Cleanup

xarray/backends/api.py

@@ -98,18 +98,18 @@ def _validate_attrs(dataset):
     def check_attr(name, value):
         if isinstance(name, basestring):
             if not name:
-                raise ValueError('Invalid name for attr: string must be length '
-                                 '1 or greater for serialization to netCDF '
-                                 'files')
+                raise ValueError('Invalid name for attr: string must be '
+                                 'length 1 or greater for serialization to '
+                                 'netCDF files')
         else:
             raise TypeError("Invalid name for attr: {} must be a string for "
                             "serialization to netCDF files".format(name))
 
         if not isinstance(value, (basestring, Number, np.ndarray, np.number,
                                   list, tuple)):
             raise TypeError('Invalid value for attr: {} must be a number '
-                            'string, ndarray or a list/tuple of numbers/strings '
-                            'for serialization to netCDF '
+                            'string, ndarray or a list/tuple of '
+                            'numbers/strings for serialization to netCDF '
                             'files'.format(value))
 
     # Check attrs on the dataset itself
@@ -228,9 +228,11 @@ def maybe_decode_store(store, lock=False):
             try:
                 from dask.base import tokenize
             except ImportError:
-                import dask  # raise the usual error if dask is entirely missing
+                # raise the usual error if dask is entirely missing
+                import dask
                 if StrictVersion(dask.__version__) < StrictVersion('0.6'):
-                    raise ImportError('xarray requires dask version 0.6 or newer')
+                    raise ImportError(
+                        'xarray requires dask version 0.6 or newer')
                 else:
                     raise
 

xarray/core/alignment.py

@@ -6,7 +6,6 @@
 from collections import defaultdict
 
 import numpy as np
-import pandas as pd
 
 from . import ops, utils
 from .common import _maybe_promote

xarray/core/common.py

@@ -4,7 +4,7 @@
 import numpy as np
 import pandas as pd
 
-from .pycompat import (basestring, suppress, dask_array_type, OrderedDict)
+from .pycompat import basestring, suppress, dask_array_type, OrderedDict
 from . import formatting
 from .utils import SortedKeysDict, not_implemented, Frozen
 
@@ -599,9 +599,11 @@ def where(self, cond, other=None, drop=False):
         ----------
         cond : boolean DataArray or Dataset
         other : unimplemented, optional
-            Unimplemented placeholder for compatibility with future numpy / pandas versions
+            Unimplemented placeholder for compatibility with future
+            numpy / pandas versions
         drop : boolean, optional
-            Coordinate labels that only correspond to NA values should be dropped
+            Coordinate labels that only correspond to NA values should be
+            dropped
 
         Returns
         -------
@@ -633,7 +635,8 @@ def where(self, cond, other=None, drop=False):
           * y        (y) int64 0 1 2 3 4
         """
         if other is not None:
-            raise NotImplementedError("The optional argument 'other' has not yet been implemented")
+            raise NotImplementedError("The optional argument 'other' has not "
+                                      "yet been implemented")
 
         if drop:
             from .dataarray import DataArray
@@ -675,11 +678,11 @@ def __enter__(self):
     def __exit__(self, exc_type, exc_value, traceback):
         self.close()
 
-    # this has no runtime function - these are listed so IDEs know these methods
-    # are defined and don't warn on these operations
-    __lt__ = __le__ =__ge__ = __gt__ = __add__ = __sub__ = __mul__ = \
-    __truediv__ = __floordiv__ = __mod__ = __pow__ = __and__  = __xor__ = \
-    __or__ = __div__ = __eq__ = __ne__ = not_implemented
+    # this has no runtime function - these are listed so IDEs know these
+    # methods are defined and don't warn on these operations
+    __lt__ = __le__ = __ge__ = __gt__ = __add__ = __sub__ = __mul__ = \
+        __truediv__ = __floordiv__ = __mod__ = __pow__ = __and__ = __xor__ = \
+        __or__ = __div__ = __eq__ = __ne__ = not_implemented
 
 
 def _maybe_promote(dtype):

xarray/core/dataset.py

@@ -28,8 +28,6 @@
                        broadcast_variables)
 from .pycompat import (iteritems, basestring, OrderedDict,
                        dask_array_type, range)
-from .combine import concat
-from .formatting import ensure_valid_repr
 from .options import OPTIONS
 
 # list of attributes of pd.DatetimeIndex that are ndarrays of time info
@@ -154,8 +152,8 @@ def merge_indexes(
         for n in var_names:
             names.append(n)
             var = variables[n]
-            if (current_index_variable is not None and
-                        var.dims != current_index_variable.dims):
+            if ((current_index_variable is not None) and
+                    (var.dims != current_index_variable.dims)):
                 raise ValueError(
                     "dimension mismatch between %r %s and %r %s"
                     % (dim, current_index_variable.dims, n, var.dims))
@@ -1222,7 +1220,6 @@ def isel_points(self, dim='points', **indexers):
         Dataset.sel_points
         DataArray.isel_points
         """
-        from .dataarray import DataArray
 
         indexer_dims = set(indexers)
 
@@ -2098,7 +2095,7 @@ def reduce(self, func, dim=None, keep_attrs=False, numeric_only=False,
                 if name not in self.coords:
                     if (not numeric_only or
                             np.issubdtype(var.dtype, np.number) or
-                                var.dtype == np.bool_):
+                            (var.dtype == np.bool_)):
                         if len(reduce_dims) == 1:
                             # unpack dimensions for the benefit of functions
                             # like np.argmin which can't handle tuple arguments
@@ -2810,7 +2807,7 @@ def filter_by_attrs(self, **kwargs):
             for attr_name, pattern in kwargs.items():
                 attr_value = variable.attrs.get(attr_name)
                 if ((callable(pattern) and pattern(attr_value))
-                    or attr_value == pattern):
+                        or attr_value == pattern):
                     selection.append(var_name)
         return self[selection]
 

xarray/core/formatting.py

@@ -16,8 +16,7 @@
 from pandas.tslib import OutOfBoundsDatetime
 
 from .options import OPTIONS
-from .pycompat import (
-    PY2, unicode_type, bytes_type, dask_array_type, OrderedDict, basestring)
+from .pycompat import PY2, unicode_type, bytes_type, dask_array_type
 
 
 def pretty_print(x, numchars):
@@ -49,7 +48,7 @@ def ensure_valid_repr(string):
     On Python 2, this means we need to convert unicode to bytes. We won't need
     this function once we drop Python 2.7 support.
     """
-    if PY2 and isinstance(string, unicode):
+    if PY2 and isinstance(string, unicode_type):
         string = string.encode('utf-8')
     return string
 

xarray/core/groupby.py

@@ -82,6 +82,7 @@ def _consolidate_slices(slices):
     """Consolidate adjacent slices in a list of slices.
     """
     result = []
+    last_slice = slice(None)
     for slice_ in slices:
         if not isinstance(slice_, slice):
             raise ValueError('list element is not a slice: %r' % slice_)

xarray/core/npcompat.py

@@ -24,7 +24,6 @@ def _maybe_view_as_subclass(original_array, new_array):
                 new_array.__array_finalize__(original_array)
         return new_array
 
-
     def _broadcast_to(array, shape, subok, readonly):
         shape = tuple(shape) if np.iterable(shape) else (shape,)
         array = np.array(array, copy=False, subok=subok)
@@ -41,7 +40,6 @@ def _broadcast_to(array, shape, subok, readonly):
             result.flags.writeable = True
         return result
 
-
     def broadcast_to(array, shape, subok=False):
         """Broadcast an array to a new shape.
 
@@ -78,7 +76,6 @@ def broadcast_to(array, shape, subok=False):
         """
         return _broadcast_to(array, shape, subok=subok, readonly=True)
 
-
     def stack(arrays, axis=0):
         """
         Join a sequence of arrays along a new axis.
@@ -143,7 +140,6 @@ def stack(arrays, axis=0):
         expanded_arrays = [arr[sl] for arr in arrays]
         return np.concatenate(expanded_arrays, axis=axis)
 
-
     def _replace_nan(a, val):
         """
         If `a` is of inexact type, make a copy of `a`, replace NaNs with
@@ -185,7 +181,6 @@ def _replace_nan(a, val):
         np.copyto(a, val, where=mask)
         return a, mask
 
-
     def nanprod(a, axis=None, dtype=None, out=None, keepdims=0):
         """
         Return the product of array elements over a given axis treating Not a
@@ -255,12 +250,11 @@ def nanprod(a, axis=None, dtype=None, out=None, keepdims=0):
         a, mask = _replace_nan(a, 1)
         return np.prod(a, axis=axis, dtype=dtype, out=out, keepdims=keepdims)
 
-
     def nancumsum(a, axis=None, dtype=None, out=None):
         """
-        Return the cumulative sum of array elements over a given axis treating Not a
-        Numbers (NaNs) as zero.  The cumulative sum does not change when NaNs are
-        encountered and leading NaNs are replaced by zeros.
+        Return the cumulative sum of array elements over a given axis treating
+        Not a Numbers (NaNs) as zero.  The cumulative sum does not change when
+        NaNs are encountered and leading NaNs are replaced by zeros.
 
         Zeros are returned for slices that are all-NaN or empty.
 
@@ -320,12 +314,11 @@ def nancumsum(a, axis=None, dtype=None, out=None):
         a, mask = _replace_nan(a, 0)
         return np.cumsum(a, axis=axis, dtype=dtype, out=out)
 
-
     def nancumprod(a, axis=None, dtype=None, out=None):
         """
-        Return the cumulative product of array elements over a given axis treating Not a
-        Numbers (NaNs) as one.  The cumulative product does not change when NaNs are
-        encountered and leading NaNs are replaced by ones.
+        Return the cumulative product of array elements over a given axis
+        treating Not a Numbers (NaNs) as one.  The cumulative product does not
+        change when NaNs are encountered and leading NaNs are replaced by ones.
 
         Ones are returned for slices that are all-NaN or empty.
 

xarray/core/utils.py

@@ -101,8 +101,8 @@ def equivalent(first, second):
     if isinstance(first, np.ndarray) or isinstance(second, np.ndarray):
         return ops.array_equiv(first, second)
     else:
-        return (first is second or
-                first == second or
+        return ((first is second) or
+                (first == second) or
                 (pd.isnull(first) and pd.isnull(second)))
 
 

xarray/core/variable.py

@@ -896,8 +896,8 @@ def reduce(self, func, dim=None, axis=None, keep_attrs=False,
 
         if getattr(func, 'keep_dims', False):
             if dim is None and axis is None:
-                raise ValueError("must supply either single 'dim' or 'axis' argument to %s"
-                                 % (func.__name__))
+                raise ValueError("must supply either single 'dim' or 'axis' "
+                                 "argument to %s" % (func.__name__))
 
         if dim is not None:
             axis = self.get_axis_num(dim)

xarray/plot/plot.py

@@ -227,8 +227,6 @@ def hist(darray, figsize=None, size=None, aspect=None, ax=None, **kwargs):
         Additional keyword arguments to matplotlib.pyplot.hist
 
     """
-    import matplotlib.pyplot as plt
-
     ax = get_axis(figsize, size, aspect, ax)
 
     no_nan = np.ravel(darray.values)

xarray/tests/__init__.py

@@ -9,8 +9,7 @@
 from numpy.testing import assert_array_equal
 import pytest
 
-from xarray.core import utils, nputils, ops
-from xarray.core.variable import as_variable
+from xarray.core import utils
 from xarray.core.pycompat import PY3
 from xarray.testing import assert_equal, assert_identical, assert_allclose