Add netcdftime as an optional dependency.

.travis.yml

@@ -45,6 +45,8 @@ matrix:
     env: CONDA_ENV=py36-rasterio1.0alpha
   - python: 3.6
     env: CONDA_ENV=py36-zarr-dev
+  - python: 3.6
+    env: CONDA_ENV=py36-netcdftime-dev
   - python: 3.5
     env: CONDA_ENV=docs
   allow_failures:
@@ -73,6 +75,8 @@ matrix:
     env: CONDA_ENV=py36-rasterio1.0alpha
   - python: 3.6
     env: CONDA_ENV=py36-zarr-dev
+  - python: 3.6
+    env: CONDA_ENV=py36-netcdftime-dev
 
 before_install:
   - if [[ "$TRAVIS_PYTHON_VERSION" == "2.7" ]]; then

ci/requirements-py36-netcdftime-dev.yml

@@ -0,0 +1,13 @@
+name: test_env
+channels:
+  - conda-forge
+dependencies:
+  - python=3.6
+  - pytest
+  - flake8
+  - numpy
+  - pandas
+  - netcdftime
+  - pip:
+    - coveralls
+    - pytest-cov

doc/installing.rst

@@ -25,6 +25,8 @@ For netCDF and IO
 - `pynio <https://www.pyngl.ucar.edu/Nio.shtml>`__: for reading GRIB and other
   geoscience specific file formats
 - `zarr <http://zarr.readthedocs.io/>`__: for chunked, compressed, N-dimensional arrays.
+- `netcdftime <https://github.com/Unidata/netcdftime>`__: recommended if you
+  want to encode/decode datetimes for non-standard calendars.
 
 For accelerating xarray
 ~~~~~~~~~~~~~~~~~~~~~~~

doc/whats-new.rst

@@ -93,6 +93,10 @@ Enhancements
 - Speed of reindexing/alignment with dask array is orders of magnitude faster
   when inserting missing values  (:issue:`1847`).
   By `Stephan Hoyer <https://github.com/shoyer>`_.
+- Add ``netcdftime`` as an optional dependency of xarray. This allows for
+  encoding/decoding of datetimes with non-standard calendars without the
+  netCDF4 dependency (:issue:`1084`).
+  By `Joe Hamman <https://github.com/jhamman>`_.
 
 .. _Zarr: http://zarr.readthedocs.io/
 

xarray/backends/api.py

@@ -443,7 +443,7 @@ def open_mfdataset(paths, chunks=None, concat_dim=_CONCAT_DIM_DEFAULT,
                    lock=None, data_vars='all', coords='different', **kwargs):
     """Open multiple files as a single dataset.
 
-    Requires dask to be installed. See documentation for details on dask [1].  
+    Requires dask to be installed. See documentation for details on dask [1].
     Attributes from the first dataset file are used for the combined dataset.
 
     Parameters

xarray/coding/times.py

@@ -40,6 +40,26 @@
                         'milliseconds', 'microseconds'])
 
 
+def _import_netcdftime():
+    '''
+    helper function handle the transition to netcdftime as a stand-alone
+    package
+    '''
+    try:
+        # Try importing netcdftime directly
+        import netcdftime as nctime
+        if not hasattr(nctime, 'num2date'):
+            # must have gotten an old version from netcdf4-python
+            raise ImportError
+    except ImportError:
+        # in netCDF4 the num2date/date2num function are top-level api
+        try:
+            import netCDF4 as nctime
+        except ImportError:
+            raise ImportError("Failed to import netcdftime")
+    return nctime
+
+
 def _netcdf_to_numpy_timeunit(units):
     units = units.lower()
     if not units.endswith('s'):
@@ -59,23 +79,23 @@ def _unpack_netcdf_time_units(units):
     return delta_units, ref_date
 
 
-def _decode_datetime_with_netcdf4(num_dates, units, calendar):
-    import netCDF4 as nc4
+def _decode_datetime_with_netcdftime(num_dates, units, calendar):
+    nctime = _import_netcdftime()
 
-    dates = np.asarray(nc4.num2date(num_dates, units, calendar))
+    dates = np.asarray(nctime.num2date(num_dates, units, calendar))
     if (dates[np.nanargmin(num_dates)].year < 1678 or
             dates[np.nanargmax(num_dates)].year >= 2262):
         warnings.warn('Unable to decode time axis into full '
                       'numpy.datetime64 objects, continuing using dummy '
-                      'netCDF4.datetime objects instead, reason: dates out'
+                      'netcdftime.datetime objects instead, reason: dates out'
                       ' of range', SerializationWarning, stacklevel=3)
     else:
         try:
             dates = nctime_to_nptime(dates)
         except ValueError as e:
             warnings.warn('Unable to decode time axis into full '
                           'numpy.datetime64 objects, continuing using '
-                          'dummy netCDF4.datetime objects instead, reason:'
+                          'dummy netcdftime.datetime objects instead, reason:'
                           '{0}'.format(e), SerializationWarning, stacklevel=3)
     return dates
 
@@ -111,15 +131,15 @@ def decode_cf_datetime(num_dates, units, calendar=None):
     numpy array of date time objects.
 
     For standard (Gregorian) calendars, this function uses vectorized
-    operations, which makes it much faster than netCDF4.num2date. In such a
+    operations, which makes it much faster than netcdftime.num2date. In such a
     case, the returned array will be of type np.datetime64.
 
     Note that time unit in `units` must not be smaller than microseconds and
     not larger than days.
 
     See also
     --------
-    netCDF4.num2date
+    netcdftime.num2date
     """
     num_dates = np.asarray(num_dates)
     flat_num_dates = num_dates.ravel()
@@ -137,7 +157,7 @@ def decode_cf_datetime(num_dates, units, calendar=None):
             ref_date = pd.Timestamp(ref_date)
         except ValueError:
             # ValueError is raised by pd.Timestamp for non-ISO timestamp
-            # strings, in which case we fall back to using netCDF4
+            # strings, in which case we fall back to using netcdftime
             raise OutOfBoundsDatetime
 
         # fixes: https://github.com/pydata/pandas/issues/14068
@@ -155,9 +175,8 @@ def decode_cf_datetime(num_dates, units, calendar=None):
                  ref_date).values
 
     except (OutOfBoundsDatetime, OverflowError):
-        dates = _decode_datetime_with_netcdf4(flat_num_dates.astype(np.float),
-                                              units,
-                                              calendar)
+        dates = _decode_datetime_with_netcdftime(
+            flat_num_dates.astype(np.float), units, calendar)
 
     return dates.reshape(num_dates.shape)
 
@@ -215,7 +234,7 @@ def infer_timedelta_units(deltas):
 
 
 def nctime_to_nptime(times):
-    """Given an array of netCDF4.datetime objects, return an array of
+    """Given an array of netcdftime.datetime objects, return an array of
     numpy.datetime64 objects of the same size"""
     times = np.asarray(times)
     new = np.empty(times.shape, dtype='M8[ns]')
@@ -235,20 +254,20 @@ def _cleanup_netcdf_time_units(units):
     return units
 
 
-def _encode_datetime_with_netcdf4(dates, units, calendar):
-    """Fallback method for encoding dates using netCDF4-python.
+def _encode_datetime_with_netcdftime(dates, units, calendar):
+    """Fallback method for encoding dates using netcdftime.
 
     This method is more flexible than xarray's parsing using datetime64[ns]
     arrays but also slower because it loops over each element.
     """
-    import netCDF4 as nc4
+    nctime = _import_netcdftime()
 
     if np.issubdtype(dates.dtype, np.datetime64):
         # numpy's broken datetime conversion only works for us precision
         dates = dates.astype('M8[us]').astype(datetime)
 
     def encode_datetime(d):
-        return np.nan if d is None else nc4.date2num(d, units, calendar)
+        return np.nan if d is None else nctime.date2num(d, units, calendar)
 
     return np.vectorize(encode_datetime)(dates)
 
@@ -268,7 +287,7 @@ def encode_cf_datetime(dates, units=None, calendar=None):
 
     See also
     --------
-    netCDF4.date2num
+    netcdftime.date2num
     """
     dates = np.asarray(dates)
 
@@ -283,7 +302,7 @@ def encode_cf_datetime(dates, units=None, calendar=None):
     delta, ref_date = _unpack_netcdf_time_units(units)
     try:
         if calendar not in _STANDARD_CALENDARS or dates.dtype.kind == 'O':
-            # parse with netCDF4 instead
+            # parse with netcdftime instead
             raise OutOfBoundsDatetime
         assert dates.dtype == 'datetime64[ns]'
 
@@ -293,7 +312,7 @@ def encode_cf_datetime(dates, units=None, calendar=None):
         num = (dates - ref_date) / time_delta
 
     except (OutOfBoundsDatetime, OverflowError):
-        num = _encode_datetime_with_netcdf4(dates, units, calendar)
+        num = _encode_datetime_with_netcdftime(dates, units, calendar)
 
     num = cast_to_int_if_safe(num)
     return (num, units, calendar)

xarray/tests/__init__.py

@@ -68,6 +68,7 @@ def _importorskip(modname, minversion=None):
 has_netCDF4, requires_netCDF4 = _importorskip('netCDF4')
 has_h5netcdf, requires_h5netcdf = _importorskip('h5netcdf')
 has_pynio, requires_pynio = _importorskip('Nio')
+has_netcdftime, requires_netcdftime = _importorskip('netcdftime')
 has_dask, requires_dask = _importorskip('dask')
 has_bottleneck, requires_bottleneck = _importorskip('bottleneck')
 has_rasterio, requires_rasterio = _importorskip('rasterio')

xarray/tests/test_conventions.py

@@ -13,8 +13,8 @@
 from xarray.core import utils, indexing
 from xarray.testing import assert_identical
 from . import (
-    TestCase, requires_netCDF4, unittest, raises_regex, IndexerMaker,
-    assert_array_equal)
+    TestCase, requires_netCDF4, requires_netcdftime, unittest, raises_regex,
+    IndexerMaker, assert_array_equal)
 from .test_backends import CFEncodedDataTest
 from xarray.core.pycompat import iteritems
 from xarray.backends.memory import InMemoryDataStore
@@ -181,7 +181,7 @@ def test_decode_cf_with_conflicting_fill_missing_value():
     assert_identical(actual, expected)
 
 
-@requires_netCDF4
+@requires_netcdftime
 class TestEncodeCFVariable(TestCase):
     def test_incompatible_attributes(self):
         invalid_vars = [
@@ -237,7 +237,7 @@ def test_multidimensional_coordinates(self):
         assert 'coordinates' not in attrs
 
 
-@requires_netCDF4
+@requires_netcdftime
 class TestDecodeCF(TestCase):
     def test_dataset(self):
         original = Dataset({
@@ -303,7 +303,7 @@ def test_invalid_time_units_raises_eagerly(self):
         with raises_regex(ValueError, 'unable to decode time'):
             decode_cf(ds)
 
-    @requires_netCDF4
+    @requires_netcdftime
     def test_dataset_repr_with_netcdf4_datetimes(self):
         # regression test for #347
         attrs = {'units': 'days since 0001-01-01', 'calendar': 'noleap'}
@@ -316,7 +316,7 @@ def test_dataset_repr_with_netcdf4_datetimes(self):
         ds = decode_cf(Dataset({'time': ('time', [0, 1], attrs)}))
         assert '(time) datetime64[ns]' in repr(ds)
 
-    @requires_netCDF4
+    @requires_netcdftime
     def test_decode_cf_datetime_transition_to_invalid(self):
         # manually create dataset with not-decoded date
         from datetime import datetime