intro.rst revision 11986:c12e4625ab56
1.. image:: pybind11-logo.png 2 3About this project 4================== 5**pybind11** is a lightweight header-only library that exposes C++ types in Python 6and vice versa, mainly to create Python bindings of existing C++ code. Its 7goals and syntax are similar to the excellent `Boost.Python`_ library by David 8Abrahams: to minimize boilerplate code in traditional extension modules by 9inferring type information using compile-time introspection. 10 11.. _Boost.Python: http://www.boost.org/doc/libs/release/libs/python/doc/index.html 12 13The main issue with Boost.Python—and the reason for creating such a similar 14project—is Boost. Boost is an enormously large and complex suite of utility 15libraries that works with almost every C++ compiler in existence. This 16compatibility has its cost: arcane template tricks and workarounds are 17necessary to support the oldest and buggiest of compiler specimens. Now that 18C++11-compatible compilers are widely available, this heavy machinery has 19become an excessively large and unnecessary dependency. 20 21Think of this library as a tiny self-contained version of Boost.Python with 22everything stripped away that isn't relevant for binding generation. Without 23comments, the core header files only require ~2.5K lines of code and depend on 24Python (2.7 or 3.x) and the C++ standard library. This compact implementation 25was possible thanks to some of the new C++11 language features (specifically: 26tuples, lambda functions and variadic templates). Since its creation, this 27library has grown beyond Boost.Python in many ways, leading to dramatically 28simpler binding code in many common situations. 29 30Core features 31************* 32The following core C++ features can be mapped to Python 33 34- Functions accepting and returning custom data structures per value, reference, or pointer 35- Instance methods and static methods 36- Overloaded functions 37- Instance attributes and static attributes 38- Arbitrary exception types 39- Enumerations 40- Callbacks 41- Iterators and ranges 42- Custom operators 43- Single and multiple inheritance 44- STL data structures 45- Iterators and ranges 46- Smart pointers with reference counting like ``std::shared_ptr`` 47- Internal references with correct reference counting 48- C++ classes with virtual (and pure virtual) methods can be extended in Python 49 50Goodies 51******* 52In addition to the core functionality, pybind11 provides some extra goodies: 53 54- It is possible to bind C++11 lambda functions with captured variables. The 55 lambda capture data is stored inside the resulting Python function object. 56 57- pybind11 uses C++11 move constructors and move assignment operators whenever 58 possible to efficiently transfer custom data types. 59 60- It's easy to expose the internal storage of custom data types through 61 Pythons' buffer protocols. This is handy e.g. for fast conversion between 62 C++ matrix classes like Eigen and NumPy without expensive copy operations. 63 64- pybind11 can automatically vectorize functions so that they are transparently 65 applied to all entries of one or more NumPy array arguments. 66 67- Python's slice-based access and assignment operations can be supported with 68 just a few lines of code. 69 70- Everything is contained in just a few header files; there is no need to link 71 against any additional libraries. 72 73- Binaries are generally smaller by a factor of at least 2 compared to 74 equivalent bindings generated by Boost.Python. A recent pybind11 conversion 75 of `PyRosetta`_, an enormous Boost.Python binding project, reported a binary 76 size reduction of **5.4x** and compile time reduction by **5.8x**. 77 78- When supported by the compiler, two new C++14 features (relaxed constexpr and 79 return value deduction) are used to precompute function signatures at compile 80 time, leading to smaller binaries. 81 82- With little extra effort, C++ types can be pickled and unpickled similar to 83 regular Python objects. 84 85.. _PyRosetta: http://graylab.jhu.edu/RosettaCon2016/PyRosetta-4.pdf 86 87Supported compilers 88******************* 89 901. Clang/LLVM (any non-ancient version with C++11 support) 912. GCC (any non-ancient version with C++11 support) 923. Microsoft Visual Studio 2015 or newer 934. Intel C++ compiler v15 or newer 94