Other Languages (Running Linux, 4th Edition)

13.6. Other Languages

Many other popular (and not-so-popular) languages are available for Linux. For the most part, however, these work identically on Linux as on other Unix systems, so there's not much in the way of news there. There are also so many of them that we can't cover them in much detail here. We do want to let you know what's out there, however, and explain some of the differences between the various languages and compilers.

Python has gained a lot of attention lately because it is a powerful mixture of different programming paradigms and styles. For example, it is one of the very few interpreted object-oriented programming languages (Perl being another example, but only relatively late in its existence). Python fans say it is especially easy to learn. Python was written and designed almost entirely by Guido van Rossum, who chose the name because he wrote the interpreter while watching reruns of the British TV show Monty Python's Flying Circus. The language is introduced in Learning Python by Mark Lutz and David Ascher and covered in detail in Programming Python by Mark Lutz (both published by O'Reilly).

As nice and useful as Perl is, it has one disadvantage — or at least many people think so — namely, that you can write the same code in many different ways. This has given Perl the reputation that it's easy to write code in Perl, but hard to read it. (The point is that another programmer might do things differently from you, and you are therefore not used to reading this style.)

This means that Perl might not be the right choice for developing code that later must be maintained for years to come.

If you normally develop software in C, C++, or Java, and from time to time you want to do some scripting, you might find that Perl's syntax is too different from what you are normally used to — e.g., you need to type a dollar in front of a variable:

foreach $user ...

Before we look into a bit more detail at what Python is, let us suggest that whether you choose to program in Perl or Python is largely a matter of "religion," just as it is a matter of "religion" whether you use Emacs or vi, or whether you use KDE or GNOME. Perl and Python both fill the gap between real languages like C/C++/Java and scripting languages like the language built into bash or tcsh.

In contrast to Perl, Python was designed from the beginning to be a real programming language, with many of the constructs inspired from C. This does undoubtedly mean that Python programs are easier to read than Perl ones, even though they might come out slightly longer.

Python is an object-oriented language, but you do not need to program in an object-oriented fashion if you do not want to. This makes it possible for you to start your scripting without worrying about object orientation, and as you go along and your script gets longer and more complicated, you can easily convert it to use objects.

Python scripts are interpreted, which means that you do not need to wait for a long compilation process to take place. Python programs are internally byte-compiled on the fly, which ensures that they still run at an acceptable speed. In normal daily use, you don't really notice all this, except for the fact that when you write a .py file, Python will create a .pyc file.

Python has lists, tuples, strings, and associative arrays (or in Python lingo, dictionaries) built into the syntax of the language, which makes working with these types very easy.

Python comes with an extensive library, similar in power to what we saw previously for Perl. See http://www.python.org/doc/current/lib/lib.html for a complete library reference.

Let's complete this short introduction to Python by looking at a small Python script. This will hopefully give you an idea of the level of abstraction Python works on. The script does the same as the earlier Perl script. Your first impression of the script might very well be that it is way longer than the Perl script. Remember that we are forcing Python to "compete" here in the area where Perl is most powerful. To compensate, we find that this script is more straightforward to read.

Also notice the indentation. While indentation is optional in most other languages and just makes the code more readable, it is required in Python and is one of its characterizing features.

1    #!/usr/bin/python
2    
3    import sys, re, string
4    
5    minutes = {  }
6    count = {  }
7    line = sys.stdin.readline( )
8    while line:
9      match = re.match( "^(\S*)\s*.*\(([0-9]+):([0-9]+)\)\s*$", line )
10     if match:
11       user = match.group(1)
12       time = string.atoi(match.group(2))*60 + string.atoi(match.group(3))
13       if not count.has_key( user ):
14         minutes[ user ] = 0
15         count[ user ]   = 0
16       minutes[ user ] += time
17       count[user] += 1
18     line = sys.stdin.readline( )
19
20   for user in count.keys( ):
21     hour = `minutes[user]/60`
22     min = minutes[user] % 60
23     if min < 10:
24       minute = "0" + `min`
25     else:
26       minute = `min`
27     print "User " + user + ", total login time " + \
28           hour + ":" + minute + \
29           ", total logins " + `count[user]`

The script should be self-explanatory, with a few exceptions. On line 3 we import the libraries we want to use. Having imported string, for instance, we may use it as in line 12, where we use the method atoi from the library string.

On lines 5 and 6 we initialize two dictionaries. In contrast to Perl, we need to initialize them before we can assign values to them. Line 7 reads a line from standard input. When no more lines can be read, the readline method returns None, which is the equivalent to a null pointer.

Line 9 matches the line read from stdin against a regular expression, and returns a match object as a result of matching. This object contains a method for accessing the subparts of the match. Line 21 converts the result of the division minutes[user]/60 to a string. This is done using two back quotes.

You can read all about Python at http://www.python.org or in Learning Python by Mark Lutz and David Ascher and in Programming Python by Mark Lutz, both from O'Reilly.

Another recent development in the area of scripting languages, the Ruby language was developed in Japan and has gained an impressive following there. It is an object-oriented scripting language that goes (if possible) even further than Python in its use of objects.

Tcl (Tool Command Language) is a language that was meant as a glue for connecting programs together, but it has become most famous for its included, easy-to-use windowing toolkit, Tk.

LISP is an interpreted language used in many applications, ranging from artificial intelligence to statistics. It is used primarily in computer science because it defines a clean, logical interface for working with algorithms. (It also uses a lot of parentheses, something of which computer scientists are always fond.) It is a functional programming language and is very generalized. Many operations are defined in terms of recursion instead of linear loops. Expressions are hierarchical, and data is represented by lists of items.

Several LISP interpreters are available for Linux. Emacs LISP is a fairly complete implementation in itself. It has many features that allow it to interact directly with Emacs — input and output through Emacs buffers, for example — but it may be used for non-Emacs-related applications as well.

Also available is CLISP, a Common LISP implementation by Bruno Haible of Karlsruhe University and Michael Stoll of Munich University. It includes an interpreter, a compiler, and a subset of CLOS (Common LISP Object System, an object-oriented extension to LISP). CLX, a Common LISP interface to the X Window System, is also available, and it runs under CLISP. CLX allows you to write X-based applications in LISP. Austin Kyoto Common LISP, another LISP implementation, is available and compatible with CLX as well.

SWI-Prolog, a complete Prolog implementation by Jan Wielemaker of the University of Amsterdam, is also available. Prolog is a logic-based language, allowing you to make logical assertions, define heuristics for validating those assertions, and make decisions based on them. It is a useful language for AI applications.

Also available are several Scheme interpreters, including MIT Scheme, a complete Scheme interpreter conforming to the R⁴ standard. Scheme is a dialect of LISP that offers a cleaner, more general programming model. It is a good LISP dialect for computer science applications and for studying algorithms.

At least two implementations of Ada are available — AdaEd, an Ada interpreter, and GNAT, the GNU Ada Translator. GNAT is actually a full-fledged optimizing Ada compiler. It is to Ada what gcc is to C and C++.

Along the same vein, two other popular language translators exist for Linux — p2c, a Pascal-to-C translator, and f2c, a FORTRAN-to-C translator. If you're concerned that these translators won't function as well as bona fide compilers, don't be. Both p2c and f2c have proven to be robust and useful for heavy Pascal and FORTRAN use.

f2c is Fortran-77-compliant, and a number of tools are available for it as well. ftnchek is a FORTRAN checker, similar to lint. Both the LAPACK numerical methods library and the mpfun multiprecision FORTRAN library have been ported to Linux using f2c. toolpack is a collection of FORTRAN tools that includes such items as a source-code pretty printer, a precision converter, and a portability checker.

Among the miscellaneous other languages available for Linux are interpreters for APL, Rexx, Forth, ML, and Eiffel, as well as a Simula-to-C translator. The GNU versions of the compiler tools lex and yacc (renamed to flex and bison, respectively), which are used for many software packages, have also been ported to Linux. lex and yacc are invaluable for creating any kind of parser or translator, most commonly used when writing compilers.