slsDetectorPackage/libs/pybind/docs/basics.rst

First steps

This sections demonstrates the basic features of pybind11. Before getting started, make sure that development environment is set up to compile the included set of test cases.

Compiling the test cases

Linux/macOS

On Linux you'll need to install the python-dev or python3-dev packages as well as cmake. On macOS, the included python version works out of the box, but cmake must still be installed.

After installing the prerequisites, run

mkdir build
cd build
cmake ..
make check -j 4

The last line will both compile and run the tests.

Windows

On Windows, only Visual Studio 2017 and newer are supported.

Note

To use the C++17 in Visual Studio 2017 (MSVC 14.1), pybind11 requires the flag /permissive- to be passed to the compiler to enforce standard conformance. When building with Visual Studio 2019, this is not strictly necessary, but still advised.

To compile and run the tests:

mkdir build
cd build
cmake ..
cmake --build . --config Release --target check

This will create a Visual Studio project, compile and run the target, all from the command line.

Note

If all tests fail, make sure that the Python binary and the testcases are compiled for the same processor type and bitness (i.e. either i386 or x86_64). You can specify x86_64 as the target architecture for the generated Visual Studio project using cmake -A x64 ...

Advanced users who are already familiar with Boost.Python may want to skip the tutorial and look at the test cases in the tests directory, which exercise all features of pybind11.

Header and namespace conventions

For brevity, all code examples assume that the following two lines are present:

#include <pybind11/pybind11.h>

namespace py = pybind11;

Some features may require additional headers, but those will be specified as needed.

Creating bindings for a simple function

Let's start by creating Python bindings for an extremely simple function, which adds two numbers and returns their result:

int add(int i, int j) {
    return i + j;
}

For simplicity¹, we'll put both this function and the binding code into a file named example.cpp with the following contents:

#include <pybind11/pybind11.h>

int add(int i, int j) {
    return i + j;
}

PYBIND11_MODULE(example, m) {
    m.doc() = "pybind11 example plugin"; // optional module docstring

    m.def("add", &add, "A function that adds two numbers");
}

The PYBIND11_MODULE macro creates a function that will be called when an import statement is issued from within Python. The module name (example) is given as the first macro argument (it should not be in quotes). The second argument (m) defines a variable of type py::module_ <module> which is the main interface for creating bindings. The method module_::def generates binding code that exposes the add() function to Python.

Note

Notice how little code was needed to expose our function to Python: all details regarding the function's parameters and return value were automatically inferred using template metaprogramming. This overall approach and the used syntax are borrowed from Boost.Python, though the underlying implementation is very different.

pybind11 is a header-only library, hence it is not necessary to link against any special libraries and there are no intermediate (magic) translation steps. On Linux, the above example can be compiled using the following command:

$ c++ -O3 -Wall -shared -std=c++11 -fPIC $(python3 -m pybind11 --includes) example.cpp -o example$(python3-config --extension-suffix)

Note

If you used include_as_a_submodule to get the pybind11 source, then use $(python3-config --includes) -Iextern/pybind11/include instead of $(python3 -m pybind11 --includes) in the above compilation, as explained in building_manually.

For more details on the required compiler flags on Linux and macOS, see building_manually. For complete cross-platform compilation instructions, refer to the compiling page.

The python_example and cmake_example repositories are also a good place to start. They are both complete project examples with cross-platform build systems. The only difference between the two is that python_example uses Python's setuptools to build the module, while cmake_example uses CMake (which may be preferable for existing C++ projects).

Building the above C++ code will produce a binary module file that can be imported to Python. Assuming that the compiled module is located in the current directory, the following interactive Python session shows how to load and execute the example:

$ python
Python 3.9.10 (main, Jan 15 2022, 11:48:04)
[Clang 13.0.0 (clang-1300.0.29.3)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import example
>>> example.add(1, 2)
3
>>>

Keyword arguments

With a simple code modification, it is possible to inform Python about the names of the arguments ("i" and "j" in this case).

m.def("add", &add, "A function which adds two numbers",
      py::arg("i"), py::arg("j"));

arg is one of several special tag classes which can be used to pass metadata into module_::def. With this modified binding code, we can now call the function using keyword arguments, which is a more readable alternative particularly for functions taking many parameters:

>>> import example
>>> example.add(i=1, j=2)
3L

The keyword names also appear in the function signatures within the documentation.

>>> help(example)

....

FUNCTIONS
    add(...)
        Signature : (i: int, j: int) -> int

        A function which adds two numbers

A shorter notation for named arguments is also available:

// regular notation
m.def("add1", &add, py::arg("i"), py::arg("j"));
// shorthand
using namespace pybind11::literals;
m.def("add2", &add, "i"_a, "j"_a);

The _a suffix forms a C++11 literal which is equivalent to arg. Note that the literal operator must first be made visible with the directive using namespace pybind11::literals. This does not bring in anything else from the pybind11 namespace except for literals.

Default arguments

Suppose now that the function to be bound has default arguments, e.g.:

int add(int i = 1, int j = 2) {
    return i + j;
}

Unfortunately, pybind11 cannot automatically extract these parameters, since they are not part of the function's type information. However, they are simple to specify using an extension of arg:

m.def("add", &add, "A function which adds two numbers",
      py::arg("i") = 1, py::arg("j") = 2);

The default values also appear within the documentation.

>>> help(example)

....

FUNCTIONS
    add(...)
        Signature : (i: int = 1, j: int = 2) -> int

        A function which adds two numbers

The shorthand notation is also available for default arguments:

// regular notation
m.def("add1", &add, py::arg("i") = 1, py::arg("j") = 2);
// shorthand
m.def("add2", &add, "i"_a=1, "j"_a=2);

Exporting variables

To expose a value from C++, use the attr function to register it in a module as shown below. Built-in types and general objects (more on that later) are automatically converted when assigned as attributes, and can be explicitly converted using the function py::cast.

PYBIND11_MODULE(example, m) {
    m.attr("the_answer") = 42;
    py::object world = py::cast("World");
    m.attr("what") = world;
}

These are then accessible from Python:

>>> import example
>>> example.the_answer
42
>>> example.what
'World'

Supported data types

A large number of data types are supported out of the box and can be used seamlessly as functions arguments, return values or with py::cast in general. For a full overview, see the advanced/cast/index section.

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1. In practice, implementation and binding code will generally be located in separate files.↩︎