?? tutorial.qbk
字號:
[library python
[version 1.0]
[authors [de Guzman, Joel], [Abrahams, David]]
[copyright 2002 2003 2004 2005 Joel de Guzman, David Abrahams]
[category inter-language support]
[purpose
Reflects C++ classes and functions into Python
]
[license
Distributed under the Boost Software License, Version 1.0.
(See accompanying file LICENSE_1_0.txt or copy at
<ulink url="http://www.boost.org/LICENSE_1_0.txt">
http://www.boost.org/LICENSE_1_0.txt
</ulink>)
]
]
[/ QuickBook Document version 0.9 ]
[def __note__ [$images/note.png]]
[def __alert__ [$images/alert.png]]
[def __tip__ [$images/tip.png]]
[def :-) [$images/smiley.png]]
[def __jam__ [$images/jam.png]]
[section QuickStart]
The Boost Python Library is a framework for interfacing Python and
C++. It allows you to quickly and seamlessly expose C++ classes
functions and objects to Python, and vice-versa, using no special
tools -- just your C++ compiler. It is designed to wrap C++ interfaces
non-intrusively, so that you should not have to change the C++ code at
all in order to wrap it, making Boost.Python ideal for exposing
3rd-party libraries to Python. The library's use of advanced
metaprogramming techniques simplifies its syntax for users, so that
wrapping code takes on the look of a kind of declarative interface
definition language (IDL).
[h2 Hello World]
Following C/C++ tradition, let's start with the "hello, world". A C++
Function:
char const* greet()
{
return "hello, world";
}
can be exposed to Python by writing a Boost.Python wrapper:
#include <boost/python.hpp>
using namespace boost::python;
BOOST_PYTHON_MODULE(hello)
{
def("greet", greet);
}
That's it. We're done. We can now build this as a shared library. The
resulting DLL is now visible to Python. Here's a sample Python session:
[python]
>>> import hello
>>> print hello.greet()
hello, world
[c++]
[:['[*Next stop... Building your Hello World module from start to finish...]]]
[endsect]
[section:hello Building Hello World]
[h2 From Start To Finish]
Now the first thing you'd want to do is to build the Hello World module and
try it for yourself in Python. In this section, we shall outline the steps
necessary to achieve that. We shall use the build tool that comes bundled
with every boost distribution: [*bjam].
[blurb __note__ [*Building without bjam]\n\n
Besides bjam, there are of course other ways to get your module built.
What's written here should not be taken as "the one and only way".
There are of course other build tools apart from [^bjam].\n\n
Take note however that the preferred build tool for Boost.Python is bjam.
There are so many ways to set up the build incorrectly. Experience shows
that 90% of the "I can't build Boost.Python" problems come from people
who had to use a different tool.
]
We shall skip over the details. Our objective will be to simply create the
hello world module and run it in Python. For a complete reference to
building Boost.Python, check out: [@../../../building.html building.html].
After this brief ['bjam] tutorial, we should have built two DLLs:
* boost_python.dll
* hello.pyd
if you are on Windows, and
* libboost_python.so
* hello.so
if you are on Unix.
The tutorial example can be found in the directory:
[^libs/python/example/tutorial]. There, you can find:
* hello.cpp
* Jamfile
The [^hello.cpp] file is our C++ hello world example. The [^Jamfile] is a
minimalist ['bjam] script that builds the DLLs for us.
Before anything else, you should have the bjam executable in your boost
directory or somewhere in your path such that [^bjam] can be executed in
the command line. Pre-built Boost.Jam executables are available for most
platforms. The complete list of Bjam executables can be found
[@http://sourceforge.net/project/showfiles.php?group_id=7586 here].
[h2 Let's Jam!]
__jam__
Here is our minimalist Jamfile:
[pre
# This is the top of our own project tree
project-root ;
import python ;
extension hello # Declare a Python extension called hello
: hello.cpp # source
# requirements and dependencies for Boost.Python extensions
<template>@boost/libs/python/build/extension
;
]
First, we need to specify our location. You may place your project anywhere.
[^project-root] allows you to do that.
[pre
project-root ;
]
By doing so, you'll need a Jamrules file. Simply copy the one in the
[@../../../../example/tutorial/Jamrules example/tutorial directory] and tweak
the [^path-global BOOST_ROOT] to where your boost root directory is. The file
has [@../../../../example/tutorial/Jamrules detailed instructions] you can follow.
Then we will import the definitions needed by Python modules:
[pre
import python ;
]
Finally we declare our [^hello] extension:
[pre
extension hello # Declare a Python extension called hello
: hello.cpp # source
# requirements and dependencies for Boost.Python extensions
<template>@boost/libs/python/build/extension
;
]
The last part tells BJam that we are depending on the Boost Python Library.
[h2 Running bjam]
['bjam] is run using your operating system's command line interpreter.
[:Start it up.]
Make sure that the environment is set so that we can invoke the C++
compiler. With MSVC, that would mean running the [^Vcvars32.bat] batch
file. For instance:
[pre
C:\Program Files\Microsoft Visual Studio .NET 2003\Common7\Tools\vsvars32.bat
]
Some environment variables will have to be setup for proper building of our
Python modules. Example:
[pre
set PYTHON_ROOT=c:/dev/tools/python
set PYTHON_VERSION=2.2
]
The above assumes that the Python installation is in [^c:/dev/tools/python]
and that we are using Python version 2.2. You'll have to tweak these
appropriately.
[blurb __tip__ Be sure not to include a third number, e.g. [*not] "2.2.1",
even if that's the version you have.]
Take note that you may also do that through the Jamrules file we put in
our project as detailed above. The file
has [@../../../../example/tutorial/Jamrules detailed instructions] you
can follow.
Now we are ready... Be sure to [^cd] to [^libs/python/example/tutorial]
where the tutorial [^"hello.cpp"] and the [^"Jamfile"] is situated.
Finally:
bjam -sTOOLS=vc-7_1
We are again assuming that we are using Microsoft Visual C++ version 7.1. If
not, then you will have to specify the appropriate tool. See
[@../../../../../../tools/build/index.html Building Boost Libraries] for
further details.
It should be building now:
[pre
cd C:\dev\boost\libs\python\example\tutorial
bjam -sTOOLS=msvc
...patience...
...found 1703 targets...
...updating 40 targets...
]
And so on... Finally:
[pre
Creating library bin\boost\libs\python\build\boost_python.dll\vc-7_1\debug\th
reading-multi\boost_python.lib and object bin\boost\libs\python\build\boost_pyth
on.dll\vc-7_1\debug\threading-multi\boost_python.exp
vc-C++ bin\tutorial\hello.pyd\vc-7_1\debug\threading-multi\hello.obj
hello.cpp
vc-Link bin\tutorial\hello.pyd\vc-7_1\debug\threading-multi\hello.pyd bin\tutori
al\hello.pyd\vc-7_1\debug\threading-multi\hello.lib
Creating library bin\tutorial\hello.pyd\vc-7_1\debug\threading-multi\hello.li
b and object bin\tutorial\hello.pyd\vc-7_1\debug\threading-multi\hello.exp
...updated 31 targets...
]
If all is well, you should now have:
* boost_python.dll
* hello.pyd
if you are on Windows, and
* libboost_python.so
* hello.so
if you are on Unix.
[^boost_python.dll] and [^hello.pyd] can be found somewhere in your project's
[^bin] directory. After a successful build, you can just link in these DLLs with
the Python interpreter. In Windows for example, you can simply put these libraries
inside the directory where the Python executable is.
You may now fire up Python and run our hello module:
[python]
>>> import hello
>>> print hello.greet()
hello, world
[c++]
[:[*There you go... Have fun!]]
[endsect]
[section:exposing Exposing Classes]
Now let's expose a C++ class to Python.
Consider a C++ class/struct that we want to expose to Python:
struct World
{
void set(std::string msg) { this->msg = msg; }
std::string greet() { return msg; }
std::string msg;
};
We can expose this to Python by writing a corresponding Boost.Python
C++ Wrapper:
#include <boost/python.hpp>
using namespace boost::python;
BOOST_PYTHON_MODULE(hello)
{
class_<World>("World")
.def("greet", &World::greet)
.def("set", &World::set)
;
}
Here, we wrote a C++ class wrapper that exposes the member functions
[^greet] and [^set]. Now, after building our module as a shared library, we
may use our class [^World] in Python. Here's a sample Python session:
[python]
>>> import hello
>>> planet = hello.World()
>>> planet.set('howdy')
>>> planet.greet()
'howdy'
[section Constructors]
Our previous example didn't have any explicit constructors.
Since [^World] is declared as a plain struct, it has an implicit default
constructor. Boost.Python exposes the default constructor by default,
which is why we were able to write
>>> planet = hello.World()
We may wish to wrap a class with a non-default constructor. Let us
build on our previous example:
[c++]
struct World
{
World(std::string msg): msg(msg) {} // added constructor
void set(std::string msg) { this->msg = msg; }
std::string greet() { return msg; }
std::string msg;
};
This time [^World] has no default constructor; our previous
wrapping code would fail to compile when the library tried to expose
it. We have to tell [^class_<World>] about the constructor we want to
expose instead.
#include <boost/python.hpp>
using namespace boost::python;
BOOST_PYTHON_MODULE(hello)
{
class_<World>("World", init<std::string>())
.def("greet", &World::greet)
.def("set", &World::set)
;
}
[^init<std::string>()] exposes the constructor taking in a
[^std::string] (in Python, constructors are spelled
"[^"__init__"]").
We can expose additional constructors by passing more [^init<...>]s to
the [^def()] member function. Say for example we have another World
constructor taking in two doubles:
class_<World>("World", init<std::string>())
.def(init<double, double>())
.def("greet", &World::greet)
.def("set", &World::set)
;
On the other hand, if we do not wish to expose any constructors at
all, we may use [^no_init] instead:
class_<Abstract>("Abstract", no_init)
This actually adds an [^__init__] method which always raises a
Python RuntimeError exception.
[endsect]
[section Class Data Members]
Data members may also be exposed to Python so that they can be
accessed as attributes of the corresponding Python class. Each data
member that we wish to be exposed may be regarded as [*read-only] or
[*read-write]. Consider this class [^Var]:
struct Var
{
Var(std::string name) : name(name), value() {}
std::string const name;
float value;
};
Our C++ [^Var] class and its data members can be exposed to Python:
class_<Var>("Var", init<std::string>())
.def_readonly("name", &Var::name)
.def_readwrite("value", &Var::value);
Then, in Python, assuming we have placed our Var class inside the namespace
hello as we did before:
[python]
>>> x = hello.Var('pi')
>>> x.value = 3.14
?? 快捷鍵說明
復制代碼
Ctrl + C
搜索代碼
Ctrl + F
全屏模式
F11
切換主題
Ctrl + Shift + D
顯示快捷鍵
?
增大字號
Ctrl + =
減小字號
Ctrl + -