[pre-commit.ci] pre-commit autoupdate

.pre-commit-config.yaml

@@ -1,6 +1,6 @@
 repos:
 -   repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.16.4
+    rev: v0.16.5
     hooks:
     -   id: ruff-check
         args: ["--fix"]
@@ -33,7 +33,7 @@ repos:
               docs/references.bib|
           )
 -   repo: https://github.com/pre-commit/mirrors-clang-format
-    rev: v22.1.8
+    rev: v23.1.0
     hooks:
     -   id: clang-format
         args: [--style=file, -i]

docs/contributing.md

@@ -155,6 +155,7 @@ The `add_nb_cuda_module` helper automatically handles:
   ```python
   from rapids_singlecell._cuda import _my_module_cuda as _my
 
+
   def my_function(adata):
       # _my is either the real module or None
       _my.kernel(...)

docs/gpu_configuration.md

@@ -175,7 +175,7 @@ AnnData stores {attr}`~anndata.AnnData.raw` in CPU memory, even when `.X` was al
 rsc.get.anndata_to_GPU(adata)
 adata.raw = adata.copy()
 
-print(type(adata.X))      # CuPy or cupyx: GPU
+print(type(adata.X))  # CuPy or cupyx: GPU
 print(type(adata.raw.X))  # NumPy or SciPy: CPU
 ```
 

docs/memory_management.md

@@ -52,6 +52,7 @@ cp.cuda.set_allocator(rmm_cupy_allocator)
 import rmm
 import cupy as cp
 from rmm.allocators.cupy import rmm_cupy_allocator
+
 rmm.reinitialize(
     managed_memory=False,
     pool_allocator=True,

docs/out_of_core.md

@@ -21,9 +21,9 @@ from dask_cuda import LocalCUDACluster
 cluster = LocalCUDACluster(
     CUDA_VISIBLE_DEVICES="0,1,2,3,4,5,6,7",
     protocol="ucx",
-    threads_per_worker=1,           # GPU-safe default
-    rmm_pool_size="80%",            # per-worker pool; % of free VRAM at start
-    rmm_managed_memory=False,       # avoid UM to maximize P2P
+    threads_per_worker=1,  # GPU-safe default
+    rmm_pool_size="80%",  # per-worker pool; % of free VRAM at start
+    rmm_managed_memory=False,  # avoid UM to maximize P2P
     rmm_allocator_external_lib_list=["cupy"],  # auto-patch CuPy to use RMM
 )
 client = Client(cluster)
@@ -36,10 +36,10 @@ from dask.distributed import Client
 from dask_cuda import LocalCUDACluster
 
 cluster = LocalCUDACluster(
-    CUDA_VISIBLE_DEVICES="0,1",     # scale as needed
-    protocol="tcp",                 # TCP is often more predictable with UVM
+    CUDA_VISIBLE_DEVICES="0,1",  # scale as needed
+    protocol="tcp",  # TCP is often more predictable with UVM
     threads_per_worker=1,
-    rmm_managed_memory=True,        # allow oversubscription (paging)
+    rmm_managed_memory=True,  # allow oversubscription (paging)
     rmm_allocator_external_lib_list=["cupy"],
 )
 client = Client(cluster)
@@ -85,6 +85,7 @@ adata = ad.AnnData(
 
 ```python
 import rapids_singlecell as rsc
+
 rsc.get.anndata_to_GPU(adata)
 # Normalize and transform
 rsc.pp.normalize_total(adata)
@@ -106,7 +107,6 @@ Most functions operate lazily; use `.compute()` only when you need concrete valu
 ```python
 # Dense dask+cupy matrix → cupy
 X_gpu = adata.X.compute()
-
 ```
 
 ## Persist and chunk sizes

docs/usage_principles.md

@@ -86,7 +86,7 @@ from rapids_singlecell import ptg
 distance = ptg.Distance(metric="edistance", obsm_key="X_pca")
 result = distance.pairwise(adata, groupby="perturbation")
 res, res_var = distance.pairwise(
-	adata, groupby="perturbation", bootstrap=True, n_bootstrap=100, multi_gpu=None
+    adata, groupby="perturbation", bootstrap=True, n_bootstrap=100, multi_gpu=None
 )
 ```