refactor: Refactored the way of warnings (#864)

* refactor: Refactored the way of warnings * remove unused imports * fix: Fix stacklevel in warnings * regenerated async * nit * Updated some warnings with show once * fix: Fix stack levels * Updated async * Update qdrant_client/qdrant_remote.py Co-authored-by: George <[email protected]> * Update async client * Updated warnings * Updated warnings * Updated warnings * fix: fix warning level * fix: fix warning level in async * fix: revert append payload condition --------- Co-authored-by: George <[email protected]>
qdrant · Jan 16, 2025 · 908977e · 908977e
1 parent a0d6c4b
commit 908977e
Show file tree

Hide file tree

Showing 13 changed files with 163 additions and 70 deletions.
diff --git a/qdrant_client/async_qdrant_client.py b/qdrant_client/async_qdrant_client.py
@@ -1502,6 +1502,7 @@ async def upsert(
                 message="\n            Usage of `grpc.PointStruct` is deprecated. Please use `models.PointStruct` instead.\n            ",
                 category=DeprecationWarning,
                 idx="grpc-input",
+                stacklevel=4,
             )
         requires_inference = self._inference_inspector.inspect(points)
         if requires_inference and (not self.cloud_inference):

diff --git a/qdrant_client/async_qdrant_fastembed.py b/qdrant_client/async_qdrant_fastembed.py
@@ -10,7 +10,6 @@
 # ******  WARNING: THIS FILE IS AUTOGENERATED  ******
 
 import uuid
-import warnings
 from itertools import tee
 from typing import Any, Iterable, Optional, Sequence, Union, get_args
 from copy import deepcopy
@@ -29,6 +28,7 @@
 from qdrant_client.http import models
 from qdrant_client.hybrid.fusion import reciprocal_rank_fusion
 from qdrant_client import grpc
+from qdrant_client.common.client_warnings import show_warning
 
 try:
     from fastembed import (
@@ -151,10 +151,10 @@ def set_model(
             None
         """
         if max_length is not None:
-            warnings.warn(
-                "max_length parameter is deprecated and will be removed in the future. It's not used by fastembed models.",
-                DeprecationWarning,
-                stacklevel=2,
+            show_warning(
+                message="max_length parameter is deprecated and will be removed in the future. It's not used by fastembed models.",
+                category=DeprecationWarning,
+                stacklevel=3,
             )
         self._get_or_init_model(
             model_name=embedding_model_name,

diff --git a/qdrant_client/async_qdrant_remote.py b/qdrant_client/async_qdrant_remote.py
@@ -10,10 +10,8 @@
 # ******  WARNING: THIS FILE IS AUTOGENERATED  ******
 
 import importlib.metadata
-import logging
 import math
 import platform
-import warnings
 from multiprocessing import get_all_start_methods
 from typing import (
     Any,
@@ -31,6 +29,7 @@
 import numpy as np
 from grpc import Compression
 from urllib3.util import Url, parse_url
+from qdrant_client.common.client_warnings import show_warning, show_warning_once
 from qdrant_client import grpc as grpc
 from qdrant_client._pydantic_compat import construct
 from qdrant_client.auth import BearerAuth
@@ -117,7 +116,11 @@ def __init__(
         self._rest_headers = kwargs.pop("metadata", {})
         if api_key is not None:
             if self._scheme == "http":
-                warnings.warn("Api key is used with an insecure connection.")
+                show_warning(
+                    message="Api key is used with an insecure connection.",
+                    category=UserWarning,
+                    stacklevel=4,
+                )
             self._rest_headers["api-key"] = api_key
             self._grpc_headers.append(("api-key", api_key))
         client_version = importlib.metadata.version("qdrant-client")
@@ -147,7 +150,11 @@ def __init__(
             self._timeout = self.DEFAULT_GRPC_TIMEOUT
         if self._auth_token_provider is not None:
             if self._scheme == "http":
-                warnings.warn("Auth token provider is used with an insecure connection.")
+                show_warning(
+                    message="Auth token provider is used with an insecure connection.",
+                    category=UserWarning,
+                    stacklevel=4,
+                )
             bearer_auth = BearerAuth(self._auth_token_provider)
             self._rest_args["auth"] = bearer_auth
         self.openapi_client: AsyncApis[AsyncApiClient] = AsyncApis(
@@ -165,12 +172,16 @@ def __init__(
                 self.rest_uri, self._rest_headers, self._rest_args.get("auth")
             )
             if not server_version:
-                warnings.warn(
-                    f"Failed to obtain server version. Unable to check client-server compatibility. Set check_version=False to skip version check."
+                show_warning(
+                    message=f"Failed to obtain server version. Unable to check client-server compatibility. Set check_version=False to skip version check.",
+                    category=UserWarning,
+                    stacklevel=4,
                 )
             elif not is_compatible(client_version, server_version):
-                warnings.warn(
-                    f"Qdrant client version {client_version} is incompatible with server version {server_version}. Major versions should match and minor version difference must not exceed 1. Set check_version=False to skip version check."
+                show_warning(
+                    message=f"Qdrant client version {client_version} is incompatible with server version {server_version}. Major versions should match and minor version difference must not exceed 1. Set check_version=False to skip version check.",
+                    category=UserWarning,
+                    stacklevel=4,
                 )
 
     @property
@@ -182,16 +193,20 @@ async def close(self, grpc_grace: Optional[float] = None, **kwargs: Any) -> None
             try:
                 await self._grpc_channel.close(grace=grpc_grace)
             except AttributeError:
-                logging.warning(
-                    "Unable to close grpc_channel. Connection was interrupted on the server side"
+                show_warning(
+                    message="Unable to close grpc_channel. Connection was interrupted on the server side",
+                    category=UserWarning,
+                    stacklevel=4,
                 )
             except RuntimeError:
                 pass
         try:
             await self.http.aclose()
         except Exception:
-            logging.warning(
-                "Unable to close http connection. Connection was interrupted on the server side"
+            show_warning(
+                message="Unable to close http connection. Connection was interrupted on the server side",
+                category=UserWarning,
+                stacklevel=4,
             )
         self._closed = True
 
@@ -367,8 +382,11 @@ async def search(
         **kwargs: Any,
     ) -> list[types.ScoredPoint]:
         if not append_payload:
-            logging.warning(
-                "Usage of `append_payload` is deprecated. Please consider using `with_payload` instead"
+            show_warning_once(
+                message="Usage of `append_payload` is deprecated. Please consider using `with_payload` instead",
+                category=DeprecationWarning,
+                stacklevel=5,
+                idx="search-append-payload",
             )
             with_payload = append_payload
         if isinstance(query_vector, np.ndarray):
@@ -2435,7 +2453,12 @@ async def create_collection(
         **kwargs: Any,
     ) -> bool:
         if init_from is not None:
-            logging.warning("init_from is deprecated")
+            show_warning_once(
+                message="init_from is deprecated",
+                category=DeprecationWarning,
+                stacklevel=5,
+                idx="create-collection-init-from",
+            )
         if self._prefer_grpc:
             if isinstance(vectors_config, (models.VectorParams, dict)):
                 vectors_config = RestToGrpc.convert_vectors_config(vectors_config)
@@ -2697,7 +2720,12 @@ async def create_payload_index(
         **kwargs: Any,
     ) -> types.UpdateResult:
         if field_type is not None:
-            warnings.warn("field_type is deprecated, use field_schema instead", DeprecationWarning)
+            show_warning_once(
+                message="field_type is deprecated, use field_schema instead",
+                category=DeprecationWarning,
+                stacklevel=5,
+                idx="payload-index-field-type",
+            )
             field_schema = field_type
         if self._prefer_grpc:
             field_index_params = None

diff --git a/qdrant_client/common/client_warnings.py b/qdrant_client/common/client_warnings.py
@@ -4,12 +4,15 @@
 SEEN_MESSAGES = set()
 
 
-def show_warning(message: str, category: type[Warning] = UserWarning) -> None:
-    warnings.warn(message, category, stacklevel=4)
+def show_warning(message: str, category: type[Warning] = UserWarning, stacklevel: int = 2) -> None:
+    warnings.warn(message, category, stacklevel=stacklevel)
 
 
 def show_warning_once(
-    message: str, category: type[Warning] = UserWarning, idx: Optional[str] = None
+    message: str,
+    category: type[Warning] = UserWarning,
+    idx: Optional[str] = None,
+    stacklevel: int = 1,
 ) -> None:
     """
     Show a warning of the specified category only once per program run.
@@ -18,4 +21,4 @@ def show_warning_once(
 
     if key not in SEEN_MESSAGES:
         SEEN_MESSAGES.add(key)
-        show_warning(message, category)
+        show_warning(message, category, stacklevel)
diff --git a/qdrant_client/local/async_qdrant_local.py b/qdrant_client/local/async_qdrant_local.py
@@ -12,7 +12,6 @@
 import importlib.metadata
 import itertools
 import json
-import logging
 import os
 import shutil
 from copy import deepcopy
@@ -21,7 +20,7 @@
 from uuid import uuid4
 import numpy as np
 import portalocker
-from qdrant_client.common.client_warnings import show_warning_once
+from qdrant_client.common.client_warnings import show_warning, show_warning_once
 from qdrant_client._pydantic_compat import to_dict
 from qdrant_client.async_client_base import AsyncQdrantBase
 from qdrant_client.conversions import common_types as types
@@ -77,8 +76,10 @@ async def close(self, **kwargs: Any) -> None:
             if collection is not None:
                 collection.close()
             else:
-                logging.warning(
-                    f"Collection appears to be None before closing. The existing collections are: {list(self.collections.keys())}"
+                show_warning(
+                    message=f"Collection appears to be None before closing. The existing collections are: {list(self.collections.keys())}",
+                    category=UserWarning,
+                    stacklevel=4,
                 )
         try:
             if self._flock_file is not None and (not self._flock_file.closed):
@@ -108,10 +109,10 @@ def _load(self) -> None:
                     )
                     self.collections[collection_name] = collection
                     if len(collection.ids) > self.LARGE_DATA_THRESHOLD:
-                        show_warning_once(
+                        show_warning(
                             f"Local mode is not recommended for collections with more than {self.LARGE_DATA_THRESHOLD:,} points. Collection <{collection_name}> contains {len(collection.ids)} points. Consider using Qdrant in Docker or Qdrant Cloud for better performance with large datasets.",
                             category=UserWarning,
-                            idx="large-local-collection",
+                            stacklevel=5,
                         )
                 self.aliases = meta["aliases"]
         lock_file_path = os.path.join(self.location, ".lock")
@@ -1044,16 +1045,22 @@ async def create_payload_index(
         field_type: Optional[types.PayloadSchemaType] = None,
         **kwargs: Any,
     ) -> types.UpdateResult:
-        logging.warning(
-            "Payload indexes have no effect in the local Qdrant. Please use server Qdrant if you need payload indexes."
+        show_warning_once(
+            message="Payload indexes have no effect in the local Qdrant. Please use server Qdrant if you need payload indexes.",
+            category=UserWarning,
+            idx="create-local-payload-indexes",
+            stacklevel=5,
         )
         return self._default_update_result()
 
     async def delete_payload_index(
         self, collection_name: str, field_name: str, **kwargs: Any
     ) -> types.UpdateResult:
-        logging.warning(
-            "Payload indexes have no effect in the local Qdrant. Please use server Qdrant if you need payload indexes."
+        show_warning_once(
+            message="Payload indexes have no effect in the local Qdrant. Please use server Qdrant if you need payload indexes.",
+            category=UserWarning,
+            idx="delete-local-payload-indexes",
+            stacklevel=5,
         )
         return self._default_update_result()
 

diff --git a/qdrant_client/local/local_collection.py b/qdrant_client/local/local_collection.py
@@ -2196,6 +2196,7 @@ def upsert(self, points: Union[Sequence[models.PointStruct], models.Batch]) -> N
                 "Consider using Qdrant in Docker or Qdrant Cloud for better performance with large datasets.",
                 category=UserWarning,
                 idx="large-local-collection",
+                stacklevel=6,
             )
 
     def _update_named_vectors(

diff --git a/qdrant_client/local/qdrant_local.py b/qdrant_client/local/qdrant_local.py
@@ -21,7 +21,7 @@
 import numpy as np
 import portalocker
 
-from qdrant_client.common.client_warnings import show_warning_once
+from qdrant_client.common.client_warnings import show_warning, show_warning_once
 from qdrant_client._pydantic_compat import to_dict
 from qdrant_client.client_base import QdrantBase
 from qdrant_client.conversions import common_types as types
@@ -77,9 +77,11 @@ def close(self, **kwargs: Any) -> None:
             if collection is not None:
                 collection.close()
             else:
-                logging.warning(
-                    f"Collection appears to be None before closing. The existing collections are: "
-                    f"{list(self.collections.keys())}"
+                show_warning(
+                    message=f"Collection appears to be None before closing. The existing collections are: "
+                    f"{list(self.collections.keys())}",
+                    category=UserWarning,
+                    stacklevel=4,
                 )
 
         try:
@@ -111,14 +113,14 @@ def _load(self) -> None:
                     )
                     self.collections[collection_name] = collection
                     if len(collection.ids) > self.LARGE_DATA_THRESHOLD:
-                        show_warning_once(
+                        show_warning(
                             f"Local mode is not recommended for collections with more than "
                             f"{self.LARGE_DATA_THRESHOLD:,} points. "
                             f"Collection <{collection_name}> contains {len(collection.ids)} points. "
                             "Consider using Qdrant in Docker or Qdrant Cloud for better performance "
                             "with large datasets.",
                             category=UserWarning,
-                            idx="large-local-collection",
+                            stacklevel=5,
                         )
                 self.aliases = meta["aliases"]
 
@@ -1133,16 +1135,22 @@ def create_payload_index(
         field_type: Optional[types.PayloadSchemaType] = None,
         **kwargs: Any,
     ) -> types.UpdateResult:
-        logging.warning(
-            "Payload indexes have no effect in the local Qdrant. Please use server Qdrant if you need payload indexes."
+        show_warning_once(
+            message="Payload indexes have no effect in the local Qdrant. Please use server Qdrant if you need payload indexes.",
+            category=UserWarning,
+            idx="create-local-payload-indexes",
+            stacklevel=5,
         )
         return self._default_update_result()
 
     def delete_payload_index(
         self, collection_name: str, field_name: str, **kwargs: Any
     ) -> types.UpdateResult:
-        logging.warning(
-            "Payload indexes have no effect in the local Qdrant. Please use server Qdrant if you need payload indexes."
+        show_warning_once(
+            message="Payload indexes have no effect in the local Qdrant. Please use server Qdrant if you need payload indexes.",
+            category=UserWarning,
+            idx="delete-local-payload-indexes",
+            stacklevel=5,
         )
         return self._default_update_result()
 

diff --git a/qdrant_client/qdrant_client.py b/qdrant_client/qdrant_client.py
@@ -1553,6 +1553,7 @@ def upsert(
             """,
                 category=DeprecationWarning,
                 idx="grpc-input",
+                stacklevel=4,
             )
 
         requires_inference = self._inference_inspector.inspect(points)

diff --git a/qdrant_client/qdrant_fastembed.py b/qdrant_client/qdrant_fastembed.py
@@ -1,5 +1,4 @@
 import uuid
-import warnings
 from itertools import tee
 from typing import Any, Iterable, Optional, Sequence, Union, get_args
 from copy import deepcopy
@@ -21,6 +20,7 @@
 from qdrant_client.http import models
 from qdrant_client.hybrid.fusion import reciprocal_rank_fusion
 from qdrant_client import grpc
+from qdrant_client.common.client_warnings import show_warning
 
 try:
     from fastembed import (
@@ -153,11 +153,11 @@ def set_model(
         """
 
         if max_length is not None:
-            warnings.warn(
-                "max_length parameter is deprecated and will be removed in the future. "
+            show_warning(
+                message="max_length parameter is deprecated and will be removed in the future. "
                 "It's not used by fastembed models.",
-                DeprecationWarning,
-                stacklevel=2,
+                category=DeprecationWarning,
+                stacklevel=3,
             )
 
         self._get_or_init_model(