def test_query_output_multi_float_vec_field(self, vec_fields): """ target: test query and output multi float vec fields method: a.specify multi vec field as output b.specify output_fields with wildcard % expected: verify query result """ # init collection with two float vector fields schema = cf.gen_schema_multi_vector_fields(vec_fields) collection_w = self.init_collection_wrap( name=cf.gen_unique_str(prefix), schema=schema) df = cf.gen_dataframe_multi_vec_fields(vec_fields=vec_fields) collection_w.insert(df) assert collection_w.num_entities == ct.default_nb # query with two vec output_fields output_fields = [ ct.default_int64_field_name, ct.default_float_vec_field_name ] for vec_field in vec_fields: output_fields.append(vec_field.name) res = df.loc[:1, output_fields].to_dict('records') collection_w.load() collection_w.query(default_term_expr, output_fields=output_fields, check_task=CheckTasks.check_query_results, check_items={ exp_res: res, "with_vec": True })
def init_multi_fields_collection_wrap(self, name=cf.gen_unique_str()): vec_fields = [cf.gen_float_vec_field(ct.another_float_vec_field_name)] schema = cf.gen_schema_multi_vector_fields(vec_fields) collection_w = self.init_collection_wrap(name=name, schema=schema) df = cf.gen_dataframe_multi_vec_fields(vec_fields=vec_fields) collection_w.insert(df) assert collection_w.num_entities == ct.default_nb return collection_w, df
def test_insert_multi_float_vec_fields(self, vec_fields): """ target: test insert into multi float vec fields collection method: create collection with different schema and insert expected: verify num entities """ schema = cf.gen_schema_multi_vector_fields(vec_fields) collection_w = self.init_collection_wrap(name=cf.gen_unique_str(prefix), schema=schema) df = cf.gen_dataframe_multi_vec_fields(vec_fields=vec_fields) collection_w.insert(df) assert collection_w.num_entities == ct.default_nb