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Currently pybind11 always translates values returned by Python functions invoked from C++ code by copying, even when moving is feasible--and, more importantly, even when moving is required. The first, and relatively minor, concern is that moving may be considerably more efficient for some types. The second problem, however, is more serious: there's currently no way python code can return a non-copyable type to C++ code. I ran into this while trying to add a PYBIND11_OVERLOAD of a virtual method that returns just such a type: it simply fails to compile because this: overload = ... overload(args).template cast<ret_type>(); involves a copy: overload(args) returns an object instance, and the invoked object::cast() loads the returned value, then returns a copy of the loaded value. We can, however, safely move that returned value *if* the object has the only reference to it (i.e. if ref_count() == 1) and the object is itself temporary (i.e. if it's an rvalue). This commit does that by adding an rvalue-qualified object::cast() method that allows the returned value to be move-constructed out of the stored instance when feasible. This basically comes down to three cases: - For objects that are movable but not copyable, we always try the move, with a runtime exception raised if this would involve moving a value with multiple references. - When the type is both movable and non-trivially copyable, the move happens only if the invoked object has a ref_count of 1, otherwise the object is copied. (Trivially copyable types are excluded from this case because they are typically just collections of primitive types, which can be copied just as easily as they can be moved.) - Non-movable and trivially copy constructible objects are simply copied. This also adds examples to example-virtual-functions that shows both a non-copyable object and a movable/copyable object in action: the former raises an exception if returned while holding a reference, the latter invokes a move constructor if unreferenced, or a copy constructor if referenced. Basically this allows code such as: class MyClass(Pybind11Class): def somemethod(self, whatever): mt = MovableType(whatever) # ... return mt which allows the MovableType instance to be returned to the C++ code via its move constructor. Of course if you attempt to violate this by doing something like: self.value = MovableType(whatever) return self.value you get an exception--but right now, the pybind11-side of that code won't compile at all. |
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example | ||
include/pybind11 | ||
pybind11 | ||
tools | ||
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.gitignore | ||
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CMakeLists.txt | ||
CONTRIBUTING.md | ||
LICENSE | ||
MANIFEST.in | ||
README.md | ||
setup.cfg | ||
setup.py |
pybind11 — Seamless operability between C++11 and Python
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 ~2.5K lines of code and depend on Python (2.7 or 3.x) 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 http://pybind11.readthedocs.org/en/latest. A PDF version of the manual is available here.
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
- Custom operators
- STL data structures
- Iterators and ranges
- 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:
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pybind11 uses C++11 move constructors and move assignment operators whenever possible to efficiently transfer custom data types.
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It is possible to bind C++11 lambda functions with captured variables. The lambda capture data is stored inside the resulting Python function object.
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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.
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pybind11 can automatically vectorize functions so that they are transparently applied to all entries of one or more NumPy array arguments.
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Python's slice-based access and assignment operations can be supported with just a few lines of code.
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Everything is contained in just a few header files; there is no need to link against any additional libraries.
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Binaries are generally smaller by a factor of 2 or more compared to equivalent bindings generated by Boost.Python.
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When supported by the compiler, two new C++14 features (relaxed constexpr and return value deduction) are used to precompute function signatures at compile time, leading to smaller binaries.
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With little extra effort, C++ types can be pickled and unpickled similar to regular Python objects.
Supported compilers
- Clang/LLVM (any non-ancient version with C++11 support)
- GCC (any non-ancient version with C++11 support)
- Microsoft Visual Studio 2015 or newer
- Intel C++ compiler 16 or newer (15 with a workaround)
- Cygwin/GCC (tested on 2.5.1)
About
This project was created by Wenzel Jakob. Significant features and/or improvements to the code were contributed by Jonas Adler, Sylvain Corlay, Axel Huebl, @hulucc, Sergey Lyskov Johan Mabille, Tomasz Miąsko, Dean Moldovan, Ben Pritchard, Boris Schäling, and Pim Schellart.
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.