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The [[http://cppyy.readthedocs.io|cppyy]] package integrates the Clang/LLVM-based [[https://github.com/vgvassilev/cling|Cling C++ interpreter]] into Python, providing interactive access to C/C++ from Python. It enables calling C++ from Python and calling Python from C++. Using precompiled modules, a class loader, and an everything-lazy implementation, cppyy is designed for automatic generation of Python bindings for large scale C++ programs. PyPy supports cppyy natively for high performance, as described in this [[http://wlav.web.cern.ch/wlav/Cppyy_LavrijsenDutta_PyHPC16.pdf|PyHPC'16]] paper. | The [[http://cppyy.readthedocs.io|cppyy]] package provides fast, automatic, Python-C++ bindings, including run-time instantiation of C++ templates, cross-inheritance, callbacks, auto-casting, transparent use of smart pointers, etc., etc. Many C++ idioms are automatically recognized and "pythonized" (given a Python look-and-feel), allowing drop-in placement in Python idioms and integration with standard libraries such as NumPy and ctypes. Most importantly it makes it possible to write higher-level (with ownership, threading, and application-specific rules) Python modules on top of C++ in pure Python, without the need to learn an intermediate language or language extension. |
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Thanks to LLVM's JIT, cppyy supports embedded C++ code, automatic template instantiations, auto-downcasting, callbacks, cross-language inheritance, etc., etc. Where possible, C++ idioms are automatically recognized and "pythonized" (given a Python look-and-feel). If necessary, a pythonization API provides further fine tuning for memory ownership, threading, and application-specific conversions. | Cppyy works by integrating the Clang/LLVM-based [[https://github.com/vgvassilev/cling|Cling C++ interpreter]], providing interactive access to C/C++ from Python. It enables calling C++ from Python and calling Python from C++. Using precompiled modules, a class loader, and an everything-lazy implementation, cppyy is designed for automatic generation of Python bindings for large scale C++ programs. PyPy supports cppyy natively for high performance, as described in this [[http://wlav.web.cern.ch/wlav/Cppyy_LavrijsenDutta_PyHPC16.pdf|PyHPC'16]] paper. |
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If you prefer conda, cpppy is also available from conda-forge for Linux and Mac: {{{ $ conda install -c conda-forge cppyy }}} |
The cppyy package provides fast, automatic, Python-C++ bindings, including run-time instantiation of C++ templates, cross-inheritance, callbacks, auto-casting, transparent use of smart pointers, etc., etc. Many C++ idioms are automatically recognized and "pythonized" (given a Python look-and-feel), allowing drop-in placement in Python idioms and integration with standard libraries such as NumPy and ctypes. Most importantly it makes it possible to write higher-level (with ownership, threading, and application-specific rules) Python modules on top of C++ in pure Python, without the need to learn an intermediate language or language extension.
Cppyy works by integrating the Clang/LLVM-based Cling C++ interpreter, providing interactive access to C/C++ from Python. It enables calling C++ from Python and calling Python from C++. Using precompiled modules, a class loader, and an everything-lazy implementation, cppyy is designed for automatic generation of Python bindings for large scale C++ programs. PyPy supports cppyy natively for high performance, as described in this PyHPC'16 paper.
An example session follows:
1 >>> import cppyy
2 >>> cppyy.cppdef("""
3 ... class MyClass {
4 ... public:
5 ... MyClass(int i) : m_data(i) {}
6 ... virtual ~MyClass() {}
7 ... virtual int add_int(int i) { return m_data + i; }
8 ... int m_data;
9 ... };""") # defines a new C++ class
10 >>> from cppyy.gbl import MyClass # bound on-the-fly
11 >>> v = cppyy.gbl.std.vector[MyClass]() # template generated
12 >>> v += [MyClass(i) for i in range(2)]
13 >>> len(v)
14 2
15 >>> for m in v: # idiomatically mapped
16 ... print(m.m_data)
17 ...
18 0
19 1
20 # create a C++ function on the fly and attach on the Python side
21 >>> cppyy.cppdef("auto add_int = [](MyClass* m, int a) { return m->m_data + a; };")
22 >>> MyClass.add_int = lambda self, i: cppyy.gbl.add_int(self, i)
23 >>> for m in v:
24 ... print(m.add_int(1))
25 ...
26 1
27 2
28 # cross inheritence (CPython only for now)
29 >>> class PyMyClass(MyClass):
30 ... def add_int(self, i):
31 ... return self.m_data + 2*i
32 ...
33 # helper on C++ side to show inheritence
34 >>> cppyy.cppdef("int callback(MyClass* m, int i) { return m->add_int(i); }")
35 >>> cppyy.gbl.callback(m, 2) # calls C++ add_int
36 3
37 >>> cppyy.gbl.callback(PyMyClass(1), 2) # calls Python-side override
38 5
Source and wheels (for ManyLinux, Mac, and Windows 32b and 64b) are available on PyPI. To install, run:
$ python -m pip install cppyy
If you prefer conda, cpppy is also available from conda-forge for Linux and Mac:
$ conda install -c conda-forge cppyy
Full details are in the cppyy documentation: http://cppyy.readthedocs.io