Update to mypy1.7 (#8501)

* fix mypy1.7 errors

* pin mypy to <1.8

* add entry to whats-new

Author: headtr1ck

.github/workflows/ci-additional.yaml

@@ -117,7 +117,7 @@ jobs:
           python xarray/util/print_versions.py
       - name: Install mypy
         run: |
-          python -m pip install "mypy<1.7" --force-reinstall
+          python -m pip install "mypy<1.8" --force-reinstall
 
       - name: Run mypy
         run: |
@@ -171,7 +171,7 @@ jobs:
           python xarray/util/print_versions.py
       - name: Install mypy
         run: |
-          python -m pip install "mypy<1.7" --force-reinstall
+          python -m pip install "mypy<1.8" --force-reinstall
 
       - name: Run mypy
         run: |

doc/whats-new.rst

@@ -79,6 +79,8 @@ Internal Changes
 - :py:meth:`DataArray.bfill` & :py:meth:`DataArray.ffill` now use numbagg by
   default, which is up to 5x faster where parallelization is possible. (:pull:`8339`)
   By `Maximilian Roos <https://github.com/max-sixty>`_.
+- Update mypy version to 1.7 (:issue:`8448`, :pull:`8501`).
+  By `Michael Niklas <https://github.com/headtr1ck>`_.
 
 .. _whats-new.2023.11.0:
 

xarray/core/alignment.py

@@ -681,7 +681,7 @@ def align(
     ...
 
 
-def align(  # type: ignore[misc]
+def align(
     *objects: T_Alignable,
     join: JoinOptions = "inner",
     copy: bool = True,
@@ -1153,7 +1153,7 @@ def broadcast(
     ...
 
 
-def broadcast(  # type: ignore[misc]
+def broadcast(
     *args: T_Alignable, exclude: str | Iterable[Hashable] | None = None
 ) -> tuple[T_Alignable, ...]:
     """Explicitly broadcast any number of DataArray or Dataset objects against

xarray/core/dataset.py

@@ -7979,8 +7979,8 @@ def sortby(
             variables = variables
         arrays = [v if isinstance(v, DataArray) else self[v] for v in variables]
         aligned_vars = align(self, *arrays, join="left")
-        aligned_self = aligned_vars[0]
-        aligned_other_vars: tuple[DataArray, ...] = aligned_vars[1:]
+        aligned_self = cast("Self", aligned_vars[0])
+        aligned_other_vars = cast(tuple[DataArray, ...], aligned_vars[1:])
         vars_by_dim = defaultdict(list)
         for data_array in aligned_other_vars:
             if data_array.ndim != 1: