A C++ financial pricing library required a Python interface for quantitative analysts to perform research and development.
The first attempt used a .NET assembly with pythonnet, but it suffered from poor performance and a lack of IDE support.
Pybind11 was selected over the Python/C API for its ability to minimize boilerplate code when creating direct C++ bindings.
The initial pybind11 implementation still lacked crucial features like type hints, Pythonic collections, and pickling support for multiprocessing.
PEP 484 and .pyi stub files provide a type interface for the C++ extension module, enabling autocompletion and navigation in IDEs.
Using std::variant simplifies function arguments and implementing magic methods like __iter__ makes C++ collections behave like native Python ones.
The copy_reg module is used to register custom serialization and deserialization functions, making C++ objects picklable for multiprocessing.
The final solution combines pybind11 with several enhancements, and a code generator is recommended to maintain the bindings for large projects.
The speaker answers audience questions about propagating C++ exceptions, comparing pybind11 to SWIG, and the specific code generator used.
fulfillmenttools
Köln, Germany
21:02Andy Terrel
25:29Diana Gastrin
26:28Nils Kasseckert
45:27Andreas Fertig
39:04Bobur Umurzokov
1:00:16Bjarne Stroustrup
1:01:15Bjarne Stroustrup
24:13Jonathan Müller
Jobs that call for the skills explored in this talk.
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