diff options
Diffstat (limited to '3rdparty/pybind11/docs/advanced/pycpp')
| -rw-r--r-- | 3rdparty/pybind11/docs/advanced/pycpp/numpy.rst | 84 | ||||
| -rw-r--r-- | 3rdparty/pybind11/docs/advanced/pycpp/object.rst | 95 | ||||
| -rw-r--r-- | 3rdparty/pybind11/docs/advanced/pycpp/utilities.rst | 4 |
3 files changed, 157 insertions, 26 deletions
diff --git a/3rdparty/pybind11/docs/advanced/pycpp/numpy.rst b/3rdparty/pybind11/docs/advanced/pycpp/numpy.rst index 458f99e9..19ed10b3 100644 --- a/3rdparty/pybind11/docs/advanced/pycpp/numpy.rst +++ b/3rdparty/pybind11/docs/advanced/pycpp/numpy.rst @@ -57,17 +57,17 @@ specification. struct buffer_info { void *ptr; - ssize_t itemsize; + py::ssize_t itemsize; std::string format; - ssize_t ndim; - std::vector<ssize_t> shape; - std::vector<ssize_t> strides; + py::ssize_t ndim; + std::vector<py::ssize_t> shape; + std::vector<py::ssize_t> strides; }; To create a C++ function that can take a Python buffer object as an argument, simply use the type ``py::buffer`` as one of its arguments. Buffers can exist in a great variety of configurations, hence some safety checks are usually -necessary in the function body. Below, you can see an basic example on how to +necessary in the function body. Below, you can see a basic example on how to define a custom constructor for the Eigen double precision matrix (``Eigen::MatrixXd``) type, which supports initialization from compatible buffer objects (e.g. a NumPy matrix). @@ -81,7 +81,7 @@ buffer objects (e.g. a NumPy matrix). constexpr bool rowMajor = Matrix::Flags & Eigen::RowMajorBit; py::class_<Matrix>(m, "Matrix", py::buffer_protocol()) - .def("__init__", [](Matrix &m, py::buffer b) { + .def(py::init([](py::buffer b) { typedef Eigen::Stride<Eigen::Dynamic, Eigen::Dynamic> Strides; /* Request a buffer descriptor from Python */ @@ -101,8 +101,8 @@ buffer objects (e.g. a NumPy matrix). auto map = Eigen::Map<Matrix, 0, Strides>( static_cast<Scalar *>(info.ptr), info.shape[0], info.shape[1], strides); - new (&m) Matrix(map); - }); + return Matrix(map); + })); For reference, the ``def_buffer()`` call for this Eigen data type should look as follows: @@ -274,9 +274,9 @@ simply using ``vectorize``). py::buffer_info buf3 = result.request(); - double *ptr1 = (double *) buf1.ptr, - *ptr2 = (double *) buf2.ptr, - *ptr3 = (double *) buf3.ptr; + double *ptr1 = static_cast<double *>(buf1.ptr); + double *ptr2 = static_cast<double *>(buf2.ptr); + double *ptr3 = static_cast<double *>(buf3.ptr); for (size_t idx = 0; idx < buf1.shape[0]; idx++) ptr3[idx] = ptr1[idx] + ptr2[idx]; @@ -309,17 +309,17 @@ where ``N`` gives the required dimensionality of the array: m.def("sum_3d", [](py::array_t<double> x) { auto r = x.unchecked<3>(); // x must have ndim = 3; can be non-writeable double sum = 0; - for (ssize_t i = 0; i < r.shape(0); i++) - for (ssize_t j = 0; j < r.shape(1); j++) - for (ssize_t k = 0; k < r.shape(2); k++) + for (py::ssize_t i = 0; i < r.shape(0); i++) + for (py::ssize_t j = 0; j < r.shape(1); j++) + for (py::ssize_t k = 0; k < r.shape(2); k++) sum += r(i, j, k); return sum; }); m.def("increment_3d", [](py::array_t<double> x) { auto r = x.mutable_unchecked<3>(); // Will throw if ndim != 3 or flags.writeable is false - for (ssize_t i = 0; i < r.shape(0); i++) - for (ssize_t j = 0; j < r.shape(1); j++) - for (ssize_t k = 0; k < r.shape(2); k++) + for (py::ssize_t i = 0; i < r.shape(0); i++) + for (py::ssize_t j = 0; j < r.shape(1); j++) + for (py::ssize_t k = 0; k < r.shape(2); k++) r(i, j, k) += 1.0; }, py::arg().noconvert()); @@ -371,6 +371,8 @@ Ellipsis Python 3 provides a convenient ``...`` ellipsis notation that is often used to slice multidimensional arrays. For instance, the following snippet extracts the middle dimensions of a tensor with the first and last index set to zero. +In Python 2, the syntactic sugar ``...`` is not available, but the singleton +``Ellipsis`` (of type ``ellipsis``) can still be used directly. .. code-block:: python @@ -384,3 +386,51 @@ operation on the C++ side: py::array a = /* A NumPy array */; py::array b = a[py::make_tuple(0, py::ellipsis(), 0)]; + +.. versionchanged:: 2.6 + ``py::ellipsis()`` is now also avaliable in Python 2. + +Memory view +=========== + +For a case when we simply want to provide a direct accessor to C/C++ buffer +without a concrete class object, we can return a ``memoryview`` object. Suppose +we wish to expose a ``memoryview`` for 2x4 uint8_t array, we can do the +following: + +.. code-block:: cpp + + const uint8_t buffer[] = { + 0, 1, 2, 3, + 4, 5, 6, 7 + }; + m.def("get_memoryview2d", []() { + return py::memoryview::from_buffer( + buffer, // buffer pointer + { 2, 4 }, // shape (rows, cols) + { sizeof(uint8_t) * 4, sizeof(uint8_t) } // strides in bytes + ); + }) + +This approach is meant for providing a ``memoryview`` for a C/C++ buffer not +managed by Python. The user is responsible for managing the lifetime of the +buffer. Using a ``memoryview`` created in this way after deleting the buffer in +C++ side results in undefined behavior. + +We can also use ``memoryview::from_memory`` for a simple 1D contiguous buffer: + +.. code-block:: cpp + + m.def("get_memoryview1d", []() { + return py::memoryview::from_memory( + buffer, // buffer pointer + sizeof(uint8_t) * 8 // buffer size + ); + }) + +.. note:: + + ``memoryview::from_memory`` is not available in Python 2. + +.. versionchanged:: 2.6 + ``memoryview::from_memory`` added. diff --git a/3rdparty/pybind11/docs/advanced/pycpp/object.rst b/3rdparty/pybind11/docs/advanced/pycpp/object.rst index 117131ed..6c7525ce 100644 --- a/3rdparty/pybind11/docs/advanced/pycpp/object.rst +++ b/3rdparty/pybind11/docs/advanced/pycpp/object.rst @@ -1,6 +1,8 @@ Python types ############ +.. _wrappers: + Available wrappers ================== @@ -13,6 +15,13 @@ Available types include :class:`handle`, :class:`object`, :class:`bool_`, :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. + +.. _casting_back_and_forth: + Casting back and forth ====================== @@ -47,20 +56,21 @@ 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"); + py::object Decimal = py::module_::import("decimal").attr("Decimal"); .. code-block:: cpp // Try to import scipy - py::object scipy = py::module::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 +It is also possible to call Python classes, functions and methods via ``operator()``. .. code-block:: cpp @@ -71,11 +81,11 @@ via ``operator()``. .. code-block:: cpp // Use Python to make our directories - py::object os = py::module::import("os"); + 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 +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 @@ -99,8 +109,8 @@ Python method. 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`` +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 @@ -168,3 +178,74 @@ Generalized unpacking according to PEP448_ is also supported: 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). diff --git a/3rdparty/pybind11/docs/advanced/pycpp/utilities.rst b/3rdparty/pybind11/docs/advanced/pycpp/utilities.rst index 369e7c94..c15051fb 100644 --- a/3rdparty/pybind11/docs/advanced/pycpp/utilities.rst +++ b/3rdparty/pybind11/docs/advanced/pycpp/utilities.rst @@ -42,7 +42,7 @@ redirects output to the corresponding Python streams: m.def("noisy_func", []() { py::scoped_ostream_redirect stream( std::cout, // std::ostream& - py::module::import("sys").attr("stdout") // Python output + py::module_::import("sys").attr("stdout") // Python output ); call_noisy_func(); }); @@ -104,7 +104,7 @@ can be used. ... // Evaluate in scope of main module - py::object scope = py::module::import("__main__").attr("__dict__"); + py::object scope = py::module_::import("__main__").attr("__dict__"); // Evaluate an isolated expression int result = py::eval("my_variable + 10", scope).cast<int>(); |