Revisit # noqa annotations (#3359)

asv_bench/benchmarks/__init__.py

@@ -16,7 +16,7 @@ def decorator(func):
 
 def requires_dask():
     try:
-        import dask  # noqa
+        import dask  # noqa: F401
     except ImportError:
         raise NotImplementedError
 

asv_bench/benchmarks/dataarray_missing.py

@@ -5,7 +5,7 @@
 from . import randn, requires_dask
 
 try:
-    import dask  # noqa
+    import dask  # noqa: F401
 except ImportError:
     pass
 

doc/examples/_code/weather_data_setup.py

@@ -1,6 +1,6 @@
 import numpy as np
 import pandas as pd
-import seaborn as sns  # noqa, pandas aware plotting library
+import seaborn as sns
 
 import xarray as xr
 

doc/gallery/plot_cartopy_facetgrid.py

@@ -12,7 +12,7 @@
 For more details see `this discussion`_ on github.
 
 .. _this discussion: https://github.com/pydata/xarray/issues/1397#issuecomment-299190567
-"""  # noqa
+"""
 
 
 import cartopy.crs as ccrs

setup.py

@@ -86,7 +86,7 @@
 - Issue tracker: http://github.com/pydata/xarray/issues
 - Source code: http://github.com/pydata/xarray
 - SciPy2015 talk: https://www.youtube.com/watch?v=X0pAhJgySxk
-"""  # noqa
+"""
 
 
 setup(

xarray/backends/api.py

@@ -42,12 +42,12 @@
 
 def _get_default_engine_remote_uri():
     try:
-        import netCDF4  # noqa
+        import netCDF4  # noqa: F401
 
         engine = "netcdf4"
     except ImportError:  # pragma: no cover
         try:
-            import pydap  # noqa
+            import pydap  # noqa: F401
 
             engine = "pydap"
         except ImportError:
@@ -61,13 +61,13 @@ def _get_default_engine_remote_uri():
 def _get_default_engine_grib():
     msgs = []
     try:
-        import Nio  # noqa
+        import Nio  # noqa: F401
 
         msgs += ["set engine='pynio' to access GRIB files with PyNIO"]
     except ImportError:  # pragma: no cover
         pass
     try:
-        import cfgrib  # noqa
+        import cfgrib  # noqa: F401
 
         msgs += ["set engine='cfgrib' to access GRIB files with cfgrib"]
     except ImportError:  # pragma: no cover
@@ -80,7 +80,7 @@ def _get_default_engine_grib():
 
 def _get_default_engine_gz():
     try:
-        import scipy  # noqa
+        import scipy  # noqa: F401
 
         engine = "scipy"
     except ImportError:  # pragma: no cover
@@ -90,12 +90,12 @@ def _get_default_engine_gz():
 
 def _get_default_engine_netcdf():
     try:
-        import netCDF4  # noqa
+        import netCDF4  # noqa: F401
 
         engine = "netcdf4"
     except ImportError:  # pragma: no cover
         try:
-            import scipy.io.netcdf  # noqa
+            import scipy.io.netcdf  # noqa: F401
 
             engine = "scipy"
         except ImportError:
@@ -722,44 +722,41 @@ def open_mfdataset(
 ):
     """Open multiple files as a single dataset.
 
-    If combine='by_coords' then the function ``combine_by_coords`` is used to 
-    combine the datasets into one before returning the result, and if 
-    combine='nested' then ``combine_nested`` is used. The filepaths must be 
-    structured according to which combining function is used, the details of 
-    which are given in the documentation for ``combine_by_coords`` and 
-    ``combine_nested``. By default the old (now deprecated) ``auto_combine`` 
-    will be used, please specify either ``combine='by_coords'`` or 
-    ``combine='nested'`` in future. Requires dask to be installed. See 
-    documentation for details on dask [1]. Attributes from the first dataset 
-    file are used for the combined dataset.
+    If combine='by_coords' then the function ``combine_by_coords`` is used to combine
+    the datasets into one before returning the result, and if combine='nested' then
+    ``combine_nested`` is used. The filepaths must be structured according to which
+    combining function is used, the details of which are given in the documentation for
+    ``combine_by_coords`` and ``combine_nested``. By default the old (now deprecated)
+    ``auto_combine`` will be used, please specify either ``combine='by_coords'`` or
+    ``combine='nested'`` in future. 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
     ----------
     paths : str or sequence
-        Either a string glob in the form "path/to/my/files/*.nc" or an explicit
-        list of files to open. Paths can be given as strings or as pathlib
-        Paths. If concatenation along more than one dimension is desired, then
-        ``paths`` must be a nested list-of-lists (see ``manual_combine`` for
-        details). (A string glob will be expanded to a 1-dimensional list.)
+        Either a string glob in the form "path/to/my/files/*.nc" or an explicit list of
+        files to open. Paths can be given as strings or as pathlib Paths. If
+        concatenation along more than one dimension is desired, then ``paths`` must be a
+        nested list-of-lists (see ``manual_combine`` for details). (A string glob will
+        be expanded to a 1-dimensional list.)
     chunks : int or dict, optional
-        Dictionary with keys given by dimension names and values given by chunk
-        sizes. In general, these should divide the dimensions of each dataset.
-        If int, chunk each dimension by ``chunks``.
-        By default, chunks will be chosen to load entire input files into
-        memory at once. This has a major impact on performance: please see the
-        full documentation for more details [2].
+        Dictionary with keys given by dimension names and values given by chunk sizes.
+        In general, these should divide the dimensions of each dataset. If int, chunk
+        each dimension by ``chunks``. By default, chunks will be chosen to load entire
+        input files into memory at once. This has a major impact on performance: please
+        see the full documentation for more details [2].
     concat_dim : str, or list of str, DataArray, Index or None, optional
-        Dimensions to concatenate files along.  You only
-        need to provide this argument if any of the dimensions along which you
-        want to concatenate is not a dimension in the original datasets, e.g.,
-        if you want to stack a collection of 2D arrays along a third dimension.
-        Set ``concat_dim=[..., None, ...]`` explicitly to
+        Dimensions to concatenate files along.  You only need to provide this argument
+        if any of the dimensions along which you want to concatenate is not a dimension
+        in the original datasets, e.g., if you want to stack a collection of 2D arrays
+        along a third dimension. Set ``concat_dim=[..., None, ...]`` explicitly to
         disable concatenation along a particular dimension.
     combine : {'by_coords', 'nested'}, optional
-        Whether ``xarray.combine_by_coords`` or ``xarray.combine_nested`` is 
-        used to combine all the data. If this argument is not provided, 
-        `xarray.auto_combine` is used, but in the future this behavior will 
-        switch to use `xarray.combine_by_coords` by default.
+        Whether ``xarray.combine_by_coords`` or ``xarray.combine_nested`` is used to
+        combine all the data. If this argument is not provided, `xarray.auto_combine` is
+        used, but in the future this behavior will switch to use
+        `xarray.combine_by_coords` by default.
     compat : {'identical', 'equals', 'broadcast_equals',
               'no_conflicts', 'override'}, optional
         String indicating how to compare variables of the same name for
@@ -854,7 +851,7 @@ def open_mfdataset(
 
     .. [1] http://xarray.pydata.org/en/stable/dask.html
     .. [2] http://xarray.pydata.org/en/stable/dask.html#chunking-and-performance
-    """  # noqa
+    """
     if isinstance(paths, str):
         if is_remote_uri(paths):
             raise ValueError(

xarray/backends/locks.py

@@ -21,9 +21,7 @@
 NETCDFC_LOCK = SerializableLock()
 
 
-_FILE_LOCKS = (
-    weakref.WeakValueDictionary()
-)  # type: MutableMapping[Any, threading.Lock]  # noqa
+_FILE_LOCKS = weakref.WeakValueDictionary()  # type: MutableMapping[Any, threading.Lock]
 
 
 def _get_threaded_lock(key):

xarray/conventions.py

@@ -753,7 +753,7 @@ def cf_encoder(variables, attributes):
     for var in new_vars.values():
         bounds = var.attrs["bounds"] if "bounds" in var.attrs else None
         if bounds and bounds in new_vars:
-            # see http://cfconventions.org/cf-conventions/cf-conventions.html#cell-boundaries # noqa
+            # see http://cfconventions.org/cf-conventions/cf-conventions.html#cell-boundaries
             for attr in [
                 "units",
                 "standard_name",

xarray/core/alignment.py

@@ -13,8 +13,8 @@
 from .variable import IndexVariable, Variable
 
 if TYPE_CHECKING:
-    from .dataarray import DataArray  # noqa: F401
-    from .dataset import Dataset  # noqa: F401
+    from .dataarray import DataArray
+    from .dataset import Dataset
 
 
 def _get_joiner(join):
@@ -350,8 +350,8 @@ def deep_align(
 
     This function is not public API.
     """
-    from .dataarray import DataArray  # noqa: F811
-    from .dataset import Dataset  # noqa: F811
+    from .dataarray import DataArray
+    from .dataset import Dataset
 
     if indexes is None:
         indexes = {}
@@ -411,7 +411,7 @@ def is_alignable(obj):
 
 
 def reindex_like_indexers(
-    target: Union["DataArray", "Dataset"], other: Union["DataArray", "Dataset"]
+    target: "Union[DataArray, Dataset]", other: "Union[DataArray, Dataset]"
 ) -> Dict[Hashable, pd.Index]:
     """Extract indexers to align target with other.
 
@@ -503,7 +503,7 @@ def reindex_variables(
     new_indexes : OrderedDict
         Dict of indexes associated with the reindexed variables.
     """
-    from .dataarray import DataArray  # noqa: F811
+    from .dataarray import DataArray
 
     # create variables for the new dataset
     reindexed = OrderedDict()  # type: OrderedDict[Any, Variable]
@@ -600,8 +600,8 @@ def _get_broadcast_dims_map_common_coords(args, exclude):
 
 def _broadcast_helper(arg, exclude, dims_map, common_coords):
 
-    from .dataarray import DataArray  # noqa: F811
-    from .dataset import Dataset  # noqa: F811
+    from .dataarray import DataArray
+    from .dataset import Dataset
 
     def _set_dims(var):
         # Add excluded dims to a copy of dims_map

xarray/core/common.py

@@ -293,7 +293,7 @@ def _ipython_key_completions_(self) -> List[str]:
         """Provide method for the key-autocompletions in IPython.
         See http://ipython.readthedocs.io/en/stable/config/integrating.html#tab-completion
         For the details.
-        """  # noqa
+        """
         item_lists = [
             item
             for sublist in self._item_sources
@@ -669,7 +669,7 @@ def groupby(self, group, squeeze: bool = True, restore_coord_dims: bool = None):
         --------
         core.groupby.DataArrayGroupBy
         core.groupby.DatasetGroupBy
-        """  # noqa
+        """
         return self._groupby_cls(
             self, group, squeeze=squeeze, restore_coord_dims=restore_coord_dims
         )
@@ -732,7 +732,7 @@ def groupby_bins(
         References
         ----------
         .. [1] http://pandas.pydata.org/pandas-docs/stable/generated/pandas.cut.html
-        """  # noqa
+        """
         return self._groupby_cls(
             self,
             group,
@@ -808,7 +808,7 @@ def rolling(
         --------
         core.rolling.DataArrayRolling
         core.rolling.DatasetRolling
-        """  # noqa
+        """
         dim = either_dict_or_kwargs(dim, window_kwargs, "rolling")
         return self._rolling_cls(self, dim, min_periods=min_periods, center=center)
 
@@ -1005,7 +1005,7 @@ def resample(
         ----------
 
         .. [1] http://pandas.pydata.org/pandas-docs/stable/timeseries.html#offset-aliases
-        """  # noqa
+        """
         # TODO support non-string indexer after removing the old API.
 
         from .dataarray import DataArray

xarray/core/dataarray.py

@@ -3054,7 +3054,7 @@ def integrate(
         return self._from_temp_dataset(ds)
 
     # this needs to be at the end, or mypy will confuse with `str`
-    # https://mypy.readthedocs.io/en/latest/common_issues.html#dealing-with-conflicting-names  # noqa
+    # https://mypy.readthedocs.io/en/latest/common_issues.html#dealing-with-conflicting-names
     str = property(StringAccessor)
 
 

xarray/core/dataset.py

@@ -1063,7 +1063,7 @@ def copy(self, deep: bool = False, data: Mapping = None) -> "Dataset":
         See Also
         --------
         pandas.DataFrame.copy
-        """  # noqa
+        """
         if data is None:
             variables = OrderedDict(
                 (k, v.copy(deep=deep)) for k, v in self._variables.items()
@@ -1714,7 +1714,7 @@ def chunk(
             from dask.base import tokenize
         except ImportError:
             # raise the usual error if dask is entirely missing
-            import dask  # noqa
+            import dask  # noqa: F401
 
             raise ImportError("xarray requires dask version 0.9 or newer")
 
@@ -4178,7 +4178,7 @@ def apply(
         Data variables:
             foo      (dim_0, dim_1) float64 0.3751 1.951 1.945 0.2948 0.711 0.3948
             bar      (x) float64 1.0 2.0
-        """  # noqa
+        """
         variables = OrderedDict(
             (k, maybe_wrap_array(v, func(v, *args, **kwargs)))
             for k, v in self.data_vars.items()
@@ -5381,7 +5381,7 @@ def filter_by_attrs(self, **kwargs):
             temperature     (x, y, time) float64 25.86 20.82 6.954 23.13 10.25 11.68 ...
             precipitation   (x, y, time) float64 5.702 0.9422 2.075 1.178 3.284 ...
 
-        """  # noqa
+        """
         selection = []
         for var_name, variable in self.variables.items():
             has_value_flag = False

xarray/core/indexing.py

@@ -331,7 +331,7 @@ class ExplicitIndexer:
     __slots__ = ("_key",)
 
     def __init__(self, key):
-        if type(self) is ExplicitIndexer:  # noqa
+        if type(self) is ExplicitIndexer:
             raise TypeError("cannot instantiate base ExplicitIndexer objects")
         self._key = tuple(key)
 
@@ -1261,7 +1261,7 @@ def _indexing_array_and_key(self, key):
             array = self.array
             # We want 0d slices rather than scalars. This is achieved by
             # appending an ellipsis (see
-            # https://docs.scipy.org/doc/numpy/reference/arrays.indexing.html#detailed-notes).  # noqa
+            # https://docs.scipy.org/doc/numpy/reference/arrays.indexing.html#detailed-notes).
             key = key.tuple + (Ellipsis,)
         else:
             raise TypeError("unexpected key type: {}".format(type(key)))