fix(dashboard): enabled scraper access without existing data

dashboard/app.py

@@ -126,14 +126,15 @@ def main():
         empty_msg = "No scraped subreddits found."
         icon = "📁"
     
+    selected_sub = None
+    
     if not options:
         st.sidebar.warning(empty_msg)
         if source_type == "Subreddits":
-            st.sidebar.code("python main.py <sub_name> ...")
+            st.sidebar.info("Go to '⚙️ Scraper' tab to start scraping.")
+        else:
+            st.sidebar.info("Go to '⚙️ Scraper' tab to start scraping users.")
     else:
-            st.sidebar.code("python main.py <user> --user ...")
-        return # Stop execution if no data for selected type
-    
         # Selector
         selected_sub = st.sidebar.selectbox(
             f"Select {source_type[:-1]}", # "Select Subreddit" or "Select User"
@@ -141,24 +142,42 @@ def main():
             format_func=lambda x: f"{icon} {x[2:] if x.startswith(('r_', 'u_')) else x}"
         )
     
-    # Load data
+    # Load data if selected
+    posts_df = pd.DataFrame()
+    comments_df = pd.DataFrame()
+    data_loaded = False
+    
+    if selected_sub:
         data_dir = Path(__file__).parent.parent / 'data'
         sub_path = data_dir / selected_sub
         data = load_subreddit_data(sub_path)
         
-    if 'posts' not in data:
-        st.error("No posts data found!")
-        return
-    
+        if 'posts' in data:
             posts_df = data['posts']
             comments_df = data.get('comments', pd.DataFrame())
+            data_loaded = True
+        else:
+            st.error("No posts data found for selected item!")
     
-    # Main content tabs
-    tab1, tab2, tab3, tab4, tab5, tab6, tab7 = st.tabs([
-        "📊 Overview", "📈 Analytics", "🔍 Search", "💬 Comments", "⚙️ Scraper", "📋 Job History", "🔌 Integrations"
-    ])
+    # Define Tabs
+    # Data tabs only if data loaded
+    tab_list = []
+    if data_loaded:
+        tab_list.extend(["📊 Overview", "📈 Analytics", "🔍 Search", "💬 Comments"])
     
-    with tab1:
+    # Always present tabs
+    tab_list.extend(["⚙️ Scraper", "📋 Job History", "🔌 Integrations"])
+    
+    # Create tabs
+    tabs = st.tabs(tab_list)
+    
+    # Map tabs to variables for easy access
+    tab_map = {name: tabs[i] for i, name in enumerate(tab_list)}
+    
+    # --- RENDER TABS ---
+    
+    if data_loaded:
+        with tab_map["📊 Overview"]:
             st.header(f"📊 Overview: {selected_sub}")
             
             # Metrics row
@@ -204,7 +223,7 @@ def main():
                 top_posts = posts_df.nlargest(10, 'score')[['title', 'score', 'num_comments', 'post_type', 'created_utc']]
                 st.dataframe(top_posts)
 
-    with tab2:
+        with tab_map["📈 Analytics"]:
             st.header("📈 Analytics")
             
             # Sentiment Analysis
@@ -259,7 +278,7 @@ def main():
                     for day, avg_score in timing_data['best_days']:
                         st.write(f"• {day} - Avg Score: {avg_score:.1f}")
 
-    with tab3:
+        with tab_map["🔍 Search"]:
             st.header("🔍 Search Posts")
             
             # Search form
@@ -310,7 +329,7 @@ def main():
                 st.write(f"Found {len(filtered)} results")
                 st.dataframe(filtered[['title', 'score', 'num_comments', 'post_type', 'author', 'created_utc']].head(50))
 
-    with tab4:
+        with tab_map["💬 Comments"]:
             st.header("💬 Comments Analysis")
             
             if len(comments_df) == 0:
@@ -345,7 +364,9 @@ def main():
                     top_authors = comments_df['author'].value_counts().head(10)
                     st.bar_chart(top_authors)
 
-    with tab5:
+    # Scraper Tab (Always visible)
+    with tab_map["⚙️ Scraper"]:
+
         st.header("⚙️ Scraper Controls")
         
         # Persistence logic