3 ms·

Well, I do not quite agree with your argument that Python is "always memory-hungry". As a matter of fact, writing "good" Python code is a very seldom observed a

by fnl 16y ago

Well, I do not quite agree with your argument that Python is "always memory-hungry". As a matter of fact, writing "good" Python code is a very seldom observed art and most performance issues can be gotten rid of if you know enough about the language and follow the style and design advices of true "Pythonistas", as the "gurus" there call themselves (and many more who do not deserve that title ;)). However, I have been programming several years in Java on an earlier assignment, where stuff got so clumsy I wrote a 6 page manual for my team outlining "don't do's" in Java because it would either cost tons of performance or memory, mostly related to very basic stuff such as instantiation strategies and everything that might be "good" for OOD, but bad for performance. We ended up writing most of the core of the system in Lisp and then generated the "light-weight" Java stuff from a DSL one of our Lisp "masters" had conjured, to avoid all the bloat you have to go through to write simple things such as walkers, etc. in Java. If I ever had real memory problems ever, I must say it was with JVM, and it took me months to, for example, come up with a solution to index a few TBs with Lucene and the JVM "crashing" (well, hanging) because of gc (although that was back more than five years now, so things will have gotten better, I admit). Nay, I must say the Python/C combo is much to my liking. I want something that fits into that picture, not so much an alternative. And there I currently see Erlang as quite promising combo to my two favorite languages, after going through all the advice and pointers everybody here gave me.

leif 16y ago
> As a matter of fact, writing "good" Python code is a very seldom observed art and most performance issues can be gotten rid of if you know enough about the language and follow the style and design advices of true "Pythonistas", as the "gurus" there call themselves (and many more who do not deserve that title ;)). First of all, should performant code in your language be "seldom observed" and require the knowledge of the "gurus"? I should hope not. I have written plenty of optimized python in my day, and it's always been a decent constant behind c or java, no matter how many of the "best practices" I follow. Pypy may be a different story, but their toolchain was too complex and slow last I looked. Most of python's best practices are language bugs, anyway. Generators are great, but most of the rest is crap. I should cache my namespace lookups outside the loop? Why can't you do that for me, Python? That's one of the simplest compiler optimizations we have. All the fastest Python is written in C extensions. Why do you think this is?
- fnl 16y ago
  As an update: Python 3k solves the namespace issue you mention. (And I hope more and more dev's will finally move on, I love it and only can say it is 100% worth the switch! I'll never again code in pre-3k if not forced to.) And no, I am not saying that Python outperforms Java, obviously. But it can provide very decent performance at very low LOCs. And then you can identify the bottlenecks and implement that part in C. Overall, a much faster approach than writing in Java (and, obviously, than writing in pure C) with final performance rates beating a JVM easily. EDIT: No, that is actually even too complicated than what I mostly need to do: For the real bottlenecks I usually just need to find the C library that solves that hard part (e.g., some number-crunching stuff I am doing) and already has a Python wrapper, or you generate one (hello SWIG), or, worst case, you really have to write one (yet have to find that case, although).

by fnl 16y ago

leif 16y ago

> As a matter of fact, writing "good" Python code is a very seldom observed art and most performance issues can be gotten rid of if you know enough about the language and follow the style and design advices of true "Pythonistas", as the "gurus" there call themselves (and many more who do not deserve that title ;)). First of all, should performant code in your language be "seldom observed" and require the knowledge of the "gurus"? I should hope not. I have written plenty of optimized python in my day, and it's always been a decent constant behind c or java, no matter how many of the "best practices" I follow. Pypy may be a different story, but their toolchain was too complex and slow last I looked. Most of python's best practices are language bugs, anyway. Generators are great, but most of the rest is crap. I should cache my namespace lookups outside the loop? Why can't you do that for me, Python? That's one of the simplest compiler optimizations we have. All the fastest Python is written in C extensions. Why do you think this is?

fnl 16y ago
As an update: Python 3k solves the namespace issue you mention. (And I hope more and more dev's will finally move on, I love it and only can say it is 100% worth the switch! I'll never again code in pre-3k if not forced to.) And no, I am not saying that Python outperforms Java, obviously. But it can provide very decent performance at very low LOCs. And then you can identify the bottlenecks and implement that part in C. Overall, a much faster approach than writing in Java (and, obviously, than writing in pure C) with final performance rates beating a JVM easily. EDIT: No, that is actually even too complicated than what I mostly need to do: For the real bottlenecks I usually just need to find the C library that solves that hard part (e.g., some number-crunching stuff I am doing) and already has a Python wrapper, or you generate one (hello SWIG), or, worst case, you really have to write one (yet have to find that case, although).