intro.rst revision 12037:d28054ac6ec9 
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.
20Think of this library as a tiny self-contained version of Boost.Python with
21everything stripped away that isn't relevant for binding generation. Without
22comments, the core header files only require ~4K lines of code and depend on
23Python (2.7 or 3.x, or PyPy2.7 >= 5.7) and the C++ standard library. This
24compact implementation was possible thanks to some of the new C++11 language
25features (specifically: tuples, lambda functions and variadic templates). Since
26its creation, this library has grown beyond Boost.Python in many ways, leading
27to dramatically simpler binding code in many common situations.
28
29Core features
30*************
31The following core C++ features can be mapped to Python
32
33- Functions accepting and returning custom data structures per value, reference, or pointer
34- Instance methods and static methods
35- Overloaded functions
36- Instance attributes and static attributes
37- Arbitrary exception types
38- Enumerations
39- Callbacks
40- Iterators and ranges
41- Custom operators
42- Single and multiple inheritance
43- STL data structures
44- Iterators and ranges
45- Smart pointers with reference counting like ``std::shared_ptr``
46- Internal references with correct reference counting
47- C++ classes with virtual (and pure virtual) methods can be extended in Python
48
49Goodies
50*******
51In addition to the core functionality, pybind11 provides some extra goodies:
52
53- Python 2.7, 3.x, and PyPy (PyPy2.7 >= 5.7) are supported with an
54  implementation-agnostic interface.
55
56- It is possible to bind C++11 lambda functions with captured variables. The
57  lambda capture data is stored inside the resulting Python function object.
58
59- pybind11 uses C++11 move constructors and move assignment operators whenever
60  possible to efficiently transfer custom data types.
61
62- It's easy to expose the internal storage of custom data types through
63  Pythons' buffer protocols. This is handy e.g. for fast conversion between
64  C++ matrix classes like Eigen and NumPy without expensive copy operations.
65
66- pybind11 can automatically vectorize functions so that they are transparently
67  applied to all entries of one or more NumPy array arguments.
68
69- Python's slice-based access and assignment operations can be supported with
70  just a few lines of code.
71
72- Everything is contained in just a few header files; there is no need to link
73  against any additional libraries.
74
75- Binaries are generally smaller by a factor of at least 2 compared to
76  equivalent bindings generated by Boost.Python. A recent pybind11 conversion
77  of `PyRosetta`_, an enormous Boost.Python binding project, reported a binary
78  size reduction of **5.4x** and compile time reduction by **5.8x**.
79
80- When supported by the compiler, two new C++14 features (relaxed constexpr and
81  return value deduction) are used to precompute function signatures at compile
82  time, leading to smaller binaries.
83
84- With little extra effort, C++ types can be pickled and unpickled similar to
85  regular Python objects.
86
87.. _PyRosetta: http://graylab.jhu.edu/RosettaCon2016/PyRosetta-4.pdf
88
89Supported compilers
90*******************
91
921. Clang/LLVM (any non-ancient version with C++11 support)
932. GCC 4.8 or newer
943. Microsoft Visual Studio 2015 or newer
954. Intel C++ compiler v15 or newer
96