[pre-commit.ci] pre-commit autoupdate

.pre-commit-config.yaml

@@ -2,7 +2,7 @@ exclude: '^docs/conf.py'
 
 repos:
 - repo: https://github.com/pre-commit/pre-commit-hooks
-  rev: v4.4.0
+  rev: v6.0.0
   hooks:
   - id: trailing-whitespace
   - id: check-added-large-files
@@ -18,22 +18,22 @@ repos:
     args: ['--fix=auto']  # replace 'auto' with 'lf' to enforce Linux/Mac line endings or 'crlf' for Windows
 
 - repo: https://github.com/PyCQA/docformatter
-  rev: v1.7.5
+  rev: v1.7.8
   hooks:
     - id: docformatter
       additional_dependencies: [tomli]
       args: [--in-place, --wrap-descriptions=120, --wrap-summaries=120]
       # --config, ./pyproject.toml
 
-- repo: https://github.com/psf/black
-  rev: 23.9.1
+- repo: https://github.com/psf/black-pre-commit-mirror
+  rev: 26.5.1
   hooks:
   - id: black
     language_version: python3
 
 - repo: https://github.com/astral-sh/ruff-pre-commit
   # Ruff version.
-  rev: v0.0.287
+  rev: v0.16.1
   hooks:
     - id: ruff
       args: [--fix, --exit-non-zero-on-fix]

setup.py

@@ -1,15 +1,16 @@
-"""Setup file for biocborn. Use setup.cfg to configure your project.
+"""Setup file for biocborn.
 
-This file was generated with PyScaffold 4.5.
-PyScaffold helps you to put up the scaffold of your new Python project.
-Learn more under: https://pyscaffold.org/
+Use setup.cfg to configure your project. This file was generated with PyScaffold 4.5. PyScaffold helps you to put up the
+scaffold of your new Python project. Learn more under:
+https://pyscaffold.org/
 """
+
 from setuptools import setup
 
 if __name__ == "__main__":
     try:
         setup(use_scm_version={"version_scheme": "no-guess-dev"})
-    except:  # noqa
+    except:
         print(
             "\n\nAn error occurred while building the project, "
             "please ensure you have the most updated version of setuptools, "

src/biocborn/_checks.py

@@ -1,4 +1,5 @@
-from typing import Any, Callable
+from collections.abc import Callable
+from typing import Any
 
 __author__ = "jkanche"
 __copyright__ = "jkanche"

src/biocborn/heatmap.py

@@ -1,5 +1,5 @@
+from collections.abc import Sequence
 from functools import singledispatch
-from typing import Optional, Sequence, Union
 
 from biocframe import BiocFrame
 from matplotlib.axes import Axes
@@ -26,9 +26,9 @@ def _heatmap_plot(x, kwargs) -> Axes:
 @singledispatch
 def plot_heatmap(
     x,
-    features: Optional[Union[str, Sequence]] = None,
-    annotations: Optional[Union[str, Sequence]] = None,
-    assay_name: Optional[str] = None,
+    features: str | Sequence | None = None,
+    annotations: str | Sequence | None = None,
+    assay_name: str | None = None,
     **kwargs,
 ):
     """Plot a heatmap. A wrapper around seaborn's
@@ -96,9 +96,9 @@ def _plot_heatmap_df(x: DataFrame, **kwargs):
 @plot_heatmap.register
 def _plot_heatmap_sce(
     x: SingleCellExperiment,
-    features: Optional[Union[str, Sequence]] = None,
-    annotations: Optional[Union[str, Sequence]] = None,
-    assay_name: Optional[str] = None,
+    features: str | Sequence | None = None,
+    annotations: str | Sequence | None = None,
+    assay_name: str | None = None,
     **kwargs,
 ):
     if assay_name is None:

src/biocborn/reduced_dims.py

@@ -1,5 +1,5 @@
+from collections.abc import Sequence
 from functools import singledispatch
-from typing import Optional, Sequence, Union
 from warnings import warn
 
 from numpy import ndarray
@@ -28,11 +28,11 @@ def _dim_plot(x: ArrayLike, y: ArrayLike, kwargs) -> FacetGrid:
 @singledispatch
 def plot_reduced_dim(
     x,
-    dimred: Optional[str] = None,
-    color_by: Optional[Union[str, Sequence]] = None,
-    size_by: Optional[Union[str, Sequence]] = None,
-    shape_by: Optional[Union[str, Sequence]] = None,
-    assay_name: Optional[Union[str, Sequence]] = None,
+    dimred: str | None = None,
+    color_by: str | Sequence | None = None,
+    size_by: str | Sequence | None = None,
+    shape_by: str | Sequence | None = None,
+    assay_name: str | Sequence | None = None,
     **kwargs,
 ) -> FacetGrid:
     """Plot cell-level reduced dimensions.
@@ -111,9 +111,9 @@ def plot_reduced_dim(
 @plot_reduced_dim.register
 def _plot_reduced_dim_numpy(
     x: ndarray,
-    color_by: Optional[Sequence] = None,
-    size_by: Optional[Sequence] = None,
-    shape_by: Optional[Sequence] = None,
+    color_by: Sequence | None = None,
+    size_by: Sequence | None = None,
+    shape_by: Sequence | None = None,
     **kwargs,
 ) -> FacetGrid:
     NCELLS = x.shape[0]
@@ -160,11 +160,11 @@ def _plot_reduced_dim_numpy(
 @plot_reduced_dim.register
 def _plot_reduced_dim_sce(
     x: SingleCellExperiment,
-    dimred: Optional[str] = None,
-    color_by: Optional[Union[str, Sequence]] = None,
-    size_by: Optional[Union[str, Sequence]] = None,
-    shape_by: Optional[Union[str, Sequence]] = None,
-    assay_name: Optional[Union[str, Sequence]] = None,
+    dimred: str | None = None,
+    color_by: str | Sequence | None = None,
+    size_by: str | Sequence | None = None,
+    shape_by: str | Sequence | None = None,
+    assay_name: str | Sequence | None = None,
     **kwargs,
 ) -> FacetGrid:
     if assay_name is None:

src/biocborn/types.py

@@ -1,4 +1,5 @@
-from typing import Sequence, Union
+from collections.abc import Sequence
+from typing import Union
 
 from numpy import ndarray
 

src/biocborn/utils.py

@@ -1,5 +1,6 @@
 from collections import namedtuple
-from typing import Literal, Sequence, Tuple
+from collections.abc import Sequence
+from typing import Literal
 
 from biocframe import BiocFrame
 from numpy import int32, zeros
@@ -29,7 +30,6 @@ def factorize(x: Sequence) -> FactorizedArray:
     Returns:
         FactorizedArray: A factorized tuple.
     """
-
     if not isinstance(x, list):
         raise TypeError("x is not a list")
 
@@ -68,7 +68,7 @@ def _extract_variable_from_sce(
     assay: str,
     check_col_data: bool = True,
     check_row_data: bool = True,
-) -> Tuple[Sequence, Literal["annotation", "gene"]]:
+) -> tuple[Sequence, Literal["annotation", "gene"]]:
     """Extract a variable from :py:class:`~singlecellexperiment.SingleCellExperiment.SingleCellExperiment`.
 
     Variable ``var_value`` can either be a column in the