diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 8607de368..07bab4b9b 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -1,7 +1,7 @@
-files: "libpysal\/"
+files: "libpysal\/|docs\/"
 repos:
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: "v0.5.0"
+    rev: "v0.6.9"
     hooks:
       - id: ruff
       - id: ruff-format
diff --git a/docs/conf.py b/docs/conf.py
index 24c4648f0..973e917ed 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -1,5 +1,3 @@
-# -*- coding: utf-8 -*-
-#
 # libpysal documentation build configuration file, created by
 # sphinx-quickstart on Wed Jun  6 15:54:22 2018.
 #
@@ -17,8 +15,8 @@
 # documentation root, use os.path.abspath to make it absolute, like shown here.
 #
 import sphinx_bootstrap_theme
-import libpysal
 
+import libpysal
 
 # -- General configuration ------------------------------------------------
 
diff --git a/docs/user-guide/data/examples.ipynb b/docs/user-guide/data/examples.ipynb
index 051fef910..fe32a7931 100644
--- a/docs/user-guide/data/examples.ipynb
+++ b/docs/user-guide/data/examples.ipynb
@@ -35,7 +35,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from libpysal.examples import get_path \n"
+    "from libpysal.examples import get_path"
    ]
   },
   {
@@ -72,6 +72,7 @@
    "outputs": [],
    "source": [
     "import libpysal\n",
+    "\n",
     "dbf = libpysal.io.open(get_path(\"mexicojoin.dbf\"))"
    ]
   },
@@ -357,7 +358,7 @@
     }
    ],
    "source": [
-    "libpysal.examples.load_example('dataset42')"
+    "libpysal.examples.load_example(\"dataset42\")"
    ]
   },
   {
@@ -387,7 +388,7 @@
     }
    ],
    "source": [
-    "balt_url = libpysal.examples.get_url('Baltimore')\n",
+    "balt_url = libpysal.examples.get_url(\"Baltimore\")\n",
     "balt_url"
    ]
   },
@@ -421,7 +422,7 @@
     }
    ],
    "source": [
-    "libpysal.examples.explain('taz')"
+    "libpysal.examples.explain(\"taz\")"
    ]
   },
   {
@@ -430,7 +431,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "taz = libpysal.examples.load_example('taz')"
+    "taz = libpysal.examples.load_example(\"taz\")"
    ]
   },
   {
@@ -485,7 +486,7 @@
     }
    ],
    "source": [
-    "libpysal.examples.explain('Baltimore')"
+    "libpysal.examples.explain(\"Baltimore\")"
    ]
   },
   {
@@ -502,7 +503,7 @@
     }
    ],
    "source": [
-    "balt = libpysal.examples.load_example('Baltimore')"
+    "balt = libpysal.examples.load_example(\"Baltimore\")"
    ]
   },
   {
@@ -673,7 +674,8 @@
    ],
    "source": [
     "from libpysal.examples import explain\n",
-    "explain('Tampa1')"
+    "\n",
+    "explain(\"Tampa1\")"
    ]
   },
   {
@@ -691,7 +693,8 @@
    ],
    "source": [
     "from libpysal.examples import load_example\n",
-    "tampa1 = load_example('Tampa1')"
+    "\n",
+    "tampa1 = load_example(\"Tampa1\")"
    ]
   },
   {
@@ -820,7 +823,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "tampa_counties_shp = tampa1.load('tampa_counties.shp')"
+    "tampa_counties_shp = tampa1.load(\"tampa_counties.shp\")"
    ]
   },
   {
@@ -858,7 +861,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "tampa_df = geopandas.read_file(tampa1.get_path('tampa_counties.shp'))"
+    "tampa_df = geopandas.read_file(tampa1.get_path(\"tampa_counties.shp\"))"
    ]
   },
   {
@@ -936,7 +939,7 @@
     }
    ],
    "source": [
-    "libpysal.examples.explain('Rio Grande do Sul')"
+    "libpysal.examples.explain(\"Rio Grande do Sul\")"
    ]
   },
   {
@@ -960,7 +963,7 @@
     }
    ],
    "source": [
-    "rio = libpysal.examples.load_example('Rio Grande do Sul')"
+    "rio = libpysal.examples.load_example(\"Rio Grande do Sul\")"
    ]
   },
   {
@@ -1051,7 +1054,7 @@
     }
    ],
    "source": [
-    "libpysal.examples.remote_datasets.datasets # a listing of all remotes"
+    "libpysal.examples.remote_datasets.datasets  # a listing of all remotes"
    ]
   },
   {
diff --git a/docs/user-guide/graph/matching-graph.ipynb b/docs/user-guide/graph/matching-graph.ipynb
index 0c0394bb2..b4f2e5faf 100644
--- a/docs/user-guide/graph/matching-graph.ipynb
+++ b/docs/user-guide/graph/matching-graph.ipynb
@@ -22,13 +22,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import sys\n",
     "import os\n",
-    "sys.path.append(os.path.abspath('..'))\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
+    "import sys\n",
+    "\n",
+    "sys.path.append(os.path.abspath(\"..\"))\n",
     "import geopandas\n",
-    "import pandas"
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np"
    ]
   },
   {
@@ -46,7 +46,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "points = np.row_stack([(10.2, 5.1), (4.7, 2.2), (5.3, 5.7), (2.7, 5.3), (7,4)])\n",
+    "points = np.row_stack([(10.2, 5.1), (4.7, 2.2), (5.3, 5.7), (2.7, 5.3), (7, 4)])\n",
     "gdf = geopandas.GeoDataFrame(geometry=geopandas.points_from_xy(*points.T))"
    ]
   },
@@ -108,8 +108,8 @@
     }
    ],
    "source": [
-    "f, ax =plt.subplots(1,3)\n",
-    "for i,g in enumerate((g1, g2, g3)):\n",
+    "f, ax = plt.subplots(1, 3)\n",
+    "for i, g in enumerate((g1, g2, g3)):\n",
     "    g.plot(gdf, ax=ax[i])\n",
     "    ax[i].set_title(f\"k = {i+1}\")"
    ]
@@ -128,6 +128,7 @@
    "outputs": [],
    "source": [
     "import geodatasets\n",
+    "\n",
     "stores = geopandas.read_file(geodatasets.get_path(\"geoda liquor_stores\")).explode(\n",
     "    index_parts=False\n",
     ")"
@@ -261,8 +262,8 @@
     }
    ],
    "source": [
-    "f, ax =plt.subplots(1,3)\n",
-    "for i,g in enumerate((g1, g5, g10)):\n",
+    "f, ax = plt.subplots(1, 3)\n",
+    "for i, g in enumerate((g1, g5, g10)):\n",
     "    g.plot(stores, ax=ax[i], nodes=False)\n",
     "    ax[i].set_title(f\"k = {(1, 5, 10)[i]}\")"
    ]
@@ -293,8 +294,8 @@
    "source": [
     "sources = stores.sample(100)\n",
     "sinks = stores[~stores.index.isin(sources.index)].sample(100)\n",
-    "ax = sources.plot(color='red')\n",
-    "sinks.plot(color='blue', ax=ax)\n",
+    "ax = sources.plot(color=\"red\")\n",
+    "sinks.plot(color=\"blue\", ax=ax)\n",
     "plt.show()"
    ]
   },
@@ -304,8 +305,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from libpysal.graph._matching import _spatial_matching\n",
-    "import shapely"
+    "import shapely\n",
+    "\n",
+    "from libpysal.graph._matching import _spatial_matching"
    ]
   },
   {
@@ -334,7 +336,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "crosspattern_heads, crosspattern_tails, weights, mip = _spatial_matching(x=sink_coordinates, y = source_coordinates, n_matches=1, return_mip=True)"
+    "crosspattern_heads, crosspattern_tails, weights, mip = _spatial_matching(\n",
+    "    x=sink_coordinates, y=source_coordinates, n_matches=1, return_mip=True\n",
+    ")"
    ]
   },
   {
@@ -364,12 +368,13 @@
    "outputs": [],
    "source": [
     "lines = shapely.linestrings(\n",
-    "    list( \n",
-    "    zip(\n",
-    "        map(list, source_coordinates[crosspattern_heads]),\n",
-    "        map(list, sink_coordinates[crosspattern_tails])\n",
+    "    list(\n",
+    "        zip(\n",
+    "            map(list, source_coordinates[crosspattern_heads]),\n",
+    "            map(list, sink_coordinates[crosspattern_tails]),\n",
+    "            strict=False,\n",
+    "        )\n",
     "    )\n",
-    ")\n",
     ")"
    ]
   },
@@ -390,9 +395,9 @@
     }
    ],
    "source": [
-    "ax = sources.plot(color='red')\n",
-    "sinks.plot(color='blue', ax=ax)\n",
-    "geopandas.GeoSeries(lines).plot(linewidth=1, color='k', ax=ax)\n",
+    "ax = sources.plot(color=\"red\")\n",
+    "sinks.plot(color=\"blue\", ax=ax)\n",
+    "geopandas.GeoSeries(lines).plot(linewidth=1, color=\"k\", ax=ax)\n",
     "plt.show()"
    ]
   }
diff --git a/docs/user-guide/graph/w_g_migration.ipynb b/docs/user-guide/graph/w_g_migration.ipynb
index 6111ff91f..a8ef58763 100644
--- a/docs/user-guide/graph/w_g_migration.ipynb
+++ b/docs/user-guide/graph/w_g_migration.ipynb
@@ -47,8 +47,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from libpysal import weights\n",
-    "from libpysal import graph"
+    "from libpysal import graph, weights"
    ]
   },
   {
@@ -85,11 +84,10 @@
    "source": [
     "%matplotlib inline\n",
     "\n",
-    "import seaborn as sns\n",
-    "import pandas as pd\n",
     "import geopandas as gpd\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
+    "import pandas as pd\n",
+    "import seaborn as sns\n",
+    "\n",
     "from libpysal import examples\n",
     "\n",
     "%load_ext watermark\n",
@@ -2710,7 +2708,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "w_queen.transform = 'r'\n",
+    "w_queen.transform = \"r\"\n",
     "wlag = lag_spatial(w_queen, y)"
    ]
   },
@@ -3111,7 +3109,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "ngdf = gdf.set_index('NAME')"
+    "ngdf = gdf.set_index(\"NAME\")"
    ]
   },
   {
@@ -3162,7 +3160,7 @@
     }
    ],
    "source": [
-    "g['Ashe']"
+    "g[\"Ashe\"]"
    ]
   },
   {
@@ -3742,9 +3740,9 @@
     }
    ],
    "source": [
-    "m = ngdf.loc[g['Ashe'].index].explore(color=\"#25b497\")\n",
-    "ngdf.loc[['Ashe']].explore(m=m, color=\"#fa94a5\")\n",
-    "g.explore(ngdf, m=m, focal='Ashe')"
+    "m = ngdf.loc[g[\"Ashe\"].index].explore(color=\"#25b497\")\n",
+    "ngdf.loc[[\"Ashe\"]].explore(m=m, color=\"#fa94a5\")\n",
+    "g.explore(ngdf, m=m, focal=\"Ashe\")"
    ]
   },
   {
diff --git a/docs/user-guide/weights/Raster_awareness_API.ipynb b/docs/user-guide/weights/Raster_awareness_API.ipynb
index 2e09dacae..af971e738 100644
--- a/docs/user-guide/weights/Raster_awareness_API.ipynb
+++ b/docs/user-guide/weights/Raster_awareness_API.ipynb
@@ -25,13 +25,13 @@
    "source": [
     "%matplotlib inline\n",
     "\n",
-    "from libpysal.weights import Rook, Queen, raster\n",
     "import matplotlib.pyplot as plt\n",
-    "from splot import libpysal as splot\n",
     "import numpy as np\n",
     "import xarray as xr\n",
-    "import pandas as pd\n",
-    "from esda import Moran_Local"
+    "from esda import Moran_Local\n",
+    "from splot import libpysal as splot\n",
+    "\n",
+    "from libpysal.weights import Queen, Rook, raster"
    ]
   },
   {
@@ -82,7 +82,8 @@
     }
    ],
    "source": [
-    "ds = xr.tutorial.open_dataset(\"air_temperature.nc\")  # -> returns a xarray.Dataset object\n",
+    "# -> returns a xarray.Dataset object\n",
+    "ds = xr.tutorial.open_dataset(\"air_temperature.nc\")\n",
     "da = ds[\"air\"]  # we'll use the \"air\" data variable for further analysis\n",
     "print(da)"
    ]
@@ -116,8 +117,8 @@
     }
    ],
    "source": [
-    "da = da.groupby('time.month').mean()\n",
-    "print(da.coords)  # as a result time dim is replaced by month "
+    "da = da.groupby(\"time.month\").mean()\n",
+    "print(da.coords)  # as a result time dim is replaced by month"
    ]
   },
   {
@@ -149,8 +150,12 @@
     }
    ],
    "source": [
-    "# let's plot over month, each facet will represent the mean air temperature in a given month.\n",
-    "da.plot(col=\"month\", col_wrap=4,) "
+    "# let's plot over month, each facet will represent\n",
+    "# the mean air temperature in a given month.\n",
+    "da.plot(\n",
+    "    col=\"month\",\n",
+    "    col_wrap=4,\n",
+    ")"
    ]
   },
   {
@@ -191,9 +196,12 @@
    ],
    "source": [
     "coords_labels = {}\n",
-    "coords_labels[\"z_label\"] = \"month\"  # since month does not belong to the default list we need to pass it using a dictionary\n",
+    "# since month does not belong to the default list we\n",
+    "# need to pass it using a dictionary\n",
+    "coords_labels[\"z_label\"] = \"month\"\n",
     "w_queen = Queen.from_xarray(\n",
-    "    da, z_value=12, coords_labels=coords_labels, sparse=False)  # We'll use data from 12th layer (in our case layer=month)"
+    "    da, z_value=12, coords_labels=coords_labels, sparse=False\n",
+    ")  # We'll use data from 12th layer (in our case layer=month)"
    ]
   },
   {
@@ -297,7 +305,9 @@
    ],
    "source": [
     "# Converting obtained data back to DataArray\n",
-    "moran_da = raster.w2da(lisa.p_sim, w_queen)  # w2da accepts list/1d array/pd.Series and a weight object aligned to passed data\n",
+    "moran_da = raster.w2da(\n",
+    "    lisa.p_sim, w_queen\n",
+    ")  # w2da accepts list/1d array/pd.Series and a weight object aligned to passed data\n",
     "print(moran_da)"
    ]
   },
@@ -387,8 +397,10 @@
    ],
    "source": [
     "# Lets load a netCDF Surface dataset\n",
-    "ds = xr.open_dataset('ECMWF_ERA-40_subset.nc')    # After loading netCDF dataset we obtained a xarray.Dataset object\n",
-    "print(ds)                                         # This Dataset object containes several data variables"
+    "ds = xr.open_dataset(\n",
+    "    \"ECMWF_ERA-40_subset.nc\"\n",
+    ")  # After loading netCDF dataset we obtained a xarray.Dataset object\n",
+    "print(ds)  # This Dataset object containes several data variables"
    ]
   },
   {
@@ -414,8 +426,10 @@
     }
    ],
    "source": [
-    "da = ds[\"p2t\"]  # this will give us the required DataArray with p2t (2 metre temperature) data variable\n",
-    "da = da.groupby('time.day').mean()\n",
+    "# this will give us the required DataArray with p2t\n",
+    "# (2 metre temperature) data variable\n",
+    "da = ds[\"p2t\"]\n",
+    "da = da.groupby(\"time.day\").mean()\n",
     "print(da.dims)"
    ]
   },
@@ -447,7 +461,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "data = da.to_series()[w_rook.index]  # we derived the data from DataArray similar to our last example "
+    "data = da.to_series()[\n",
+    "    w_rook.index\n",
+    "]  # we derived the data from DataArray similar to our last example"
    ]
   },
   {
@@ -479,7 +495,9 @@
    ],
    "source": [
     "da1 = raster.wsp2da(data, w_rook, attrs=da.attrs, coords=da[12:13].coords)\n",
-    "xr.DataArray.equals(da[12:13], da1)  # method to compare 2 DataArray, if true then w2da was successfull"
+    "xr.DataArray.equals(\n",
+    "    da[12:13], da1\n",
+    ")  # method to compare 2 DataArray, if true then w2da was successfull"
    ]
   },
   {
@@ -524,7 +542,7 @@
    ],
    "source": [
     "# Loading raster data with missing values\n",
-    "da = xr.open_rasterio('/data/Downloads/lux_ppp_2019.tif')\n",
+    "da = xr.open_rasterio(\"/data/Downloads/lux_ppp_2019.tif\")\n",
     "print(da)"
    ]
   },
@@ -557,7 +575,9 @@
     }
    ],
    "source": [
-    "da.where(da.values>da.attrs[\"nodatavals\"][0]).plot() # we can see that the DataArray contains missing values."
+    "da.where(\n",
+    "    da.values > da.attrs[\"nodatavals\"][0]\n",
+    ").plot()  # we can see that the DataArray contains missing values."
    ]
   },
   {
@@ -607,8 +627,8 @@
     }
    ],
    "source": [
-    "f,ax = plt.subplots(1,3,figsize=(4*4,4), subplot_kw=dict(aspect='equal'))\n",
-    "da_s.where(da_s.values>da_s.attrs[\"nodatavals\"][0]).plot(ax=ax[0])\n",
+    "f, ax = plt.subplots(1, 3, figsize=(4 * 4, 4), subplot_kw=dict(aspect=\"equal\"))\n",
+    "da_s.where(da_s.values > da_s.attrs[\"nodatavals\"][0]).plot(ax=ax[0])\n",
     "ax[0].set_title(\"Sliced raster\")\n",
     "splot.plot_spatial_weights(w_rook, data=da_s, ax=ax[1])\n",
     "ax[1].set_title(\"Rook contiguity\")\n",
@@ -634,8 +654,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Building a test DataArray \n",
-    "da_s = raster.testDataArray((1,5,10), rand=True)"
+    "# Building a test DataArray\n",
+    "da_s = raster.testDataArray((1, 5, 10), rand=True)"
    ]
   },
   {
@@ -765,7 +785,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.2"
+   "version": "3.12.7"
   }
  },
  "nbformat": 4,
diff --git a/docs/user-guide/weights/categorical_lag.ipynb b/docs/user-guide/weights/categorical_lag.ipynb
index 37cb9af5e..6a5b87950 100644
--- a/docs/user-guide/weights/categorical_lag.ipynb
+++ b/docs/user-guide/weights/categorical_lag.ipynb
@@ -15,11 +15,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    ">>> from libpysal.graph._spatial_lag import _lag_spatial\n",
-    ">>> import numpy as np\n",
-    ">>> from libpysal.weights.util import lat2W\n",
-    ">>> from libpysal.graph import Graph\n",
-    ">>> graph = Graph.from_W(lat2W(3,3))\n"
+    "import numpy as np\n",
+    "\n",
+    "from libpysal.graph import Graph\n",
+    "from libpysal.graph._spatial_lag import _lag_spatial\n",
+    "from libpysal.weights.util import lat2W\n",
+    "\n",
+    "graph = Graph.from_W(lat2W(3, 3))"
    ]
   },
   {
@@ -40,9 +42,8 @@
     }
    ],
    "source": [
-    ">>> y = np.arange(9)\n",
-    ">>> _lag_spatial(graph, y)\n",
-    "\n"
+    "y = np.arange(9)\n",
+    "_lag_spatial(graph, y)"
    ]
   },
   {
@@ -63,26 +64,10 @@
     }
    ],
    "source": [
-    ">>> y = np.array([*'ababcbcbc'])\n",
-    ">>> _lag_spatial(graph, y, categorical=True)"
+    "y = np.array([*\"ababcbcbc\"])\n",
+    "_lag_spatial(graph, y, categorical=True)"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "84523f3b-3909-4e33-a7b9-11a70b263308",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "689efe78-b402-4bbc-b8f1-28c24faf9777",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
   {
    "cell_type": "code",
    "execution_count": 28,
@@ -101,8 +86,8 @@
     }
    ],
    "source": [
-    ">>> y[3] = 'a'\n",
-    ">>> y"
+    "y[3] = \"a\"\n",
+    "y"
    ]
   },
   {
@@ -123,8 +108,8 @@
     }
    ],
    "source": [
-    ">>> np.random.seed(12345)\n",
-    ">>> _lag_spatial(graph, y, categorical=True, ties='random')"
+    "np.random.seed(12345)\n",
+    "_lag_spatial(graph, y, categorical=True, ties=\"random\")"
    ]
   },
   {
@@ -145,7 +130,7 @@
     }
    ],
    "source": [
-    ">>> _lag_spatial(graph, y, categorical=True, ties='random')"
+    "_lag_spatial(graph, y, categorical=True, ties=\"random\")"
    ]
   },
   {
@@ -166,7 +151,7 @@
     }
    ],
    "source": [
-    ">>> _lag_spatial(graph, y, categorical=True, ties='tryself')"
+    "_lag_spatial(graph, y, categorical=True, ties=\"tryself\")"
    ]
   },
   {
@@ -192,22 +177,6 @@
     "_lag_spatial(graph, y, categorical=True)"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b77d9c3b-e923-428b-8b61-f383a1af42fe",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b120ef88-dd80-4b9d-8c7c-8b413d476e08",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -226,14 +195,15 @@
     }
    ],
    "source": [
-    ">>> import libpysal\n",
-    ">>> import numpy as np\n",
-    ">>> np.random.seed(12345)\n",
-    ">>> w = libpysal.weights.lat2W(3, 3)\n",
-    ">>> y = np.array([*'ababcbcbc'])\n",
-    ">>> y_l = libpysal.weights.lag_categorical(w, y)\n",
-    ">>> np.array_equal(y_l, np.array(['b', 'a', 'b', 'c', 'b', 'c', 'b', 'c', 'b']))\n",
-    "\n"
+    "import numpy as np\n",
+    "\n",
+    "import libpysal\n",
+    "\n",
+    "np.random.seed(12345)\n",
+    "w = libpysal.weights.lat2W(3, 3)\n",
+    "y = np.array([*\"ababcbcbc\"])\n",
+    "y_l = libpysal.weights.lag_categorical(w, y)\n",
+    "np.array_equal(y_l, np.array([\"b\", \"a\", \"b\", \"c\", \"b\", \"c\", \"b\", \"c\", \"b\"]))"
    ]
   },
   {
@@ -331,6 +301,7 @@
    ],
    "source": [
     "import numpy\n",
+    "\n",
     "_lag_spatial(g, numpy.array(y), categorical=True)"
    ]
   },
@@ -360,7 +331,7 @@
     }
    ],
    "source": [
-    "_lag_spatial(g, numpy.array(y), categorical=True, ties='tryself')"
+    "_lag_spatial(g, numpy.array(y), categorical=True, ties=\"tryself\")"
    ]
   },
   {
@@ -381,7 +352,7 @@
     }
    ],
    "source": [
-    "np.array_equal(y_l, _lag_spatial(g, numpy.array(y), categorical=True, ties='random'))"
+    "np.array_equal(y_l, _lag_spatial(g, numpy.array(y), categorical=True, ties=\"random\"))"
    ]
   },
   {
@@ -402,7 +373,7 @@
     }
    ],
    "source": [
-    "np.array_equal(y_l, _lag_spatial(g, numpy.array(y), categorical=True, ties='raise'))"
+    "np.array_equal(y_l, _lag_spatial(g, numpy.array(y), categorical=True, ties=\"raise\"))"
    ]
   },
   {
@@ -431,7 +402,7 @@
     }
    ],
    "source": [
-    "y[3] = 'a'\n",
+    "y[3] = \"a\"\n",
     "y"
    ]
   },
@@ -463,7 +434,7 @@
     }
    ],
    "source": [
-    "_lag_spatial(g, numpy.array(y), categorical=True, ties='random')"
+    "_lag_spatial(g, numpy.array(y), categorical=True, ties=\"random\")"
    ]
   },
   {
@@ -484,7 +455,7 @@
     }
    ],
    "source": [
-    "_lag_spatial(g, numpy.array(y), categorical=True, ties='tryself')"
+    "_lag_spatial(g, numpy.array(y), categorical=True, ties=\"tryself\")"
    ]
   },
   {
@@ -508,7 +479,7 @@
    ],
    "source": [
     "y_l = libpysal.weights.lag_categorical(w, y)\n",
-    "np.array_equal(y_l, _lag_spatial(g, numpy.array(y), categorical=True, ties='raise'))"
+    "np.array_equal(y_l, _lag_spatial(g, numpy.array(y), categorical=True, ties=\"raise\"))"
    ]
   },
   {
@@ -520,14 +491,6 @@
    "source": [
     "y_l"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "2a9f175a-4108-408e-b17b-7147861d1375",
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
@@ -546,7 +509,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.2"
+   "version": "3.12.7"
   }
  },
  "nbformat": 4,
diff --git a/docs/user-guide/weights/voronoi.ipynb b/docs/user-guide/weights/voronoi.ipynb
index f91fd9639..ff1a18928 100644
--- a/docs/user-guide/weights/voronoi.ipynb
+++ b/docs/user-guide/weights/voronoi.ipynb
@@ -22,10 +22,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import sys\n",
     "import os\n",
-    "sys.path.append(os.path.abspath('..'))\n",
-    "import libpysal"
+    "import sys\n",
+    "\n",
+    "sys.path.append(os.path.abspath(\"..\"))"
    ]
   },
   {
@@ -34,7 +34,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from libpysal.cg.voronoi  import voronoi, voronoi_frames"
+    "from libpysal.cg.voronoi import voronoi, voronoi_frames"
    ]
   },
   {
@@ -120,9 +120,8 @@
    "outputs": [],
    "source": [
     "%matplotlib inline\n",
-    "import matplotlib\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt"
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np"
    ]
   },
   {
@@ -155,8 +154,8 @@
    ],
    "source": [
     "fig, ax = plt.subplots()\n",
-    "region_df.plot(ax=ax, color='blue',edgecolor='black', alpha=0.3)\n",
-    "point_df.plot(ax=ax, color='red')\n"
+    "region_df.plot(ax=ax, color=\"blue\", edgecolor=\"black\", alpha=0.3)\n",
+    "point_df.plot(ax=ax, color=\"red\")"
    ]
   },
   {
@@ -174,7 +173,7 @@
    "source": [
     "n_points = 200\n",
     "np.random.seed(12345)\n",
-    "points = np.random.random((n_points,2))*10 + 10\n",
+    "points = np.random.random((n_points, 2)) * 10 + 10\n",
     "results = voronoi(points)\n",
     "mins = points.min(axis=0)\n",
     "maxs = points.max(axis=0)"
@@ -228,7 +227,7 @@
    ],
    "source": [
     "fig, ax = plt.subplots()\n",
-    "points_df.plot(ax=ax, color='red')"
+    "points_df.plot(ax=ax, color=\"red\")"
    ]
   },
   {
@@ -261,8 +260,8 @@
    ],
    "source": [
     "fig, ax = plt.subplots()\n",
-    "regions_df.plot(ax=ax, color='blue',edgecolor='black', alpha=0.3)\n",
-    "points_df.plot(ax=ax, color='red')"
+    "regions_df.plot(ax=ax, color=\"blue\", edgecolor=\"black\", alpha=0.3)\n",
+    "points_df.plot(ax=ax, color=\"red\")"
    ]
   },
   {
@@ -313,12 +312,12 @@
    ],
    "source": [
     "fig, ax = plt.subplots()\n",
-    "regions_df.plot(ax=ax, edgecolor='black', facecolor='blue', alpha=0.2 )\n",
-    "points_df.plot(ax=ax, color='red')\n",
+    "regions_df.plot(ax=ax, edgecolor=\"black\", facecolor=\"blue\", alpha=0.2)\n",
+    "points_df.plot(ax=ax, color=\"red\")\n",
     "plt.xlim(minx, maxx)\n",
     "plt.ylim(miny, maxy)\n",
-    "plt.title(\"buffer: %f, n: %d\"%(r,n_points))\n",
-    "plt.show()\n"
+    "plt.title(\"buffer: %f, n: %d\" % (r, n_points))\n",
+    "plt.show()"
    ]
   },
   {
@@ -421,7 +420,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "idx = [i for i in range(w.n) if w.cardinalities[i]==12]"
+    "idx = [i for i in range(w.n) if w.cardinalities[i] == 12]"
    ]
   },
   {
diff --git a/docs/user-guide/weights/weights.ipynb b/docs/user-guide/weights/weights.ipynb
index b06937a51..621f666c7 100644
--- a/docs/user-guide/weights/weights.ipynb
+++ b/docs/user-guide/weights/weights.ipynb
@@ -13,8 +13,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import sys\n",
-    "import os"
+    "import os\n",
+    "import sys"
    ]
   },
   {
@@ -23,7 +23,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "sys.path.append(os.path.abspath('..'))\n",
+    "sys.path.append(os.path.abspath(\"..\"))\n",
     "import libpysal"
    ]
   },
@@ -108,7 +108,7 @@
     }
    ],
    "source": [
-    "libpysal.examples.explain('mexico')"
+    "libpysal.examples.explain(\"mexico\")"
    ]
   },
   {
@@ -125,10 +125,11 @@
    "outputs": [],
    "source": [
     "import geopandas\n",
+    "\n",
     "pth = libpysal.examples.get_path(\"mexicojoin.shp\")\n",
     "gdf = geopandas.read_file(pth)\n",
     "\n",
-    "from libpysal.weights import Queen, Rook, KNN"
+    "from libpysal.weights import KNN, Queen, Rook"
    ]
   },
   {
@@ -138,7 +139,7 @@
    "outputs": [],
    "source": [
     "%matplotlib inline\n",
-    "import matplotlib.pyplot as plt\n"
+    "import matplotlib.pyplot as plt"
    ]
   },
   {
@@ -241,10 +242,13 @@
     }
    ],
    "source": [
-    "ax = gdf.plot(edgecolor='grey', facecolor='w')\n",
-    "f,ax = w_rook.plot(gdf, ax=ax, \n",
-    "        edge_kws=dict(color='r', linestyle=':', linewidth=1),\n",
-    "        node_kws=dict(marker=''))\n",
+    "ax = gdf.plot(edgecolor=\"grey\", facecolor=\"w\")\n",
+    "f, ax = w_rook.plot(\n",
+    "    gdf,\n",
+    "    ax=ax,\n",
+    "    edge_kws=dict(color=\"r\", linestyle=\":\", linewidth=1),\n",
+    "    node_kws=dict(marker=\"\"),\n",
+    ")\n",
     "ax.set_axis_off()"
    ]
   },
@@ -488,7 +492,7 @@
     }
    ],
    "source": [
-    "w_rook.neighbors[0] # the first location has two neighbors at locations 1 and 22"
+    "w_rook.neighbors[0]  # the first location has two neighbors at locations 1 and 22"
    ]
   },
   {
@@ -511,7 +515,7 @@
     }
    ],
    "source": [
-    "gdf['NAME'][[0, 1,22]]"
+    "gdf[\"NAME\"][[0, 1, 22]]"
    ]
   },
   {
@@ -596,10 +600,13 @@
     }
    ],
    "source": [
-    "ax = gdf.plot(edgecolor='grey', facecolor='w')\n",
-    "f,ax = w_queen.plot(gdf, ax=ax, \n",
-    "        edge_kws=dict(color='r', linestyle=':', linewidth=1),\n",
-    "        node_kws=dict(marker=''))\n",
+    "ax = gdf.plot(edgecolor=\"grey\", facecolor=\"w\")\n",
+    "f, ax = w_queen.plot(\n",
+    "    gdf,\n",
+    "    ax=ax,\n",
+    "    edge_kws=dict(color=\"r\", linestyle=\":\", linewidth=1),\n",
+    "    node_kws=dict(marker=\"\"),\n",
+    ")\n",
     "ax.set_axis_off()"
    ]
   },
@@ -649,7 +656,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "c9 = [idx for idx,c in w_queen.cardinalities.items() if c==9]"
+    "c9 = [idx for idx, c in w_queen.cardinalities.items() if c == 9]"
    ]
   },
   {
@@ -670,7 +677,7 @@
     }
    ],
    "source": [
-    "gdf['NAME'][c9]"
+    "gdf[\"NAME\"][c9]"
    ]
   },
   {
@@ -743,21 +750,28 @@
    ],
    "source": [
     "import numpy as np\n",
-    "f,ax = plt.subplots(1,2,figsize=(10, 6), subplot_kw=dict(aspect='equal'))\n",
-    "gdf.plot(edgecolor='grey', facecolor='w', ax=ax[0])\n",
-    "w_rook.plot(gdf, ax=ax[0], \n",
-    "        edge_kws=dict(color='r', linestyle=':', linewidth=1),\n",
-    "        node_kws=dict(marker=''))\n",
-    "ax[0].set_title('Rook')\n",
+    "\n",
+    "f, ax = plt.subplots(1, 2, figsize=(10, 6), subplot_kw=dict(aspect=\"equal\"))\n",
+    "gdf.plot(edgecolor=\"grey\", facecolor=\"w\", ax=ax[0])\n",
+    "w_rook.plot(\n",
+    "    gdf,\n",
+    "    ax=ax[0],\n",
+    "    edge_kws=dict(color=\"r\", linestyle=\":\", linewidth=1),\n",
+    "    node_kws=dict(marker=\"\"),\n",
+    ")\n",
+    "ax[0].set_title(\"Rook\")\n",
     "ax[0].axis(np.asarray([-105.0, -95.0, 21, 26]))\n",
     "\n",
-    "ax[0].axis('off')\n",
-    "gdf.plot(edgecolor='grey', facecolor='w', ax=ax[1])\n",
-    "w_queen.plot(gdf, ax=ax[1], \n",
-    "        edge_kws=dict(color='r', linestyle=':', linewidth=1),\n",
-    "        node_kws=dict(marker=''))\n",
-    "ax[1].set_title('Queen')\n",
-    "ax[1].axis('off')\n",
+    "ax[0].axis(\"off\")\n",
+    "gdf.plot(edgecolor=\"grey\", facecolor=\"w\", ax=ax[1])\n",
+    "w_queen.plot(\n",
+    "    gdf,\n",
+    "    ax=ax[1],\n",
+    "    edge_kws=dict(color=\"r\", linestyle=\":\", linewidth=1),\n",
+    "    node_kws=dict(marker=\"\"),\n",
+    ")\n",
+    "ax[1].set_title(\"Queen\")\n",
+    "ax[1].axis(\"off\")\n",
     "ax[1].axis(np.asarray([-105.0, -95.0, 21, 26]))"
    ]
   },
@@ -809,10 +823,13 @@
     }
    ],
    "source": [
-    "ax = gdf.plot(edgecolor='grey', facecolor='w')\n",
-    "f,ax = w_knn.plot(gdf, ax=ax, \n",
-    "        edge_kws=dict(color='r', linestyle=':', linewidth=1),\n",
-    "        node_kws=dict(marker=''))\n",
+    "ax = gdf.plot(edgecolor=\"grey\", facecolor=\"w\")\n",
+    "f, ax = w_knn.plot(\n",
+    "    gdf,\n",
+    "    ax=ax,\n",
+    "    edge_kws=dict(color=\"r\", linestyle=\":\", linewidth=1),\n",
+    "    node_kws=dict(marker=\"\"),\n",
+    ")\n",
     "ax.set_axis_off()"
    ]
   },
@@ -830,7 +847,7 @@
    "outputs": [],
    "source": [
     "pth = libpysal.examples.get_path(\"mexicojoin.shp\")\n",
-    "from libpysal.weights import Queen, Rook, KNN"
+    "from libpysal.weights import KNN, Queen, Rook"
    ]
   },
   {
@@ -895,10 +912,13 @@
     }
    ],
    "source": [
-    "ax = gdf.plot(edgecolor='grey', facecolor='w')\n",
-    "f,ax = w_knn1.plot(gdf, ax=ax, \n",
-    "        edge_kws=dict(color='r', linestyle=':', linewidth=1),\n",
-    "        node_kws=dict(marker=''))\n",
+    "ax = gdf.plot(edgecolor=\"grey\", facecolor=\"w\")\n",
+    "f, ax = w_knn1.plot(\n",
+    "    gdf,\n",
+    "    ax=ax,\n",
+    "    edge_kws=dict(color=\"r\", linestyle=\":\", linewidth=1),\n",
+    "    node_kws=dict(marker=\"\"),\n",
+    ")\n",
     "ax.set_axis_off()"
    ]
   },
@@ -915,7 +935,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "w_knn3 = KNN.from_shapefile(pth,k=3)"
+    "w_knn3 = KNN.from_shapefile(pth, k=3)"
    ]
   },
   {
@@ -937,10 +957,13 @@
     }
    ],
    "source": [
-    "ax = gdf.plot(edgecolor='grey', facecolor='w')\n",
-    "f,ax = w_knn3.plot(gdf, ax=ax, \n",
-    "        edge_kws=dict(color='r', linestyle=':', linewidth=1),\n",
-    "        node_kws=dict(marker=''))\n",
+    "ax = gdf.plot(edgecolor=\"grey\", facecolor=\"w\")\n",
+    "f, ax = w_knn3.plot(\n",
+    "    gdf,\n",
+    "    ax=ax,\n",
+    "    edge_kws=dict(color=\"r\", linestyle=\":\", linewidth=1),\n",
+    "    node_kws=dict(marker=\"\"),\n",
+    ")\n",
     "ax.set_axis_off()"
    ]
   },
@@ -966,7 +989,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "w = lat2W(4,3)"
+    "w = lat2W(4, 3)"
    ]
   },
   {
@@ -1053,7 +1076,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "rs = libpysal.examples.get_path('map_RS_BR.shp')"
+    "rs = libpysal.examples.get_path(\"map_RS_BR.shp\")"
    ]
   },
   {
@@ -1193,11 +1216,14 @@
     }
    ],
    "source": [
-    "plt.rcParams[\"figure.figsize\"] = (20,15)\n",
-    "ax = rs_df.plot(edgecolor='grey', facecolor='w')\n",
-    "f,ax = wq.plot(rs_df, ax=ax, \n",
-    "        edge_kws=dict(color='r', linestyle=':', linewidth=1),\n",
-    "        node_kws=dict(marker=''))\n",
+    "plt.rcParams[\"figure.figsize\"] = (20, 15)\n",
+    "ax = rs_df.plot(edgecolor=\"grey\", facecolor=\"w\")\n",
+    "f, ax = wq.plot(\n",
+    "    rs_df,\n",
+    "    ax=ax,\n",
+    "    edge_kws=dict(color=\"r\", linestyle=\":\", linewidth=1),\n",
+    "    node_kws=dict(marker=\"\"),\n",
+    ")\n",
     "\n",
     "ax.set_axis_off()"
    ]
@@ -1221,14 +1247,16 @@
     }
    ],
    "source": [
-    "\n",
-    "ax = rs_df.plot(edgecolor='grey', facecolor='w')\n",
-    "f,ax = wf.plot(rs_df, ax=ax, \n",
-    "        edge_kws=dict(color='r', linestyle=':', linewidth=1),\n",
-    "        node_kws=dict(marker=''))\n",
-    "ax.set_title('Rio Grande do Sul: Nonplanar Weights')\n",
+    "ax = rs_df.plot(edgecolor=\"grey\", facecolor=\"w\")\n",
+    "f, ax = wf.plot(\n",
+    "    rs_df,\n",
+    "    ax=ax,\n",
+    "    edge_kws=dict(color=\"r\", linestyle=\":\", linewidth=1),\n",
+    "    node_kws=dict(marker=\"\"),\n",
+    ")\n",
+    "ax.set_title(\"Rio Grande do Sul: Nonplanar Weights\")\n",
     "ax.set_axis_off()\n",
-    "plt.savefig('rioGrandeDoSul.png')\n"
+    "plt.savefig(\"rioGrandeDoSul.png\")"
    ]
   },
   {
diff --git a/libpysal/examples/tests/test_available.py b/libpysal/examples/tests/test_available.py
index 549d2b422..59166a07a 100644
--- a/libpysal/examples/tests/test_available.py
+++ b/libpysal/examples/tests/test_available.py
@@ -20,7 +20,7 @@
 class TestExamples:
     def test_available(self):
         examples = available()
-        assert type(examples) == pandas.core.frame.DataFrame
+        assert isinstance(examples, pandas.DataFrame)
         assert examples.shape == (99, 3)
 
     def test_data_home(self):
diff --git a/pyproject.toml b/pyproject.toml
index 80dba4d4d..8f7740beb 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -82,12 +82,27 @@ include = ["libpysal", "libpysal.*"]
 line-length = 88
 lint.select = ["E", "F", "W", "I", "UP", "N", "B", "A", "C4", "SIM", "ARG"]
 target-version = "py310"
-exclude = ["libpysal/tests/*", "docs/*"]
+exclude = [
+    "libpysal/tests/*",
+    "libpysal/cg/tests/fast_point_in_polygon_algorithm.ipynb"
+]
+include = ["*.py", "*.ipynb"]
+
 [tool.ruff.lint.per-file-ignores]
 "*__init__.py" = [
     "F401",  # imported but unused
     "F403",  # star import; unable to detect undefined names
 ]
+"*.ipynb" = [
+    "C408",  # Unnecessary `dict` call
+    "E402",  # Module level import not at top of cell
+]
+"docs/conf.py" = [
+    "A001",  # Variable `copyright` is shadowing a Python builtin
+    "E501",  # Line too long
+    "UP031",  # Use format specifiers instead of percent format
+]
+
 
 
 [tool.coverage.run]