| About this project |
| ================== |
| **pybind11** is a lightweight header 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. |
| |
| .. _Boost.Python: http://www.boost.org/doc/libs/release/libs/python/doc/index.html |
| |
| 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. The whole |
| codebase requires less than 3000 lines of code and only depends 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 (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. |
| |
| Core features |
| ************* |
| The following core C++ features can be mapped 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 |
| - Exceptions |
| - Enumerations |
| - Callbacks |
| - Custom operators |
| - 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: |
| |
| - 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. |
| |