pybind11-global 2.12.1

Core features

pybind11 can map the following core C++ features to Python:

• Functions accepting and returning custom data structures per value, reference, or pointer

• Instance methods and static methods

• Overloaded functions

• Instance attributes and static attributes

• Arbitrary exception types

• Enumerations

• Callbacks

• Iterators and ranges

• Custom operators

• Single and multiple inheritance

• STL data structures

• Smart pointers with reference counting like std::shared_ptr

• Internal references with correct reference counting

• C++ classes with virtual (and pure virtual) methods can be extended in Python

• Integrated NumPy support (NumPy 2 requires pybind11 2.12+)

Goodies

In addition to the core functionality, pybind11 provides some extra goodies:

• Python 3.6+, and PyPy3 7.3 are supported with an implementation-agnostic interface (pybind11 2.9 was the last version to support Python 2 and 3.5).

• It is possible to bind C++11 lambda functions with captured variables. The lambda capture data is stored inside the resulting Python function object.

• pybind11 uses C++11 move constructors and move assignment operators whenever possible to efficiently transfer custom data types.

• It’s easy to expose the internal storage of custom data types through Pythons’ buffer protocols. This is handy e.g. for fast conversion between C++ matrix classes like Eigen and NumPy without expensive copy operations.

• pybind11 can automatically vectorize functions so that they are transparently applied to all entries of one or more NumPy array arguments.

• Python’s slice-based access and assignment operations can be supported with just a few lines of code.

• Everything is contained in just a few header files; there is no need to link against any additional libraries.

• Binaries are generally smaller by a factor of at least 2 compared to equivalent bindings generated by Boost.Python. A recent pybind11 conversion of PyRosetta, an enormous Boost.Python binding project, reported a binary size reduction of 5.4x and compile time reduction by 5.8x.

• Function signatures are precomputed at compile time (using constexpr), leading to smaller binaries.

• With little extra effort, C++ types can be pickled and unpickled similar to regular Python objects.

Supported compilers

1. Clang/LLVM 3.3 or newer (for Apple Xcode’s clang, this is 5.0.0 or newer)

2. GCC 4.8 or newer

3. Microsoft Visual Studio 2017 or newer

4. Intel classic C++ compiler 18 or newer (ICC 20.2 tested in CI)

5. Cygwin/GCC (previously tested on 2.5.1)

6. NVCC (CUDA 11.0 tested in CI)

7. NVIDIA PGI (20.9 tested in CI)

About

This project was created by Wenzel Jakob. Significant features and/or improvements to the code were contributed by Jonas Adler, Lori A. Burns, Sylvain Corlay, Eric Cousineau, Aaron Gokaslan, Ralf Grosse-Kunstleve, Trent Houliston, Axel Huebl, @hulucc, Yannick Jadoul, Sergey Lyskov, Johan Mabille, Tomasz Miąsko, Dean Moldovan, Ben Pritchard, Jason Rhinelander, Boris Schäling, Pim Schellart, Henry Schreiner, Ivan Smirnov, Boris Staletic, and Patrick Stewart.

We thank Google for a generous financial contribution to the continuous integration infrastructure used by this project.