def test_logs_updated_chunks_data_with_meta_chunks(
self, background_job_manager: BackgroundJobManager) -> None:
"""Test logs updated chunks data when meta chunks is not empty."""
fake_not_empty_data_frame = DataFrame({"col1": [42]})
mocked_sql_to_data_frame: MagicMock = MagicMock()
mocked_sql_to_data_frame.return_value = fake_not_empty_data_frame
background_job_manager._sql_to_data_frame = ( # type: ignore
mocked_sql_to_data_frame)
background_job_manager._create_chunks_dictionary = MagicMock(
) # type: ignore
background_job_manager._calculate_chunks_difference = MagicMock(
) # type: ignore
background_job_manager._calculate_chunks_difference.return_value = {
"new": 55
} # type: ignore
background_job_manager._update_chunks_data()
global mocked_storage_cursor
background_job_manager._create_chunks_dictionary.assert_called_once_with( # type: ignore
fake_not_empty_data_frame)
background_job_manager._calculate_chunks_difference.assert_called_once(
) # type: ignore
mocked_storage_cursor.log_meta_information.assert_called_once_with(
"chunks_data", {"chunks_data_meta_information": '{"new": 55}'}, 42)
mocked_storage_cursor = MagicMock()
mocked_storage_cursor.log_meta_information.return_value = None
def test_successfully_calculates_chunk_differences(
self, background_job_manager: BackgroundJobManager) -> None:
"""Test successfully calculates chunks differences."""
fake_base_dict: Dict[str, Dict[str, List[int]]] = {
"customer": {
"c_custkey": [15000],
"c_name": [15000]
},
"supplier": {
"s_address": [1000],
"s_comment": [600]
},
}
fake_substractor_dict: Dict[str, Dict[str, List[int]]] = {
"customer": {
"c_custkey": [1000],
"c_name": [5000]
},
"supplier": {
"s_address": [1000],
"s_comment": [555]
},
}
expected_dict: Dict[str, Dict[str, List[int]]] = {
"customer": {
"c_custkey": [14000],
"c_name": [10000]
},
"supplier": {
"s_address": [0],
"s_comment": [45]
},
}
received_dict: Dict = background_job_manager._calculate_chunks_difference(
fake_base_dict, fake_substractor_dict)
assert expected_dict == received_dict