Use hypothesis for tests

buildscripts/incremental/build.cmd

@@ -1,6 +1,6 @@
 
 call activate %CONDA_ENV%
 
-python -m pip install -e .
+python -m pip install -e .[dev]
 
 if %errorlevel% neq 0 exit /b %errorlevel%

buildscripts/incremental/build.sh

@@ -5,4 +5,4 @@ source activate $CONDA_ENV
 # Make sure any error below is reported as such
 set -v -e
 
-python -m pip install -e .
+python -m pip install -e .[dev]

numba_scipy/tests/test_special.py

@@ -1,17 +1,31 @@
 """Tests the scipy.special bindings
 """
-import numba_scipy.special # noqa
+import numba_scipy.special  # noqa
 from scipy.special import beta
 from numba import njit
 import numpy as np
 
+from hypothesis import given, settings
+import hypothesis.strategies as st
+from hypothesis.extra.numpy import arrays as st_arrays
 
-def test_beta():
 
+@given(st.floats(0, 20), st.floats(0, 20))
+def test_beta_scalars(x, y):
+    @njit
+    def test_impl(a, b):
+        return beta(a, b)
+
+    np.testing.assert_allclose(test_impl(x, y), test_impl.py_func(x, y))
+
+
+@given(
+    st_arrays(np.float, 10, st.floats(0, 20)), st_arrays(np.float, 10, st.floats(0, 20))
+)
+@settings(deadline=None)
+def test_beta_arrays(x, y):
     @njit
     def test_impl(a, b):
         return beta(a, b)
 
-    x = np.linspace(0, 20, 50)
-    y = x[::-1]
     np.testing.assert_allclose(test_impl(x, y), test_impl.py_func(x, y))

setup.py

@@ -29,6 +29,12 @@
     packages=['numba_scipy'],
     setup_requires=[],
     install_requires=_install_requires,
+    extras_require={
+        "dev": [
+            "pytest",
+            "hypothesis[numpy]",
+        ],
+    },
     license="BSD",
     zip_safe=False,
     )