docs: Use README.rst in docs as home page (#2500)

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recursive-include pybind11/include/pybind11 *.h
recursive-include pybind11 *.py
include pybind11/share/cmake/pybind11/*.cmake
include LICENSE README.md pyproject.toml setup.py setup.cfg
include LICENSE README.rst pyproject.toml setup.py setup.cfg

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README.md
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![pybind11 logo](https://github.com/pybind/pybind11/raw/master/docs/pybind11-logo.png)
# pybind11 — Seamless operability between C++11 and Python
[![Documentation Status](https://readthedocs.org/projects/pybind11/badge/?version=master)](http://pybind11.readthedocs.org/en/master/?badge=master)
[![Documentation Status](https://readthedocs.org/projects/pybind11/badge/?version=stable)](http://pybind11.readthedocs.org/en/stable/?badge=stable)
[![Gitter chat](https://img.shields.io/gitter/room/gitterHQ/gitter.svg)](https://gitter.im/pybind/Lobby)
[![CI](https://github.com/pybind/pybind11/workflows/CI/badge.svg)](https://github.com/pybind/pybind11/actions)
[![Build status](https://ci.appveyor.com/api/projects/status/riaj54pn4h08xy40?svg=true)](https://ci.appveyor.com/project/wjakob/pybind11)
**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.
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 3.5+, or PyPy) 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.
Tutorial and reference documentation is provided at
[pybind11.readthedocs.org][]. A PDF version of the manual is available
[here][docs-pdf].
## Core features
pybind11 can map the following core C++ features 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
- 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, 3.5+, and PyPy (tested on 7.3) 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][pyrosetta-report] a binary size reduction of **5.4x** and compile
time reduction by **5.8x**.
- Function signatures are precomputed at compile time (using `constexpr`),
leading to smaller binaries.
- With little extra effort, C++ types can be pickled and unpickled similar to
regular Python objects.
## Supported compilers
1. Clang/LLVM 3.3 or newer (for Apple Xcode's clang, this is 5.0.0 or newer)
2. GCC 4.8 or newer
3. Microsoft Visual Studio 2015 Update 3 or newer
4. Intel C++ compiler 17 or newer (16 with pybind11 v2.0 and 15 with pybind11
v2.0 and a [workaround][intel-15-workaround])
5. Cygwin/GCC (tested on 2.5.1)
6. NVCC (CUDA 11 tested)
7. NVIDIA PGI (20.7 tested)
## About
This project was created by [Wenzel Jakob](http://rgl.epfl.ch/people/wjakob).
Significant features and/or improvements to the code were contributed by
Jonas Adler,
Lori A. Burns,
Sylvain Corlay,
Trent Houliston,
Axel Huebl,
@hulucc,
Sergey Lyskov
Johan Mabille,
Tomasz Miąsko,
Dean Moldovan,
Ben Pritchard,
Jason Rhinelander,
Boris Schäling,
Pim Schellart,
Henry Schreiner,
Ivan Smirnov, and
Patrick Stewart.
### Contributing
See the [contributing guide][] for information on building and contributing to
pybind11.
### License
pybind11 is provided under a BSD-style license that can be found in the
[`LICENSE`][] file. By using, distributing, or contributing to this project,
you agree to the terms and conditions of this license.
[pybind11.readthedocs.org]: http://pybind11.readthedocs.org/en/master
[docs-pdf]: https://media.readthedocs.org/pdf/pybind11/master/pybind11.pdf
[Boost.Python]: http://www.boost.org/doc/libs/1_58_0/libs/python/doc/
[pyrosetta-report]: http://graylab.jhu.edu/RosettaCon2016/PyRosetta-4.pdf
[contributing guide]: https://github.com/pybind/pybind11/blob/master/.github/CONTRIBUTING.md
[`LICENSE`]: https://github.com/pybind/pybind11/blob/master/LICENSE
[intel-15-workaround]: https://github.com/pybind/pybind11/issues/276

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README.rst Normal file
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.. figure:: https://github.com/pybind/pybind11/raw/master/docs/pybind11-logo.png
:alt: pybind11 logo
pybind11 — Seamless operability between C++11 and Python
========================================================
|Documentation Status| |image1| |Gitter chat| |CI| |Build status|
**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 <http://www.boost.org/doc/libs/1_58_0/libs/python/doc/>`_
library by David Abrahams: to minimize boilerplate code in traditional
extension modules by inferring type information using compile-time
introspection.
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 isnt relevant for binding
generation. Without comments, the core header files only require ~4K
lines of code and depend on Python (2.7 or 3.5+, or PyPy) 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.
Tutorial and reference documentation is provided at
`pybind11.readthedocs.org <http://pybind11.readthedocs.org/en/master>`_.
A PDF version of the manual is available
`here <https://media.readthedocs.org/pdf/pybind11/master/pybind11.pdf>`_.
And the source code is always available at
`github.com/pybind/pybind11 <https://github.com/pybind/pybind11>`_.
Core features
-------------
pybind11 can map the following core C++ features 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
- 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, 3.5+, and PyPy (tested on 7.3) 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.
- Its 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.
- Pythons 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 <http://graylab.jhu.edu/RosettaCon2016/PyRosetta-4.pdf>`_
a binary size reduction of **5.4x** and compile time reduction by
**5.8x**.
- Function signatures are precomputed at compile time (using
``constexpr``), leading to smaller binaries.
- With little extra effort, C++ types can be pickled and unpickled
similar to regular Python objects.
Supported compilers
-------------------
1. Clang/LLVM 3.3 or newer (for Apple Xcodes clang, this is 5.0.0 or
newer)
2. GCC 4.8 or newer
3. Microsoft Visual Studio 2015 Update 3 or newer
4. Intel C++ compiler 17 or newer (16 with pybind11 v2.0 and 15 with
pybind11 v2.0 and a
`workaround <https://github.com/pybind/pybind11/issues/276>`_)
5. Cygwin/GCC (tested on 2.5.1)
6. NVCC (CUDA 11 tested)
7. NVIDIA PGI (20.7 tested)
About
-----
This project was created by `Wenzel
Jakob <http://rgl.epfl.ch/people/wjakob>`_. Significant features and/or
improvements to the code were contributed by Jonas Adler, Lori A. Burns,
Sylvain Corlay, Trent Houliston, Axel Huebl, @hulucc, Sergey Lyskov
Johan Mabille, Tomasz Miąsko, Dean Moldovan, Ben Pritchard, Jason
Rhinelander, Boris Schäling, Pim Schellart, Henry Schreiner, Ivan
Smirnov, and Patrick Stewart.
Contributing
~~~~~~~~~~~~
See the `contributing
guide <https://github.com/pybind/pybind11/blob/master/.github/CONTRIBUTING.md>`_
for information on building and contributing to pybind11.
License
~~~~~~~
pybind11 is provided under a BSD-style license that can be found in the
`LICENSE <https://github.com/pybind/pybind11/blob/master/LICENSE>`_
file. By using, distributing, or contributing to this project, you agree
to the terms and conditions of this license.
.. |Documentation Status| image:: https://readthedocs.org/projects/pybind11/badge/?version=master
:target: http://pybind11.readthedocs.org/en/master/?badge=master
.. |image1| image:: https://readthedocs.org/projects/pybind11/badge/?version=stable
:target: http://pybind11.readthedocs.org/en/stable/?badge=stable
.. |Gitter chat| image:: https://img.shields.io/gitter/room/gitterHQ/gitter.svg
:target: https://gitter.im/pybind/Lobby
.. |CI| image:: https://github.com/pybind/pybind11/workflows/CI/badge.svg
:target: https://github.com/pybind/pybind11/actions
.. |Build status| image:: https://ci.appveyor.com/api/projects/status/riaj54pn4h08xy40?svg=true
:target: https://ci.appveyor.com/project/wjakob/pybind11

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@ -31,7 +31,7 @@ import subprocess
# Add any Sphinx extension module names here, as strings. They can be
# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
# ones.
extensions = ['breathe']
extensions = ['breathe', 'sphinx.ext.imgconverter']
breathe_projects = {'pybind11': '.build/doxygenxml/'}
breathe_default_project = 'pybind11'
@ -242,7 +242,10 @@ latex_elements = {
#'pointsize': '10pt',
# Additional stuff for the LaTeX preamble.
'preamble': r'\DeclareUnicodeCharacter{00A0}{}',
'preamble': r'''
\DeclareUnicodeCharacter{00A0}{}
\DeclareUnicodeCharacter{2194}{<->}
''',
# Latex figure (float) alignment
#'figure_align': 'htbp',

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@ -1,11 +1,4 @@
.. only: not latex
.. image:: pybind11-logo.png
pybind11 --- Seamless operability between C++11 and Python
==========================================================
Source code available at `github.com/pybind/pybind11 <https://github.com/pybind/pybind11>`_.
.. include:: ../README.rst
.. only: not latex
@ -14,7 +7,6 @@ Source code available at `github.com/pybind/pybind11 <https://github.com/pybind/
.. toctree::
:maxdepth: 1
intro
changelog
upgrade

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@ -1,93 +0,0 @@
.. 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
- 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**.
- Function signatures are precomputed at compile time (using ``constexpr``),
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>`_ )

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@ -1,6 +1,6 @@
[metadata]
long_description = file: README.md
long_description_content_type = text/markdown
long_description = file: README.rst
long_description_content_type = text/x-rst
description = Seamless operability between C++11 and Python
author = Wenzel Jakob
author_email = "wenzel.jakob@epfl.ch"

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@ -80,7 +80,7 @@ sdist_files = {
"setup.py",
"LICENSE",
"MANIFEST.in",
"README.md",
"README.rst",
"PKG-INFO",
}