def test_case_1(self):
"""
Test basic path: read existing file in parquet format
"""
_ds = DataSet()
_ds.open_dataset('./data/MICROFEAT@RENKO_EURJPY_10_Bid_UTC',
format='parquet')
_test_1 = _ds.metadata['mf_columns'][0] == 'tick_mean'
_test_2 = len(_ds.data) == 2584
return _test_1 and _test_2
def test_case_5(self):
"""
Test alternative path: read existing file in csv format and pass options to pandas:
"""
_ds = DataSet()
_ds.open_dataset('./data/MICROFEAT@RENKO_EURJPY_10_Bid_UTC',
format='csv',
index_col='date_time')
_test_1 = _ds.metadata['mf_columns'][0] == 'tick_mean'
_test_2 = len(_ds.data) == 2584
return (_ds.data.index.name == 'date_time')
def test_case_4(self):
"""
Test alternative path: read non-existent format for existing file
"""
_ds = DataSet()
try:
_ds.open_dataset('./data/MICROFEAT@RENKO_EURJPY_10_Bid_UTC',
format='xls')
except Exception as e:
print(str(e))
return True
return False
def test_case_3(self):
"""
Test alternative path: read non existing file
"""
_ds = DataSet()
try:
_ds.open_dataset('./datax/MICROFEAT@RENKO_EURJPY_10_Bid_UTC',
format='csv')
except FileNotFoundError as e:
print(str(e))
return True
return False
def test_case_7(self):
"""
Test alternative path: read and write csv format file
"""
_fn = 'MICROFEAT@RENKO_EURJPY_10_Bid_UTC'
_ds = DataSet()
_ds.open_dataset(f'./data/{_fn}', format='csv')
_ds.set_metadata('test_case', 6)
_ds.data['test_case'] = 6
_fn_new = _fn.replace('MICROFEAT', 'TEST')
_ds.save_dataset(f'./data/{_fn_new}', format='csv')
_ds_new = DataSet()
_ds_new.open_dataset(f'./data/{_fn_new}', format='csv')
_test_1 = _ds_new.metadata['test_case'] == 6
_test_2 = _ds.data['test_case'].mean() == 6
return _test_1 and _test_2