Clean up some tests and drop numpy 1 tests

.github/workflows/ci.yml

@@ -45,7 +45,7 @@ jobs:
           - py310
           - py311
           - py312
-          - np1x
+          - py313
     steps:
       - name: Checkout branch
         uses: actions/checkout@v4

ndonnx/_core/_numericimpl.py

@@ -1,4 +1,4 @@
-# Copyright (c) QuantCo 2023-2024
+# Copyright (c) QuantCo 2023-2025
 # SPDX-License-Identifier: BSD-3-Clause
 
 from __future__ import annotations

ndonnx/_core/_utils.py

@@ -1,4 +1,4 @@
-# Copyright (c) QuantCo 2023-2024
+# Copyright (c) QuantCo 2023-2025
 # SPDX-License-Identifier: BSD-3-Clause
 from __future__ import annotations
 
@@ -168,7 +168,7 @@ def via_upcast(
             via_dtype = int_dtype
         else:
             raise TypeError(
-                f"Can't upcast unsigned type `{dtype}`. Available implementations are for `{*available_types,}`"
+                f"Can't upcast unsigned type `{dtype}`. Available implementations are for `{(*available_types,)}`"
             )
     elif isinstance(dtype, (dtypes.Integral, dtypes.NullableIntegral)) or dtype in (
         dtypes.nbool,
@@ -178,7 +178,7 @@ def via_upcast(
             via_dtype = int_dtype
         else:
             raise TypeError(
-                f"Can't upcast signed type `{dtype}`. Available implementations are for `{*available_types,}`"
+                f"Can't upcast signed type `{dtype}`. Available implementations are for `{(*available_types,)}`"
             )
     elif isinstance(dtype, (dtypes.Floating, dtypes.NullableFloating)):
         if (
@@ -188,7 +188,7 @@ def via_upcast(
             via_dtype = float_dtype
         else:
             raise TypeError(
-                f"Can't upcast float type `{dtype}`. Available implementations are for `{*available_types,}`"
+                f"Can't upcast float type `{dtype}`. Available implementations are for `{(*available_types,)}`"
             )
     else:
         raise TypeError(f"Expected numerical data type, found {dtype}")

pixi.toml

@@ -74,16 +74,16 @@ python = "3.10.*"
 python = "3.11.*"
 [feature.py312.dependencies]
 python = "3.12.*"
-[feature.np1x.dependencies]
-python = "3.11.*"
-numpy = "1.*"
+[feature.py313.dependencies]
+python = "3.13.*"
+
 
 [environments]
 default = ["test", "lint"]
 py310 = ["py310", "test"]
 py311 = ["py311", "test"]
 py312 = ["py312", "test"]
-np1x = ["np1x", "test"]
+py313 = ["py313", "test"]
 docs = ["docs"]
 build = ["build"]
 lint = { features = ["lint"], no-default-feature = true }

pyproject.toml

@@ -20,6 +20,7 @@ classifiers = [
     "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",
+    "Programming Language :: Python :: 3.13",
 ]
 requires-python = ">=3.10"
 dependencies = ["numpy", "spox>=0.10", "typing_extensions"]

tests/test_core.py

@@ -1,4 +1,4 @@
-# Copyright (c) QuantCo 2023-2024
+# Copyright (c) QuantCo 2023-2025
 # SPDX-License-Identifier: BSD-3-Clause
 
 from __future__ import annotations
@@ -554,60 +554,6 @@ def test_all(x):
     assert_array_equal(ndx.all(x).to_numpy(), np.all(x.to_numpy()))
 
 
-@pytest.mark.parametrize(
-    "side",
-    [
-        "left",
-        "right",
-    ],
-)
-def test_searchsorted(side):
-    a_val = [0, 1, 2, 5, 5, 6, 10, 15]
-    b_val = [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 10, 15, 20, 20]
-    c_val = np.searchsorted(a_val, b_val, side)
-
-    a = ndx.asarray(a_val, dtype=ndx.int64)
-    b = ndx.asarray(b_val, dtype=ndx.int64)
-    c = ndx.searchsorted(a, b, side=side)
-    assert_array_equal(c_val, c.to_numpy())
-
-
-@pytest.mark.skip(reason="TODO: onnxruntime")
-@pytest.mark.parametrize(
-    "side",
-    [
-        "left",
-        "right",
-    ],
-)
-def test_searchsorted_nans(side):
-    a_val = np.array([0, 1, 2, 5, 5, 6, 10, 15, np.nan])
-    b_val = np.array([0, 1, 2, np.nan, np.nan])
-    c_val = np.searchsorted(a_val, b_val, side)
-
-    a = ndx.array(shape=(len(a_val),), dtype=ndx.float64)
-    b = ndx.array(shape=(len(b_val),), dtype=ndx.float64)
-    c = ndx.searchsorted(a, b, side=side)
-
-    model = ndx.build({"a": a, "b": b}, {"c": c})
-
-    assert_array_equal(c_val, run(model, dict(a=a_val, b=b_val))["c"])
-
-
-def test_searchsorted_raises():
-    with pytest.raises(TypeError):
-        a = ndx.array(shape=(), dtype=ndx.int64)
-        b = ndx.array(shape=(), dtype=ndx.float64)
-
-        ndx.searchsorted(a, b)
-
-    with pytest.raises(ValueError):
-        a = ndx.array(shape=(3,), dtype=ndx.int64)
-        b = ndx.array(shape=(3,), dtype=ndx.int64)
-
-        ndx.searchsorted(a, b, side="middle")  # type: ignore[arg-type]
-
-
 def test_truediv():
     x = ndx.asarray([1, 2, 3], dtype=ndx.int64)
     y = ndx.asarray([2, 3, 3], dtype=ndx.int64)

tests/test_iter.py

@@ -1,4 +1,4 @@
-# Copyright (c) QuantCo 2023-2024
+# Copyright (c) QuantCo 2023-2025
 # SPDX-License-Identifier: BSD-3-Clause
 
 import pytest
@@ -10,7 +10,7 @@ def test_iter_for_loop():
     n = 5
     a = ndx.array(shape=(n,), dtype=ndx.int64)
 
-    for i, el in enumerate(a):  # type: ignore
+    for i, el in enumerate(a):
         assert isinstance(el, ndx.Array)
         if i > n:
             assert False, "Iterated past the number of elements"