Update ui/ui_generators.py

ui/ui_generators.py

@@ -31,90 +31,7 @@ FORMULA_ICON = "ƒ"
 ACTIVE_ICON = "❌ Close" # Ensure this matches app.py
 
 
-def display_main_dashboard(token_state):
-    """Generates HTML for the main dashboard display using data from token_state."""
-    if not token_state or not token_state.get("token"):
-        logging.warning("Dashboard display: Access denied. No token available.")
-        return "❌ Access denied. No token available for dashboard."
-
-    html_parts = ["<div style='padding:10px;'><h3>Dashboard Overview</h3>"]
-
-    # Display Recent Posts
-    posts_df = token_state.get("bubble_posts_df", pd.DataFrame())
-    html_parts.append(f"<h4>Recent Posts ({len(posts_df)} in Bubble):</h4>")
-    if not posts_df.empty:
-        cols_to_show_posts = [col for col in [BUBBLE_POST_DATE_COLUMN_NAME, 'text', 'sentiment', 'summary_text', 'li_eb_label'] if col in posts_df.columns]
-        if not cols_to_show_posts:
-            html_parts.append("<p>No relevant post columns found to display.</p>")
-        else:
-            display_df_posts = posts_df.copy()
-            if BUBBLE_POST_DATE_COLUMN_NAME in display_df_posts.columns:
-                try:
-                    # Ensure the date column is datetime before formatting
-                    display_df_posts[BUBBLE_POST_DATE_COLUMN_NAME] = pd.to_datetime(display_df_posts[BUBBLE_POST_DATE_COLUMN_NAME], errors='coerce')
-                    display_df_posts = display_df_posts.sort_values(by=BUBBLE_POST_DATE_COLUMN_NAME, ascending=False)
-                    # Format for display after sorting
-                    display_df_posts[BUBBLE_POST_DATE_COLUMN_NAME] = display_df_posts[BUBBLE_POST_DATE_COLUMN_NAME].dt.strftime(UI_DATE_FORMAT)
-                except Exception as e:
-                    logging.error(f"Error formatting post dates for display: {e}")
-                    html_parts.append("<p>Error formatting post dates.</p>")
-            html_parts.append(display_df_posts[cols_to_show_posts].head().to_html(escape=False, index=False, classes="table table-striped table-sm"))
-    else:
-        html_parts.append("<p>No posts loaded from Bubble.</p>")
-    html_parts.append("<hr/>")
-
-    # Display Recent Mentions
-    mentions_df = token_state.get("bubble_mentions_df", pd.DataFrame())
-    html_parts.append(f"<h4>Recent Mentions ({len(mentions_df)} in Bubble):</h4>")
-    if not mentions_df.empty:
-        cols_to_show_mentions = [col for col in [BUBBLE_MENTIONS_DATE_COLUMN_NAME, "mention_text", "sentiment_label"] if col in mentions_df.columns]
-        if not cols_to_show_mentions:
-            html_parts.append("<p>No relevant mention columns found to display.</p>")
-        else:
-            display_df_mentions = mentions_df.copy()
-            if BUBBLE_MENTIONS_DATE_COLUMN_NAME in display_df_mentions.columns:
-                try:
-                    display_df_mentions[BUBBLE_MENTIONS_DATE_COLUMN_NAME] = pd.to_datetime(display_df_mentions[BUBBLE_MENTIONS_DATE_COLUMN_NAME], errors='coerce')
-                    display_df_mentions = display_df_mentions.sort_values(by=BUBBLE_MENTIONS_DATE_COLUMN_NAME, ascending=False)
-                    display_df_mentions[BUBBLE_MENTIONS_DATE_COLUMN_NAME] = display_df_mentions[BUBBLE_MENTIONS_DATE_COLUMN_NAME].dt.strftime(UI_DATE_FORMAT)
-                except Exception as e:
-                    logging.error(f"Error formatting mention dates for display: {e}")
-                    html_parts.append("<p>Error formatting mention dates.</p>")
-            html_parts.append(display_df_mentions[cols_to_show_mentions].head().to_html(escape=False, index=False, classes="table table-striped table-sm"))
-    else:
-        html_parts.append("<p>No mentions loaded from Bubble.</p>")
-    html_parts.append("<hr/>")
-
-    # Display Follower Statistics Summary
-    follower_stats_df = token_state.get("bubble_follower_stats_df", pd.DataFrame())
-    html_parts.append(f"<h4>Follower Statistics ({len(follower_stats_df)} entries in Bubble):</h4>")
-    if not follower_stats_df.empty:
-        monthly_gains = follower_stats_df[follower_stats_df[FOLLOWER_STATS_TYPE_COLUMN] == 'follower_gains_monthly'].copy()
-        if not monthly_gains.empty and FOLLOWER_STATS_CATEGORY_COLUMN in monthly_gains.columns and \
-           FOLLOWER_STATS_ORGANIC_COLUMN in monthly_gains.columns and FOLLOWER_STATS_PAID_COLUMN in monthly_gains.columns:
-            try:
-                monthly_gains.loc[:, FOLLOWER_STATS_CATEGORY_COLUMN_DT] = pd.to_datetime(monthly_gains[FOLLOWER_STATS_CATEGORY_COLUMN], errors='coerce')
-                monthly_gains_display = monthly_gains.sort_values(by=FOLLOWER_STATS_CATEGORY_COLUMN_DT, ascending=False)
-                latest_gain = monthly_gains_display.head(1).copy()
-                if not latest_gain.empty:
-                    latest_gain.loc[:, FOLLOWER_STATS_CATEGORY_COLUMN] = latest_gain[FOLLOWER_STATS_CATEGORY_COLUMN_DT].dt.strftime(UI_DATE_FORMAT)
-                    html_parts.append("<h5>Latest Monthly Follower Gain:</h5>")
-                    html_parts.append(latest_gain[[FOLLOWER_STATS_CATEGORY_COLUMN, FOLLOWER_STATS_ORGANIC_COLUMN, FOLLOWER_STATS_PAID_COLUMN]].to_html(escape=True, index=False, classes="table table-sm"))
-                else:
-                    html_parts.append("<p>No valid monthly follower gain data to display after processing.</p>")
-            except Exception as e:
-                logging.error(f"Error formatting follower gain dates for display: {e}", exc_info=True)
-                html_parts.append("<p>Error displaying monthly follower gain data.</p>")
-        else:
-            html_parts.append("<p>No monthly follower gain data or required columns are missing.</p>")
-
-        demographics_count = len(follower_stats_df[follower_stats_df[FOLLOWER_STATS_TYPE_COLUMN] != 'follower_gains_monthly'])
-        html_parts.append(f"<p>Total demographic entries (seniority, industry, etc.): {demographics_count}</p>")
-    else:
-        html_parts.append("<p>No follower statistics loaded from Bubble.</p>")
-
-    html_parts.append("</div>")
-    return "".join(html_parts)
+# Removed display_main_dashboard as its content is now directly embedded in app.py for the Home tab.
 
 
 def run_mentions_tab_display(token_state):
@@ -169,7 +86,7 @@ def run_mentions_tab_display(token_state):
         finally:
             # Ensure plt.close is called on the figure object, not plt itself if it's not the same
             if fig_plot_local and fig_plot_local is not plt: # Check if fig_plot_local is a Figure object
-                 plt.close(fig_plot_local)
+                    plt.close(fig_plot_local)
     return mentions_html_output, fig
 
 
@@ -243,7 +160,7 @@ def run_follower_stats_tab_display(token_state):
         plot_monthly_gains = None
     finally:
         if fig_gains_local and fig_gains_local is not plt:
-             plt.close(fig_gains_local)
+            plt.close(fig_gains_local)
     html_parts.append("<hr/>")
 
 
@@ -280,7 +197,7 @@ def run_follower_stats_tab_display(token_state):
         plot_seniority_dist = None
     finally:
         if fig_seniority_local and fig_seniority_local is not plt:
-             plt.close(fig_seniority_local)
+            plt.close(fig_seniority_local)
     html_parts.append("<hr/>")
 
     # Industry Plot
@@ -427,3 +344,4 @@ def build_analytics_tab_plot_area(plot_configs):
         logging.error(f"MISMATCH: Expected {len(plot_configs)} plot objects, but created {len(plot_ui_objects)}.")
     
     return plot_ui_objects, section_titles_map
+