I am trying to wrap a c++ library using pybind11 so I can use it with Python 3.x.
I tried wrapping the code using swig, but I ran into an issue where SWIG would generate the cxx file, but would not read the headers I was referencing, so it was suggested that I use pybind11 because it's better than swig (this is opinion I know), but I am having trouble finding resources on how I can reference/build the project.
My environment is:
Windows 10 x64
Anacondas build 4.4.0 with Python 3.6
Visual Studios 2015 Professional (c++ installed)
When I create my interface file for Swig, I can do something easy like:
```
%module filegdbapi
%{
#include "FileGDBAPI.h"
%}
%include "FileGDBAPI.h"
```
Then on the swig build, I can reference the -I to the location of the .h files.
How do I do something like this in pybind11? Is it that simple?
The documentation for pybind11 always shows building wrappers when you have the .cpp files. Can I use pybind11 in a ways that I can build a wrapper with swig? If so, how do you setup the files?
Can someone point me to a project that just generates a python wrapper from existing c++ code?
Thank you
Despite serving the same purpose, SWIG and Pybind11 are different tools.
As the name implies, SWIG (Simplified Wrapper and Interface Generator) is a generator tool that create Python binding for existing C++ code, using definitions written in a special language.
Pybind11, on the other hand, is a header-only C++ library that wraps raw Python-C API (that is old-style C and has steep learning curve) and allows to write Python bindings in modern C++. But you write those binding yourself by hand, using whatever C++ entities (functions, classes, templates etc.) that pybind11:: namespace provides.
How do I do something like this in pybind11? Is it that simple?
Can someone point me to a project that just generates a python wrapper from existing c++ code?
You can check Binder project http://cppbinder.readthedocs.io
Binder is a tool for automatic generation of Python bindings for C++11 projects using Pybind11 and Clang LibTooling libraries. That is, Binder, takes a C++ project and compiles it into objects and functions that are all usable within Python. Binder is different from prior tools in that it handles special features new in C++11.
The basic usage seems to be very easy, similar to your description for SWIG
1) Gather data about what classes/functions are available and acquire in-depth information of class heritage, member functions and standalone functions type signatures.
2) Generate bindings code
3) Compile code into shared library
Binder is tool that aims to automate steps 1 and 2.
The sad news is that it seems to be Linux only, so to use it under Windows you will need to install virtual Linux or use a Docker container with build tools.
You may want to look into cffi for this.
http://cffi.readthedocs.io/en/latest/
and this for a sample project using it:
https://github.com/wolever/python-cffi-example
Incidentally, you will be able to ship the code with pypy too, which some people may consider as a plus.
Related
I need to access data via USB from a beam profiler. I've tried using the USB module in python to access it, but unfortunately the company who makes this device "does not support development in Python". The project I am working on is to eventually create a GUI (via Python) to automate a motor and pull data from the device. So it has to be done in Python, or I'm going to have to discard the first half of the code and redo it in C++.
I think the reason the device can only interface with C/C++ is because of the header and library files that come with the driver download.
I've looked at Cython but am still very unsure how it can help me. I'm just trying to access the header files for the driver in python and somehow execute the C commands in python.
BTW I am using Anaconda (if that matters).
Thank-you for any clarification and help!
Check out boost.python
Here is an intro:
The Boost Python Library is a framework for interfacing Python and
C++. It allows you to quickly and seamlessly expose C++ classes
functions and objects to Python, and vice-versa, using no special
tools -- just your C++ compiler. It is designed to wrap C++ interfaces
non-intrusively, so that you should not have to change the C++ code at
all in order to wrap it, making Boost.Python ideal for exposing
3rd-party libraries to Python. The library's use of advanced
metaprogramming techniques simplifies its syntax for users, so that
wrapping code takes on the look of a kind of declarative interface
definition language (IDL).
It includes support for:
References and Pointers
Globally Registered Type Coercions
Automatic Cross-Module Type Conversions
Efficient Function Overloading
C++ to Python Exception Translation
Default Arguments
Keyword Arguments
Manipulating Python objects in C++
Exporting C++ Iterators as Python Iterators
Documentation Strings
and many more.
I have a main file(main.cpp) and a header file(nodes.hpp). The main file takes N(any positive integer) as input argument and by using the functions of header file it gives output say 'x & y' (both double).
Note:
Both main and header files are written in C++.
Both main and header files instead of using data structues as arrays,vectors, make use of Eigen Library.
I have to write a python wrapper for them, I have working knowledge of python but have never used any wrapper.
Can anybody please refer or give some notes about using python wrpper for such code?
Here are your options:
You can use ctypes, and I consider this the cleanest solution, because you convert your program to a shared library that can be called by any other software, not only Python. You, though, have to write a C-interface for your program yourself.
You can use Python C-Extension, and I consider this the worst solution, because it's very low level, and prone to memory leaks, and costs lots of time to implement one function, and is Python-version dependent. Basically this is good to start a Python interpreter inside your C++. You can create PyObjects (which is the main building block of any Python type) and deal with them insdie C/C++.
You can use SWIG, where it automatically creates the the interface that you have to create with ctypes through an interface file that you define. People say it's very good, but the documentation is not as good.
You can use Boost.Python, which is good, but it has a very ugly build system with bjam. If you can manage to bypass that, then it's even better than ctypes. I'm a big boost fan, but bjam is why I don't use this.
What I do typically is ctypes. I trust it because it emphasizes the single-reponsibility principle. The library has a job that's separate from the interface (the C-interface), which is also separate from your Python script that uses that interface and exposes "the easy functionality" to the user.
Use Boost.Python. Here is my tutorial, previously on SO Docs.
Using Boost.Python
Things are easy when you have to use a C++ library in a Python project. Just you can use Boost.
First of all here is a list of components you need:
A CMakeList.txt file, because you're going to use CMake.
The C++ files of the C++ project.
The python file - this is your python project.
Let's start with a small C++ file. Our C++ project has only one method which returns some string "This is the first try". Call it CppProject.cpp
char const *firstMethod() {
return "This is the first try.";
}
BOOST_PYTHON_MODULE(CppProject) {
boost::python::def("getTryString", firstMethod); // boost::python is the namespace
}
Have a CMakeLists.txt file a below:
cmake_minimum_required(VERSION 2.8.3)
FIND_PACKAGE(PythonInterp)
FIND_PACKAGE(PythonLibs)
FIND_PACKAGE(Boost COMPONENTS python)
INCLUDE_DIRECTORIES(${Boost_INCLUDE_DIRS} ${PYTHON_INCLUDE_DIRS})
PYTHON_ADD_MODULE(NativeLib CppProject)
FILE(COPY MyProject.py DESTINATION .) # See the whole tutorial to understand this line
By this part of the tutorial everything is so easy. you can import the library and call method in your python project. Call your python project MyProject.py.
import NativeLib
print (NativeLib.getTryString)
In order to run your project follow the instructions below:
Create a directory with the name build.
Enter into that directory.
Give the command cmake -DCMAKE_BUILD_TYPE=Release ..
make
python MyProject.py. Now, you have to see the string which the method in your C++ project returns.
Another tool for C++ wrapper generation is CLIF. Released in 2017, Google uses this for most everything these days. We no longer allow new SWIG wrappers to be written for Python internally.
It is built on top of Clang for the C++ parsing and requires relatively idiomatic modern C++ API use (unsurprisingly following Google's Style Guide) rather than any attempt to allow you to shoot yourself in the foot via SWIG's "support everything poorly" approach.
Try with official documentation:
https://docs.python.org/2/extending/extending.html
this link will provide you simple example of how to include a cpp module and use it from the python interpreter, or if this is possible try with Cython: http://cython.org/
Cython will allow you to write C-like, Python-like code which will be translated to CPP compiled and then will be easily accessible from the Python.
You can use Boost.Python
or go with the Python native interface
I would recommend Boost.Python if you already have Boost set up.
I'm working in an embedded Linux environment and I have some Python code which I would like to use. My Python code is just doing some math, not using any library other than Numpy and the common ones.
Is there any way to build up a library that I can call from C or C++ code?
Embedding the CPython interpreter into a C or C++ program is actually pretty straightforward.
The official documentation has some complete examples.
Also, check out SWIG and Boost.Python.
I'm designing musical training games using JUCE -- a multiplatform C++ framework that allows me to code audio/visuals close to the wire.
However, I have coded my gameplay (control flow / data-processing) in Python -- it is complex and I wish to keep changing it so I can experiment with different gameplays. Python is ideal for this kind of rapid prototyping work.
So I would like my (platform independent, so Win/OSX/Lin/iOS/And) C++ to start up a Python runtime, feed it a .py file, and then call various functions in that .py. Also I would like to be able to call back to the C++ code from the .py.
Here is the relevant official Python documentation: https://docs.python.org/2/extending/extending.html
And here is a CodeProject article: http://www.codeproject.com/Articles/11805/Embedding-Python-in-C-C-Part-I
However, neither of them seem to address the issue of multiplatform.
The technique seems to be to link with the library libpython.a, and #include which contains the various functions for starting up the runtime environment, loading scripts, executing python-code, etc.
But surely this libpython.a would need to be compiled separately per platform? If so, this wouldn't be a very clean solution, so could I instead add the Python source code to my project and get it to compile the .a?
How can I go about doing this?
EDIT: https://wiki.python.org/moin/boost.python/EmbeddingPython
EDIT2: I'm pretty sure trying to bring in the full CPython source code is overkill here -- someone must have made some stripped down Python implementation in C/C++ that doesn't support any system-calls/multithreading/fancy-stuff -- just works through Python syntax line by line. Looking thru https://wiki.python.org/moin/PythonImplementations but I can't see an obvious candidate.
EDIT3: https://github.com/micropython/micropython should be added to that last page, but still it doesn't look like it is what I'm after
There's an entire chapter of the Python docs that explain the different approaches you can take embedding a Python interpreter into another app.
Embedding Python is similar to extending it, but not quite. The
difference is that when you extend Python, the main program of the
application is still the Python interpreter, while if you embed
Python, the main program may have nothing to do with Python — instead,
some parts of the application occasionally call the Python interpreter
to run some Python code.
So if you are embedding Python, you are providing your own main
program. One of the things this main program has to do is initialize
the Python interpreter. At the very least, you have to call the
function Py_Initialize(). There are optional calls to pass command
line arguments to Python. Then later you can call the interpreter from
any part of the application.
There are several different ways to call the interpreter: you can pass
a string containing Python statements to PyRun_SimpleString(), or you
can pass a stdio file pointer and a file name (for identification in
error messages only) to PyRun_SimpleFile(). You can also call the
lower-level operations described in the previous chapters to construct
and use Python objects.
A simple demo of embedding Python can be found in the directory
Demo/embed/ of the source distribution.
I recently decided to create a project that mixes C++ with Python, thus getting the best of both worlds. My idea was to do rapid prototyping of classes and functions in Python for obvious reasons, but still being able to call C++ code within Python (for obvious reasons as well). So instead of embedding Python in the C++ framework, I suggest you do the opposite: embed your C++ framework into a Python project. In order to do so, you just have to write very simple interface files and let Swig take care of the interfacing part.
If you want to start from scratch, there's a nice tool called cookiecutter that can be used to generate a project templates. You can choose either the cookiecutter-pypackage, or the cookiecutter-pylibrary, the latter improving over the former as described here. Interestingly, you can also use the cookiecutter code to generate the structure of a C++ project. This empty project uses the CMake build system, which IMHO is the best framework for developing platform independent C++ code. I then had to decide on the directory structure for this mixed project, so one of my previous posts describes this in detail. Good luck!
I'm using SWIG to embed Python into my C++ application, and to extend it as well, i.e. access my C++ API in Python outside my application. SWIG and Python are multi-platform, so that is not really an issue. One of the main advantage of SWIG is that it can generate bindings for a lot of languages. There are also a lot of C++ code wrappers that could be used, for example boost.python or cython.
Check these links on SO:
Extending python - to swig, not to swig or Cython
Exposing a C++ API to Python
Or you can go the hard way and use plain Python/C API.
I'm working in an embedded Linux environment and I have some Python code which I would like to use. My Python code is just doing some math, not using any library other than Numpy and the common ones.
Is there any way to build up a library that I can call from C or C++ code?
Embedding the CPython interpreter into a C or C++ program is actually pretty straightforward.
The official documentation has some complete examples.
Also, check out SWIG and Boost.Python.