Remove outdated code related to compatibility with netcdftime

doc/whats-new.rst

@@ -22,6 +22,11 @@ Breaking changes
 ~~~~~~~~~~~~~~~~
 
 - Minimum cftime version is now 1.0.3. By `Deepak Cherian <https://github.com/dcherian>`_.
+- All leftover support for dates from non-standard calendars through netcdftime, the
+  module included in versions of netCDF4 prior to 1.4 that eventually became the
+  cftime package, has been removed in favor of relying solely on the standalone
+  cftime package (:pull:`3450`).  By `Spencer Clark 
+  <https://github.com/spencerkclark>`_. 
 
 New Features
 ~~~~~~~~~~~~

xarray/coding/times.py

@@ -39,34 +39,6 @@
 )
 
 
-def _import_cftime():
-    """
-    helper function handle the transition to netcdftime/cftime
-    as a stand-alone package
-    """
-    try:
-        import cftime
-    except ImportError:
-        # in netCDF4 the num2date/date2num function are top-level api
-        try:
-            import netCDF4 as cftime
-        except ImportError:
-            raise ImportError("Failed to import cftime")
-    return cftime
-
-
-def _require_standalone_cftime():
-    """Raises an ImportError if the standalone cftime is not found"""
-    try:
-        import cftime  # noqa: F401
-    except ImportError:
-        raise ImportError(
-            "Decoding times with non-standard calendars "
-            "or outside the pandas.Timestamp-valid range "
-            "requires the standalone cftime package."
-        )
-
-
 def _netcdf_to_numpy_timeunit(units):
     units = units.lower()
     if not units.endswith("s"):
@@ -119,16 +91,11 @@ def _decode_cf_datetime_dtype(data, units, calendar, use_cftime):
 
 
 def _decode_datetime_with_cftime(num_dates, units, calendar):
-    cftime = _import_cftime()
+    import cftime
 
-    if cftime.__name__ == "cftime":
-        return np.asarray(
-            cftime.num2date(num_dates, units, calendar, only_use_cftime_datetimes=True)
-        )
-    else:
-        # Must be using num2date from an old version of netCDF4 which
-        # does not have the only_use_cftime_datetimes option.
-        return np.asarray(cftime.num2date(num_dates, units, calendar))
+    return np.asarray(
+        cftime.num2date(num_dates, units, calendar, only_use_cftime_datetimes=True)
+    )
 
 
 def _decode_datetime_with_pandas(flat_num_dates, units, calendar):
@@ -354,7 +321,7 @@ def _encode_datetime_with_cftime(dates, units, calendar):
     This method is more flexible than xarray's parsing using datetime64[ns]
     arrays but also slower because it loops over each element.
     """
-    cftime = _import_cftime()
+    import cftime
 
     if np.issubdtype(dates.dtype, np.datetime64):
         # numpy's broken datetime conversion only works for us precision

xarray/tests/__init__.py

@@ -78,10 +78,6 @@ def LooseVersion(vstring):
 requires_scipy_or_netCDF4 = pytest.mark.skipif(
     not has_scipy_or_netCDF4, reason="requires scipy or netCDF4"
 )
-has_cftime_or_netCDF4 = has_cftime or has_netCDF4
-requires_cftime_or_netCDF4 = pytest.mark.skipif(
-    not has_cftime_or_netCDF4, reason="requires cftime or netCDF4"
-)
 try:
     import_seaborn()
     has_seaborn = True

xarray/tests/test_accessor_dt.py

@@ -7,10 +7,8 @@
 from . import (
     assert_array_equal,
     assert_equal,
-    has_cftime,
-    has_cftime_or_netCDF4,
-    has_dask,
     raises_regex,
+    requires_cftime,
     requires_dask,
 )
 
@@ -199,7 +197,7 @@ def times_3d(times):
     )
 
 
-@pytest.mark.skipif(not has_cftime, reason="cftime not installed")
+@requires_cftime
 @pytest.mark.parametrize(
     "field", ["year", "month", "day", "hour", "dayofyear", "dayofweek"]
 )
@@ -217,7 +215,7 @@ def test_field_access(data, field):
     assert_equal(result, expected)
 
 
-@pytest.mark.skipif(not has_cftime, reason="cftime not installed")
+@requires_cftime
 def test_cftime_strftime_access(data):
     """ compare cftime formatting against datetime formatting """
     date_format = "%Y%m%d%H"
@@ -232,8 +230,8 @@ def test_cftime_strftime_access(data):
     assert_equal(result, expected)
 
 
-@pytest.mark.skipif(not has_dask, reason="dask not installed")
-@pytest.mark.skipif(not has_cftime, reason="cftime not installed")
+@requires_cftime
+@requires_dask
 @pytest.mark.parametrize(
     "field", ["year", "month", "day", "hour", "dayofyear", "dayofweek"]
 )
@@ -254,8 +252,8 @@ def test_dask_field_access_1d(data, field):
     assert_equal(result.compute(), expected)
 
 
-@pytest.mark.skipif(not has_dask, reason="dask not installed")
-@pytest.mark.skipif(not has_cftime, reason="cftime not installed")
+@requires_cftime
+@requires_dask
 @pytest.mark.parametrize(
     "field", ["year", "month", "day", "hour", "dayofyear", "dayofweek"]
 )
@@ -286,7 +284,7 @@ def cftime_date_type(calendar):
     return _all_cftime_date_types()[calendar]
 
 
-@pytest.mark.skipif(not has_cftime, reason="cftime not installed")
+@requires_cftime
 def test_seasons(cftime_date_type):
     dates = np.array([cftime_date_type(2000, month, 15) for month in range(1, 13)])
     dates = xr.DataArray(dates)
@@ -307,15 +305,3 @@ def test_seasons(cftime_date_type):
     seasons = xr.DataArray(seasons)
 
     assert_array_equal(seasons.values, dates.dt.season.values)
-
-
-@pytest.mark.skipif(not has_cftime_or_netCDF4, reason="cftime or netCDF4 not installed")
-def test_dt_accessor_error_netCDF4(cftime_date_type):
-    da = xr.DataArray(
-        [cftime_date_type(1, 1, 1), cftime_date_type(2, 1, 1)], dims=["time"]
-    )
-    if not has_cftime:
-        with pytest.raises(TypeError):
-            da.dt.month
-    else:
-        da.dt.month

xarray/tests/test_cftimeindex.py

@@ -15,7 +15,7 @@
 )
 from xarray.tests import assert_array_equal, assert_identical
 
-from . import has_cftime, has_cftime_or_netCDF4, raises_regex, requires_cftime
+from . import raises_regex, requires_cftime
 from .test_coding_times import (
     _ALL_CALENDARS,
     _NON_STANDARD_CALENDARS,
@@ -653,7 +653,7 @@ def test_indexing_in_dataframe_iloc(df, index):
     assert result.equals(expected)
 
 
-@pytest.mark.skipif(not has_cftime_or_netCDF4, reason="cftime not installed")
+@requires_cftime
 def test_concat_cftimeindex(date_type):
     da1 = xr.DataArray(
         [1.0, 2.0], coords=[[date_type(1, 1, 1), date_type(1, 2, 1)]], dims=["time"]
@@ -663,11 +663,7 @@ def test_concat_cftimeindex(date_type):
     )
     da = xr.concat([da1, da2], dim="time")
 
-    if has_cftime:
-        assert isinstance(da.indexes["time"], CFTimeIndex)
-    else:
-        assert isinstance(da.indexes["time"], pd.Index)
-        assert not isinstance(da.indexes["time"], CFTimeIndex)
+    assert isinstance(da.indexes["time"], CFTimeIndex)
 
 
 @requires_cftime