Update app.py

app.py

@@ -18,12 +18,10 @@ import gradio as gr
 APP_TITLE = "ALCO Liquidity & Interest-Rate Risk Dashboard"
 TABLE_FQN = "my_db.main.masterdataset_v"   # source table
 VIEW_FQN = "my_db.main.positions_v"        # normalized view created by this app
-EXPORT_DIR = Path("exports")
-EXPORT_DIR.mkdir(exist_ok=True)
 
 PRODUCT_ASSETS = [
     "loan", "overdraft", "advances", "bills", "bill",
-    "tbond", "t-bond", "tbill", "t-bill", "repo_asset", "assets"
+    "tbond", "t-bond", "tbill", "t-bill", "repo_asset"
 ]
 PRODUCT_SOF = [
     "fd", "term_deposit", "td", "savings", "current",
@@ -40,11 +38,22 @@ def connect_md() -> duckdb.DuckDBPyConnection:
     return duckdb.connect(f"md:?motherduck_token={token}")
 
 def discover_columns(conn: duckdb.DuckDBPyConnection, table_fqn: str) -> List[str]:
-    # More robust than information_schema across DuckDB/MotherDuck
-    df = conn.execute(f"DESCRIBE {table_fqn};").fetchdf()
-    # DuckDB: columns listed under 'column_name'
-    name_col = "column_name" if "column_name" in df.columns else df.columns[0]
-    return [str(c).lower() for c in df[name_col].tolist()]
+    # Try DESCRIBE first (fast), fall back to information_schema
+    try:
+        df = conn.execute(f"DESCRIBE {table_fqn};").fetchdf()
+        name_col = "column_name" if "column_name" in df.columns else df.columns[0]
+        return [str(c).lower() for c in df[name_col].tolist()]
+    except Exception:
+        df = conn.execute(
+            f"""
+            SELECT lower(column_name) AS col
+            FROM information_schema.columns
+            WHERE table_catalog = split_part('{table_fqn}', '.', 1)
+              AND table_schema  = split_part('{table_fqn}', '.', 2)
+              AND table_name    = split_part('{table_fqn}', '.', 3)
+            """
+        ).fetchdf()
+        return df["col"].tolist()
 
 def build_view_sql(existing_cols: List[str]) -> str:
     wanted = [
@@ -64,8 +73,10 @@ def build_view_sql(existing_cols: List[str]) -> str:
 
     sof_list = ", ".join([f"'{p}'" for p in PRODUCT_SOF])
     asset_list = ", ".join([f"'{p}'" for p in PRODUCT_ASSETS])
+
     bucket_case = (
-        f"CASE WHEN lower(product) IN ({sof_list}) THEN 'SoF' "
+        f"CASE "
+        f"WHEN lower(product) IN ({sof_list}) THEN 'SoF' "
         f"WHEN lower(product) IN ({asset_list}) THEN 'Assets' "
         f"ELSE 'Unknown' END AS bucket"
     )
@@ -167,56 +178,41 @@ def irr_sql(cols: List[str]) -> str:
     GROUP BY bucket;
     """
 
-def export_excel(as_of: str, assets_t1: float, sof_t1: float, net_gap_t1: float,
-                 ladder: pd.DataFrame, irr: pd.DataFrame) -> Path:
-    out = EXPORT_DIR / f"alco_report_{as_of or 'NA'}.xlsx"
-    with pd.ExcelWriter(out, engine="xlsxwriter") as xw:
-        pd.DataFrame({
-            "as_of_date": [as_of or "N/A"],
-            "assets_t1": [assets_t1],
-            "sof_t1": [sof_t1],
-            "net_gap_t1": [net_gap_t1],
-        }).to_excel(xw, index=False, sheet_name="kpis")
-        (ladder if ladder is not None else pd.DataFrame()).to_excel(xw, index=False, sheet_name="ladder")
-        (irr if irr is not None else pd.DataFrame()).to_excel(xw, index=False, sheet_name="irr")
-    return out
-
 # =========================
 # Dashboard callback
 # =========================
-def run_dashboard() -> Tuple[str, str, str, str, str, Any, pd.DataFrame, pd.DataFrame, str]:
+def run_dashboard() -> Tuple[str, str, str, str, str, Any, pd.DataFrame, pd.DataFrame]:
     """
     Returns:
-      status, as_of, assets_t1, sof_t1, net_gap_t1, figure, ladder_df, irr_df, excel_path
-      (all text values are returned as strings to avoid component type errors)
+      status, as_of, assets_t1, sof_t1, net_gap_t1, figure, ladder_df, irr_df
+      (text KPIs to avoid component type errors)
     """
     try:
         conn = connect_md()
 
-        # Discover columns & build view
+        # 1) Discover columns & build view
         cols = discover_columns(conn, TABLE_FQN)
         ensure_view(conn, cols)
 
-        # as_of (optional)
+        # 2) As-of (optional)
         as_of = "N/A"
         if "as_of_date" in cols:
             tmp = conn.execute(f"SELECT max(as_of_date) AS d FROM {VIEW_FQN}").fetchdf()
             if not tmp.empty and not pd.isna(tmp["d"].iloc[0]):
                 as_of = str(tmp["d"].iloc[0])[:10]
 
-        # KPIs
+        # 3) KPIs
         kpi = conn.execute(KPI_SQL).fetchdf()
         assets_t1 = safe_num(kpi["assets_t1"].iloc[0]) if not kpi.empty else 0.0
         sof_t1    = safe_num(kpi["sof_t1"].iloc[0]) if not kpi.empty else 0.0
         net_gap   = safe_num(kpi["net_gap_t1"].iloc[0]) if not kpi.empty else 0.0
 
-        # Ladder & IRR
+        # 4) Ladder & IRR
         ladder = conn.execute(LADDER_SQL).fetchdf()
         irr    = conn.execute(irr_sql(cols)).fetchdf()
 
+        # 5) Chart
         fig = plot_ladder(ladder)
-        xlsx = export_excel(as_of, assets_t1, sof_t1, net_gap, ladder, irr)
-        xlsx_str = str(xlsx if xlsx.exists() else "")
 
         status = "✅ OK"
         return (
@@ -228,12 +224,10 @@ def run_dashboard() -> Tuple[str, str, str, str, str, Any, pd.DataFrame, pd.Data
             fig,
             ladder,
             irr,
-            xlsx_str,
         )
 
     except Exception as e:
         tb = traceback.format_exc()
-        # Return placeholders + human-readable error in status
         empty_df = pd.DataFrame()
         fig = plot_ladder(empty_df)
         return (
@@ -245,7 +239,6 @@ def run_dashboard() -> Tuple[str, str, str, str, str, Any, pd.DataFrame, pd.Data
             fig,
             empty_df,
             empty_df,
-            "",
         )
 
 # =========================
@@ -254,7 +247,7 @@ def run_dashboard() -> Tuple[str, str, str, str, str, Any, pd.DataFrame, pd.Data
 with gr.Blocks(title=APP_TITLE) as demo:
     gr.Markdown(f"# {APP_TITLE}\n_Source:_ `{TABLE_FQN}` → `{VIEW_FQN}`")
 
-    status = gr.Textbox(label="Status", interactive=False, lines=5)
+    status = gr.Textbox(label="Status", interactive=False, lines=8)
 
     with gr.Row():
         refresh_btn = gr.Button("🔄 Refresh", variant="primary")
@@ -270,11 +263,10 @@ with gr.Blocks(title=APP_TITLE) as demo:
     chart = gr.Plot(label="Maturity Ladder")
     ladder_df = gr.Dataframe(label="Ladder Detail")
     irr_df = gr.Dataframe(label="Interest-Rate Risk (approx)")
-    excel_file = gr.File(label="Excel export", interactive=False)
 
     refresh_btn.click(
         fn=run_dashboard,
-        outputs=[status, as_of, a1, a2, a3, chart, ladder_df, irr_df, excel_file],
+        outputs=[status, as_of, a1, a2, a3, chart, ladder_df, irr_df],
     )
 
 if __name__ == "__main__":