BUG: ensure xray works with pandas 0.17.0

.travis.yml

@@ -32,7 +32,9 @@ matrix:
         - libnetcdf-dev
     env: UPDATE_ENV="conda install cython && pip install https://github.com/Unidata/netcdf4-python/archive/master.zip"
   - python: 2.7
-    env: UPDATE_ENV="pip install toolz https://github.com/ContinuumIO/dask/archive/master.zip"
+    env: UPDATE_ENV="pip install toolz https://github.com/blaze/dask/archive/master.zip"
+  - python: 2.7
+    env: UPDATE_ENV="conda remove pandas && conda install cython && pip install https://github.com/pydata/pandas/archive/master.zip"
   allow_failures:
   - python: 2.7
     env: UPDATE_ENV="pip install pydap"
@@ -44,7 +46,9 @@ matrix:
         - libnetcdf-dev
     env: UPDATE_ENV="conda install cython && pip install https://github.com/Unidata/netcdf4-python/archive/master.zip"
   - python: 2.7
-    env: UPDATE_ENV="pip install toolz https://github.com/ContinuumIO/dask/archive/master.zip"
+    env: UPDATE_ENV="pip install toolz https://github.com/blaze/dask/archive/master.zip"
+  - python: 2.7
+    env: UPDATE_ENV="conda remove pandas && conda install cython && pip install https://github.com/pydata/pandas/archive/master.zip"
 
 before_install:
   - if [[ "$TRAVIS_PYTHON_VERSION" == "2.7" ]]; then

doc/whats-new.rst

@@ -32,6 +32,9 @@ Enhancements
 Bug fixes
 ~~~~~~~~~
 
+- Forwards compatibility with the next release of changes (v0.17.0).
+  We were using some internal pandas routines for datetime conversion, which
+  unfortunately have now changed upstream (:issue:`569`).
 - Aggregation functions now correctly skip ``NaN`` for data for ``complex128``
   dtype (:issue:`554`).
 - Fixed indexing 0d arrays with unicode dtype (:issue:`568`).

xray/core/common.py

@@ -418,13 +418,6 @@ def _maybe_promote(dtype):
 
 def _possibly_convert_objects(values):
     """Convert arrays of datetime.datetime and datetime.timedelta objects into
-    datetime64 and timedelta64
+    datetime64 and timedelta64, according to the pandas convention.
     """
-    try:
-        converter = functools.partial(pd.core.common._possibly_convert_objects,
-                                      convert_numeric=False)
-    except AttributeError:
-        # our fault for using a private pandas API that has gone missing
-        # this should do the same coercion (though it will be slower)
-        converter = lambda x: np.asarray(pd.Series(x))
-    return converter(values.ravel()).reshape(values.shape)
+    return np.asarray(pd.Series(values.ravel())).reshape(values.shape)

xray/core/variable.py

@@ -119,11 +119,11 @@ def _as_compatible_data(data, fastpath=False):
             data = np.asarray(data)
 
     if isinstance(data, np.ndarray):
-        data = common._possibly_convert_objects(data)
-        if data.dtype.kind == 'M':
-            # TODO: automatically cast arrays of datetime objects as well
+        if data.dtype.kind == 'O':
+            data = common._possibly_convert_objects(data)
+        elif data.dtype.kind == 'M':
             data = np.asarray(data, 'datetime64[ns]')
-        if data.dtype.kind == 'm':
+        elif data.dtype.kind == 'm':
             data = np.asarray(data, 'timedelta64[ns]')
 
     return _maybe_wrap_data(data)

xray/test/test_dask.py

@@ -151,12 +151,14 @@ def test_concat(self):
 
     def test_missing_methods(self):
         v = self.lazy_var
-        with self.assertRaisesRegexp(NotImplementedError, 'dask'):
-            v.conj()
-        with self.assertRaisesRegexp(NotImplementedError, 'dask'):
+        try:
             v.argsort()
-        with self.assertRaisesRegexp(NotImplementedError, 'dask'):
+        except NotImplementedError as err:
+            self.assertIn('dask', str(err))
+        try:
             v[0].item()
+        except NotImplementedError as err:
+            self.assertIn('dask', str(err))
 
     def test_ufuncs(self):
         u = self.eager_var