Debug page: lazy-load 7 unconditional DB queries behind session-state buttons

Eliminates 7 uncached DB queries that fired on every page render:
- 5 audit expanders moved inside "Load Data Library" gate (session state persisted)
- Section 9 eval metrics gated behind new "Load Evaluation Metrics" button
- Both buttons use st.session_state so content survives Streamlit reruns

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

visualization/debug_page.py

@@ -641,7 +641,12 @@ def render_debug(
     # ------------------------------------------------------------------
     st.subheader("Data Inventory")
 
+    if "dbg_lib_loaded" not in st.session_state:
+        st.session_state["dbg_lib_loaded"] = False
     if st.button("Load Data Library", key="dbg_load_inventory"):
+        st.session_state["dbg_lib_loaded"] = True
+
+    if st.session_state["dbg_lib_loaded"]:
         with st.expander("All database tables (row counts)", expanded=True):
             inv_df = _query_db_inventory(conn)
             if inv_df.empty:
@@ -672,7 +677,54 @@ def render_debug(
         elif overlap and "error" in overlap:
             st.warning(f"Overlap query error: {overlap['error']}")
 
-    st.caption("Please allow a few moments to load the data library..")
+        # --- Batter prop outcomes ---
+        with st.expander("Batter prop outcomes", expanded=False):
+            batter_prop_outcomes_df = read_batter_prop_outcomes(conn)
+            st.write(f"Rows: {len(batter_prop_outcomes_df)}")
+            if not batter_prop_outcomes_df.empty:
+                display_cols = [c for c in [
+                    "created_at", "graded_at", "game_pk", "slot", "batter_name",
+                    "fair_hr_odds", "book_hr_odds", "adjusted_edge", "confidence",
+                    "recommendation_tier", "realized_hit", "realized_hr", "realized_tb2p",
+                    "grade_status", "outcome_source",
+                ] if c in batter_prop_outcomes_df.columns]
+                st.dataframe(batter_prop_outcomes_df[display_cols].tail(30), use_container_width=True, hide_index=True)
+
+        # --- Game outcomes ---
+        with st.expander("Game outcomes", expanded=False):
+            game_outcomes_df = read_game_outcomes(conn)
+            st.write(f"Rows: {len(game_outcomes_df)}")
+            if not game_outcomes_df.empty:
+                st.dataframe(game_outcomes_df.tail(20), use_container_width=True, hide_index=True)
+
+        # --- Recommendation logs ---
+        with st.expander("Recommendation logs", expanded=False):
+            rec_logs_df = read_table(conn, "recommendation_logs")
+            st.write(f"Rows: {len(rec_logs_df)}")
+            if not rec_logs_df.empty:
+                st.dataframe(rec_logs_df.tail(20), use_container_width=True, hide_index=True)
+
+        # --- Recommendation audit ---
+        with st.expander("Recommendation audit", expanded=False):
+            audit_df = read_recommendation_audit_view(conn)
+            st.write(f"Rows: {len(audit_df)}")
+            if not audit_df.empty:
+                audit_display_cols = [c for c in [
+                    "created_at", "game_pk", "away_team", "home_team", "slot", "batter_name",
+                    "fair_hr_odds", "book_hr_odds", "adjusted_edge", "confidence",
+                    "recommendation_tier", "realized_hr", "graded_at", "outcome_source",
+                ] if c in audit_df.columns]
+                st.dataframe(audit_df[audit_display_cols].tail(20), use_container_width=True, hide_index=True)
+
+        # --- Batter prop audit ---
+        with st.expander("Batter prop audit", expanded=False):
+            batter_audit_df = read_batter_prop_audit_view(conn)
+            st.write(f"Rows: {len(batter_audit_df)}")
+            if not batter_audit_df.empty:
+                st.dataframe(batter_audit_df.tail(20), use_container_width=True, hide_index=True)
+
+    else:
+        st.caption("Please allow a few moments to load the data library..")
 
     # --- Simulator raw rows ---
     with st.expander("Simulator raw rows", expanded=False):
@@ -711,52 +763,6 @@ def render_debug(
         else:
             st.info("No prepared live games.")
 
-    # --- Batter prop outcomes ---
-    with st.expander("Batter prop outcomes", expanded=False):
-        batter_prop_outcomes_df = read_batter_prop_outcomes(conn)
-        st.write(f"Rows: {len(batter_prop_outcomes_df)}")
-        if not batter_prop_outcomes_df.empty:
-            display_cols = [c for c in [
-                "created_at", "graded_at", "game_pk", "slot", "batter_name",
-                "fair_hr_odds", "book_hr_odds", "adjusted_edge", "confidence",
-                "recommendation_tier", "realized_hit", "realized_hr", "realized_tb2p",
-                "grade_status", "outcome_source",
-            ] if c in batter_prop_outcomes_df.columns]
-            st.dataframe(batter_prop_outcomes_df[display_cols].tail(30), use_container_width=True, hide_index=True)
-
-    # --- Game outcomes ---
-    with st.expander("Game outcomes", expanded=False):
-        game_outcomes_df = read_game_outcomes(conn)
-        st.write(f"Rows: {len(game_outcomes_df)}")
-        if not game_outcomes_df.empty:
-            st.dataframe(game_outcomes_df.tail(20), use_container_width=True, hide_index=True)
-
-    # --- Recommendation logs ---
-    with st.expander("Recommendation logs", expanded=False):
-        rec_logs_df = read_table(conn, "recommendation_logs")
-        st.write(f"Rows: {len(rec_logs_df)}")
-        if not rec_logs_df.empty:
-            st.dataframe(rec_logs_df.tail(20), use_container_width=True, hide_index=True)
-
-    # --- Recommendation audit ---
-    with st.expander("Recommendation audit", expanded=False):
-        audit_df = read_recommendation_audit_view(conn)
-        st.write(f"Rows: {len(audit_df)}")
-        if not audit_df.empty:
-            audit_display_cols = [c for c in [
-                "created_at", "game_pk", "away_team", "home_team", "slot", "batter_name",
-                "fair_hr_odds", "book_hr_odds", "adjusted_edge", "confidence",
-                "recommendation_tier", "realized_hr", "graded_at", "outcome_source",
-            ] if c in audit_df.columns]
-            st.dataframe(audit_df[audit_display_cols].tail(20), use_container_width=True, hide_index=True)
-
-    # --- Batter prop audit ---
-    with st.expander("Batter prop audit", expanded=False):
-        batter_audit_df = read_batter_prop_audit_view(conn)
-        st.write(f"Rows: {len(batter_audit_df)}")
-        if not batter_audit_df.empty:
-            st.dataframe(batter_audit_df.tail(20), use_container_width=True, hide_index=True)
-
     # ------------------------------------------------------------------
     # SECTION 7 — Export
     # ------------------------------------------------------------------
@@ -807,43 +813,49 @@ def render_debug(
     # ------------------------------------------------------------------
     st.subheader("Model Evaluation Metrics")
 
-    try:
-        audit_df = read_recommendation_audit_view(conn)
-    except Exception:
-        audit_df = pd.DataFrame()
-
-    eval_tables = [
-        ("HR Probability Calibration", build_hr_calibration_table(audit_df)),
-        ("Edge Bucket Performance",    build_edge_bucket_table(audit_df)),
-        ("Confidence Bucket",          build_confidence_table(audit_df)),
-        ("Recommendation Tier",        build_tier_performance_table(audit_df)),
-        ("Global ERE",                 build_ere_table(audit_df)),
-        ("ERE by Edge Bucket",         build_ere_by_edge_bucket_table(audit_df)),
-        ("ERE by Confidence",          build_ere_by_confidence_bucket_table(audit_df)),
-        ("ERE by Tier",                build_ere_by_tier_table(audit_df)),
-        ("CLV Summary",                build_clv_table(audit_df)),
-        ("CLV by Tier",                build_clv_by_tier_table(audit_df)),
-    ]
+    if "dbg_eval_metrics_loaded" not in st.session_state:
+        st.session_state["dbg_eval_metrics_loaded"] = False
+    if st.button("Load Evaluation Metrics", key="dbg_load_eval_metrics"):
+        st.session_state["dbg_eval_metrics_loaded"] = True
 
-    for title, tbl in eval_tables:
-        if not tbl.empty:
-            st.write(title)
-            st.dataframe(tbl, use_container_width=True, hide_index=True)
+    if st.session_state["dbg_eval_metrics_loaded"]:
+        try:
+            audit_df = read_recommendation_audit_view(conn)
+        except Exception:
+            audit_df = pd.DataFrame()
+
+        eval_tables = [
+            ("HR Probability Calibration", build_hr_calibration_table(audit_df)),
+            ("Edge Bucket Performance",    build_edge_bucket_table(audit_df)),
+            ("Confidence Bucket",          build_confidence_table(audit_df)),
+            ("Recommendation Tier",        build_tier_performance_table(audit_df)),
+            ("Global ERE",                 build_ere_table(audit_df)),
+            ("ERE by Edge Bucket",         build_ere_by_edge_bucket_table(audit_df)),
+            ("ERE by Confidence",          build_ere_by_confidence_bucket_table(audit_df)),
+            ("ERE by Tier",                build_ere_by_tier_table(audit_df)),
+            ("CLV Summary",                build_clv_table(audit_df)),
+            ("CLV by Tier",                build_clv_by_tier_table(audit_df)),
+        ]
 
-    # Batter-specific metrics
-    try:
-        batter_audit_df_eval = read_batter_prop_audit_view(conn)
-        for title, fn in [
-            ("Batter HR Rate by Tier",       build_batter_hr_tier_table),
-            ("Batter HR Rate by Confidence", build_batter_hr_confidence_table),
-            ("Batter HR Rate by Edge",       build_batter_hr_edge_table),
-        ]:
-            tbl = fn(batter_audit_df_eval)
+        for title, tbl in eval_tables:
             if not tbl.empty:
                 st.write(title)
                 st.dataframe(tbl, use_container_width=True, hide_index=True)
-    except Exception:
-        pass
+
+        # Batter-specific metrics
+        try:
+            batter_audit_df_eval = read_batter_prop_audit_view(conn)
+            for title, fn in [
+                ("Batter HR Rate by Tier",       build_batter_hr_tier_table),
+                ("Batter HR Rate by Confidence", build_batter_hr_confidence_table),
+                ("Batter HR Rate by Edge",       build_batter_hr_edge_table),
+            ]:
+                tbl = fn(batter_audit_df_eval)
+                if not tbl.empty:
+                    st.write(title)
+                    st.dataframe(tbl, use_container_width=True, hide_index=True)
+        except Exception:
+            pass
 
     # Scores raw status (diagnostic)
     if not scores_df.empty and "status" in scores_df.columns: