Update pre-commit (#6249)

.pre-commit-config.yaml

@@ -20,7 +20,7 @@ repos:
       - id: check-json
       - id: detect-private-key
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.4.4
+    rev: v0.4.5
     hooks:
       - id: ruff
         files: holoviews/|scripts/
@@ -30,7 +30,7 @@ repos:
       - id: clean-notebook
         args: [--strip-trailing-newlines]
   - repo: https://github.com/codespell-project/codespell
-    rev: v2.2.6
+    rev: v2.3.0
     hooks:
       - id: codespell
         additional_dependencies:

examples/reference/elements/bokeh/HexTiles.ipynb

@@ -28,7 +28,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "``HexTiles`` provide a representation of the data as a bivariate histogram useful for visualizing the structure in larger datasets. The ``HexTiles`` are computed by tesselating the x-, y-ranges of the data, storing the number of points falling in each hexagonal bin. By default ``HexTiles`` simply counts the data in each bin but it also supports weighted aggregations. Currently only linearly spaced bins are supported when using the bokeh backend.\n",
+    "``HexTiles`` provide a representation of the data as a bivariate histogram useful for visualizing the structure in larger datasets. The ``HexTiles`` are computed by tessellating the x-, y-ranges of the data, storing the number of points falling in each hexagonal bin. By default ``HexTiles`` simply counts the data in each bin but it also supports weighted aggregations. Currently only linearly spaced bins are supported when using the bokeh backend.\n",
     "\n",
     "As a simple example we will generate 100,000 normally distributed points and plot them using ``HexTiles``:"
    ]

examples/reference/elements/matplotlib/HexTiles.ipynb

@@ -29,7 +29,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "``HexTiles`` provide a representation of the data as a bivariate histogram useful for visualizing the structure in larger datasets. The ``HexTiles`` are computed by tesselating the x-, y-ranges of the data, storing the number of points falling in each hexagonal bin. By default ``HexTiles`` simply counts the data in each bin but it also supports weighted aggregations. Currently only linearly spaced bins are supported when using the bokeh backend.\n",
+    "``HexTiles`` provide a representation of the data as a bivariate histogram useful for visualizing the structure in larger datasets. The ``HexTiles`` are computed by tessellating the x-, y-ranges of the data, storing the number of points falling in each hexagonal bin. By default ``HexTiles`` simply counts the data in each bin but it also supports weighted aggregations. Currently only linearly spaced bins are supported when using the bokeh backend.\n",
     "\n",
     "As a simple example we will generate 100,000 normally distributed points and plot them using ``HexTiles``:"
    ]

pyproject.toml

@@ -180,6 +180,6 @@ known-first-party = ["holoviews"]
 combine-as-imports = true
 
 [tool.codespell]
-ignore-words-list = "lod,nd,ndoes,reenabled,spreaded,whn,ser"
+ignore-words-list = "lod,nd,ndoes,reenabled,spreaded,whn,ser,assertIn"
 skip = "doc/generate_modules.py"
 write-changes = true