pybind11/docs/intro.rst

.. image:: pybind11-logo.png

About this project
==================
**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.

.. _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. Without
comments, the core header files only require ~4K lines of code and depend on
Python (2.7 or 3.x, or PyPy2.7 >= 5.7) 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.

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
- Arbitrary exception types
- Enumerations
- Callbacks
- Iterators and ranges
- Custom operators
- Single and multiple inheritance
- 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:

- Python 2.7, 3.x, and PyPy (PyPy2.7 >= 5.7) are supported with an
  implementation-agnostic interface.

- 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.

- Everything is contained in just a few header files; there is no need to link
  against any additional libraries.

- Binaries are generally smaller by a factor of at least 2 compared to
  equivalent bindings generated by Boost.Python. A recent pybind11 conversion
  of `PyRosetta`_, an enormous Boost.Python binding project, reported a binary
  size reduction of **5.4x** and compile time reduction by **5.8x**.

- 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.

- With little extra effort, C++ types can be pickled and unpickled similar to
  regular Python objects.

.. _PyRosetta: http://graylab.jhu.edu/RosettaCon2016/PyRosetta-4.pdf

Supported compilers
*******************

1. Clang/LLVM (any non-ancient version with C++11 support)
2. GCC 4.8 or newer
3. Microsoft Visual Studio 2015 or newer
4. Intel C++ compiler v17 or newer (v16 with pybind11 v2.0 and v15 with pybind11 v2.0 and a `workaround <https://github.com/pybind/pybind11/issues/276>`_ )
Very minor documentation fixes, updated logo 2016-01-17 21:36:36 +00:00			`.. image:: pybind11-logo.png`

took a stab at some documentation 2015-10-13 00:57:16 +00:00			`About this project`
			`==================`
minor doc update 2015-10-18 12:48:24 +00:00			`pybind11 is a lightweight header-only library that exposes C++ types in Python`
took a stab at some documentation 2015-10-13 00:57:16 +00:00			`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`
remainder of documentation 2015-10-13 21:21:54 +00:00			`inferring type information using compile-time introspection.`
took a stab at some documentation 2015-10-13 00:57:16 +00:00
			`.. _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`
do more work with classes from pytypes.h (especially for STL container casting) 2016-01-17 21:36:41 +00:00			`everything stripped away that isn't relevant for binding generation. Without`
updated LOC values in README.md and intro.rst 2016-12-26 12:26:17 +00:00			`comments, the core header files only require ~4K lines of code and depend on`
			`Python (2.7 or 3.x, or PyPy2.7 >= 5.7) 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.`
took a stab at some documentation 2015-10-13 00:57:16 +00:00
			`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`
Multiple inheritance support 2016-09-11 11:00:40 +00:00			`- Arbitrary exception types`
took a stab at some documentation 2015-10-13 00:57:16 +00:00			`- Enumerations`
			`- Callbacks`
Multiple inheritance support 2016-09-11 11:00:40 +00:00			`- Iterators and ranges`
took a stab at some documentation 2015-10-13 00:57:16 +00:00			`- Custom operators`
Multiple inheritance support 2016-09-11 11:00:40 +00:00			`- Single and multiple inheritance`
took a stab at some documentation 2015-10-13 00:57:16 +00:00			`- STL data structures`
Multiple inheritance support 2016-09-11 11:00:40 +00:00			`- Iterators and ranges`
took a stab at some documentation 2015-10-13 00:57:16 +00:00			- 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:`

fixed pypy minimum version 2016-12-18 16:08:13 +00:00			`- Python 2.7, 3.x, and PyPy (PyPy2.7 >= 5.7) are supported with an`
WIP: PyPy support (#527) This commit includes modifications that are needed to get pybind11 to work with PyPy. The full test suite compiles and runs except for a last few functions that are commented out (due to problems in PyPy that were reported on the PyPy bugtracker). Two somewhat intrusive changes were needed to make it possible: two new tags ``py::buffer_protocol()`` and ``py::metaclass()`` must now be specified to the ``class_`` constructor if the class uses the buffer protocol and/or requires a metaclass (e.g. for static properties). Note that this is only for the PyPy version based on Python 2.7 for now. When the PyPy 3.x has caught up in terms of cpyext compliance, a PyPy 3.x patch will follow. 2016-12-16 14:00:46 +00:00			`implementation-agnostic interface.`

took a stab at some documentation 2015-10-13 00:57:16 +00:00			`- 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.`

fixed another typo 2015-12-04 22:58:23 +00:00			`- Everything is contained in just a few header files; there is no need to link`
minor doc update 2015-10-18 12:48:24 +00:00			`against any additional libraries.`
Much more efficient generation of function signatures, updated docs This modification taps into some newer C++14 features (if present) to generate function signatures considerably more efficiently at compile time rather than at run time. With this change, pybind11 binaries are now 2.1 times smaller compared to the Boost.Python baseline in the benchmark. Compilation times get a nice improvement as well. Visual Studio 2015 unfortunately doesn't implement 'constexpr' well enough yet to support this change and uses a runtime fallback. 2016-01-17 21:36:36 +00:00
mention pyrosetta stats 2016-08-19 07:32:58 +00:00			`- Binaries are generally smaller by a factor of at least 2 compared to`
			`equivalent bindings generated by Boost.Python. A recent pybind11 conversion`
..one more typo 2016-09-21 17:30:23 +00:00			of `PyRosetta`_, an enormous Boost.Python binding project, reported a binary
mention pyrosetta stats 2016-08-19 07:32:58 +00:00			`size reduction of 5.4x and compile time reduction by 5.8x.`

Very minor documentation fixes, updated logo 2016-01-17 21:36:36 +00:00			`- When supported by the compiler, two new C++14 features (relaxed constexpr and`
added note about supported compiler versions 2016-02-20 20:00:45 +00:00			`return value deduction) are used to precompute function signatures at compile`
Much more efficient generation of function signatures, updated docs This modification taps into some newer C++14 features (if present) to generate function signatures considerably more efficiently at compile time rather than at run time. With this change, pybind11 binaries are now 2.1 times smaller compared to the Boost.Python baseline in the benchmark. Compilation times get a nice improvement as well. Visual Studio 2015 unfortunately doesn't implement 'constexpr' well enough yet to support this change and uses a runtime fallback. 2016-01-17 21:36:36 +00:00			`time, leading to smaller binaries.`
added note about supported compiler versions 2016-02-20 20:00:45 +00:00
convenience wrapper for constructing iterators (fixes #142) 2016-04-13 21:33:00 +00:00			`- With little extra effort, C++ types can be pickled and unpickled similar to`
			`regular Python objects.`

..mention in benchmark docs as well 2016-08-19 07:38:14 +00:00			`.. _PyRosetta: http://graylab.jhu.edu/RosettaCon2016/PyRosetta-4.pdf`

added note about supported compiler versions 2016-02-20 20:00:45 +00:00			`Supported compilers`
			`*******************`

			`1. Clang/LLVM (any non-ancient version with C++11 support)`
Make non-ancient version of GCC explicit in documentation (it means 4.8+) (#575) 2016-12-28 11:10:11 +00:00			`2. GCC 4.8 or newer`
added note about supported compiler versions 2016-02-20 20:00:45 +00:00			`3. Microsoft Visual Studio 2015 or newer`
Enforces intel icpc >= 2017, fixes #1121 (#1363) 2018-04-29 11:48:25 +00:00			4. Intel C++ compiler v17 or newer (v16 with pybind11 v2.0 and v15 with pybind11 v2.0 and a `workaround <https://github.com/pybind/pybind11/issues/276>`_ )