一般而言,boost bind 是如何在幕后工作的?
无需花很长时间查看 boost 源代码,有人可以简要介绍一下 boost 绑定是如何实现的吗?
Without spending a long time reviewing the boost source code, could someone give me a quick rundown of how boost bind is implemented?
推荐答案
我喜欢这段 bind
源码:
template<class R, class F, class L> class bind_t
{
public:
typedef bind_t this_type;
bind_t(F f, L const & l): f_(f), l_(l) {}
#define BOOST_BIND_RETURN return
#include <boost/bind/bind_template.hpp>
#undef BOOST_BIND_RETURN
};
告诉你几乎所有你需要知道的,真的.
Tells you almost all you need to know, really.
bind_template
标头扩展为内联 operator()
定义列表.比如最简单的:
The bind_template
header expands to a list of inline operator()
definitions. For example, the simplest:
result_type operator()()
{
list0 a;
BOOST_BIND_RETURN l_(type<result_type>(), f_, a, 0);
}
我们可以看到 BOOST_BIND_RETURN
宏此时扩展为 return
,所以该行更像是 return l_(type...)
.
We can see the BOOST_BIND_RETURN
macro expands to return
at this point so the line is more like return l_(type...)
.
一个参数版本在这里:
template<class A1> result_type operator()(A1 & a1)
{
list1<A1 &> a(a1);
BOOST_BIND_RETURN l_(type<result_type>(), f_, a, 0);
}
非常相似.
listN
类是参数列表的包装器.这里有很多深奥的魔法,但我并不太了解.他们还重载了调用神秘的 unwrap
函数的 operator()
.忽略一些编译器特定的重载,它不会做很多事情:
The listN
classes are wrappers for the parameter lists. There is a lot of deep magic going on here that I don't really understand too much though. They have also overloaded operator()
that calls the mysterious unwrap
function. Ignoring some compiler specific overloads, it doesn't do a lot:
// unwrap
template<class F> inline F & unwrap(F * f, long)
{
return *f;
}
template<class F> inline F & unwrap(reference_wrapper<F> * f, int)
{
return f->get();
}
template<class F> inline F & unwrap(reference_wrapper<F> const * f, int)
{
return f->get();
}
命名约定似乎是:F
是bind
的函数参数的类型.R
是返回类型.L
往往是一个参数类型列表.还有很多复杂性,因为不同数量的参数有不少于九个重载.最好不要想太多.
The naming convention seems to be: F
is the type of the function parameter to bind
. R
is the return type. L
tends to be a list of parameter types. There are also a lot of complications because there are no less than nine overloads for different numbers of parameters. Best not to dwell on that too much.
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