Backport PR #2007 on branch 0.11.x ([pre-commit.ci] pre-commit autoupdate) (#2030)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

Author: flying-sheep

.pre-commit-config.yaml

@@ -1,12 +1,12 @@
 repos:
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.11.12
+    rev: v0.12.3
     hooks:
-      - id: ruff
+      - id: ruff-check
         args: ["--fix"]
       - id: ruff-format
   - repo: https://github.com/biomejs/pre-commit
-    rev: v1.9.4
+    rev: v2.1.1
     hooks:
       - id: biome-format
   - repo: https://github.com/ComPWA/taplo-pre-commit

biome.jsonc

@@ -1,9 +1,9 @@
 {
-    "$schema": "https://biomejs.dev/schemas/1.9.4/schema.json",
+    "$schema": "https://biomejs.dev/schemas/2.1.1/schema.json",
     "formatter": { "useEditorconfig": true },
     "overrides": [
         {
-            "include": ["./.vscode/*.json", "**/*.jsonc", "**/asv.conf.json"],
+            "includes": ["./.vscode/*.json", "**/*.jsonc", "**/asv.conf.json"],
             "json": {
                 "formatter": {
                     "trailingCommas": "all",

docs/conf.py

@@ -103,16 +103,20 @@ def setup(app: Sphinx):
     awkward=("https://awkward-array.org/doc/stable", None),
     cupy=("https://docs.cupy.dev/en/stable", None),
     dask=("https://docs.dask.org/en/stable", None),
+    fsspec=("https://filesystem-spec.readthedocs.io/en/stable/", None),
     h5py=("https://docs.h5py.org/en/latest", None),
     hdf5plugin=("https://hdf5plugin.readthedocs.io/en/latest", None),
+    kvikio=("https://docs.rapids.ai/api/kvikio/stable/", None),
     loompy=("https://linnarssonlab.org/loompy", None),
     numpy=("https://numpy.org/doc/stable", None),
+    obstore=("https://developmentseed.org/obstore/latest/", None),
     pandas=("https://pandas.pydata.org/pandas-docs/stable", None),
     python=("https://docs.python.org/3", None),
     scipy=("https://docs.scipy.org/doc/scipy", None),
     sklearn=("https://scikit-learn.org/stable", None),
     xarray=("https://docs.xarray.dev/en/stable", None),
     zarr=("https://zarr.readthedocs.io/en/v2.18.4/", None),
+    zarrs=("https://zarrs-python.readthedocs.io/en/stable/", None),
 )
 qualname_overrides = {
     "h5py._hl.group.Group": "h5py.Group",

pyproject.toml

@@ -189,16 +189,12 @@ select = [
     "PYI", # Typing
 ]
 ignore = [
-    # line too long -> we accept long comment lines; formatter gets rid of long code lines
-    "E501",
-    # Do not assign a lambda expression, use a def -> AnnData allows lambda expression assignments,
-    "E731",
-    # allow I, O, l as variable names -> I is the identity matrix, i, j, k, l is reasonable indexing notation
-    "E741",
-    # We use relative imports from parent modules
-    "TID252",
-    # Shadowing loop variables isn’t a big deal
-    "PLW2901",
+    "E501",    # line too long -> we accept long comment lines; formatter gets rid of long code lines
+    "E731",    # Do not assign a lambda expression, use a def -> AnnData allows lambda expression assignments,
+    "E741",    # allow I, O, l as variable names -> I is the identity matrix, i, j, k, l is reasonable indexing notation
+    "TID252",  # We use relative imports from parent modules
+    "PLC0415", # We use a lot of non-top-level imports
+    "PLW2901", # Shadowing loop variables isn’t a big deal
 ]
 [tool.ruff.lint.per-file-ignores]
 # E721 comparing types, but we specifically are checking that we aren't getting subtypes (views)

src/anndata/_core/aligned_df.py

@@ -42,7 +42,7 @@ def mk_index(l: int) -> pd.Index:
         df = pd.DataFrame(
             anno,
             index=None if length is None else mk_index(length),
-            columns=None if len(anno) else [],
+            columns=None if anno else [],
         )
 
     if length is None:

src/anndata/_core/anndata.py

@@ -62,7 +62,7 @@
     from .index import Index
 
 
-class AnnData(metaclass=utils.DeprecationMixinMeta):
+class AnnData(metaclass=utils.DeprecationMixinMeta):  # noqa: PLW1641
     """\
     An annotated data matrix.
 

src/anndata/_io/h5ad.py

@@ -174,7 +174,7 @@ def read_h5ad_backed(
 
 def read_h5ad(
     filename: PathLike[str] | str,
-    backed: Literal["r", "r+"] | bool | None = None,
+    backed: Literal["r", "r+"] | bool | None = None,  # noqa: FBT001
     *,
     as_sparse: Sequence[str] = (),
     as_sparse_fmt: type[CSMatrix] = sparse.csr_matrix,

src/anndata/_io/read.py

@@ -368,7 +368,7 @@ def _iter_lines(file_like: Iterable[str]) -> Generator[str, None, None]:
 def _read_text(
     f: Iterator[str],
     delimiter: str | None,
-    first_column_names: bool | None,
+    first_column_names: bool | None,  # noqa: FBT001
     dtype: str,
 ) -> AnnData:
     comments = []

src/anndata/_io/specs/methods.py

@@ -949,7 +949,7 @@ def read_dataframe_partial(
     df = pd.DataFrame(
         {k: read_elem_partial(elem[k], indices=indices[0]) for k in columns},
         index=read_elem_partial(elem[idx_key], indices=indices[0]),
-        columns=columns if len(columns) else None,
+        columns=columns if columns else None,
     )
     if idx_key != "_index":
         df.index.name = idx_key

src/anndata/utils.py

@@ -265,14 +265,15 @@ def make_index_unique(index: pd.Index, join: str = "-"):
                 example_colliding_values.append(tentative_new_name)
 
     if issue_interpretation_warning:
-        warnings.warn(
-            f"Suffix used ({join}[0-9]+) to deduplicate index values may make index "
-            + "values difficult to interpret. There values with a similar suffixes in "
-            + "the index. Consider using a different delimiter by passing "
-            + "`join={delimiter}`"
-            + "Example key collisions generated by the make_index_unique algorithm: "
-            + str(example_colliding_values)
+        msg = (
+            f"Suffix used ({join}[0-9]+) to deduplicate index values may make index values difficult to interpret. "
+            "There values with a similar suffixes in the index. "
+            "Consider using a different delimiter by passing `join={delimiter}`. "
+            "Example key collisions generated by the make_index_unique algorithm: "
+            f"{example_colliding_values}"
         )
+        # 3: caller -> 2: `{obs,var}_names_make_unique` -> 1: here
+        warnings.warn(msg, UserWarning, stacklevel=3)
     values[indices_dup] = values_dup
     index = pd.Index(values, name=index.name)
     return index