chore: Changed warning stack level

refactor: Refactored user warnings in local mode when large upload
qdrant · Dec 4, 2024 · d935b23 · d935b23
1 parent 581f580
commit d935b23
Show file tree

Hide file tree

Showing 4 changed files with 11 additions and 18 deletions.
diff --git a/qdrant_client/common/client_warnings.py b/qdrant_client/common/client_warnings.py
@@ -5,7 +5,7 @@
 
 
 def show_warning(message: str, category: type[Warning] = UserWarning) -> None:
-    warnings.warn(message, category, stacklevel=2)
+    warnings.warn(message, category, stacklevel=4)
 
 
 def show_warning_once(

diff --git a/qdrant_client/local/async_qdrant_local.py b/qdrant_client/local/async_qdrant_local.py
@@ -109,7 +109,7 @@ def _load(self) -> None:
                     self.collections[collection_name] = collection
                     if len(collection.ids) > self.LARGE_DATA_THRESHOLD:
                         show_warning_once(
-                            message=f"Local mode is not recommended for collections with more than {self.LARGE_DATA_THRESHOLD:,} points. Consider using Qdrant docker (http/grpc) or Qdrant cloud for better performance with large datasets.",
+                            message=f"Local mode is not recommended for collections with more than {self.LARGE_DATA_THRESHOLD:,} points, currect collection contains {len(collection.ids)}.Consider using Qdrant in docker or Qdrant cloud for better performance with large datasets.",
                             category=UserWarning,
                             idx="large-local-collection",
                         )

diff --git a/qdrant_client/local/local_collection.py b/qdrant_client/local/local_collection.py
@@ -2161,20 +2161,6 @@ def _upsert_point(self, point: models.PointStruct) -> None:
             self.storage.persist(point)
 
     def upsert(self, points: Union[Sequence[models.PointStruct], models.Batch]) -> None:
-        points_count = (
-            len(points)
-            if isinstance(points, list)
-            else len(points.ids)
-            if isinstance(points, models.Batch)
-            else 0
-        )
-        if len(self.ids) + points_count > self.LARGE_DATA_THRESHOLD:
-            show_warning_once(
-                f"Local mode is not recommended for collections with more than {self.LARGE_DATA_THRESHOLD:,} points. "
-                "Consider using Qdrant docker (http/grpc) or Qdrant cloud for better performance with large datasets.",
-                category=UserWarning,
-                idx="large-local-collection",
-            )
         if isinstance(points, list):
             for point in points:
                 self._upsert_point(point)
@@ -2199,6 +2185,13 @@ def upsert(self, points: Union[Sequence[models.PointStruct], models.Batch]) -> N
                         vector=vector,
                     )
                 )
+        if len(self.ids) > self.LARGE_DATA_THRESHOLD:
+            show_warning_once(
+                f"Local mode is not recommended for collections with more than {self.LARGE_DATA_THRESHOLD:,} points, currect collection contains {len(self.ids)}."
+                "Consider using Qdrant in docker or Qdrant cloud for better performance with large datasets.",
+                category=UserWarning,
+                idx="large-local-collection",
+            )
         else:
             raise ValueError(f"Unsupported type: {type(points)}")
 

diff --git a/qdrant_client/local/qdrant_local.py b/qdrant_client/local/qdrant_local.py
@@ -112,8 +112,8 @@ def _load(self) -> None:
                     self.collections[collection_name] = collection
                     if len(collection.ids) > self.LARGE_DATA_THRESHOLD:
                         show_warning_once(
-                            message=f"Local mode is not recommended for collections with more than {self.LARGE_DATA_THRESHOLD:,} points. "
-                            "Consider using Qdrant docker (http/grpc) or Qdrant cloud for better performance with large datasets.",
+                            message=f"Local mode is not recommended for collections with more than {self.LARGE_DATA_THRESHOLD:,} points, currect collection contains {len(collection.ids)}."
+                            "Consider using Qdrant in docker or Qdrant cloud for better performance with large datasets.",
                             category=UserWarning,
                             idx="large-local-collection",
                         )