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