Calling C/C++ from Python?
⚡TLDR
To interface C/C++ in Python, ctypes, a built-in module in Python, is a great tool:
The Comprehensive Guide
How to Interface C/C++ functions
To activate C++ functions from Python:
- Wrap your C++ code inside
extern "C"
to counteract C++ name-mangling. Because sometimes names can be deceiving! - Compile your code into a shared library. Libraries are more fun when they're shared, right?
- Load and call the functions in Python using
ctypes
. It’s like making an international phone call.
Dealing with Data Structures
For complex data types and classes:
- Boost.Python: Provides an elegant and seamless interface for Python to directly interact with C++. It's like a two-way dictionary!
- pybind11: It's a light-weight library that provides bindings between modern C++ and Python. Less is more!
- SWIG: It's a tool that helps you to convert nearly all constructs of C++ to Python.
Gotchas and Debugging Tips
While binding C++ libraries, don't forget:
- All dependencies should be met. Sometimes, it's all about teamwork!
- To install the python-dev package when SWIG is around. It's like SWIG's best friend.
- Lastly, smack your library into a shared library suitable for your OS. Because one size definitely does NOT fit all!
Delving Deeper Into The Rabbit Hole
Thinking in terms of 'Speed'
Remember:
- Update the C/C++ code for maximum efficiency.
- It's wiser to avoid copying data between Python and C/C++ to minimize overhead.
- Memory is a scarce resource. Use it wisely!
Getting the hang of pybind11 and Boost.Python
Here are some tips for using these tools:
- You can test small changes using interactive Python sessions. No need for a full-fledged IDE!
- Punch automation with tools like CMake. Time is of the essence!
- Speed is nothing without control. Use Control C(++).
Cross-Compatibility
Ensure cross-platform support:
- Hide the platform-specific logic within C/C++. Less is more!
- Tools that work on all target platforms save time and effort.
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