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pybind11
Commit d4258baf by Wenzel Jakob
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generate more compact binaries

parent fa70d302
Showing with 568 additions and 365 deletions
CMakeLists.txt
......@@ -44,11 +44,11 @@ include_directories(${PYTHON_INCLUDE_DIR} include)
add_library(example SHARED
include/pybind/cast.h
include/pybind/common.h
include/pybind/mpl.h
include/pybind/operators.h
include/pybind/pybind.h
include/pybind/pytypes.h
include/pybind/typeid.h
include/pybind/numpy.h
example/example.cpp
example/example1.cpp
example/example2.cpp
......@@ -59,6 +59,7 @@ add_library(example SHARED
example/example7.cpp
example/example8.cpp
example/example9.cpp
example/example10.cpp
)
set_target_properties(example PROPERTIES PREFIX "")
......
README.md
......@@ -17,13 +17,13 @@ become an excessively large and unnecessary dependency.
Think of this library as a tiny self-contained version of Boost.Python with
everything stripped away that isn't relevant for binding generation. The whole
codebase requires just over 2000 lines of code and just depends on Python and
codebase requires just over 2000 lines of code and only depends on Python and
the C++ standard library. This compact implementation was possible thanks to
some of the new C++11 language features (tuples, lambda functions and variadic
templates), and by only targeting Python 3.x and higher.
## Core features
The following C++ features can be mapped to Python
The following core C++ features can be mapped to Python
- Functions accepting and returning custom data structures per value, reference, or pointer
- Instance methods and static methods
......@@ -44,12 +44,18 @@ In addition to the core functionality, pybind11 provides some extra goodies:
Pythons' buffer protocols. This is handy e.g. for fast conversion between
C++ matrix classes like Eigen and NumPy without expensive copy operations.
- pybind11 can automatically vectorize functions so that they are transparently
applied to all entries of one or more NumPy array arguments.
- Python's slice-based access and assignment operations can be supported with
just a few lines of code.
- pybind11 uses C++11 move constructors and move assignment operators whenever
possible to efficiently transfer custom data types.
- It is possible to bind C++11 lambda functions with captured variables. The
lambda capture data is stored inside the resulting Python function object.
## Limitations
Various things that Boost.Python can do remain unsupported, e.g.:
......@@ -104,3 +110,152 @@ PYTHON_PLUGIN(example) {
return m.ptr();
}
```
## A collection of specific use cases (mostly buffer-related for now)
For brevity, let's set
```C++
namespace py = pybind;
```
### Exposing buffer views
Python supports an extremely general and convenient approach for exchanging
data between plugin libraries. Types can expose a buffer view which provides
fast direct access to the raw internal representation. Suppose we want to bind
the following simplistic Matrix class:
```C++
class Matrix {
public:
Matrix(size_t rows, size_t cols) : m_rows(rows), m_cols(cols) {
m_data = new float[rows*cols];
}
float *data() { return m_data; }
size_t rows() const { return m_rows; }
size_t cols() const { return m_cols; }
private:
size_t m_rows, m_cols;
float *m_data;
};
```
The following binding code exposes the ``Matrix`` contents as a buffer object,
making it possible to cast Matrixes into NumPy arrays. It is even possible to
completely avoid copy operations with Python expressions like
``np.array(matrix_instance, copy = False)``.
```C++
py::class_<Matrix>(m, "Matrix")
.def_buffer([](Matrix &m) -> py::buffer_info {
return py::buffer_info(
m.data(), /* Pointer to buffer */
sizeof(float), /* Size of one scalar */
py::format_descriptor<float>::value(), /* Python struct-style format descriptor */
2, /* Number of dimensions */
{ m.rows(), m.cols() }, /* Buffer dimensions */
{ sizeof(float) * m.rows(), /* Strides (in bytes) for each index */
sizeof(float) }
);
});
```
The snippet above binds a lambda function, which can create ``py::buffer_info``
description records on demand describing a given matrix. The contents of
``py::buffer_info`` mirror the Python buffer protocol specification.
```C++
struct buffer_info {
void *ptr;
size_t itemsize;
std::string format;
int ndim;
std::vector<size_t> shape;
std::vector<size_t> strides;
};
```
### Taking Python buffer objects as arguments
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
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).
```C++
py::class_<Eigen::MatrixXd>(m, "MatrixXd")
.def("__init__", [](Eigen::MatrixXd &m, py::buffer b) {
/* Request a buffer descriptor from Python */
py::buffer_info info = b.request();
/* Some sanity checks ... */
if (info.format != py::format_descriptor<double>::value())
throw std::runtime_error("Incompatible format: expected a double array!");
if (info.ndim != 2)
throw std::runtime_error("Incompatible buffer dimension!");
if (info.strides[0] == sizeof(double)) {
/* Buffer has the right layout -- directly copy. */
new (&m) Eigen::MatrixXd(info.shape[0], info.shape[1]);
memcpy(m.data(), info.ptr, sizeof(double) * m.size());
} else {
/* Oops -- the buffer is transposed */
new (&m) Eigen::MatrixXd(info.shape[1], info.shape[0]);
memcpy(m.data(), info.ptr, sizeof(double) * m.size());
m.transposeInPlace();
}
});
```
### Taking NumPy arrays as arguments
By exchanging ``py::buffer`` with ``py::array`` in the above snippet, we can
restrict the function so that it only accepts NumPy arrays (rather than any
type of Python object satisfying the buffer object protocol).
In many situations, we want to define a function which only accepts a NumPy
array of a certain data type. This is possible via the ``py::array_dtype<T>``
template. For instance, the following function requires the argument to be a
dense array of doubles in C-style ordering.
```C++
void f(py::array_dtype<double> array);
```
When it is invoked with a different type (e.g. an integer), the binding code
will attempt to cast the input into a NumPy array of the requested type.
### Auto-vectorizing a function over NumPy array arguments
Suppose we want to bind a function with the following signature to Python so
that it can process arbitrary NumPy array arguments (vectors, matrices, general
N-D arrays) in addition to its normal arguments:
```C++
double my_func(int x, float y, double z);
```
This is extremely simple to do!
```C++
m.def("vectorized_func", py::vectorize(my_func));
```
Invoking the function like below causes 4 calls to be made to ``my_func`` with
each of the the array elements. The result is returned as a NumPy array of type
``numpy.dtype.float64``.
```Python
>>> x = np.array([[1, 3],[5, 7]])
>>> y = np.array([[2, 4],[6, 8]])
>>> z = 3
>>> result = vectorized_func(x, y, z)
```
The scalar argument ``z`` is transparently replicated 4 times. The input
arrays ``x`` and ``y`` are automatically converted into the right types (they
are of type ``numpy.dtype.int64`` but need to be ``numpy.dtype.int32`` and
``numpy.dtype.float32``, respectively)
Sometimes we might want to explitly exclude an argument from the vectorization
because it makes little sense to wrap it in a NumPy array. For instance,
suppose the function signature was
```C++
double my_func(int x, float y, my_custom_type *z);
```
This can be done with a stateful Lambda closure:
```C++
// Vectorize a lambda function with a capture object (e.g. to exclude some arguments from the vectorization)
m.def("vectorized_func",
[](py::array_dtype<int> x, py::array_dtype<float> y, my_custom_type *z) {
auto stateful_closure = [z](int x, float y) { return my_func(x, y, z); };
return py::vectorize(stateful_closure)(x, y);
}
);
```
example/example.cpp
......@@ -18,6 +18,7 @@ void init_ex6(py::module &);
void init_ex7(py::module &);
void init_ex8(py::module &);
void init_ex9(py::module &);
void init_ex10(py::module &);
PYTHON_PLUGIN(example) {
py::module m("example", "pybind example plugin");
......@@ -31,6 +32,7 @@ PYTHON_PLUGIN(example) {
init_ex7(m);
init_ex8(m);
init_ex9(m);
init_ex10(m);
return m.ptr();
}
example/example10.cpp 0 → 100644
/*
example/example10.cpp -- Example 10: auto-vectorize functions for NumPy
Copyright (c) 2015 Wenzel Jakob <wenzel@inf.ethz.ch>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#include "example.h"
#include <pybind/numpy.h>
double my_func(int x, float y, double z) {
std::cout << "my_func(x:int=" << x << ", y:float=" << y << ", z:float=" << z << ")" << std::endl;
return x*y*z;
}
void init_ex10(py::module &m) {
// Vectorize all arguments (though non-vector arguments are also allowed)
m.def("vectorized_func", py::vectorize(my_func));
// Vectorize a lambda function with a capture object (e.g. to exclude some arguments from the vectorization)
m.def("vectorized_func2",
[](py::array_dtype<int> x, py::array_dtype<float> y, float z) {
return py::vectorize([z](int x, float y) { return my_func(x, y, z); })(x, y);
}
);
}
example/example10.py 0 → 100644
#!/usr/bin/env python3
import sys
sys.path.append('.')
import example
import numpy as np
from example import vectorized_func
from example import vectorized_func2
for f in [vectorized_func, vectorized_func2]:
print(f(1, 2, 3))
print(f(np.array(1), np.array(2), 3))
print(f(np.array([1, 3]), np.array([2, 4]), 3))
print(f(np.array([[1, 3, 5], [7, 9, 11]]), np.array([[2, 4, 6], [8, 10, 12]]), 3))
print(np.array([[1, 3, 5], [7, 9, 11]])* np.array([[2, 4, 6], [8, 10, 12]])*3)
include/pybind/common.h
......@@ -30,10 +30,10 @@
#include <vector>
#include <string>
#include <stdexcept>
#include <functional>
#include <unordered_map>
#include <iostream>
#include <memory>
#include <functional>
/// Include Python header, disable linking to pythonX_d.lib on Windows in debug mode
#if defined(_MSC_VER)
......@@ -79,31 +79,27 @@ enum class return_value_policy : int {
/// Format strings for basic number types
template <typename type> struct format_descriptor { };
template<> struct format_descriptor<int8_t> { static std::string value() { return "b"; }; };
template<> struct format_descriptor<uint8_t> { static std::string value() { return "B"; }; };
template<> struct format_descriptor<int16_t> { static std::string value() { return "h"; }; };
template<> struct format_descriptor<uint16_t> { static std::string value() { return "H"; }; };
template<> struct format_descriptor<int32_t> { static std::string value() { return "i"; }; };
template<> struct format_descriptor<uint32_t> { static std::string value() { return "I"; }; };
template<> struct format_descriptor<int64_t> { static std::string value() { return "q"; }; };
template<> struct format_descriptor<uint64_t> { static std::string value() { return "Q"; }; };
template<> struct format_descriptor<float> { static std::string value() { return "f"; }; };
template<> struct format_descriptor<double> { static std::string value() { return "d"; }; };
#define DECL_FMT(t, n) template<> struct format_descriptor<t> { static std::string value() { return n; }; };
DECL_FMT(int8_t, "b"); DECL_FMT(uint8_t, "B"); DECL_FMT(int16_t, "h"); DECL_FMT(uint16_t, "H");
DECL_FMT(int32_t, "i"); DECL_FMT(uint32_t, "I"); DECL_FMT(int64_t, "q"); DECL_FMT(uint64_t, "Q");
DECL_FMT(float , "f"); DECL_FMT(double, "d");
#undef DECL_FMT
/// Information record describing a Python buffer object
struct buffer_info {
void *ptr;
size_t itemsize;
size_t itemsize, count;
std::string format; // for dense contents, this should be set to format_descriptor<T>::value
int ndim;
std::vector<size_t> shape;
std::vector<size_t> strides;
buffer_info(void *ptr, size_t itemsize, const std::string &format,
int ndim, const std::vector<size_t> &shape,
const std::vector<size_t> &strides)
buffer_info(void *ptr, size_t itemsize, const std::string &format, int ndim,
const std::vector<size_t> &shape, const std::vector<size_t> &strides)
: ptr(ptr), itemsize(itemsize), format(format), ndim(ndim),
shape(shape), strides(strides) {}
shape(shape), strides(strides) {
count = 1; for (int i=0; i<ndim; ++i) count *= shape[i];
}
};
// C++ bindings of core Python exceptions
......@@ -140,7 +136,29 @@ struct internals {
std::unordered_map<void *, PyObject *> registered_instances;
};
/// Return a reference to the current 'internals' information
inline internals &get_internals();
/// Index sequence for convenient template metaprogramming involving tuples
template<size_t ...> struct index_sequence { };
template<size_t N, size_t ...S> struct make_index_sequence : make_index_sequence <N - 1, N - 1, S...> { };
template<size_t ...S> struct make_index_sequence <0, S...> { typedef index_sequence<S...> type; };
/// Strip the class from a method type
template <typename T> struct remove_class {};
template <typename C, typename R, typename... A> struct remove_class<R (C::*)(A...)> { typedef R type(A...); };
template <typename C, typename R, typename... A> struct remove_class<R (C::*)(A...) const> { typedef R type(A...); };
/// Helper template to strip away type modifiers
template <typename T> struct decay { typedef T type; };
template <typename T> struct decay<const T> { typedef typename decay<T>::type type; };
template <typename T> struct decay<T*> { typedef typename decay<T>::type type; };
template <typename T> struct decay<T&> { typedef typename decay<T>::type type; };
template <typename T> struct decay<T&&> { typedef typename decay<T>::type type; };
template <typename T, size_t N> struct decay<const T[N]> { typedef typename decay<T>::type type; };
template <typename T, size_t N> struct decay<T[N]> { typedef typename decay<T>::type type; };
/// Helper type to replace 'void' in some expressions
struct void_type { };
NAMESPACE_END(detail)
NAMESPACE_END(pybind)
include/pybind/mpl.h deleted 100644 → 0
/*
pybind/mpl.h: Simple library for type manipulation and template metaprogramming
Copyright (c) 2015 Wenzel Jakob <wenzel@inf.ethz.ch>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#pragma once
#include <pybind/common.h>
#include <tuple>
NAMESPACE_BEGIN(pybind)
NAMESPACE_BEGIN(mpl)
/// Index sequence for convenient template metaprogramming involving tuples
template<size_t ...> struct index_sequence { };
template<size_t N, size_t ...S> struct make_index_sequence : make_index_sequence <N - 1, N - 1, S...> { };
template<size_t ...S> struct make_index_sequence <0, S...> { typedef index_sequence<S...> type; };
/// Helper template to strip away type modifiers
template <typename T> struct normalize_type { typedef T type; };
template <typename T> struct normalize_type<const T> { typedef typename normalize_type<T>::type type; };
template <typename T> struct normalize_type<T*> { typedef typename normalize_type<T>::type type; };
template <typename T> struct normalize_type<T&> { typedef typename normalize_type<T>::type type; };
template <typename T> struct normalize_type<T&&> { typedef typename normalize_type<T>::type type; };
template <typename T, size_t N> struct normalize_type<const T[N]> { typedef typename normalize_type<T>::type type; };
template <typename T, size_t N> struct normalize_type<T[N]> { typedef typename normalize_type<T>::type type; };
NAMESPACE_BEGIN(detail)
/// Strip the class from a method type
template <typename T> struct remove_class {};
template <typename C, typename R, typename... A> struct remove_class<R (C::*)(A...)> { typedef R type(A...); };
template <typename C, typename R, typename... A> struct remove_class<R (C::*)(A...) const> { typedef R type(A...); };
/**
* \brief Convert a lambda function to a std::function
* From http://stackoverflow.com/questions/11893141/inferring-the-call-signature-of-a-lambda-or-arbitrary-callable-for-make-functio
*/
template <typename T> struct lambda_signature_impl {
using type = typename remove_class<
decltype(&std::remove_reference<T>::type::operator())>::type;
};
template <typename R, typename... A> struct lambda_signature_impl<R (A...)> { typedef R type(A...); };
template <typename R, typename... A> struct lambda_signature_impl<R (&)(A...)> { typedef R type(A...); };
template <typename R, typename... A> struct lambda_signature_impl<R (*)(A...)> { typedef R type(A...); };
template <typename T> using lambda_signature = typename lambda_signature_impl<T>::type;
template <typename F> using make_function_type = std::function<lambda_signature<F>>;
NAMESPACE_END(detail)
template<typename F> detail::make_function_type<F> make_function(F &&f) {
return detail::make_function_type<F>(std::forward<F>(f)); }
NAMESPACE_BEGIN(detail)
struct void_type { };
/// Helper functions for calling a function using a tuple argument while dealing with void/non-void return values
template <typename RetType> struct tuple_dispatch {
typedef RetType return_type;
template<typename Func, typename Arg, size_t ... S> return_type operator()(const Func &f, Arg && args, index_sequence<S...>) {
return f(std::get<S>(std::forward<Arg>(args))...);
}
};
/// Helper functions for calling a function using a tuple argument (special case for void return values)
template <> struct tuple_dispatch<void> {
typedef void_type return_type;
template<typename Func, typename Arg, size_t ... S> return_type operator()(const Func &f, Arg &&args, index_sequence<S...>) {
f(std::get<S>(std::forward<Arg>(args))...);
return return_type();
}
};
NAMESPACE_END(detail)
/// For lambda functions delegate to their 'operator()'
template <typename T> struct function_traits : function_traits<typename detail::make_function_type<T>> { };
/* Deal with reference arguments */
template <typename ReturnType, typename... Args>
struct function_traits<ReturnType(*&)(Args...)> : function_traits<ReturnType(*)(Args...)> {};
template <typename ClassType, typename ReturnType, typename... Args>
struct function_traits<ReturnType(ClassType::*&)(Args...)> : function_traits<ReturnType(ClassType::*)(Args...)> {};
template <typename ClassType, typename ReturnType, typename... Args>
struct function_traits<ReturnType(ClassType::*&)(Args...) const> : function_traits<ReturnType(ClassType::*)(Args...) const> {};
/// Type traits for function pointers
template <typename ReturnType, typename... Args>
struct function_traits<ReturnType(*)(Args...)> {
enum {
nargs = sizeof...(Args),
is_method = 0,
is_const = 0
};
typedef std::function<ReturnType (Args...)> f_type;
typedef detail::tuple_dispatch<ReturnType> dispatch_type;
typedef typename dispatch_type::return_type return_type;
typedef std::tuple<Args...> args_type;
template <size_t i> struct arg {
typedef typename std::tuple_element<i, args_type>::type type;
};
static f_type cast(ReturnType (*func)(Args ...)) { return func; }
static return_type dispatch(const f_type &f, args_type &&args) {
return dispatch_type()(f, std::move(args),
typename make_index_sequence<nargs>::type());
}
};
/// Type traits for ordinary methods
template <typename ClassType, typename ReturnType, typename... Args>
struct function_traits<ReturnType(ClassType::*)(Args...)> {
enum {
nargs = sizeof...(Args),
is_method = 1,
is_const = 0
};
typedef std::function<ReturnType(ClassType &, Args...)> f_type;
typedef detail::tuple_dispatch<ReturnType> dispatch_type;
typedef typename dispatch_type::return_type return_type;
typedef std::tuple<ClassType&, Args...> args_type;
template <size_t i> struct arg {
typedef typename std::tuple_element<i, args_type>::type type;
};
static f_type cast(ReturnType (ClassType::*func)(Args ...)) { return std::mem_fn(func); }
static return_type dispatch(const f_type &f, args_type &&args) {
return dispatch_type()(f, std::move(args),
typename make_index_sequence<nargs+1>::type());
}
};
/// Type traits for const methods
template <typename ClassType, typename ReturnType, typename... Args>
struct function_traits<ReturnType(ClassType::*)(Args...) const> {
enum {
nargs = sizeof...(Args),
is_method = 1,
is_const = 1
};
typedef std::function<ReturnType (const ClassType &, Args...)> f_type;
typedef detail::tuple_dispatch<ReturnType> dispatch_type;
typedef typename dispatch_type::return_type return_type;
typedef std::tuple<const ClassType&, Args...> args_type;
template <size_t i> struct arg {
typedef typename std::tuple_element<i, args_type>::type type;
};
static f_type cast(ReturnType (ClassType::*func)(Args ...) const) {
return std::mem_fn(func);
}
static return_type dispatch(const f_type &f, args_type &&args) {
return dispatch_type()(f, std::move(args),
typename make_index_sequence<nargs+1>::type());
}
};
/// Type traits for std::functions
template <typename ReturnType, typename... Args>
struct function_traits<std::function<ReturnType(Args...)>> {
enum {
nargs = sizeof...(Args),
is_method = 0,
is_const = 0
};
typedef std::function<ReturnType (Args...)> f_type;
typedef detail::tuple_dispatch<ReturnType> dispatch_type;
typedef typename dispatch_type::return_type return_type;
typedef std::tuple<Args...> args_type;
template <size_t i> struct arg {
typedef typename std::tuple_element<i, args_type>::type type;
};
static f_type cast(const f_type &func) { return func; }
static return_type dispatch(const f_type &f, args_type &&args) {
return dispatch_type()(f, std::move(args),
typename make_index_sequence<nargs>::type());
}
};
NAMESPACE_END(mpl)
NAMESPACE_END(pybind)
include/pybind/numpy.h 0 → 100644
/*
pybind/numpy.h: Basic NumPy support, auto-vectorization support
Copyright (c) 2015 Wenzel Jakob <wenzel@inf.ethz.ch>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#pragma once
#include <pybind/pybind.h>
#if defined(_MSC_VER)
#pragma warning(push)
#pragma warning(disable: 4127) // warning C4127: Conditional expression is constant
#endif
NAMESPACE_BEGIN(pybind)
class array : public buffer {
protected:
struct API {
enum Entries {
API_PyArray_Type = 2,
API_PyArray_DescrFromType = 45,
API_PyArray_FromAny = 69,
API_PyArray_NewCopy = 85,
API_PyArray_NewFromDescr = 94,
API_NPY_C_CONTIGUOUS = 0x0001,
API_NPY_F_CONTIGUOUS = 0x0002,
API_NPY_NPY_ARRAY_FORCECAST = 0x0010,
API_NPY_ENSURE_ARRAY = 0x0040
};
static API lookup() {
PyObject *numpy = PyImport_ImportModule("numpy.core.multiarray");
PyObject *capsule = numpy ? PyObject_GetAttrString(numpy, "_ARRAY_API") : nullptr;
void **api_ptr = (void **) (capsule ? PyCapsule_GetPointer(capsule, NULL) : nullptr);
Py_XDECREF(capsule);
Py_XDECREF(numpy);
if (api_ptr == nullptr)
throw std::runtime_error("Could not acquire pointer to NumPy API!");
API api;
api.PyArray_Type = (decltype(api.PyArray_Type)) api_ptr[API_PyArray_Type];
api.PyArray_DescrFromType = (decltype(api.PyArray_DescrFromType)) api_ptr[API_PyArray_DescrFromType];
api.PyArray_FromAny = (decltype(api.PyArray_FromAny)) api_ptr[API_PyArray_FromAny];
api.PyArray_NewCopy = (decltype(api.PyArray_NewCopy)) api_ptr[API_PyArray_NewCopy];
api.PyArray_NewFromDescr = (decltype(api.PyArray_NewFromDescr)) api_ptr[API_PyArray_NewFromDescr];
return api;
}
bool PyArray_Check(PyObject *obj) const { return (bool) PyObject_TypeCheck(obj, PyArray_Type); }
PyObject *(*PyArray_DescrFromType)(int);
PyObject *(*PyArray_NewFromDescr)
(PyTypeObject *, PyObject *, int, Py_intptr_t *,
Py_intptr_t *, void *, int, PyObject *);
PyObject *(*PyArray_NewCopy)(PyObject *, int);
PyTypeObject *PyArray_Type;
PyObject *(*PyArray_FromAny) (PyObject *, PyObject *, int, int, int, PyObject *);
};
public:
PYBIND_OBJECT_DEFAULT(array, buffer, lookup_api().PyArray_Check)
template <typename Type> array(size_t size, const Type *ptr) {
API& api = lookup_api();
PyObject *descr = api.PyArray_DescrFromType(
(int) format_descriptor<Type>::value()[0]);
if (descr == nullptr)
throw std::runtime_error("NumPy: unsupported buffer format!");
Py_intptr_t shape = (Py_intptr_t) size;
PyObject *tmp = api.PyArray_NewFromDescr(
api.PyArray_Type, descr, 1, &shape, nullptr, (void *) ptr, 0, nullptr);
if (tmp == nullptr)
throw std::runtime_error("NumPy: unable to create array!");
m_ptr = api.PyArray_NewCopy(tmp, -1 /* any order */);
Py_DECREF(tmp);
if (m_ptr == nullptr)
throw std::runtime_error("NumPy: unable to copy array!");
}
array(const buffer_info &info) {
API& api = lookup_api();
if (info.format.size() != 1)
throw std::runtime_error("Unsupported buffer format!");
PyObject *descr = api.PyArray_DescrFromType(info.format[0]);
if (descr == nullptr)
throw std::runtime_error("NumPy: unsupported buffer format '" + info.format + "'!");
PyObject *tmp = api.PyArray_NewFromDescr(
api.PyArray_Type, descr, info.ndim, (Py_intptr_t *) &info.shape[0],
(Py_intptr_t *) &info.strides[0], info.ptr, 0, nullptr);
if (tmp == nullptr)
throw std::runtime_error("NumPy: unable to create array!");
m_ptr = api.PyArray_NewCopy(tmp, -1 /* any order */);
Py_DECREF(tmp);
if (m_ptr == nullptr)
throw std::runtime_error("NumPy: unable to copy array!");
}
protected:
static API &lookup_api() {
static API api = API::lookup();
return api;
}
};
template <typename T> class array_dtype : public array {
public:
PYBIND_OBJECT_CVT(array_dtype, array, is_non_null, m_ptr = ensure(m_ptr));
array_dtype() : array() { }
static bool is_non_null(PyObject *ptr) { return ptr != nullptr; }
static PyObject *ensure(PyObject *ptr) {
API &api = lookup_api();
PyObject *descr = api.PyArray_DescrFromType(format_descriptor<T>::value()[0]);
return api.PyArray_FromAny(ptr, descr, 0, 0,
API::API_NPY_C_CONTIGUOUS | API::API_NPY_ENSURE_ARRAY |
API::API_NPY_NPY_ARRAY_FORCECAST, nullptr);
}
};
NAMESPACE_BEGIN(detail)
PYBIND_TYPE_CASTER_PYTYPE(array)
PYBIND_TYPE_CASTER_PYTYPE(array_dtype<int8_t>) PYBIND_TYPE_CASTER_PYTYPE(array_dtype<uint8_t>)
PYBIND_TYPE_CASTER_PYTYPE(array_dtype<int16_t>) PYBIND_TYPE_CASTER_PYTYPE(array_dtype<uint16_t>)
PYBIND_TYPE_CASTER_PYTYPE(array_dtype<int32_t>) PYBIND_TYPE_CASTER_PYTYPE(array_dtype<uint32_t>)
PYBIND_TYPE_CASTER_PYTYPE(array_dtype<int64_t>) PYBIND_TYPE_CASTER_PYTYPE(array_dtype<uint64_t>)
PYBIND_TYPE_CASTER_PYTYPE(array_dtype<float>) PYBIND_TYPE_CASTER_PYTYPE(array_dtype<double>)
NAMESPACE_END(detail)
template <typename func_type, typename return_type, typename... args_type, size_t... Index>
std::function<object(array_dtype<args_type>...)>
vectorize(func_type &&f, return_type (*) (args_type ...),
detail::index_sequence<Index...>) {
return [f](array_dtype<args_type>... args) -> array {
/* Request buffers from all parameters */
const size_t N = sizeof...(args_type);
std::array<buffer_info, N> buffers {{ args.request()... }};
/* Determine dimensions parameters of output array */
int ndim = 0; size_t count = 0;
std::vector<size_t> shape;
for (size_t i=0; i<N; ++i) {
if (buffers[i].count > count) {
ndim = buffers[i].ndim;
shape = buffers[i].shape;
count = buffers[i].count;
}
}
std::vector<size_t> strides(ndim);
if (ndim > 0) {
strides[ndim-1] = sizeof(return_type);
for (int i=ndim-1; i>0; --i)
strides[i-1] = strides[i] * shape[i];
}
/* Check if the parameters are actually compatible */
for (size_t i=0; i<N; ++i) {
if (buffers[i].count != 1 && (buffers[i].ndim != ndim || buffers[i].shape != shape))
throw std::runtime_error("pybind::vectorize: incompatible size/dimension of inputs!");
}
/* Call the function */
std::vector<return_type> result(count);
for (size_t i=0; i<count; ++i)
result[i] = f((buffers[Index].count == 1
? *((args_type *) buffers[Index].ptr)
: ((args_type *) buffers[Index].ptr)[i])...);
if (count == 1)
return cast(result[0]);
/* Return the result */
return array(buffer_info(result.data(), sizeof(return_type),
format_descriptor<return_type>::value(),
ndim, shape, strides));
};
}
template <typename func_type, typename return_type, typename... args_type>
std::function<object(array_dtype<args_type>...)>
vectorize(func_type &&f, return_type (*f_) (args_type ...) = nullptr) {
return vectorize(f, f_, typename detail::make_index_sequence<sizeof...(args_type)>::type());
}
template <typename return_type, typename... args_type>
std::function<object(array_dtype<args_type>...)> vectorize(return_type (*f) (args_type ...)) {
return vectorize(f, f);
}
template <typename func> auto vectorize(func &&f) -> decltype(
vectorize(std::forward<func>(f), (typename detail::remove_class<decltype(&std::remove_reference<func>::type::operator())>::type *) nullptr)) {
return vectorize(std::forward<func>(f), (typename detail::remove_class<decltype(
&std::remove_reference<func>::type::operator())>::type *) nullptr);
}
NAMESPACE_END(pybind)
#if defined(_MSC_VER)
#pragma warning(pop)
#endif
include/pybind/operators.h
......@@ -17,13 +17,12 @@ NAMESPACE_BEGIN(detail)
/// Enumeration with all supported operator types
enum op_id : int {
op_add, op_sub, op_mul, op_div, op_mod, op_divmod, op_pow,
op_lshift, op_rshift, op_and, op_xor, op_or, op_neg,
op_pos, op_abs, op_invert, op_int, op_long, op_float,
op_str, op_cmp, op_gt, op_ge, op_lt, op_le, op_eq, op_ne,
op_iadd, op_isub, op_imul, op_idiv, op_imod, op_ilshift,
op_irshift, op_iand, op_ixor, op_ior, op_complex, op_bool,
op_nonzero, op_repr, op_truediv
op_add, op_sub, op_mul, op_div, op_mod, op_divmod, op_pow, op_lshift,
op_rshift, op_and, op_xor, op_or, op_neg, op_pos, op_abs, op_invert,
op_int, op_long, op_float, op_str, op_cmp, op_gt, op_ge, op_lt, op_le,
op_eq, op_ne, op_iadd, op_isub, op_imul, op_idiv, op_imod, op_ilshift,
op_irshift, op_iand, op_ixor, op_ior, op_complex, op_bool, op_nonzero,
op_repr, op_truediv
};
enum op_type : int {
......@@ -33,12 +32,11 @@ enum op_type : int {
};
struct self_t { };
static const self_t self = self_t();
/// Type for an unused type slot
struct undefined_t { };
static const self_t self = self_t();
/// Don't warn about an unused variable
inline self_t __self() { return self; }
......@@ -140,7 +138,6 @@ PYBIND_UNARY_OPERATOR(float, float_, (double) l)
#undef PYBIND_BINARY_OPERATOR
#undef PYBIND_INPLACE_OPERATOR
#undef PYBIND_UNARY_OPERATOR
NAMESPACE_END(detail)
using detail::self;
......
include/pybind/pybind.h
......@@ -22,49 +22,112 @@
NAMESPACE_BEGIN(pybind)
/// Wraps an arbitrary C++ function/method/lambda function/.. into a callable Python object
class cpp_function : public function {
public:
private:
/// Chained list of function entries for overloading
struct function_entry {
std::function<PyObject* (PyObject *)> impl;
PyObject * (*impl) (function_entry *, PyObject *, PyObject *);
void *data;
std::string signature, doc;
bool is_constructor;
return_value_policy policy;
function_entry *next = nullptr;
};
/// Picks a suitable return value converter from cast.h
template <typename T> using return_value_caster =
detail::type_caster<typename std::conditional<
std::is_void<T>::value, detail::void_type, typename detail::decay<T>::type>::type>;
/// Picks a suitable argument value converter from cast.h
template <typename ... T> using arg_value_caster =
detail::type_caster<typename std::tuple<T...>>;
public:
cpp_function() { }
template <typename Func> cpp_function(
Func &&_func, const char *name = nullptr, const char *doc = nullptr,
return_value_policy policy = return_value_policy::automatic,
function sibling = function(), bool is_method = false) {
/* Function traits extracted from the template type 'Func' */
typedef mpl::function_traits<Func> f_traits;
/* Suitable input and output casters */
typedef typename detail::type_caster<typename f_traits::args_type> cast_in;
typedef typename detail::type_caster<typename mpl::normalize_type<typename f_traits::return_type>::type> cast_out;
typename f_traits::f_type func = f_traits::cast(std::forward<Func>(_func));
/// Vanilla function pointers
template <typename return_type, typename... arg_type>
cpp_function(return_type (*f)(arg_type...), const char *name = nullptr,
const char *doc = nullptr, return_value_policy policy = return_value_policy::automatic,
const function &sibling = function(), bool is_method = false) {
typedef arg_value_caster<arg_type...> cast_in;
typedef return_value_caster<return_type> cast_out;
auto impl = [func, policy](PyObject *pyArgs) -> PyObject *{
auto impl = [](function_entry *entry, PyObject *pyArgs, PyObject *parent) -> PyObject * {
cast_in args;
if (!args.load(pyArgs, true))
return nullptr;
PyObject *parent = policy != return_value_policy::reference_internal
? nullptr : PyTuple_GetItem(pyArgs, 0);
return cast_out::cast(
f_traits::dispatch(func, args.operator typename f_traits::args_type()),
policy, parent);
if (!args.load(pyArgs, true)) return nullptr;
auto f = (return_type (*) (arg_type...)) entry->data;
return cast_out::cast(args.template call<return_type>(f),
entry->policy, parent);
};
initialize(name, doc, cast_in::name() + std::string(" -> ") + cast_out::name(),
sibling, is_method, std::move(impl));
sibling, is_method, policy, impl, (void *) f);
}
/// Delegating helper constructor to deal with lambda functions
template <typename func>
cpp_function(func &&f, const char *name = nullptr,
const char *doc = nullptr,
return_value_policy policy = return_value_policy::automatic,
const function &sibling = function(), bool is_method = false) {
initialize(std::forward<func>(f), name, doc, policy, sibling, is_method,
(typename detail::remove_class<decltype(
&std::remove_reference<func>::type::operator())>::type *) nullptr);
}
/// Class methods (non-const)
template <typename return_type, typename class_type, typename ... arg_type> cpp_function(
return_type (class_type::*f)(arg_type...), const char *name = nullptr,
const char *doc = nullptr, return_value_policy policy = return_value_policy::automatic,
const function &sibling = function(), bool is_method = false) {
initialize([f](class_type *c, arg_type... args) -> return_type { return (c->*f)(args...); },
name, doc, policy, sibling, is_method, (return_type (*)(class_type *, arg_type ...)) nullptr);
}
/// Class methods (const)
template <typename return_type, typename class_type, typename ... arg_type> cpp_function(
return_type (class_type::*f)(arg_type...) const, const char *name = nullptr,
const char *doc = nullptr, return_value_policy policy = return_value_policy::automatic,
const function &sibling = function(), bool is_method = false) {
initialize([f](const class_type *c, arg_type... args) -> return_type { return (c->*f)(args...); },
name, doc, policy, sibling, is_method, (return_type (*)(const class_type *, arg_type ...)) nullptr);
}
private:
/// Functors, lambda functions, etc.
template <typename func, typename return_type, typename... arg_type>
void initialize(func &&f, const char *name, const char *doc,
return_value_policy policy, const function &sibling,
bool is_method, return_type (*)(arg_type...)) {
typedef arg_value_caster<arg_type...> cast_in;
typedef return_value_caster<return_type> cast_out;
struct capture { typename std::remove_reference<func>::type f; };
void *ptr = new capture { std::forward<func>(f) };
auto impl = [](function_entry *entry, PyObject *pyArgs, PyObject *parent) -> PyObject *{
cast_in args;
if (!args.load(pyArgs, true)) return nullptr;
func &f = ((capture *) entry->data)->f;
return cast_out::cast(args.template call<return_type>(f),
entry->policy, parent);
};
initialize(name, doc, cast_in::name() + std::string(" -> ") + cast_out::name(),
sibling, is_method, policy, impl, ptr);
}
static PyObject *dispatcher(PyObject *self, PyObject *args, PyObject * /* kwargs */) {
function_entry *overloads = (function_entry *) PyCapsule_GetPointer(self, nullptr);
PyObject *result = nullptr;
PyObject *parent = PyTuple_Size(args) > 0 ? PyTuple_GetItem(args, 0) : nullptr;
try {
for (function_entry *it = overloads; it != nullptr; it = it->next) {
if ((result = it->impl(args)) != nullptr)
if ((result = it->impl(it, args, parent)) != nullptr)
break;
}
} catch (const error_already_set &) { return nullptr;
......@@ -100,15 +163,19 @@ private:
void initialize(const char *name, const char *doc,
const std::string &signature, function sibling,
bool is_method, std::function<PyObject *(PyObject *)> &&impl) {
bool is_method, return_value_policy policy,
PyObject *(*impl) (function_entry *, PyObject *, PyObject *),
void *data) {
if (name == nullptr)
name = "";
/* Linked list of function call handlers (for overloading) */
function_entry *entry = new function_entry();
entry->impl = std::move(impl);
entry->impl = impl;
entry->is_constructor = !strcmp(name, "__init__");
entry->policy = policy;
entry->signature = signature;
entry->data = data;
if (doc) entry->doc = doc;
if (!sibling.ptr() || !PyCFunction_Check(sibling.ptr())) {
......@@ -159,16 +226,15 @@ private:
class cpp_method : public cpp_function {
public:
cpp_method () { }
template <typename Func>
cpp_method(Func &&_func, const char *name = nullptr, const char *doc = nullptr,
return_value_policy policy = return_value_policy::automatic,
function sibling = function())
: cpp_function(std::forward<Func>(_func), name, doc, policy, sibling, true) { }
template <typename func> cpp_method(func &&f, const char *name = nullptr,
const char *doc = nullptr, return_value_policy
policy = return_value_policy::automatic, function sibling = function())
: cpp_function(std::forward<func>(f), name, doc, policy, sibling, true) {}
};
class module : public object {
public:
PYTHON_OBJECT_DEFAULT(module, object, PyModule_Check)
PYBIND_OBJECT_DEFAULT(module, object, PyModule_Check)
module(const char *name, const char *doc = nullptr) {
PyModuleDef *def = new PyModuleDef();
......@@ -214,7 +280,7 @@ template <typename ... Args> struct init;
/// Basic support for creating new Python heap types
class custom_type : public object {
public:
PYTHON_OBJECT_DEFAULT(custom_type, object, PyType_Check)
PYBIND_OBJECT_DEFAULT(custom_type, object, PyType_Check)
custom_type(object &scope, const char *name_, const std::string &type_name,
size_t type_size, size_t instance_size,
......@@ -364,14 +430,13 @@ protected:
static void releasebuffer(PyObject *, Py_buffer *view) { delete (buffer_info *) view->internal; }
};
NAMESPACE_END(detail)
template <typename type, typename holder_type = std::unique_ptr<type>> class class_ : public detail::custom_type {
public:
typedef detail::instance<type, holder_type> instance_type;
PYTHON_OBJECT(class_, detail::custom_type, PyType_Check)
PYBIND_OBJECT(class_, detail::custom_type, PyType_Check)
class_(object &scope, const char *name, const char *doc = nullptr)
: detail::custom_type(scope, name, type_id<type>(), sizeof(type),
......@@ -603,6 +668,3 @@ NAMESPACE_END(pybind)
#if defined(_MSC_VER)
#pragma warning(pop)
#endif
#undef PYTHON_OBJECT
#undef PYTHON_OBJECT_DEFAULT
include/pybind/pytypes.h
......@@ -19,9 +19,7 @@ class object;
class str;
class object;
class dict;
NAMESPACE_BEGIN(detail)
class accessor;
NAMESPACE_END(detail)
namespace detail { class accessor; }
/// Holds a reference to a Python object (no reference counting)
class handle {
......@@ -189,7 +187,6 @@ private:
PyObject *dict, *key, *value;
ssize_t pos = 0;
};
NAMESPACE_END(detail)
inline detail::accessor handle::operator[](handle key) { return detail::accessor(ptr(), key.ptr(), false); }
......@@ -197,21 +194,24 @@ inline detail::accessor handle::operator[](const char *key) { return detail::acc
inline detail::accessor handle::attr(handle key) { return detail::accessor(ptr(), key.ptr(), true); }
inline detail::accessor handle::attr(const char *key) { return detail::accessor(ptr(), key, true); }
#define PYTHON_OBJECT(Name, Parent, CheckFun) \
Name(const handle &h, bool borrowed) : Parent(h, borrowed) { } \
Name(const object& o): Parent(o) { } \
Name(object&& o): Parent(std::move(o)) { } \
Name& operator=(object&& o) { return static_cast<Name&>(object::operator=(std::move(o))); } \
Name& operator=(object& o) { return static_cast<Name&>(object::operator=(o)); } \
#define PYBIND_OBJECT_CVT(Name, Parent, CheckFun, CvtStmt) \
Name(const handle &h, bool borrowed) : Parent(h, borrowed) { CvtStmt; } \
Name(const object& o): Parent(o) { CvtStmt; } \
Name(object&& o): Parent(std::move(o)) { CvtStmt; } \
Name& operator=(object&& o) { return static_cast<Name&>(object::operator=(std::move(o))); CvtStmt; } \
Name& operator=(object& o) { return static_cast<Name&>(object::operator=(o)); CvtStmt; } \
bool check() const { return m_ptr != nullptr && (bool) CheckFun(m_ptr); }
#define PYTHON_OBJECT_DEFAULT(Name, Parent, CheckFun) \
PYTHON_OBJECT(Name, Parent, CheckFun) \
#define PYBIND_OBJECT(Name, Parent, CheckFun) \
PYBIND_OBJECT_CVT(Name, Parent, CheckFun, )
#define PYBIND_OBJECT_DEFAULT(Name, Parent, CheckFun) \
PYBIND_OBJECT(Name, Parent, CheckFun) \
Name() : Parent() { }
class str : public object {
public:
PYTHON_OBJECT_DEFAULT(str, object, PyUnicode_Check)
PYBIND_OBJECT_DEFAULT(str, object, PyUnicode_Check)
str(const char *s) : object(PyUnicode_FromString(s), false) { }
operator const char *() const { return PyUnicode_AsUTF8(m_ptr); }
};
......@@ -221,13 +221,13 @@ inline std::ostream &operator<<(std::ostream &os, const object &obj) { os << (co
class bool_ : public object {
public:
PYTHON_OBJECT_DEFAULT(bool_, object, PyBool_Check)
PYBIND_OBJECT_DEFAULT(bool_, object, PyBool_Check)
operator bool() const { return m_ptr && PyLong_AsLong(m_ptr) != 0; }
};
class int_ : public object {
public:
PYTHON_OBJECT_DEFAULT(int_, object, PyLong_Check)
PYBIND_OBJECT_DEFAULT(int_, object, PyLong_Check)
int_(int value) : object(PyLong_FromLong((long) value), false) { }
int_(size_t value) : object(PyLong_FromSize_t(value), false) { }
int_(ssize_t value) : object(PyLong_FromSsize_t(value), false) { }
......@@ -236,7 +236,7 @@ public:
class float_ : public object {
public:
PYTHON_OBJECT_DEFAULT(float_, object, PyFloat_Check)
PYBIND_OBJECT_DEFAULT(float_, object, PyFloat_Check)
float_(float value) : object(PyFloat_FromDouble((double) value), false) { }
float_(double value) : object(PyFloat_FromDouble((double) value), false) { }
operator float() const { return (float) PyFloat_AsDouble(m_ptr); }
......@@ -245,7 +245,7 @@ public:
class slice : public object {
public:
PYTHON_OBJECT_DEFAULT(slice, object, PySlice_Check)
PYBIND_OBJECT_DEFAULT(slice, object, PySlice_Check)
slice(ssize_t start_, ssize_t stop_, ssize_t step_) {
int_ start(start_), stop(stop_), step(step_);
m_ptr = PySlice_New(start.ptr(), stop.ptr(), step.ptr());
......@@ -257,7 +257,7 @@ public:
class capsule : public object {
public:
PYTHON_OBJECT_DEFAULT(capsule, object, PyCapsule_CheckExact)
PYBIND_OBJECT_DEFAULT(capsule, object, PyCapsule_CheckExact)
capsule(void *value) : object(PyCapsule_New(value, nullptr, nullptr), false) { }
template <typename T> operator T *() const {
T * result = static_cast<T *>(PyCapsule_GetPointer(m_ptr, nullptr));
......@@ -268,7 +268,7 @@ public:
class tuple : public object {
public:
PYTHON_OBJECT_DEFAULT(tuple, object, PyTuple_Check)
PYBIND_OBJECT_DEFAULT(tuple, object, PyTuple_Check)
tuple(size_t size) : object(PyTuple_New((Py_ssize_t) size), false) { }
size_t size() const { return (size_t) PyTuple_Size(m_ptr); }
detail::tuple_accessor operator[](size_t index) { return detail::tuple_accessor(ptr(), index); }
......@@ -276,7 +276,7 @@ public:
class dict : public object {
public:
PYTHON_OBJECT(dict, object, PyDict_Check)
PYBIND_OBJECT(dict, object, PyDict_Check)
dict() : object(PyDict_New(), false) { }
size_t size() const { return (size_t) PyDict_Size(m_ptr); }
detail::dict_iterator begin() { return (++detail::dict_iterator(ptr(), 0)); }
......@@ -285,7 +285,7 @@ public:
class list : public object {
public:
PYTHON_OBJECT(list, object, PyList_Check)
PYBIND_OBJECT(list, object, PyList_Check)
list(size_t size = 0) : object(PyList_New((ssize_t) size), false) { }
size_t size() const { return (size_t) PyList_Size(m_ptr); }
detail::list_iterator begin() { return detail::list_iterator(ptr(), 0); }
......@@ -296,12 +296,12 @@ public:
class function : public object {
public:
PYTHON_OBJECT_DEFAULT(function, object, PyFunction_Check)
PYBIND_OBJECT_DEFAULT(function, object, PyFunction_Check)
};
class buffer : public object {
public:
PYTHON_OBJECT_DEFAULT(buffer, object, PyObject_CheckBuffer)
PYBIND_OBJECT_DEFAULT(buffer, object, PyObject_CheckBuffer)
buffer_info request(bool writable = false) {
int flags = PyBUF_STRIDES | PyBUF_FORMAT;
......@@ -322,88 +322,6 @@ private:
Py_buffer *view = nullptr;
};
class array : public buffer {
protected:
struct API {
enum Entries {
API_PyArray_Type = 2,
API_PyArray_DescrFromType = 45,
API_PyArray_NewCopy = 85,
API_PyArray_NewFromDescr = 94
};
static API lookup() {
PyObject *numpy = PyImport_ImportModule("numpy.core.multiarray");
PyObject *capsule = numpy ? PyObject_GetAttrString(numpy, "_ARRAY_API") : nullptr;
void **api_ptr = (void **) (capsule ? PyCapsule_GetPointer(capsule, NULL) : nullptr);
Py_XDECREF(capsule);
Py_XDECREF(numpy);
if (api_ptr == nullptr)
throw std::runtime_error("Could not acquire pointer to NumPy API!");
API api;
api.PyArray_DescrFromType = (decltype(api.PyArray_DescrFromType)) api_ptr[API_PyArray_DescrFromType];
api.PyArray_NewFromDescr = (decltype(api.PyArray_NewFromDescr)) api_ptr[API_PyArray_NewFromDescr];
api.PyArray_NewCopy = (decltype(api.PyArray_NewCopy)) api_ptr[API_PyArray_NewCopy];
api.PyArray_Type = (decltype(api.PyArray_Type)) api_ptr[API_PyArray_Type];
return api;
}
bool PyArray_Check(PyObject *obj) const {
return (bool) PyObject_TypeCheck(obj, PyArray_Type);
}
PyObject *(*PyArray_DescrFromType)(int);
PyObject *(*PyArray_NewFromDescr)
(PyTypeObject *, PyObject *, int, Py_intptr_t *,
Py_intptr_t *, void *, int, PyObject *);
PyObject *(*PyArray_NewCopy)(PyObject *, int);
PyTypeObject *PyArray_Type;
};
public:
PYTHON_OBJECT_DEFAULT(array, buffer, lookup_api().PyArray_Check)
template <typename Type> array(size_t size, const Type *ptr) {
API& api = lookup_api();
PyObject *descr = api.PyArray_DescrFromType(
(int) format_descriptor<Type>::value()[0]);
if (descr == nullptr)
throw std::runtime_error("NumPy: unsupported buffer format!");
Py_intptr_t shape = (Py_intptr_t) size;
PyObject *tmp = api.PyArray_NewFromDescr(
api.PyArray_Type, descr, 1, &shape, nullptr, (void *) ptr, 0, nullptr);
if (tmp == nullptr)
throw std::runtime_error("NumPy: unable to create array!");
m_ptr = api.PyArray_NewCopy(tmp, -1 /* any order */);
Py_DECREF(tmp);
if (m_ptr == nullptr)
throw std::runtime_error("NumPy: unable to copy array!");
}
array(const buffer_info &info) {
API& api = lookup_api();
if (info.format.size() != 1)
throw std::runtime_error("Unsupported buffer format!");
PyObject *descr = api.PyArray_DescrFromType(info.format[0]);
if (descr == nullptr)
throw std::runtime_error("NumPy: unsupported buffer format '" + info.format + "'!");
PyObject *tmp = api.PyArray_NewFromDescr(
api.PyArray_Type, descr, info.ndim, (Py_intptr_t *) &info.shape[0],
(Py_intptr_t *) &info.strides[0], info.ptr, 0, nullptr);
if (tmp == nullptr)
throw std::runtime_error("NumPy: unable to create array!");
m_ptr = api.PyArray_NewCopy(tmp, -1 /* any order */);
Py_DECREF(tmp);
if (m_ptr == nullptr)
throw std::runtime_error("NumPy: unable to copy array!");
}
protected:
static API &lookup_api() {
static API api = API::lookup();
return api;
}
};
NAMESPACE_BEGIN(detail)
inline internals &get_internals() {
static internals *internals_ptr = nullptr;
......
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