Fix tests

docs/indexes.rst

@@ -76,7 +76,7 @@ on fields ``_from`` and ``_to``. For more information on indexes, refer to
             },
         )
 
-        # Index creation may succeed even if vector training fails.
+        # Index creation may succeed even if there is insufficient training data.
         if vector_index.training_state != "ready":
             raise RuntimeError(
                 vector_index.error_message or "Vector index is not ready"
@@ -86,7 +86,10 @@ Omitted or scaling-object ``nLists``, ``numberOfDocsPerCentroid``, factory
 placeholders such as ``IVF{},Flat``, and successful-but-unusable creation
 behavior require ArangoDB 3.12.10 or later. A successful creation response
 means that the index exists, but callers should check ``training_state`` before
-using it. If training fails permanently, the state is ``"unusable"`` and
-``error_message`` describes the failure.
+using it. If there is insufficient data to train the index, the state is
+``"unusable"`` and ``error_message`` describes the failure. Invalid index
+definitions, such as an ``nLists`` value that disagrees with the number of
+centroids in the factory string, are rejected during creation with
+``IndexCreateError`` and no index is created.
 
 See :class:`arangoasync.collection.StandardCollection` for API specification.

tests/test_collection.py

@@ -337,24 +337,6 @@ async def test_collection_index(doc_col, bad_col, cluster, db_version):
         await doc_col.delete_index(default_index.id)
         await doc_col.delete_index(scaling_index.id)
 
-        # A permanent training failure still creates an unusable index.
-        unusable_index = await doc_col.add_index(
-            "vector",
-            ["embedding1"],
-            {
-                "name": "vector_index_unusable",
-                "params": {
-                    "metric": "cosine",
-                    "dimension": 128,
-                    "nLists": 2,
-                    "factory": "IVF3,Flat",
-                },
-            },
-        )
-        assert unusable_index.training_state == "unusable"
-        assert unusable_index.error_message
-        await doc_col.delete_index(unusable_index.id)
-
         # Invalid requests continue to fail at the HTTP layer.
         with pytest.raises(IndexCreateError) as err:
             await doc_col.add_index(
@@ -378,6 +360,30 @@ async def test_collection_index(doc_col, bad_col, cluster, db_version):
     assert await doc_col.delete_index(idx2.id, ignore_missing=True) is False
 
 
+@pytest.mark.asyncio
+async def test_unusable_vector_index(doc_col, db_version):
+    if db_version < version.parse("3.12.10"):
+        pytest.skip("Unusable vector index test requires ArangoDB 3.12.10+")
+
+    # One training vector is insufficient for two centroids.
+    await doc_col.insert({"embedding": [1.0, 1.0]})
+    index = await doc_col.add_index(
+        "vector",
+        ["embedding"],
+        {
+            "name": "vector_index_unusable",
+            "params": {
+                "metric": "cosine",
+                "dimension": 2,
+                "nLists": 2,
+            },
+        },
+    )
+    assert index.training_state == "unusable"
+    assert index.error_message
+    await doc_col.delete_index(index.id)
+
+
 @pytest.mark.asyncio
 async def test_collection_truncate_count(docs, doc_col, bad_col):
     # Test errors

tests/test_user.py

@@ -4,6 +4,7 @@
 from arangoasync.errno import USER_NOT_FOUND
 from arangoasync.exceptions import (
     CollectionCreateError,
+    CollectionListError,
     DocumentInsertError,
     PermissionResetError,
     PermissionUpdateError,
@@ -176,6 +177,14 @@ async def test_user_change_permissions(sys_db, arango_client, db):
     with pytest.raises(PermissionResetError):
         await db.reset_permission(username, db.name)
     await sys_db.reset_permission(username, db.name)
+    assert await sys_db.permission(username, db.name) == "none"
+    # ArangoDB 4.0 returns 403 where earlier versions returned 401.
+    with pytest.raises(CollectionCreateError) as err:
+        await db2.create_collection(generate_col_name())
+    assert err.value.http_code in {401, 403}
+    with pytest.raises(CollectionListError) as err:
+        await db2.collections()
+    assert err.value.http_code in {401, 403}
     with pytest.raises(DocumentInsertError):
         await col.insert({"_key": "test"})