/*
Major subtleties ahead: Most hash schemes depend on having a "good" hash
function, in the sense of simulating randomness. Python doesn't: its most
-important hash functions (for strings and ints) are very regular in common
+important hash functions (for ints) are very regular in common
cases:
- >>> map(hash, (0, 1, 2, 3))
+ >>>[hash(i) for i in range(4)]
[0, 1, 2, 3]
- >>> map(hash, ("namea", "nameb", "namec", "named"))
- [-1658398457, -1658398460, -1658398459, -1658398462]
- >>>
This isn't necessarily bad! To the contrary, in a table of size 2**i, taking
the low-order i bits as the initial table index is extremely fast, and there
-are no collisions at all for dicts indexed by a contiguous range of ints.
-The same is approximately true when keys are "consecutive" strings. So this
-gives better-than-random behavior in common cases, and that's very desirable.
+are no collisions at all for dicts indexed by a contiguous range of ints. So
+this gives better-than-random behavior in common cases, and that's very
+desirable.
OTOH, when collisions occur, the tendency to fill contiguous slices of the
hash table makes a good collision resolution strategy crucial. Taking only