# 3 Scripting Languages

- The two language view of the world
- How does a scripting language talk to C?
  - Wrapper functions
  - Variable linking
  - Constants
  - Structures and classes
  - Shadow classes
- Building scripting language extensions
  - Shared libraries and dynamic loading
  - Linking with shared libraries
  - Static linking

This chapter provides a brief overview of scripting language extension programming and the mechanisms by which scripting language interpreters access C and C++ code.

## 3.1 The two language view of the world

When a scripting language is used to control a C program, the resulting system tends to look as follows:

In this programming model, the scripting language interpreter is used for high level control whereas the underlying functionality of the C/C++ program is accessed through special scripting language "commands." If you have ever tried to write your own simple command interpreter, you might view the scripting language approach to be a highly advanced implementation of that. Likewise, If you have ever used a package such as MATLAB or IDL, it is a very similar model--the interpreter executes user commands and scripts. However, most of the underlying functionality is written in a low-level language like C or Fortran.

The two-language model of computing is extremely powerful because it exploits the strengths of each language. C/C++ can be used for maximal performance and complicated systems programming tasks. Scripting languages can be used for rapid prototyping, interactive debugging, scripting, and access to high-level data structures such associative arrays.

## 3.2 How does a scripting language talk to C?

Scripting languages are built around a parser that knows how to execute commands and scripts. Within this parser, there is a mechanism for executing commands and accessing variables. Normally, this is used to implement the builtin features of the language. However, by extending the interpreter, it is usually possible to add new commands and variables. To do this, most languages define a special API for adding new commands. Furthermore, a special foreign function interface defines how these new commands are supposed to hook into the interpreter.

Typically, when you add a new command to a scripting interpreter you need to do two things; first you need to write a special "wrapper" function that serves as the glue between the interpreter and the underlying C function. Then you need to give the interpreter information about the wrapper by providing details about the name of the function, arguments, and so forth. The next few sections illustrate the process.

### 3.2.1 Wrapper functions

Suppose you have an ordinary C function like this :

>     int fact(int n) {
>     	if (n <= 1) return 1;
>     	else return n*fact(n-1);
>     }

In order to access this function from a scripting language, it is necessary to write a special "wrapper" function that serves as the glue between the scripting language and the underlying C function. A wrapper function must do three things :

- Gather function arguments and make sure they are valid.
- Call the C function.
- Convert the return value into a form recognized by the scripting language.

As an example, the Tcl wrapper function for the `fact()` function above example might look like the following :

>     int wrap_fact(ClientData clientData, Tcl_Interp *interp,
>     		int argc, char *argv[]) {
>     	int result;
>     	int arg0;
>     	if (argc != 2) {
>     		interp->result = "wrong # args";
>     		return TCL_ERROR;
>     	}
>     	arg0 = atoi(argv[1]);
>     	result = fact(arg0);
>     	sprintf(interp->result,"%d", result);
>     	return TCL_OK;
>     }

Once you have created a wrapper function, the final step is to tell the scripting language about the new function. This is usually done in an initialization function called by the language when the module is loaded. For example, adding the above function to the Tcl interpreter requires code like the following :

>     int Wrap_Init(Tcl_Interp *interp) {
>     	Tcl_CreateCommand(interp, "fact", wrap_fact, (ClientData) NULL,
>     				(Tcl_CmdDeleteProc *) NULL);
>     	return TCL_OK;
>     }

When executed, Tcl will now have a new command called "`fact`" that you can use like any other Tcl command.

Although the process of adding a new function to Tcl has been illustrated, the procedure is almost identical for Perl and Python. Both require special wrappers to be written and both need additional initialization code. Only the specific details are different.

### 3.2.2 Variable linking

Variable linking refers to the problem of mapping a C/C++ global variable to a variable in the scripting language interpeter. For example, suppose you had the following variable:

>     double Foo = 3.5;

It might be nice to access it from a script as follows (shown for Perl):

>     $a = $Foo * 2.3;   # Evaluation
>     $Foo = $a + 2.0;   # Assignment

To provide such access, variables are commonly manipulated using a pair of get/set functions. For example, whenever the value of a variable is read, a "get" function is invoked. Similarly, whenever the value of a variable is changed, a "set" function is called.

In many languages, calls to the get/set functions can be attached to evaluation and assignment operators. Therefore, evaluating a variable such as `$Foo` might implicitly call the get function. Similarly, typing `$Foo = 4` would call the underlying set function to change the value.

### 3.2.3 Constants

In many cases, a C program or library may define a large collection of constants. For example:

>     #define RED   0xff0000
>     #define BLUE  0x0000ff
>     #define GREEN 0x00ff00

To make constants available, their values can be stored in scripting language variables such as `$RED`, `$BLUE`, and `$GREEN`. Virtually all scripting languages provide C functions for creating variables so installing constants is usually a trivial exercise.

### 3.2.4 Structures and classes

Although scripting languages have no trouble accessing simple functions and variables, accessing C/C++ structures and classes present a different problem. This is because the implementation of structures is largely related to the problem of data representation and layout. Furthermore, certain language features are difficult to map to an interpreter. For instance, what does C++ inheritance mean in a Perl interface?

The most straightforward technique for handling structures is to implement a collection of accessor functions that hide the underlying representation of a structure. For example,

>     struct Vector {
>     	Vector();
>     	~Vector();
>     	double x,y,z;
>     };

can be transformed into the following set of functions :

>     Vector *new_Vector();
>     void delete_Vector(Vector *v);
>     double Vector_x_get(Vector *v);
>     double Vector_y_get(Vector *v);
>     double Vector_y_get(Vector *v);
>     void Vector_x_set(Vector *v, double x);
>     void Vector_y_set(Vector *v, double y);
>     void Vector_z_set(Vector *v, double z);

Now, from an interpreter these function might be used as follows:

>     % set v [new_Vector]
>     % Vector_x_set $v 3.5
>     % Vector_y_get $v
>     % delete_Vector $v
>     % ...

Since accessor functions provide a mechanism for accessing the internals of an object, the interpreter does not need to know anything about the actual representation of a `Vector`.

### 3.2.5 Shadow classes

In certain cases, it is possible to use the low-level accessor functions to create something known as a "shadow" class. A "shadow class" is a special kind of object that gets created in a scripting language to access a C/C++ class (or struct) in a way that looks like the original structure (that is, it "shadows" the real C++ class). For example, if you have the following C definition :

>     class Vector {
>     public:
>     	Vector();
>     	~Vector();
>     	double x,y,z;
>     };

A shadow classing mechanism would allow you to access the structure in a more natural manner from the interpreter. For example, in Python, you might want to do this:

>     >>> v = Vector()
>     >>> v.x = 3
>     >>> v.y = 4
>     >>> v.z = -13
>     >>> ...
>     >>> del v

Similarly, in Perl5 you may want the interface to work like this:

>     $v = new Vector;
>     $v->{x} = 3;
>     $v->{y} = 4;
>     $v->{z} = -13;

Finally, in Tcl :

>     Vector v
>     v configure -x 3 -y 4 -z 13

When shadow classes are used, two objects are at really work--one in the scripting language, and an underlying C/C++ object. Operations affect both objects equally and for all practical purposes, it appears as if you are simply manipulating a C/C++ object.

## 3.3 Building scripting language extensions

The final step in using a scripting language with your C/C++ application is adding your extensions to the scripting language itself. There are two primary approaches for doing this. The preferred technique is to build a dynamically loadable extension in the form a shared library. Alternatively, you can recompile the scripting language interpreter with your extensions added to it.

### 3.3.1 Shared libraries and dynamic loading

To create a shared library or DLL, you often need to look at the manual pages for your compiler and linker. However, the procedure for a few common machines is shown below:

>     # Build a shared library for Solaris
>     gcc -c example.c example_wrap.c -I/usr/local/include
>     ld -G example.o example_wrap.o -o example.so

>     # Build a shared library for Linux
>     agcc -fpic -c example.c example_wrap.c -I/usr/local/include
>     gcc -shared example.o example_wrap.o -o example.so

>     # Build a shared library for Irix
>     gcc -c example.c example_wrap.c -I/usr/local/include
>     ld -shared example.o example_wrap.o -o example.so

To use your shared library, you simply use the corresponding command in the scripting language (load, import, use, etc...). This will import your module and allow you to start using it. For example:

>     % load ./example.so
>     % fact 4
>     24
>     %

When working with C++ codes, the process of building shared libraries may be more complicated--primarily due to the fact that C++ modules may need additional code in order to operate correctly. On many machines, you can build a shared C++ module by following the above procedures, but changing the link line to the following :

>     c++ -shared example.o example_wrap.o -o example.so

### 3.3.2 Linking with shared libraries

When building extensions as shared libraries, it is not uncommon for your extension to rely upon other shared libraries on your machine. In order for the extension to work, it needs to be able to find all of these libraries at run-time. Otherwise, you may get an error such as the following :

>     >>> import graph
>     Traceback (innermost last):
>       File "<stdin>", line 1, in ?
>       File "/home/sci/data1/beazley/graph/graph.py", line 2, in ?
>         import graphc
>     ImportError:  1101:/home/sci/data1/beazley/bin/python: rld: Fatal Error: cannot
>     successfully map soname 'libgraph.so' under any of the filenames /usr/lib/libgraph.so:/
>     lib/libgraph.so:/lib/cmplrs/cc/libgraph.so:/usr/lib/cmplrs/cc/libgraph.so:
>     >>>

What this error means is that the extension module created by SWIG depends upon a shared library called "`libgraph.so`" that the system was unable to locate. To fix this problem, there are a few approaches you can take.

- Link your extension and explicitly tell the linker where the required libraries are located. Often times, this can be done with a special linker flag such as `-R`, `-rpath`, etc. This is not implemented in a standard manner so read the man pages for your linker to find out more about how to set the search path for shared libraries.
- Put shared libraries in the same directory as the executable. This technique is sometimes required for correct operation on non-Unix platforms.
- Set the UNIX environment variable `LD_LIBRARY_PATH` to the directory where shared libraries are located before running Python. Although this is an easy solution, it is not recommended. Consider setting the path using linker options instead.

### 3.3.3 Static linking

With static linking, you rebuild the scripting language interpreter with extensions. The process usually involves compiling a short main program that adds your customized commands to the language and starts the interpreter. You then link your program with a library to produce a new scripting language executable.

Although static linking is supported on all platforms, this is not the preferred technique for building scripting language extensions. In fact, there are very few practical reasons for doing this--consider using shared libraries instead.