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pybind11rosettacommons 2.6.0
pybind11 — Seamless operability between C++11 and Python
Warning
Combining older versions of pybind11 (< 2.6.0) with the brand-new Python
3.9.0 will trigger undefined behavior that typically manifests as crashes
during interpreter shutdown (but could also destroy your data. You have been
warned.)
We recommend that you wait for Python 3.9.1 slated for release in December,
which will include a fix
that resolves this problem. In the meantime, please update to the latest
version of pybind11 (2.6.0 or newer), which includes a temporary workaround
specifically when Python 3.9.0 is detected at runtime.
pybind11 is 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 excellent
Boost.Python
library 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 (2.7 or 3.5+, 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 at
pybind11.readthedocs.io.
A PDF version of the manual is available
here.
And the source code is always available at
github.com/pybind/pybind11.
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
Goodies
In addition to the core functionality, pybind11 provides some extra
goodies:
Python 2.7, 3.5+, and PyPy/PyPy3 7.3 are supported with an
implementation-agnostic interface.
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
Clang/LLVM 3.3 or newer (for Apple Xcode’s clang, this is 5.0.0 or
newer)
GCC 4.8 or newer
Microsoft Visual Studio 2015 Update 3 or newer
Intel C++ compiler 18 or newer
(possible issue on 20.2)
Cygwin/GCC (tested on 2.5.1)
NVCC (CUDA 11.0 tested)
NVIDIA PGI (20.7 and 20.9 tested)
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, 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.
Contributing
See the contributing
guide
for information on building and contributing to pybind11.
License
pybind11 is provided under a BSD-style license that can be found in the
LICENSE
file. By using, distributing, or contributing to this project, you agree
to the terms and conditions of this license.
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
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