Port tests to pytest
Use simple asserts and pytest's powerful introspection to make testing
simpler. This merges the old .py/.ref file pairs into simple .py files
where the expected values are right next to the code being tested.
This commit does not touch the C++ part of the code and replicates the
Python tests exactly like the old .ref-file-based approach.
diff --git a/tests/test_numpy_vectorize.py b/tests/test_numpy_vectorize.py
new file mode 100644
index 0000000..6fcf808
--- /dev/null
+++ b/tests/test_numpy_vectorize.py
@@ -0,0 +1,80 @@
+import pytest
+
+with pytest.suppress(ImportError):
+ import numpy as np
+
+
+@pytest.requires_numpy
+def test_vectorize(capture):
+ from pybind11_tests import vectorized_func, vectorized_func2, vectorized_func3
+
+ assert np.isclose(vectorized_func3(np.array(3 + 7j)), [6 + 14j])
+
+ for f in [vectorized_func, vectorized_func2]:
+ with capture:
+ assert np.isclose(f(1, 2, 3), 6)
+ assert capture == "my_func(x:int=1, y:float=2, z:float=3)"
+ with capture:
+ assert np.isclose(f(np.array(1), np.array(2), 3), 6)
+ assert capture == "my_func(x:int=1, y:float=2, z:float=3)"
+ with capture:
+ assert np.allclose(f(np.array([1, 3]), np.array([2, 4]), 3), [6, 36])
+ assert capture == """
+ my_func(x:int=1, y:float=2, z:float=3)
+ my_func(x:int=3, y:float=4, z:float=3)
+ """
+ with capture:
+ a, b, c = np.array([[1, 3, 5], [7, 9, 11]]), np.array([[2, 4, 6], [8, 10, 12]]), 3
+ assert np.allclose(f(a, b, c), a * b * c)
+ assert capture == """
+ my_func(x:int=1, y:float=2, z:float=3)
+ my_func(x:int=3, y:float=4, z:float=3)
+ my_func(x:int=5, y:float=6, z:float=3)
+ my_func(x:int=7, y:float=8, z:float=3)
+ my_func(x:int=9, y:float=10, z:float=3)
+ my_func(x:int=11, y:float=12, z:float=3)
+ """
+ with capture:
+ a, b, c = np.array([[1, 2, 3], [4, 5, 6]]), np.array([2, 3, 4]), 2
+ assert np.allclose(f(a, b, c), a * b * c)
+ assert capture == """
+ my_func(x:int=1, y:float=2, z:float=2)
+ my_func(x:int=2, y:float=3, z:float=2)
+ my_func(x:int=3, y:float=4, z:float=2)
+ my_func(x:int=4, y:float=2, z:float=2)
+ my_func(x:int=5, y:float=3, z:float=2)
+ my_func(x:int=6, y:float=4, z:float=2)
+ """
+ with capture:
+ a, b, c = np.array([[1, 2, 3], [4, 5, 6]]), np.array([[2], [3]]), 2
+ assert np.allclose(f(a, b, c), a * b * c)
+ assert capture == """
+ my_func(x:int=1, y:float=2, z:float=2)
+ my_func(x:int=2, y:float=2, z:float=2)
+ my_func(x:int=3, y:float=2, z:float=2)
+ my_func(x:int=4, y:float=3, z:float=2)
+ my_func(x:int=5, y:float=3, z:float=2)
+ my_func(x:int=6, y:float=3, z:float=2)
+ """
+
+
+@pytest.requires_numpy
+def test_type_selection(capture):
+ from pybind11_tests import selective_func
+
+ with capture:
+ selective_func(np.array([1], dtype=np.int32))
+ selective_func(np.array([1.0], dtype=np.float32))
+ selective_func(np.array([1.0j], dtype=np.complex64))
+ assert capture == """
+ Int branch taken.
+ Float branch taken.
+ Complex float branch taken.
+ """
+
+
+@pytest.requires_numpy
+def test_docs(doc):
+ from pybind11_tests import vectorized_func
+
+ assert doc(vectorized_func) == "vectorized_func(arg0: numpy.ndarray[int], arg1: numpy.ndarray[float], arg2: numpy.ndarray[float]) -> object"