Newly-relaxed limits on random.randrange(). Also added some info about

Karatsuba's better cache behavior with extremely large multiplicands.
This commit is contained in:
Tim Peters 2002-08-16 03:40:07 +00:00
parent f808b891d6
commit 012c0a393a
1 changed files with 12 additions and 5 deletions

View File

@ -93,11 +93,13 @@ Core and builtins
inputs have roughly the same size. If they both have about N digits,
Karatsuba multiplication has O(N**1.58) runtime (the exponent is
log_base_2(3)) instead of the previous O(N**2). Measured results may
be better or worse than that, depending on platform quirks. Note that
this is a simple implementation, and there's no intent here to compete
with, e.g., GMP. It gives a very nice speedup when it applies, but
a package devoted to fast large-integer arithmetic should run circles
around it.
be better or worse than that, depending on platform quirks. Besides
the O() improvement in raw instruction count, the Karatsuba algorithm
appears to have much better cache behavior on extremely large integers
(starting in the ballpark of a million bits). Note that this is a
simple implementation, and there's no intent here to compete with,
e.g., GMP. It gives a very nice speedup when it applies, but a package
devoted to fast large-integer arithmetic should run circles around it.
- u'%c' will now raise a ValueError in case the argument is an
integer outside the valid range of Unicode code point ordinals.
@ -296,6 +298,11 @@ Extension modules
Library
- random.randrange(-sys.maxint-1, sys.maxint) no longer raises
OverflowError. That is, it now accepts any combination of 'start'
and 'stop' arguments so long as each is in the range of Python's
bounded integers.
- New "algorithms" module: heapq, implements a heap queue. Thanks to
Kevin O'Connor for the code and François Pinard for an entertaining
write-up explaining the theory and practical uses of heaps.