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First steps

docs/basics.rst

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.. _basics:

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

.. code-block:: bash

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 enforce standard conformance: https://docs.microsoft.com/en-us/cpp/build/reference/permissive-standards-conformance?view=vs-2017

To compile and run the tests:

.. code-block:: batch

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 ..``.

.. seealso::

Advanced users who are already familiar with Boost.Python may want to skip
the tutorial and look at the test cases in the :file:`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:

.. code-block:: cpp

#include <pybind11/pybind11.h>

namespace py = pybind11;

.. note::

``pybind11/pybind11.h`` includes ``Python.h``, as such it must be the first file
included in any source file or header for `the same reasons as Python.h`_.

.. _the same reasons as Python.h: https://docs.python.org/3/extending/extending.html#a-simple-example

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

.. _simple_example:

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:

.. code-block:: cpp

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

For simplicity [#f1]_, we'll put both this function and the binding code into a file named :file:example.cpp with the following contents:

.. code-block:: cpp

#include <pybind11/pybind11.h>

namespace py = pybind11;

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

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

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

.. [#f1] In practice, implementation and binding code will generally be located in separate files.

The :func: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 :class:py::module_ <module> which is the main interface for creating bindings. The method :func: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:

.. code-block:: bash

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

.. note::

If you used :ref:`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 :ref:`building_manually`.

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

.. _python_example: https://github.com/pybind/python_example .. _cmake_example: https://github.com/pybind/cmake_example

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:

.. code-block:: pycon

$ 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_args:

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).

.. code-block:: cpp

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

:class:arg is one of several special tag classes which can be used to pass metadata into :func: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:

.. code-block:: pycon

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

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

.. code-block:: pycon

>>> 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:

.. code-block:: cpp

// 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 :var:_a suffix forms a C++11 literal which is equivalent to :class: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_args:

Default arguments

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

.. code-block:: cpp

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 :class:arg:

.. code-block:: cpp

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.

.. code-block:: pycon

>>> 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:

.. code-block:: cpp

// 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.

.. code-block:: cpp

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

These are then accessible from Python:

.. code-block:: pycon

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

.. _supported_types:

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 :doc:advanced/cast/index section.