1-DAV-202 Data Management 2023/24
Previously 2-INF-185 Data Source Integration
Lcpp
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Python is a very flexible language with many libraries, but programs in Python can be slow and take a lot of memory compared with programs written for example in C++. In this lecture we will see how to combine C++ and Python so that you write core algorithmic parts in C++ but use Python to do other less time-sensitive computations, such as parsing inputs. We will be using pybind11 library to do that.
Here is an example C++ code, which can be converted as an extension and used in Python:
#include <pybind11/pybind11.h>
#include <pybind11/stl.h>
#include <vector>
#include <string>
using std::vector;
using std::string;
// Here is your class code
struct MyClass {
MyClass() {}
int f(vector<string> arr) {
int ss = 0;
for (auto &s: arr) {
ss += s.size();
}
return ss;
}
};
// This is the binding code, every function you want to export, must be declared here
PYBIND11_MODULE(example, m) {
m.doc() = "pybind11 example plugin"; // optional module docstring
pybind11::class_<MyClass>(m, "MyClass")
.def(pybind11::init())
.def("f", &MyClass::f);
}
We can then compile this code to be used as Python module:
c++ -O3 -Wall -shared -std=c++11 -fPIC $(python3 -m pybind11 --includes) example.cc -o example$(python3-config --extension-suffix)
And then we can import it in Python (we need to be in same directory as compiled output):
import example
c = example.MyClass()
print(c.f(["aaa", "bb"]))
print(c.f([]))