mirror of
https://gitlab.com/kicad/code/kicad.git
synced 2024-11-24 23:45:02 +00:00
287 lines
8.8 KiB
ReStructuredText
287 lines
8.8 KiB
ReStructuredText
Python types
|
|
############
|
|
|
|
.. _wrappers:
|
|
|
|
Available wrappers
|
|
==================
|
|
|
|
All major Python types are available as thin C++ wrapper classes. These
|
|
can also be used as function parameters -- see :ref:`python_objects_as_args`.
|
|
|
|
Available types include :class:`handle`, :class:`object`, :class:`bool_`,
|
|
:class:`int_`, :class:`float_`, :class:`str`, :class:`bytes`, :class:`tuple`,
|
|
:class:`list`, :class:`dict`, :class:`slice`, :class:`none`, :class:`capsule`,
|
|
:class:`iterable`, :class:`iterator`, :class:`function`, :class:`buffer`,
|
|
:class:`array`, and :class:`array_t`.
|
|
|
|
.. warning::
|
|
|
|
Be sure to review the :ref:`pytypes_gotchas` before using this heavily in
|
|
your C++ API.
|
|
|
|
.. _instantiating_compound_types:
|
|
|
|
Instantiating compound Python types from C++
|
|
============================================
|
|
|
|
Dictionaries can be initialized in the :class:`dict` constructor:
|
|
|
|
.. code-block:: cpp
|
|
|
|
using namespace pybind11::literals; // to bring in the `_a` literal
|
|
py::dict d("spam"_a=py::none(), "eggs"_a=42);
|
|
|
|
A tuple of python objects can be instantiated using :func:`py::make_tuple`:
|
|
|
|
.. code-block:: cpp
|
|
|
|
py::tuple tup = py::make_tuple(42, py::none(), "spam");
|
|
|
|
Each element is converted to a supported Python type.
|
|
|
|
A `simple namespace`_ can be instantiated using
|
|
|
|
.. code-block:: cpp
|
|
|
|
using namespace pybind11::literals; // to bring in the `_a` literal
|
|
py::object SimpleNamespace = py::module_::import("types").attr("SimpleNamespace");
|
|
py::object ns = SimpleNamespace("spam"_a=py::none(), "eggs"_a=42);
|
|
|
|
Attributes on a namespace can be modified with the :func:`py::delattr`,
|
|
:func:`py::getattr`, and :func:`py::setattr` functions. Simple namespaces can
|
|
be useful as lightweight stand-ins for class instances.
|
|
|
|
.. _simple namespace: https://docs.python.org/3/library/types.html#types.SimpleNamespace
|
|
|
|
.. _casting_back_and_forth:
|
|
|
|
Casting back and forth
|
|
======================
|
|
|
|
In this kind of mixed code, it is often necessary to convert arbitrary C++
|
|
types to Python, which can be done using :func:`py::cast`:
|
|
|
|
.. code-block:: cpp
|
|
|
|
MyClass *cls = ...;
|
|
py::object obj = py::cast(cls);
|
|
|
|
The reverse direction uses the following syntax:
|
|
|
|
.. code-block:: cpp
|
|
|
|
py::object obj = ...;
|
|
MyClass *cls = obj.cast<MyClass *>();
|
|
|
|
When conversion fails, both directions throw the exception :class:`cast_error`.
|
|
|
|
.. _python_libs:
|
|
|
|
Accessing Python libraries from C++
|
|
===================================
|
|
|
|
It is also possible to import objects defined in the Python standard
|
|
library or available in the current Python environment (``sys.path``) and work
|
|
with these in C++.
|
|
|
|
This example obtains a reference to the Python ``Decimal`` class.
|
|
|
|
.. code-block:: cpp
|
|
|
|
// Equivalent to "from decimal import Decimal"
|
|
py::object Decimal = py::module_::import("decimal").attr("Decimal");
|
|
|
|
.. code-block:: cpp
|
|
|
|
// Try to import scipy
|
|
py::object scipy = py::module_::import("scipy");
|
|
return scipy.attr("__version__");
|
|
|
|
|
|
.. _calling_python_functions:
|
|
|
|
Calling Python functions
|
|
========================
|
|
|
|
It is also possible to call Python classes, functions and methods
|
|
via ``operator()``.
|
|
|
|
.. code-block:: cpp
|
|
|
|
// Construct a Python object of class Decimal
|
|
py::object pi = Decimal("3.14159");
|
|
|
|
.. code-block:: cpp
|
|
|
|
// Use Python to make our directories
|
|
py::object os = py::module_::import("os");
|
|
py::object makedirs = os.attr("makedirs");
|
|
makedirs("/tmp/path/to/somewhere");
|
|
|
|
One can convert the result obtained from Python to a pure C++ version
|
|
if a ``py::class_`` or type conversion is defined.
|
|
|
|
.. code-block:: cpp
|
|
|
|
py::function f = <...>;
|
|
py::object result_py = f(1234, "hello", some_instance);
|
|
MyClass &result = result_py.cast<MyClass>();
|
|
|
|
.. _calling_python_methods:
|
|
|
|
Calling Python methods
|
|
========================
|
|
|
|
To call an object's method, one can again use ``.attr`` to obtain access to the
|
|
Python method.
|
|
|
|
.. code-block:: cpp
|
|
|
|
// Calculate e^π in decimal
|
|
py::object exp_pi = pi.attr("exp")();
|
|
py::print(py::str(exp_pi));
|
|
|
|
In the example above ``pi.attr("exp")`` is a *bound method*: it will always call
|
|
the method for that same instance of the class. Alternately one can create an
|
|
*unbound method* via the Python class (instead of instance) and pass the ``self``
|
|
object explicitly, followed by other arguments.
|
|
|
|
.. code-block:: cpp
|
|
|
|
py::object decimal_exp = Decimal.attr("exp");
|
|
|
|
// Compute the e^n for n=0..4
|
|
for (int n = 0; n < 5; n++) {
|
|
py::print(decimal_exp(Decimal(n));
|
|
}
|
|
|
|
Keyword arguments
|
|
=================
|
|
|
|
Keyword arguments are also supported. In Python, there is the usual call syntax:
|
|
|
|
.. code-block:: python
|
|
|
|
def f(number, say, to):
|
|
... # function code
|
|
|
|
|
|
f(1234, say="hello", to=some_instance) # keyword call in Python
|
|
|
|
In C++, the same call can be made using:
|
|
|
|
.. code-block:: cpp
|
|
|
|
using namespace pybind11::literals; // to bring in the `_a` literal
|
|
f(1234, "say"_a="hello", "to"_a=some_instance); // keyword call in C++
|
|
|
|
Unpacking arguments
|
|
===================
|
|
|
|
Unpacking of ``*args`` and ``**kwargs`` is also possible and can be mixed with
|
|
other arguments:
|
|
|
|
.. code-block:: cpp
|
|
|
|
// * unpacking
|
|
py::tuple args = py::make_tuple(1234, "hello", some_instance);
|
|
f(*args);
|
|
|
|
// ** unpacking
|
|
py::dict kwargs = py::dict("number"_a=1234, "say"_a="hello", "to"_a=some_instance);
|
|
f(**kwargs);
|
|
|
|
// mixed keywords, * and ** unpacking
|
|
py::tuple args = py::make_tuple(1234);
|
|
py::dict kwargs = py::dict("to"_a=some_instance);
|
|
f(*args, "say"_a="hello", **kwargs);
|
|
|
|
Generalized unpacking according to PEP448_ is also supported:
|
|
|
|
.. code-block:: cpp
|
|
|
|
py::dict kwargs1 = py::dict("number"_a=1234);
|
|
py::dict kwargs2 = py::dict("to"_a=some_instance);
|
|
f(**kwargs1, "say"_a="hello", **kwargs2);
|
|
|
|
.. seealso::
|
|
|
|
The file :file:`tests/test_pytypes.cpp` contains a complete
|
|
example that demonstrates passing native Python types in more detail. The
|
|
file :file:`tests/test_callbacks.cpp` presents a few examples of calling
|
|
Python functions from C++, including keywords arguments and unpacking.
|
|
|
|
.. _PEP448: https://www.python.org/dev/peps/pep-0448/
|
|
|
|
.. _implicit_casting:
|
|
|
|
Implicit casting
|
|
================
|
|
|
|
When using the C++ interface for Python types, or calling Python functions,
|
|
objects of type :class:`object` are returned. It is possible to invoke implicit
|
|
conversions to subclasses like :class:`dict`. The same holds for the proxy objects
|
|
returned by ``operator[]`` or ``obj.attr()``.
|
|
Casting to subtypes improves code readability and allows values to be passed to
|
|
C++ functions that require a specific subtype rather than a generic :class:`object`.
|
|
|
|
.. code-block:: cpp
|
|
|
|
#include <pybind11/numpy.h>
|
|
using namespace pybind11::literals;
|
|
|
|
py::module_ os = py::module_::import("os");
|
|
py::module_ path = py::module_::import("os.path"); // like 'import os.path as path'
|
|
py::module_ np = py::module_::import("numpy"); // like 'import numpy as np'
|
|
|
|
py::str curdir_abs = path.attr("abspath")(path.attr("curdir"));
|
|
py::print(py::str("Current directory: ") + curdir_abs);
|
|
py::dict environ = os.attr("environ");
|
|
py::print(environ["HOME"]);
|
|
py::array_t<float> arr = np.attr("ones")(3, "dtype"_a="float32");
|
|
py::print(py::repr(arr + py::int_(1)));
|
|
|
|
These implicit conversions are available for subclasses of :class:`object`; there
|
|
is no need to call ``obj.cast()`` explicitly as for custom classes, see
|
|
:ref:`casting_back_and_forth`.
|
|
|
|
.. note::
|
|
If a trivial conversion via move constructor is not possible, both implicit and
|
|
explicit casting (calling ``obj.cast()``) will attempt a "rich" conversion.
|
|
For instance, ``py::list env = os.attr("environ");`` will succeed and is
|
|
equivalent to the Python code ``env = list(os.environ)`` that produces a
|
|
list of the dict keys.
|
|
|
|
.. TODO: Adapt text once PR #2349 has landed
|
|
|
|
Handling exceptions
|
|
===================
|
|
|
|
Python exceptions from wrapper classes will be thrown as a ``py::error_already_set``.
|
|
See :ref:`Handling exceptions from Python in C++
|
|
<handling_python_exceptions_cpp>` for more information on handling exceptions
|
|
raised when calling C++ wrapper classes.
|
|
|
|
.. _pytypes_gotchas:
|
|
|
|
Gotchas
|
|
=======
|
|
|
|
Default-Constructed Wrappers
|
|
----------------------------
|
|
|
|
When a wrapper type is default-constructed, it is **not** a valid Python object (i.e. it is not ``py::none()``). It is simply the same as
|
|
``PyObject*`` null pointer. To check for this, use
|
|
``static_cast<bool>(my_wrapper)``.
|
|
|
|
Assigning py::none() to wrappers
|
|
--------------------------------
|
|
|
|
You may be tempted to use types like ``py::str`` and ``py::dict`` in C++
|
|
signatures (either pure C++, or in bound signatures), and assign them default
|
|
values of ``py::none()``. However, in a best case scenario, it will fail fast
|
|
because ``None`` is not convertible to that type (e.g. ``py::dict``), or in a
|
|
worse case scenario, it will silently work but corrupt the types you want to
|
|
work with (e.g. ``py::str(py::none())`` will yield ``"None"`` in Python).
|