diff --git a/.github/workflows/build-wheels.yml b/.github/workflows/build-wheels.yml
index c10efe43..36188309 100644
--- a/.github/workflows/build-wheels.yml
+++ b/.github/workflows/build-wheels.yml
@@ -22,10 +22,10 @@ jobs:
     steps:
       - uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
       - name: Set up micromamba
-        uses: mamba-org/setup-micromamba@7f29b8b80078b1b601dfa018b0f7425c587c63bb
+        uses: mamba-org/setup-micromamba@add3a49764cedee8ee24e82dfde87f5bc2914462
       - name: Build wheels
-        uses: pypa/cibuildwheel@c923d83ad9c1bc00211c5041d0c3f73294ff88f6 # v3.1.4
-      - uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
+        uses: pypa/cibuildwheel@9c00cb4f6b517705a3794b22395aedc36257242c # v3.2.1
+      - uses: actions/upload-artifact@330a01c490aca151604b8cf639adc76d48f6c5d4 # v5.0.0
         with:
           name: cibw-wheels-${{ matrix.os }}-${{ strategy.job-index }}
           path: ./wheelhouse/*.whl
@@ -43,7 +43,7 @@ jobs:
         run: python -m pip install setuptools setuptools-scm wheel mako numpy 'Cython!=3.0.4'
       - name: Build sdist
         run: python setup.py sdist
-      - uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
+      - uses: actions/upload-artifact@330a01c490aca151604b8cf639adc76d48f6c5d4 # v5.0.0
         with:
           path: dist/*.tar.gz
 
@@ -57,7 +57,7 @@ jobs:
     permissions:
       id-token: write
     steps:
-      - uses: actions/download-artifact@634f93cb2916e3fdff6788551b99b062d0335ce0 # v5.0.0
+      - uses: actions/download-artifact@018cc2cf5baa6db3ef3c5f8a56943fffe632ef53 # v6.0.0
         with:
           merge-multiple: true
           path: dist
@@ -75,7 +75,7 @@ jobs:
     permissions:
       id-token: write
     steps:
-      - uses: actions/download-artifact@634f93cb2916e3fdff6788551b99b062d0335ce0 # v5.0.0
+      - uses: actions/download-artifact@018cc2cf5baa6db3ef3c5f8a56943fffe632ef53 # v6.0.0
         with:
           merge-multiple: true
           path: dist
diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 249ed76d..c35e0101 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -21,7 +21,7 @@ jobs:
       - name: Checkout branch
         uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
       - name: Set up pixi
-        uses: prefix-dev/setup-pixi@fef5c9568ca6c4ff7707bf840ab0692ba3f08293 # v0.9.0
+        uses: prefix-dev/setup-pixi@28eb668aafebd9dede9d97c4ba1cd9989a4d0004 # v0.9.2
         with:
           environments: lint default
       - name: pre-commit
@@ -40,15 +40,18 @@ jobs:
           - { os: ubuntu-latest, environment: 'py311' }
           - { os: ubuntu-latest, environment: 'py312' }
           - { os: ubuntu-latest, environment: 'py313' }
+          - { os: ubuntu-latest, environment: 'py314' }
           - { os: windows-latest, environment: 'py313' }
+          - { os: windows-latest, environment: 'py314' }
           - { os: macos-latest, environment: 'py313' }
+          - { os: macos-latest, environment: 'py314' }
           - { os: ubuntu-latest, environment: 'oldies' }
           - { os: ubuntu-latest, environment: 'nightly' }
     steps:
       - name: Checkout branch
         uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
       - name: Set up pixi
-        uses: prefix-dev/setup-pixi@fef5c9568ca6c4ff7707bf840ab0692ba3f08293 # v0.9.0
+        uses: prefix-dev/setup-pixi@28eb668aafebd9dede9d97c4ba1cd9989a4d0004 # v0.9.2
         with:
           environments: ${{ matrix.environment }}
       - name: Update dependencies
diff --git a/.github/workflows/conda-build.yml b/.github/workflows/conda-build.yml
index 55cd3d07..35c55bef 100644
--- a/.github/workflows/conda-build.yml
+++ b/.github/workflows/conda-build.yml
@@ -33,7 +33,7 @@ jobs:
         uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
       - name: Fetch full git history
         run: git fetch --prune --unshallow
-      - uses: mamba-org/setup-micromamba@7f29b8b80078b1b601dfa018b0f7425c587c63bb
+      - uses: mamba-org/setup-micromamba@add3a49764cedee8ee24e82dfde87f5bc2914462
         with:
           init-shell: ${{ matrix.os == 'windows-latest' && 'cmd.exe' || 'bash' }}
           micromamba-version: 1.5.10-0
diff --git a/.github/workflows/daily.yml b/.github/workflows/daily.yml
index f68138ac..134abb61 100644
--- a/.github/workflows/daily.yml
+++ b/.github/workflows/daily.yml
@@ -21,11 +21,13 @@ jobs:
             NOTE: 'Nightly Builds' # run once with nightlies
           - environment: 'py313'
             NOTE: 'Python 3.13' # run once with normal dependencies
+          - environment: 'py314'
+            NOTE: 'Python 3.14' # run once with normal dependencies
     steps:
       - name: Checkout branch
         uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
       - name: Set up pixi
-        uses: prefix-dev/setup-pixi@fef5c9568ca6c4ff7707bf840ab0692ba3f08293 # v0.9.0
+        uses: prefix-dev/setup-pixi@28eb668aafebd9dede9d97c4ba1cd9989a4d0004 # v0.9.2
         with:
           environments: ${{ matrix.environment }}
       - name: Update dependencies
diff --git a/.github/workflows/scorecard.yml b/.github/workflows/scorecard.yml
index a54ae0d5..c7cfbe91 100644
--- a/.github/workflows/scorecard.yml
+++ b/.github/workflows/scorecard.yml
@@ -40,7 +40,7 @@ jobs:
           persist-credentials: false
 
       - name: "Run analysis"
-        uses: ossf/scorecard-action@05b42c624433fc40578a4040d5cf5e36ddca8cde # v2.4.2
+        uses: ossf/scorecard-action@4eaacf0543bb3f2c246792bd56e8cdeffafb205a # v2.4.3
         with:
           results_file: results.sarif
           results_format: sarif
@@ -65,7 +65,7 @@ jobs:
       # Upload the results as artifacts (optional). Commenting out will disable uploads of run results in SARIF
       # format to the repository Actions tab.
       - name: "Upload artifact"
-        uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
+        uses: actions/upload-artifact@330a01c490aca151604b8cf639adc76d48f6c5d4 # v5.0.0
         with:
           name: SARIF file
           path: results.sarif
@@ -74,6 +74,6 @@ jobs:
       # Upload the results to GitHub's code scanning dashboard (optional).
       # Commenting out will disable upload of results to your repo's Code Scanning dashboard
       - name: "Upload to code-scanning"
-        uses: github/codeql-action/upload-sarif@2d2f57ed3a96a5c55ea34a02d2787de24943ebea # v3.28.15
+        uses: github/codeql-action/upload-sarif@80cb6b56b93de3e779c7d476d9100d06fb87c877 # v3.28.15
         with:
           sarif_file: results.sarif
diff --git a/CHANGELOG.rst b/CHANGELOG.rst
index 1f63e67b..2b0b6f61 100644
--- a/CHANGELOG.rst
+++ b/CHANGELOG.rst
@@ -7,10 +7,20 @@
 Changelog
 =========
 
+
+4.1.3 - 2025-11-12
+------------------
+
+**Bug fixes:**
+
+- Fixed :meth:`CategoricalMatrix.transpose_matvec` to operate on read-only buffers as well.
+- Fixed incorrect calculation of the shape of a :class:`CategoricalMatrix` when initialized with zero categories and ``drop_first=True``.
+
+
 4.1.2 - 2025-07-17
 ------------------
 
-**Bug fix:**
+**Bug fixes:**
 
 - Fixed a bug which caused issues when constructing tabmat matrices from existing ``ModelSpec``\s when they contained categorical columns with all levels dropped.
 - We can now treat dedicated pandas string series - which are the defaults for strings since pandas 2.3 - as categoricals.
diff --git a/pixi.lock b/pixi.lock
index f3cbedda..f9da686b 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -5,332 +5,337 @@ environments:
     - url: https://conda.anaconda.org/conda-forge/
     packages:
       linux-64:
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-4_kmp_llvm.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/binutils-2.44-h4852527_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/binutils_impl_linux-64-2.44-h4bf12b8_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/binutils_linux-64-2.44-h4852527_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/blas-2.135-mkl.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/blas-devel-3.9.0-35_hcf00494_mkl.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/brotli-1.1.0-hb03c661_4.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/brotli-bin-1.1.0-hb03c661_4.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-h4bc722e_7.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-6_kmp_llvm.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/binutils-2.44-h4852527_5.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/binutils_impl_linux-64-2.44-h9d8b0ac_5.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/binutils_linux-64-2.44-h4852527_5.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/blas-2.138-mkl.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/blas-devel-3.9.0-38_hcf00494_mkl.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/brotli-1.2.0-h41a2e66_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/brotli-bin-1.2.0-hf2c8021_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_8.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/c-compiler-1.11.0-h4d9bdce_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2025.8.3-hbd8a1cb_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/click-8.2.1-pyh707e725_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/conda-gcc-specs-14.3.0-hb991d5c_4.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/contourpy-1.3.3-py313h7037e92_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2025.10.5-hbd8a1cb_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/click-8.3.0-pyh707e725_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/conda-gcc-specs-14.3.0-hb991d5c_7.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/contourpy-1.3.3-py314h9891dd4_3.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/cxx-compiler-1.11.0-hfcd1e18_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/cycler-0.12.1-pyhd8ed1ab_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/cython-3.1.3-py313h3484ee8_2.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/fonttools-4.59.2-py313h3dea7bd_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/formulaic-1.2.0-py313h78bf25f_2.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/freetype-2.13.3-ha770c72_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/gcc-14.3.0-h76bdaa0_4.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/gcc_impl_linux-64-14.3.0-hd9e9e21_4.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/gcc_linux-64-14.3.0-h1382650_11.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/gxx-14.3.0-he448592_4.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_impl_linux-64-14.3.0-he663afc_4.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_linux-64-14.3.0-ha7acb78_11.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cython-3.2.0-py314h1807b08_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/fonttools-4.60.1-pyh7db6752_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/formulaic-1.2.1-pyhd8ed1ab_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/freetype-2.14.1-ha770c72_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/gcc-14.3.0-h76bdaa0_7.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/gcc_impl_linux-64-14.3.0-hd9e9e21_7.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/gcc_linux-64-14.3.0-h298d278_12.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/gxx-14.3.0-he448592_7.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_impl_linux-64-14.3.0-he663afc_7.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_linux-64-14.3.0-h95f728e_12.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-75.1-he02047a_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/importlib-metadata-8.7.0-pyhe01879c_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/interface_meta-1.3.0-pyhd8ed1ab_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/jemalloc-local-5.3.0-h5888daf_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/kernel-headers_linux-64-4.18.0-he073ed8_8.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/kiwisolver-1.4.9-py313hc8edb43_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/kiwisolver-1.4.9-py314h97ea11e_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/lcms2-2.17-h717163a_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.44-h1423503_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.44-h1aa0949_5.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/lerc-4.0.0-h0aef613_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libblas-3.9.0-35_hfdb39a5_mkl.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libbrotlicommon-1.1.0-hb03c661_4.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libbrotlidec-1.1.0-hb03c661_4.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libbrotlienc-1.1.0-hb03c661_4.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcblas-3.9.0-35_h372d94f_mkl.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libdeflate-1.24-h86f0d12_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libblas-3.9.0-38_h5875eb1_mkl.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libbrotlicommon-1.2.0-h09219d5_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libbrotlidec-1.2.0-hd53d788_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libbrotlienc-1.2.0-h02bd7ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcblas-3.9.0-38_hfef963f_mkl.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libdeflate-1.25-h17f619e_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.7.1-hecca717_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.4.6-h2dba641_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libfreetype-2.13.3-ha770c72_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libfreetype6-2.13.3-h48d6fc4_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-15.1.0-h767d61c_4.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/libgcc-devel_linux-64-14.3.0-h85bb3a7_104.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-15.1.0-h69a702a_4.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgfortran-15.1.0-h69a702a_4.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-15.1.0-hcea5267_4.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-15.1.0-h767d61c_4.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libhwloc-2.12.1-default_h3d81e11_1000.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.5.2-h9ec8514_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libfreetype-2.14.1-ha770c72_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libfreetype6-2.14.1-h73754d4_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-15.2.0-h767d61c_7.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/libgcc-devel_linux-64-14.3.0-h85bb3a7_107.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-15.2.0-h69a702a_7.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgfortran-15.2.0-h69a702a_7.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-15.2.0-hcd61629_7.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-15.2.0-h767d61c_7.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libhwloc-2.12.1-default_h7f8ec31_1002.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libiconv-1.18-h3b78370_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libjemalloc-local-5.3.0-h5888daf_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libjpeg-turbo-3.1.0-hb9d3cd8_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/liblapack-3.9.0-35_hc41d3b0_mkl.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/liblapacke-3.9.0-35_hbc6e62b_mkl.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libjpeg-turbo-3.1.2-hb03c661_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/liblapack-3.9.0-38_h5e43f62_mkl.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/liblapacke-3.9.0-38_hdba1596_mkl.conda
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   license: Apache-2.0
   license_family: APACHE
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-  timestamp: 1753465863221
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-  - aws-c-cal >=0.9.2,<0.9.3.0a0
-  - aws-c-common >=0.12.4,<0.12.5.0a0
+  - aws-c-common >=0.12.5,<0.12.6.0a0
+  - aws-c-cal >=0.9.8,<0.9.9.0a0
   license: Apache-2.0
   license_family: APACHE
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-  timestamp: 1753465872617
-- conda: https://conda.anaconda.org/conda-forge/linux-64/aws-c-mqtt-0.13.3-h19deb91_3.conda
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   - libgcc >=14
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-  - aws-c-common >=0.12.4,<0.12.5.0a0
-  - aws-c-http >=0.10.4,<0.10.5.0a0
+  - __glibc >=2.17,<3.0.a0
+  - aws-c-common >=0.12.5,<0.12.6.0a0
+  - aws-c-io >=0.23.2,<0.23.3.0a0
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   license: Apache-2.0
   license_family: APACHE
-  size: 216117
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-  - aws-c-http >=0.10.4,<0.10.5.0a0
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+  - aws-c-common >=0.12.5,<0.12.6.0a0
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-  - aws-c-http >=0.10.4,<0.10.5.0a0
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+  - aws-c-http >=0.10.7,<0.10.8.0a0
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   license: Apache-2.0
   license_family: APACHE
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/aws-c-s3-0.8.6-h800fcd2_2.conda
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-  - aws-c-cal >=0.9.2,<0.9.3.0a0
-  - aws-c-common >=0.12.4,<0.12.5.0a0
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+  - aws-c-cal >=0.9.8,<0.9.9.0a0
+  - aws-c-http >=0.10.7,<0.10.8.0a0
   license: Apache-2.0
   license_family: APACHE
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-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/aws-c-s3-0.8.6-h6ded10d_2.conda
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+  - aws-c-http >=0.10.7,<0.10.8.0a0
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   license: Apache-2.0
   license_family: APACHE
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-  - aws-c-io >=0.21.2,<0.21.3.0a0
-  - aws-c-auth >=0.9.0,<0.9.1.0a0
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+  - aws-c-http >=0.10.7,<0.10.8.0a0
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-  - __glibc >=2.17,<3.0.a0
   - libgcc >=14
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+  - __glibc >=2.17,<3.0.a0
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   license: Apache-2.0
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-  - aws-c-common >=0.12.4,<0.12.5.0a0
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   license: Apache-2.0
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+- conda: https://conda.anaconda.org/conda-forge/linux-64/aws-crt-cpp-0.35.0-h719b17a_2.conda
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   license: Apache-2.0
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-  - python >=3.9
+  - python >=3.10
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+  - python_abi 3.14.* *_cp314
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+  - cctools_osx-arm64 1024.3.*
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+  - clang 19.1.*
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-  - libbrotlidec >=1.1.0,<1.2.0a0
-  - libbrotlienc >=1.1.0,<1.2.0a0
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-  - arrow-cpp <0.0a0
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+  - arrow-cpp <0.0a0
+  - apache-arrow-proc =*=cpu
   license: Apache-2.0
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+  build_number: 3
+  sha256: 90259f086d83cdd14704f7a79e2883b8f1d8ba8d5b2e4aa2d73f76a1451ef21d
+  md5: c5ca32835f04c27585e9e6d28f76de9a
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   - libabseil >=20250512.1,<20250513.0a0
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-  - libarrow-acero 21.0.0 h7d8d6a5_1_cpu
-  - libarrow-dataset 21.0.0 h7d8d6a5_1_cpu
+  - libarrow 22.0.0 h0832232_3_cpu
+  - libarrow-acero 22.0.0 h7d8d6a5_3_cpu
+  - libarrow-dataset 22.0.0 h7d8d6a5_3_cpu
   - libprotobuf >=6.31.1,<6.31.2.0a0
   - ucrt >=10.0.20348.0
   - vc >=14.3,<15
   - vc14_runtime >=14.44.35208
   license: Apache-2.0
   license_family: APACHE
-  size: 354156
-  timestamp: 1754309358342
+  size: 358455
+  timestamp: 1762051870178
 - conda: https://conda.anaconda.org/conda-forge/linux-64/libblas-3.9.0-20_linux64_openblas.conda
   build_number: 20
   sha256: 8a0ee1de693a9b3da4a11b95ec81b40dd434bd01fa1f5f38f8268cd2146bf8f0
@@ -8396,38 +8097,41 @@ packages:
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   size: 14433
   timestamp: 1700568383457
-- conda: https://conda.anaconda.org/conda-forge/linux-64/libblas-3.9.0-35_h59b9bed_openblas.conda
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-  sha256: 83d0755acd486660532003bc2562223504b57732bc7e250985391ce335692cf7
-  md5: eaf80af526daf5745295d9964c2bd3cf
+- conda: https://conda.anaconda.org/conda-forge/linux-64/libblas-3.9.0-38_h4a7cf45_openblas.conda
+  build_number: 38
+  sha256: b26a32302194e05fa395d5135699fd04a905c6ad71f24333f97c64874e053623
+  md5: 3509b5e2aaa5f119013c8969fdd9a905
   depends:
   - libopenblas >=0.3.30,<0.3.31.0a0
   - libopenblas >=0.3.30,<1.0a0
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-  - liblapack  3.9.0   35*_openblas
-  - libcblas   3.9.0   35*_openblas
-  - liblapacke 3.9.0   35*_openblas
-  - mkl <2025
+  - libcblas   3.9.0   38*_openblas
+  - blas 2.138   openblas
+  - liblapacke 3.9.0   38*_openblas
+  - mkl <2026
+  - liblapack  3.9.0   38*_openblas
   license: BSD-3-Clause
-  size: 16937
-  timestamp: 1757002815691
-- conda: https://conda.anaconda.org/conda-forge/linux-64/libblas-3.9.0-35_hfdb39a5_mkl.conda
-  build_number: 35
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-  md5: 9fedd782400297fa574e739146f04e34
+  license_family: BSD
+  size: 17522
+  timestamp: 1761680084434
+- conda: https://conda.anaconda.org/conda-forge/linux-64/libblas-3.9.0-38_h5875eb1_mkl.conda
+  build_number: 38
+  sha256: 92da128915b6d074524fda62f1fc39b003eef97033be6c08bdc985bc01df5adc
+  md5: 964191c395c74240f6ab88bbecdaf612
   depends:
-  - mkl >=2024.2.2,<2025.0a0
+  - mkl >=2025.3.0,<2026.0a0
   constrains:
-  - liblapacke 3.9.0   35*_mkl
-  - blas 2.135   mkl
-  - liblapack  3.9.0   35*_mkl
-  - libcblas   3.9.0   35*_mkl
+  - liblapack  3.9.0   38*_mkl
+  - blas 2.138   mkl
+  - libcblas   3.9.0   38*_mkl
+  - liblapacke 3.9.0   38*_mkl
   track_features:
   - blas_mkl
+  - blas_mkl_2
   license: BSD-3-Clause
-  size: 17387
-  timestamp: 1757002960950
+  license_family: BSD
+  size: 17918
+  timestamp: 1761680169865
 - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libblas-3.9.0-20_osxarm64_openblas.conda
   build_number: 20
   sha256: 5b5b8394352c8ca06b15dcc9319d0af3e9f1dc03fc0a6f6deef05d664d6b763a
@@ -8444,22 +8148,23 @@ packages:
   license_family: BSD
   size: 14722
   timestamp: 1700568881837
-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libblas-3.9.0-35_h10e41b3_openblas.conda
-  build_number: 35
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-  md5: 0b59bf8bb0bc16b2c5bdae947a44e1f1
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libblas-3.9.0-38_h51639a9_openblas.conda
+  build_number: 38
+  sha256: 1850e189ca9b623497b857cf905bb2c8d57c8a42de5aed63a9b0bd857a1af2ae
+  md5: 90a49011b477170c063b385cbacf9138
   depends:
   - libopenblas >=0.3.30,<0.3.31.0a0
   - libopenblas >=0.3.30,<1.0a0
   constrains:
-  - libcblas   3.9.0   35*_openblas
-  - liblapacke 3.9.0   35*_openblas
-  - liblapack  3.9.0   35*_openblas
-  - mkl <2025
-  - blas 2.135   openblas
+  - liblapack  3.9.0   38*_openblas
+  - libcblas   3.9.0   38*_openblas
+  - mkl <2026
+  - liblapacke 3.9.0   38*_openblas
+  - blas 2.138   openblas
   license: BSD-3-Clause
-  size: 17191
-  timestamp: 1757003619794
+  license_family: BSD
+  size: 17695
+  timestamp: 1761680554564
 - conda: https://conda.anaconda.org/conda-forge/win-64/libblas-3.9.0-35_h5709861_mkl.conda
   build_number: 35
   sha256: 4180e7ab27ed03ddf01d7e599002fcba1b32dcb68214ee25da823bac371ed362
@@ -8472,104 +8177,120 @@ packages:
   - libcblas   3.9.0   35*_mkl
   - liblapacke 3.9.0   35*_mkl
   license: BSD-3-Clause
+  license_family: BSD
   size: 66044
   timestamp: 1757003486248
-- conda: https://conda.anaconda.org/conda-forge/linux-64/libbrotlicommon-1.1.0-hb03c661_4.conda
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-  md5: 1d29d2e33fe59954af82ef54a8af3fe1
+- conda: https://conda.anaconda.org/conda-forge/win-64/libblas-3.9.0-38_hf2e6a31_mkl.conda
+  build_number: 38
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+  md5: dcee15907da751895e20b4d1ac94568d
+  depends:
+  - mkl >=2025.3.0,<2026.0a0
+  constrains:
+  - blas 2.138   mkl
+  - liblapacke 3.9.0   38*_mkl
+  - libcblas   3.9.0   38*_mkl
+  - liblapack  3.9.0   38*_mkl
+  license: BSD-3-Clause
+  license_family: BSD
+  size: 66706
+  timestamp: 1761680784374
+- conda: https://conda.anaconda.org/conda-forge/linux-64/libbrotlicommon-1.2.0-h09219d5_0.conda
+  sha256: fbbcd11742bb8c96daa5f4f550f1804a902708aad2092b39bec3faaa2c8ae88a
+  md5: 9b3117ec960b823815b02190b41c0484
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   - libgcc >=14
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   license_family: MIT
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-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libbrotlicommon-1.1.0-h6caf38d_4.conda
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   license_family: MIT
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+- conda: https://conda.anaconda.org/conda-forge/win-64/libbrotlicommon-1.2.0-hc82b238_0.conda
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/libbrotlidec-1.1.0-hb03c661_4.conda
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+- conda: https://conda.anaconda.org/conda-forge/linux-64/libbrotlidec-1.2.0-hd53d788_0.conda
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+  - libbrotlicommon 1.2.0 h09219d5_0
   - libgcc >=14
   license: MIT
   license_family: MIT
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-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libbrotlidec-1.1.0-h6caf38d_4.conda
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-  - libbrotlicommon 1.1.0 h6caf38d_4
+  - libbrotlicommon 1.2.0 h87ba0bc_0
   license: MIT
   license_family: MIT
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-- conda: https://conda.anaconda.org/conda-forge/win-64/libbrotlidec-1.1.0-hfd05255_4.conda
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+  - libbrotlicommon 1.2.0 hc82b238_0
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-  - libbrotlicommon 1.1.0 hb03c661_4
+  - libbrotlicommon 1.2.0 h09219d5_0
   - libgcc >=14
   license: MIT
   license_family: MIT
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-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libbrotlienc-1.1.0-h6caf38d_4.conda
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+  md5: 4e3fec2238527187566e26a5ddbc2f83
   depends:
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-  - libbrotlicommon 1.1.0 h6caf38d_4
+  - libbrotlicommon 1.2.0 h87ba0bc_0
   license: MIT
   license_family: MIT
-  size: 275791
-  timestamp: 1756599724058
-- conda: https://conda.anaconda.org/conda-forge/win-64/libbrotlienc-1.1.0-hfd05255_4.conda
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-  md5: 37f4669f8ac2f04d826440a8f3f42300
+  size: 291133
+  timestamp: 1761592499578
+- conda: https://conda.anaconda.org/conda-forge/win-64/libbrotlienc-1.2.0-ha521d6b_0.conda
+  sha256: eb54110ee720e4a73b034d0c2bb0f26eadf79a1bd6b0656ebdf914da8f14989d
+  md5: f780291507a3f91d93a7147daea082f8
   depends:
-  - libbrotlicommon 1.1.0 hfd05255_4
+  - libbrotlicommon 1.2.0 hc82b238_0
   - ucrt >=10.0.20348.0
   - vc >=14.3,<15
   - vc14_runtime >=14.44.35208
   license: MIT
   license_family: MIT
-  size: 245418
-  timestamp: 1756599770744
+  size: 253172
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 - conda: https://conda.anaconda.org/conda-forge/linux-64/libcblas-3.9.0-20_linux64_openblas.conda
   build_number: 20
   sha256: 0e34fb0f82262f02fcb279ab4a1db8d50875dc98e3019452f8f387e6bf3c0247
@@ -8585,34 +8306,36 @@ packages:
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   size: 14383
   timestamp: 1700568410580
-- conda: https://conda.anaconda.org/conda-forge/linux-64/libcblas-3.9.0-35_h372d94f_mkl.conda
-  build_number: 35
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-  md5: 25fab7e2988299928dea5939d9958293
+- conda: https://conda.anaconda.org/conda-forge/linux-64/libcblas-3.9.0-38_h0358290_openblas.conda
+  build_number: 38
+  sha256: 7fe653f45c01eb16d7b48ad934b068dad2885d6f4a7c41512b6a5f1f522bffe9
+  md5: bcd928a9376a215cd9164a4312dd5e98
   depends:
-  - libblas 3.9.0 35_hfdb39a5_mkl
+  - libblas 3.9.0 38_h4a7cf45_openblas
   constrains:
-  - blas 2.135   mkl
-  - liblapack  3.9.0   35*_mkl
-  - liblapacke 3.9.0   35*_mkl
-  track_features:
-  - blas_mkl
+  - blas 2.138   openblas
+  - liblapack  3.9.0   38*_openblas
+  - liblapacke 3.9.0   38*_openblas
   license: BSD-3-Clause
-  size: 17021
-  timestamp: 1757002973897
-- conda: https://conda.anaconda.org/conda-forge/linux-64/libcblas-3.9.0-35_he106b2a_openblas.conda
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-  md5: e62d58d32431dabed236c860dfa566ca
+  license_family: BSD
+  size: 17503
+  timestamp: 1761680091587
+- conda: https://conda.anaconda.org/conda-forge/linux-64/libcblas-3.9.0-38_hfef963f_mkl.conda
+  build_number: 38
+  sha256: 94e0599d062a892e5ca3c2240feb7cb754779d68075f301bcb1fb5f290b6a6fd
+  md5: b71baaa269cfecb2b0ffb6eaff577d88
   depends:
-  - libblas 3.9.0 35_h59b9bed_openblas
+  - libblas 3.9.0 38_h5875eb1_mkl
   constrains:
-  - blas 2.135   openblas
-  - liblapack  3.9.0   35*_openblas
-  - liblapacke 3.9.0   35*_openblas
+  - liblapack  3.9.0   38*_mkl
+  - blas 2.138   mkl
+  - liblapacke 3.9.0   38*_mkl
+  track_features:
+  - blas_mkl
   license: BSD-3-Clause
-  size: 16900
-  timestamp: 1757002826333
+  license_family: BSD
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+  timestamp: 1761680182631
 - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libcblas-3.9.0-20_osxarm64_openblas.conda
   build_number: 20
   sha256: d3a74638f60e034202e373cf2950c69a8d831190d497881d13cbf789434d2489
@@ -8627,19 +8350,20 @@ packages:
   license_family: BSD
   size: 14642
   timestamp: 1700568912840
-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libcblas-3.9.0-35_hb3479ef_openblas.conda
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-  sha256: dfd8dd4eea94894a01c1e4d9a409774ad2b71f77e713eb8c0dc62bb47abe2f0b
-  md5: 7f8a6b52d39bde47c6f2d3ef96bd5e68
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libcblas-3.9.0-38_hb0561ab_openblas.conda
+  build_number: 38
+  sha256: 5ab5a9aa350a5838d91f0e4feed30f765cbea461ee9515bf214d459c3378a531
+  md5: eab61fcb277d6fa9f059bba437fd3612
   depends:
-  - libblas 3.9.0 35_h10e41b3_openblas
+  - libblas 3.9.0 38_h51639a9_openblas
   constrains:
-  - liblapacke 3.9.0   35*_openblas
-  - blas 2.135   openblas
-  - liblapack  3.9.0   35*_openblas
+  - liblapack  3.9.0   38*_openblas
+  - liblapacke 3.9.0   38*_openblas
+  - blas 2.138   openblas
   license: BSD-3-Clause
-  size: 17163
-  timestamp: 1757003634172
+  license_family: BSD
+  size: 17685
+  timestamp: 1761680563279
 - conda: https://conda.anaconda.org/conda-forge/win-64/libcblas-3.9.0-35_h2a3cdd5_mkl.conda
   build_number: 35
   sha256: 88939f6c1b5da75bd26ce663aa437e1224b26ee0dab5e60cecc77600975f397e
@@ -8651,19 +8375,34 @@ packages:
   - liblapack  3.9.0   35*_mkl
   - liblapacke 3.9.0   35*_mkl
   license: BSD-3-Clause
+  license_family: BSD
   size: 66398
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-  - libcblas   3.9.0   35*_openblas
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+  - libcblas   3.9.0   38*_openblas
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-  - libcblas   3.9.0   35*_mkl
+  - blas 2.138   mkl
+  - libcblas   3.9.0   38*_mkl
+  - liblapacke 3.9.0   38*_mkl
   track_features:
   - blas_mkl
   license: BSD-3-Clause
-  size: 17011
-  timestamp: 1757002986706
+  license_family: BSD
+  size: 17563
+  timestamp: 1761680194101
 - conda: https://conda.anaconda.org/conda-forge/osx-arm64/liblapack-3.9.0-20_osxarm64_openblas.conda
   build_number: 20
   sha256: e13f79828a7752f6e0a74cbe62df80c551285f6c37de86bc3bd9987c97faca57
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   timestamp: 1700568930669
-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/liblapack-3.9.0-35_hc9a63f6_openblas.conda
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-  md5: 437d6c679b3d959d87b3b735fcc0b4ee
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/liblapack-3.9.0-38_hd9741b5_openblas.conda
+  build_number: 38
+  sha256: df4f43d2ba45b7b80a45e8c0e51d3d7675a00047089beea7dc54e685825df9f6
+  md5: 4525f30079caf1a2290538c2c531f354
   depends:
-  - libblas 3.9.0 35_h10e41b3_openblas
+  - libblas 3.9.0 38_h51639a9_openblas
   constrains:
-  - liblapacke 3.9.0   35*_openblas
-  - libcblas   3.9.0   35*_openblas
-  - blas 2.135   openblas
+  - liblapacke 3.9.0   38*_openblas
+  - blas 2.138   openblas
+  - libcblas   3.9.0   38*_openblas
   license: BSD-3-Clause
-  size: 17166
-  timestamp: 1757003647724
+  license_family: BSD
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+  timestamp: 1761680572118
 - conda: https://conda.anaconda.org/conda-forge/win-64/liblapack-3.9.0-35_hf9ab0e9_mkl.conda
   build_number: 35
   sha256: 56e0992fb58eed8f0d5fa165b8621fa150b84aa9af1467ea0a7a9bb7e2fced4f
@@ -9468,49 +9212,67 @@ packages:
   - libcblas   3.9.0   35*_mkl
   - liblapacke 3.9.0   35*_mkl
   license: BSD-3-Clause
+  license_family: BSD
   size: 78485
   timestamp: 1757003541803
-- conda: https://conda.anaconda.org/conda-forge/linux-64/liblapacke-3.9.0-35_hbc6e62b_mkl.conda
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-  md5: 426313fe1dc5ad3060efea56253fcd76
+- conda: https://conda.anaconda.org/conda-forge/win-64/liblapack-3.9.0-38_hf9ab0e9_mkl.conda
+  build_number: 38
+  sha256: 3b8d2d800f48fb9045a976c5a10cefe742142df88decf5a5108fe6b7c8fb5b50
+  md5: eb3167046ffba0ceb4a8824fb1b79a69
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-  - libcblas 3.9.0 35_h372d94f_mkl
-  - liblapack 3.9.0 35_hc41d3b0_mkl
+  - libblas 3.9.0 38_hf2e6a31_mkl
   constrains:
-  - blas 2.135   mkl
+  - blas 2.138   mkl
+  - liblapacke 3.9.0   38*_mkl
+  - libcblas   3.9.0   38*_mkl
+  license: BSD-3-Clause
+  license_family: BSD
+  size: 79298
+  timestamp: 1761680854566
+- conda: https://conda.anaconda.org/conda-forge/linux-64/liblapacke-3.9.0-38_hdba1596_mkl.conda
+  build_number: 38
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+  md5: e921f74a7e330577c859f5e0e58b7a5b
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+  - libcblas 3.9.0 38_hfef963f_mkl
+  - liblapack 3.9.0 38_h5e43f62_mkl
+  constrains:
+  - blas 2.138   mkl
   track_features:
   - blas_mkl
   license: BSD-3-Clause
-  size: 17031
-  timestamp: 1757002999615
-- conda: https://conda.anaconda.org/conda-forge/win-64/liblapacke-3.9.0-35_h3ae206f_mkl.conda
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-  md5: d777c47b311db74f7d4c76c9a0cb2306
+  license_family: BSD
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+  timestamp: 1761680205484
+- conda: https://conda.anaconda.org/conda-forge/win-64/liblapacke-3.9.0-38_h3ae206f_mkl.conda
+  build_number: 38
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+  md5: a5d6c0566ea0c793076986b86dbcf378
   depends:
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-  - libcblas 3.9.0 35_h2a3cdd5_mkl
-  - liblapack 3.9.0 35_hf9ab0e9_mkl
+  - libblas 3.9.0 38_hf2e6a31_mkl
+  - libcblas 3.9.0 38_h2a3cdd5_mkl
+  - liblapack 3.9.0 38_hf9ab0e9_mkl
   constrains:
-  - blas 2.135   mkl
+  - blas 2.138   mkl
   license: BSD-3-Clause
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-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libllvm19-19.1.7-hc4b4ae8_1.conda
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-  md5: 020aeb16fc952ac441852d8eba2cf2fd
+  license_family: BSD
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+  timestamp: 1761680889508
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libllvm19-19.1.7-h8e0c9ce_2.conda
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   depends:
   - __osx >=11.0
-  - libcxx >=18
-  - libxml2 >=2.13.5,<2.14.0a0
+  - libcxx >=19
+  - libxml2
+  - libxml2-16 >=2.14.5
   - libzlib >=1.3.1,<2.0a0
-  - zstd >=1.5.6,<1.6.0a0
+  - zstd >=1.5.7,<1.6.0a0
   license: Apache-2.0 WITH LLVM-exception
   license_family: Apache
-  size: 27012197
-  timestamp: 1737781370567
+  size: 26914852
+  timestamp: 1757353228286
 - conda: https://conda.anaconda.org/conda-forge/linux-64/liblzma-5.8.1-hb9d3cd8_2.conda
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@@ -9544,36 +9306,6 @@ packages:
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   timestamp: 1749230611612
-- conda: https://conda.anaconda.org/conda-forge/linux-64/liblzma-devel-5.8.1-hb9d3cd8_2.conda
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-  - libgcc >=13
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-  license: 0BSD
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-  timestamp: 1749230061968
-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/liblzma-devel-5.8.1-h39f12f2_2.conda
-  sha256: 974804430e24f0b00f3a48b67ec10c9f5441c9bb3d82cc0af51ba45b8a75a241
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-  timestamp: 1749230297170
-- conda: https://conda.anaconda.org/conda-forge/win-64/liblzma-devel-5.8.1-h2466b09_2.conda
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-  - vc >=14.2,<15
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-  license: 0BSD
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 - conda: https://conda.anaconda.org/conda-forge/linux-64/libmpdec-4.0.0-hb9d3cd8_0.conda
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@@ -9658,9 +9390,9 @@ packages:
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   timestamp: 1700536004164
-- conda: https://conda.anaconda.org/conda-forge/linux-64/libopenblas-0.3.30-pthreads_h94d23a6_2.conda
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-  md5: dfc5aae7b043d9f56ba99514d5e60625
+- conda: https://conda.anaconda.org/conda-forge/linux-64/libopenblas-0.3.30-pthreads_h94d23a6_3.conda
+  sha256: 200899e5acc01fa29550d2782258d9cf33e55ce4cbce8faed9c6fe0b774852aa
+  md5: ac2e4832427d6b159576e8a68305c722
   depends:
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   - libgcc >=14
@@ -9670,8 +9402,8 @@ packages:
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   license: BSD-3-Clause
   license_family: BSD
-  size: 5938936
-  timestamp: 1755474342204
+  size: 5918287
+  timestamp: 1761748180250
 - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libopenblas-0.3.25-openmp_h6c19121_0.conda
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@@ -9685,9 +9417,9 @@ packages:
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   timestamp: 1700535987588
-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libopenblas-0.3.30-openmp_h60d53f8_2.conda
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-  md5: d004259fd8d3d2798b16299d6ad6c9e9
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libopenblas-0.3.30-openmp_ha158390_3.conda
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+  md5: a18a7f471c517062ee71b843ef95eb8a
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@@ -9697,8 +9429,8 @@ packages:
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   license: BSD-3-Clause
   license_family: BSD
-  size: 4284696
-  timestamp: 1755471861128
+  size: 4285762
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 - conda: https://conda.anaconda.org/conda-forge/linux-64/libopentelemetry-cpp-1.21.0-hb9b0907_1.conda
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@@ -9751,54 +9483,54 @@ packages:
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/libparquet-21.0.0-h790f06f_1_cpu.conda
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+- conda: https://conda.anaconda.org/conda-forge/linux-64/libparquet-22.0.0-h7376487_3_cpu.conda
+  build_number: 3
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+  - openssl >=3.5.4,<4.0a0
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+  - libarrow 22.0.0 h4f7d3e6_3_cpu
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+  - openssl >=3.5.4,<4.0a0
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   license: Apache-2.0
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-  size: 909390
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 - conda: https://conda.anaconda.org/conda-forge/linux-64/libpng-1.6.50-h421ea60_1.conda
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+- conda: https://conda.anaconda.org/conda-forge/linux-64/libprotobuf-6.31.1-h49aed37_2.conda
+  sha256: 1679f16c593d769f3dab219adb1117cbaaddb019080c5a59f79393dc9f45b84f
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-  - libgcc >=13
-  - libstdcxx >=13
+  - libgcc >=14
+  - libstdcxx >=14
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+- conda: https://conda.anaconda.org/conda-forge/win-64/libprotobuf-6.31.1-hdcda5b4_2.conda
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/libre2-11-2025.07.22-h7b12aa8_0.conda
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+  - re2 2025.11.05.*
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-  - clang       19.1.7
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-  - zstd >=1.5.6,<1.6.0a0
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+  - python >=3.10
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   license_family: BSD
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+  - vc >=14.3,<15
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+  - zstd >=1.5.7,<1.6.0a0
   license: Python-2.0
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-- conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.9-8_cp39.conda
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-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/xz-gpl-tools-5.8.1-h9a6d368_2.conda
-  sha256: a0790cfb48d240e7b655b0d797a00040219cf39e3ee38e2104e548515df4f9c2
-  md5: 09b1442c1d49ac7c5f758c44695e77d1
-  depends:
-  - __osx >=11.0
-  - liblzma 5.8.1 h39f12f2_2
-  constrains:
-  - xz 5.8.1.*
-  license: 0BSD AND LGPL-2.1-or-later AND GPL-2.0-or-later
-  size: 34103
-  timestamp: 1749230329933
-- conda: https://conda.anaconda.org/conda-forge/linux-64/xz-tools-5.8.1-hb9d3cd8_2.conda
-  sha256: 58034f3fca491075c14e61568ad8b25de00cb3ae479de3e69be6d7ee5d3ace28
-  md5: 1bad2995c8f1c8075c6c331bf96e46fb
-  depends:
-  - __glibc >=2.17,<3.0.a0
-  - libgcc >=13
-  - liblzma 5.8.1 hb9d3cd8_2
-  constrains:
-  - xz 5.8.1.*
-  license: 0BSD AND LGPL-2.1-or-later
-  size: 96433
-  timestamp: 1749230076687
-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/xz-tools-5.8.1-h39f12f2_2.conda
-  sha256: 9d1232705e3d175f600dc8e344af9182d0341cdaa73d25330591a28532951063
-  md5: 37996935aa33138fca43e4b4563b6a28
-  depends:
-  - __osx >=11.0
-  - liblzma 5.8.1 h39f12f2_2
-  constrains:
-  - xz 5.8.1.*
-  license: 0BSD AND LGPL-2.1-or-later
-  size: 86425
-  timestamp: 1749230316106
-- conda: https://conda.anaconda.org/conda-forge/win-64/xz-tools-5.8.1-h2466b09_2.conda
-  sha256: 38712f0e62f61741ab69d7551fa863099f5be769bdf9fdbc28542134874b4e88
-  md5: e1b62ec0457e6ba10287a49854108fdb
-  depends:
-  - liblzma 5.8.1 h2466b09_2
-  - ucrt >=10.0.20348.0
-  - vc >=14.2,<15
-  - vc14_runtime >=14.29.30139
-  constrains:
-  - xz 5.8.1.*
-  license: 0BSD AND LGPL-2.1-or-later
-  size: 67419
-  timestamp: 1749230666460
+  size: 146026
+  timestamp: 1761578757777
 - conda: https://conda.anaconda.org/conda-forge/linux-64/yaml-0.2.5-h280c20c_3.conda
   sha256: 6d9ea2f731e284e9316d95fa61869fe7bbba33df7929f82693c121022810f4ad
   md5: a77f85f77be52ff59391544bfe73390a
@@ -16398,44 +15869,48 @@ packages:
   license_family: MIT
   size: 63944
   timestamp: 1753484092156
-- conda: https://conda.anaconda.org/conda-forge/linux-64/zeromq-4.3.5-h3b0a872_7.conda
-  sha256: a4dc72c96848f764bb5a5176aa93dd1e9b9e52804137b99daeebba277b31ea10
-  md5: 3947a35e916fcc6b9825449affbf4214
+- conda: https://conda.anaconda.org/conda-forge/linux-64/zeromq-4.3.5-h387f397_9.conda
+  sha256: 47cfe31255b91b4a6fa0e9dbaf26baa60ac97e033402dbc8b90ba5fee5ffe184
+  md5: 8035e5b54c08429354d5d64027041cad
   depends:
+  - libstdcxx >=14
+  - libgcc >=14
   - __glibc >=2.17,<3.0.a0
-  - krb5 >=1.21.3,<1.22.0a0
-  - libgcc >=13
+  - libgcc >=14
   - libsodium >=1.0.20,<1.0.21.0a0
-  - libstdcxx >=13
+  - krb5 >=1.21.3,<1.22.0a0
   license: MPL-2.0
   license_family: MOZILLA
-  size: 335400
-  timestamp: 1731585026517
-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/zeromq-4.3.5-hc1bb282_7.conda
-  sha256: 9e585569fe2e7d3bea71972cd4b9f06b1a7ab8fa7c5139f92a31cbceecf25a8a
-  md5: f7e6b65943cb73bce0143737fded08f1
+  size: 310648
+  timestamp: 1757370847287
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/zeromq-4.3.5-h888dc83_9.conda
+  sha256: b6f9c130646e5971f6cad708e1eee278f5c7eea3ca97ec2fdd36e7abb764a7b8
+  md5: 26f39dfe38a2a65437c29d69906a0f68
   depends:
   - __osx >=11.0
-  - krb5 >=1.21.3,<1.22.0a0
-  - libcxx >=18
+  - libcxx >=19
   - libsodium >=1.0.20,<1.0.21.0a0
+  - krb5 >=1.21.3,<1.22.0a0
   license: MPL-2.0
   license_family: MOZILLA
-  size: 281565
-  timestamp: 1731585108039
-- conda: https://conda.anaconda.org/conda-forge/win-64/zeromq-4.3.5-ha9f60a1_7.conda
-  sha256: 15cc8e2162d0a33ffeb3f7b7c7883fd830c54a4b1be6a4b8c7ee1f4fef0088fb
-  md5: e03f2c245a5ee6055752465519363b1c
+  size: 244772
+  timestamp: 1757371008525
+- conda: https://conda.anaconda.org/conda-forge/win-64/zeromq-4.3.5-h5bddc39_9.conda
+  sha256: 690cf749692c8ea556646d1a47b5824ad41b2f6dfd949e4cdb6c44a352fcb1aa
+  md5: a6c8f8ee856f7c3c1576e14b86cd8038
   depends:
-  - krb5 >=1.21.3,<1.22.0a0
-  - libsodium >=1.0.20,<1.0.21.0a0
+  - vc >=14.3,<15
+  - vc14_runtime >=14.44.35208
   - ucrt >=10.0.20348.0
-  - vc >=14.2,<15
-  - vc14_runtime >=14.29.30139
+  - vc >=14.3,<15
+  - vc14_runtime >=14.44.35208
+  - ucrt >=10.0.20348.0
+  - libsodium >=1.0.20,<1.0.21.0a0
+  - krb5 >=1.21.3,<1.22.0a0
   license: MPL-2.0
   license_family: MOZILLA
-  size: 2527503
-  timestamp: 1731585151036
+  size: 265212
+  timestamp: 1757370864284
 - conda: https://conda.anaconda.org/conda-forge/noarch/zipp-3.23.0-pyhd8ed1ab_0.conda
   sha256: 7560d21e1b021fd40b65bfb72f67945a3fcb83d78ad7ccf37b8b3165ec3b68ad
   md5: df5e78d904988eb55042c0c97446079f
@@ -16466,49 +15941,84 @@ packages:
   license_family: Other
   size: 77606
   timestamp: 1727963209370
-- conda: https://conda.anaconda.org/conda-forge/linux-64/zstandard-0.24.0-py313h736c1ce_1.conda
-  sha256: 5a148ac6fc01e41e635e1e5ac4a0fb834e29599a737cd5dddec98ae393bf9efc
-  md5: 2ca7715c89929da3d648144f8b34cf99
+- conda: https://conda.anaconda.org/conda-forge/linux-64/zlib-ng-2.2.5-hde8ca8f_0.conda
+  sha256: 3a8e7798deafd0722b6b5da50c36b7f361a80b30165d600f7760d569a162ff95
+  md5: 1920c3502e7f6688d650ab81cd3775fd
   depends:
   - __glibc >=2.17,<3.0.a0
-  - cffi >=1.11
   - libgcc >=14
-  - python >=3.13,<3.14.0a0
-  - python_abi 3.13.* *_cp313
+  - libstdcxx >=14
+  license: Zlib
+  license_family: Other
+  size: 110843
+  timestamp: 1754587144298
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/zlib-ng-2.2.5-h3470cca_0.conda
+  sha256: 82e3b57478d536b68229d1dbcdabe728fada5dbe77f9238a5fff5fc37a7fa758
+  md5: c86493f35e79c93b04ff0279092b53e2
+  depends:
+  - __osx >=11.0
+  - libcxx >=19
+  license: Zlib
+  license_family: Other
+  size: 87296
+  timestamp: 1761843121173
+- conda: https://conda.anaconda.org/conda-forge/win-64/zlib-ng-2.2.5-h32d8bfd_0.conda
+  sha256: 67a3113acf3506f1cf1c72e0748742217a20edc6c1c1c19631f901c5e028d2bc
+  md5: dec092b1a069abafc38655ded65a7b29
+  depends:
+  - ucrt >=10.0.20348.0
+  - vc >=14.3,<15
+  - vc14_runtime >=14.44.35208
+  license: Zlib
+  license_family: Other
+  size: 111682
+  timestamp: 1761842670565
+- conda: https://conda.anaconda.org/conda-forge/linux-64/zstandard-0.25.0-py314h0f05182_1.conda
+  sha256: e589f694b44084f2e04928cabd5dda46f20544a512be2bdb0d067d498e4ac8d0
+  md5: 2930a6e1c7b3bc5f66172e324a8f5fc3
+  depends:
+  - python
+  - cffi >=1.11
   - zstd >=1.5.7,<1.5.8.0a0
+  - __glibc >=2.17,<3.0.a0
+  - libgcc >=14
   - zstd >=1.5.7,<1.6.0a0
+  - python_abi 3.14.* *_cp314
   license: BSD-3-Clause
-  size: 428554
-  timestamp: 1756841112889
-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/zstandard-0.24.0-py313hff09f02_1.conda
-  sha256: 5e5a6f0fb2d1c08a72918b5d2d97dff2692327b772f48445d27e440d1ef69a6a
-  md5: 43b6a7c0b0ae0baa7937a769b74ca2f6
+  size: 473605
+  timestamp: 1762512687493
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/zstandard-0.25.0-py314h9d33bd4_1.conda
+  sha256: cdeb350914094e15ec6310f4699fa81120700ca7ab7162a6b3421f9ea9c690b4
+  md5: 8a92a736ab23b4633ac49dcbfcc81e14
   depends:
-  - __osx >=11.0
+  - python
   - cffi >=1.11
-  - python >=3.13,<3.14.0a0
-  - python >=3.13,<3.14.0a0 *_cp313
-  - python_abi 3.13.* *_cp313
   - zstd >=1.5.7,<1.5.8.0a0
+  - python 3.14.* *_cp314
+  - __osx >=11.0
+  - python_abi 3.14.* *_cp314
   - zstd >=1.5.7,<1.6.0a0
   license: BSD-3-Clause
-  size: 349620
-  timestamp: 1756841373649
-- conda: https://conda.anaconda.org/conda-forge/win-64/zstandard-0.24.0-py313hcdcf24b_1.conda
-  sha256: 4a2f488f8df9b19c14f7b66b55431146d18f8070bd722f1760713e28a0c3e9ec
-  md5: b35c9d56c92c2d3846908b87e4d40ede
+  size: 397786
+  timestamp: 1762512730914
+- conda: https://conda.anaconda.org/conda-forge/win-64/zstandard-0.25.0-py314hc5dbbe4_1.conda
+  sha256: 87bf6ba2dcc59dfbb8d977b9c29d19b6845ad54e092ea8204dcec62d7b461a30
+  md5: c1ef46c3666be935fbb7460c24950cff
   depends:
+  - python
   - cffi >=1.11
-  - python >=3.13,<3.14.0a0
-  - python_abi 3.13.* *_cp313
+  - zstd >=1.5.7,<1.5.8.0a0
+  - vc >=14.3,<15
+  - vc14_runtime >=14.44.35208
   - ucrt >=10.0.20348.0
   - vc >=14.3,<15
   - vc14_runtime >=14.44.35208
-  - zstd >=1.5.7,<1.5.8.0a0
+  - ucrt >=10.0.20348.0
   - zstd >=1.5.7,<1.6.0a0
+  - python_abi 3.14.* *_cp314
   license: BSD-3-Clause
-  size: 351525
-  timestamp: 1756841550515
+  size: 381179
+  timestamp: 1762512709971
 - conda: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.7-hb8e6e7a_2.conda
   sha256: a4166e3d8ff4e35932510aaff7aa90772f84b4d07e9f6f83c614cba7ceefe0eb
   md5: 6432cb5d4ac0046c3ac0a8a0f95842f9
diff --git a/pixi.toml b/pixi.toml
index 2313959e..d247b2e2 100644
--- a/pixi.toml
+++ b/pixi.toml
@@ -1,10 +1,10 @@
-[project]
+[workspace]
 name = "tabmat"
 channels = ["conda-forge"]
 platforms = ["linux-64", "osx-arm64", "win-64"]
 
 [tasks]
-postinstall = "pip install --no-use-pep517 --no-build-isolation --no-deps --disable-pip-version-check -e ."
+postinstall = "pip install --no-build-isolation --no-deps --disable-pip-version-check -e ."
 
 [tasks.install-nightlies]
 cmd = """
@@ -79,7 +79,14 @@ inputs = [
 pre-commit-install = "pre-commit install"
 pre-commit-run = "pre-commit run -a"
 
-[build-dependencies]
+[dependencies]
+formulaic = ">=0.6.4"
+numpy = ">=1.24.0"
+pandas = ">=1.4.4"
+scipy = ">=1.7.3"
+narwhals = ">=1.4.1"
+
+# build dependencies
 c-compiler = "*"
 cxx-compiler = "*"
 cython = "*"
@@ -91,19 +98,12 @@ xsimd = "<11|>12.1"
 [target.unix.dependencies]
 jemalloc-local = "*"
 
-[host-dependencies]
-python = ">=3.9"
+# host dependencies
+python = ">=3.10"
 pip = "*"
 setuptools = "*"
 wheel = "*"
 
-[dependencies]
-formulaic = ">=0.6.4"
-numpy = ">=1.24.0"
-pandas = ">=1.4.4"
-scipy = ">=1.7.3"
-narwhals = ">=1.4.1"
-
 [feature.dev.dependencies]
 ipython = "*"
 ipykernel = "*"
@@ -140,8 +140,6 @@ blas = { build = "*mkl" }
 [feature.benchmark.target.linux-64.dependencies]
 blas = { build = "*mkl" }
 
-[feature.py39.dependencies]
-python = "3.9.*"
 [feature.py310.dependencies]
 python = "3.10.*"
 [feature.py311.dependencies]
@@ -150,10 +148,11 @@ python = "3.11.*"
 python = "3.12.*"
 [feature.py313.dependencies]
 python = "3.13.*"
+[feature.py314.dependencies]
+python = "3.14.*"
 
 [feature.oldies.dependencies]
-setuptools = "62.*"
-python = "=3.9.19"
+python = "=3.10"
 numpy = "=1.24.0"
 pandas = "=1.4.4"
 scipy = "=1.7.3"
@@ -164,11 +163,11 @@ narwhals = "=1.4.1"
 default = ["dev", "test"]
 docs = ["docs"]
 benchmark = ["benchmark"]
-py39 = ["py39", "test"]
 py310 = ["py310", "test"]
 py311 = ["py311", "test"]
 py312 = ["py312", "test"]
 py313 = ["py313", "test"]
+py314 = ["py314", "test"]
 oldies = ["oldies", "test"]
 lint = { features = ["lint"], no-default-feature = true}
-nightly = ["py313", "test"]
+nightly = ["py314", "test"]
diff --git a/pyproject.toml b/pyproject.toml
index f9061e82..f5f06d70 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -10,7 +10,7 @@ requires = [
 
 [tool.ruff]
 line-length = 88
-target-version = "py39"
+target-version = "py310"
 
 [tool.ruff.lint]
 ignore = ["E731", "N802", "N803", "N806"]
@@ -31,7 +31,7 @@ select = [
 known-first-party = ["tabmat"]
 
 [tool.mypy]
-python_version = '3.9'
+python_version = '3.10'
 exclude = [
   "tests/",
 ]
@@ -49,6 +49,7 @@ skip = [
   "cp36*",
   "cp37*",
   "cp38*",
+  "cp39*",
 ]
 test-requires = ["pytest", "pytest-xdist"]
 test-command = "pytest {package}/tests/test_matrices.py"
diff --git a/setup.py b/setup.py
index 0661e4df..00b9d168 100644
--- a/setup.py
+++ b/setup.py
@@ -141,7 +141,6 @@
 setup(
     name="tabmat",
     use_scm_version={"version_scheme": "post-release"},
-    setup_requires=["setuptools_scm"],
     description="Efficient matrix representations for working with tabular data.",
     long_description=long_description,
     long_description_content_type="text/markdown",
@@ -150,16 +149,16 @@
     author_email="noreply@quantco.com",
     classifiers=[  # Optional
         "Programming Language :: Python :: 3",
-        "Programming Language :: Python :: 3.9",
         "Programming Language :: Python :: 3.10",
         "Programming Language :: Python :: 3.11",
         "Programming Language :: Python :: 3.12",
         "Programming Language :: Python :: 3.13",
+        "Programming Language :: Python :: 3.14",
     ],
     package_dir={"": "src"},
     packages=find_packages(where="src"),
     install_requires=["formulaic>=0.6", "narwhals", "numpy", "scipy"],
-    python_requires=">=3.9",
+    python_requires=">=3.10",
     ext_modules=cythonize(
         ext_modules,
         annotate=False,
diff --git a/src/tabmat/benchmark/generate_matrices.py b/src/tabmat/benchmark/generate_matrices.py
index e5e770fe..47e12cd0 100644
--- a/src/tabmat/benchmark/generate_matrices.py
+++ b/src/tabmat/benchmark/generate_matrices.py
@@ -13,7 +13,7 @@ def make_dense_matrices(n_rows: int, n_cols: int) -> dict:
     dense_matrices = {"numpy_C": np.random.random((n_rows, n_cols))}
     dense_matrices["numpy_F"] = dense_matrices["numpy_C"].copy(order="F")
     assert dense_matrices["numpy_F"].flags["F_CONTIGUOUS"]
-    dense_matrices["tabmat"] = tm.DenseMatrix(dense_matrices["numpy_C"])
+    dense_matrices["tabmat"] = tm.DenseMatrix(dense_matrices["numpy_C"])  # type: ignore
     return dense_matrices
 
 
diff --git a/src/tabmat/benchmark/main.py b/src/tabmat/benchmark/main.py
index 3f6656bd..c0436f02 100644
--- a/src/tabmat/benchmark/main.py
+++ b/src/tabmat/benchmark/main.py
@@ -1,6 +1,5 @@
 import pickle
 import time
-from typing import Union
 
 import click
 import numpy as np
@@ -21,7 +20,7 @@
 from tabmat.benchmark.memory_tools import track_peak_mem
 
 
-def _sandwich(mat: Union[tm.MatrixBase, np.ndarray, sps.csc_matrix], vec: np.ndarray):
+def _sandwich(mat: tm.MatrixBase | np.ndarray | sps.csc_matrix, vec: np.ndarray):
     if isinstance(mat, (tm.MatrixBase, tm.StandardizedMatrix)):
         mat.sandwich(vec)
     elif isinstance(mat, np.ndarray):
@@ -32,7 +31,7 @@ def _sandwich(mat: Union[tm.MatrixBase, np.ndarray, sps.csc_matrix], vec: np.nda
 
 
 def _transpose_matvec(
-    mat: Union[tm.MatrixBase, np.ndarray, sps.csc_matrix], vec: np.ndarray
+    mat: tm.MatrixBase | np.ndarray | sps.csc_matrix, vec: np.ndarray
 ):
     if isinstance(mat, (tm.MatrixBase, tm.StandardizedMatrix)):
         return mat.transpose_matvec(vec)
@@ -69,7 +68,7 @@ def get_op_names():
 
 def run_one_benchmark_set(
     matrices: dict[
-        str, Union[tm.MatrixBase, tm.StandardizedMatrix, np.ndarray, sps.spmatrix]
+        str, tm.MatrixBase | tm.StandardizedMatrix | np.ndarray | sps.spmatrix
     ],
     include_baseline: bool,
     name: str,
diff --git a/src/tabmat/categorical_matrix.py b/src/tabmat/categorical_matrix.py
index 26d47aee..263dc63f 100644
--- a/src/tabmat/categorical_matrix.py
+++ b/src/tabmat/categorical_matrix.py
@@ -165,7 +165,6 @@ def matvec(mat, vec):
 import importlib.util
 import re
 import warnings
-from typing import Optional, Union
 
 import narwhals.stable.v1 as nw
 import numpy as np
@@ -207,7 +206,7 @@ def matvec(mat, vec):
     pl = None  # type: ignore
 
 
-def _is_indexer_full_length(full_length: int, indexer: Union[slice, np.ndarray]):
+def _is_indexer_full_length(full_length: int, indexer: slice | np.ndarray):
     if isinstance(indexer, np.ndarray):
         if (indexer > full_length - 1).any():
             raise IndexError("Index out-of-range.")
@@ -285,9 +284,9 @@ def _extract_codes_and_categories(cat_vec) -> tuple[np.ndarray, np.ndarray]:
 
 
 def _row_col_indexing(
-    arr: Union[np.ndarray, sps.spmatrix],
-    rows: Optional[np.ndarray],
-    cols: Optional[np.ndarray],
+    arr: np.ndarray | sps.spmatrix,
+    rows: np.ndarray | None,
+    cols: np.ndarray | None,
 ) -> np.ndarray:
     if isinstance(rows, slice) and rows == slice(None, None, None):
         rows = None
@@ -298,7 +297,7 @@ def _row_col_indexing(
     is_col_indexed = not (cols is None or len(cols) == arr.shape[1])
 
     if is_row_indexed and is_col_indexed:
-        return arr[np.ix_(rows, cols)]
+        return arr[np.ix_(rows, cols)]  # type: ignore
     elif is_row_indexed:
         return arr[rows]
     elif is_col_indexed:
@@ -342,11 +341,11 @@ class CategoricalMatrix(MatrixBase):
     def __init__(
         self,
         cat_vec,
-        categories: Optional[np.ndarray] = None,
+        categories: np.ndarray | None = None,
         drop_first: bool = False,
         dtype: numpy.typing.DTypeLike = np.float64,
-        column_name: Optional[str] = None,
-        term_name: Optional[str] = None,
+        column_name: str | None = None,
+        term_name: str | None = None,
         column_name_format: str = "{name}[{category}]",
         cat_missing_method: str = "fail",
         cat_missing_name: str = "(MISSING)",
@@ -408,7 +407,7 @@ def __init__(
                 "When creating a CategoricalMatrix with indices and categories, "
                 "indices must be castable to a numpy int32 dtype."
             )
-        self.shape = (len(self.indices), len(self.categories) - int(drop_first))
+        self.shape = (len(self.indices), max(len(self.categories) - int(drop_first), 0))
         self.x_csc = None
         self.dtype = np.dtype(dtype)
 
@@ -462,9 +461,9 @@ def recover_orig(self) -> np.ndarray:
 
     def _matvec_setup(
         self,
-        other: Union[list, np.ndarray],
-        cols: Optional[np.ndarray] = None,
-    ) -> tuple[np.ndarray, Optional[np.ndarray]]:
+        other: list | np.ndarray,
+        cols: np.ndarray | None = None,
+    ) -> tuple[np.ndarray, np.ndarray | None]:
         other = np.asarray(other)
         if other.ndim > 1:
             raise NotImplementedError(
@@ -485,9 +484,9 @@ def _matvec_setup(
 
     def matvec(
         self,
-        other: Union[list, np.ndarray],
-        cols: Optional[np.ndarray] = None,
-        out: Optional[np.ndarray] = None,
+        other: list | np.ndarray,
+        cols: np.ndarray | None = None,
+        out: np.ndarray | None = None,
     ) -> np.ndarray:
         """
         Multiply self with vector 'other', and add vector 'out' if it is present.
@@ -533,10 +532,10 @@ def matvec(
 
     def transpose_matvec(
         self,
-        vec: Union[np.ndarray, list],
-        rows: Optional[np.ndarray] = None,
-        cols: Optional[np.ndarray] = None,
-        out: Optional[np.ndarray] = None,
+        vec: np.ndarray | list,
+        rows: np.ndarray | None = None,
+        cols: np.ndarray | None = None,
+        out: np.ndarray | None = None,
     ) -> np.ndarray:
         """
 
@@ -608,9 +607,9 @@ def transpose_matvec(
 
     def sandwich(
         self,
-        d: Union[np.ndarray, list],
-        rows: Optional[np.ndarray] = None,
-        cols: Optional[np.ndarray] = None,
+        d: np.ndarray | list,
+        rows: np.ndarray | None = None,
+        cols: np.ndarray | None = None,
     ) -> sps.dia_matrix:
         """
         Perform a sandwich product: X.T @ diag(d) @ X.
@@ -647,9 +646,9 @@ def _cross_sandwich(
         self,
         other: MatrixBase,
         d: np.ndarray,
-        rows: Optional[np.ndarray] = None,
-        L_cols: Optional[np.ndarray] = None,
-        R_cols: Optional[np.ndarray] = None,
+        rows: np.ndarray | None = None,
+        L_cols: np.ndarray | None = None,
+        R_cols: np.ndarray | None = None,
     ) -> np.ndarray:
         """Perform a sandwich product: X.T @ diag(d) @ Y."""
         if isinstance(other, DenseMatrix):
@@ -751,9 +750,9 @@ def _cross_dense(
         self,
         other: np.ndarray,
         d: np.ndarray,
-        rows: Optional[np.ndarray],
-        L_cols: Optional[np.ndarray],
-        R_cols: Optional[np.ndarray],
+        rows: np.ndarray | None,
+        L_cols: np.ndarray | None,
+        R_cols: np.ndarray | None,
     ) -> np.ndarray:
         if other.flags["C_CONTIGUOUS"]:
             is_c_contiguous = True
@@ -785,9 +784,9 @@ def _cross_categorical(
         self,
         other,
         d: np.ndarray,
-        rows: Optional[np.ndarray],
-        L_cols: Optional[np.ndarray],
-        R_cols: Optional[np.ndarray],
+        rows: np.ndarray | None,
+        L_cols: np.ndarray | None,
+        R_cols: np.ndarray | None,
     ) -> np.ndarray:
         if not isinstance(other, CategoricalMatrix):
             raise TypeError
@@ -817,9 +816,9 @@ def _cross_sparse(
         self,
         other: sps.csc_matrix,
         d: np.ndarray,
-        rows: Optional[np.ndarray],
-        L_cols: Optional[np.ndarray],
-        R_cols: Optional[np.ndarray],
+        rows: np.ndarray | None,
+        L_cols: np.ndarray | None,
+        R_cols: np.ndarray | None,
     ) -> np.ndarray:
         term_1 = self.multiply(d)  # multiply will deal with drop_first
 
@@ -872,9 +871,9 @@ def __repr__(self):
     def get_names(
         self,
         type: str = "column",
-        missing_prefix: Optional[str] = None,
-        indices: Optional[list[int]] = None,
-    ) -> list[Optional[str]]:
+        missing_prefix: str | None = None,
+        indices: list[int] | None = None,
+    ) -> list[str | None]:
         """Get column names.
 
         For columns that do not have a name, a default name is created using the
@@ -922,7 +921,7 @@ def get_names(
         else:
             return [name] * (len(self.categories) - self.drop_first)
 
-    def set_names(self, names: Union[str, list[Optional[str]]], type: str = "column"):
+    def set_names(self, names: str | list[str | None], type: str = "column"):
         """Set column names.
 
         Parameters
diff --git a/src/tabmat/constructor.py b/src/tabmat/constructor.py
index a605c99a..cb551ec9 100644
--- a/src/tabmat/constructor.py
+++ b/src/tabmat/constructor.py
@@ -1,7 +1,7 @@
 import sys
 import warnings
 from collections.abc import Mapping
-from typing import Any, Optional, Union
+from typing import Any
 
 import narwhals.stable.v1 as nw
 import numpy as np
@@ -79,7 +79,7 @@ def from_df(
     -------
     SplitMatrix
     """
-    matrices: list[Union[DenseMatrix, SparseMatrix, CategoricalMatrix]] = []
+    matrices: list[DenseMatrix | SparseMatrix | CategoricalMatrix] = []
     indices: list[np.ndarray] = []
     is_cat: list[bool] = []
 
@@ -303,10 +303,10 @@ def from_csc(mat: sps.csc_matrix, threshold=0.1, column_names=None, term_names=N
 
 
 def from_formula(
-    formula: Union[str, Formula],
+    formula: str | Formula,
     data,
     ensure_full_rank: bool = False,
-    na_action: Union[str, NAAction] = NAAction.IGNORE,
+    na_action: str | NAAction = NAAction.IGNORE,
     dtype: numpy.typing.DTypeLike = np.float64,
     sparse_threshold: float = 0.1,
     cat_threshold: int = 4,
@@ -317,7 +317,7 @@ def from_formula(
     intercept_name: str = "Intercept",
     include_intercept: bool = False,
     add_column_for_intercept: bool = True,
-    context: Optional[Union[int, Mapping[str, Any]]] = None,
+    context: int | Mapping[str, Any] | None = None,
 ) -> SplitMatrix:
     """
     Transform a pandas data frame to a SplitMatrix using a Wilkinson formula.
diff --git a/src/tabmat/constructor_util.py b/src/tabmat/constructor_util.py
index 772baeb0..0b1ad619 100644
--- a/src/tabmat/constructor_util.py
+++ b/src/tabmat/constructor_util.py
@@ -1,5 +1,4 @@
 from collections.abc import Sequence
-from typing import Optional
 
 import numpy as np
 import scipy.sparse as sps
@@ -11,8 +10,8 @@
 def _split_sparse_and_dense_parts(
     arg1: sps.csc_matrix,
     threshold: float = 0.1,
-    column_names: Optional[Sequence[Optional[str]]] = None,
-    term_names: Optional[Sequence[Optional[str]]] = None,
+    column_names: Sequence[str | None] | None = None,
+    term_names: Sequence[str | None] | None = None,
 ) -> tuple[DenseMatrix, SparseMatrix, np.ndarray, np.ndarray]:
     """
     Split matrix.
diff --git a/src/tabmat/dense_matrix.py b/src/tabmat/dense_matrix.py
index 907230e6..3c564519 100644
--- a/src/tabmat/dense_matrix.py
+++ b/src/tabmat/dense_matrix.py
@@ -1,5 +1,4 @@
 import textwrap
-from typing import Optional, Union
 
 import numpy as np
 
@@ -139,8 +138,8 @@ def unpack(self):
     def sandwich(
         self,
         d: np.ndarray,
-        rows: Optional[np.ndarray] = None,
-        cols: Optional[np.ndarray] = None,
+        rows: np.ndarray | None = None,
+        cols: np.ndarray | None = None,
     ) -> np.ndarray:
         """Perform a sandwich product: X.T @ diag(d) @ X."""
         d = np.asarray(d)
@@ -152,9 +151,9 @@ def _cross_sandwich(
         self,
         other: MatrixBase,
         d: np.ndarray,
-        rows: Optional[np.ndarray] = None,
-        L_cols: Optional[np.ndarray] = None,
-        R_cols: Optional[np.ndarray] = None,
+        rows: np.ndarray | None = None,
+        L_cols: np.ndarray | None = None,
+        R_cols: np.ndarray | None = None,
     ):
         from .categorical_matrix import CategoricalMatrix
         from .sparse_matrix import SparseMatrix
@@ -174,10 +173,10 @@ def _get_col_stds(self, weights: np.ndarray, col_means: np.ndarray) -> np.ndarra
 
     def _matvec_helper(
         self,
-        vec: Union[list, np.ndarray],
-        rows: Optional[np.ndarray],
-        cols: Optional[np.ndarray],
-        out: Optional[np.ndarray],
+        vec: list | np.ndarray,
+        rows: np.ndarray | None,
+        cols: np.ndarray | None,
+        out: np.ndarray | None,
         transpose: bool,
     ):
         # Because the dense_rmatvec takes a row array and col array, it has
@@ -223,10 +222,10 @@ def _matvec_helper(
 
     def transpose_matvec(
         self,
-        vec: Union[np.ndarray, list],
-        rows: Optional[np.ndarray] = None,
-        cols: Optional[np.ndarray] = None,
-        out: Optional[np.ndarray] = None,
+        vec: np.ndarray | list,
+        rows: np.ndarray | None = None,
+        cols: np.ndarray | None = None,
+        out: np.ndarray | None = None,
     ) -> np.ndarray:
         """Perform: self[rows, cols].T @ vec[rows]."""
         check_transpose_matvec_out_shape(self, out)
@@ -234,9 +233,9 @@ def transpose_matvec(
 
     def matvec(
         self,
-        vec: Union[np.ndarray, list],
-        cols: Optional[np.ndarray] = None,
-        out: Optional[np.ndarray] = None,
+        vec: np.ndarray | list,
+        cols: np.ndarray | None = None,
+        out: np.ndarray | None = None,
     ) -> np.ndarray:
         """Perform self[:, cols] @ other[cols]."""
         check_matvec_out_shape(self, out)
@@ -262,9 +261,9 @@ def multiply(self, other):
     def get_names(
         self,
         type: str = "column",
-        missing_prefix: Optional[str] = None,
-        indices: Optional[list[int]] = None,
-    ) -> list[Optional[str]]:
+        missing_prefix: str | None = None,
+        indices: list[int] | None = None,
+    ) -> list[str | None]:
         """Get column names.
 
         For columns that do not have a name, a default name is created using the
@@ -306,7 +305,7 @@ def get_names(
 
         return names.tolist()
 
-    def set_names(self, names: Union[str, list[Optional[str]]], type: str = "column"):
+    def set_names(self, names: str | list[str | None], type: str = "column"):
         """Set column names.
 
         Parameters
diff --git a/src/tabmat/ext/cat_split_helpers-tmpl.cpp b/src/tabmat/ext/cat_split_helpers-tmpl.cpp
index df7a21c6..af5793cc 100644
--- a/src/tabmat/ext/cat_split_helpers-tmpl.cpp
+++ b/src/tabmat/ext/cat_split_helpers-tmpl.cpp
@@ -5,7 +5,7 @@
 template <typename Int, typename F>
 void _transpose_matvec_${type}(
     Int n_rows,
-    Int* indices,
+    const Int* indices,
     F* other,
     F* res,
     Int res_size
diff --git a/src/tabmat/ext/categorical.pyx b/src/tabmat/ext/categorical.pyx
index be97844b..5852fc0e 100644
--- a/src/tabmat/ext/categorical.pyx
+++ b/src/tabmat/ext/categorical.pyx
@@ -16,12 +16,12 @@ ctypedef fused win_numeric:
     long long
 
 cdef extern from "cat_split_helpers.cpp":
-    void _transpose_matvec_all_rows_fast[Int, F](Int, Int*, F*, F*, Int)
-    void _transpose_matvec_all_rows_complex[Int, F](Int, Int*, F*, F*, Int, bool)
+    void _transpose_matvec_all_rows_fast[Int, F](Int, const int*, F*, F*, Int)
+    void _transpose_matvec_all_rows_complex[Int, F](Int, const int*, F*, F*, Int, bool)
 
 
 def transpose_matvec_fast(
-    int[:] indices,
+    const int[:] indices,
     floating[:] other,
     int n_cols,
     dtype,
@@ -68,7 +68,7 @@ def transpose_matvec_fast(
 
 
 def transpose_matvec_complex(
-    int[:] indices,
+    const int[:] indices,
     floating[:] other,
     int n_cols,
     dtype,
diff --git a/src/tabmat/formula.py b/src/tabmat/formula.py
index 0f97af3a..342b96f6 100644
--- a/src/tabmat/formula.py
+++ b/src/tabmat/formula.py
@@ -3,7 +3,7 @@
 from abc import ABC, abstractmethod
 from collections import OrderedDict
 from collections.abc import Iterable
-from typing import Any, Optional, Union
+from typing import Any
 
 import numpy as np
 import numpy.typing
@@ -301,7 +301,7 @@ class _InteractableVector(ABC):
     wrappers over numpy arrays, scipy sparse matrices and pandas categoricals.
     """
 
-    name: Optional[str]
+    name: str | None
 
     @abstractmethod
     def to_tabmat(
@@ -346,7 +346,7 @@ def set_name(self, name, name_format):
 
 
 class _InteractableDenseVector(_InteractableVector):
-    def __init__(self, values: np.ndarray, name: Optional[str] = None):
+    def __init__(self, values: np.ndarray, name: str | None = None):
         self.values = values
         self.name = name
 
@@ -362,7 +362,7 @@ def to_tabmat(
         dtype: numpy.typing.DTypeLike = np.float64,
         sparse_threshold: float = 0.1,
         cat_threshold: int = 4,
-    ) -> Union[SparseMatrix, DenseMatrix]:
+    ) -> SparseMatrix | DenseMatrix:
         if (self.values != 0).mean() > sparse_threshold:
             return DenseMatrix(self.values, column_names=[self.name])
         else:
@@ -382,7 +382,7 @@ def set_name(self, name, name_format=None) -> "_InteractableDenseVector":
 
 
 class _InteractableSparseVector(_InteractableVector):
-    def __init__(self, values: sps.csc_matrix, name: Optional[str] = None):
+    def __init__(self, values: sps.csc_matrix, name: str | None = None):
         self.values = values
         self.name = name
 
@@ -417,7 +417,7 @@ def __init__(
         codes: np.ndarray,
         categories: list[str],
         multipliers: np.ndarray,
-        name: Optional[str] = None,
+        name: str | None = None,
     ):
         # sentinel values for codes:
         # -1: missing
@@ -475,7 +475,7 @@ def to_tabmat(
         dtype: numpy.typing.DTypeLike = np.float64,
         sparse_threshold: float = 0.1,
         cat_threshold: int = 4,
-    ) -> Union[CategoricalMatrix, SparseMatrix, SplitMatrix]:
+    ) -> CategoricalMatrix | SparseMatrix | SplitMatrix:
         codes = self.codes.copy()
         categories = self.categories.copy()
         if -2 in self.codes:
@@ -673,7 +673,7 @@ def _interact_categoricals(
 def _C(
     data,
     *,
-    levels: Optional[Iterable[str]] = None,
+    levels: Iterable[str] | None = None,
     missing_method: str = "fail",
     missing_name: str = "(MISSING)",
     spans_intercept: bool = True,
@@ -717,7 +717,7 @@ def encoder(
 def encode_contrasts(
     data,
     *,
-    levels: Optional[Iterable[str]] = None,
+    levels: Iterable[str] | None = None,
     missing_method: str = "fail",
     missing_name: str = "(MISSING)",
     reduced_rank: bool = False,
diff --git a/src/tabmat/matrix_base.py b/src/tabmat/matrix_base.py
index 3670a08c..beb466b5 100644
--- a/src/tabmat/matrix_base.py
+++ b/src/tabmat/matrix_base.py
@@ -1,5 +1,5 @@
 from abc import ABC, abstractmethod
-from typing import Any, Optional, Union
+from typing import Any
 
 import numpy as np
 
@@ -13,7 +13,7 @@ class MatrixBase(ABC):
 
     @abstractmethod
     def matvec(
-        self, other, cols: Optional[np.ndarray] = None, out: Optional[np.ndarray] = None
+        self, other, cols: np.ndarray | None = None, out: np.ndarray | None = None
     ):
         """
         Perform: self[:, cols] @ other[cols], so result[i] = sum_j self[i, j] other[j].
@@ -33,10 +33,10 @@ def matvec(
     @abstractmethod
     def transpose_matvec(
         self,
-        vec: Union[np.ndarray, list],
-        rows: Optional[np.ndarray] = None,
-        cols: Optional[np.ndarray] = None,
-        out: Optional[np.ndarray] = None,
+        vec: np.ndarray | list,
+        rows: np.ndarray | None = None,
+        cols: np.ndarray | None = None,
+        out: np.ndarray | None = None,
     ) -> np.ndarray:
         """
         Perform: self[rows, cols].T @ vec[rows], so result[i] = sum_j self[j, i] vec[j].
@@ -65,8 +65,8 @@ def transpose_matvec(
     def sandwich(
         self,
         d: np.ndarray,
-        rows: Optional[np.ndarray] = None,
-        cols: Optional[np.ndarray] = None,
+        rows: np.ndarray | None = None,
+        cols: np.ndarray | None = None,
     ) -> np.ndarray:
         """
         Perform a sandwich product: (self[rows, cols].T * d[rows]) @ self[rows, cols].
@@ -94,7 +94,7 @@ def toarray(self) -> np.ndarray:  # noqa D102
         """Convert self into an np.ndarray."""
         pass
 
-    def __rmatmul__(self, other: Union[np.ndarray, list]) -> np.ndarray:
+    def __rmatmul__(self, other: np.ndarray | list) -> np.ndarray:
         """
         Perform other @ X = (X.T @ other.T).T = X.transpose_matvec(other.T).T.
 
@@ -127,7 +127,7 @@ def _get_col_stds(  # noqa D102
 
     def standardize(
         self, weights: np.ndarray, center_predictors: bool, scale_predictors: bool
-    ) -> tuple[Any, np.ndarray, Optional[np.ndarray]]:
+    ) -> tuple[Any, np.ndarray, np.ndarray | None]:
         """
         Return a StandardizedMatrix along with the column means and column standard
         deviations.
@@ -174,9 +174,9 @@ def __getitem__(self, item):
     def get_names(
         self,
         type: str = "column",
-        missing_prefix: Optional[str] = None,
-        indices: Optional[list[int]] = None,
-    ) -> list[Optional[str]]:
+        missing_prefix: str | None = None,
+        indices: list[int] | None = None,
+    ) -> list[str | None]:
         """Get column names.
 
         For columns that do not have a name, a default name is created using the
@@ -204,7 +204,7 @@ def get_names(
         """
         pass
 
-    def set_names(self, names: Union[str, list[Optional[str]]], type: str = "column"):
+    def set_names(self, names: str | list[str | None], type: str = "column"):
         """Set column names.
 
         Parameters
@@ -225,7 +225,7 @@ def column_names(self):
         return self.get_names(type="column")
 
     @column_names.setter
-    def column_names(self, names: list[Optional[str]]):
+    def column_names(self, names: list[str | None]):
         self.set_names(names, type="column")
 
     @property
@@ -237,7 +237,7 @@ def term_names(self):
         return self.get_names(type="term")
 
     @term_names.setter
-    def term_names(self, names: list[Optional[str]]):
+    def term_names(self, names: list[str | None]):
         self.set_names(names, type="term")
 
     # Higher priority than numpy arrays, so behavior for funcs like "@" defaults to the
diff --git a/src/tabmat/sparse_matrix.py b/src/tabmat/sparse_matrix.py
index 324c2be4..d319c166 100644
--- a/src/tabmat/sparse_matrix.py
+++ b/src/tabmat/sparse_matrix.py
@@ -1,5 +1,3 @@
-from typing import Optional, Union
-
 import numpy as np
 from scipy import sparse as sps
 
@@ -175,8 +173,8 @@ def dot(self, other):
     def sandwich(
         self,
         d: np.ndarray,
-        rows: Optional[np.ndarray] = None,
-        cols: Optional[np.ndarray] = None,
+        rows: np.ndarray | None = None,
+        cols: np.ndarray | None = None,
     ) -> np.ndarray:
         """Perform a sandwich product: X.T @ diag(d) @ X."""
         d = np.asarray(d)
@@ -188,9 +186,9 @@ def _cross_sandwich(
         self,
         other: MatrixBase,
         d: np.ndarray,
-        rows: Optional[np.ndarray],
-        L_cols: Optional[np.ndarray] = None,
-        R_cols: Optional[np.ndarray] = None,
+        rows: np.ndarray | None,
+        L_cols: np.ndarray | None = None,
+        R_cols: np.ndarray | None = None,
     ):
         """Perform a sandwich product: X.T @ diag(d) @ Y."""
         from .categorical_matrix import CategoricalMatrix
@@ -207,9 +205,9 @@ def sandwich_dense(
         self,
         B: np.ndarray,
         d: np.ndarray,
-        rows: Optional[np.ndarray],
-        L_cols: Optional[np.ndarray],
-        R_cols: Optional[np.ndarray],
+        rows: np.ndarray | None,
+        L_cols: np.ndarray | None,
+        R_cols: np.ndarray | None,
     ) -> np.ndarray:
         """Perform a sandwich product: self.T @ diag(d) @ B."""
         if not hasattr(d, "dtype"):
@@ -230,10 +228,10 @@ def sandwich_dense(
 
     def _matvec_helper(
         self,
-        vec: Union[list, np.ndarray],
-        rows: Optional[np.ndarray],
-        cols: Optional[np.ndarray],
-        out: Optional[np.ndarray],
+        vec: list | np.ndarray,
+        rows: np.ndarray | None,
+        cols: np.ndarray | None,
+        out: np.ndarray | None,
         transpose: bool,
     ):
         vec = np.asarray(vec)
@@ -275,7 +273,7 @@ def _matvec_helper(
         return out
 
     def matvec(
-        self, vec, cols: Optional[np.ndarray] = None, out: Optional[np.ndarray] = None
+        self, vec, cols: np.ndarray | None = None, out: np.ndarray | None = None
     ):
         """Perform self[:, cols] @ other[cols]."""
         check_matvec_out_shape(self, out)
@@ -283,10 +281,10 @@ def matvec(
 
     def transpose_matvec(
         self,
-        vec: Union[np.ndarray, list],
-        rows: Optional[np.ndarray] = None,
-        cols: Optional[np.ndarray] = None,
-        out: Optional[np.ndarray] = None,
+        vec: np.ndarray | list,
+        rows: np.ndarray | None = None,
+        cols: np.ndarray | None = None,
+        out: np.ndarray | None = None,
     ) -> np.ndarray:
         """Perform: self[rows, cols].T @ vec[rows]."""
         check_transpose_matvec_out_shape(self, out)
@@ -336,9 +334,9 @@ def multiply(self, other):
     def get_names(
         self,
         type: str = "column",
-        missing_prefix: Optional[str] = None,
-        indices: Optional[list[int]] = None,
-    ) -> list[Optional[str]]:
+        missing_prefix: str | None = None,
+        indices: list[int] | None = None,
+    ) -> list[str | None]:
         """Get column names.
 
         For columns that do not have a name, a default name is created using the
@@ -380,7 +378,7 @@ def get_names(
 
         return names.tolist()
 
-    def set_names(self, names: Union[str, list[Optional[str]]], type: str = "column"):
+    def set_names(self, names: str | list[str | None], type: str = "column"):
         """Set column names.
 
         Parameters
diff --git a/src/tabmat/split_matrix.py b/src/tabmat/split_matrix.py
index bac1ace3..b1395620 100644
--- a/src/tabmat/split_matrix.py
+++ b/src/tabmat/split_matrix.py
@@ -1,6 +1,5 @@
 import warnings
 from collections.abc import Sequence
-from typing import Optional, Union
 
 import numpy as np
 from scipy import sparse as sps
@@ -19,7 +18,7 @@
 )
 
 
-def as_tabmat(a: Union[MatrixBase, StandardizedMatrix, np.ndarray, sps.spmatrix]):
+def as_tabmat(a: MatrixBase | StandardizedMatrix | np.ndarray | sps.spmatrix):
     """Convert an array to a corresponding MatrixBase type.
 
     If the input is already a MatrixBase, return untouched.
@@ -37,7 +36,7 @@ def as_tabmat(a: Union[MatrixBase, StandardizedMatrix, np.ndarray, sps.spmatrix]
         raise ValueError(f"Cannot convert type {type(a)} to Matrix.")
 
 
-def hstack(tup: Sequence[Union[MatrixBase, np.ndarray, sps.spmatrix]]) -> MatrixBase:
+def hstack(tup: Sequence[MatrixBase | np.ndarray | sps.spmatrix]) -> MatrixBase:
     """Stack arrays in sequence horizontally (column wise).
 
     This is equivalent to concatenation along the second axis,
@@ -61,7 +60,7 @@ def hstack(tup: Sequence[Union[MatrixBase, np.ndarray, sps.spmatrix]]) -> Matrix
         return SplitMatrix(matrices)
 
 
-def _prepare_out_array(out: Optional[np.ndarray], out_shape, out_dtype) -> np.ndarray:
+def _prepare_out_array(out: np.ndarray | None, out_shape, out_dtype) -> np.ndarray:
     if out is None:
         out = np.zeros(out_shape, out_dtype)
     else:
@@ -171,7 +170,7 @@ class SplitMatrix(MatrixBase):
     def __init__(
         self,
         matrices: Sequence[MatrixBase],
-        indices: Optional[list[np.ndarray]] = None,
+        indices: list[np.ndarray] | None = None,
     ):
         flatten_matrices = []
         index_corrections = []
@@ -267,8 +266,8 @@ def __init__(
         assert self.shape[1] > 0
 
     def _split_col_subsets(
-        self, cols: Optional[np.ndarray]
-    ) -> tuple[list[np.ndarray], Union[list[np.ndarray], list[None]], int]:
+        self, cols: np.ndarray | None
+    ) -> tuple[list[np.ndarray], list[np.ndarray] | list[None], int]:
         """
         Return tuple of things helpful for applying column restrictions to sub-matrices.
 
@@ -311,7 +310,7 @@ def toarray(self) -> np.ndarray:
             out[:, idx] = mat.toarray()
         return out
 
-    def getcol(self, i: int) -> Union[np.ndarray, sps.csr_matrix]:
+    def getcol(self, i: int) -> np.ndarray | sps.csr_matrix:
         """Return matrix column at specified index."""
         # wrap-around indexing
         i %= self.shape[1]
@@ -323,9 +322,9 @@ def getcol(self, i: int) -> Union[np.ndarray, sps.csr_matrix]:
 
     def sandwich(
         self,
-        d: Union[np.ndarray, list],
-        rows: Optional[np.ndarray] = None,
-        cols: Optional[np.ndarray] = None,
+        d: np.ndarray | list,
+        rows: np.ndarray | None = None,
+        cols: np.ndarray | None = None,
     ) -> np.ndarray:
         """Perform a sandwich product: X.T @ diag(d) @ X."""
         d = np.asarray(d)
@@ -373,8 +372,8 @@ def _get_col_stds(self, weights: np.ndarray, col_means: np.ndarray) -> np.ndarra
     def matvec(
         self,
         v: np.ndarray,
-        cols: Optional[np.ndarray] = None,
-        out: Optional[np.ndarray] = None,
+        cols: np.ndarray | None = None,
+        out: np.ndarray | None = None,
     ) -> np.ndarray:
         """Perform self[:, cols] @ other[cols]."""
         assert not isinstance(v, sps.spmatrix)
@@ -398,7 +397,7 @@ def matvec(
         # as the target for storing the final output. This reduces the number
         # of output arrays allocated from 2 to 1.
         is_matrix_dense = [isinstance(m, DenseMatrix) for m in self.matrices]
-        dense_matrix_idx: Union[int, np.intp]
+        dense_matrix_idx: int | np.intp
         if np.any(is_matrix_dense):
             dense_matrix_idx = np.argmax(is_matrix_dense)
             sub_cols = subset_cols[dense_matrix_idx]
@@ -421,10 +420,10 @@ def matvec(
 
     def transpose_matvec(
         self,
-        v: Union[np.ndarray, list],
-        rows: Optional[np.ndarray] = None,
-        cols: Optional[np.ndarray] = None,
-        out: Optional[np.ndarray] = None,
+        v: np.ndarray | list,
+        rows: np.ndarray | None = None,
+        cols: np.ndarray | None = None,
+        out: np.ndarray | None = None,
     ) -> np.ndarray:
         """
         Perform: self[rows, cols].T @ vec[rows].
@@ -499,9 +498,9 @@ def __repr__(self):
     def get_names(
         self,
         type: str = "column",
-        missing_prefix: Optional[str] = None,
-        indices: Optional[list[int]] = None,
-    ) -> list[Optional[str]]:
+        missing_prefix: str | None = None,
+        indices: list[int] | None = None,
+    ) -> list[str | None]:
         """Get column names.
 
         For columns that do not have a name, a default name is created using the
@@ -532,7 +531,7 @@ def get_names(
             names[idx] = mat.get_names(type, missing_prefix, idx)
         return names.tolist()
 
-    def set_names(self, names: Union[str, list[Optional[str]]], type: str = "column"):
+    def set_names(self, names: str | list[str | None], type: str = "column"):
         """Set column names.
 
         Parameters
diff --git a/src/tabmat/standardized_mat.py b/src/tabmat/standardized_mat.py
index 930279c3..2ed2bbea 100644
--- a/src/tabmat/standardized_mat.py
+++ b/src/tabmat/standardized_mat.py
@@ -1,5 +1,3 @@
-from typing import Optional, Union
-
 import numpy as np
 from scipy import sparse as sps
 
@@ -36,8 +34,8 @@ class StandardizedMatrix:
     def __init__(
         self,
         mat: MatrixBase,
-        shift: Union[np.ndarray, list],
-        mult: Optional[Union[np.ndarray, list]] = None,
+        shift: np.ndarray | list,
+        mult: np.ndarray | list | None = None,
     ):
         shift_arr = np.atleast_1d(np.squeeze(shift))
         expected_shape = (mat.shape[1],)
@@ -68,9 +66,9 @@ def __init__(
 
     def matvec(
         self,
-        other_mat: Union[np.ndarray, list],
-        cols: Optional[np.ndarray] = None,
-        out: Optional[np.ndarray] = None,
+        other_mat: np.ndarray | list,
+        cols: np.ndarray | None = None,
+        out: np.ndarray | None = None,
     ) -> np.ndarray:
         """
         Perform self[:, cols] @ other[cols].
@@ -123,8 +121,8 @@ def getcol(self, i: int):
     def sandwich(
         self,
         d: np.ndarray,
-        rows: Optional[np.ndarray] = None,
-        cols: Optional[np.ndarray] = None,
+        rows: np.ndarray | None = None,
+        cols: np.ndarray | None = None,
     ) -> np.ndarray:
         """Perform a sandwich product: X.T @ diag(d) @ X."""
         if not hasattr(d, "dtype"):
@@ -177,10 +175,10 @@ def unstandardize(self) -> MatrixBase:
 
     def transpose_matvec(
         self,
-        other: Union[np.ndarray, list],
-        rows: Optional[np.ndarray] = None,
-        cols: Optional[np.ndarray] = None,
-        out: Optional[np.ndarray] = None,
+        other: np.ndarray | list,
+        rows: np.ndarray | None = None,
+        cols: np.ndarray | None = None,
+        out: np.ndarray | None = None,
     ) -> np.ndarray:
         """
         Perform: self[rows, cols].T @ vec[rows].
@@ -229,7 +227,7 @@ def transpose_matvec(
             out[cols] += res
             return out
 
-    def __rmatmul__(self, other: Union[np.ndarray, list]) -> np.ndarray:
+    def __rmatmul__(self, other: np.ndarray | list) -> np.ndarray:
         """
         Return matrix multiplication with other.
 
@@ -311,9 +309,9 @@ def __repr__(self):
     def get_names(
         self,
         type: str = "column",
-        missing_prefix: Optional[str] = None,
-        indices: Optional[list[int]] = None,
-    ) -> list[Optional[str]]:
+        missing_prefix: str | None = None,
+        indices: list[int] | None = None,
+    ) -> list[str | None]:
         """Get column names.
 
         For columns that do not have a name, a default name is created using the
@@ -341,7 +339,7 @@ def get_names(
         """
         return self.mat.get_names(type, missing_prefix, indices)
 
-    def set_names(self, names: Union[str, list[Optional[str]]], type: str = "column"):
+    def set_names(self, names: str | list[str | None], type: str = "column"):
         """Set column names.
 
         Parameters
@@ -362,7 +360,7 @@ def column_names(self):
         return self.get_names(type="column")
 
     @column_names.setter
-    def column_names(self, names: list[Optional[str]]):
+    def column_names(self, names: list[str | None]):
         self.set_names(names, type="column")
 
     @property
@@ -374,5 +372,5 @@ def term_names(self):
         return self.get_names(type="term")
 
     @term_names.setter
-    def term_names(self, names: list[Optional[str]]):
+    def term_names(self, names: list[str | None]):
         self.set_names(names, type="term")
diff --git a/src/tabmat/util.py b/src/tabmat/util.py
index 58dcb093..a75cfd8f 100644
--- a/src/tabmat/util.py
+++ b/src/tabmat/util.py
@@ -1,10 +1,8 @@
-from typing import Optional
-
 import numpy as np
 
 
 def set_up_rows_or_cols(
-    arr: Optional[np.ndarray], length: int, dtype=np.int32
+    arr: np.ndarray | None, length: int, dtype=np.int32
 ) -> np.ndarray:
     """Set up rows or columns using input array and input length."""
     if arr is None:
@@ -14,8 +12,8 @@ def set_up_rows_or_cols(
 
 def setup_restrictions(
     shape: tuple[int, int],
-    rows: Optional[np.ndarray],
-    cols: Optional[np.ndarray],
+    rows: np.ndarray | None,
+    cols: np.ndarray | None,
     dtype=np.int32,
 ) -> tuple[np.ndarray, np.ndarray]:
     """Set up row and column restrictions."""
@@ -24,7 +22,7 @@ def setup_restrictions(
     return rows, cols
 
 
-def _check_out_shape(out: Optional[np.ndarray], expected_first_dim: int) -> None:
+def _check_out_shape(out: np.ndarray | None, expected_first_dim: int) -> None:
     if out is not None and out.shape[0] != expected_first_dim:
         raise ValueError(
             f"""The first dimension of 'out' must be {expected_first_dim}, but it is
@@ -32,12 +30,12 @@ def _check_out_shape(out: Optional[np.ndarray], expected_first_dim: int) -> None
         )
 
 
-def check_transpose_matvec_out_shape(mat, out: Optional[np.ndarray]) -> None:
+def check_transpose_matvec_out_shape(mat, out: np.ndarray | None) -> None:
     """Assert that the first dimension of the transpose_matvec output is correct."""
     _check_out_shape(out, mat.shape[1])
 
 
-def check_matvec_out_shape(mat, out: Optional[np.ndarray]) -> None:
+def check_matvec_out_shape(mat, out: np.ndarray | None) -> None:
     """Assert that the first dimension of the matvec output is correct."""
     _check_out_shape(out, mat.shape[0])
 
diff --git a/tests/test_categorical_matrix.py b/tests/test_categorical_matrix.py
index 556d298d..cf75490a 100644
--- a/tests/test_categorical_matrix.py
+++ b/tests/test_categorical_matrix.py
@@ -241,3 +241,8 @@ def test_polars_non_contiguous_codes():
 
     indices, categories = _extract_codes_and_categories(cat_series)
     np.testing.assert_array_equal(str_series, categories[indices].tolist())
+
+
+def test_shape_of_empty():
+    cat_mat = CategoricalMatrix([], drop_first=True)
+    assert cat_mat.shape == (0, 0)
diff --git a/tests/test_matrices.py b/tests/test_matrices.py
index a0da0b8e..6b431e35 100644
--- a/tests/test_matrices.py
+++ b/tests/test_matrices.py
@@ -1,5 +1,4 @@
 import warnings
-from typing import Optional, Union
 
 import numpy as np
 import pandas as pd
@@ -51,7 +50,7 @@ def categorical_matrix_drop_first():
 
 
 def get_unscaled_matrices() -> list[
-    Union[tm.DenseMatrix, tm.SparseMatrix, tm.CategoricalMatrix]
+    tm.DenseMatrix | tm.SparseMatrix | tm.CategoricalMatrix
 ]:
     return [
         dense_matrix_F(),
@@ -218,7 +217,7 @@ def test_sandwich_dtype_mismatch_raises(mat):
 
 @pytest.mark.parametrize("mat", get_matrices())
 @pytest.mark.parametrize("i", [1, -2])
-def test_getcol(mat: Union[tm.MatrixBase, tm.StandardizedMatrix], i):
+def test_getcol(mat: tm.MatrixBase | tm.StandardizedMatrix, i):
     col = mat.getcol(i)
 
     if not isinstance(col, np.ndarray):
@@ -260,7 +259,7 @@ def test_to_array_standardized_mat(mat: tm.StandardizedMatrix):
 @pytest.mark.parametrize("cols", [None, [], [1], np.array([1])])
 @pytest.mark.parametrize("other_shape", [[], [1], [2]])
 def test_matvec(
-    mat: Union[tm.MatrixBase, tm.StandardizedMatrix], other_type, cols, other_shape
+    mat: tm.MatrixBase | tm.StandardizedMatrix, other_type, cols, other_shape
 ):
     """
     Mat.
@@ -330,7 +329,7 @@ def process_mat_vec_subsets(mat, vec, mat_rows, mat_cols, vec_idxs):
 @pytest.mark.parametrize("rows", [None, [], [2], np.arange(2)])
 @pytest.mark.parametrize("cols", [None, [], [1], np.arange(1)])
 def test_transpose_matvec(
-    mat: Union[tm.MatrixBase, tm.StandardizedMatrix], other_type, rows, cols
+    mat: tm.MatrixBase | tm.StandardizedMatrix, other_type, rows, cols
 ):
     other_as_list = [3.0, -0.1, 0]
     other = other_type(other_as_list)
@@ -377,11 +376,11 @@ def test_transpose_matvec(
 @pytest.mark.parametrize("L_cols", [None, [1], np.arange(1)])
 @pytest.mark.parametrize("R_cols", [None, [1], np.arange(1)])
 def test_cross_sandwich(
-    mat_i: Union[tm.DenseMatrix, tm.SparseMatrix, tm.CategoricalMatrix],
-    mat_j: Union[tm.DenseMatrix, tm.SparseMatrix, tm.CategoricalMatrix],
-    rows: Optional[np.ndarray],
-    L_cols: Optional[np.ndarray],
-    R_cols: Optional[np.ndarray],
+    mat_i: tm.DenseMatrix | tm.SparseMatrix | tm.CategoricalMatrix,
+    mat_j: tm.DenseMatrix | tm.SparseMatrix | tm.CategoricalMatrix,
+    rows: np.ndarray | None,
+    L_cols: np.ndarray | None,
+    R_cols: np.ndarray | None,
 ):
     assert mat_i.shape[0] == mat_j.shape[0]
     d = np.random.random(mat_i.shape[0])
@@ -400,7 +399,7 @@ def test_cross_sandwich(
 @pytest.mark.parametrize("rows", [None, [], [1], np.arange(2)])
 @pytest.mark.parametrize("cols", [None, [], [0], np.arange(1)])
 def test_self_sandwich(
-    mat: Union[tm.MatrixBase, tm.StandardizedMatrix], vec_type, rows, cols
+    mat: tm.MatrixBase | tm.StandardizedMatrix, vec_type, rows, cols
 ):
     vec_as_list = [3, 0.1, 1]
     vec = vec_type(vec_as_list)
@@ -415,7 +414,7 @@ def test_self_sandwich(
 
 @pytest.mark.parametrize("rows", [None, [], [0], np.arange(2)])
 @pytest.mark.parametrize("cols", [None, [], [0], np.arange(1)])
-def test_split_sandwich(rows: Optional[np.ndarray], cols: Optional[np.ndarray]):
+def test_split_sandwich(rows: np.ndarray | None, cols: np.ndarray | None):
     mat = complex_split_matrix()
     d = np.random.random(mat.shape[0])
     result = mat.sandwich(d, rows=rows, cols=cols)
@@ -454,7 +453,7 @@ def test_transpose(mat):
     "vec_type",
     [lambda x: x, np.array],
 )
-def test_rmatmul(mat: Union[tm.MatrixBase, tm.StandardizedMatrix], vec_type):
+def test_rmatmul(mat: tm.MatrixBase | tm.StandardizedMatrix, vec_type):
     vec_as_list = [3.0, -0.1, 0]
     vec = vec_type(vec_as_list)
     res = mat.__rmatmul__(vec)
@@ -466,14 +465,14 @@ def test_rmatmul(mat: Union[tm.MatrixBase, tm.StandardizedMatrix], vec_type):
 
 
 @pytest.mark.parametrize("mat", get_matrices())
-def test_matvec_raises(mat: Union[tm.MatrixBase, tm.StandardizedMatrix]):
+def test_matvec_raises(mat: tm.MatrixBase | tm.StandardizedMatrix):
     with pytest.raises(ValueError):
         mat.matvec(np.ones(11))
 
 
 @pytest.mark.parametrize("mat", get_matrices())
 @pytest.mark.parametrize("dtype", [np.float64, np.float32])
-def test_astype(mat: Union[tm.MatrixBase, tm.StandardizedMatrix], dtype):
+def test_astype(mat: tm.MatrixBase | tm.StandardizedMatrix, dtype):
     new_mat = mat.astype(dtype)
     assert np.issubdtype(new_mat.dtype, dtype)
     vec = np.zeros(mat.shape[1], dtype=dtype)
@@ -570,7 +569,7 @@ def test_standardize(
 
 
 @pytest.mark.parametrize("mat", get_matrices())
-def test_indexing_int_row(mat: Union[tm.MatrixBase, tm.StandardizedMatrix]):
+def test_indexing_int_row(mat: tm.MatrixBase | tm.StandardizedMatrix):
     res = mat[0, :]
     if not isinstance(res, np.ndarray):
         res = res.toarray()
@@ -579,7 +578,7 @@ def test_indexing_int_row(mat: Union[tm.MatrixBase, tm.StandardizedMatrix]):
 
 
 @pytest.mark.parametrize("mat", get_matrices())
-def test_indexing_range_row(mat: Union[tm.MatrixBase, tm.StandardizedMatrix]):
+def test_indexing_range_row(mat: tm.MatrixBase | tm.StandardizedMatrix):
     res = mat[0:2, :]
     assert res.ndim == 2
     if not isinstance(res, np.ndarray):
diff --git a/tests/test_split_matrix.py b/tests/test_split_matrix.py
index da8d2452..f1360b98 100644
--- a/tests/test_split_matrix.py
+++ b/tests/test_split_matrix.py
@@ -1,5 +1,3 @@
-from typing import Optional, Union
-
 import numpy as np
 import pandas as pd
 import pytest
@@ -63,7 +61,7 @@ def split_mat() -> SplitMatrix:
 
 def get_split_with_cat_components(
     missing,
-) -> list[Union[tm.SparseMatrix, tm.DenseMatrix, tm.CategoricalMatrix]]:
+) -> list[tm.SparseMatrix | tm.DenseMatrix | tm.CategoricalMatrix]:
     n_rows = 10
     np.random.seed(0)
     dense_1 = tm.DenseMatrix(np.random.random((n_rows, 3)))
@@ -203,7 +201,7 @@ def test_split_col_subsets(mat: tm.SplitMatrix, cols):
     subset_cols_indices, subset_cols, n_cols = mat._split_col_subsets(cols)
     n_cols_correct = mat.shape[1] if cols is None else len(cols)
 
-    def _get_lengths(vec_list: list[Optional[np.ndarray]]):
+    def _get_lengths(vec_list: list[np.ndarray | None]):
         return (
             mat_.shape[1] if v is None else len(v)
             for v, mat_ in zip(vec_list, mat.matrices)
diff --git a/tests/test_transpose_matvec.py b/tests/test_transpose_matvec.py
new file mode 100644
index 00000000..ef8b3b06
--- /dev/null
+++ b/tests/test_transpose_matvec.py
@@ -0,0 +1,24 @@
+import narwhals as nw
+import numpy as np
+import pandas as pd
+
+import tabmat as tm
+
+
+def test_transpose_matvec_does_not_crash():
+    # With high n_categories CategoricalMatrix.indices is read-only.
+    # As a result, transpose_matvec method crashed with "buffer
+    # source array is read-only".
+
+    n = 797_586
+    n_categories = 58_059
+    categories = [f"cat[{i}]" for i in range(n_categories)]
+    indices = np.linspace(0, n_categories - 1, n).round().astype(int)
+    cat_vec = pd.Series(pd.Categorical.from_codes(indices, categories=categories))
+    cat_vec_nw = nw.from_native(cat_vec, allow_series=True)
+    weights = np.ones(n)
+    cat_matrix_tm = tm.CategoricalMatrix(cat_vec_nw)
+
+    result = cat_matrix_tm.transpose_matvec(weights)
+
+    assert result is not None