don't type check __getattr__

doc/whats-new.rst

@@ -137,6 +137,11 @@ Internal Changes
   By `Yash Saboo <https://github.com/yashsaboo>`_, `Nirupam K N
   <https://github.com/Nirupamkn>`_ and `Mathias Hauser
   <https://github.com/mathause>`_.
+  - Added ``@no_type_check`` to ``__getattr__`` of :py:class:`Dataset` and :py:class:`DataArray`.
+  This can help to identify missing methods but may lead to typing errors in downstream libraries.
+  The recommendation in this case is to use the index operator when accessing variables or
+  coordinates, e.g. ``da["longitude"]``, and to add ``#type: ignore`` for accessors, e.g.
+  ``da.geo  # type: ignore`` (:issue:`4601`). By `Mathias Hauser <https://github.com/mathause>`_.
 
 .. _whats-new.0.16.1:
 

xarray/core/common.py

@@ -14,6 +14,7 @@
     Tuple,
     TypeVar,
     Union,
+    no_type_check,
 )
 
 import numpy as np
@@ -218,6 +219,7 @@ def _item_sources(self) -> List[Mapping[Hashable, Any]]:
         """List of places to look-up items for key-autocompletion"""
         return []
 
+    @no_type_check  # so missing methods raise a type error
     def __getattr__(self, name: str) -> Any:
         if name not in {"__dict__", "__setstate__"}:
             # this avoids an infinite loop when pickle looks for the
@@ -365,7 +367,7 @@ def squeeze(
         numpy.squeeze
         """
         dims = get_squeeze_dims(self, dim, axis)
-        return self.isel(drop=drop, **{d: 0 for d in dims})
+        return self.isel({d: 0 for d in dims}, drop=drop)
 
     def get_index(self, key: Hashable) -> pd.Index:
         """Get an index for a dimension, with fall-back to a default RangeIndex"""
@@ -693,7 +695,7 @@ def groupby(self, group, squeeze: bool = True, restore_coord_dims: bool = None):
                 f"`squeeze` must be True or False, but {squeeze} was supplied"
             )
 
-        return self._groupby_cls(
+        return self._groupby_cls(  # type: ignore
             self, group, squeeze=squeeze, restore_coord_dims=restore_coord_dims
         )
 
@@ -756,7 +758,7 @@ def groupby_bins(
         ----------
         .. [1] http://pandas.pydata.org/pandas-docs/stable/generated/pandas.cut.html
         """
-        return self._groupby_cls(
+        return self._groupby_cls(  # type: ignore
             self,
             group,
             squeeze=squeeze,
@@ -787,7 +789,7 @@ def weighted(self, weights):
         Missing values can be replaced by ``weights.fillna(0)``.
         """
 
-        return self._weighted_cls(self, weights)
+        return self._weighted_cls(self, weights)  # type: ignore
 
     def rolling(
         self,
@@ -861,7 +863,7 @@ def rolling(
         """
 
         dim = either_dict_or_kwargs(dim, window_kwargs, "rolling")
-        return self._rolling_cls(
+        return self._rolling_cls(  # type: ignore
             self, dim, min_periods=min_periods, center=center, keep_attrs=keep_attrs
         )
 
@@ -972,7 +974,7 @@ def coarsen(
             keep_attrs = _get_keep_attrs(default=False)
 
         dim = either_dict_or_kwargs(dim, window_kwargs, "coarsen")
-        return self._coarsen_cls(
+        return self._coarsen_cls(  # type: ignore
             self,
             dim,
             boundary=boundary,
@@ -1139,7 +1141,7 @@ def resample(
         group = DataArray(
             dim_coord, coords=dim_coord.coords, dims=dim_coord.dims, name=RESAMPLE_DIM
         )
-        resampler = self._resample_cls(
+        resampler = self._resample_cls(  # type: ignore
             self,
             group=group,
             dim=dim_name,
@@ -1376,6 +1378,52 @@ def __getitem__(self, value):
         # implementations of this class should implement this method
         raise NotImplementedError()
 
+    def isel(
+        self,
+        indexers: Mapping[Hashable, Any] = None,
+        drop: bool = False,
+        missing_dims: str = "raise",
+        **indexers_kwargs: Any,
+    ):
+        # implementations of this class should implement this method / for type checking
+        raise NotImplementedError()
+
+    @property
+    def dims(self):
+        # implementations of this class should implement this method / for type checking
+        raise NotImplementedError()
+
+    @property
+    def indexes(self):
+        # implementations of this class should implement this method / for type checking
+        raise NotImplementedError()
+
+    @property
+    def sizes(self):
+        # implementations of this class should implement this method / for type checking
+        raise NotImplementedError()
+
+    def copy(self, deep=True, data=None):
+        # implementations of this class should implement this method / for type checking
+        raise NotImplementedError()
+
+    @property
+    def encoding(self) -> Dict:
+        # implementations of this class should implement this method / for type checking
+        raise NotImplementedError()
+
+    def reindex(
+        self,
+        indexers: Mapping[Hashable, Any] = None,
+        method: str = None,
+        tolerance=None,
+        copy: bool = True,
+        fill_value: Any = dtypes.NA,
+        **indexers_kwargs: Any,
+    ):
+        # implementations of this class should implement this method / for type checking
+        raise NotImplementedError()
+
 
 def full_like(other, fill_value, dtype: DTypeLike = None):
     """Return a new object with the same shape and type as a given object.

xarray/core/dataset.py

@@ -3784,12 +3784,8 @@ def merge(
         )
         return self._replace(**merge_result._asdict())
 
-    def _assert_all_in_dataset(
-        self, names: Iterable[Hashable], virtual_okay: bool = False
-    ) -> None:
+    def _assert_all_in_dataset(self, names: Iterable[Hashable]) -> None:
         bad_names = set(names) - set(self._variables)
-        if virtual_okay:
-            bad_names -= self.virtual_variables
         if bad_names:
             raise ValueError(
                 "One or more of the specified variables "
@@ -6132,7 +6128,8 @@ def polyfit(
                 # deficient ranks nor does it output the "full" info (issue dask/dask#6516)
                 skipna_da = True
             elif skipna is None:
-                skipna_da = np.any(da.isnull())
+                # no type checking because ops are injected
+                skipna_da = np.any(da.isnull())  # type: ignore
 
             dims_to_stack = [dimname for dimname in da.dims if dimname != dim]
             stacked_coords: Dict[Hashable, DataArray] = {}

xarray/core/weighted.py

@@ -154,7 +154,8 @@ def _sum_of_weights(
         """ Calculate the sum of weights, accounting for missing values """
 
         # we need to mask data values that are nan; else the weights are wrong
-        mask = da.notnull()
+        # no type checking because ops are injected
+        mask = da.notnull()  # type: ignore
 
         # bool -> int, because ``xr.dot([True, True], [True, True])`` -> True
         # (and not 2); GH4074