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by Thomas Guest.
Original Post: Mixing Python and C++
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I can’t get over how neat Python is. Sometime soon I’d like to work
on a mixed language system: Python for the tricky bits, C++ for the
speedy bits.
I haven’t changed my mind. As usual, it’s been an evolution rather
than a revolution – step by step, I’ve got closer to realising this
ambition, and finally, now, I think I can say I’ve achieved it.
Why Python and C++?
No particular reason. C++ is the systems programming language I know
best. When you need to get close to the silicon, it does the job very
well. And Python is the high level language I know best. When you want to
write concise, flexible software, it does the job very well.
Really, though, I’d be just as happy to write the tricky code in any
decent high-level language, switching in low-level languages as
dictated by performance and platform requirements.
Mixed language development
Perhaps the most obvious way to mix languages is in a single program:
you start off by writing the program in Python. If it doesn’t go
quickly enough, you profile it and write a C++ library to look after
the slow bits. There are disadvantages to this, though:
you have to figure out how to interface between the two languages
the library and the program can become interdependent and harder to test in isolation
your IDE and build system may not like it
As a consequence, this turns out to be a technique I’ve used relatively
little. Here are some of other techniques I’ve used more frequently.
Code Generation. Python is a great language for generating code
– either in Python or C++, or in any other language.
Multiple Processes. Rather than sharing a single process, the
C++ and the Python can run as separate executables. C++ does the
heavy lifting; Python manages the complex application logic. A
side-effect is that the operating system can use separate processors
for the separate processes without all the problems associated with
multi-threaded code.
Prototyping. Sometimes a compiled C++ program is required. I’ve
found that sketching out a prototype in Python then simply rewriting
it in C++ can work well. The prototype can be used as both a
reference implementation and a source of test data.
Testing. Python is a great tool for creating test data and for running tests.
Refactoring. C++ lacks the refactoring tool support available
for (e.g.) Java, but simple Python scripts can do the job well enough.
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