numpy 2.x scalar types np.float32 and others are no longer convertible

Commencez par le reproducer de test_module.cpp et les exemples de conversion de scalaires Python indiqués, puis suivez les convertisseurs rvalue intégrés de Boost.Python pour double, float, int et long, en particulier leurs chemins PyFloat_Check et PyLong_Check. Le travail est terminé lorsque le reproducer accepte les types scalaires NumPy décrits dans l'issue sans nécessiter de conversion Python explicite, tout en préservant le comportement existant pour les valeurs intégrées.

Summary

In NumPy 2.0, scalar types such as np.float32, np.int32, and np.int64 no longer subclass Python's built-in float or int (per
NEP 51). Boost.Python's built-in rvalue converters for C++ double, float, int, and long use PyFloat_Check / PyLong_Check, which return false for these NumPy scalars. The result is ArgumentError: Python argument types did not match C++ signature for any Boost.Python-wrapped function that previously accepted NumPy scalars via implicit conversion.

np.float64 is unaffected because it still subclasses Python float.

Reproducing

Put the following in test_module.cpp:

#include <boost/python.hpp>

double take_double(double x) { return x; }
float take_float(float x) { return x; }
int take_int(int x) { return x; }
long take_long(long x) { return x; }

BOOST_PYTHON_MODULE(test_module)
{
  using namespace boost::python;
  def("take_double", take_double);
  def("take_float", take_float);
  def("take_int", take_int);
  def("take_long", take_long);
}

Then do:

wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh -b -p $PWD/mc3
source mc3/etc/profile.d/conda.sh
conda create -y -p $PWD/env -c conda-forge python=3.11 "numpy>=2.0" libboost-python-devel gxx_linux-64
conda activate $PWD/env
$CXX -shared -fPIC -o test_module.so test_module.cpp -Ienv/include/python3.11 -Ienv/include -Lenv/lib -lboost_python311 -Wl,-rpath,env/lib
python -c "import numpy as np; import test_module; test_module.take_double(np.float32(1.5))"

The python script at the bottom of the issue gives some more types that don't convert.

Workaround

Users can explicitly convert before passing to Boost.Python:

func(float(np.float32(1.5)))   # works
func(int(np.int32(42)))        # works
func(np.float32(1.5).item())   # also works

I have implemented this in a few places and I'm sure many others have as well. See https://github.com/cctbx/cctbx_project/issues/1084

Longer python reproducer

import numpy as np
import test_module

# Show which numpy scalars still subclass builtins (the root cause)
for np_type in [np.float64, np.float32, np.float16,
                np.int64, np.int32, np.int16, np.int8]:
  builtin = float if np.issubdtype(np_type, np.floating) else int
  print("issubclass(%s, %s): %s" % (
    np_type.__name__, builtin.__name__, issubclass(np_type, builtin)))
print()

scalar_values = [
  np.float64(1.5),
  np.float32(1.5),
  np.float16(1.5),
  np.int64(42),
  np.int32(42),
  np.int16(42),
  np.int8(42),
  np.uint64(42),
  np.uint32(42),
]

functions = [
  (test_module.take_double, "take_double"),
  (test_module.take_float,  "take_float"),
  (test_module.take_int,    "take_int"),
  (test_module.take_long,   "take_long"),
]

for func, func_name in functions:
  for scalar in scalar_values:
    try:
      result = func(scalar)
      print("Pass", func_name, type(scalar))
    except Exception as e:
      print("Fail", func_name, type(scalar))