# Background

GObject, and its lower-level type system, GType, are used by GTK+ and most GNOME libraries to provide:

- object-oriented C-based APIs and

- automatic transparent API bindings to other compiled or interpreted languages.

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.

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.

## Data types and programming

One could say 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.

In C, the language provides types such as char, long, pointer. 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 (assuming one exists), 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).

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:

    my $tmp = 10;
    print "this is an integer converted to a string:" . $tmp . "\n";

Of course, it is also often possible to explicitly specify conversions when the default conversions provided by the language are not intuitive.

## Exporting a C API

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.

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.

For the sake of discussion, here is a sample C function and the associated 32 bit x86 assembly code generated by GCC on a Linux computer:

    static void
    function_foo (int foo)
    {
    }

    int
    main (int   argc,
          char *argv[])
    {
    	function_foo (10);

    	return 0;
    }

    push   $0xa
    call   0x80482f4 <function_foo>

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_foo`. As you can see, C function calls are implemented by GCC as native function calls (this is probably the fastest implementation possible).

Now, let's say we want to call the C function `function_foo` from a Python program. To do this, the Python interpreter needs to:

- Find where the function is located. This probably means finding the binary generated by the C compiler which exports this function.

- Load the code of the function in executable memory.

- Convert the Python parameters to C-compatible parameters before calling the function.

- Call the function with the right calling convention.

- Convert the return values of the C function to Python-compatible variables to return them to the Python code.

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:

- 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.

- 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.

- 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 dynamic type

  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.

  library is then used by special generic glue code to automatically convert function parameters and function calling conventions between different runtime domains.

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.
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.

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.