1b7d5d849f
Use a simple quadratically probed, open addressed hash table. We could use a parfect hash function, but it would take longer to compute in Python, and this is not in the critical path performancewise.
77 lines
1.9 KiB
Python
77 lines
1.9 KiB
Python
"""
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Generate constant hash tables.
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The `constant_hash` module can generate constant pre-populated hash tables. We
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don't attempt parfect hashing, but simply generate an open addressed
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quadratically probed hash table.
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"""
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def simple_hash(s):
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"""
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Compute a primitive hash of a string.
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Example:
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>>> hex(simple_hash("Hello"))
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'0x2fa70c01'
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>>> hex(simple_hash("world"))
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'0x5b0c31d5'
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"""
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h = 5381
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for c in s:
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h = ((h ^ ord(c)) + ((h >> 6) + (h << 26))) & 0xffffffff
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return h
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def next_power_of_two(x):
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"""
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Compute the next power of two that is greater than `x`:
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>>> next_power_of_two(0)
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1
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>>> next_power_of_two(1)
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2
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>>> next_power_of_two(2)
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4
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>>> next_power_of_two(3)
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4
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>>> next_power_of_two(4)
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8
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"""
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s = 1
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while x & (x + 1) != 0:
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x |= x >> s
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s *= 2
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return x + 1
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def compute_quadratic(items, hash_function):
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"""
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Compute an open addressed, quadratically probed hash table containing
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`items`. The returned table is a list containing the elements of the
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iterable `items` and `None` in unused slots.
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:param items: Iterable set of items to place in hash table.
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:param hash_function: Hash function which takes an item and returns a
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number.
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Simple example (see hash values above, they collide on slot 1):
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>>> compute_quadratic(['Hello', 'world'], simple_hash)
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[None, 'Hello', 'world', None]
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"""
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items = list(items)
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# Table size must be a power of two. Aim for >20% unused slots.
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size = next_power_of_two(int(1.20*len(items)))
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table = [None] * size
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for i in items:
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h = hash_function(i) % size
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s = 0
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while table[h] is not None:
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s += 1
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h = (h + s) % size
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table[h] = i
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return table
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if __name__ == "__main__":
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import doctest
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doctest.testmod()
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