# pybind11 — Seamless operability between C++11 and Python
[](http://pybind11.readthedocs.org/en/master/?badge=master)
[](http://pybind11.readthedocs.org/en/stable/?badge=stable)
[](https://gitter.im/pybind/Lobby)
[](https://travis-ci.org/pybind/pybind11)
[](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](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 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.
Tutorial and reference documentation is provided at
[http://pybind11.readthedocs.org/en/master](http://pybind11.readthedocs.org/en/master).
A PDF version of the manual is available
[here](https://media.readthedocs.org/pdf/pybind11/master/pybind11.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
- 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](http://graylab.jhu.edu/RosettaCon2016/PyRosetta-4.pdf) 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.
## 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 16 or newer (15 with a [workaround](https://github.com/pybind/pybind11/issues/276))
5. Cygwin/GCC (tested on 2.5.1)
## 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,
Sylvain Corlay,
Trent Houliston,
Axel Huebl,
@hulucc,
Sergey Lyskov
Johan Mabille,
Tomasz Miąsko,
Dean Moldovan,
Ben Pritchard,
Jason Rhinelander,
Boris Schäling,
Pim Schellart,
Ivan Smirnov, and
Patrick Stewart.
### 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.
C++第三方库xlnt-用于读写Excel文件
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C++第三方库xlnt-用于读写Excel文件 （428个子文件） 
xlnt.3 61KB buildfile 3KB miniz.c 309KB xmlparse.c 193KB genx.c 56KB xmltok_impl.c 44KB xmltok.c 42KB xmlrole.c 33KB char-props.c 18KB sha512.c 9KB sha1.c 6KB xmltok_ns.c 3KB setup.cfg 238B .clang-format 2KB ucm.cmake 23KB pybind11Tools.cmake 8KB FindPythonLibsNew.cmake 8KB FindArrow.cmake 5KB FindEigen3.cmake 3KB FindCatch.cmake 2KB pkg-config.pc.cmake 293B xlsx_consumer.cpp 118KB xlsx_producer.cpp 108KB aes.cpp 86KB number_formatter.cpp 64KB worksheet_test_suite.cpp 52KB workbook.cpp 47KB compound_document.cpp 38KB number_format_test_suite.cpp 35KB worksheet.cpp 33KB serialization_test_suite.cpp 28KB cell_test_suite.cpp 27KB cell.cpp 23KB zstream.cpp 19KB workbook_test_suite.cpp 17KB header_footer_code.cpp 16KB custom_value_traits.cpp 15KB xlntpyarrow.lib.cpp 14KB xlsx_crypto_producer.cpp 13KB xlsx_crypto_consumer.cpp 13KB numeric_util_test_suite.cpp 12KB documentation.cpp 10KB optional_tests.cpp 10KB manifest.cpp 9KB number_format.cpp 9KB img2xlsx.cpp 8KB named_range_test_suite.cpp 8KB range.cpp 8KB path.cpp 7KB header_footer.cpp 7KB cell_reference.cpp 7KB cell_iterator.cpp 7KB range_iterator.cpp 7KB index_types.cpp 7KB encryption_info.cpp 7KB styles.cpp 7KB vector_streambuf.cpp 6KB color.cpp 6KB style.cpp 6KB string_to_double.cpp 6KB fill.cpp 6KB constants.cpp 6KB format.cpp 5KB rich_text_test_suite.cpp 5KB streaming_workbook_reader.cpp 5KB double_to_string.cpp 5KB base64.cpp 5KB helper_test_suite.cpp 5KB font.cpp 5KB range_reference.cpp 5KB datetime_test_suite.cpp 5KB border.cpp 5KB datetime.cpp 5KB range_test_suite.cpp 4KB rich_text.cpp 4KB fill_test_suite.cpp 4KB cell_vector.cpp 4KB time.cpp 4KB ext_list.cpp 4KB phonetic_pr.cpp 4KB variant.cpp 4KB spreadsheet_drawing.cpp 4KB conditional_format.cpp 4KB exceptions.cpp 4KB alignment.cpp 4KB date.cpp 4KB named_range.cpp 4KB streaming_workbook_writer.cpp 3KB timedelta.cpp 3KB worksheet_iterator.cpp 3KB profiling.cpp 3KB index_types_test_suite.cpp 3KB sha.cpp 3KB timedelta_test_suite.cpp 3KB page_setup.cpp 3KB color_test_suite.cpp 3KB writer.cpp 3KB hyperlink.cpp 3KB style_test_suite.cpp 3KB variant_tests.cpp 3KB共 428 条
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