feat: enrich SQL explorer schema browser with PK/FK, row counts, search, collapsible tables

services/api/app.py

@@ -2121,24 +2121,72 @@ async def analytics_schema():
 @app.get("/api/analytics/pg-schema")
 async def pg_schema():
     """Return PostgreSQL table/column metadata for the schema browser."""
-    rows = await pool.fetch("""
-        SELECT t.table_name, c.column_name, c.data_type, c.is_nullable
+    # Columns with ordinal position
+    col_rows = await pool.fetch("""
+        SELECT t.table_name, c.column_name, c.data_type, c.is_nullable,
+               c.column_default
         FROM information_schema.tables t
         JOIN information_schema.columns c
             ON t.table_name = c.table_name AND t.table_schema = c.table_schema
         WHERE t.table_schema = 'public' AND t.table_type = 'BASE TABLE'
         ORDER BY t.table_name, c.ordinal_position
     """)
+
+    # Primary key columns
+    pk_rows = await pool.fetch("""
+        SELECT kcu.table_name, kcu.column_name
+        FROM information_schema.table_constraints tc
+        JOIN information_schema.key_column_usage kcu
+            ON tc.constraint_name = kcu.constraint_name
+            AND tc.table_schema = kcu.table_schema
+        WHERE tc.table_schema = 'public' AND tc.constraint_type = 'PRIMARY KEY'
+    """)
+    pk_set: set[tuple[str, str]] = {(r["table_name"], r["column_name"]) for r in pk_rows}
+
+    # Foreign key columns with referenced table
+    fk_rows = await pool.fetch("""
+        SELECT kcu.table_name, kcu.column_name,
+               ccu.table_name AS foreign_table
+        FROM information_schema.table_constraints tc
+        JOIN information_schema.key_column_usage kcu
+            ON tc.constraint_name = kcu.constraint_name
+            AND tc.table_schema = kcu.table_schema
+        JOIN information_schema.constraint_column_usage ccu
+            ON tc.constraint_name = ccu.constraint_name
+            AND tc.table_schema = ccu.table_schema
+        WHERE tc.table_schema = 'public' AND tc.constraint_type = 'FOREIGN KEY'
+    """)
+    fk_map: dict[tuple[str, str], str] = {
+        (r["table_name"], r["column_name"]): r["foreign_table"] for r in fk_rows
+    }
+
+    # Approximate row counts from pg_stat
+    count_rows = await pool.fetch("""
+        SELECT relname AS table_name, reltuples::bigint AS row_estimate
+        FROM pg_class
+        WHERE relnamespace = (SELECT oid FROM pg_namespace WHERE nspname = 'public')
+          AND relkind = 'r'
+    """)
+    row_counts: dict[str, int] = {r["table_name"]: max(0, r["row_estimate"]) for r in count_rows}
+
     tables: dict[str, dict[str, Any]] = {}
-    for row in rows:
+    for row in col_rows:
         tname = row["table_name"]
         if tname not in tables:
-            tables[tname] = {"name": tname, "columns": []}
-        tables[tname]["columns"].append({
+            tables[tname] = {"name": tname, "row_estimate": row_counts.get(tname, 0), "columns": []}
+        col_info: dict[str, Any] = {
             "name": row["column_name"],
             "type": row["data_type"],
             "nullable": row["is_nullable"] == "YES",
-        })
+        }
+        if (tname, row["column_name"]) in pk_set:
+            col_info["primary_key"] = True
+        fk_ref = fk_map.get((tname, row["column_name"]))
+        if fk_ref:
+            col_info["references"] = fk_ref
+        if row["column_default"] is not None:
+            col_info["has_default"] = True
+        tables[tname]["columns"].append(col_info)
     return {"catalog": "postgresql", "schema": "public", "tables": list(tables.values())}