Switch to ty for type checking

Author: gerlero

.github/workflows/ci.yml

@@ -36,11 +36,9 @@ jobs:
       uses: actions/setup-python@v6
       with:
         python-version-file: pyproject.toml
-    - name: Check types with mypy
+    - name: Check types with ty
       run: |
-        uv add pip
-        uv run mypy --install-types --non-interactive
-        uv run mypy
+        uv run ty check
 
   test:
     runs-on: ubuntu-22.04

CONTRIBUTING.md

@@ -64,7 +64,7 @@ pytest
 Type check the code with:
 
 ```bash
-mypy
+ty check
 ```
 
 ### Linting

README.md

@@ -3,8 +3,8 @@
 [![Documentation](https://img.shields.io/readthedocs/foamlib)](https://foamlib.readthedocs.io/)
 [![CI](https://github.com/gerlero/foamlib/actions/workflows/ci.yml/badge.svg)](https://github.com/gerlero/foamlib/actions/workflows/ci.yml)
 [![Codecov](https://codecov.io/gh/gerlero/foamlib/branch/main/graph/badge.svg)](https://codecov.io/gh/gerlero/foamlib)
-[![Checked with mypy](http://www.mypy-lang.org/static/mypy_badge.svg)](http://mypy-lang.org/)
 [![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)
+[![ty](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ty/main/assets/badge/v0.json)](https://github.com/astral-sh/ty)
 [![uv](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/uv/main/assets/badge/v0.json)](https://github.com/astral-sh/uv)
 [![Publish](https://github.com/gerlero/foamlib/actions/workflows/pypi-publish.yml/badge.svg)](https://github.com/gerlero/foamlib/actions/workflows/pypi-publish.yml)
 [![PyPI](https://img.shields.io/pypi/v/foamlib)](https://pypi.org/project/foamlib/)

examples/basic/diffusioncheck.py

@@ -136,7 +136,7 @@
 y = y[end]
 z = z[end]
 
-DT = case.transport_properties["DT"].value
+DT = case.transport_properties["DT"].value  # ty: ignore[possibly-unbound-attribute]
 U = case[0]["U"].internal_field[0]
 
 for time in case[1:]:

examples/parametricStudy/createStudyGrid.py

@@ -3,7 +3,7 @@
 from foamlib.preprocessing.grid_parameter_sweep import CaseParameter, GridParameter
 from foamlib.preprocessing.of_dict import FoamDictInstruction
 from foamlib.preprocessing.parameter_study import grid_generator
-from foamlib.preprocessing.system import simulationParameters
+from foamlib.preprocessing.system import simulation_parameters
 
 # damBreak
 root = Path(__file__).parent
@@ -28,7 +28,7 @@ def grid_parameters(scale) -> list[int]:
     #     file_name=Path("system/simulationParameters"),
     #     keys=[f"res{i}"],
     # )
-    modify_dict=[simulationParameters(keys=[f"res{i}"]) for i in range(1, 6)],
+    modify_dict=[simulation_parameters(keys=[f"res{i}"]) for i in range(1, 6)],
     parameters=[
         CaseParameter(name="coarse", values=grid_parameters(1)),
         CaseParameter(name="mid", values=grid_parameters(2)),
@@ -38,7 +38,7 @@ def grid_parameters(scale) -> list[int]:
 
 init_height = GridParameter(
     parameter_name="initHeight",
-    modify_dict=[simulationParameters(keys=["initHeight"])],
+    modify_dict=[simulation_parameters(keys=["initHeight"])],
     parameters=[
         CaseParameter(name="height_02", values=[0.2]),
         CaseParameter(name="height_03", values=[0.3]),

examples/parametricStudy/gatherResults.py

@@ -15,7 +15,7 @@
 out_files = list_function_objects(root / "Cases")
 
 
-def max_height_filter(table: pd.DataFrame, parameters: dict[str, str]) -> pd.DataFrame:
+def max_height_filter(table: pd.DataFrame, parameters: list[dict[str, str]]) -> pd.DataFrame:
     """Filter the table to get the maximum height."""
     d = {
         "x": [table["x"].max()],
@@ -31,21 +31,24 @@ def max_height_filter(table: pd.DataFrame, parameters: dict[str, str]) -> pd.Dat
     source=out_files["forces--force.dat"], dir_name=root / "Cases"
 )
 # %%
+assert forces is not None
 forces.to_csv(
     results / "forces.csv",
     index=False,
 )
 
 probe_u = load_tables(source=out_files["probes--U"], dir_name=root / "Cases")
+assert probe_u is not None
 probe_u.to_csv(
     results / "probe_u.csv",
     index=False,
 )
 
-file = DataSource(file_name="U_freeSurface.raw", folder="freeSurface")
+file = DataSource(file_name="U_freeSurface.raw", folder="freeSurface")  # ty: ignore[missing-argument]
 surface_heights = load_tables(
     source=file, dir_name=root / "Cases", filter_table=max_height_filter
 )
+assert surface_heights is not None
 surface_heights.to_csv(
     results / "surface_heights.csv",
     index=False,

foamlib/_cases/_subprocess.py

@@ -103,9 +103,9 @@ def run_sync(
                         timeout=0.1
                     ):  # Small timeout to allow log monitoring
                         assert key.fileobj in open_streams
-                        if not (line := key.fileobj.readline()):  # type: ignore [union-attr]
+                        if not (line := key.fileobj.readline()):
                             selector.unregister(key.fileobj)
-                            open_streams.remove(key.fileobj)  # type: ignore [arg-type]
+                            open_streams.remove(key.fileobj)
                         elif key.fileobj is proc.stdout:
                             process_stdout(line)
                             if output is not None:

foamlib/_cases/async_.py

@@ -150,7 +150,7 @@ async def _run(
     async def _rmtree(
         path: os.PathLike[str] | str, *, ignore_errors: bool = False
     ) -> None:
-        await aioshutil.rmtree(path, ignore_errors=ignore_errors)  # type: ignore [call-arg]
+        await aioshutil.rmtree(path, ignore_errors=ignore_errors)
 
     @override
     @staticmethod

foamlib/_files/_parsing/parsed.py

@@ -121,7 +121,7 @@ def put(
         self._remove_child_entries(keywords)
 
     @override
-    def add(  # type: ignore[override]
+    def add(
         self,
         keywords: tuple[str, ...],
         data: Data | StandaloneData | EllipsisType,

foamlib/_files/_serialization.py

@@ -56,10 +56,10 @@ def normalize(
     bool_ok: bool = True,
 ) -> Data | StandaloneData | SubDict:
     if isinstance(data, Mapping):
-        items = ((normalize(k, bool_ok=False), normalize(v)) for k, v in data.items())  # type: ignore [arg-type, misc]
+        items = ((normalize(k, bool_ok=False), normalize(v)) for k, v in data.items())
         if keywords is None:
-            return as_dict_check_unique(items)  # type: ignore [arg-type]
-        ret1: SubDict = MultiDict(items)  # type: ignore [arg-type]
+            return as_dict_check_unique(items)
+        ret1: SubDict = MultiDict(items)
         seen = set()
         for k, v in ret1.items():
             if k.startswith("#"):
@@ -112,7 +112,7 @@ def normalize(
                 if arr.ndim == 1 or (arr.ndim == 2 and arr.shape[1] in (3, 6, 9)):
                     return arr
 
-            return [normalize(d) for d in data]  # type: ignore [arg-type, return-value]
+            return [normalize(d) for d in data]
 
         if isinstance(data, int):
             return float(data)
@@ -122,7 +122,7 @@ def normalize(
     if isinstance(data, np.ndarray):
         ret2 = data.tolist()
         assert isinstance(ret2, (int, float, list))
-        return ret2  # type: ignore [return-value]
+        return ret2
 
     if (
         not isinstance(data, DimensionSet)
@@ -139,19 +139,19 @@ def normalize(
         if isinstance(k2, Mapping):
             msg = "Keyword in keyword entry cannot be a dictionary"
             raise ValueError(msg)
-        k2 = normalize(k2, bool_ok=False)  # type: ignore [arg-type]
-        v2 = normalize(v2)  # type: ignore [arg-type]
-        return (k2, v2)  # type: ignore [return-value]
+        k2 = normalize(k2, bool_ok=False)
+        v2 = normalize(v2)
+        return (k2, v2)
 
     if (
         is_sequence(data)
         and not isinstance(data, DimensionSet)
         and not isinstance(data, tuple)
     ):
-        return [normalize(d) for d in data]  # type: ignore [arg-type, return-value]
+        return [normalize(d) for d in data]
 
     if isinstance(data, tuple) and not isinstance(data, DimensionSet):
-        return tuple(normalize(d, keywords=keywords) for d in data)  # type: ignore [misc]
+        return tuple(normalize(d, keywords=keywords) for d in data)
 
     if isinstance(data, str):
         with contextlib.suppress(ValueError, KeyError):
@@ -178,7 +178,7 @@ def dumps(
     header: SubDictLike | None = None,
     tuple_is_keyword_entry: bool = False,
 ) -> bytes:
-    data = normalize(data, keywords=keywords)  # type: ignore [arg-type, misc]
+    data = normalize(data, keywords=keywords)
 
     if isinstance(data, Mapping):
         return (
@@ -287,7 +287,7 @@ def dumps(
 
     if is_sequence(data):
         return (
-            b"(" + b" ".join(dumps(v, tuple_is_keyword_entry=True) for v in data) + b")"  # type: ignore [arg-type]
+            b"(" + b" ".join(dumps(v, tuple_is_keyword_entry=True) for v in data) + b")"
         )
 
     if data is True: