Update app.py

app.py

@@ -127,21 +127,21 @@ def download_data(tickers, start_date, end_date, interval, output_dir):
     """
     downloaded = []
     os.makedirs(output_dir, exist_ok=True)
-    for ticker in tickers:
-        st.info(f"Downloading data for {ticker}...")
+
+    progress_bar = st.progress(0)
+    for i, ticker in enumerate(tickers):
         try:
             stock = yf.Ticker(ticker)
             data = stock.history(
                 start=start_date, end=end_date, interval=interval)
-            if data.empty:
-                st.warning(f"No data returned for {ticker}. Skipping.")
-                continue
-            output_file = os.path.join(output_dir, f"{ticker}.csv")
-            data.to_csv(output_file)
-            downloaded.append(ticker)
-            st.success(f"Saved data for {ticker} to {output_file}")
-        except Exception as e:
-            st.error(f"Error downloading data for {ticker}: {e}")
+            if not data.empty:
+                output_file = os.path.join(output_dir, f"{ticker}.csv")
+                data.to_csv(output_file)
+                downloaded.append(ticker)
+        except Exception:
+            pass
+        progress_bar.progress((i + 1) / len(tickers))
+    progress_bar.empty()
     return downloaded
 
 # -----------------------------
@@ -197,22 +197,41 @@ def main():
         st.header("Controls")
 
         # Exclude the "test" group
-        available_groups = [grp for grp in market_config.get(
-            'groups', {}).keys() if grp.lower() != "test"]
-        # Default to "all" if available, else first available group.
-        default_group = "all" if "all" in available_groups else available_groups[0]
-        selected_groups = st.multiselect(
-            "Select Asset Groups", available_groups, default=[default_group])
-
-        # Build the union of tickers from the selected groups
-        all_tickers = []
-        for group in selected_groups:
-            group_tickers = market_config['groups'][group]
-            all_tickers.extend(group_tickers)
-        all_tickers = sorted(set(all_tickers))
-
-        # Select tickers from the combined list
-        selected_tickers = st.multiselect("Select Tickers", all_tickers)
+        # Direct Ticker Input
+        ticker_input = st.text_input('Enter Ticker Symbol (e.g., AAPL):')
+
+        # Optional Asset Group Selection
+        use_groups = st.checkbox('Or select from predefined groups')
+
+        selected_tickers = []
+
+        if ticker_input:
+            selected_tickers.append(ticker_input.upper().strip())
+
+        if use_groups:
+
+            available_groups = [grp for grp in market_config.get(
+                'groups', {}).keys() if grp.lower() != "test"]
+
+            selected_groups = st.multiselect(
+                "Select Asset Groups", available_groups)
+
+            # Build the union of tickers from the selected groups
+
+            group_tickers = []
+
+            for group in selected_groups:
+
+                group_tickers.extend(market_config['groups'][group])
+
+            group_tickers = sorted(set(group_tickers))
+
+            if group_tickers:
+
+                group_selected = st.multiselect(
+                    "Select Additional Tickers from Groups:", group_tickers)
+
+                selected_tickers.extend(group_selected)
 
         # Date Range Selection
         default_end = date.today()
@@ -475,7 +494,8 @@ def main():
                         if show_var:
                             var = predictor.calculate_var(
                                 combined_data[ticker])
-                            st.write(f"Value at Risk (95%) for {ticker}: {var:.2%}")
+                            st.write(
+                                f"Value at Risk (95%) for {ticker}: {var:.2%}")
                         if show_patterns or show_breakouts:
                             ticker_data = load_ticker_data(output_dir, ticker)
                             if ticker_data is not None:
@@ -525,8 +545,8 @@ def main():
                    - Data is downloaded automatically.
                 
                 3. **Configure Predictives & Risk Tools** 🤖📊
-                   - Our predictive models combine historical data with real-time market signals to forecast trends—helping you anticipate price movements and spot emerging opportunities.
-                   - Our risk analysis tools compute key metrics like Value at Risk (VaR) and perform stress tests to evaluate potential losses, giving you critical insights into risk exposure.
+                   - Predictive models combine historical data with real-time market signals to forecast trends—helping anticipate price movements and spot emerging opportunities.
+                   - Risk analysis tools compute key metrics like Value at Risk (VaR) and perform stress tests to evaluate potential losses, giving critical insights into risk exposure.
                    - Configure these tools to complement your overall technical analysis.
                 
                 4. **Enhance Your Analysis with Indicators** ⚙️