chore: update max line length

.github/workflows/pre-commit.yml

@@ -4,6 +4,9 @@ on:
   - push
   - pull_request
 
+permissions:
+  contents: read
+
 jobs:
   pre-commit:
     runs-on: ubuntu-latest

.github/workflows/pytest.yml

@@ -4,18 +4,30 @@ on:
   - pull_request
   - push
 
+permissions:
+  contents: read
+
 jobs:
   pytest:
-    runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+      matrix:
+        os: [ubuntu-latest, windows-latest, macos-latest]
+        python-version: ["3.10", "3.11", "3.12", "3.13"]
+    runs-on: ${{ matrix.os }}
 
     steps:
       - uses: actions/checkout@v4
 
       - uses: actions/setup-python@v5
         with:
-          python-version: '3.12'
+          python-version: ${{ matrix.python-version }}
           cache: 'pip'
 
+      - name: Show Python
+        run: |
+          python -c "import sys, platform; print(f'Executable: {sys.executable}\nVersion: {platform.python_version()}\nImplementation: {platform.python_implementation()}\nPlatform: {platform.platform()}')"
+
       - name: Install dependencies
         run: pip install '.[dev]'
 
@@ -25,3 +37,4 @@ jobs:
       - uses: codecov/codecov-action@v5
         with:
           token: ${{ secrets.CODECOV_TOKEN }}
+          flags: os-${{ matrix.os }}, python-${{ matrix.python-version }}

.github/workflows/wheels.yml

@@ -4,6 +4,9 @@ on:
   - push
   - pull_request
 
+permissions:
+  contents: read
+
 jobs:
   build:
     name: Build distribution

.pre-commit-config.yaml

@@ -38,20 +38,15 @@ repos:
   - id: sort-simple-yaml
   - id: trailing-whitespace
 
-- repo: https://github.com/google/yapf
-  rev: v0.40.2
-  hooks:
-  - id: yapf
-    language: system
-
-- repo: https://github.com/pylint-dev/pylint
-  rev: v3.3.1
-  hooks:
-  - id: pylint
-    language: system
-
 - repo: https://github.com/pre-commit/mirrors-mypy
   rev: v1.13.0
   hooks:
   - id: mypy
     language: system
+
+- repo: https://github.com/astral-sh/ruff-pre-commit
+  rev: v0.12.11
+  hooks:
+  - id: ruff-check
+    args: [--fix]
+  - id: ruff-format

grassmann_tensor/version.py

@@ -11,6 +11,7 @@
 except ModuleNotFoundError:
     try:
         import importlib.metadata
+
         __version__ = importlib.metadata.version("parity")
     except importlib.metadata.PackageNotFoundError:
         __version__ = "0.0.0"

pyproject.toml

@@ -8,39 +8,35 @@ dynamic = ["version"]
 dependencies = [
   "torch",
 ]
-requires-python = ">=3"
+requires-python = ">=3.10"
 authors = [{ email = "hzhangxyz@outlook.com", name = "Hao Zhang" }]
 description = "A Grassmann algebra tensor package"
 readme = "README.md"
 license = "GPL-3.0-or-later"
 
 [project.optional-dependencies]
 dev = [
-  "yapf",
-  "pylint",
   "mypy",
   "pytest",
   "pytest-cov",
+  "ruff",
 ]
 
 [tool.setuptools_scm]
 version_file = "grassmann_tensor/_version.py"
 version_scheme = "no-guess-dev"
 fallback_version = "0.0.0"
 
-[tool.yapf]
-based_on_style = "google"
-column_limit = 200
-
-[tool.pylint]
-max-line-length = 200
-ignore-paths = [
-  "grassmann_tensor/_version.py",
-  "tests/*",
-]
-
 [tool.mypy]
 disallow_untyped_calls = true
 disallow_untyped_defs = true
 disallow_incomplete_defs = true
 check_untyped_defs = true
+
+[tool.ruff]
+line-length = 100
+
+[tool.ruff.lint]
+select = ["E4", "E7", "E9", "F"]
+
+[tool.ruff.format]

tests/arithmetic_test.py

@@ -5,52 +5,69 @@
 from grassmann_tensor import GrassmannTensor
 
 
-@pytest.fixture(params=[
-    (
-        GrassmannTensor((False, False), ((2, 2), (1, 3)), torch.randn([4, 4])),
-        GrassmannTensor((False, False), ((2, 2), (1, 3)), torch.randn([4, 4])),
-    ),
-    (
-        GrassmannTensor((True, False, True), ((1, 1), (2, 2), (3, 1)), torch.randn([2, 4, 4])),
-        GrassmannTensor((True, False, True), ((1, 1), (2, 2), (3, 1)), torch.randn([2, 4, 4])),
-    ),
-    (
-        GrassmannTensor((True, True, False, False), ((1, 2), (2, 2), (1, 1), (3, 1)), torch.randn([3, 4, 2, 4])),
-        GrassmannTensor((True, True, False, False), ((1, 2), (2, 2), (1, 1), (3, 1)), torch.randn([3, 4, 2, 4])),
-    ),
-])
+@pytest.fixture(
+    params=[
+        (
+            GrassmannTensor((False, False), ((2, 2), (1, 3)), torch.randn([4, 4])),
+            GrassmannTensor((False, False), ((2, 2), (1, 3)), torch.randn([4, 4])),
+        ),
+        (
+            GrassmannTensor((True, False, True), ((1, 1), (2, 2), (3, 1)), torch.randn([2, 4, 4])),
+            GrassmannTensor((True, False, True), ((1, 1), (2, 2), (3, 1)), torch.randn([2, 4, 4])),
+        ),
+        (
+            GrassmannTensor(
+                (True, True, False, False),
+                ((1, 2), (2, 2), (1, 1), (3, 1)),
+                torch.randn([3, 4, 2, 4]),
+            ),
+            GrassmannTensor(
+                (True, True, False, False),
+                ((1, 2), (2, 2), (1, 1), (3, 1)),
+                torch.randn([3, 4, 2, 4]),
+            ),
+        ),
+    ]
+)
 def tensors(request: pytest.FixtureRequest) -> tuple[GrassmannTensor, GrassmannTensor]:
     return request.param
 
 
-@pytest.fixture(params=[
-    (
-        GrassmannTensor((False, False), ((2, 2), (1, 3)), torch.randn([4, 4])),
-        GrassmannTensor((False,), ((2, 2),), torch.randn([4])),
-    ),
-    (
-        GrassmannTensor((True, False, True), ((1, 1), (2, 2), (3, 1)), torch.randn([2, 4, 4])),
-        GrassmannTensor((True, False, True), ((1, 2), (2, 2), (3, 1)), torch.randn([3, 4, 4])),
-    ),
-    (
-        GrassmannTensor((True, True, False), ((1, 2), (2, 2), (3, 1)), torch.randn([3, 4, 4])),
-        GrassmannTensor((True, True, False, False), ((3, 2), (2, 2), (1, 1), (3, 1)), torch.randn([5, 4, 2, 4])),
-    ),
-])
+@pytest.fixture(
+    params=[
+        (
+            GrassmannTensor((False, False), ((2, 2), (1, 3)), torch.randn([4, 4])),
+            GrassmannTensor((False,), ((2, 2),), torch.randn([4])),
+        ),
+        (
+            GrassmannTensor((True, False, True), ((1, 1), (2, 2), (3, 1)), torch.randn([2, 4, 4])),
+            GrassmannTensor((True, False, True), ((1, 2), (2, 2), (3, 1)), torch.randn([3, 4, 4])),
+        ),
+        (
+            GrassmannTensor((True, True, False), ((1, 2), (2, 2), (3, 1)), torch.randn([3, 4, 4])),
+            GrassmannTensor(
+                (True, True, False, False),
+                ((3, 2), (2, 2), (1, 1), (3, 1)),
+                torch.randn([5, 4, 2, 4]),
+            ),
+        ),
+    ]
+)
 def mismatch_tensors(request: pytest.FixtureRequest) -> tuple[GrassmannTensor, GrassmannTensor]:
     return request.param
 
 
-@pytest.fixture(params=[
-    torch.randn([]),
-    torch.randn([]).item(),
-])
+@pytest.fixture(
+    params=[
+        torch.randn([]),
+        torch.randn([]).item(),
+    ]
+)
 def scalar(request: pytest.FixtureRequest) -> torch.Tensor | float:
     return request.param
 
 
 class FakeTensor:
-
     def __init__(self) -> None:
         pass
 
@@ -106,15 +123,20 @@ def __rtruediv__(self, other: typing.Any) -> FakeTensor:
 @pytest.mark.parametrize(
     "unsupported_type",
     [
-        "string",  #string
-        None,  #NoneType
-        {"key", "value"},  #dict
-        [1, 2, 3],  #list
-        {1, 2},  #set
-        object(),  #arbitrary object
-        FakeTensor(),  #an ill defined tensor-like object
-    ])
-def test_arithmetic(unsupported_type: typing.Any, tensors: tuple[GrassmannTensor, GrassmannTensor], scalar: torch.Tensor | float) -> None:
+        "string",  # string
+        None,  # NoneType
+        {"key", "value"},  # dict
+        [1, 2, 3],  # list
+        {1, 2},  # set
+        object(),  # arbitrary object
+        FakeTensor(),  # an ill defined tensor-like object
+    ],
+)
+def test_arithmetic(
+    unsupported_type: typing.Any,
+    tensors: tuple[GrassmannTensor, GrassmannTensor],
+    scalar: torch.Tensor | float,
+) -> None:
     tensor_a, tensor_b = tensors
 
     # Test __pos__ method.

tests/attributes_test.py

@@ -5,17 +5,19 @@
 Initialization = tuple[tuple[bool, ...], tuple[tuple[int, int], ...], torch.Tensor]
 
 
-@pytest.fixture(params=[
-    ((False, False), ((2, 2), (2, 2)), torch.randn([4, 4])),
-    ((False, True), ((2, 2), (1, 3)), torch.randn([4, 4])),
-    ((False, True), ((2, 0), (1, 3)), torch.randn([2, 4])),
-    ((True, False), ((0, 2), (1, 3)), torch.randn([2, 4])),
-    ((True, False), ((0, 0), (1, 3)), torch.randn([0, 4])),
-    ((True,), ((2, 0),), torch.randn([2])),
-    ((False,), ((0, 2),), torch.randn([2])),
-    ((), (), torch.randn([])),
-    ((False, False, True), ((2, 2), (1, 3), (4, 0)), torch.randn([4, 4, 4])),
-])
+@pytest.fixture(
+    params=[
+        ((False, False), ((2, 2), (2, 2)), torch.randn([4, 4])),
+        ((False, True), ((2, 2), (1, 3)), torch.randn([4, 4])),
+        ((False, True), ((2, 0), (1, 3)), torch.randn([2, 4])),
+        ((True, False), ((0, 2), (1, 3)), torch.randn([2, 4])),
+        ((True, False), ((0, 0), (1, 3)), torch.randn([0, 4])),
+        ((True,), ((2, 0),), torch.randn([2])),
+        ((False,), ((0, 2),), torch.randn([2])),
+        ((), (), torch.randn([])),
+        ((False, False, True), ((2, 2), (1, 3), (4, 0)), torch.randn([4, 4, 4])),
+    ]
+)
 def x(request: pytest.FixtureRequest) -> Initialization:
     return request.param
 
@@ -50,7 +52,9 @@ def test_mask(x: Initialization) -> None:
     tensor = GrassmannTensor(*x)
     assert tensor.mask.shape == tensor.tensor.shape
     assert tensor.mask.dtype == torch.bool
-    for indices in zip(*torch.unravel_index(torch.arange(tensor.tensor.numel()), tensor.tensor.shape)):
+    for indices in zip(
+        *torch.unravel_index(torch.arange(tensor.tensor.numel()), tensor.tensor.shape)
+    ):
         mask = tensor.mask[indices]
         expect = False
         for rank, parity in enumerate(tensor.parity):

tests/clone_test.py

@@ -37,7 +37,9 @@ def test_clone(
     if parity:
         assert cloned_tensor._parity is not None
         assert original_tensor._parity is not None
-        assert all(torch.equal(c, o) for c, o in zip(cloned_tensor._parity, original_tensor._parity))
+        assert all(
+            torch.equal(c, o) for c, o in zip(cloned_tensor._parity, original_tensor._parity)
+        )
     else:
         assert cloned_tensor._parity is original_tensor._parity
     if mask:

tests/conversion_test.py

@@ -47,7 +47,10 @@ def test_conversion(
     assert y.arrow == x.arrow
     assert y.edges == x.edges
     assert y.tensor.dtype == torch.complex128 if dtype_arg != "none" else torch.float32
-    assert y.tensor.device.type == (torch.device(device_str) if device_arg != "none" else torch.device("cpu:0")).type
+    assert (
+        y.tensor.device.type
+        == (torch.device(device_str) if device_arg != "none" else torch.device("cpu:0")).type
+    )
     assert torch.allclose(y.tensor, x.tensor.to(dtype=y.tensor.dtype, device=y.tensor.device))