Package: pybind11-global
pybind11 — Seamless operability between C++11 and PythonSetuptools example•Scikit-build example•CMake examplepybind11is a lightweight header-only library that exposes C++ types
in Python and vice versa, mainly to create Python bindings of existing
C++ code. Its goals and syntax are similar to the excellentBoost.Pythonlibrary by David Abrahams: to minimize boilerplate code in traditional
extension modules by inferring type information using compile-time
introspection.The main issue with Boost.Python—and the reason for creating such a
similar project—is Boost. Boost is an enormously large and complex suite
of utility libraries that works with almost every C++ compiler in
existence. This compatibility has its cost: arcane template tricks and
workarounds are necessary to support the oldest and buggiest of compiler
specimens. Now that C++11-compatible compilers are widely available,
this heavy machinery has become an excessively large and unnecessary
dependency.Think of this library as a tiny self-contained version of Boost.Python
with everything stripped away that isn’t relevant for binding
generation. Without comments, the core header files only require ~4K
lines of code and depend on Python (3.6+, or PyPy) and the C++
standard library. This compact implementation was possible thanks to
some of the new C++11 language features (specifically: tuples, lambda
functions and variadic templates). Since its creation, this library has
grown beyond Boost.Python in many ways, leading to dramatically simpler
binding code in many common situations.Tutorial and reference documentation is provided atpybind11.readthedocs.io.
A PDF version of the manual is availablehere.
And the source code is always available atgithub.com/pybind/pybind11.Core featurespybind11 can map the following core C++ features to Python:Functions accepting and returning custom data structures per value,
reference, or pointerInstance methods and static methodsOverloaded functionsInstance attributes and static attributesArbitrary exception typesEnumerationsCallbacksIterators and rangesCustom operatorsSingle and multiple inheritanceSTL data structuresSmart pointers with reference counting likestd::shared_ptrInternal references with correct reference countingC++ classes with virtual (and pure virtual) methods can be extended
in PythonGoodiesIn 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,reporteda binary size reduction of5.4xand compile time reduction by5.8x.Function signatures are precomputed at compile time (usingconstexpr), leading to smaller binaries.With little extra effort, C++ types can be pickled and unpickled
similar to regular Python objects.Supported compilersClang/LLVM 3.3 or newer (for Apple Xcode’s clang, this is 5.0.0 or
newer)GCC 4.8 or newerMicrosoft Visual Studio 2017 or newerIntel classic C++ compiler 18 or newer (ICC 20.2 tested in CI)Cygwin/GCC (previously tested on 2.5.1)NVCC (CUDA 11.0 tested in CI)NVIDIA PGI (20.9 tested in CI)AboutThis project was created byWenzel
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.ContributingSee thecontributing
guidefor information on building and contributing to pybind11.Licensepybind11 is provided under a BSD-style license that can be found in theLICENSEfile. By using, distributing, or contributing to this project, you agree
to the terms and conditions of this license.