On Fri, 16 Nov 2007 11:24:24 +0100, Hrvoje Niksic wrote: > Steven D'Aprano <[EMAIL PROTECTED]> writes: > >>> Can you post minimal code that exhibits this behavior on Python 2.5.1? >>> The OP posted a lot of different versions, most of which worked just >>> fine for most people. >> >> Who were testing it on single-CPU, 32 bit systems. > > Still, I'd like to see a test case that fails (works slowly) for you, so > that I (and others) can try it on different machines. As I said, the OP > posted several versions of his code, and tended to depend on a specific > dataset. A minimal test case would help more people debug it.
http://groups.google.com.au/group/comp.lang.python/msg/b33ceaf01db10a86 #!/usr/bin/python """Read a big file into a dict.""" import gc import time print "Starting at %s" % time.asctime() flag = gc.isenabled() gc.disable() id2name = {} for n, line in enumerate(open('id2name.txt', 'r')): if n % 1000000 == 0: # Give feedback. print "Line %d" % n id,name = line.strip().split(':', 1) id = long(id) id2name[id] = name print "Items in dict:", len(id2name) print "Completed import at %s" % time.asctime() print "Starting to delete dict..." del id2name print "Completed deletion at %s" % time.asctime() if flag: gc.enable() print "Finishing at %s" % time.asctime() I've since tried variants where the dict keys were kept as strings, and it made no difference to the speed, and where the data was kept as a list of (key, value) tuples, which made a HUGE difference. You should also read this post here: http://groups.google.com.au/group/comp.lang.python/msg/2535dc213bc45f84 showing Perl running very fast on the same machine that Python was running like a one-legged sloth. -- Steven. -- http://mail.python.org/mailman/listinfo/python-list
