def test_should_call_csv_reader_and_storage_engine(self, write_mock):
batch_frames = [list(range(5))] * 2
# creates a dummy.csv
create_sample_csv()
file_path = 'dummy.csv'
table_metainfo = 'info'
batch_mem_size = 3000
file_options = {}
file_options['file_format'] = FileFormatType.CSV
column_list = [
TupleValueExpression(col_name='id', table_alias='dummy'),
TupleValueExpression(col_name='frame_id', table_alias='dummy'),
TupleValueExpression(col_name='video_id', table_alias='dummy')
]
plan = type(
"LoadDataPlan", (), {
'table_metainfo': table_metainfo,
'file_path': file_path,
'batch_mem_size': batch_mem_size,
'column_list': column_list,
'file_options': file_options
})
load_executor = LoadDataExecutor(plan)
batch = next(load_executor.exec())
write_mock.has_calls(call(table_metainfo, batch_frames[0]),
call(table_metainfo, batch_frames[1]))
# Note: We call exec() from the child classes.
self.assertEqual(
batch,
Batch(
pd.DataFrame([{
'CSV': file_path,
'Number of loaded frames': 20
}])))
# remove the dummy.csv
file_remove('dummy.csv')
def tearDown(self):
file_remove('dummy.avi')
def tearDown(self):
file_remove('dummy.csv')
def tearDown(self):
file_remove("dummy.avi")
def tearDownClass(cls):
file_remove('ua_detrac.mp4')
def tearDownClass(cls):
file_remove("dummy.avi")
def tearDownClass(cls):
file_remove('dummy.avi')
file_remove('ua_detrac.mp4')
