def test_calculate_entries_without_registered_calculations(self):
cols = ['braz', 'uiae', 'dummy_calc', 'nrtd']
cc = ColumnCalculator(cols)
entries = ('braz', 'uiae', 1, 'nrtd', )
result = cc.add_entries(list(entries))
self.assertEqual(tuple(result), entries)
result = cc.calculate_entries(list(entries))
self.assertEqual(result, entries)
def get_latest(cls, session, columns):
cc = ColumnCalculator(columns)
menu_entries = cls.map_names_to_attributes(columns)
menu_entries = cc.add_entries(menu_entries)
query = session.query(*menu_entries)
query = query.order_by(cls.id.desc())
entry = query.first()
return cc.calculate_entries(entry)
def test_add_entries(self):
class DummyCalculation(object):
name = 'dummy_calc'
needed_columns = ['foo', 'bar']
ColumnCalculator.register_calculation(DummyCalculation)
cols = ['braz', 'uiae', 'dummy_calc', 'nrtd']
cc = ColumnCalculator(cols)
expected = ['braz', 'uiae', 'foo', 'bar', 'nrtd']
result = cc.add_entries(cols)
self.assertEqual(result, expected)
def test_calculate_entries(self):
class DummyCalculation(object):
name = 'dummy_calc'
needed_columns = ['foo', 'bar']
@staticmethod
def calc(val1, val2):
return val1 - val2
ColumnCalculator.register_calculation(DummyCalculation)
cols = ['braz', 'uiae', 'dummy_calc', 'nrtd']
cc = ColumnCalculator(cols)
entries = ['braz', 'uiae', 1, 5, 'nrtd']
result = cc.calculate_entries(entries)
expected = ('braz', 'uiae', -4, 'nrtd', )
self.assertEqual(result, expected)
def get_values_in_timespan_wo_avg(cls, session, columns, span_with_resolution):
cc = ColumnCalculator(columns)
menu_entries = cls.map_names_to_attributes(columns)
menu_entries = cc.add_entries(menu_entries)
tsp_start = span_with_resolution.start_as_timestamp()
tsp_end = span_with_resolution.end_as_timestamp()
query = session.query(*menu_entries)
query = query.filter(cls.tsp.between(tsp_start, tsp_end))
result = query.all()
if len(result) != 0:
result = tuple(cc.calculate_entries(r) for r in result)
return result
def get_values_in_timespan_with_avg(cls, session, columns, span_with_resolution):
cc = ColumnCalculator(columns)
menu_entries = cls.map_names_to_attributes(columns)
menu_entries = cc.add_entries(menu_entries)
avg_columns = map(func.avg, menu_entries)
ret = []
for avg_start, avg_end in span_with_resolution:
query = session.query(*avg_columns)
query = query.filter(cls.tsp.between(avg_start,
avg_end))
result = query.all()[0]
if result[0] is not None:
ret.append(cc.calculate_entries(result))
return tuple(ret)
