Source: python-hypothesis Version: 6.64.0-1 Severity: serious User: debian...@lists.debian.org Usertags: regression
Hi Maintainer Recently, the autopkgtests of python-hypothesis regressed in testing [1]. I've copied what I hope is the relevant part of the log below. Regards Graham [1] https://ci.debian.net/packages/p/python-hypothesis/testing/amd64/ =================================== FAILURES =================================== _______________ test_overflowing_integers_are_deprecated[False] ________________ fill = False > ??? tests/numpy/test_gen_data.py:347: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ tests/common/utils.py:102: in inverted_test f(*arguments, **kwargs) tests/numpy/test_gen_data.py:347: in test_overflowing_integers_are_deprecated ??? tests/numpy/test_gen_data.py:354: in test_overflowing_integers_are_deprecated arr = data.draw(nps.arrays(dtype="int8", shape=(1,), **kw)) /usr/lib/python3/dist-packages/hypothesis/strategies/_internal/core.py:1836: in draw result = self.conjecture_data.draw(strategy) /usr/lib/python3/dist-packages/hypothesis/internal/conjecture/data.py:946: in draw return strategy.do_draw(self) /usr/lib/python3/dist-packages/hypothesis/strategies/_internal/lazy.py:156: in do_draw return data.draw(self.wrapped_strategy) /usr/lib/python3/dist-packages/hypothesis/internal/conjecture/data.py:941: in draw return strategy.do_draw(self) /usr/lib/python3/dist-packages/hypothesis/extra/numpy.py:324: in do_draw self.set_element(data.draw(self.fill), one_element, 0, fill=True) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = <hypothesis.extra.numpy.ArrayStrategy object at 0x7f3c03eefdc0> val = 300, result = array([44], dtype=int8), idx = 0 def set_element(self, val, result, idx, *, fill=False): try: result[idx] = val except TypeError as err: raise InvalidArgument( f"Could not add element={val!r} of {val.dtype!r} to array of " f"{result.dtype!r} - possible mismatch of time units in dtypes?" ) from err try: elem_changed = self._check_elements and val != result[idx] and val == val except Exception as err: # pragma: no cover # This branch only exists to help debug weird behaviour in Numpy, # such as the string problems we had a while back. raise HypothesisException( "Internal error when checking element=%r of %r to array of %r" % (val, val.dtype, result.dtype) ) from err if elem_changed: strategy = self.fill if fill else self.element_strategy if self.dtype.kind == "f": # pragma: no cover # This logic doesn't trigger in our coverage tests under Numpy 1.24+, # with built-in checks for overflow, but we keep it for good error # messages and compatibility with older versions of Numpy. try: is_subnormal = 0 < abs(val) < np.finfo(self.dtype).tiny except Exception: # val may be a non-float that does not support the # operations __lt__ and __abs__ is_subnormal = False if is_subnormal: raise InvalidArgument( f"Generated subnormal float {val} from strategy " f"{strategy} resulted in {result[idx]!r}, probably " "as a result of NumPy being built with flush-to-zero " "compiler options. Consider passing " "allow_subnormal=False." ) > raise InvalidArgument( "Generated array element %r from %r cannot be represented as " "dtype %r - instead it becomes %r (type %r). Consider using a more " "precise strategy, for example passing the `width` argument to " "`floats()`." % (val, strategy, self.dtype, result[idx], type(result[idx])) ) E hypothesis.errors.InvalidArgument: Generated array element 300 from just(300) cannot be represented as dtype dtype('int8') - instead it becomes 44 (type <class 'numpy.int8'>). Consider using a more precise strategy, for example passing the `width` argument to `floats()`. E Falsifying example: test_overflowing_integers_are_deprecated( E data=data(...), E fill=False, E ) /usr/lib/python3/dist-packages/hypothesis/extra/numpy.py:229: InvalidArgument ________________ test_overflowing_integers_are_deprecated[True] ________________ fill = True > ??? tests/numpy/test_gen_data.py:347: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ tests/common/utils.py:102: in inverted_test f(*arguments, **kwargs) tests/numpy/test_gen_data.py:347: in test_overflowing_integers_are_deprecated ??? tests/numpy/test_gen_data.py:354: in test_overflowing_integers_are_deprecated arr = data.draw(nps.arrays(dtype="int8", shape=(1,), **kw)) /usr/lib/python3/dist-packages/hypothesis/strategies/_internal/core.py:1836: in draw result = self.conjecture_data.draw(strategy) /usr/lib/python3/dist-packages/hypothesis/internal/conjecture/data.py:946: in draw return strategy.do_draw(self) /usr/lib/python3/dist-packages/hypothesis/strategies/_internal/lazy.py:156: in do_draw return data.draw(self.wrapped_strategy) /usr/lib/python3/dist-packages/hypothesis/internal/conjecture/data.py:941: in draw return strategy.do_draw(self) /usr/lib/python3/dist-packages/hypothesis/extra/numpy.py:324: in do_draw self.set_element(data.draw(self.fill), one_element, 0, fill=True) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = <hypothesis.extra.numpy.ArrayStrategy object at 0x7f3c083d0d30> val = 300, result = array([44], dtype=int8), idx = 0 def set_element(self, val, result, idx, *, fill=False): try: result[idx] = val except TypeError as err: raise InvalidArgument( f"Could not add element={val!r} of {val.dtype!r} to array of " f"{result.dtype!r} - possible mismatch of time units in dtypes?" ) from err try: elem_changed = self._check_elements and val != result[idx] and val == val except Exception as err: # pragma: no cover # This branch only exists to help debug weird behaviour in Numpy, # such as the string problems we had a while back. raise HypothesisException( "Internal error when checking element=%r of %r to array of %r" % (val, val.dtype, result.dtype) ) from err if elem_changed: strategy = self.fill if fill else self.element_strategy if self.dtype.kind == "f": # pragma: no cover # This logic doesn't trigger in our coverage tests under Numpy 1.24+, # with built-in checks for overflow, but we keep it for good error # messages and compatibility with older versions of Numpy. try: is_subnormal = 0 < abs(val) < np.finfo(self.dtype).tiny except Exception: # val may be a non-float that does not support the # operations __lt__ and __abs__ is_subnormal = False if is_subnormal: raise InvalidArgument( f"Generated subnormal float {val} from strategy " f"{strategy} resulted in {result[idx]!r}, probably " "as a result of NumPy being built with flush-to-zero " "compiler options. Consider passing " "allow_subnormal=False." ) > raise InvalidArgument( "Generated array element %r from %r cannot be represented as " "dtype %r - instead it becomes %r (type %r). Consider using a more " "precise strategy, for example passing the `width` argument to " "`floats()`." % (val, strategy, self.dtype, result[idx], type(result[idx])) ) E hypothesis.errors.InvalidArgument: Generated array element 300 from just(300) cannot be represented as dtype dtype('int8') - instead it becomes 44 (type <class 'numpy.int8'>). Consider using a more precise strategy, for example passing the `width` argument to `floats()`. E Falsifying example: test_overflowing_integers_are_deprecated( E data=data(...), E fill=True, E ) /usr/lib/python3/dist-packages/hypothesis/extra/numpy.py:229: InvalidArgument
