Author Archive

I’ve always been one of the (not so) few geeks who run Linux on PowerPC.
Sometime ago, Linus himself was one of us, however, it appears that now
he uses a different machine.

Since Apple dropped PPC, the Linux PPC world is quite in turmoil. The architecture is perceived as almost dead. However, new interest comes from the Linux on PS3 projects.

In any case Ubuntu dropped official support for PPC. That was a sad piece of new, since I was quite satisfied with it. I had to recompile the kernel in order to fully support my machine (but this would have been solved in successive releases).

I got back to Debian. I’ve been a Debian user since Woody, and I liked it ever since. I was a Debian unstable user, and I have always been satisfied with it. However, this time it was different. I’ve had many more troubles: each upgrade broke something I needed.

I don’t know if it’s a matter of developers paying more attention to Ubuntu or whatever: the point is that using Debian unstable as a ‘reliable’ desktop system on power pc seemed quite hard. I don’t want to blame Debian developers: it’s unstable. No warranties. I used it at my own risk.

Since Debian is unsuitable for my present needs (no hassle, no config, no time), I considered switching Yellow Dog. I know that these days a PPC community mantained version of Ubuntu has been released.

I bought a Yellow Dog Enhanced account, since I did want to support their work and I was interested in support, if something was not perferct in the first place. Remember, no time.

I installed the distribution from the DVD. My hardware was entirely recognized correctly. From the soundcard to the backlit keyboard. My video card should also work with dual head, though I haven’t tried it yet. YD comes with a nice GUI to do this.

The only thing that was not working was the airport card. I just had to get the fwcutter and extract the firmware. Then it worked. Moreover, the network applet that stays in the notification area works great. I don’t know why, but in Debian and Ubuntu for some reasons it did not work properly (in Ubuntu from a certain moment the whole network-manager stopped working). I did not investigate as I needed less time to write a couple of shell scripts to configure the network interfaces when I needed to switch.

I have always been skeptical about rpm-based distros. Once I used SuSE, but after using Debian I got somewhat convinced of the superiority of the Debian packages. More accurate studies on rpm done recently seem to go in another direction: it was not that deb is better than rpm. It is just that deb repositories were maintained more carefully.

YellowDog repositories are maintained quite carefully. However, there is not a lot of software. I suppose something like 1000 packages (Debian has got ten times that). So I had to learn how to cook my own rpms or simply build software from sources and install it with make install. This is probably the major drawback. However, I’m pretty satisfied with Yellow Dog.

A few days ago, I switched to Yellow Dog for my powerbook.
I’m very satisfied with the hardware support. It’s the first distro
that supported my backlit keyboard from the beginning.

However, it lacks a lot of software packages. Most of them can be
taken from Fedora PPC (it’s advised to use those of Fedora Core 5
or). However, other must be compiled.

For example, I had to compile swi-prolog, since the software I’m working
on at the moment is written in Prolog. Swi Prolog itself was easy to install.
I compiled it and I had it working in a few minutes.

However, I was unable to compile XPCE. While I do not use the library itself,
I find it useful sometimes to use gtrace or the ‘graphic’ help.
The problem reported was that Xpm was not found. However, I installed
both libxpm and its development files. The ./configure script reported
that it was not able to link against libXpm.

I first tried manually linking and it worked, so I had a look at the log.
In fact it wasn’t libxpm fault. The test program tried to link both libxpm
and libxt, and the latter failed. Amazingly, the configure script did not
check for errors in linking libxt, so the erroro reported was totally
misleading.
The problem was that there was no libXt.so, but only libXt.so.6. I had to
manually create the symbolic link.

Eventually, I bumped into another error (this time during ‘make’).
The culprit was once again Xt: it seemed that some of its ’standard’ header
files were missing. I found a fedora 5 devel package that fixed that
and I was able to compile xpce.

Quite unfortunately, I can’t use it now. Another bug in the installation of
xorg conjures against me. This bug can be seen using a Tkinter canvas too.
The problem is that ‘names’ of colors are not found (probably because rgb.txt
is in the wrong place). Xpce fails and so does many stuff with Tkinter.

I don’t know where rgb.txt should be. I tried to put it in standard places,
but up to now the server does not find it. The problem is that I have to restart the server each time (and since sometimes this hangs the whole system, I have to reboot, and Red Hat derived distros have slow boots.)

Queste sono le FAQ del newsgroup italiano dedicato a C++.
Mi sono reso conto che in effetti non è facilissimo trovarle,
ache se contengono molte informazioni che risparmierebbero
domande banali sul newsgroup.

Per cui, nel caso, le linko.
Link.

Queste sono le FAQ del newsgroup italiano dedicato a C++.
Mi sono reso conto che in effetti non è facilissimo trovarle,
ache se contengono molte informazioni che risparmierebbero
domande banali sul newsgroup.

Per cui, nel caso, le linko.
Link.

An image is worth a thousand words.

It was a matter of mod-probing i2c-dev.
It is a custom Linux 2.6.20 Kernel on Debian Unstable. Cool!

It happens quite often that I use synaptic to manage packages on my debian.
However, sometime I save the markings in order to perform the installations another time.
For example I need to apt-get something quickly without waiting for the whole thing to be
downloaded and installed.

The standard procedure would be running synaptic again and then loading the markings.
However, in this cases I don’t feel like I need to start the whole synaptic thing.
I’d prefer a small command line utility that processes the saved markings.

I wrote one. It is very simple. It uses sudo, so every now and then it asks the password.
Of course one could do a better job, but I had not time to do something better.

#!/usr/bin/env ruby

args = $*
if args.size == 0
  puts "You should provide a file to process"
  exit 0
end

dict = Hash.new

File.open(args[0]) do |f|
  f.each_line do |line|
    key, action = *line.split
    dict[key] = action
  end
end

# sudo apt-get #{v} #{k}

dict.each do |k, v|
  exec(”sudo apt-get -y #{v} #{k}”) if fork.nil?
  Process.wait
end

What is a scripting language?

From Wikipedia we read that:

Scripting languages (commonly called scripting programming languages or script languages) are computer programming languages that are typically interpreted and can be typed directly from a keyboard. Thus, scripts are often distinguished from programs, because programs are converted permanently into binary executable files (i.e., zeros and ones) before they are run. Scripts remain in their original form and are interpreted command-by-command each time they are run. Scripts were created to shorten the traditional edit-compile-link-run process.

Of course any self respecting computer scientist knows that definition is meaningless, because a language is a mathematical construct
and is not tied to its implementation. You can write a C interpreter, for example (and there are some). You can also write a compiler for any ‘interpreted language’ (of course the term ‘interpreted language is also meaningless). And there are theoretical constructs (Futamura projections) that given any interpreter are able to build a compiler from it (you could implement them even in practice, though it would be terribly inefficient).

However, any other definition would be misleading as well: if you define a scripting language as a language you can use to “script” (as in “bash script”), then you’ve got definition that’s even more stupid. bash is a scripting language, and so it is Python. However, if someone writes an application that is scripted in C, C becomes a ’scripting language’).

Both definitions have an additional problem: scripting languages are considered somewhat inferior to ‘non-scripting languages’. Some even use the term ‘true programming languages’ (and this ‘true programming languages’ are usually considered to be C and C++, for example).

Lisp, Haskell, OCaml, Prolog

In this dissertation on ’scripting languages’, Lisp is quite emblematic. Lisp can be compiled (there are some Lisp compilers around). But Lisp can also be interpreted. This is one of the most
widespread Lisp environments (and it is an interpreter). Moreover, in Emacs you can just run some Lisp snippets. And Emacs itself is scripted in Lisp (thus Lisp would be a scripting language according to the second definition). However, no one can assert that it is not a ‘true’ programming language. Emacs itself is a beautiful (and complex) piece of software, and a lot of ‘real’ (and extremely difficult) stuff in the AI field has been written in Lisp.

Haskell can be another example. Hugs is an interpreter, ghc is both an interpreter and a compiler. And Haskell is even statically typed (so you see, being dynamic is
not necessary ). The very same applies for OCaml or Prolog. And all this
languages have been used by the most theory-oriented computer scientist to
implement real programs.

I suppose nobody would say that Lisp or Haskell are ’scripting languages’ (even if according to the definitions they are — Haskell is used in many configuration tools by Linspire programmers).

Bash, Perl, Python, Ruby.

All this languages have been labeled as ’scripting languages’. And in fact according to definitions, they are. However, they are very different languages.

Bash is a very simple language designed to do simple things. Unix system administrators used it intensively (along with awk and sed and other utilities) to automate many repetitive tasks. Although this is surely ‘programming’, in some sense it’s different from programming an application from scratch. Some even consider it a ‘lower level’ kind of programming (and surely we must recognize that skills involved in writing a boot script are different from skills used to write a compiler)

Perl was born in this environment: its goal was textual manipulations and interactions between processes in a system. It is a nicer alternative to bash + awk in many situations. Later it has been added a fully fledged object model, but in the while it has been used to write very complex applications that go outside the ‘lower level programming domain’ that is usually associated with ’scripting’. Even though I don’t like Perl anymore, it is a general purpose language, with the same dignity of C or C++.

The ’scripting language’ monicker is not fitting anymore. And it is even less fitting for Python. Python has been an object oriented programming language from the beginning. Good software engineering practices have always been employed. However, many consider it just another scripting language. And of course Python makes a great scripting language.

The domains in which Python excels are the same in which Java is used, for example. However, Python can be used for scripting, too. That is to say… some (and I’d be tempted to say ‘most’ ) ’scripting languages’ can be used both as general purpose languages and automation/scripting.

The reason why they can be used for automation/scripting and that they are easier to use and we can write programs faster. The development cycle is faster, too. And to me, they all seem good properties.

I think that the very same features that make Python (or Ruby) great for scripting, make it even greater for general purpose programming. That is to say we should consider a ’scripting language’ not a poorer language, but a better one (yeah, of course this is exaggerated, since there are languages suited for scripting that are not suited for general purpose programming — AppleScript and bash, for example).

I usually call one single emacs server (I’ve got (server-start) at the very beginning of my .emacs), then connect to it with some emacsclient.

Unfortunately enough emacsclient just quits if there is no active emacs server.

I need a process that tries to run emacsclient: if there is no active server, it runs emacs.
Moreover, emacsclient has a -n switch that makes it return ASAP, so the terminal is available for more commands.
emacs has not such a switch, but that behaviour is the one I want.

So I decided to write a small ruby script that does just this:

1. Tries to run emacsclient with the -n option.
2. If it succeeds, we are done. Otherwise we run Emacs doing some
   standard posix process manipulation in order to return to the shell as soon as possible.

This is the script:

#!/usr/bin/env ruby

fork do
  exec('emacsclient', '-n', *$*)
end
Process.wait
if $?.exitstatus != 0
  fork do
    Process.setsid
    Signal.trap('HUP', 'SIG_IGN')
    exec('emacs', *$*) if fork.nil?
    exit!(0)
  end
  Process.wait
end

Ubuntu discontinued?

Recently there are rumors that Ubuntu PPC will be discontinued.
In fact there is an IRC log about it:

Something asked a few times: Will PPC support be discontinued soon?
We will make a final decision on PPC for Feisty by the end of next week
if there is sufficient community contribution on this, then the community port can be just as good as a Canonical-supported one
we would keep the builds in place, but not block the release if things failed to build
so if people step up to unblock issues when they occur, then PPC would be on the same footing as it currently is
sabdfl, will “but ps3 is ppc” be a valid argument? (asked a few times as well)
the extra architecture costs us a lot in terms of testing bandwidth at release time, and figuring out issues like how to deal with the live CD are compicated
if SONY fund Ubuntu-on-PS3 then I guarantee it will happen

I have to say I’ve not been pleased about it. Of course Canonical should make its own interests: that is to say, if they feel that supporting PPC is not worth it, they are doing the right thing. However, it’s quite sad: there are a loto of perfectly functioning G3, G4 and G5 machines out there. Dropping support like this, seems to be the way commercial companies act.

The point is that we must realize that Canonical is a commercial company. You just can’t do anything about it and accept it.

Since at the moment I run Linux mostly on a PPC machine (my notebook), PPC support becomes a key factor in chosing the right distribution. My choice was obvious: I had been using Debian for ages before Ubuntu, why not going back to Debian? Welcome home, Debian!

Debian PPC

I downloaded the DVD iso for testing. Since I’m running on PPC, the new graphical installer is still experimental. Moreover, I quite feel at home with good old Debian textual installer.

Installation was really smooth. Debian recognised all my hardware with no need for manual intervention. Of course the airport card did not work without bcm43xx-fwcutter. Unfortunately enough, I left my working ethernet cable at the university, in the office I share with some fellow students. This was just a small delay.

Quite interesting Debian recognised my display better than Ubuntu (I still don’t know why, but I had to set the resolution manually or Ubuntu would not start X11). However, Debian did not preload pbbuttons (that are used for the notebook multimedia keys, volume, lcd backlight, etc).

In fact I think a noob prefers to find a system with no multimedia buttons and working graphics than vice-versa. It seems that the guys at Debian did a pretty good work. Nonetheless, I’m quite sad for the exclusion of pbbuttons: I did chose a macro-package (when installing) called ‘laptop’ or something like that. I think that pbbuttons should be included in the first DVD. In fact most PPC machine out there should be laptops (well, maybe not ‘most’, but surely a great number).

Everything else worked smoothly. I recompiled the kernel (I would like to have that backlit keyboard working, it should work even with the 2.6.18 default kernel, but maybe something useful was not compiled into it). The backlit keyboard still does not work, which is a pity, but is something I can live without. Beryl does not work too (but it didn’t work with Ubuntu, either). And it should work. But that is another thing I can happily live without.

I recently bought the Ruby Cookbook. I bought the italian version (whose title is ‘Ruby Cookbook con elementi di Rails’ which roughly translates to ‘Ruby Cookbook with elements of Rails’). However, the book itself is not different.

Although I prefer to read technical books in English, I often buy books in Italian in order to show the publisher interest on that particular technology. In fact, in a country where most people avoid buying book in English because they feel they are ‘too’ difficult (like in Italy), good technologies do not spread if there are no good books in the local language.

The first impression with the book has been terribly negative. Actually if instead of buying the book online, I found it in a shop and leafed through it, I suppose I would have put it down.

Strings in Ruby are much like strings in other dynamic languages like Perl, Python
and PHP. They’re not too much different from strings in Java and C. Ruby strings are dynamic, mutable, and flexible.

In this paragraph you learn that “Ruby strings are dynamic, mutable, and flexible.” And that is true. However, you get another impression: the authors do not know what they are talking about.

They say that Ruby strings are ‘much like’ the strings in Perl. This is almost true (well, Perl unicode support is much better than Ruby, and Perl deals natively with unicode strings. However, saying that Ruby strings are like Python strings is plainly wrong: Python strings are immutable and are somewhat more akin to Ruby symbols (in fact if you call intern on a Python string you get something semantically very similar to a Ruby symbol). Moreover, Python deals with unicode natively.

Again, the comparison with Java strings is plainly wrong: in Java strings are immutable. The comparison with C is terrible: in C, strings are not even a primitive data type.

As I said before, at this point I was tempted to put the book on a shelf and never open it again. Luckily enough I went on and soon enough I found out I bought one of the best books on Ruby available.

The impression that the authors are not competent (or at least they speak of something they do not know) is plainly wrong. A few chapters later, there are some chapters that quite accurately confront Ruby pragmatic with Python one. They are poignant and precise: definitely the authors know both languages quite well. I suppose the ‘bad’ paragraph at the beginning was a tentative to be didactical.

The book in fact is quite didactical. You can read it with almost no previous knowledge of Ruby. The reader is guided through Ruby syntactical conventions (for example when dealing with strings, you learn that parentheses are optional, which is known to everybody who coded a bit in Ruby).

In the later chapters (most notably the ones on modules and objects), the reader learns the nature of Ruby power, and how to reason and develop in order to unleash that power. This book is a cookbook, but every single receipt does more than teaching a way to achieve its goal: it teaches something about the way Ruby programmers should think and code *in general*. In fact you can consider this cookbook a ‘beginner’ book that teaches by examples (and that is a very effective way in a language such as Ruby). Of course, there is also plenty of intermediate and advanced stuff, or subjects not covered elsewhere (for example the ones about image manipulation).

This is a precious book and the ideal companion for everyone who’s seriously motivated in learning Ruby. But it is also a book that a Ruby programmer may want to keep on her desk to find out how to do things without reinventing the wheel.

Introduction

Ruby is the new boy in town. Until a couple of years ago, nobody really
spoke about Ruby. It was really popular in Japan, but outside it was just
one of the many ’scripting’ languages that the open source world has
developed over the years.

The big names were using Python or Perl. Well, most of them were using PHP,
but in fact this does not matter: while Perl, Python and Ruby are excellent
languages (even if it is almost impossible someone really likes both Perl
and Python, nonetheless Perl has its merits), PHP plainly sucks.
And then of course
there was that Java everybody was talking about and C# (but the open source
guys usually said positive things about it only if in the same sentence
the word ‘mono’ occurred).

In the last few years Rails changed things. Now a lot of people are talking
about Ruby and dynamic languages. A lot of Java developers discovered the
power of dynamic languages and dynamic typing, after years spent saying
that the only saviour was static typing. In fact it seems to me that there
is kind of a revolution in the IT world.

Python and Ruby and Lisp and …

Rails is a pretty good framework. The documentation is acceptable even for
those who grew up with Sun’s bloated documentation (I still prefer to read
the code if the language itself is readable enough).

Ruby is a really nice language. In fact you can see it as a (Perl–)++.
It kept almost all nice features from Perl, and dropped some of the worse.
Of course a Perl Monger would disagree, but I’m a pythonist after all.

One of the most interesting things, in my opinion, is that Ruby and Python
are quite similar (even if they start from different points of view). I feel
quite comfortable with both languages, and even their pragmatic is not
really different. Moreover differences tend to depend on different
syntax, rather than on different semantics.

For example in Ruby is quite frequent to ‘open’ classes and add methods.
This is something you can do in Python, even if there isn’t a special
syntax.

>> class A(object): pass
  >> a = A()
  >> a.foo()
  Traceback (most recent call last)
  ...
  <type 'exceptions.AttributeError'>: 'A' object has no attribute 'foo'
  >> def ext_foo(self): print 'foo'
  >> A.foo = ext_foo
  >> a.foo()
  foo

Of course this is far less elegant, and that’s way it’s something less
frequently done in Python.

Ruby has another ‘advantage’ over Python. It’s syntax is less rigid,
and in fact the most typical thing that is in Ruby pragmatic is to
write a DSL in the language itself and program in that DSL.

There are a lot of examples of this strategy in Rails itself. However, this
approach is not new at all. Lisp programmers have been using it since the
beginning, that is to say it’s almost forty years they code DLS in Lisp and
use them to write the application.

Duck typing vs. duck hyping.

Unfortunately I hear people saying quite often that ‘Ruby invented duck typing’. People that just
discovered Ruby, seem quite certain about it. Some of them even told me that
in Python you ‘were not really duck typing’ and that it was something
peculiar to Ruby. But let’s look at the definition (from Wikipedia):

Duck typing is a form of dynamic typing in which a variable’s value itself implicitly determines what the variable can do. This implies that an object is interchangeable with any other object that implements the same interface, regardless of whether the objects have a related inheritance hierarchy. Duck typing is a feature of programming languages such as Smalltalk, Python, Ruby, and ColdFusion.

Of course this is something that you can do in Python. And you can also do it in Objective C, by the way. And in Python it is something plainly obvious, too. Everybody does it, everybody likes it. But nobody thought about using a fancy name when describing the practice in books and blogs.

Amazingly, the term ‘duck typing’ (that some think it’s a Ruby peculiar feature) was probably used for the first time by Alex Martelli when speaking about Python typing system. It was Jul 26 2000, and the english language Ruby newsgroup had been active since the first days of may. There was a mailing list of course, but nonetheless Ruby was relatively unknown outside Japan.

In other words, don’t check whether it IS-a duck: check
whether it QUACKS-like-a duck, WALKS-like-a duck,
etc, etc, depending on exactly what subset of duck-like
behaviour you need to play your language-games with. If
the argument fails this specific-ducklyhood-subset-test, then
you can shrug, ask “why a duck?” (at least, you can if you’re
a Marx Brothers fan and have memorized “Cocoanuts”‘ script;
Monty Python one-true-wayists will have to find their own
simile here), and move on to the next set of tests (why-a-no-
chicken immediately comes to mind, but then one would have
to ask why it crosses the road, so I think we’d better snip it).

Alex’s original post

That is the reason why I say that Ruby supports ‘duck hyping’. Ruby is a very good language. I suppose that if I learnt Ruby before Python, I’d probably like Ruby more than Python (because the languages are quite equivalent, it’s my head that now works in a somewhat more pythonic way). However, there are a lot of people that are really *good* at selling Ruby. An excellent publisher based his early success on Ruby books, the creator of Rails has lots of marketing skills, and so on.

However, I was wondering: why Ruby and not Python? I don’t believe in fortune. To discover the answer (that in this particular case I guarantee it’ s not 42) we must analyze in which ways syntactical features of Ruby (since semantically they are quite interchangeable) influence the language pragmatic, and in which ways the pragmatic contributed to build Ruby success.

And when we are into pragmatic, we are not in the world of the compiler: we are in the world of the programmers. That is to say: we must understand why Ruby has appeal even where Python has not. We must understand in which way the language influenced the way of thinking of so many people, and why Python did not.

In Python Metaclasses are considered an advanced and difficult to use technique. This is certainly true. Developers of ‘production code’ are often discouraged to use metaclasses, since code that makes use of metaclasses is often overly complex (especially for people who are not used to metaclasses).

A further reason to avoid metaclasses is that they truly can be avoided. They do not add much power to Python. However, there are cases when they make ‘client’ code more readable.

Consider this situation: we have a finite set of strings that are used as dictionary keys in several parts of our application. Of course, we don’t want to use explicit strings in every point where they are needed. This is too error prone and bugs are more difficult to track.

A good solution is to put all the strings in a module. We will have code such as

  FOO1 = 'foo1'
  FOO2 = 'foo2'

Good. However, we may want to loop over the constants. One of the more pythonic solutions is this one:

targets = {
    ‘SEARCH‘        : ‘search‘    ,
    ‘INFO‘          : ‘info‘      ,
    ‘VARIANTS‘      : ‘variants‘  ,
    ‘DEPS‘          : ‘deps‘      ,
    ‘DEPENDENTS‘    : ‘dependents‘,
    ‘INSTALL‘       : ‘install‘   ,
    ‘UNINSTALL‘     : ‘uninstall‘ ,
    ‘ACTIVATE‘      : ‘activate‘  ,
    ‘DEACTIVATE‘    : ‘deactivate‘,
    ‘INSTALLED‘     : ‘installed‘ ,
    ‘LOCATION‘      : ‘location‘  ,
    ‘CONTENTS‘      : ‘contents‘  ,
    ‘PROVIDES‘      : ‘provides‘  ,
    ‘SYNC‘          : ‘sync‘      ,
    ‘OUTDATED‘      : ‘outdated‘  ,
    ‘UPGRADE‘       : ‘upgrade‘   ,
    ‘CLEAN‘         : ‘clean‘     ,
    ‘ECHO‘          : ‘echo‘      ,
    ‘LIST‘          : ‘list‘      ,
    ‘VERSION‘       : ‘version‘   ,
    ‘SELFUPDATE‘    : ‘selfupdate‘,
    ‘HELP‘          : ‘help‘
}

locals().update(targets)

In this way we can do whatever we want. However, we could use a class instead of a module. We simply define the constants as class variables. Then we can easily use the locals built-in to create the array of constants. But with a little metaclass trick, we can write more interesting client code.

We could for example write things like:

        for k in PackageKey:
            # do something

or

        if key in PackageKey:
            return self.foo(key)

We can use metaclasses to define a class object that behaves in the way above.

class _ConstantNamespace(type):
    def __iter__(cls):
        for v in cls.keys:
            yield v

class PackageKey(object):
    __metaclass__ = _ConstantNamespace

    NAME                   = ‘name‘
    VERSION                = ‘version‘
    REVISION               = ‘revision‘
    DIRECTORY              = ‘directory‘
    VARIANTS               = ‘variants‘
    HOMEPAGE               = ‘homepage‘
    DESCRIPTION            = ‘description‘
    BUILD_DEPENDENCIES     = ‘build_dependencies‘
    LIBRARY_DEPENDENCIES   = ‘library_dependencies‘
    RUNTIME_DEPENDENCIES   = ‘runtime_dependencies‘
    PLATFORMS              = ‘platforms‘
    MAINTAINERS            = ‘maintainers‘
    keys = [ locals()[key] for key in locals().keys()
             if key.upper() == key and (key.isalpha() or key.endswith(‘_DEPENDENCIES‘))]

Although some tips are clearly wrong (e.g. having wrong permissions causes problems, it may even prevent some applications from working, but clearly has no impact on performance), most of them are useful and interesting.

Link

Concurrency in Java is complex to use and expensive in computational resources. Because of these difficulties, Java-taught programmers conclude that concurrency is a fundamentally complex and expensive concept. Program specifications are designed around the difficulties, often in a contorted way. Biut these difficulties are not fundamental at all. There are forms of concurrency that are quite useful and yet as easy to program as sequential programs (e.g., stream programming as exemplified by Unix pipes). Furthermore, it is possible to implement threads, the basic unit of concurrency, almost as cheaply as procedure calls. If the programmer were taught about concurrency in the correct way, then he or she would be able to specify for and program in system without concurrency restrictions (including improved versions of Java). (Concepts, Techniques and Models of Computer Programming, Peter Van Roy and Seif Haridi)

First of all, I completely agree with the authors. I like learning new languages/paradigms/models and find quite restricting sticking to just One Language, One Platform, One Model. I’m fond of Python (but indeed Python is an excellent imperative/object oriented language that allows functional programming — and logic programming is experimented among other things in pypy). I also like Ruby (again Imperative with functional capabilities). I recently discovered the power of Prolog, and I love Haskell (although I never wrote any substantial piece of software in Haskell).

I can’t imagine working with Java and only with Java (and the same applies to ‘C++ and only C++’ or whatever). However, there is plenty of programmers out there that chose One Language, One Platform, One Model and stick with it. I’m wondering if we can generalize Dijkstra statement

The use of COBOL cripples the mind; its teaching should, therefore, be regarded as a criminal offence.

In fact it seems that Java has the very same problem. A lot of Java programmers are only able to formulate problems (and solve them) thinking in Java. One may argue that maybe business programmers already had their mind crippled, but I don’t think this is the case.

I’m afraid to say the problem is not limited to Java, of course (it’s just more evident because there a lot of Java programmers). There are a lot of excellent C++ (for example) programmers that simply do not believe that large programs written in dynamically typed languages can work (and of course they are wrong, since we can exhibit such programs). On the other hand some Python/Ruby/etc advocates think that static typing is fundamentally bad. In fact it is not: Java type-system is poorly designed. It’s not that static typing is wrong or clumsy. Haskell and OCaml are statically typed, but types do not get in the way: they are a concrete help for the programmer (but this does not imply that a language should be statically typed).

My opinion is that more programming languages, models, paradigms should be taught to programmers. For two main reasons: first, they know more ways to solve a problem and hopefully they will be able to choose the best one; second, they will be able to adapt concepts coming from other models/paradigms/languages to the language they are currently using, thus making the design more elegant.

Elegance is not a dispensable luxury but a quality that decides between success and failure. (Dijkstra)

This article won’t be very interesting for people living in an English speaking country: most technology books are written in (or at least translated to) English. However, things change if you do live in a country where English is not the main language (like Italy) and most people can’t read English comfortably (again, like Italy).

A lot of people working in the IT field here find it more difficult to read in English than in Italian, and they choose books translated in Italian, if they are available.

I prefer English books: they usually cost less and there are no translation errors (by definition). Moreover, there are less errors in general, since more people read the book (and thus has the opportunity to find and report errors). Famous hackers and scientists from all the world usually speak English (and deliver lectures in English): they also tend to write books in English (even if it is not their main language).

Moreover, there are subjects where the translated books (for example Python books in Italy) are *not* the ‘best’ books on the subject. For example in Italy you can buy ‘Programmare in Python’ (that is the translation of Learning Python) or the *very* old ‘Python 2.1 Tutto ed oltre’ (that refers to Python 2.1 and is still being sold). Python in a Nutshell (whose author *is* Italian) is not available, and the list of ‘missing’ titles is much longer.

In a country like Italy, availability of books on a particular technology can be one of the main reasons why that technology is adopted. In fact a lot of Microsoft books (or books on Microsoft products) are translated (or even written from scratch in Italian by Italians). Another language that fills whole bookcases in our bookshops is Java. PHP has a lot of beginners books, too.

In my opinion none of the aforementioned programming environments excels. Java has a beautiful library (although terribly over-engineered) and a very promising VM, but the language itself sucks. PHP has a horrible library, a terrible Virtual Machine and the language itself sucks even more. .Net has a wonderful VM (but unfortunately not cross-platform — a part from Mono), but C# is not better than Java, and VB… luckily enough you can run a recent Python version in the .Net environment, but again, you don’t find a lot (if any) of information about this in Italian books.

Every time a new programmer goes to a bookshop to buy a book to start learning programming, he is very likely to find a book on Java/MS/PHP. And until he ‘grows’ up, and learns to look for pieces of information in other places, he will be bound to those technologies. In fact she could have learned sooner (and having more fun) if she discovered Rails (for Web development) or Python. There *are* some books on those subjects (and a whole free book — but in English — on Django (a Python Rails-like framework), however, they are a few, and someone who starts looks for ‘big names’.

I’s a couple of day I’m hacking with xmodmap and keycodes to make my keyboard behave as I expect.
Recently it sprang to my mind that with SuSE 7.1 I used a utility called xkeycaps.

Unfortunately enough xkeycaps generates an .Xmodmap with keycodes expressed as hex numbers, while xev shows code as decimal numbers

This simple ruby oneliner converts an .Xmodmap file with hex codes to one with decimal codes

cat .Xmodmap.hex |
ruby -n -e "if $_ =~ /keycode\s*(0x[A-F0-9][A-F0-9])\s*=\s*(.+?)\n/; puts \”keycode #{$1.hex} = #{$2} \” else puts $_ end”>
.Xmodmap.dec

provided you called the hex .Xmodmap ‘.Xmodmap.hex’.

Suppose we have an XML parser that converts an XML file into a Prolog term.
We may (quite) easily build one with DCG. I will be doing one soon, for values of ’soon’ that depend on the status of my thesis.
We describe the way the prolog term is built:

Text is simply a prolog term. In a less naive implementation we may want to use the string datatype. However, to show the power of a declarative approach, things would not change a lot. Moreover, if we are using swi-prolog (a widespread open source implementation) internally itis able to use UCS (that is a superset of 16 bit Unicode). We only have to make the parser smart enough to convert entities in the right Unicode character and the whole thing will behave correctly

Attributes are represented as key:value terms, where : is a binary infix functor. Again, this is quite a natural representation.

A tag is represented like an tag(Attributes, Children) term, where term is the name of the tag, andl Attributes and Children are (possibly empty) lists of attributes and ‘children’. This representation is not very clever. In fact you can have more optimized programs representing tags like element(tag, Attributes, Children). That is the way things are done in SWI-Prolog official SGML/XML parser library, but this is a simple example.
A ‘child’ is either a tag or a text section.

This (informal) description can be translated in a straightforward manner in a prolog program. The last thing before presenting the source is an example term representing a very simple XHTML file.

html([], [head([], ['']), body([], [p([], ['ciao ciao', img([src:'ciao.jpg'], [])]) ])])

And now the (81 lines long) prolog source code. You can call it with pp_tag(Term), where Term is the term representing the XML file.

pp_tag(Tag) :-
	!,
	pp_tag(Tag, 0).

pp_tag(Tag, N) :-
	Tag =.. [Tag_Name, Attributes, []],
	!,
	s(N),
	write(’<'),
	write(Tag_Name),
	pp_attributes(Attributes),
	write(' />‘).
pp_tag(Tag, N) :-
	Tag =.. [Tag_Name, Attributes, Children],
	!,
	s(N),
	write(’<'),
	write(Tag_Name),
	pp_attributes(Attributes),
	write('>‘),
	N1 is N+1,
	pp_children(Children, N1),
	nl,
	tab(N),
	write(’‘).

pp_text(Text, N) :-
	name(Text, Chars),
	pp_lines(Chars, N).

pp_line(Line, N) :-
	name(Atom_Line, Line),
	s(N),
	write(Atom_Line).
pp_lines(Lines, N) :-
	((append(Line, [10|Rest], Lines), !),
	    pp_line(Line, N),
	    pp_lines(Rest, N)
	;
	    Line = Lines,
	    pp_line(Line, N)
	).

pp_children([], _N) :-
	!.
pp_children([X|Xs], N) :-
	!,
	pp_child(X, N),
	pp_children(Xs, N).

pp_child(Child, N) :-
	pp_tag(Child, N)
	;
	pp_text(Child, N).

pp_attribute(Name:Value) :-
	!,
	write(Name),
	write(’='),
	pp_quoted(Value).

pp_attributes([]) :-
	!.
pp_attributes([X|Xs]) :-
	write(’ ‘),
	pp_attribute(X),
	pp_attributes(Xs).

pp_quoted(Term) :-
	!,
	write(’”‘),
	write(Term),
	write(’”‘).

s(0) :-
	!.
s(N) :-
	nl,
	tab(N).

Of course this is a ‘toy’ implementation. You find the real thing here.

How much I love windowmaker…
Now it is much less used than once… Most people do use KDE or GNOME (or XFCE) and the good old Window Managers are kind of forgotten (or maybe simply unknown to the masses). However, when I started KDE was slow and took every single byte of RAM from my machine. GNOME was somewhat lighter. However, the desktop environment was not polished and practical (it wasn’t even the 2.0).

In fact some window managers/desktop environment had higher usability (at least in my opinion) even though you had to renounce to a good file-manager (and back than gmc/nautilus was not as good as today).One of those is WindowMaker.

Simple and powerful. As it is today. Well… I restored it on my Ubuntu. Without the debian menu you have to build the application menu yourself (and that is a pain in the ass). However, since most of the times I’m only using firefox, emacs and a terminal, I managed to do it in a very short time.

A couple of days ago it arrived my own copy of “Compilers: Principles, Techniques & Tool” by Aho, Lam, Sethi and Ullman, better known as the “Dragonbook” (look at the cover to understand why). This weekend I am starting reading the 992 page long book. Actually I find it well written and very clear, even though I’m at the beginning of the book.

I suspect things will get more complicated while proceeding further. However, I find the subject dramatically interesting. I hope to find enough time to read it quickly and eventually start implementing something. Some ideas contained in the book I suppose will be of great help for my thesis (in fact I’m implementing something that is closely related to a compiler).

Easy…

;; mouse-wheel: scroll
(global-set-key [mouse-4] ’scroll-down)
(global-set-key [mouse-5] ’scroll-up)

I found a lot of posts about this, but none worked for me. I just took some pieces of information here and there and I came up with this (that works for me).

Emacs 21.4 on Ubuntu PPC.

Today, while checking my gmail account I read an ad about Servoy being an alternative to Ruby and Rails

Actually, I wanted to check out what was that. I thought about some crappy PHP framework that pretended to do what Rails just cloning its structure, but without Ruby power

In the homepage the first thing you learn about Servoy is that Ruby syntax is complex and that Rails has limited capabilities. Further analisys makes me think it’s a Java based environment scripted in Javascript. Basically they are asserting that Javascript syntax is clearer than Ruby one (which is debatable) and that a RAD like thing built on Java is less limited than Rails. Note that Servoy is not Java: it is something built on Java (so I don’t expect it to be as powerful as Java, or it would be as complex as well).
I’m not against RAD or ‘easy’ environments. I just find ridiculous when they say that Rails is limited (that is false) and that a closed component system is more complete.

Moreover, I don’t know anyone using this Servoy. I haven’t read about it on tech magazines, my fellow developers haven’t heard about it either. My opinion is that it’s a small environment tool that uses Rails popularity (as a comparison) to convince people to pay them for something they could have done easier in Rails.

The same conclusions have been made by this blogger

This is are some (simple) exercises in Prolog using difference lists.
They should be correct, but I have to say I’m a beginning Prolog programmer… so…

inorder_dl(tree(X, L, R), Xs-Ys) :-
	inorder_dl(L, Xs-[X|Zs]),
	inorder_dl(R, Zs-Ys).
inorder_dl(void, Xs-Xs).

preorder_dl(tree(X, L, R), [X|Xs]-Ys) :-
	preorder_dl(L, Xs-Zs),
	preorder_dl(R, Zs-Ys).
preorder_dl(void, Xs-Xs).

postorder_dl(tree(X, L, R), Xs-Zs) :-
	postorder_dl(R, Ys-[X|Zs]),
	postorder_dl(L, Xs-Ys).
postorder_dl(void, Xs-Xs).