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Hello, thank you for creating this tool !
The following code:
import unittest
try:
import numpy # pylint: disable=unused-import
HAS_NUMPY = True
except ImportError:
HAS_NUMPY = False
@unittest.skipUnless(HAS_NUMPY, "This test requires the numpy library.")
class BrainNumpyCoreFromNumericTest(unittest.TestCase):
numpy_functions = (("sum", "[1, 2]"),)
def test_numpy_function_calls_inferred_as_ndarray(self):
"""
Test that calls to numpy functions are inferred as numpy.ndarray
"""
licit_array_types = (".ndarray",)
for func_ in self.numpy_functions:
with self.subTest(typ=func_):
inferred_values = list(self._inferred_numpy_func_call(*func_))
self.assertEqual(
len(inferred_values),
1,
msg=f"Too much inferred value for {func_[0]:s}",
)
self.assertIn(
inferred_values[-1].pytype(),
licit_array_types,
msg=f"Illicit type for {func_[0]:s} ({inferred_values[-1].pytype()})",
)Give the following result:
import pytest
try:
import numpy # pylint: disable=unused-import
HAS_NUMPY = True
except ImportError:
HAS_NUMPY = False
from astroid import builder
@pytest.mark.skipif(not HAS_NUMPY, "This test requires the numpy library.")
class TestBrainNumpyCoreFromNumeric:
"""
Test the numpy core fromnumeric brain module
"""
numpy_functions = (("sum", "[1, 2]"),)
def test_numpy_function_calls_inferred_as_ndarray(self):
"""
Test that calls to numpy functions are inferred as numpy.ndarray
"""
licit_array_types = (".ndarray",)
for func_ in self.numpy_functions:
with self.subTest(typ=func_):
inferred_values = list(self._inferred_numpy_func_call(*func_))
assert (
len(inferred_values) == 1
), f"Too much inferred value for {func_[0]:s}"
assert (
inferred_values[-1].pytype() in licit_array_types
), f"Illicit type for {func_[0]:s} ({inferred_values[-1].pytype()})"I think self.subTest(typ=func_): should be converted to a pytest.parametrize.
Reference documentation
Context : I'm trying to migrate astroid's test to pytest style, there's 36 subtests 😄
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