deps: Update dependency pyrefly to v1

pixi.toml

@@ -71,7 +71,7 @@ actionlint = ">=1.7.12,<2"
 blacken-docs = ">=1.20.0,<2"
 pytest = ">=9.0.3,<10"
 validate-pyproject = ">=0.25,<0.26"
-pyrefly = ">=0.63.1,<0.64"
+pyrefly = ">=1.0.0,<1.1"
 zizmor = ">=1.24.1,<1.25"
 # NOTE: don't add cupy, jax, pytorch, or sparse here,
 # as they slow down mypy and are not portable across target OSs

tests/test_funcs.py

@@ -140,7 +140,7 @@ def test_dtype_propagation(self, xp: ModuleType, library: Backend):
             cond,
             (x, y),
             self.f1,
-            lambda x, y: mxp.astype(x - y, xp.int64),  # pyright: ignore[reportArgumentType]
+            lambda x, y: mxp.astype(x - y, xp.int64),  # pyright: ignore[reportArgumentType] # pyrefly: ignore[bad-argument-type]
         )
         assert actual.dtype == xp.int64
 

tests/test_lazy.py

@@ -452,6 +452,6 @@ def f(x: Array) -> Array:
     with pytest.raises(ValueError, match="multiple shapes but only one dtype"):
         _ = lazy_apply(f, x, shape=[(1,), (2,)], dtype=np.int32)  # type: ignore[call-overload]  # pyright: ignore[reportCallIssue,reportArgumentType]
     with pytest.raises(ValueError, match="single shape but multiple dtypes"):
-        _ = lazy_apply(f, x, shape=(1,), dtype=[np.int32, np.int64])  # pyright: ignore[reportCallIssue,reportArgumentType]
+        _ = lazy_apply(f, x, shape=(1,), dtype=[np.int32, np.int64])  # pyright: ignore[reportCallIssue,reportArgumentType] # pyrefly: ignore[no-matching-overload]
     with pytest.raises(ValueError, match="2 shapes and 1 dtypes"):
         _ = lazy_apply(f, x, shape=[(1,), (2,)], dtype=[np.int32])  # type: ignore[arg-type]  # pyright: ignore[reportCallIssue,reportArgumentType]