Use ruff-format instead of black, bump ruff version (#963)

Issue: rapidsai/build-planning#130

Authors:
  - Kyle Edwards (https://github.com/KyleFromNVIDIA)

Approvers:
  - Gregory Lee (https://github.com/grlee77)
  - https://github.com/jakirkham

URL: #963

Author: KyleFromNVIDIA

.pre-commit-config.yaml

@@ -13,17 +13,13 @@ repos:
       - id: trailing-whitespace
       - id: end-of-file-fixer
       - id: debug-statements
-  - repo: https://github.com/psf/black
-    rev: 23.10.1
-    hooks:
-      - id: black
-        args: ["--config", "python/cucim/pyproject.toml"]
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.6.1
+    rev: v0.14.3
     hooks:
-      - id: ruff
+      - id: ruff-check
         types_or: [python, pyi]
         args: [--fix, --exit-non-zero-on-fix, --config, "python/cucim/pyproject.toml"]
+      - id: ruff-format
   - repo: https://github.com/codespell-project/codespell
     rev: v2.2.6
     hooks:

benchmarks/skimage/_image_bench.py

@@ -202,20 +202,14 @@ def run_benchmark(self, duration=3, verbose=True):
                     props = cp.cuda.runtime.getDeviceProperties(device.id)
                     gpu_name = props["name"].decode()
 
-                df.at[index, "GPU: DEV Name"] = [
-                    gpu_name for i in range(len(df))
-                ]
+                df.at[index, "GPU: DEV Name"] = [gpu_name for i in range(len(df))]
                 cmd = "cat /proc/cpuinfo"
                 cpuinfo = subprocess.check_output(cmd, shell=True).strip()
                 cpu_name = (
-                    re.search("\nmodel name.*\n", cpuinfo.decode())
-                    .group(0)
-                    .strip("\n")
+                    re.search("\nmodel name.*\n", cpuinfo.decode()).group(0).strip("\n")
                 )
                 cpu_name = cpu_name.replace("model name\t: ", "")
-                df.at[index, "CPU: DEV Name"] = [
-                    cpu_name for i in range(len(df))
-                ]
+                df.at[index, "CPU: DEV Name"] = [cpu_name for i in range(len(df))]
 
                 # accelerations[arr_index] = df.at[index,  "GPU accel"]
                 if verbose:

benchmarks/skimage/bench_convolve.py

@@ -4,6 +4,7 @@
 """
 Benchmark locally modified ndimage functions vs. their CuPy counterparts
 """
+
 import cupy as cp
 import cupyx.scipy.ndimage as ndi
 from cupyx.profiler import benchmark

benchmarks/skimage/cucim_color_bench.py

@@ -41,9 +41,7 @@ class ColorBench(ImageBench):
     def set_args(self, dtype):
         if self.shape[-1] != 3:
             raise ValueError("shape must be 3 on the last axis")
-        imaged = cupy.testing.shaped_random(
-            self.shape, xp=cp, dtype=dtype, scale=1.0
-        )
+        imaged = cupy.testing.shaped_random(self.shape, xp=cp, dtype=dtype, scale=1.0)
         image = cp.asnumpy(imaged)
         self.args_cpu = (image,)
         self.args_gpu = (imaged,)
@@ -79,9 +77,7 @@ class RGBABench(ImageBench):
     def set_args(self, dtype):
         if self.shape[-1] != 4:
             raise ValueError("shape must be 4 on the last axis")
-        imaged = cupy.testing.shaped_random(
-            self.shape, xp=cp, dtype=dtype, scale=1.0
-        )
+        imaged = cupy.testing.shaped_random(self.shape, xp=cp, dtype=dtype, scale=1.0)
         image = cp.asnumpy(imaged)
         self.args_cpu = (image,)
         self.args_gpu = (imaged,)
@@ -116,9 +112,7 @@ def __init__(
 
     def _generate_labels(self, dtype):
         ndim = len(self.shape)
-        blobs_kwargs = dict(
-            blob_size_fraction=0.05, volume_fraction=0.35, rng=5
-        )
+        blobs_kwargs = dict(blob_size_fraction=0.05, volume_fraction=0.35, rng=5)
         # binary blobs only creates square outputs
         labels = measure.label(
             data.binary_blobs(max(self.shape), n_dim=ndim, **blobs_kwargs)
@@ -314,8 +308,7 @@ def main(args):
         "--img_size",
         type=str,
         help=(
-            "Size of input image (omit color channel, it will be appended "
-            "as needed)"
+            "Size of input image (omit color channel, it will be appended as needed)"
         ),
         required=True,
     )

benchmarks/skimage/cucim_exposure_bench.py

@@ -23,9 +23,7 @@ def set_args(self, dtype):
             scale = 256
         else:
             scale = 1.0
-        imaged = cupy.testing.shaped_random(
-            self.shape, xp=cp, dtype=dtype, scale=scale
-        )
+        imaged = cupy.testing.shaped_random(self.shape, xp=cp, dtype=dtype, scale=scale)
         image = cp.asnumpy(imaged)
         self.args_cpu = (image,)
         self.args_gpu = (imaged,)
@@ -37,9 +35,7 @@ def set_args(self, dtype):
             scale = 256
         else:
             scale = 1.0
-        imaged = cupy.testing.shaped_random(
-            self.shape, xp=cp, dtype=dtype, scale=scale
-        )
+        imaged = cupy.testing.shaped_random(self.shape, xp=cp, dtype=dtype, scale=scale)
         imaged2 = cupy.testing.shaped_random(
             self.shape, xp=cp, dtype=dtype, scale=scale
         )

benchmarks/skimage/cucim_feature_bench.py

@@ -40,9 +40,7 @@ def set_args(self, dtype):
             offsets = rng.integers(0, np.prod(img.shape), num_ellipse)
             locs = np.unravel_index(offsets, img.shape)
             for loc in zip(*locs):
-                loc = tuple(
-                    min(p, s - es) for p, s, es in zip(loc, img.shape, e.shape)
-                )
+                loc = tuple(min(p, s - es) for p, s, es in zip(loc, img.shape, e.shape))
                 sl = tuple(slice(p, p + es) for p, es in zip(loc, e.shape))
                 img[sl] = e
         else:

benchmarks/skimage/cucim_filters_bench.py

@@ -162,9 +162,7 @@ def main(args):
 
         if function_name == "gabor" and np.prod(shape) > 1000000:
             # avoid cases that are too slow on the CPU
-            var_kwargs["frequency"] = [
-                f for f in var_kwargs["frequency"] if f >= 0.1
-            ]
+            var_kwargs["frequency"] = [f for f in var_kwargs["frequency"] if f >= 0.1]
 
         if function_name == "median":
             footprints = []

benchmarks/skimage/cucim_measure_bench.py

@@ -236,9 +236,7 @@ def main(args):
             continue
 
         if function_name in ["label", "regionprops"]:
-            Tester = (
-                LabelBench if function_name == "label" else RegionpropsBench
-            )
+            Tester = LabelBench if function_name == "label" else RegionpropsBench
 
             for contiguous_labels in [True, False]:
                 if contiguous_labels:
@@ -293,9 +291,7 @@ def main(args):
             if function_name == "block_reduce":
                 ndim = len(shape)
                 if shape[-1] == 3:
-                    block_sizes = [
-                        (b,) * (ndim - 1) + (3,) for b in (16, 32, 64)
-                    ]
+                    block_sizes = [(b,) * (ndim - 1) + (3,) for b in (16, 32, 64)]
                 else:
                     block_sizes = [(b,) * ndim for b in (16, 32, 64)]
                 var_kwargs["block_size"] = block_sizes
@@ -308,9 +304,7 @@ def main(args):
                 ndim = len(shape)
                 footprint_sizes = [3, 5, 7, 9] if ndim == 2 else [3, 5, 7]
                 for footprint_size in [3, 5, 7, 9]:
-                    footprints.append(
-                        np.ones((footprint_sizes,) * ndim, dtype=bool)
-                    )
+                    footprints.append(np.ones((footprint_sizes,) * ndim, dtype=bool))
                 var_kwargs["footprint"] = footprints
 
             if function_name in ["gaussian", "unsharp_mask"]:
@@ -337,9 +331,7 @@ def main(args):
 
 
 if __name__ == "__main__":
-    parser = argparse.ArgumentParser(
-        description="Benchmarking cuCIM measure functions"
-    )
+    parser = argparse.ArgumentParser(description="Benchmarking cuCIM measure functions")
     func_name_choices = [
         "label",
         "regionprops",

benchmarks/skimage/cucim_metrics_bench.py

@@ -56,9 +56,7 @@ def __init__(
 
     def _generate_labels(self, dtype, rng=5):
         ndim = len(self.shape)
-        blobs_kwargs = dict(
-            blob_size_fraction=0.05, volume_fraction=0.35, rng=rng
-        )
+        blobs_kwargs = dict(blob_size_fraction=0.05, volume_fraction=0.35, rng=rng)
         # binary blobs only creates square outputs
         labels = measure.label(
             data.binary_blobs(max(self.shape), n_dim=ndim, **blobs_kwargs)
@@ -171,9 +169,7 @@ def main(args):
                 run_cpu=run_cpu,
             )
         else:
-            raise ValueError(
-                f"benchmark function not configured for {function_name}"
-            )
+            raise ValueError(f"benchmark function not configured for {function_name}")
         results = B.run_benchmark(duration=args.duration)
         all_results = pd.concat([all_results, results["full"]])
 
@@ -185,9 +181,7 @@ def main(args):
 
 
 if __name__ == "__main__":
-    parser = argparse.ArgumentParser(
-        description="Benchmarking cuCIM metrics functions"
-    )
+    parser = argparse.ArgumentParser(description="Benchmarking cuCIM metrics functions")
     func_name_choices = [
         "structural_similarity",
         "mean_squared_error",

benchmarks/skimage/cucim_morphology_bench.py

@@ -322,8 +322,7 @@ def main(args):
         "--img_size",
         type=str,
         help=(
-            "Size of input image (omit color channel, it will be appended "
-            "as needed)"
+            "Size of input image (omit color channel, it will be appended as needed)"
         ),
         required=True,
     )