blocks|key|1862129|text|Python网站本身就有一个很棒的set+of+examples，还有API+documentation。这就是我在需要写C扩展时所用的全部代码。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1862130|entityMap|0|LINK|mutability|MUTABLE|url|http://docs.python.org/extending/|1|http://docs.python.org/c-api/^0|H|F|0|Z|H|1|0^^$0|@$1|2|3|4|5|6|7|N|8|@]|9|@$A|O|B|P|1|Q]|$A|R|B|S|1|T]]|C|$]]|$1|D|3|-4|5|6|7|U|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]|L|$5|G|H|I|C|$J|M]]]]

The Python website itself has a great <a href="http://docs.python.org/extending/" rel="noreferrer">set of examples</a>, as well as <a href="http://docs.python.org/c-api/" rel="noreferrer">API documentation</a>. That's literally all I used when I needed to write C extensions.

blocks|key|4602639|text|我将为C%2B%2B内容添加对Boost.Python的强制性引用。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|4602640|entityMap|0|LINK|mutability|MUTABLE|url|http://www.boost.org/doc/libs/1_39_0/libs/python/doc/index.html^0|B|C|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

I'll add the obligatory reference to <a href="http://www.boost.org/doc/libs/1_39_0/libs/python/doc/index.html" rel="noreferrer">Boost.Python</a> for C++ stuff.

blocks|key|4602533|text|我们使用SWIG来包装我们的C/C%2B%2B库，以便在Python中使用。它工作得很好。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4602534|http://www.swig.org/|offset|length|4602535|entityMap|0|LINK|mutability|MUTABLE|url^0|0|0|K|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|N|8|@]|9|@$D|O|E|P|1|Q]]|A|$]]|$1|F|3|-4|5|6|7|R|8|@]|9|@]|A|$]]]|G|$H|$5|I|J|K|A|$L|C]]]]

We use SWIG to wrap our C/C++ libraries for use in Python. It works quite well.

<a href="http://www.swig.org/" rel="noreferrer">http://www.swig.org/</a>

blocks|key|1867164|text|我发现还没有人指出我最喜欢的包装C%2B%2B代码的解决方案之一，SIP+(我相信它也适用于包装C语言，就像SWIG和Boost一样，但我从来没有用过它)。它是Riverbank+Software开发的工具，用来制作PyQt，它是非常棒的Qt+C%2B%2B跨平台框架的Python接口--因此，如果您的C%2B%2B代码使用任何Qt功能，那么它是一个自然的选择，就像如果您的C%2B%2B代码使用Boost，那么Boost+Python就是自然的选择。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1867165|SWIG是我们在工作中使用的(+10年前它是一个合理的决定；-)，理论上它的优势是它还可以包装C或C%2B%2B代码，以便从Java、Perl、Tcl等使用--但是如果你只关心Python，那么很难看到任何让它脱颖而出的东西。|1867166|如果您只是包装现有的DLL/+so，除了Cython之外，其他答案已经指出了(我赞同，但是--它最近变化非常快，所以如果您需要更稳定的东西，请注意)，考虑标准函数模块ctypes+--我不会将其用于非常广泛的工作(C或C%2B%2B编译器会指出的“oops”错误，您可能会使用ctype导致运行时崩溃)，但对于小型任务，它是很棒的(而且非常方便，因为它附带了标准Python发行版！)。|1867167|优秀的老C应用编程接口还没有消亡--今天刚刚遇到了Case，他最近一直在为我的优秀旧开源项目gmpy做大部分的工作，我们一起决定至少在gmpy的下一个版本中坚持使用C+API+--当它稳定下来时，我们会考虑切换到Cython，但我们一致认为，现在转换还为时过早。(我们甚至没有想到任何其他选择，因为gmpy的主要观点是尽可能快得让人眼花缭乱！)|1867168|entityMap|0|LINK|mutability|MUTABLE|url|http://www.riverbankcomputing.co.uk/software/sip/intro|1|http://docs.python.org/library/ctypes.html|2|http://code.google.com/p/gmpy/^0|T|3|0|0|0|2B|6|1|0|1A|4|2|0^^$0|@$1|2|3|4|5|6|7|V|8|@]|9|@$A|W|B|X|1|Y]]|C|$]]|$1|D|3|E|5|6|7|Z|8|@]|9|@]|C|$]]|$1|F|3|G|5|6|7|10|8|@]|9|@$A|11|B|12|1|13]]|C|$]]|$1|H|3|I|5|6|7|14|8|@]|9|@$A|15|B|16|1|17]]|C|$]]|$1|J|3|-4|5|6|7|18|8|@]|9|@]|C|$]]]|K|$L|$5|M|N|O|C|$P|Q]]|R|$5|M|N|O|C|$P|S]]|T|$5|M|N|O|C|$P|U]]]]

I see nobody's yet pointed out one of my favorite solutions for wrapping C++ code, <a href="http://www.riverbankcomputing.co.uk/software/sip/intro" rel="noreferrer">SIP</a> (I believe it also works for wrapping C, like SWIG and unlike Boost, but I've never used it that way). It's the tool Riverbank Software developed to make PyQt, the Python interface to the wonderful Qt C++ cross-platform framework -- so it's a natural choice if your C++ code uses any Qt functionality, just like Boost Python is the natural choice if your C++ code uses Boost.

SWIG is what we use at work (a reasonable decision when it was made 10 years ago;-) and has the theoretical advantage that it can also wrap C or C++ code for use from Java, Perl, Tcl, etc -- but if you only care about Python it's hard to see anything to make it stand out.

If you're just wrapping an existing DLL/so, besides Cython, which other answers have pointed out (and I endorse, but -- it's changing very fast these days, so take care if you need something more stable), consider the standard function module <a href="http://docs.python.org/library/ctypes.html" rel="noreferrer">ctypes</a> -- I wouldn't use it for very extensive work ("oops" errors that a C or C++ compiler would point out to you can cause runtime crashes with ctypes), but for small jobs it's great (and very handy since it comes with standard Python distributions!-).

The good old C API ain't dead yet - just met today with Case, the great guy who's been doing most of the running lately for my good old open source project <a href="http://code.google.com/p/gmpy/" rel="noreferrer">gmpy</a>, and together we decided to stick with the C API for at least the next release of gmpy -- we'll consider switching to Cython when it stabilizes, but we agreed that the switch would still be a bit premature now. (We didn't even think of any other alternative because gmpy's main point is to be as blindingly fast as we can possibly make it!-).

blocks|key|1862197|text|有很多解决方案。一般来说，您应该尽可能避免使用它，因为编写C扩展很乏味。通常，有必要使用第三方库。在这种情况下，我认为今天获胜的解决方案是cython。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1862198|Cython是一种“看起来像python”的语言，但可以通过使用可选类型来使其速度更快。您可以直接在内部调用C函数，并且大多数引用计数(C扩展中的难题)都是自动完成的。根据我的经验，它比boost.python、swig或ctypes要好得多：|1862199|1862200|boost.python只对包装C%2B%2B扩展有意义。我发现它太复杂了，出错的时候很难调试。|unordered-list-item|1862201|swig有相当多的开销，而且不会产生好的代码。对于一些函数来说，它工作得很好，但非平凡的扩展通常使用类型映射，而且语法在|1862202|中很快就变得丑陋起来|1862203|使用cython，您可以使用python对象(list、dict等)。来包装你的C库。当然，如果你仅仅为了速度的原因而需要编写自己的扩展，那么它也是非常有用的。在科学python社区中，我认为当需要速度时，cython已经成为首选工具。|1862204|entityMap|0|LINK|mutability|MUTABLE|url|http://www.cython.org/^0|1X|6|0|0|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|X|8|@]|9|@$A|Y|B|Z|1|10]]|C|$]]|$1|D|3|E|5|6|7|11|8|@]|9|@]|C|$]]|$1|F|3|-4|5|6|7|12|8|@]|9|@]|C|$]]|$1|G|3|H|5|I|7|13|8|@]|9|@]|C|$]]|$1|J|3|K|5|I|7|14|8|@]|9|@]|C|$]]|$1|L|3|M|5|6|7|15|8|@]|9|@]|C|$]]|$1|N|3|O|5|6|7|16|8|@]|9|@]|C|$]]|$1|P|3|-4|5|6|7|17|8|@]|9|@]|C|$]]]|Q|$R|$5|S|T|U|C|$V|W]]]]

There are many solutions. In general, you should avoid it if possible, as writing C extensions is tedious. Often, it is necessary to use a 3rd party library. In that case, I think the winning solution today is <a href="http://www.cython.org/" rel="nofollow noreferrer">cython</a>.

Cython is a languages which "looks like python", but can be made much faster by using optional typing. You can call directly C functions inside, and most of the reference counting (the hard problem in C extensions) is done automatically. In my experience, it is much better than boost.python, swig, or ctypes:

<ul>
<li>boost.python only makes sense for wrapping C++ extensions IMHO. I find it too complicated, and hard to debug when something goes wrong.</li>
<li>swig has quite some overhead, and does not lead to good code. It works ok for a couple of functions, but non trivial extensions often use typemaps, and the syntax get ugly quickly </li>
</ul>

With cython, you can use python objects (list, dict, etc...) to wrap your C library. Of course, it is also very useful if you need to write your own extension just for speed reasons. In the scientific python community, I think cython has become the tool of choice when speed is needed.

blocks|key|4602778|text|我过去使用过pycxx，我真的很喜欢使用这个库。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|4602779|在我看来，它比SWIG更容易使用。我真的无法与boost.python相比，因为我从来没有真正使用过boost。我认为pycxx比boost.python更轻，但我可能错了。|4602780|pycxx的关键点在于它是python+c+api的c%2B%2B包装器。它是面向对象的，它隐藏了所有困难的机制。对于python程序员来说，这是非常直观的。它非常容易使用，并且有一些很好的入门示例。|4602781|对于在c%2B%2B中进行python扩展，我确实推荐pycxx作为一等公民。|4602782|entityMap|0|LINK|mutability|MUTABLE|url|http://cxx.sourceforge.net/^0|6|5|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|R|8|@]|9|@$A|S|B|T|1|U]]|C|$]]|$1|D|3|E|5|6|7|V|8|@]|9|@]|C|$]]|$1|F|3|G|5|6|7|W|8|@]|9|@]|C|$]]|$1|H|3|I|5|6|7|X|8|@]|9|@]|C|$]]|$1|J|3|-4|5|6|7|Y|8|@]|9|@]|C|$]]]|K|$L|$5|M|N|O|C|$P|Q]]]]

I've used <a href="http://cxx.sourceforge.net/" rel="nofollow noreferrer">pycxx</a> in the past and I've really enjoyed to use this lib. 

In my opinion, it is easier to use than SWIG. I can't really compare to boost.python because I've never really used boost. I think that pycxx is lighter than boost.python but I may be wrong.

The key point with pycxx is that it is a c++ wrapper of the python c api. It is object-oriented and it hides all the difficult mechanism. It is quite intuitive for a python programmer. It is very easy to use and there is some nice examples for getting started.

I do recommend pycxx as a first-class citizen for making python extension in c++.

blocks|key|1862150|text|是的，你需要这个：http://www.python.org/doc/ext/|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1862151|当然还有一个C/C%2B%2B编译器。|1862152|如果你描述你正在尝试做什么，以及你正在做什么样的扩展，我相信人们会给你更多的信息。|1862153|如果你想这样做的话，你可以使用SWIG这样的东西来包装库。如果你只是想要加速，C通常是答案，但并不总是如此，等等。|1862154|entityMap|0|LINK|mutability|MUTABLE|url|http://www.python.org/doc/ext/^0|9|U|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|R|8|@]|9|@$A|S|B|T|1|U]]|C|$]]|$1|D|3|E|5|6|7|V|8|@]|9|@]|C|$]]|$1|F|3|G|5|6|7|W|8|@]|9|@]|C|$]]|$1|H|3|I|5|6|7|X|8|@]|9|@]|C|$]]|$1|J|3|-4|5|6|7|Y|8|@]|9|@]|C|$]]]|K|$L|$5|M|N|O|C|$P|Q]]]]

Yes, you need this: <a href="http://www.python.org/doc/ext/" rel="nofollow noreferrer">http://www.python.org/doc/ext/</a>

And of course also a C/C++ compiler.

If you describe what you are trying to do, and what kind of extensions you are making I'm sure people can give you more info.

There are things like SWIG to wrap libraries, if that's what you want to do. If you just want speedups, C is often the answer, but not always, etc.

blocks|key|1862269|text|我很惊讶还没有人提到pybind11。Pybind11是amazing！|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1862270|从他们的文档中：|1862271|Python+pybind11是一个轻量级的仅包含头文件的库，它在|1862272|中公开C%2B%2B类型，反之亦然，主要用于创建现有C%2B%2B代码的Python绑定。它的目标和语法类似于David+Abrahams的优秀Boost.Python库:通过使用编译时内省推断类型信息，最小化传统扩展模块中的样板代码。|blockquote|1862273|1862274|1862275|..。|1862276|1862277|将这个库看作是一个小型的、自包含的Boost.Python版本，去掉了与绑定生成无关的所有内容。没有注释，核心头文件只需要大约4K行代码，并依赖于Python+(2.7或3.x，或Py2.7+>=+5.7)和C%2B%2B标准库。|1862278|1862279|1862280|查看pybind11+github存储库，那里有大量的信息，以及features和goodies的全面列表。|1862281|带有示例的文档可以在here中找到。|1862282|entityMap|0|LINK|mutability|MUTABLE|url|https://github.com/pybind/pybind11|1|https://www.reddit.com/r/Python/comments/9ei08u/pybind11_is_amazing/|2|https://github.com/pybind/pybind11#core-features|3|https://github.com/pybind/pybind11#goodies|4|https://pybind11.readthedocs.io/en/stable/^0|A|8|0|S|7|1|0|0|0|0|0|0|0|0|0|0|0|W|8|2|15|7|3|0|A|4|4|0^^$0|@$1|2|3|4|5|6|7|1D|8|@]|9|@$A|1E|B|1F|1|1G]|$A|1H|B|1I|1|1J]]|C|$]]|$1|D|3|E|5|6|7|1K|8|@]|9|@]|C|$]]|$1|F|3|G|5|6|7|1L|8|@]|9|@]|C|$]]|$1|H|3|I|5|J|7|1M|8|@]|9|@]|C|$]]|$1|K|3|-4|5|6|7|1N|8|@]|9|@]|C|$]]|$1|L|3|-4|5|6|7|1O|8|@]|9|@]|C|$]]|$1|M|3|N|5|6|7|1P|8|@]|9|@]|C|$]]|$1|O|3|-4|5|6|7|1Q|8|@]|9|@]|C|$]]|$1|P|3|Q|5|J|7|1R|8|@]|9|@]|C|$]]|$1|R|3|-4|5|6|7|1S|8|@]|9|@]|C|$]]|$1|S|3|-4|5|6|7|1T|8|@]|9|@]|C|$]]|$1|T|3|U|5|6|7|1U|8|@]|9|@$A|1V|B|1W|1|1X]|$A|1Y|B|1Z|1|20]]|C|$]]|$1|V|3|W|5|6|7|21|8|@]|9|@$A|22|B|23|1|24]]|C|$]]|$1|X|3|-4|5|6|7|25|8|@]|9|@]|C|$]]]|Y|$Z|$5|10|11|12|C|$13|14]]|15|$5|10|11|12|C|$13|16]]|17|$5|10|11|12|C|$13|18]]|19|$5|10|11|12|C|$13|1A]]|1B|$5|10|11|12|C|$13|1C]]]]

I am surprised no one has mentioned <a href="https://github.com/pybind/pybind11" rel="nofollow noreferrer">pybind11</a> yet. Pybind11 is <a href="https://www.reddit.com/r/Python/comments/9ei08u/pybind11_is_amazing/" rel="nofollow noreferrer">amazing</a>!

From their docs:

<blockquote>
 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.
</blockquote>

...

<blockquote>
 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.
</blockquote>

Check pybind11 github repo, there's plenty of info, and a comprehensive list of <a href="https://github.com/pybind/pybind11#core-features" rel="nofollow noreferrer">features</a> and <a href="https://github.com/pybind/pybind11#goodies" rel="nofollow noreferrer">goodies</a>.

Documentation with examples can be found <a href="https://pybind11.readthedocs.io/en/stable/" rel="nofollow noreferrer">here</a>.

blocks|key|1867109|text|也许this+example能帮上忙。我认为这很简单:)|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1867110|entityMap|0|LINK|mutability|MUTABLE|url|http://github.com/felipec/libmtag-python/tree/master^0|2|C|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

Maybe <a href="http://github.com/felipec/libmtag-python/tree/master" rel="nofollow noreferrer">this example</a> helps. I think it's simple enough :)

Can anyone please give me tips on the tools or sofware to use to extend Python with C/C++? Thanks.

Extending Python with C/C++

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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有人能给我一些关于用C/C++扩展Python的工具或软件的提示吗？谢谢。

问用C/C++扩展Python
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回答 9

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回答 9

Stack Overflow用户

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