Merge pull request #5151 from yt-project/pre-commit-ci-update-config

[pre-commit.ci] pre-commit autoupdate

Author: neutrinoceros

.pre-commit-config.yaml

@@ -36,7 +36,7 @@ repos:
         additional_dependencies: [black==24.3.0]
 
 - repo: https://github.com/astral-sh/ruff-pre-commit
-  rev: v0.9.9
+  rev: v0.11.4
   hooks:
   - id: ruff-format
   - id: ruff

yt/data_objects/level_sets/clump_handling.py

@@ -289,7 +289,7 @@ def save_as_dataset(self, filename=None, fields=None):
             else:
                 clump_info[ci] = np.array(clump_info[ci])
 
-        ftypes = {ci: "clump" for ci in clump_info}
+        ftypes = dict.fromkeys(clump_info, "clump")
 
         # collect data fields
         if fields is not None:

yt/data_objects/tests/test_profiles.py

@@ -608,7 +608,7 @@ def test_unequal_data_shape_profile(self):
             ("gas", "mass"): mass,
         }
         fake_ds_med = {"current_time": yt.YTQuantity(10, "Myr")}
-        field_types = {field: "gas" for field in my_data.keys()}
+        field_types = dict.fromkeys(my_data.keys(), "gas")
         yt.save_as_dataset(fake_ds_med, "mydata.h5", my_data, field_types=field_types)
 
         ds = yt.load("mydata.h5")
@@ -633,7 +633,7 @@ def test_unequal_bin_field_profile(self):
             ("gas", "mass"): mass,
         }
         fake_ds_med = {"current_time": yt.YTQuantity(10, "Myr")}
-        field_types = {field: "gas" for field in my_data.keys()}
+        field_types = dict.fromkeys(my_data.keys(), "gas")
         yt.save_as_dataset(fake_ds_med, "mydata.h5", my_data, field_types=field_types)
 
         ds = yt.load("mydata.h5")

yt/fields/tests/test_fields.py

@@ -145,7 +145,7 @@ def get_base_ds(nprocs):
     ds.parameters["EOSType"] = 1.0
     ds.parameters["EOSSoundSpeed"] = 1.0
     ds.conversion_factors["Time"] = 1.0
-    ds.conversion_factors.update({f: 1.0 for f in fields})
+    ds.conversion_factors.update(dict.fromkeys(fields, 1.0))
     ds.gamma = 5.0 / 3.0
     ds.current_redshift = 0.0001
     ds.cosmological_simulation = 1

yt/frontends/halo_catalog/tests/test_outputs.py

@@ -12,7 +12,7 @@
 def fake_halo_catalog(data):
     filename = "catalog.0.h5"
 
-    ftypes = {field: "." for field in data}
+    ftypes = dict.fromkeys(data, ".")
     extra_attrs = {"data_type": "halo_catalog", "num_halos": data["particle_mass"].size}
 
     ds = {

yt/geometry/coordinates/coordinate_handler.py

@@ -228,11 +228,11 @@ def convert_from_spherical(self, coord):
 
     @cached_property
     def data_projection(self):
-        return {ax: None for ax in self.axis_order}
+        return dict.fromkeys(self.axis_order)
 
     @cached_property
     def data_transform(self):
-        return {ax: None for ax in self.axis_order}
+        return dict.fromkeys(self.axis_order)
 
     @cached_property
     def axis_name(self):

yt/loaders.py

@@ -341,7 +341,7 @@ def load_uniform_grid(
                     field = ("io", key)
                     mylog.debug("Reassigning '%s' to '%s'", key, field)
                 else:
-                    key = cast(FieldKey, key)
+                    key = cast("FieldKey", key)
                     field = key
                 sfh._additional_fields += (field,)
                 pdata[field] = data.pop(key)
@@ -1912,7 +1912,7 @@ def _reader(grid, field_name):
     psize = get_psize(np.array(shape), nchunks)
     left_edges, right_edges, shapes, _, _ = decompose_array(shape, psize, bbox)
     for le, re, s in zip(left_edges, right_edges, shapes, strict=True):
-        data = {_: reader for _ in fields}
+        data = dict.fromkeys(fields, reader)
         data.update({"left_edge": le, "right_edge": re, "dimensions": s, "level": 0})
         grid_data.append(data)
     return load_amr_grids(grid_data, shape, bbox=bbox, **dataset_arguments)

yt/utilities/io_handler.py

@@ -113,7 +113,7 @@ def _read_fluid_selection(
                 nodal_fields.append(field)
             else:
                 rv[field] = np.empty(size, dtype="=f8")
-        ind = {field: 0 for field in fields}
+        ind = dict.fromkeys(fields, 0)
         for field, obj, data in self.io_iter(chunks, fields):
             if data is None:
                 continue

yt/utilities/lib/octree_raytracing.py

@@ -50,7 +50,7 @@ def vertex_centered_data(self, field):
             np.zeros((2, 2, 2, data_source.ires.size), dtype="float64"), units
         )
         binary_3D_index_iter = product(*[range(2)] * 3)
-        ind = {(i, j, k): 0 for i, j, k in binary_3D_index_iter}
+        ind = dict.fromkeys(binary_3D_index_iter, 0)
         for chunk in chunks:
             with data_source._chunked_read(chunk):
                 gz = data_source._current_chunk.objs[0]

yt/visualization/fixed_resolution.py

@@ -536,7 +536,7 @@ def save_as_dataset(self, filename=None, fields=None):
         else:
             data.update(self.data)
 
-        ftypes = {field: "grid" for field in data}
+        ftypes = dict.fromkeys(data, "grid")
         extra_attrs = {
             arg: getattr(self.data_source, arg, None)
             for arg in self.data_source._con_args + self.data_source._tds_attrs