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* Description of DOuble hasing * Fix sheebang * Update double_hash.py * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update double_hash.py Co-authored-by: Christian Clauss <cclauss@me.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
54 lines
1.9 KiB
Python
54 lines
1.9 KiB
Python
#!/usr/bin/env python3
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"""
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Double hashing is a collision resolving technique in Open Addressed Hash tables.
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Double hashing uses the idea of applying a second hash function to key when a collision
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occurs. The advantage of Double hashing is that it is one of the best form of probing,
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producing a uniform distribution of records throughout a hash table. This technique
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does not yield any clusters. It is one of effective method for resolving collisions.
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Double hashing can be done using: (hash1(key) + i * hash2(key)) % TABLE_SIZE
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Where hash1() and hash2() are hash functions and TABLE_SIZE is size of hash table.
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Reference: https://en.wikipedia.org/wiki/Double_hashing
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"""
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from .hash_table import HashTable
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from .number_theory.prime_numbers import is_prime, next_prime
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class DoubleHash(HashTable):
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"""
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Hash Table example with open addressing and Double Hash
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"""
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def __init__(self, *args, **kwargs):
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super().__init__(*args, **kwargs)
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def __hash_function_2(self, value, data):
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next_prime_gt = (
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next_prime(value % self.size_table)
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if not is_prime(value % self.size_table)
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else value % self.size_table
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) # gt = bigger than
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return next_prime_gt - (data % next_prime_gt)
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def __hash_double_function(self, key, data, increment):
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return (increment * self.__hash_function_2(key, data)) % self.size_table
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def _collision_resolution(self, key, data=None):
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i = 1
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new_key = self.hash_function(data)
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while self.values[new_key] is not None and self.values[new_key] != key:
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new_key = (
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self.__hash_double_function(key, data, i)
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if self.balanced_factor() >= self.lim_charge
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else None
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)
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if new_key is None:
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break
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else:
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i += 1
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return new_key
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