Fixed ruff errors and bumped RTD Python version to 3.10

.readthedocs.yaml

@@ -2,7 +2,7 @@ version: 2
 build:
   os: ubuntu-20.04
   tools:
-    python: "3.9"
+    python: "3.10"
   apt_packages:
     - graphviz
 

pyproject.toml

@@ -180,9 +180,7 @@ ignore = [
 ]
 
 [tool.ruff]
-
-[tool.ruff.lint]
-extend-select = [
+lint.select = [
   "B",  # flake8-bugbear
   "I",  # isort
   "UP",  # pyupgrade

reproject/healpix/utils.py

@@ -33,7 +33,7 @@ def parse_input_healpix_data(input_data, field=0, hdu_in=None, nested=None):
     Parse input HEALPIX data to return a Numpy array and coordinate frame object.
     """
 
-    if isinstance(input_data, (TableHDU, BinTableHDU)):
+    if isinstance(input_data, TableHDU | BinTableHDU):
         data = input_data.data
         header = input_data.header
         coordinate_system_in = parse_coord_system(header["COORDSYS"])

reproject/mosaicking/coadd.py

@@ -248,7 +248,7 @@ def reproject_and_coadd(
         corrections = solve_corrections_sgd(offset_matrix)
         if background_reference:
             corrections -= corrections[background_reference]
-        for array, correction in zip(arrays, corrections):
+        for array, correction in zip(arrays, corrections, strict=True):
             array.array -= correction
 
     # At this point, the images are now ready to be co-added.

reproject/mosaicking/tests/test_coadd.py

@@ -386,7 +386,7 @@ def test_coadd_solar_map():
     wcs_out = WCS(Header.fromstring(HEADER_SOLAR_OUT, sep="\n"))
     scales = [1 / 6, 1, 1 / 6]
 
-    input_data = tuple((a.data * scale, a.wcs) for (a, scale) in zip(maps, scales))
+    input_data = tuple((a.data * scale, a.wcs) for (a, scale) in zip(maps, scales, strict=True))
 
     array, footprint = reproject_and_coadd(
         input_data,

reproject/mosaicking/tests/test_wcs_helpers.py

@@ -263,11 +263,11 @@ def test_input_types(valid_celestial_input_shapes, iterable):
 
     if (
         not isinstance(input_value, WCS)
-        and isinstance(input_value, (BaseLowLevelWCS, BaseHighLevelWCS))
+        and isinstance(input_value, BaseLowLevelWCS | BaseHighLevelWCS)
     ) or (
         isinstance(input_value, tuple)
         and not isinstance(input_value[1], WCS)
-        and isinstance(input_value[1], (BaseLowLevelWCS, BaseHighLevelWCS))
+        and isinstance(input_value[1], BaseLowLevelWCS | BaseHighLevelWCS)
     ):
         wcs_ref = WCS(fits.Header.fromstring(APE14_HEADER_REF, sep="\n"))
         shape_ref = (31, 50)

reproject/mosaicking/wcs_helpers.py

@@ -107,7 +107,7 @@ def find_optimal_celestial_wcs(
         iterable = False
     elif isiterable(input_data):
         if len(input_data) == 2 and isinstance(
-            input_data[1], (BaseLowLevelWCS, BaseHighLevelWCS, Header)
+            input_data[1], BaseLowLevelWCS | BaseHighLevelWCS | Header
         ):
             # Since 2-element tuples are valid single inputs we need to check for this
             iterable = False
@@ -245,7 +245,7 @@ def find_optimal_celestial_wcs(
         # rectangle
         from shapely.geometry import MultiPoint
 
-        mp = MultiPoint(list(zip(xp, yp)))
+        mp = MultiPoint(list(zip(xp, yp, strict=True)))
 
         # The following returns a list of rectangle vertices - in fact there
         # are 5 coordinates because shapely represents it as a closed polygon

reproject/tests/test_utils.py

@@ -15,7 +15,7 @@ def test_parse_input_data(tmpdir, valid_celestial_input_data, request):
     array_ref, wcs_ref, input_value, kwargs = valid_celestial_input_data
 
     data, wcs = parse_input_data(input_value, **kwargs)
-    assert isinstance(data, (da.Array, np.ndarray))
+    assert isinstance(data, da.Array | np.ndarray)
     np.testing.assert_allclose(data, array_ref)
     assert_wcs_allclose(wcs, wcs_ref)
 

reproject/utils.py

@@ -70,7 +70,7 @@ def parse_input_data(input_data, hdu_in=None):
     Parse input data to return a Numpy array and WCS object.
     """
 
-    if isinstance(input_data, (str, Path)):
+    if isinstance(input_data, str | Path):
         with fits.open(input_data) as hdul:
             return parse_input_data(hdul, hdu_in=hdu_in)
     elif isinstance(input_data, HDUList):
@@ -83,9 +83,9 @@ def parse_input_data(input_data, hdu_in=None):
             else:
                 hdu_in = 0
         return parse_input_data(input_data[hdu_in])
-    elif isinstance(input_data, (PrimaryHDU, ImageHDU, CompImageHDU)):
+    elif isinstance(input_data, PrimaryHDU | ImageHDU | CompImageHDU):
         return input_data.data, WCS(input_data.header)
-    elif isinstance(input_data, tuple) and isinstance(input_data[0], (np.ndarray, da.core.Array)):
+    elif isinstance(input_data, tuple) and isinstance(input_data[0], np.ndarray | da.core.Array):
         if isinstance(input_data[1], Header):
             return input_data[0], WCS(input_data[1])
         else:
@@ -114,7 +114,7 @@ def parse_input_shape(input_shape, hdu_in=None):
     Parse input shape information to return an array shape tuple and WCS object.
     """
 
-    if isinstance(input_shape, (str, Path)):
+    if isinstance(input_shape, str | Path):
         return parse_input_shape(fits.open(input_shape), hdu_in=hdu_in)
     elif isinstance(input_shape, HDUList):
         if hdu_in is None:
@@ -126,9 +126,9 @@ def parse_input_shape(input_shape, hdu_in=None):
             else:
                 hdu_in = 0
         return parse_input_shape(input_shape[hdu_in])
-    elif isinstance(input_shape, (PrimaryHDU, ImageHDU, CompImageHDU)):
+    elif isinstance(input_shape, PrimaryHDU | ImageHDU | CompImageHDU):
         return input_shape.shape, WCS(input_shape.header)
-    elif isinstance(input_shape, tuple) and isinstance(input_shape[0], (np.ndarray, da.core.Array)):
+    elif isinstance(input_shape, tuple) and isinstance(input_shape[0], np.ndarray | da.core.Array):
         if isinstance(input_shape[1], Header):
             return input_shape[0].shape, WCS(input_shape[1])
         else:
@@ -177,7 +177,7 @@ def parse_input_weights(input_weights, hdu_weights=None):
             else:
                 hdu_weights = 0
         return parse_input_data(input_weights[hdu_weights])[0]
-    elif isinstance(input_weights, (PrimaryHDU, ImageHDU, CompImageHDU)):
+    elif isinstance(input_weights, PrimaryHDU | ImageHDU | CompImageHDU):
         return input_weights.data
     elif isinstance(input_weights, np.ndarray):
         return input_weights
@@ -205,7 +205,7 @@ def parse_output_projection(output_projection, shape_in=None, shape_out=None, ou
                     "Need to specify shape since output header "
                     "does not contain complete shape information"
                 ) from None
-    elif isinstance(output_projection, (BaseLowLevelWCS, BaseHighLevelWCS)):
+    elif isinstance(output_projection, BaseLowLevelWCS | BaseHighLevelWCS):
         if isinstance(output_projection, BaseLowLevelWCS) and not isinstance(
             output_projection, BaseHighLevelWCS
         ):