mirror of
https://gitlab.gnome.org/GNOME/glib.git
synced 2024-11-05 08:56:16 +01:00
8db223409d
2005-05-25 Mathieu Lacage <mathieu@gnome.org> * gobject/tut_*.xml: fix lots of typos, some of which were reported by Leonardo Boshell.
174 lines
8.2 KiB
XML
174 lines
8.2 KiB
XML
<chapter>
|
|
<title>Background</title>
|
|
|
|
<para>
|
|
GObject, and its lower-level type system, GType, are used by GTK+ and most Gnome libraries to
|
|
provide:
|
|
<itemizedlist>
|
|
<listitem><para>object-oriented C-based APIs and</para></listitem>
|
|
<listitem><para>automatic transparent API bindings to other compiled
|
|
or interpreted languages.</para></listitem>
|
|
</itemizedlist>
|
|
</para>
|
|
|
|
<para>A lot of programmers are used to work with compiled-only or dynamically interpreted-only
|
|
languages and do not understand the challenges associated with cross-language interoperability.
|
|
This introduction tries to provide an insight into these challenges. describes briefly
|
|
the solution choosen by GLib.
|
|
</para>
|
|
|
|
<para>The following chapters go into greater detail into how GType and GObject work and
|
|
how you can use them as a C programmer. It is useful to keep in mind that
|
|
allowing access to C objects from other interpreted languages was one of the major design
|
|
goals: this can often explain the sometimes rather convoluted APIs and features present
|
|
in this library.
|
|
</para>
|
|
|
|
<sect1>
|
|
<title>Data types and programming</title>
|
|
|
|
<para>
|
|
One could say (I have seen such definitions used in some textbooks on programming language theory)
|
|
that a programming language is merely a way to create data types and manipulate them. Most languages
|
|
provide a number of language-native types and a few primitives to create more complex types based
|
|
on these primitive types.
|
|
</para>
|
|
|
|
<para>
|
|
In C, the language provides types such as <emphasis>char</emphasis>, <emphasis>long</emphasis>,
|
|
<emphasis>pointer</emphasis>. During compilation of C code, the compiler maps these
|
|
language types to the compiler's target architecture machine types. If you are using a C interpreter
|
|
(I have never seen one myself but it is possible :), the interpreter (the program which interprets
|
|
the source code and executes it) maps the language types to the machine types of the target machine at
|
|
runtime, during the program execution (or just before execution if it uses a Just In Time compiler engine).
|
|
</para>
|
|
|
|
<para>Perl and Python which are interpreted languages do not really provide type definitions similar
|
|
to those used by C. Perl and Python programmers manipulate variables and the type of the variables
|
|
is decided only upon the first assignment or upon the first use which forces a type on the variable.
|
|
The interpreter also often provides a lot of automatic conversions from one type to the other. For example,
|
|
in Perl, a variable which holds an integer can be automatically converted to a string given the
|
|
required context:
|
|
<programlisting>
|
|
my $tmp = 10;
|
|
print "this is an integer converted to a string:" . $tmp . "\n";
|
|
</programlisting>
|
|
Of course, it is also often possible to explicitely specify conversions when the default conversions provided
|
|
by the language are not intuitive.
|
|
</para>
|
|
|
|
</sect1>
|
|
|
|
<sect1>
|
|
<title>Exporting a C API</title>
|
|
|
|
<para>C APIs are defined by a set of functions and global variables which are usually exported from a
|
|
binary. C functions have an arbitrary number of arguments and one return value. Each function is thus
|
|
uniquely identified by the function name and the set of C types which describe the function arguments
|
|
and return value. The global variables exported by the API are similarly identified by their name and
|
|
their type.
|
|
</para>
|
|
|
|
<para>
|
|
A C API is thus merely defined by a set of names to which a set of types are associated. If you know the
|
|
function calling convention and the mapping of the C types to the machine types used by the platform you
|
|
are on, you can resolve the name of each function to find where the code associated to this function
|
|
is located in memory, and then construct a valid argument list for the function. Finally, all you have to
|
|
do is triger a call to the target C function with the argument list.
|
|
</para>
|
|
|
|
<para>
|
|
For the sake of discussion, here is a sample C function and the associated 32 bit x86
|
|
assembly code generated by gcc on my linux box:
|
|
<programlisting>
|
|
static void function_foo (int foo)
|
|
{}
|
|
|
|
int main (int argc, char *argv[])
|
|
{
|
|
|
|
function_foo (10);
|
|
|
|
return 0;
|
|
}
|
|
|
|
push $0xa
|
|
call 0x80482f4 <function_foo>
|
|
</programlisting>
|
|
The assembly code shown above is pretty straightforward: the first instruction pushes
|
|
the hexadecimal value 0xa (decimal value 10) as a 32 bit integer on the stack and calls
|
|
<function>function_foo</function>. As you can see, C function calls are implemented by
|
|
gcc by native function calls (this is probably the fastest implementation possible).
|
|
</para>
|
|
|
|
<para>
|
|
Now, let's say we want to call the C function <function>function_foo</function> from
|
|
a python program. To do this, the python interpreter needs to:
|
|
<itemizedlist>
|
|
<listitem><para>Find where the function is located. This means probably find the binary generated by the C compiler
|
|
which exports this functions.</para></listitem>
|
|
<listitem><para>Load the code of the function in executable memory.</para></listitem>
|
|
<listitem><para>Convert the python parameters to C-compatible parameters before calling
|
|
the function.</para></listitem>
|
|
<listitem><para>Call the function with the right calling convention</para></listitem>
|
|
<listitem><para>Convert the return values of the C function to python-compatible
|
|
variables to return them to the python code.</para></listitem>
|
|
</itemizedlist>
|
|
</para>
|
|
|
|
<para>The process described above is pretty complex and there are a lot of ways to make it entirely automatic
|
|
and transparent to the C and the Python programmers:
|
|
<itemizedlist>
|
|
<listitem><para>The first solution is to write by hand a lot of glue code, once for each function exported or imported,
|
|
which does the python to C parameter conversion and the C to python return value conversion. This glue code is then
|
|
linked with the interpreter which allows python programs to call a python functions which delegates the work to the
|
|
C function.</para></listitem>
|
|
<listitem><para>Another nicer solution is to automatically generate the glue code, once for each function exported or
|
|
imported, with a special compiler which
|
|
reads the original function signature.</para></listitem>
|
|
<listitem><para>The solution used by GLib is to use the GType library which holds at runtime a description of
|
|
all the objects manipulated by the programmer. This so-called <emphasis>dynamic type</emphasis><footnote>
|
|
<para>
|
|
There are numerous different implementations of dynamic type systems: all C++
|
|
compilers have one, Java and .NET have one too. A dynamic type system allows you
|
|
to get information about every instantiated object at runtime. It can be implemented
|
|
by a process-specific database: every new object created registers the characteristics
|
|
of its associated type in the type system. It can also be implemented by introspection
|
|
interfaces. The common point between all these different type systems and implementations
|
|
is that they all allow you to query for object metadata at runtime.
|
|
</para>
|
|
</footnote>
|
|
|
|
library is then
|
|
used by special generic glue code to automatically convert function parameters and function calling conventions
|
|
between different runtime domains.</para></listitem>
|
|
</itemizedlist>
|
|
The greatest advantage of the solution implemented by GType is that the glue code sitting at the runtime domain
|
|
boundaries is written once: the figure below states this more clearly.
|
|
<figure>
|
|
<mediaobject>
|
|
<imageobject> <!-- this is for HTML output -->
|
|
<imagedata fileref="glue.png" format="PNG" align="center"/>
|
|
</imageobject>
|
|
<imageobject> <!-- this is for PDF output -->
|
|
<imagedata fileref="glue.jpg" format="JPG" align="center"/>
|
|
</imageobject>
|
|
</mediaobject>
|
|
</figure>
|
|
|
|
Currently, there exist at least Python and Perl generic glue code which makes it possible to use
|
|
C objects written with GType directly in Python or Perl, with a minimum amount of work: there
|
|
is no need to generate huge amounts of glue code either automatically or by hand.
|
|
</para>
|
|
|
|
<para>Although that goal was arguably laudable, its pursuit has had a major influence on
|
|
the whole GType/GObject library. C programmers are likely to be puzzled at the complexity
|
|
of the features exposed in the following chapters if they forget that the GType/GObject library
|
|
was not only designed to offer OO-like features to C programmers but also transparent
|
|
cross-language interoperability.
|
|
</para>
|
|
|
|
</sect1>
|
|
|
|
</chapter>
|