Update ui_generators.py

ui_generators.py

@@ -1,11 +1,13 @@
 # ui_generators.py
 """
-Generates HTML content and Matplotlib plots for the Gradio UI tabs.
+Generates HTML content and Matplotlib plots for the Gradio UI tabs,
+and UI components for the Analytics tab.
 """
 import pandas as pd
 import logging
 import matplotlib.pyplot as plt
 import matplotlib # To ensure backend is switched before any plt import from other modules if app structure changes
+import gradio as gr # Added for UI components
 
 # Switch backend for Matplotlib to Agg for Gradio compatibility
 matplotlib.use('Agg')
@@ -18,6 +20,10 @@ from config import (
     FOLLOWER_STATS_PAID_COLUMN, FOLLOWER_STATS_CATEGORY_COLUMN_DT, UI_DATE_FORMAT, UI_MONTH_FORMAT
 )
 
+# Configure logging for this module if not already configured at app level
+# logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(module)s - %(message)s')
+
+
 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"):
@@ -37,8 +43,11 @@ def display_main_dashboard(token_state):
             display_df_posts = posts_df.copy()
             if BUBBLE_POST_DATE_COLUMN_NAME in display_df_posts.columns:
                 try:
-                    display_df_posts[BUBBLE_POST_DATE_COLUMN_NAME] = pd.to_datetime(display_df_posts[BUBBLE_POST_DATE_COLUMN_NAME], errors='coerce').dt.strftime(UI_DATE_FORMAT)
+                    # 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>")
@@ -58,8 +67,9 @@ def display_main_dashboard(token_state):
             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').dt.strftime(UI_DATE_FORMAT)
+                    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>")
@@ -76,15 +86,13 @@ def display_main_dashboard(token_state):
         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:
-                # FOLLOWER_STATS_CATEGORY_COLUMN for monthly gains is 'YYYY-MM-DD'
                 monthly_gains.loc[:, FOLLOWER_STATS_CATEGORY_COLUMN_DT] = pd.to_datetime(monthly_gains[FOLLOWER_STATS_CATEGORY_COLUMN], errors='coerce')
-                # Format original date column for display after sorting by datetime
                 monthly_gains_display = monthly_gains.sort_values(by=FOLLOWER_STATS_CATEGORY_COLUMN_DT, ascending=False)
-                latest_gain = monthly_gains_display.head(1).copy() # Work with a copy for modification
+                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) # or UI_MONTH_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"))
+                    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:
@@ -120,8 +128,9 @@ def run_mentions_tab_display(token_state):
     mentions_df_display = mentions_df.copy()
     if BUBBLE_MENTIONS_DATE_COLUMN_NAME in mentions_df_display.columns:
         try:
-            mentions_df_display[BUBBLE_MENTIONS_DATE_COLUMN_NAME] = pd.to_datetime(mentions_df_display[BUBBLE_MENTIONS_DATE_COLUMN_NAME], errors='coerce').dt.strftime(UI_DATE_FORMAT)
+            mentions_df_display[BUBBLE_MENTIONS_DATE_COLUMN_NAME] = pd.to_datetime(mentions_df_display[BUBBLE_MENTIONS_DATE_COLUMN_NAME], errors='coerce')
             mentions_df_display = mentions_df_display.sort_values(by=BUBBLE_MENTIONS_DATE_COLUMN_NAME, ascending=False)
+            mentions_df_display[BUBBLE_MENTIONS_DATE_COLUMN_NAME] = mentions_df_display[BUBBLE_MENTIONS_DATE_COLUMN_NAME].dt.strftime(UI_DATE_FORMAT)
         except Exception as e:
             logging.error(f"Error formatting mention dates for tab display: {e}")
             html_parts.append("<p>Error formatting mention dates.</p>")
@@ -132,7 +141,7 @@ def run_mentions_tab_display(token_state):
         html_parts.append(mentions_df_display[display_columns].head(20).to_html(escape=False, index=False, classes="table table-sm"))
 
     mentions_html_output = "\n".join(html_parts)
-    fig = None
+    fig = None # Initialize fig to None
     if not mentions_df.empty and "sentiment_label" in mentions_df.columns:
         try:
             fig_plot, ax = plt.subplots(figsize=(6,4))
@@ -142,13 +151,17 @@ def run_mentions_tab_display(token_state):
             ax.set_ylabel("Count")
             plt.xticks(rotation=45, ha='right')
             plt.tight_layout()
-            fig = fig_plot
+            fig = fig_plot # Assign the figure object
             logging.info("Mentions tab: Sentiment distribution plot generated.")
         except Exception as e:
             logging.error(f"Error generating mentions plot: {e}", exc_info=True)
-            fig = None
-    else:
-        logging.info("Mentions tab: Not enough data or 'sentiment_label' column missing for plot.")
+            # fig remains None
+        finally:
+            if fig is not None and fig is not plt: # Ensure we don't close the global plt if fig is just an alias
+                 plt.close(fig) # Close the specific figure to free memory
+            elif fig is None and plt.get_fignums(): # If fig is None but some global figure might exist from error
+                 plt.close('all')
+
 
     return mentions_html_output, fig
 
@@ -187,17 +200,15 @@ def run_follower_stats_tab_display(token_state):
 
             html_parts.append("<h4>Monthly Follower Gains (Last 13 Months):</h4>")
             table_display_df = monthly_gains_df_sorted_table.copy()
-            table_display_df.loc[:,FOLLOWER_STATS_CATEGORY_COLUMN] = table_display_df[FOLLOWER_STATS_CATEGORY_COLUMN_DT].dt.strftime(UI_MONTH_FORMAT) # Use YYYY-MM for table
+            table_display_df.loc[:,FOLLOWER_STATS_CATEGORY_COLUMN] = table_display_df[FOLLOWER_STATS_CATEGORY_COLUMN_DT].dt.strftime(UI_MONTH_FORMAT)
             html_parts.append(table_display_df[[FOLLOWER_STATS_CATEGORY_COLUMN, FOLLOWER_STATS_ORGANIC_COLUMN, FOLLOWER_STATS_PAID_COLUMN]].head(13).to_html(escape=True, index=False, classes="table table-sm"))
 
             monthly_gains_df_sorted_plot = monthly_gains_df.sort_values(by=FOLLOWER_STATS_CATEGORY_COLUMN_DT, ascending=True).copy()
-            # For plotting, group by month string to ensure unique x-ticks if multiple entries exist for a month (though unlikely for this data type)
             monthly_gains_df_sorted_plot.loc[:, '_plot_month'] = monthly_gains_df_sorted_plot[FOLLOWER_STATS_CATEGORY_COLUMN_DT].dt.strftime(UI_MONTH_FORMAT)
             plot_data = monthly_gains_df_sorted_plot.groupby('_plot_month').agg(
                 organic=(FOLLOWER_STATS_ORGANIC_COLUMN, 'sum'),
                 paid=(FOLLOWER_STATS_PAID_COLUMN, 'sum')
-            ).reset_index().sort_values(by='_plot_month')
-
+            ).reset_index().sort_values(by='_plot_month') # Ensure month order for plot
 
             fig_gains, ax_gains = plt.subplots(figsize=(10,5))
             ax_gains.plot(plot_data['_plot_month'], plot_data['organic'], marker='o', linestyle='-', label='Organic Gain')
@@ -214,6 +225,11 @@ def run_follower_stats_tab_display(token_state):
         except Exception as e:
             logging.error(f"Error processing or plotting monthly gains: {e}", exc_info=True)
             html_parts.append("<p>Error displaying monthly follower gain data.</p>")
+        finally:
+            if plot_monthly_gains is not None and plot_monthly_gains is not plt:
+                 plt.close(plot_monthly_gains)
+            elif plot_monthly_gains is None and plt.get_fignums():
+                 plt.close('all')
     else:
         html_parts.append("<p>No monthly follower gain data available or required columns missing.</p>")
     html_parts.append("<hr/>")
@@ -243,6 +259,11 @@ def run_follower_stats_tab_display(token_state):
         except Exception as e:
             logging.error(f"Error processing or plotting seniority data: {e}", exc_info=True)
             html_parts.append("<p>Error displaying follower seniority data.</p>")
+        finally:
+            if plot_seniority_dist is not None and plot_seniority_dist is not plt:
+                 plt.close(plot_seniority_dist)
+            elif plot_seniority_dist is None and plt.get_fignums():
+                 plt.close('all')
     else:
         html_parts.append("<p>No follower seniority data available or required columns missing.</p>")
     html_parts.append("<hr/>")
@@ -272,9 +293,66 @@ def run_follower_stats_tab_display(token_state):
         except Exception as e:
             logging.error(f"Error processing or plotting industry data: {e}", exc_info=True)
             html_parts.append("<p>Error displaying follower industry data.</p>")
+        finally:
+            if plot_industry_dist is not None and plot_industry_dist is not plt:
+                 plt.close(plot_industry_dist)
+            elif plot_industry_dist is None and plt.get_fignums():
+                 plt.close('all')
+
     else:
         html_parts.append("<p>No follower industry data available or required columns missing.</p>")
 
     html_parts.append("</div>")
     follower_html_output = "\n".join(html_parts)
     return follower_html_output, plot_monthly_gains, plot_seniority_dist, plot_industry_dist
+
+
+# --- NEW UI GENERATION LOGIC FOR ANALYTICS TAB ---
+def create_analytics_plot_ui_row(label, plot_id_str):
+    """
+    Creates a Gradio Row with a Plot component, a Bomb (insights) button,
+    and a hidden Column for insights.
+    """
+    # This function will be called within a gr.Blocks() context in app.py
+    with gr.Row(equal_height=False): 
+        with gr.Column(scale=7): # Main column for the plot
+            plot_component = gr.Plot(label=label)
+        with gr.Column(scale=1, min_width=60): # Smaller column for the bomb button
+            bomb_button = gr.Button("💣", variant="secondary", size="sm", elem_id=f"bomb_{plot_id_str}")
+        # Insights column, initially hidden, appears to the right
+        with gr.Column(scale=4, visible=False, elem_id=f"insights_col_{plot_id_str}") as insights_col_ui:
+            gr.Markdown(f"##### Insights: {label}") # Title for the insights panel
+            insights_markdown_ui = gr.Markdown(f"Click 💣 for insights on {label}...") # Placeholder text
+    return plot_component, bomb_button, insights_col_ui, insights_markdown_ui
+
+def build_analytics_tab_ui_components(plot_configs):
+    """
+    Builds and returns all UI components for the analytics plots based on plot_configs.
+    This function should be called within the "Analytics" TabItem context in app.py.
+    It will create the section headers and the plot rows.
+    """
+    logging.info(f"Building UI components for {len(plot_configs)} analytics plots.")
+    plot_ui_objects = {} # Stores {"plot_id": {"plot": gr.Plot, "bomb": gr.Button, "insights_col": gr.Column, "insights_md": gr.Markdown, "label": str}}
+    
+    current_section_title = ""
+    for config in plot_configs:
+        if config["section"] != current_section_title:
+            gr.Markdown(f"### {config['section']}") # Create section header
+            current_section_title = config["section"]
+        
+        # Create the plot row using the helper
+        plot_component, bomb_button, insights_col_ui, insights_markdown_ui = \
+            create_analytics_plot_ui_row(config["label"], config["id"])
+        
+        # Store the created components in the dictionary
+        plot_ui_objects[config["id"]] = {
+            "plot": plot_component,
+            "bomb": bomb_button,
+            "insights_col": insights_col_ui,
+            "insights_md": insights_markdown_ui,
+            "label": config["label"] # Store label for easy access, e.g., for insights text
+        }
+        logging.debug(f"Created UI for plot_id: {config['id']} in section: {config['section']}")
+        
+    logging.info(f"Finished building UI components for analytics tab. Total objects: {len(plot_ui_objects)}")
+    return plot_ui_objects