test: update sdk version and add cases (milvus-io#38478)

Signed-off-by: nico <[email protected]>

tests/python_client/common/code_mapping.py

@@ -40,7 +40,7 @@ class IndexErrorMessage(ExceptionsMessage):
     CheckBitmapIndex = "bitmap index are only supported on bool, int, string"
     CheckBitmapOnPK = "create bitmap index on primary key not supported"
     CheckBitmapCardinality = "failed to check bitmap cardinality limit, should be larger than 0 and smaller than 1000"
-    NotConfigable = "{0} is not configable index param"
+    NotConfigable = "{0} is not a configable index proptery"
     InvalidOffsetCache = "invalid offset cache index params"
     OneIndexPerField = "at most one distinct index is allowed per field"
     AlterOnLoadedCollection = "can't alter index on loaded collection, please release the collection first"

tests/python_client/common/common_func.py

@@ -982,13 +982,13 @@ def gen_collection_schema_all_datatype(description=ct.default_desc, primary_fiel
             if ct.append_vector_type[i%3] != ct.sparse_vector:
                 if default_value_fields.get(ct.append_vector_type[i%3]) is None:
                     vector_field = gen_float_vec_field(name=f"multiple_vector_{ct.append_vector_type[i%3]}",
-                                                              dim=multiple_dim_array[i],
-                                                              vector_data_type=ct.append_vector_type[i%3])
+                                                       dim=multiple_dim_array[i],
+                                                       vector_data_type=ct.append_vector_type[i%3])
                 else:
                     vector_field = gen_float_vec_field(name=f"multiple_vector_{ct.append_vector_type[i%3]}",
-                                                              dim=multiple_dim_array[i],
-                                                              vector_data_type=ct.append_vector_type[i%3],
-                                                              default_value=default_value_fields.get(ct.append_vector_type[i%3]))
+                                                       dim=multiple_dim_array[i],
+                                                       vector_data_type=ct.append_vector_type[i%3],
+                                                       default_value=default_value_fields.get(ct.append_vector_type[i%3]))
                 fields.append(vector_field)
             else:
                 # The field of a sparse vector cannot be dimensioned

tests/python_client/requirements.txt

@@ -27,8 +27,8 @@ pytest-parallel
 pytest-random-order
 
 # pymilvus
-pymilvus==2.5.1rc9
-pymilvus[bulk_writer]==2.5.1rc9
+pymilvus==2.5.1rc14
+pymilvus[bulk_writer]==2.5.1rc14
 
 
 # for customize config test

tests/python_client/testcases/test_index.py

@@ -1428,15 +1428,15 @@ def test_alter_index_invalid(self):
         collection_w.alter_index(ct.default_index_name, {"error_param_key": 123},
                                  check_task=CheckTasks.err_res,
                                  check_items={ct.err_code: 1100,
-                                              ct.err_msg: f"error_param_key is not configable index param"})
+                                              ct.err_msg: "error_param_key is not a configable index proptery:"})
         collection_w.alter_index(ct.default_index_name, ["error_param_type"],
                                  check_task=CheckTasks.err_res,
                                  check_items={ct.err_code: 1,
                                               ct.err_msg: f"Unexpected error"})
         collection_w.alter_index(ct.default_index_name, None,
                                  check_task=CheckTasks.err_res,
                                  check_items={ct.err_code: 1,
-                                              ct.err_msg: f"extra_params should not be None"})
+                                              ct.err_msg: "properties should not be None"})
         collection_w.alter_index(ct.default_index_name, 1000,
                                  check_task=CheckTasks.err_res,
                                  check_items={ct.err_code: 1,

tests/python_client/testcases/test_issues.py

@@ -9,6 +9,7 @@
 
 
 class TestIssues(TestcaseBase):
+
     @pytest.mark.tags(CaseLabel.L0)
     @pytest.mark.parametrize("par_key_field", [ct.default_int64_field_name])
     @pytest.mark.parametrize("use_upsert", [True, False])
@@ -75,4 +76,41 @@ def test_issue_30607(self, par_key_field, use_upsert):
                     log.info(f"dirty data found: pk {pk} with parkey {parkey_value}")
                     dirty_count += 1
                     assert dirty_count == 0
-            log.info(f"check randomly {seeds}/{num_entities}, dirty count={dirty_count}")
+            log.info(f"check randomly {seeds}/{num_entities}, dirty count={dirty_count}")
+
+    @pytest.mark.tags(CaseLabel.L2)
+    def test_issue_32294(self):
+        """
+        Method：
+        1. create a collection with partition key on collection schema with customized num_partitions
+        2. randomly check 200 entities
+        2. verify partition key values are hashed into correct partitions
+        """
+        self._connect()
+        pk_field = cf.gen_int64_field(name='pk', is_primary=True)
+        string_field = cf.gen_string_field(name="metadata")
+        vector_field = cf.gen_float_vec_field()
+        schema = cf.gen_collection_schema(fields=[pk_field, string_field, vector_field], auto_id=True)
+        collection_w = self.init_collection_wrap(schema=schema)
+
+        # insert
+        nb = 500
+        string_values = [str(i) for i in range(0, nb)]
+        float_vec_values = gen_vectors(nb, ct.default_dim)
+        string_values[0] = ('{\n'
+                            '"Header 1": "Foo1?", \n'
+                            '"document_category": "acme", \n'
+                            '"type": "passage"\n'
+                            '}')
+        string_values[1] = '{"Header 1": "Foo1?", "document_category": "acme", "type": "passage"}'
+        data = [string_values, float_vec_values]
+        collection_w.insert(data)
+        collection_w.create_index(field_name=ct.default_float_vec_field_name, index_params=ct.default_index)
+        collection_w.load()
+
+        expr = "metadata like '%passage%'"
+        collection_w.search(float_vec_values[-2:], ct.default_float_vec_field_name, {},
+                            ct.default_limit, expr, output_fields=["metadata"],
+                            check_task=CheckTasks.check_search_results,
+                            check_items={"nq": 2,
+                                         "limit": 2})

tests/python_client/testcases/test_search.py

@@ -10628,7 +10628,7 @@ def test_search_group_by_unsupported_index(self, index):
 
             # search with groupby
             err_code = 999
-            err_msg = "doesn't support search_group_by"
+            err_msg = f"current index:{index} doesn't support"
             collection_w.search(data=search_vectors, anns_field=ct.default_float_vec_field_name,
                                 param=search_params, limit=limit,
                                 group_by_field=ct.default_int8_field_name,