I'd bet it's not just about multicore scaling and general efficiency,
but also the suitability of the language itself for large, complex
projects. It's just not possible to be everything for everybody.
Python is beginner-friendly, has a very fast learning curve for
experienced programmers in other languages, and is highly productive
for throwing small and medium sized scripts together, that are
debugged through iterated testing. One might say it's optimized for
those purposes. I use it all the time because a lot of my programming
fits the pattern. The car analogy is the no-frills electric commuter
car, just hop in and aim it where you want to go; if you crash it,
brush yourself off and restart. But there are times (large production
applications) when you really want the Airbus A380 with the 100's of
automatic monitoring systems and checkout procedures to follow before
you take off, even if the skill level needed to use it is much higher
than the commuter car.
OK. The quoted link deals with Unladen Swallow, which is an attempt to deal with the
very real performance limitations of current Python systems. The remarks above deal with
productivity scalability, which is a totally different matter. So...
People can and do write large programs in Python, not just `throwing...medium sized
scripts together'. Unlike, say, Javascript, it has the necessary machinery to build very
large programs that are highly maintainable. One can reasonably compare it with Java, C#,
and Smalltalk; the facilities are comparable, and all of those (as well as Python) are
used for building enterprise systems.
I believe that the A380's control software is largely written in Ada, which is a
perfectly fine programming language that I would prefer not to write code in. For
approximately 10 years, US DOD pretty much required the use of Ada in military (and
aerospace) software (though a a couple of years ago I discovered that there is still
one remaining source of Jovial compilers that still sells to DOD). According to a
presentation by Lt. Colonel J. A. Hamilton, `Programming Language Policy in the DOD:
After The Ada Mandate', given in 1999, `We are unlikely to see a return of a programming
language mandate' (
www.drew-hamilton.com/stc99/stcAda_99.pdf). As I understand it,
the removal of the Ada mandate came from the realization (20 years after many computer
scientists *told* DOD this) that software engineering processes contribute more to
reliability than do programming language structures (c.f. Fred Brooks, `No Silver
Bullet').
So: to sum up, there are lots of large systems where Python might be totally appropriate,
especially if complemented with processes that feature careful specification and strong
automated testing. There are some large systems where Python would definitely NOT be
the language of choice, or even usable at all, because different engineering processes
were in place.
From a productivity viewpoint, there is no data to say that Python is more, less, or equally
scalable than <Language X> in that it produces correctly-tested, highly-maintainable programs
at a lower, higher, or equal cost. I would appreciate it if people who wanted to comment on
Python's scalability or lack thereof would give another programming language that they would
compare it with.
-- v
