diff --git a/.github/workflows/asv.yml b/.github/workflows/asv.yml
new file mode 100644
index 0000000..8b7c348
--- /dev/null
+++ b/.github/workflows/asv.yml
@@ -0,0 +1,107 @@
+name: ASV benchmarks
+
+on:
+  push:
+    branches: ["main"]
+  pull_request:
+    branches: ["main"]
+
+jobs:
+  run-benchmarks:
+    name: Benchmark on ${{ matrix.os }}
+    runs-on: ${{ matrix.os }}
+    permissions:
+      contents: read
+    strategy:
+      fail-fast: false
+      matrix:
+        os: [ubuntu-latest, windows-latest, macos-latest, ubuntu-24.04-arm]
+
+    steps:
+      - uses: actions/checkout@v5
+        with:
+          fetch-depth: 0
+
+      - name: Set up main branch
+        run: |
+          git branch main origin/main
+
+      - uses: prefix-dev/setup-pixi@v0.9.0
+        with:
+          environments: dev
+          cache: true
+
+      - name: Run benchmarks
+        shell: bash
+        run: |
+          MACHINE=${{ matrix.os }} pixi run asv-build
+
+      - name: Upload benchmark results
+        uses: actions/upload-artifact@v4
+        with:
+          name: asv-results-${{ matrix.os }}
+          path: asv_benchmarks/results
+  
+  publish-report:
+    name: Build HTML report
+    runs-on: ubuntu-latest
+    needs: run-benchmarks
+    permissions:
+      contents: write
+
+    steps:
+      - uses: actions/checkout@v5
+        with:
+          fetch-depth: 0
+
+      - name: Set up main branch
+        run: |
+          git branch main origin/main
+
+      - name: Prepare previous ASV results
+        uses: actions/checkout@v5
+        continue-on-error: true
+        with:
+          ref: gh-pages
+          path: gh-pages
+      
+      - name: Copy previous results
+        run: |
+          mkdir -p asv_benchmarks/results
+          cp -r gh-pages/results/* asv_benchmarks/results/ 2>/dev/null || true
+
+      - name: Download all benchmark results
+        uses: actions/download-artifact@v5
+        with:
+          pattern: asv-results-*
+
+      - name: Merge new benchmark results
+        run: |
+          for d in asv-results-*; do
+            [ -d "$d" ] || continue
+            cp -r "$d"/* "asv_benchmarks/results/"
+          done
+
+      - uses: prefix-dev/setup-pixi@v0.9.0
+        with:
+          environments: dev
+          cache: true
+
+      - name: Generate HTML report
+        run: |
+          pixi run asv-publish
+      
+      - name: Copy results to publish directory
+        run: |
+          cp -r asv_benchmarks/results html/
+
+      - name: Deploy to GitHub Pages
+        uses: peaceiris/actions-gh-pages@v4
+        if: github.event_name == 'push'
+        with:
+          github_token: ${{ secrets.GITHUB_TOKEN }}
+          publish_dir: ./html
+          keep_files: true
+          user_name: 'github-actions[bot]'
+          user_email: 'github-actions[bot]@users.noreply.github.com'
+          commit_message: ${{ github.event.head_commit.message }}
\ No newline at end of file
diff --git a/.github/workflows/emscripten.yml b/.github/workflows/emscripten.yml
index d575a71..507baa7 100644
--- a/.github/workflows/emscripten.yml
+++ b/.github/workflows/emscripten.yml
@@ -7,7 +7,7 @@ jobs:
   build-wasm-wheel:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
       - name: Build WASM wheel
         uses: pypa/cibuildwheel@v3.1.3
         env:
diff --git a/.github/workflows/publish-pypi.yml b/.github/workflows/publish-pypi.yml
index e212ac9..ef5b989 100644
--- a/.github/workflows/publish-pypi.yml
+++ b/.github/workflows/publish-pypi.yml
@@ -18,7 +18,7 @@ jobs:
       id-token: write
     steps:
       - name: Download artifacts
-        uses: actions/download-artifact@v4
+        uses: actions/download-artifact@v5
         with:
           path: dist/
           merge-multiple: true
@@ -27,9 +27,9 @@ jobs:
       - name: Publish distribution to PyPI
         if: github.event.release.prerelease == false
         uses: pypa/gh-action-pypi-publish@release/v1
-      
+
       - name: get wasm dist artifacts
-        uses: actions/download-artifact@v4
+        uses: actions/download-artifact@v5
         with:
           name: wasm_wheel
           path: wasm/
diff --git a/.github/workflows/static.yml b/.github/workflows/static.yml
index fb59137..d8b0b86 100644
--- a/.github/workflows/static.yml
+++ b/.github/workflows/static.yml
@@ -8,8 +8,8 @@ jobs:
     runs-on: ubuntu-latest
 
     steps:
-      - uses: actions/checkout@v4
-      - uses: prefix-dev/setup-pixi@v0.8.14
+      - uses: actions/checkout@v5
+      - uses: prefix-dev/setup-pixi@v0.9.0
         with:
           environments: static
           cache: true
diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml
index 9691361..5768f27 100644
--- a/.github/workflows/test.yml
+++ b/.github/workflows/test.yml
@@ -15,8 +15,8 @@ jobs:
     runs-on: ${{ matrix.os }}
 
     steps:
-      - uses: actions/checkout@v4
-      - uses: prefix-dev/setup-pixi@v0.8.14
+      - uses: actions/checkout@v5
+      - uses: prefix-dev/setup-pixi@v0.9.0
         with:
           environments: >-
             dev
diff --git a/.github/workflows/wheel.yml b/.github/workflows/wheel.yml
index be1678a..9bd4ac8 100644
--- a/.github/workflows/wheel.yml
+++ b/.github/workflows/wheel.yml
@@ -7,8 +7,8 @@ jobs:
   build-sdist:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v4
-      - uses: prefix-dev/setup-pixi@v0.8.14
+      - uses: actions/checkout@v5
+      - uses: prefix-dev/setup-pixi@v0.9.0
         with:
           environments: dev
           cache: true
@@ -31,7 +31,7 @@ jobs:
         os: [ubuntu-latest, windows-latest, macos-latest, ubuntu-24.04-arm]
     runs-on: ${{ matrix.os }}
     steps:
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v5
       - name: Build wheels
         uses: pypa/cibuildwheel@v3.1.3
         env:
diff --git a/asv_benchmarks/.gitignore b/asv_benchmarks/.gitignore
new file mode 100644
index 0000000..3bef833
--- /dev/null
+++ b/asv_benchmarks/.gitignore
@@ -0,0 +1,5 @@
+*__pycache__*
+env/
+html/
+results/
+benchmarks/cache/
\ No newline at end of file
diff --git a/asv_benchmarks/asv.conf.json b/asv_benchmarks/asv.conf.json
new file mode 100644
index 0000000..7a60b7a
--- /dev/null
+++ b/asv_benchmarks/asv.conf.json
@@ -0,0 +1,18 @@
+{
+    "version": 1,
+    "project": "fastcan",
+    "project_url": "https://github.com/scikit-learn-contrib/fastcan",
+    "show_commit_url": "https://github.com/scikit-learn-contrib/fastcan/commit/",
+    "repo": "..",
+    "branches": ["main"],
+    "environment_type": "conda",
+    "conda_channels": ["conda-forge"],
+    "build_command": ["python -m build --wheel -o {build_cache_dir} {build_dir}"],
+    "install_command": ["python -mpip install {wheel_file}"],
+    "uninstall_command": ["return-code=any python -mpip uninstall -y {project}"],
+    "pythons": ["3.13"],
+    "matrix": {
+        "scikit-learn": [""],
+        "pandas": [""]
+    }
+}
\ No newline at end of file
diff --git a/asv_benchmarks/benchmarks/__init__.py b/asv_benchmarks/benchmarks/__init__.py
new file mode 100644
index 0000000..f4e0730
--- /dev/null
+++ b/asv_benchmarks/benchmarks/__init__.py
@@ -0,0 +1 @@
+"""Benchmark suite for fastcan using ASV"""
diff --git a/asv_benchmarks/benchmarks/common.py b/asv_benchmarks/benchmarks/common.py
new file mode 100644
index 0000000..46cad89
--- /dev/null
+++ b/asv_benchmarks/benchmarks/common.py
@@ -0,0 +1,53 @@
+import pickle
+import timeit
+from abc import ABC, abstractmethod
+from pathlib import Path
+
+
+def get_estimator_path(benchmark, params):
+    """Get path of pickled fitted estimator"""
+    path = Path(__file__).resolve().parent / "cache" / "estimators"
+
+    filename = (
+        benchmark.__class__.__name__
+        + "_estimator_"
+        + "_".join(list(map(str, params)))
+        + ".pkl"
+    )
+
+    return path / filename
+
+
+class Benchmark(ABC):
+    """Abstract base class for all the benchmarks"""
+
+    timer = timeit.default_timer  # wall time
+    timeout = 500
+
+    # save estimators
+    current_path = Path(__file__).resolve().parent
+    cache_path = current_path / "cache"
+    cache_path.mkdir(exist_ok=True)
+    (cache_path / "estimators").mkdir(exist_ok=True)
+
+    def setup(self, *params):
+        """Generate dataset and load the fitted estimator"""
+        # This is run once per combination of parameters and per repeat so we
+        # need to avoid doing expensive operations there.
+
+        self.X, self.X_val, self.y, self.y_val = self.make_data(params)
+
+        est_path = get_estimator_path(self, params)
+        with est_path.open(mode="rb") as f:
+            self.estimator = pickle.load(f)
+
+    @abstractmethod
+    def make_data(self, params):
+        """Return the dataset for a combination of parameters"""
+        # The datasets are cached using joblib.Memory so it's fast and can be
+        # called for each repeat
+
+    @property
+    @abstractmethod
+    def params(self):
+        pass
diff --git a/asv_benchmarks/benchmarks/datasets.py b/asv_benchmarks/benchmarks/datasets.py
new file mode 100644
index 0000000..0682f75
--- /dev/null
+++ b/asv_benchmarks/benchmarks/datasets.py
@@ -0,0 +1,56 @@
+from pathlib import Path
+
+import numpy as np
+from joblib import Memory
+from sklearn.datasets import (
+    fetch_openml,
+    load_digits,
+    make_regression,
+)
+from sklearn.model_selection import train_test_split
+from sklearn.preprocessing import MaxAbsScaler, StandardScaler
+
+# memory location for caching datasets
+M = Memory(location=str(Path(__file__).resolve().parent / "cache"))
+
+
+@M.cache
+def _digits_dataset(n_samples=None, dtype=np.float32):
+    X, y = load_digits(return_X_y=True)
+    X = X.astype(dtype, copy=False)
+    X = MaxAbsScaler().fit_transform(X)
+    X = X[:n_samples]
+    y = y[:n_samples]
+
+    X, X_val, y, y_val = train_test_split(X, y, test_size=0.1, random_state=0)
+    return X, X_val, y, y_val
+
+
+@M.cache
+def _synth_regression_dataset(n_samples=10000, n_features=200, dtype=np.float32):
+    X, y = make_regression(
+        n_samples=n_samples,
+        n_features=n_features,
+        n_informative=n_features // 10,
+        noise=50,
+        random_state=0,
+    )
+    X = X.astype(dtype, copy=False)
+    X = StandardScaler().fit_transform(X)
+
+    X, X_val, y, y_val = train_test_split(X, y, test_size=0.1, random_state=0)
+    return X, X_val, y, y_val
+
+
+@M.cache
+def _co2_dataset(dtype=np.float32):
+    X, y = fetch_openml(data_id=41187, return_X_y=True, as_frame=False)
+    X = X[:, [1, 3]]
+    X = X.astype(dtype, copy=False)
+    n_samples = len(y)
+    n_test = int(n_samples * 0.1)
+
+    mask_train = np.arange(n_samples) < (n_samples - n_test)
+    X, X_val = X[mask_train], X[~mask_train]
+    y_train, y_val = y[mask_train], y[~mask_train]
+    return X, X_val, y_train, y_val
diff --git a/asv_benchmarks/benchmarks/fastcan.py b/asv_benchmarks/benchmarks/fastcan.py
new file mode 100644
index 0000000..121038f
--- /dev/null
+++ b/asv_benchmarks/benchmarks/fastcan.py
@@ -0,0 +1,85 @@
+import itertools
+import pickle
+
+from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
+from sklearn.linear_model import LinearRegression
+
+from fastcan import FastCan
+
+from .common import Benchmark, get_estimator_path
+from .datasets import _digits_dataset, _synth_regression_dataset
+
+
+class FastCanBenchmark(Benchmark):
+    """
+    Benchmarks for FastCan.
+    """
+
+    param_names = ["task", "alg"]
+    params = (["classif", "reg"], ["h", "eta"])
+
+    def setup_cache(self):
+        """Pickle a fitted estimator for all combinations of parameters"""
+        # This is run once per benchmark class.
+
+        param_grid = list(itertools.product(*self.params))
+
+        for params in param_grid:
+            _, alg = params
+            X, _, y, _ = self.make_data(params)
+
+            if alg == "h":
+                eta = False
+            else:
+                eta = True
+            estimator = FastCan(
+                n_features_to_select=20,
+                eta=eta,
+            )
+            estimator.fit(X, y)
+
+            est_path = get_estimator_path(self, params)
+            with est_path.open(mode="wb") as f:
+                pickle.dump(estimator, f)
+
+    def make_data(self, params):
+        task, _ = params
+        if task == "classif":
+            return _digits_dataset()
+        return _synth_regression_dataset()
+
+    def time_fit(self, *args):
+        self.estimator.fit(self.X, self.y)
+
+    def peakmem_fit(self, *args):
+        self.estimator.fit(self.X, self.y)
+
+    def track_train_score(self, *args):
+        task, _ = args
+        X_t = self.estimator.transform(self.X)
+        if task == "classif":
+            clf = LinearDiscriminantAnalysis()
+            clf.fit(X_t, self.y)
+            return float(clf.score(X_t, self.y))
+        else:
+            reg = LinearRegression()
+            reg.fit(X_t, self.y)
+            return float(reg.score(X_t, self.y))
+
+    def track_test_score(self, *args):
+        task, _ = args
+        X_t = self.estimator.transform(self.X_val)
+        if task == "classif":
+            clf = LinearDiscriminantAnalysis()
+            clf.fit(X_t, self.y_val)
+            return float(clf.score(X_t, self.y_val))
+        else:
+            reg = LinearRegression()
+            reg.fit(X_t, self.y_val)
+            return float(reg.score(X_t, self.y_val))
+
+    def time_transform(self, *args):
+        self.estimator.transform(self.X)
+
+    def peakmem_transform(self, *args):
+        self.estimator.transform(self.X)
diff --git a/asv_benchmarks/benchmarks/narx.py b/asv_benchmarks/benchmarks/narx.py
new file mode 100644
index 0000000..8c26a3a
--- /dev/null
+++ b/asv_benchmarks/benchmarks/narx.py
@@ -0,0 +1,75 @@
+import itertools
+import pickle
+
+from sklearn.metrics import r2_score
+
+from fastcan.narx import make_narx
+
+from .common import Benchmark, get_estimator_path
+from .datasets import _co2_dataset
+
+
+class NARXBenchmark(Benchmark):
+    """
+    Benchmarks for NARX.
+    """
+
+    param_names = ["opt_alg"]
+    params = (["osa", "msa"],)
+
+    n_terms_to_select = 10
+    max_delay = 10
+    poly_degree = 2
+
+    def setup_cache(self):
+        """Pickle a fitted estimator for all combinations of parameters"""
+        # This is run once per benchmark class.
+
+        param_grid = list(itertools.product(*self.params))
+
+        for params in param_grid:
+            X, _, y, _ = self.make_data(params)
+            estimator = make_narx(
+                X,
+                y,
+                n_terms_to_select=self.n_terms_to_select,
+                max_delay=self.max_delay,
+                poly_degree=self.poly_degree,
+            )
+
+            estimator = estimator.fit(X, y, coef_init="one_step_ahead")
+
+            est_path = get_estimator_path(self, params)
+            with est_path.open(mode="wb") as f:
+                pickle.dump(estimator, f)
+
+    def make_data(self, params):
+        return _co2_dataset()
+
+    def time_fit(self, *args):
+        (opt_alg,) = args
+        if opt_alg == "osa":
+            coef_init = None
+        else:
+            coef_init = [0] * (self.n_terms_to_select + 1)
+        self.estimator.fit(self.X, self.y, coef_init=coef_init)
+
+    def peakmem_fit(self, *args):
+        self.estimator.fit(self.X, self.y)
+
+    def track_train_score(self, *args):
+        y_pred = self.estimator.predict(self.X, self.y[: self.max_delay])
+        return float(r2_score(self.y, y_pred))
+
+    def track_test_score(self, *args):
+        y_val_pred = self.estimator.predict(
+            self.X_val,
+            self.y_val[: self.max_delay],
+        )
+        return float(r2_score(self.y_val, y_val_pred))
+
+    def time_predict(self, *args):
+        self.estimator.predict(self.X, self.y[: self.max_delay])
+
+    def peakmem_predict(self, *args):
+        self.estimator.predict(self.X, self.y[: self.max_delay])
diff --git a/fastcan/narx/_utils.py b/fastcan/narx/_utils.py
index 9eac000..70b88ca 100644
--- a/fastcan/narx/_utils.py
+++ b/fastcan/narx/_utils.py
@@ -102,7 +102,7 @@ def _get_term_str(term_feat_ids, term_delay_ids):
         + f"|{'Term':^{term_space}}"
         + f"|{'Coef':^{coef_space}}|"
     )
-    print(f"|{'-'*yid_space}|{'-'*term_space}|{'-'*coef_space}|")
+    print(f"|{'-' * yid_space}|{'-' * term_space}|{'-' * coef_space}|")
     for i in range(narx.n_outputs_):
         print(
             f"|{i:^{yid_space}}|"
diff --git a/pixi.lock b/pixi.lock
index c2ffa50..f2f4259 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -14,8 +14,8 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/cython-3.1.2-py313h5dec8f5_2.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/joblib-1.5.1-pyhd8ed1ab_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/libblas-3.9.0-32_h59b9bed_openblas.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcblas-3.9.0-32_he106b2a_openblas.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libblas-3.9.0-34_h59b9bed_openblas.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcblas-3.9.0-34_he106b2a_openblas.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/libgcc-15.1.0-h767d61c_4.conda
@@ -23,7 +23,7 @@ environments:
       - 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/liblapack-3.9.0-32_h7ac8fdf_openblas.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/liblapack-3.9.0-34_h7ac8fdf_openblas.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/liblzma-5.8.1-hb9d3cd8_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libmpdec-4.0.0-hb9d3cd8_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libopenblas-0.3.30-pthreads_h94d23a6_1.conda
@@ -36,7 +36,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.5-h2d0b736_3.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/ninja-1.13.1-h171cf75_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/numpy-2.3.2-py313hf6604e3_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/openssl-3.5.1-h7b32b05_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/openssl-3.5.2-h26f9b46_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-25.0-pyh29332c3_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pyproject-metadata-0.9.1-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.13.5-hec9711d_102_cp313.conda
@@ -57,8 +57,8 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cython-3.1.2-py313hbf9bc30_2.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/joblib-1.5.1-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/ld_impl_linux-aarch64-2.44-h5e2c951_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libblas-3.9.0-32_h1a9f1db_openblas.conda
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+  - pkg:pypi/anyio?source=compressed-mapping
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+  - pkg:pypi/kiwisolver?source=compressed-mapping
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-  - arrow-cpp <0.0a0
   - apache-arrow-proc =*=cpu
+  - arrow-cpp <0.0a0
+  - parquet-cpp <0.0a0
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+  - apache-arrow-proc =*=cpu
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-  - arrow-cpp <0.0a0
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-  - apache-arrow-proc =*=cpu
   license: Apache-2.0
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+  - arrow-cpp <0.0a0
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-  - libarrow-acero 21.0.0 h926bc74_0_cpu
-  - libarrow-dataset 21.0.0 h926bc74_0_cpu
+  - libarrow 21.0.0 h20b3f57_1_cpu
+  - libarrow-acero 21.0.0 h926bc74_1_cpu
+  - libarrow-dataset 21.0.0 h926bc74_1_cpu
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   license: Apache-2.0
   license_family: APACHE
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+- conda: https://conda.anaconda.org/conda-forge/win-64/libarrow-substrait-21.0.0-hf865cc0_1_cpu.conda
+  build_number: 1
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+  md5: 11889d3dcf0a07e372702463c7eb4a94
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-  - libarrow-acero 21.0.0 h7d8d6a5_0_cpu
-  - libarrow-dataset 21.0.0 h7d8d6a5_0_cpu
+  - libarrow 21.0.0 h1f0de8a_1_cpu
+  - libarrow-acero 21.0.0 h7d8d6a5_1_cpu
+  - libarrow-dataset 21.0.0 h7d8d6a5_1_cpu
   - libprotobuf >=6.31.1,<6.31.2.0a0
   - ucrt >=10.0.20348.0
   - vc >=14.3,<15
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   license_family: APACHE
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-  - liblapacke 3.9.0   32*_openblas
-  - blas 2.132   openblas
-  - liblapack  3.9.0   32*_openblas
+  - blas 2.134   openblas
+  - liblapacke 3.9.0   34*_openblas
+  - libcblas   3.9.0   34*_openblas
+  - liblapack  3.9.0   34*_openblas
   license: BSD-3-Clause
-  license_family: BSD
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-- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libblas-3.9.0-32_h1a9f1db_openblas.conda
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-  - liblapack  3.9.0   32*_openblas
-  - blas 2.132   openblas
-  - liblapacke 3.9.0   32*_openblas
+  - liblapacke 3.9.0   34*_openblas
+  - liblapack  3.9.0   34*_openblas
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   - mkl <2025
   license: BSD-3-Clause
-  license_family: BSD
   purls: []
-  size: 17341
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-- conda: https://conda.anaconda.org/conda-forge/osx-64/libblas-3.9.0-32_h7f60823_openblas.conda
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-  md5: 0f7197e3b4ecfa8aa24a371c3eaabb8a
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+- conda: https://conda.anaconda.org/conda-forge/osx-64/libblas-3.9.0-34_h7f60823_openblas.conda
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-  - blas 2.132   openblas
+  - liblapacke 3.9.0   34*_openblas
   - mkl <2025
-  - liblapacke 3.9.0   32*_openblas
-  - libcblas   3.9.0   32*_openblas
+  - libcblas   3.9.0   34*_openblas
+  - liblapack  3.9.0   34*_openblas
+  - blas 2.134   openblas
   license: BSD-3-Clause
-  license_family: BSD
   purls: []
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-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libblas-3.9.0-32_h10e41b3_openblas.conda
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+  size: 19537
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+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libblas-3.9.0-34_h10e41b3_openblas.conda
+  build_number: 34
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+  md5: cdb3e1ca1661dbf19f9aad7dad524996
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   - libopenblas >=0.3.30,<1.0a0
   constrains:
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-  - liblapack  3.9.0   32*_openblas
+  - blas 2.134   openblas
   - mkl <2025
-  - libcblas   3.9.0   32*_openblas
-  - liblapacke 3.9.0   32*_openblas
+  - liblapacke 3.9.0   34*_openblas
+  - libcblas   3.9.0   34*_openblas
+  - liblapack  3.9.0   34*_openblas
   license: BSD-3-Clause
-  license_family: BSD
   purls: []
-  size: 17520
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-- conda: https://conda.anaconda.org/conda-forge/win-64/libblas-3.9.0-32_h641d27c_mkl.conda
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-  md5: 49b36a01450e96c516bbc5486d4a0ea0
+  size: 19533
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+- conda: https://conda.anaconda.org/conda-forge/win-64/libblas-3.9.0-34_h5709861_mkl.conda
+  build_number: 34
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+  md5: a64dcde5f27b8e0e413ddfc56151664c
   depends:
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+  - mkl >=2024.2.2,<2025.0a0
   constrains:
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-  - liblapack  3.9.0   32*_mkl
-  - liblapacke 3.9.0   32*_mkl
-  - blas 2.132   mkl
+  - libcblas   3.9.0   34*_mkl
+  - liblapacke 3.9.0   34*_mkl
+  - blas 2.134   mkl
+  - liblapack  3.9.0   34*_mkl
   license: BSD-3-Clause
-  license_family: BSD
   purls: []
-  size: 3735390
-  timestamp: 1750389080409
+  size: 70548
+  timestamp: 1754682440057
 - conda: https://conda.anaconda.org/conda-forge/linux-64/libbrotlicommon-1.1.0-hb9d3cd8_3.conda
   sha256: 462a8ed6a7bb9c5af829ec4b90aab322f8bcd9d8987f793e6986ea873bbd05cf
   md5: cb98af5db26e3f482bebb80ce9d947d3
@@ -7684,81 +8863,76 @@ packages:
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-  md5: 3d3f9355e52f269cd8bc2c440d8a5263
+- conda: https://conda.anaconda.org/conda-forge/linux-64/libcblas-3.9.0-34_he106b2a_openblas.conda
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   depends:
-  - libblas 3.9.0 32_h59b9bed_openblas
+  - libblas 3.9.0 34_h59b9bed_openblas
   constrains:
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-  - liblapack  3.9.0   32*_openblas
-  - liblapacke 3.9.0   32*_openblas
+  - liblapacke 3.9.0   34*_openblas
+  - blas 2.134   openblas
+  - liblapack  3.9.0   34*_openblas
   license: BSD-3-Clause
-  license_family: BSD
   purls: []
-  size: 17308
-  timestamp: 1750388809353
-- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libcblas-3.9.0-32_hab92f65_openblas.conda
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-  md5: 2f02a3ea0960118a0a8d45cdd348b039
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+- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libcblas-3.9.0-34_hab92f65_openblas.conda
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+  - libblas 3.9.0 34_h1a9f1db_openblas
   constrains:
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-  - blas 2.132   openblas
-  - liblapacke 3.9.0   32*_openblas
+  - liblapack  3.9.0   34*_openblas
+  - liblapacke 3.9.0   34*_openblas
+  - blas 2.134   openblas
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-  license_family: BSD
   purls: []
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-- conda: https://conda.anaconda.org/conda-forge/osx-64/libcblas-3.9.0-32_hff6cab4_openblas.conda
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+- conda: https://conda.anaconda.org/conda-forge/osx-64/libcblas-3.9.0-34_hff6cab4_openblas.conda
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+  - libblas 3.9.0 34_h7f60823_openblas
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-  - liblapack  3.9.0   32*_openblas
-  - liblapacke 3.9.0   32*_openblas
+  - liblapacke 3.9.0   34*_openblas
+  - liblapack  3.9.0   34*_openblas
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+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libcblas-3.9.0-34_hb3479ef_openblas.conda
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   depends:
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+  - libblas 3.9.0 34_h10e41b3_openblas
   constrains:
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-  - liblapack  3.9.0   32*_openblas
-  - liblapacke 3.9.0   32*_openblas
+  - liblapack  3.9.0   34*_openblas
+  - blas 2.134   openblas
+  - liblapacke 3.9.0   34*_openblas
   license: BSD-3-Clause
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   purls: []
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-  md5: 054b9b4b48296e4413cf93e6ece7b27d
+  size: 19521
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+- conda: https://conda.anaconda.org/conda-forge/win-64/libcblas-3.9.0-34_h2a3cdd5_mkl.conda
+  build_number: 34
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+  md5: 25a019872ff471af70fd76d9aaaf1313
   depends:
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+  - libblas 3.9.0 34_h5709861_mkl
   constrains:
-  - liblapack  3.9.0   32*_mkl
-  - liblapacke 3.9.0   32*_mkl
-  - blas 2.132   mkl
+  - liblapacke 3.9.0   34*_mkl
+  - blas 2.134   mkl
+  - liblapack  3.9.0   34*_mkl
   license: BSD-3-Clause
-  license_family: BSD
   purls: []
-  size: 3735392
-  timestamp: 1750389122586
+  size: 70700
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 - conda: https://conda.anaconda.org/conda-forge/osx-64/libclang-cpp19.1-19.1.7-default_h3571c67_3.conda
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/libglib-2.84.2-h3618099_0.conda
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-  md5: 072ab14a02164b7c0c089055368ff776
+- conda: https://conda.anaconda.org/conda-forge/linux-64/libglib-2.84.3-hf39c6af_0.conda
+  sha256: e1ad3d9ddaa18f95ff5d244587fd1a37aca6401707f85a37f7d9b5002fcf16d0
+  md5: 467f23819b1ea2b89c3fc94d65082301
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-  - libgcc >=13
+  - libgcc >=14
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   - libzlib >=1.3.1,<2.0a0
   - pcre2 >=10.45,<10.46.0a0
   constrains:
-  - glib 2.84.2 *_0
+  - glib 2.84.3 *_0
   license: LGPL-2.1-or-later
   purls: []
-  size: 3955066
-  timestamp: 1747836671118
-- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libglib-2.84.2-hc022ef1_0.conda
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-  md5: 51323eab8e9f049d001424828c4c25a4
+  size: 3961899
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+- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libglib-2.84.3-h75d4a95_0.conda
+  sha256: 4ae5e188db3f79e336690c745946f8ee5c02f18ab314017b533446ed458a295b
+  md5: cf67d7e3b0a89dd3240c7793310facc3
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-  - libgcc >=13
+  - libgcc >=14
   - libiconv >=1.18,<2.0a0
   - libzlib >=1.3.1,<2.0a0
   - pcre2 >=10.45,<10.46.0a0
   constrains:
-  - glib 2.84.2 *_0
+  - glib 2.84.3 *_0
   license: LGPL-2.1-or-later
   purls: []
-  size: 4016850
-  timestamp: 1747836804570
-- conda: https://conda.anaconda.org/conda-forge/win-64/libglib-2.84.2-hbc94333_0.conda
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-  md5: fee05801cc5db97bec20a5e78fb3905b
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+- conda: https://conda.anaconda.org/conda-forge/win-64/libglib-2.84.3-h1c1036b_0.conda
+  sha256: bd322efaebc369e188a1dd93030325a40753a4c009e92c1f82ec481a20f0d232
+  md5: 2bcc00752c158d4a70e1eaccbf6fe8ae
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@@ -8744,14 +9918,14 @@ packages:
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   - pcre2 >=10.45,<10.46.0a0
   - ucrt >=10.0.20348.0
-  - vc >=14.2,<15
-  - vc14_runtime >=14.29.30139
+  - vc >=14.3,<15
+  - vc14_runtime >=14.44.35208
   constrains:
-  - glib 2.84.2 *_0
+  - glib 2.84.3 *_0
   license: LGPL-2.1-or-later
   purls: []
-  size: 3771466
-  timestamp: 1747837394297
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 - conda: https://conda.anaconda.org/conda-forge/linux-64/libglvnd-1.7.0-ha4b6fd6_2.conda
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-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/ruff-0.12.7-h575f11b_0.conda
+  size: 10472014
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+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/ruff-0.12.8-h575f11b_0.conda
   noarch: python
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-  md5: db9a75ae51077e52982566919fb6bc16
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   - __osx >=11.0
   license: MIT
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-- conda: https://conda.anaconda.org/conda-forge/win-64/ruff-0.12.7-hd40eec1_0.conda
+  size: 9712438
+  timestamp: 1754600916793
+- conda: https://conda.anaconda.org/conda-forge/win-64/ruff-0.12.8-hd40eec1_0.conda
   noarch: python
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-  md5: 82a88723dba120f3b7070e68523a1c9a
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+  md5: 4597f39a03982885c89c9ffa6394de1a
   depends:
   - python
   - vc >=14.3,<15
   - vc14_runtime >=14.44.35208
   - ucrt >=10.0.20348.0
   license: MIT
-  license_family: MIT
-  size: 10858681
-  timestamp: 1753906142349
+  size: 10821904
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 - conda: https://conda.anaconda.org/conda-forge/linux-64/s2n-1.5.23-h8e187f5_0.conda
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@@ -15366,6 +17777,63 @@ packages:
   purls: []
   size: 210264
   timestamp: 1643442231687
+- conda: https://conda.anaconda.org/conda-forge/linux-64/simdjson-3.13.0-h84d6215_0.conda
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+  - __glibc >=2.17,<3.0.a0
+  - libgcc >=13
+  - libstdcxx >=13
+  license: Apache-2.0
+  license_family: APACHE
+  purls: []
+  size: 248262
+  timestamp: 1749080745183
+- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/simdjson-3.13.0-h17cf362_0.conda
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+  - libstdcxx >=13
+  license: Apache-2.0
+  license_family: APACHE
+  purls: []
+  size: 214218
+  timestamp: 1749080791184
+- conda: https://conda.anaconda.org/conda-forge/osx-64/simdjson-3.13.0-h9275861_0.conda
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+  - libcxx >=18
+  license: Apache-2.0
+  license_family: APACHE
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+  timestamp: 1749080849639
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/simdjson-3.13.0-ha393de7_0.conda
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+  depends:
+  - __osx >=11.0
+  - libcxx >=18
+  license: Apache-2.0
+  license_family: APACHE
+  purls: []
+  size: 208556
+  timestamp: 1749080957534
+- conda: https://conda.anaconda.org/conda-forge/win-64/simdjson-3.13.0-hc790b64_0.conda
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+  md5: bb927044f1999ff62cb2c99d385ad597
+  depends:
+  - ucrt >=10.0.20348.0
+  - vc >=14.2,<15
+  - vc14_runtime >=14.29.30139
+  license: Apache-2.0
+  license_family: APACHE
+  purls: []
+  size: 255973
+  timestamp: 1749080928478
 - conda: https://conda.anaconda.org/conda-forge/noarch/six-1.17.0-pyhe01879c_1.conda
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   md5: 3339e3b65d58accf4ca4fb8748ab16b3
@@ -15665,6 +18133,17 @@ packages:
   - pkg:pypi/stack-data?source=hash-mapping
   size: 26988
   timestamp: 1733569565672
+- conda: https://conda.anaconda.org/conda-forge/noarch/tabulate-0.9.0-pyhd8ed1ab_2.conda
+  sha256: 090023bddd40d83468ef86573976af8c514f64119b2bd814ee63a838a542720a
+  md5: 959484a66b4b76befcddc4fa97c95567
+  depends:
+  - python >=3.9
+  license: MIT
+  license_family: MIT
+  purls:
+  - pkg:pypi/tabulate?source=hash-mapping
+  size: 37554
+  timestamp: 1733589854804
 - conda: https://conda.anaconda.org/conda-forge/osx-64/tapi-1300.6.5-h390ca13_0.conda
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   md5: c6ee25eb54accb3f1c8fc39203acfaf1
@@ -15689,19 +18168,18 @@ packages:
   purls: []
   size: 207679
   timestamp: 1725491499758
-- conda: https://conda.anaconda.org/conda-forge/win-64/tbb-2021.13.0-h62715c5_1.conda
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-  md5: 9190dd0a23d925f7602f9628b3aed511
+- conda: https://conda.anaconda.org/conda-forge/win-64/tbb-2021.13.0-h18a62a1_2.conda
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   depends:
-  - libhwloc >=2.11.2,<2.11.3.0a0
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   - ucrt >=10.0.20348.0
-  - vc >=14.2,<15
-  - vc14_runtime >=14.29.30139
+  - vc >=14.3,<15
+  - vc14_runtime >=14.44.35208
   license: Apache-2.0
-  license_family: APACHE
   purls: []
-  size: 151460
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+  size: 149955
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 - conda: https://conda.anaconda.org/conda-forge/noarch/terminado-0.18.1-pyh0d859eb_0.conda
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@@ -15861,36 +18339,36 @@ packages:
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/tornado-6.5.1-py313h536fd9c_0.conda
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-  md5: e9434a5155db25c38ade26f71a2f5a48
+- conda: https://conda.anaconda.org/conda-forge/linux-64/tornado-6.5.2-py313h07c4f96_0.conda
+  sha256: bc4df522f933ea8829334d79732d828880bb976ed03a1f68f0826b91eaaee0b1
+  md5: 01082edc358a2285f6480b918e35e1af
   depends:
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-  - libgcc >=13
+  - libgcc >=14
   - python >=3.13,<3.14.0a0
   - python_abi 3.13.* *_cp313
   license: Apache-2.0
   license_family: Apache
   purls:
   - pkg:pypi/tornado?source=hash-mapping
-  size: 873269
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-- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/tornado-6.5.1-py313h6a51379_0.conda
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-  md5: efd003285041d23e604630b18f24b9dd
+  size: 878421
+  timestamp: 1754732125966
+- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/tornado-6.5.2-py313he149459_0.conda
+  sha256: fad315dd2f2fcec68ad87415f7b63b3f3ff2a1184ecf8fd79039fcc81297e407
+  md5: 7233231d72d085bdb4fedde27b19c2e3
   depends:
-  - libgcc >=13
+  - libgcc >=14
   - python >=3.13,<3.14.0a0
   - python_abi 3.13.* *_cp313
   license: Apache-2.0
   license_family: Apache
   purls:
   - pkg:pypi/tornado?source=hash-mapping
-  size: 876988
-  timestamp: 1748005374481
-- conda: https://conda.anaconda.org/conda-forge/osx-64/tornado-6.5.1-py313h63b0ddb_0.conda
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-  md5: 7554d07cbe64f41c73a403e99bccf3c6
+  size: 877848
+  timestamp: 1754734985637
+- conda: https://conda.anaconda.org/conda-forge/osx-64/tornado-6.5.2-py313h585f44e_0.conda
+  sha256: 6703359f10133da77905743c287735177bb7f074b68b289c41e72c4756da586d
+  md5: 80dbd1e0d4eb09da8a97b3315a26d904
   depends:
   - __osx >=10.13
   - python >=3.13,<3.14.0a0
@@ -15899,11 +18377,11 @@ packages:
   license_family: Apache
   purls:
   - pkg:pypi/tornado?source=hash-mapping
-  size: 874905
-  timestamp: 1748003585372
-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/tornado-6.5.1-py313h90d716c_0.conda
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-  md5: 1ab3bef3e9aa0bba9eee2dfbedab1dba
+  size: 876047
+  timestamp: 1754732200371
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/tornado-6.5.2-py313hcdf3177_0.conda
+  sha256: e687a470c8cea7815da666493cb6161948a7a1ae118237624db7689612732a04
+  md5: d086389c0d48b2751361720665321eeb
   depends:
   - __osx >=11.0
   - python >=3.13,<3.14.0a0
@@ -15913,23 +18391,34 @@ packages:
   license_family: Apache
   purls:
   - pkg:pypi/tornado?source=hash-mapping
-  size: 874352
-  timestamp: 1748003547444
-- conda: https://conda.anaconda.org/conda-forge/win-64/tornado-6.5.1-py313ha7868ed_0.conda
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-  md5: a6a7c54e5dfc3bfad645e714cc14854c
+  size: 875854
+  timestamp: 1754732465438
+- conda: https://conda.anaconda.org/conda-forge/win-64/tornado-6.5.2-py313h5ea7bf4_0.conda
+  sha256: 6a461f7ffba2f0d90bca775fc95f58840c9b3ed3d6002659f4979a4a7b7ed344
+  md5: 57756431d27f6043d8bc1e78eb8b3c7b
   depends:
   - python >=3.13,<3.14.0a0
   - python_abi 3.13.* *_cp313
   - ucrt >=10.0.20348.0
-  - vc >=14.2,<15
-  - vc14_runtime >=14.29.30139
+  - vc >=14.3,<15
+  - vc14_runtime >=14.44.35208
   license: Apache-2.0
   license_family: Apache
   purls:
   - pkg:pypi/tornado?source=hash-mapping
-  size: 878044
-  timestamp: 1748003914685
+  size: 878818
+  timestamp: 1754732227288
+- conda: https://conda.anaconda.org/conda-forge/noarch/tqdm-4.67.1-pyhd8ed1ab_1.conda
+  sha256: 11e2c85468ae9902d24a27137b6b39b4a78099806e551d390e394a8c34b48e40
+  md5: 9efbfdc37242619130ea42b1cc4ed861
+  depends:
+  - colorama
+  - python >=3.9
+  license: MPL-2.0 or MIT
+  purls:
+  - pkg:pypi/tqdm?source=hash-mapping
+  size: 89498
+  timestamp: 1735661472632
 - conda: https://conda.anaconda.org/conda-forge/noarch/traitlets-5.14.3-pyhd8ed1ab_1.conda
   sha256: f39a5620c6e8e9e98357507262a7869de2ae8cc07da8b7f84e517c9fd6c2b959
   md5: 019a7385be9af33791c989871317e1ed
@@ -15941,16 +18430,28 @@ packages:
   - pkg:pypi/traitlets?source=hash-mapping
   size: 110051
   timestamp: 1733367480074
-- conda: https://conda.anaconda.org/conda-forge/noarch/types-python-dateutil-2.9.0.20250708-pyhd8ed1ab_0.conda
-  sha256: 843bbc8e763a96b2b4ea568cf7918b6027853d03b5d8810ab77aaa9af472a6e2
-  md5: b6d4c200582ead6427f49a189e2c6d65
+- conda: https://conda.anaconda.org/conda-forge/noarch/truststore-0.10.3-pyhe01879c_0.conda
+  sha256: df334b8978edc4f42e7056764db1a26f1e4c6e6a29d5e2ca426ed5b2f09d24a0
+  md5: 15afca3bec34c3ecbeb2028f81a51772
+  depends:
+  - python >=3.10
+  - python
+  license: MIT
+  license_family: MIT
+  purls:
+  - pkg:pypi/truststore?source=compressed-mapping
+  size: 23801
+  timestamp: 1753886790616
+- conda: https://conda.anaconda.org/conda-forge/noarch/types-python-dateutil-2.9.0.20250809-pyhd8ed1ab_0.conda
+  sha256: e54a82e474f4f4b6988c6c7186e5def628c840fca81f5d103e9f78f01d5fead1
+  md5: 63a644e158c4f8eeca0d1290ac25e0cc
   depends:
   - python >=3.9
   license: Apache-2.0 AND MIT
   purls:
   - pkg:pypi/types-python-dateutil?source=hash-mapping
-  size: 24739
-  timestamp: 1751956725061
+  size: 24646
+  timestamp: 1754722843717
 - conda: https://conda.anaconda.org/conda-forge/noarch/typing-extensions-4.14.1-h4440ef1_0.conda
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   md5: 75be1a943e0a7f99fcf118309092c635
@@ -16063,6 +18564,20 @@ packages:
   purls: []
   size: 113963
   timestamp: 1753739198723
+- conda: https://conda.anaconda.org/conda-forge/noarch/virtualenv-20.33.1-pyhd8ed1ab_0.conda
+  sha256: 7b8328d79cb7ec19929ec955fe4dbb938d35da391a74a3974c47ca2622c64b04
+  md5: 3f6ee060b1462c29b3442df71939a358
+  depends:
+  - distlib >=0.3.7,<1
+  - filelock >=3.12.2,<4
+  - platformdirs >=3.9.1,<5
+  - python >=3.9
+  license: MIT
+  license_family: MIT
+  purls:
+  - pkg:pypi/virtualenv?source=compressed-mapping
+  size: 4138678
+  timestamp: 1754419391413
 - conda: https://conda.anaconda.org/conda-forge/win-64/vs2015_runtime-14.44.35208-h38c0c73_31.conda
   sha256: 8b20152d00e1153ccb1ed377a160110482f286a6d85a82b57ffcd60517d523a7
   md5: d75abcfbc522ccd98082a8c603fce34c
@@ -16812,6 +19327,67 @@ packages:
   purls: []
   size: 63944
   timestamp: 1753484092156
+- conda: https://conda.anaconda.org/conda-forge/linux-64/yaml-cpp-0.8.0-h3f2d84a_0.conda
+  sha256: 4b0b713a4308864a59d5f0b66ac61b7960151c8022511cdc914c0c0458375eca
+  md5: 92b90f5f7a322e74468bb4909c7354b5
+  depends:
+  - libstdcxx >=13
+  - libgcc >=13
+  - __glibc >=2.17,<3.0.a0
+  - libgcc >=13
+  license: MIT
+  license_family: MIT
+  purls: []
+  size: 223526
+  timestamp: 1745307989800
+- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/yaml-cpp-0.8.0-h5ad3122_0.conda
+  sha256: e146d83cdcf92506ab709c6e10acabd18a3394a23e6334a322c57e5d1d6d9f26
+  md5: b9e5a9da5729019c4f216cf0d386a70c
+  depends:
+  - libstdcxx >=13
+  - libgcc >=13
+  license: MIT
+  license_family: MIT
+  purls: []
+  size: 213281
+  timestamp: 1745308220432
+- conda: https://conda.anaconda.org/conda-forge/osx-64/yaml-cpp-0.8.0-h92383a6_0.conda
+  sha256: 67d25c3aa2b4ee54abc53060188542d6086b377878ebf3e2b262ae7379e05a6d
+  md5: e15e9855092a8bdaaaed6ad5c173fffa
+  depends:
+  - libcxx >=18
+  - __osx >=10.13
+  license: MIT
+  license_family: MIT
+  purls: []
+  size: 145204
+  timestamp: 1745308032698
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/yaml-cpp-0.8.0-ha1acc90_0.conda
+  sha256: 66ba31cfb8014fdd3456f2b3b394df123bbd05d95b75328b7c4131639e299749
+  md5: 30475b3d0406587cf90386a283bb3cd0
+  depends:
+  - libcxx >=18
+  - __osx >=11.0
+  license: MIT
+  license_family: MIT
+  purls: []
+  size: 136222
+  timestamp: 1745308075886
+- conda: https://conda.anaconda.org/conda-forge/win-64/yaml-cpp-0.8.0-he0c23c2_0.conda
+  sha256: 031642d753e0ebd666a76cea399497cc7048ff363edf7d76a630ee0a19e341da
+  md5: 9bb5064a9fca5ca8e7d7f1ae677354b6
+  depends:
+  - vc >=14.2,<15
+  - vc14_runtime >=14.29.30139
+  - ucrt >=10.0.20348.0
+  - vc >=14.2,<15
+  - vc14_runtime >=14.29.30139
+  - ucrt >=10.0.20348.0
+  license: MIT
+  license_family: MIT
+  purls: []
+  size: 148572
+  timestamp: 1745308037198
 - conda: https://conda.anaconda.org/conda-forge/linux-64/zeromq-4.3.5-h3b0a872_7.conda
   sha256: a4dc72c96848f764bb5a5176aa93dd1e9b9e52804137b99daeebba277b31ea10
   md5: 3947a35e916fcc6b9825449affbf4214
diff --git a/pyproject.toml b/pyproject.toml
index 90c1cdb..a68e298 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -67,6 +67,11 @@ fastcan = { path = ".", editable = true }
 cython = ">=3.1.0"
 meson-python = ">=0.18.0"
 
+[tool.pixi.feature.asv.dependencies]
+asv = "*"
+libmambapy = "*"
+conda-build = "*"
+
 [tool.pixi.feature.jupyter.dependencies]
 notebook = "*"
 matplotlib = "*"
@@ -112,6 +117,11 @@ time-eta = "python -m timeit -n 5 -s 'import numpy as np; from fastcan import Fa
 profile-minibatch = { cmd = '''python -c "import cProfile; import numpy as np; from fastcan import minibatch; X = np.random.rand(100, 3000); y = np.random.rand(100, 20); cProfile.run('minibatch(X, y, 1000, 10, verbose=0)', sort='$SORT')"''', env = { SORT = "cumtime" } }
 time-narx = '''python -m timeit -n 1 -s "import numpy as np; from fastcan.narx import make_narx; rng = np.random.default_rng(5); X = rng.random((1000, 10)); y = rng.random((1000, 2)); m = make_narx(X, y, 10, max_delay=2, poly_degree=2, verbose=0)" "m.fit(X, y, coef_init='one_step_ahead', verbose=1)"'''
 
+[tool.pixi.feature.asv.tasks]
+asv-build = { cmd = "python -m asv machine --machine $MACHINE --yes && python -m asv run --show-stderr -v --machine $MACHINE $EXTRA_ARGS", cwd = "asv_benchmarks", env = { MACHINE = "MacOS-M1", EXTRA_ARGS = "" } }
+asv-publish = { cmd = "python -m asv publish", cwd = "asv_benchmarks" }
+asv-preview = { cmd = "python -m asv preview", cwd = "asv_benchmarks", depends-on = ["asv-publish"] }
+
 [tool.pixi.feature.test.tasks]
 test = { cmd = "pytest", cwd = "." }
 test-coverage = { cmd = "rm -rf .coverage && pytest --cov-report $FMT --cov=$PACKAGE .", env = { PACKAGE = "fastcan", FMT = "html" } }
@@ -138,7 +148,7 @@ nogil-h = "python -Xgil=0 -m timeit -n 5 -s 'import numpy as np; from fastcan im
 nogil-eta = "python -Xgil=0 -m timeit -n 5 -s 'import numpy as np; from fastcan import FastCan; X = np.random.rand(3000, 100); y = np.random.rand(3000, 20)' 's = FastCan(100, eta=True, verbose=0).fit(X, y)'"
 
 [tool.pixi.environments]
-dev = ["docs", "test", "build", "jupyter"]
+dev = ["docs", "test", "build", "jupyter", "asv"]
 static = { features = ["static"], no-default-feature = true }
 nogil = { features = ["nogil"], no-default-feature = true }
 
@@ -153,6 +163,10 @@ skip = [
     "./htmlcov",
     "./build",
     "./pixi.lock",
+    "./asv_benchmarks/env",
+    "./asv_benchmarks/html",
+    "./asv_benchmarks/results",
+    "./asv_benchmarks/benchmarks/cache",
 ]
 ignore-words-list = [
     "MIS", # magnetic impedance spectroscopy (MIS)
@@ -164,10 +178,14 @@ line-length = 88
 exclude = [
     ".git",
     "__pycache__",
+    "build",
     "dist",
     "doc/_build",
     "doc/auto_examples",
-    "build",
+    "asv_benchmarks/env",
+    "asv_benchmarks/html",
+    "asv_benchmarks/results",
+    "asv_benchmarks/benchmarks/cache",
 ]
 
 [tool.ruff.lint]
@@ -222,6 +240,7 @@ notice-rgx = "\\#\\ Authors:\\ The\\ fastcan\\ developers\\\r?\\\n\\#\\ SPDX\\-L
 "**/tests/*" = ["CPY001"]
 "doc/*" = ["CPY001"]
 ".github/*" = ["CPY001"]
+"asv_benchmarks/*" = ["CPY001", "TID252"]
 
 [tool.cython-lint]
 # Ignore the same error codes as ruff