Programming language productivity

malv malvert at telenet.be
Fri May 19 11:21:39 CEST 2006


John Bokma wrote:
> Connelly Barnes <connellybarnes at yahoo.com> wrote:
>
> > http://barnesc.blogspot.com/2006/05/programming-language-productivity.h
> > tml
>
> C:    3 hours to write the program, 5 hours to track down the memory leaks
> Java: 4 hours to write the program, 6 hours to get all the exception
>       handling right
> C++   5 hours to write the program after reading Stroustrup for 6 hours
>
> Just kidding, of course.
>
> Also note that Python programmers write more lines/hour which they need to
> finish in the same time as Perl programmers :-D.
>
> --
> John                               MexIT: http://johnbokma.com/mexit/
>                            personal page:       http://johnbokma.com/
>         Experienced programmer available:     http://castleamber.com/
>             Happy Customers: http://castleamber.com/testimonials.html
I am not shure whether your criterion is very valid. OK if you have to
write only one compact piece of code like in your example. Sometimes I
think that most python users fall within this category.

Once you get involved in larger projects, the dynamic nature of the
programming tool becomes much more important. I mean by this, the
ability to stop running code, modify or add to it and continue without
having to re-establish the state of the program. This may sound trivial
to many, but in major applications setting up the state again can take
a considerable processing time. Such feature should be available from
within the debugging tools.

In fact, languages like Smalltalk, Lisp and even VB offer this
possibility.
Ruby coming up strongly these days also has this dynamic reload
capability.
To sum up, I like Python very much but I don't understand how come this
basic flaw has not been taken care of. It is sufficient to search for
"reload" to see how many people have struggled with it over the years.
I hate the idea of having to take up Ruby to really find out how it
could serve me better in this most critical productivity area.




More information about the Python-list mailing list