def test_process_datapoint_gets_value():
val = Mock()
data_type = 'my_data_type'
point = {
'startTimeNanos': 1,
'endTimeNanos': 1,
'value': [{data_type: val}]
}
with patch('gfitpy.gfit_api.datetime'), \
patch('gfitpy.gfit_api.DateRange'):
ret = GfitAPI.process_datapoint(point, data_type)
assert ret['value'] == val
def test_process_datapoint_creates_timerange():
point = {
'startTimeNanos': 1000000000,
'endTimeNanos': 2000000000,
'value': [MagicMock()]
}
with patch('gfitpy.gfit_api.datetime') as dt, \
patch('gfitpy.gfit_api.DateRange') as dr:
# use the str cast as a way to distinguish what goes in (1, 2) and what comes out ('1', '2')
dt.fromtimestamp.side_effect = str
ret = GfitAPI.process_datapoint(point, Mock())
assert dt.fromtimestamp.call_args_list == [call(1), call(2)]
dr.assert_called_once_with('1.0', '2.0')
assert ret['times'] == dr.return_value
def test_process_datapoint_raises(point):
with pytest.raises(ValueError):
GfitAPI.process_datapoint(point, data_type=Mock())
