[pre-commit.ci] pre-commit autoupdate (#9202)

* [pre-commit.ci] pre-commit autoupdate

updates:
- [github.com/astral-sh/ruff-pre-commit: v0.4.7 → v0.5.0](astral-sh/ruff-pre-commit@v0.4.7...v0.5.0)
- [github.com/pre-commit/mirrors-mypy: v1.10.0 → v1.10.1](pre-commit/mirrors-mypy@v1.10.0...v1.10.1)

* Fix pre-commit

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Maximilian Roos <[email protected]>
Co-authored-by: Deepak Cherian <[email protected]>

.pre-commit-config.yaml

@@ -13,7 +13,7 @@ repos:
       - id: mixed-line-ending
   - repo: https://github.com/astral-sh/ruff-pre-commit
     # Ruff version.
-    rev: 'v0.4.7'
+    rev: 'v0.5.0'
     hooks:
       - id: ruff
         args: ["--fix", "--show-fixes"]
@@ -30,7 +30,7 @@ repos:
         additional_dependencies: ["black==24.4.2"]
       - id: blackdoc-autoupdate-black
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v1.10.0
+    rev: v1.10.1
     hooks:
       - id: mypy
         # Copied from setup.cfg

xarray/backends/zarr.py

@@ -806,7 +806,7 @@ def set_variables(self, variables, check_encoding_set, writer, unlimited_dims=No
                 for k2, v2 in attrs.items():
                     encoded_attrs[k2] = self.encode_attribute(v2)
 
-                if coding.strings.check_vlen_dtype(dtype) == str:
+                if coding.strings.check_vlen_dtype(dtype) is str:
                     dtype = str
 
                 if self._write_empty is not None:

xarray/coding/cftimeindex.py

@@ -507,7 +507,7 @@ def __contains__(self, key: Any) -> bool:
             result = self.get_loc(key)
             return (
                 is_scalar(result)
-                or type(result) == slice
+                or isinstance(result, slice)
                 or (isinstance(result, np.ndarray) and result.size > 0)
             )
         except (KeyError, TypeError, ValueError):

xarray/coding/strings.py

@@ -39,11 +39,11 @@ def check_vlen_dtype(dtype):
 
 
 def is_unicode_dtype(dtype):
-    return dtype.kind == "U" or check_vlen_dtype(dtype) == str
+    return dtype.kind == "U" or check_vlen_dtype(dtype) is str
 
 
 def is_bytes_dtype(dtype):
-    return dtype.kind == "S" or check_vlen_dtype(dtype) == bytes
+    return dtype.kind == "S" or check_vlen_dtype(dtype) is bytes
 
 
 class EncodedStringCoder(VariableCoder):
@@ -104,7 +104,7 @@ def encode_string_array(string_array, encoding="utf-8"):
 
 def ensure_fixed_length_bytes(var: Variable) -> Variable:
     """Ensure that a variable with vlen bytes is converted to fixed width."""
-    if check_vlen_dtype(var.dtype) == bytes:
+    if check_vlen_dtype(var.dtype) is bytes:
         dims, data, attrs, encoding = unpack_for_encoding(var)
         # TODO: figure out how to handle this with dask
         data = np.asarray(data, dtype=np.bytes_)

xarray/coding/variables.py

@@ -677,7 +677,7 @@ def encode(self):
         raise NotImplementedError
 
     def decode(self, variable: Variable, name: T_Name = None) -> Variable:
-        if variable.dtype == object and variable.encoding.get("dtype", False) == str:
+        if variable.dtype.kind == "O" and variable.encoding.get("dtype", False) is str:
             variable = variable.astype(variable.encoding["dtype"])
             return variable
         else:

xarray/conventions.py

@@ -273,7 +273,7 @@ def decode_cf_variable(
             var = strings.CharacterArrayCoder().decode(var, name=name)
         var = strings.EncodedStringCoder().decode(var)
 
-    if original_dtype == object:
+    if original_dtype.kind == "O":
         var = variables.ObjectVLenStringCoder().decode(var)
         original_dtype = var.dtype
 

xarray/tests/test_backends.py

@@ -863,14 +863,14 @@ def test_roundtrip_empty_vlen_string_array(self) -> None:
         # checks preserving vlen dtype for empty arrays GH7862
         dtype = create_vlen_dtype(str)
         original = Dataset({"a": np.array([], dtype=dtype)})
-        assert check_vlen_dtype(original["a"].dtype) == str
+        assert check_vlen_dtype(original["a"].dtype) is str
         with self.roundtrip(original) as actual:
             assert_identical(original, actual)
             if np.issubdtype(actual["a"].dtype, object):
                 # only check metadata for capable backends
                 # eg. NETCDF3 based backends do not roundtrip metadata
                 if actual["a"].dtype.metadata is not None:
-                    assert check_vlen_dtype(actual["a"].dtype) == str
+                    assert check_vlen_dtype(actual["a"].dtype) is str
             else:
                 assert actual["a"].dtype == np.dtype("<U1")
 

xarray/tests/test_coding_strings.py

@@ -21,13 +21,13 @@
 
 def test_vlen_dtype() -> None:
     dtype = strings.create_vlen_dtype(str)
-    assert dtype.metadata["element_type"] == str
+    assert dtype.metadata["element_type"] is str
     assert strings.is_unicode_dtype(dtype)
     assert not strings.is_bytes_dtype(dtype)
     assert strings.check_vlen_dtype(dtype) is str
 
     dtype = strings.create_vlen_dtype(bytes)
-    assert dtype.metadata["element_type"] == bytes
+    assert dtype.metadata["element_type"] is bytes
     assert not strings.is_unicode_dtype(dtype)
     assert strings.is_bytes_dtype(dtype)
     assert strings.check_vlen_dtype(dtype) is bytes

xarray/tests/test_conventions.py

@@ -564,10 +564,10 @@ def test_encode_cf_variable_with_vlen_dtype() -> None:
     )
     encoded_v = conventions.encode_cf_variable(v)
     assert encoded_v.data.dtype.kind == "O"
-    assert coding.strings.check_vlen_dtype(encoded_v.data.dtype) == str
+    assert coding.strings.check_vlen_dtype(encoded_v.data.dtype) is str
 
     # empty array
     v = Variable(["x"], np.array([], dtype=coding.strings.create_vlen_dtype(str)))
     encoded_v = conventions.encode_cf_variable(v)
     assert encoded_v.data.dtype.kind == "O"
-    assert coding.strings.check_vlen_dtype(encoded_v.data.dtype) == str
+    assert coding.strings.check_vlen_dtype(encoded_v.data.dtype) is str

xarray/tests/test_datatree.py

@@ -593,7 +593,7 @@ def test_methods(self):
         ds = create_test_data()
         dt: DataTree = DataTree(data=ds)
         assert ds.mean().identical(dt.ds.mean())
-        assert type(dt.ds.mean()) == xr.Dataset
+        assert isinstance(dt.ds.mean(), xr.Dataset)
 
     def test_arithmetic(self, create_test_datatree):
         dt = create_test_datatree()

xarray/tests/test_duck_array_ops.py

@@ -347,7 +347,7 @@ def construct_dataarray(dim_num, dtype, contains_nan, dask):
         array = rng.randint(0, 10, size=shapes).astype(dtype)
     elif np.issubdtype(dtype, np.bool_):
         array = rng.randint(0, 1, size=shapes).astype(dtype)
-    elif dtype == str:
+    elif dtype is str:
         array = rng.choice(["a", "b", "c", "d"], size=shapes)
     else:
         raise ValueError

xarray/tests/test_variable.py

@@ -178,8 +178,8 @@ def _assertIndexedLikeNDArray(self, variable, expected_value0, expected_dtype=No
         # check type or dtype is consistent for both ndarray and Variable
         if expected_dtype is None:
             # check output type instead of array dtype
-            assert type(variable.values[0]) == type(expected_value0)
-            assert type(variable[0].values) == type(expected_value0)
+            assert type(variable.values[0]) is type(expected_value0)
+            assert type(variable[0].values) is type(expected_value0)
         elif expected_dtype is not False:
             assert variable.values[0].dtype == expected_dtype
             assert variable[0].values.dtype == expected_dtype