>>> import iris
>>> from iris.time import PartialDateTime
>>> iris.FUTURE.cell_datetime_objects = True
>>> cube = iris.load_cube("/data/local/itbb/git/iris-test-data/test_data/PP/globClim1/theta.pp")
>>> print cube
air_potential_temperature / (K)     (model_level_number: 38; latitude: 145; longitude: 192)
     Dimension coordinates:
          model_level_number                           x             -               -
          latitude                                     -             x               -
          longitude                                    -             -               x
     Auxiliary coordinates:
          level_height                                 x             -               -
          sigma                                        x             -               -
     Scalar coordinates:
          forecast_period: 26280 hours
          forecast_reference_time: 2005-01-01 00:00:00
          time: 2008-01-01 00:00:00, bound=(2007-12-01 00:00:00, 2008-01-01 00:00:00)
     Attributes:
          STASH: m01s00i004
          source: Data from Met Office Unified Model 6.06
     Cell methods:
          mean: time (1 hour)
>>> cube.extract(iris.Constraint(time=lambda cell: cell == PartialDateTime(year=2008)))
<iris 'Cube' of air_potential_temperature / (K) (model_level_number: 38; latitude: 145; longitude: 192)>
>>> cube.extract(iris.Constraint(time=lambda cell: cell == PartialDateTime(day=1)))
<iris 'Cube' of air_potential_temperature / (K) (model_level_number: 38; latitude: 145; longitude: 192)>
>>> cube.extract(iris.Constraint(time=lambda cell: cell == PartialDateTime(month=1)))
>>>