On Fri, Jun 4, 2010 at 6:26 PM, Tino Dai <obe...@gmail.com> wrote: > > LOL, it's actually on the list of things to do. And hear that one will become > a > better programmer once they learn LISP. >
I most certainly did. There are very few languages as conceptually pure as this one. If you ever get it on the top of your list, check out these links. [1] is the venerable book "structure and interpretation of computer programs," commonly regarded as one of the best introductory programming books ever written. It teaches scheme. [2] is a set of excellent lectures of said book, by its writers. They are very good teachers. [1] http://mitpress.mit.edu/sicp/ [2] http://groups.csail.mit.edu/mac/classes/6.001/abelson-sussman-lectures/ > > I am always fighting the battle - more compact vs more readable :) . A couple > of > questions that I have: Why generators over map? Is it somehow more efficient > under the covers or is it for readability purposes? I noticed that you > took out the > lambda function too (not much good without a map/filter/reduce) to replace > with the generator function. Also could you give me some instances > where a generator > would be used in a real situation? I have already read the stuff on > doc.python.org about > generators. > generator expressions have essentially the same performance, but are less memory hungry, since the results do not have to be kept into memory. There is a function called imap in the itertools module that has that same benefit though, so it's not inherent to map at all. Think of the list comprehension as a more readable/concise alternative to map and filter, while generator expressions correspond to the imap/ifilter functions. Readability is the key issue here. The generator expression doesn't need a function, so the use of the lambda keyword is avoided, making it a lot shorter and easier on the eyes. It also reads more naturally. generator expressions are basically just a shortcut to generators though, which are even more powerful. Take, for example, a simple generator that yields the fibonacci sequence: def fib(): a = b = 1 while True: yield a a, b = b, a + b >>> fib() <generator object at 0x014B35F8> >>> it = fib() >>> for i in range(10): print it.next(), 1 1 2 3 5 8 13 21 34 55 >>> It's both more efficient and clearer than a function that simply calculates a list and returns the results. Plus it can actually go on infinitely, and you just take as many results from it as you need (also look at itertools for that, particularly takewhile). In practice it's used mostly for writing __iter__ methods, which is vastly simpler than a separate iterator class with the next method and everything. Just write __iter__ as a generator that yields your sequence, and you're done. Hugo _______________________________________________ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: http://mail.python.org/mailman/listinfo/tutor
