of {stock_name}",
                           xaxis_title="Date",
                           yaxis_title="Price")
-
+    
         return fig
-
     out = gr.Plot()
     inputs = [d1, d2, d3, d4, d5]
     d2.input(get_stock_graph, inputs, out)