Question

I was messing around with making a command line parser and was wondering what kind of hash algorithm python dict’s use?

The way I have it set up, I have a pattern match algorithm which matches tokenized input sequences with a dictionary key. Some of the keys are relatively long (length 5 or 6 tuples of 6-7 character strings). I was wondering if there was a point at which long dictionary keys significantly reduce the efficiency of key retrieval.

Answer 1

The hash that it uses depends on the object being used as a key — each class can define its own __hash__() method, and the value that it returns for a particular instance is what is used for the dictionary.

Python itself provides the hash implementation for str and tuple types. A quick look at the source should reveal the exact algorithm for those.

The hash of a tuple is based on the hashes of its contents. The algorithm is essentially this (simplified slightly):

def hash(tuple):
    mult = 1000003
    x = 0x345678
    for index, item in enumerate(tuple):
        x = ((x ^ hash(item)) * mult) & (1<<32)
        mult += (82520 + (len(tuple)-index)*2)
    return x + 97531

For strings, the interpreter also iterates over every character, combining them with this (again, slightly simplified) algorithm:

def hash(string):
    x = string[0] << 7
    for chr in string[1:]:
        x = ((1000003 * x) ^ chr) & (1<<32)
    return x

A bigger issue to worry about is avoiding hash collisions. Colliding hash keys will cause a linear search as the dictionary tries to find a place to store the new object (this is now being recognized as a security issue, and tha behavior may be changing in upcoming python versions)