MNT: Remove workarounds used for Python 3.8 support

Author: effigies

nibabel/filebasedimages.py

@@ -23,7 +23,7 @@
 if ty.TYPE_CHECKING:
     from .filename_parser import ExtensionSpec, FileSpec
 
-FileSniff = ty.Tuple[bytes, str]
+FileSniff = tuple[bytes, str]
 
 ImgT = ty.TypeVar('ImgT', bound='FileBasedImage')
 HdrT = ty.TypeVar('HdrT', bound='FileBasedHeader')

nibabel/nicom/ascconv.py

@@ -90,10 +90,7 @@ def assign2atoms(assign_ast, default_class=int):
             target = target.value
             prev_target_type = OrderedDict
         elif isinstance(target, ast.Subscript):
-            if isinstance(target.slice, ast.Constant):  # PY39
-                index = target.slice.value
-            else:  # PY38
-                index = target.slice.value.n
+            index = target.slice.value
             atoms.append(Atom(target, prev_target_type, index))
             target = target.value
             prev_target_type = list

nibabel/nifti1.py

@@ -671,7 +671,7 @@ def _mangle(self, dataset: DicomDataset) -> bytes:
         (38, 'eval', NiftiExtension),
         (40, 'matlab', NiftiExtension),
         (42, 'quantiphyse', NiftiExtension),
-        (44, 'mrs', NiftiExtension[ty.Dict[str, ty.Any]]),
+        (44, 'mrs', NiftiExtension[dict[str, ty.Any]]),
     ),
     fields=('code', 'label', 'handler'),
 )

nibabel/spatialimages.py

@@ -133,6 +133,7 @@
 from __future__ import annotations
 
 import typing as ty
+from functools import cache
 from typing import Literal
 
 import numpy as np
@@ -145,11 +146,6 @@
 from .viewers import OrthoSlicer3D
 from .volumeutils import shape_zoom_affine
 
-try:
-    from functools import cache
-except ImportError:  # PY38
-    from functools import lru_cache as cache
-
 if ty.TYPE_CHECKING:
     import io
     from collections.abc import Sequence

nibabel/testing/__init__.py

@@ -17,6 +17,7 @@
 import unittest
 import warnings
 from contextlib import nullcontext
+from importlib.resources import as_file, files
 from itertools import zip_longest
 
 import numpy as np
@@ -29,11 +30,6 @@
 if ty.TYPE_CHECKING:
     from importlib.resources.abc import Traversable
 
-try:
-    from importlib.resources import as_file, files
-except ImportError:  # PY38
-    from importlib_resources import as_file, files
-
 
 def get_test_data(
     subdir: ty.Literal['gifti', 'nicom', 'externals'] | None = None,

nibabel/testing/np_features.py

@@ -1,11 +1,11 @@
 """Look for changes in numpy behavior over versions"""
 
-from functools import lru_cache
+from functools import cache
 
 import numpy as np
 
 
-@lru_cache(maxsize=None)
+@cache
 def memmap_after_ufunc() -> bool:
     """Return True if ufuncs on memmap arrays always return memmap arrays
 

nibabel/tests/test_arrayproxy.py

@@ -482,9 +482,11 @@ def test_keep_file_open_true_false_invalid():
 
     for test in tests:
         filetype, kfo, have_igzip, exp_persist, exp_kfo = test
-        with InTemporaryDirectory(), mock.patch(
-            'nibabel.openers.ImageOpener', CountingImageOpener
-        ), patch_indexed_gzip(have_igzip):
+        with (
+            InTemporaryDirectory(),
+            mock.patch('nibabel.openers.ImageOpener', CountingImageOpener),
+            patch_indexed_gzip(have_igzip),
+        ):
             fname = f'testdata.{filetype}'
             # create the test data file
             if filetype == 'gz':

nibabel/tests/test_openers.py

@@ -121,8 +121,9 @@ def patch_indexed_gzip(state):
         values = (True, MockIndexedGzipFile)
     else:
         values = (False, GzipFile)
-    with mock.patch('nibabel.openers.HAVE_INDEXED_GZIP', values[0]), mock.patch(
-        'nibabel.openers.IndexedGzipFile', values[1], create=True
+    with (
+        mock.patch('nibabel.openers.HAVE_INDEXED_GZIP', values[0]),
+        mock.patch('nibabel.openers.IndexedGzipFile', values[1], create=True),
     ):
         yield
 

nibabel/volumeutils.py

@@ -235,7 +235,7 @@ def value_set(self, name: str | None = None) -> OrderedSet:
 endian_codes = Recoder(_endian_codes)
 
 
-class DtypeMapper(ty.Dict[ty.Hashable, ty.Hashable]):
+class DtypeMapper(dict[ty.Hashable, ty.Hashable]):
     """Specialized mapper for numpy dtypes
 
     We pass this mapper into the Recoder class to deal with numpy dtype