glib/docs/reference/gobject/tut_intro.xml

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<chapter id="chapter-intro">
  <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 working 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 and briefly describes
    the solution chosen 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 are interpreted languages which 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:
<informalexample><programlisting>
my $tmp = 10;
print "this is an integer converted to a string:" . $tmp . "\n";
</programlisting></informalexample>
      Of course, it is also often possible to explicitly 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 trigger 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:
<informalexample><programlisting>
static void function_foo (int foo)
{}

int main (int argc, char *argv[])
{

        function_foo (10);

        return 0;
}

push   $0xa
call   0x80482f4 &lt;function_foo>
</programlisting></informalexample>
      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 probably means finding the binary generated by the C compiler
        which exports this function.</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 C and 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 Python functions which delegate work to
        C functions.</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>