fixed sql

dashboard/server.py

@@ -83,46 +83,59 @@ async def get_analytics(
     isins: str = None,
     continents: str = None
 ):
+    # Determine if we need to join metadata
+    needs_metadata = any([
+        group_by in ["name", "continent", "sector"],
+        sub_group_by in ["name", "continent", "sector"],
+        continents is not None
+    ])
+    
+    # Use prefixes only if joining
+    t_prefix = "t." if needs_metadata else ""
+    m_prefix = "m." if needs_metadata else ""
+    
     metrics_map = {
-        "volume": "sum(t.price * t.quantity)",
+        "volume": f"sum({t_prefix}price * {t_prefix}quantity)",
-        "count": "count(*)",
+        "count": f"count(*)",
-        "avg_price": "avg(t.price)"
+        "avg_price": f"avg({t_prefix}price)"
     }
     
     groups_map = {
-        "day": "date_trunc('day', t.timestamp)",
+        "day": f"date_trunc('day', {t_prefix}timestamp)",
-        "month": "date_trunc('month', t.timestamp)",
+        "month": f"date_trunc('month', {t_prefix}timestamp)",
-        "exchange": "t.exchange",
+        "exchange": f"{t_prefix}exchange",
-        "isin": "t.isin",
+        "isin": f"{t_prefix}isin",
-        "name": "coalesce(m.name, t.isin)",
+        "name": f"coalesce({m_prefix}name, {t_prefix}isin)" if needs_metadata else "isin",
-        "continent": "coalesce(m.continent, 'Unknown')",
+        "continent": f"coalesce({m_prefix}continent, 'Unknown')" if needs_metadata else "'Unknown'",
-        "sector": "coalesce(m.sector, 'Unknown')"
+        "sector": f"coalesce({m_prefix}sector, 'Unknown')" if needs_metadata else "'Unknown'"
     }
     
     selected_metric = metrics_map.get(metric, metrics_map["volume"])
     selected_group = groups_map.get(group_by, groups_map["day"])
     
-    # We always join metadata to allow filtering by continent/sector even if not grouping by them
     query = f"select {selected_group} as label"
     
     if sub_group_by and sub_group_by in groups_map:
         query += f", {groups_map[sub_group_by]} as sub_label"
         
-    query += f", {selected_metric} as value from trades t"
+    query += f", {selected_metric} as value from trades"
-    query += " left join metadata m on t.isin = m.isin where 1=1"
+    if needs_metadata:
+        query += " t left join metadata m on t.isin = m.isin"
+    
+    query += " where 1=1"
     
     if date_from:
-        query += f" and t.timestamp >= '{date_from}'"
+        query += f" and {t_prefix}timestamp >= '{date_from}'"
     if date_to:
-        query += f" and t.timestamp <= '{date_to}'"
+        query += f" and {t_prefix}timestamp <= '{date_to}'"
         
     if isins:
         isins_list = ",".join([f"'{i.strip()}'" for i in isins.split(",")])
-        query += f" and t.isin in ({isins_list})"
+        query += f" and {t_prefix}isin in ({isins_list})"
 
-    if continents:
+    if continents and needs_metadata:
         cont_list = ",".join([f"'{c.strip()}'" for c in continents.split(",")])
-        query += f" and m.continent in ({cont_list})"
+        query += f" and {m_prefix}continent in ({cont_list})"
         
     query += " group by label"
     if sub_group_by and sub_group_by in groups_map:

verify_fix.py

@@ -0,0 +1,80 @@
+
+def mock_get_analytics(
+    metric: str = "volume", 
+    group_by: str = "day", 
+    sub_group_by: str = None,
+    date_from: str = None, 
+    date_to: str = None,
+    isins: str = None,
+    continents: str = None
+):
+    # Determine if we need to join metadata
+    needs_metadata = any([
+        group_by in ["name", "continent", "sector"],
+        sub_group_by in ["name", "continent", "sector"],
+        continents is not None
+    ])
+    
+    # Use prefixes only if joining
+    t_prefix = "t." if needs_metadata else ""
+    m_prefix = "m." if needs_metadata else ""
+    
+    metrics_map = {
+        "volume": f"sum({t_prefix}price * {t_prefix}quantity)",
+        "count": f"count(*)",
+        "avg_price": f"avg({t_prefix}price)"
+    }
+    
+    groups_map = {
+        "day": f"date_trunc('day', {t_prefix}timestamp)",
+        "month": f"date_trunc('month', {t_prefix}timestamp)",
+        "exchange": f"{t_prefix}exchange",
+        "isin": f"{t_prefix}isin",
+        "name": f"coalesce({m_prefix}name, {t_prefix}isin)" if needs_metadata else "isin",
+        "continent": f"coalesce({m_prefix}continent, 'Unknown')" if needs_metadata else "'Unknown'",
+        "sector": f"coalesce({m_prefix}sector, 'Unknown')" if needs_metadata else "'Unknown'"
+    }
+    
+    selected_metric = metrics_map.get(metric, metrics_map["volume"])
+    selected_group = groups_map.get(group_by, groups_map["day"])
+    
+    query = f"select {selected_group} as label"
+    
+    if sub_group_by and sub_group_by in groups_map:
+        query += f", {groups_map[sub_group_by]} as sub_label"
+        
+    query += f", {selected_metric} as value from trades"
+    if needs_metadata:
+        query += " t left join metadata m on t.isin = m.isin"
+    
+    query += " where 1=1"
+    
+    if date_from:
+        query += f" and {t_prefix}timestamp >= '{date_from}'"
+    if date_to:
+        query += f" and {t_prefix}timestamp <= '{date_to}'"
+        
+    if isins:
+        isins_list = ",".join([f"'{i.strip()}'" for i in isins.split(",")])
+        query += f" and {t_prefix}isin in ({isins_list})"
+
+    if continents and needs_metadata:
+        cont_list = ",".join([f"'{c.strip()}'" for c in continents.split(",")])
+        query += f" and {m_prefix}continent in ({cont_list})"
+        
+    query += " group by label"
+    if sub_group_by and sub_group_by in groups_map:
+        query += ", sub_label"
+    
+    query += " order by label asc"
+    return query
+
+# Test cases
+print("Case 1: Basic analytics (reported error case)")
+print(mock_get_analytics(metric="volume", group_by="day", date_from="2025-12-26", date_to="2026-01-25", isins="DE000LS1LUS9"))
+
+print("\nCase 2: Filtering by continent (should join)")
+print(mock_get_analytics(metric="volume", group_by="day", continents="Europe"))
+
+print("\nCase 3: Grouping by name (should join)")
+print(mock_get_analytics(metric="count", group_by="name"))