Merge remote-tracking branch 'upstream/master' into load_nonindex_coords

.travis.yml

@@ -39,6 +39,8 @@ matrix:
     env: CONDA_ENV=py36-bottleneck-dev
   - python: 3.6
     env: CONDA_ENV=py36-condaforge-rc
+  - python: 3.6
+    env: CONDA_ENV=py36-pynio-dev
   allow_failures:
   - python: 3.6
     env:
@@ -59,6 +61,8 @@ matrix:
     env: CONDA_ENV=py36-bottleneck-dev
   - python: 3.6
     env: CONDA_ENV=py36-condaforge-rc
+  - python: 3.6
+    env: CONDA_ENV=py36-pynio-dev
 
 before_install:
   - if [[ "$TRAVIS_PYTHON_VERSION" == "2.7" ]]; then

ci/requirements-py36-pynio-dev.yml

@@ -0,0 +1,25 @@
+name: test_env
+channels:
+  - conda-forge
+  - ncar
+dependencies:
+  - python=3.6
+  - dask
+  - distributed
+  - h5py
+  - h5netcdf
+  - matplotlib
+  - netcdf4
+  - pynio=dev
+  - pytest
+  - numpy
+  - pandas
+  - scipy
+  - seaborn
+  - toolz
+  - rasterio
+  - bottleneck
+  - pip:
+    - coveralls
+    - pytest-cov
+    - pydap

doc/whats-new.rst

@@ -203,6 +203,7 @@ Bug fixes
 - ``:py:meth:`~xarray.Dataset.__init__` raises a ``MergeError`` if an
   coordinate shares a name with a dimension but is comprised of arbitrary
   dimensions(:issue:`1120`).
+
 - :py:func:`~xarray.open_rasterio` method now skips rasterio.crs -attribute if
   it is none.
   By `Leevi Annala <https://github.com/leevei>`_.
@@ -215,6 +216,21 @@ Bug fixes
   when objects other than  ``Dataset`` are provided (:issue:`1555`).
   By `Joe Hamman <https://github.com/jhamman>`_.
 
+- :py:func:`xarray.concat` would eagerly load dask variables into memory if
+  the first argument was a numpy variable (:issue:`1588`).
+  By `Guido Imperiale <https://github.com/crusaderky>`_.
+
+- Fix ``netCDF4`` backend to properly roundtrip the ``shuffle`` encoding option
+  (:issue:`1606`).
+  By `Joe Hamman <https://github.com/jhamman>`_.
+
+- Fix bug when using ``pytest`` class decorators to skiping certain unittests.
+  The previous behavior unintentionally causing additional tests to be skipped
+  (:issue:`1531`). By `Joe Hamman <https://github.com/jhamman>`_.
+
+- Fix pynio backend for upcoming release of pynio with python3 support 
+  (:issue:`1611`). By `Ben Hillman <https://github/brhillman>`_.
+
 .. _whats-new.0.9.6:
 
 v0.9.6 (8 June 2017)

xarray/backends/netCDF4_.py

@@ -153,7 +153,7 @@ def _extract_nc4_variable_encoding(variable, raise_on_invalid=False,
 
     safe_to_drop = set(['source', 'original_shape'])
     valid_encodings = set(['zlib', 'complevel', 'fletcher32', 'contiguous',
-                           'chunksizes'])
+                           'chunksizes', 'shuffle'])
     if lsd_okay:
         valid_encodings.add('least_significant_digit')
 

xarray/backends/pynio_.py

@@ -57,7 +57,7 @@ def open_store_variable(self, name, var):
     def get_variables(self):
         with self.ensure_open(autoclose=False):
             return FrozenOrderedDict((k, self.open_store_variable(k, v))
-                                     for k, v in self.ds.variables.iteritems())
+                                     for k, v in self.ds.variables.items())
 
     def get_attrs(self):
         with self.ensure_open(autoclose=True):

xarray/conventions.py

@@ -858,12 +858,14 @@ def decode_cf_variable(var, concat_characters=True, mask_and_scale=True,
             if ('_FillValue' in attributes and
                 not utils.equivalent(attributes['_FillValue'],
                                      attributes['missing_value'])):
-                raise ValueError("Discovered conflicting _FillValue "
-                                 "and missing_value.  Considering "
-                                 "opening the offending dataset using "
-                                 "decode_cf=False, corrected the attributes",
-                                 "and decoding explicitly using "
-                                 "xarray.conventions.decode_cf(ds)")
+                raise ValueError("Conflicting _FillValue and missing_value "
+                                 "attributes on a variable: {} vs. {}\n\n"
+                                 "Consider opening the offending dataset "
+                                 "using decode_cf=False, correcting the "
+                                 "attributes and decoding explicitly using "
+                                 "xarray.decode_cf()."
+                                 .format(attributes['_FillValue'],
+                                         attributes['missing_value']))
             attributes['_FillValue'] = attributes.pop('missing_value')
         fill_value = np.array(pop_to(attributes, encoding, '_FillValue'))
         if fill_value.size > 1:

xarray/core/duck_array_ops.py

@@ -40,9 +40,11 @@ def _dask_or_eager_func(name, eager_module=np, list_of_args=False,
     """Create a function that dispatches to dask for dask array inputs."""
     if has_dask:
         def f(*args, **kwargs):
-            dispatch_args = args[0] if list_of_args else args
-            if any(isinstance(a, da.Array)
-                   for a in dispatch_args[:n_array_args]):
+            if list_of_args:
+                dispatch_args = args[0]
+            else:
+                dispatch_args = args[:n_array_args]
+            if any(isinstance(a, da.Array) for a in dispatch_args):
                 module = da
             else:
                 module = eager_module

xarray/core/groupby.py

@@ -236,8 +236,8 @@ def __init__(self, obj, group, squeeze=False, grouper=None, bins=None,
                 raise ValueError('index must be monotonic for resampling')
             s = pd.Series(np.arange(index.size), index)
             first_items = s.groupby(grouper).first()
+            full_index = first_items.index
             if first_items.isnull().any():
-                full_index = first_items.index
                 first_items = first_items.dropna()
             sbins = first_items.values.astype(np.int64)
             group_indices = ([slice(i, j)

xarray/tests/__init__.py

@@ -5,6 +5,7 @@
 from contextlib import contextmanager
 from distutils.version import LooseVersion
 import re
+import importlib
 
 import numpy as np
 from numpy.testing import assert_array_equal
@@ -25,111 +26,50 @@
 except ImportError:
     import mock
 
-try:
-    import scipy
-    has_scipy = True
-except ImportError:
-    has_scipy = False
-
-try:
-    import pydap.client
-    has_pydap = True
-except ImportError:
-    has_pydap = False
-
-try:
-    import netCDF4
-    has_netCDF4 = True
-except ImportError:
-    has_netCDF4 = False
-
-
-try:
-    import h5netcdf
-    has_h5netcdf = True
-except ImportError:
-    has_h5netcdf = False
-
-
-try:
-    import Nio
-    has_pynio = True
-except ImportError:
-    has_pynio = False
-
-
-try:
-    import dask.array
-    import dask
-    dask.set_options(get=dask.get)
-    has_dask = True
-except ImportError:
-    has_dask = False
-
-
-try:
-    import matplotlib
-    has_matplotlib = True
-except ImportError:
-    has_matplotlib = False
-
 
-try:
-    import bottleneck
-    if LooseVersion(bottleneck.__version__) < LooseVersion('1.1'):
-        raise ImportError('Fall back to numpy')
-    has_bottleneck = True
-except ImportError:
-    has_bottleneck = False
-
-try:
-    import rasterio
-    has_rasterio = True
-except ImportError:
-    has_rasterio = False
-
-try:
-    import pathlib
-    has_pathlib = True
-except ImportError:
+def _importorskip(modname, minversion=None):
     try:
-        import pathlib2
-        has_pathlib = True
+        mod = importlib.import_module(modname)
+        has = True
+        if minversion is not None:
+            if LooseVersion(mod.__version__) < LooseVersion(minversion):
+                raise ImportError('Minimum version not satisfied')
     except ImportError:
-        has_pathlib = False
-
-
-# slighly simpler construction that the full functions.
-# Generally `pytest.importorskip('package')` inline is even easier
-requires_matplotlib = pytest.mark.skipif(
-    not has_matplotlib, reason='requires matplotlib')
-requires_scipy = pytest.mark.skipif(
-    not has_scipy, reason='requires scipy')
-requires_pydap = pytest.mark.skipif(
-    not has_pydap, reason='requires pydap')
-requires_netCDF4 = pytest.mark.skipif(
-    not has_netCDF4, reason='requires netCDF4')
-requires_h5netcdf = pytest.mark.skipif(
-    not has_h5netcdf, reason='requires h5netcdf')
-requires_pynio = pytest.mark.skipif(
-    not has_pynio, reason='requires pynio')
-requires_scipy_or_netCDF4 = pytest.mark.skipif(
-    not has_scipy and not has_netCDF4, reason='requires scipy or netCDF4')
-requires_dask = pytest.mark.skipif(
-    not has_dask, reason='requires dask')
-requires_bottleneck = pytest.mark.skipif(
-    not has_bottleneck, reason='requires bottleneck')
-requires_rasterio = pytest.mark.skipif(
-    not has_rasterio, reason='requires rasterio')
-requires_pathlib = pytest.mark.skipif(
-    not has_pathlib, reason='requires pathlib / pathlib2'
-)
-
+        has = False
+    # TODO: use pytest.skipif instead of unittest.skipUnless
+    # Using `unittest.skipUnless` is a temporary workaround for pytest#568,
+    # wherein class decorators stain inherited classes.
+    # xref: xarray#1531, implemented in xarray #1557.
+    func = unittest.skipUnless(has, reason='requires {}'.format(modname))
+    return has, func
+
+
+has_matplotlib, requires_matplotlib = _importorskip('matplotlib')
+has_scipy, requires_scipy = _importorskip('scipy')
+has_pydap, requires_pydap = _importorskip('pydap.client')
+has_netCDF4, requires_netCDF4 = _importorskip('netCDF4')
+has_h5netcdf, requires_h5netcdf = _importorskip('h5netcdf')
+has_pynio, requires_pynio = _importorskip('Nio')
+has_dask, requires_dask = _importorskip('dask')
+has_bottleneck, requires_bottleneck = _importorskip('bottleneck')
+has_rasterio, requires_rasterio = _importorskip('rasterio')
+has_pathlib, requires_pathlib = _importorskip('pathlib')
+
+# some special cases
+has_scipy_or_netCDF4 = has_scipy or has_netCDF4
+requires_scipy_or_netCDF4 = unittest.skipUnless(
+    has_scipy_or_netCDF4, reason='requires scipy or netCDF4')
+if not has_pathlib:
+    has_pathlib, requires_pathlib = _importorskip('pathlib2')
+
+if has_dask:
+    import dask
+    dask.set_options(get=dask.get)
 
 try:
     _SKIP_FLAKY = not pytest.config.getoption("--run-flaky")
     _SKIP_NETWORK_TESTS = not pytest.config.getoption("--run-network-tests")
-except ValueError:
+except (ValueError, AttributeError):
     # Can't get config from pytest, e.g., because xarray is installed instead
     # of being run from a development version (and hence conftests.py is not
     # available). Don't run flaky tests.

xarray/tests/test_backends.py

@@ -729,6 +729,7 @@ def test_compression_encoding(self):
         data['var2'].encoding.update({'zlib': True,
                                       'chunksizes': (5, 5),
                                       'fletcher32': True,
+                                      'shuffle': True,
                                       'original_shape': data.var2.shape})
         with self.roundtrip(data) as actual:
             for k, v in iteritems(data['var2'].encoding):
@@ -1179,7 +1180,7 @@ def test_encoding_unlimited_dims(self):
 
 
 # tests pending h5netcdf fix
-@pytest.mark.xfail
+@unittest.skip
 class H5NetCDFDataTestAutocloseTrue(H5NetCDFDataTest):
     autoclose = True
 
@@ -1846,6 +1847,11 @@ def test_extract_nc4_variable_encoding(self):
         encoding = _extract_nc4_variable_encoding(var)
         self.assertEqual({}, encoding)
 
+        # regression test
+        var = xr.Variable(('x',), [1, 2, 3], {}, {'shuffle': True})
+        encoding = _extract_nc4_variable_encoding(var, raise_on_invalid=True)
+        self.assertEqual({'shuffle': True}, encoding)
+
     def test_extract_h5nc_encoding(self):
         # not supported with h5netcdf (yet)
         var = xr.Variable(('x',), [1, 2, 3], {},

xarray/tests/test_conventions.py

@@ -451,11 +451,9 @@ def test_cf_timedelta(self):
             ('1us', 'microseconds', np.int64(1)),
             (['NaT', '0s', '1s'], None, [np.nan, 0, 1]),
             (['30m', '60m'], 'hours', [0.5, 1.0]),
+            (np.timedelta64('NaT', 'ns'), 'days', np.nan),
+            (['NaT', 'NaT'], 'days', [np.nan, np.nan]),
         ]
-        if pd.__version__ >= '0.16':
-            # not quite sure why, but these examples don't work on older pandas
-            examples.extend([(np.timedelta64('NaT', 'ns'), 'days', np.nan),
-                             (['NaT', 'NaT'], 'days', [np.nan, np.nan])])
 
         for timedeltas, units, numbers in examples:
             timedeltas = pd.to_timedelta(timedeltas, box=False)