test: optimizing variable names (milvus-io#34035)

Signed-off-by: elstic <hao.wang@zilliz.com>

tests/python_client/common/common_func.py

@@ -364,10 +364,10 @@ def gen_collection_schema_all_datatype(description=ct.default_desc,
     else:
         multiple_dim_array.insert(0, dim)
         for i in range(len(multiple_dim_array)):
-            if ct.all_float_vector_types[i%3] != ct.sparse_vector:
-                fields.append(gen_float_vec_field(name=f"multiple_vector_{ct.all_float_vector_types[i%3]}",
+            if ct.append_vector_type[i%3] != ct.sparse_vector:
+                fields.append(gen_float_vec_field(name=f"multiple_vector_{ct.append_vector_type[i%3]}",
                                               dim=multiple_dim_array[i],
-                                              vector_data_type=ct.all_float_vector_types[i%3]))
+                                              vector_data_type=ct.append_vector_type[i%3]))
             else:
                 # The field of a sparse vector cannot be dimensioned
                 fields.append(gen_float_vec_field(name=f"multiple_vector_{ct.sparse_vector}",
@@ -719,7 +719,7 @@ def gen_dataframe_all_data_type(nb=ct.default_nb, dim=ct.default_dim, start=0, w
         df[ct.default_float_vec_field_name] = float_vec_values
     else:
         for i in range(len(multiple_dim_array)):
-            df[multiple_vector_field_name[i]] = gen_vectors(nb, multiple_dim_array[i], ct.all_float_vector_types[i%3])
+            df[multiple_vector_field_name[i]] = gen_vectors(nb, multiple_dim_array[i], ct.append_vector_type[i%3])
 
     if with_json is False:
         df.drop(ct.default_json_field_name, axis=1, inplace=True)
@@ -757,7 +757,7 @@ def gen_general_list_all_data_type(nb=ct.default_nb, dim=ct.default_dim, start=0
         insert_list.append(float_vec_values)
     else:
         for i in range(len(multiple_dim_array)):
-            insert_list.append(gen_vectors(nb, multiple_dim_array[i], ct.all_float_vector_types[i%3]))
+            insert_list.append(gen_vectors(nb, multiple_dim_array[i], ct.append_vector_type[i%3]))
 
     if with_json is False:
         # index = insert_list.index(json_values)
@@ -802,7 +802,7 @@ def gen_default_rows_data_all_data_type(nb=ct.default_nb, dim=ct.default_dim, st
         else:
             for i in range(len(multiple_dim_array)):
                 dict[multiple_vector_field_name[i]] = gen_vectors(nb, multiple_dim_array[i],
-                                                                  ct.all_float_vector_types[i])[0]
+                                                                  ct.append_vector_type[i])[0]
     if len(multiple_dim_array) != 0:
         with open(ct.rows_all_data_type_file_path + f'_{partition_id}' + f'_dim{dim}.txt', 'wb') as json_file:
             pickle.dump(array, json_file)
@@ -1792,7 +1792,7 @@ def insert_data(collection_w, nb=ct.default_nb, is_binary=False, is_all_data_typ
                                                                   multiple_vector_field_name=vector_name_list,
                                                                   vector_data_type=vector_data_type,
                                                                   auto_id=auto_id, primary_field=primary_field)
-                    elif vector_data_type in ct.all_float_vector_types:
+                    elif vector_data_type in ct.append_vector_type:
                         default_data = gen_general_default_list_data(nb // num, dim=dim, start=start, with_json=with_json,
                                                                      random_primary_key=random_primary_key,
                                                                      multiple_dim_array=multiple_dim_array,

tests/python_client/common/common_type.py

@@ -45,7 +45,8 @@
 float16_type = "FLOAT16_VECTOR"
 bfloat16_type = "BFLOAT16_VECTOR"
 sparse_vector = "SPARSE_FLOAT_VECTOR"
-all_float_vector_types = [float16_type, bfloat16_type, sparse_vector]
+append_vector_type = [float16_type, bfloat16_type, sparse_vector]
+all_dense_vector_types = [float_type, float16_type, bfloat16_type]
 default_sparse_vec_field_name = "sparse_vector"
 default_partition_name = "_default"
 default_resource_group_name = '__default_resource_group'

tests/python_client/testcases/test_search.py

@@ -6961,7 +6961,7 @@ def enable_dynamic_field(self, request):
     ******************************************************************
     """
     @pytest.mark.tags(CaseLabel.L0)
-    @pytest.mark.parametrize("vector_data_type", ["FLOAT_VECTOR", "FLOAT16_VECTOR", "BFLOAT16_VECTOR"])
+    @pytest.mark.parametrize("vector_data_type", ct.all_dense_vector_types)
     def test_range_search_default(self, index_type, metric, vector_data_type):
         """
         target: verify the range search returns correct results