data_structures.hashing.double_hash
===================================

.. py:module:: data_structures.hashing.double_hash

.. autoapi-nested-parse::

   Double hashing is a collision resolving technique in Open Addressed Hash tables.
   Double hashing uses the idea of applying a second hash function to key when a collision
   occurs. The advantage of Double hashing is that it is one of the best form of  probing,
   producing a uniform distribution of records throughout a hash table. This technique
   does not yield any clusters. It is one of effective method for resolving collisions.

   Double hashing can be done using: (hash1(key) + i * hash2(key)) % TABLE_SIZE
   Where hash1() and hash2() are hash functions and TABLE_SIZE is size of hash table.

   Reference: https://en.wikipedia.org/wiki/Double_hashing



Classes
-------

.. autoapisummary::

   data_structures.hashing.double_hash.DoubleHash


Module Contents
---------------

.. py:class:: DoubleHash(*args, **kwargs)

   Bases: :py:obj:`data_structures.hashing.hash_table.HashTable`


   Hash Table example with open addressing and Double Hash


   .. py:method:: __hash_double_function(key, data, increment)


   .. py:method:: __hash_function_2(value, data)


   .. py:method:: _collision_resolution(key, data=None)

      Examples:

      1. Try to add three data elements when the size is three
      >>> dh = DoubleHash(3)
      >>> dh.insert_data(10)
      >>> dh.insert_data(20)
      >>> dh.insert_data(30)
      >>> dh.keys()
      {1: 10, 2: 20, 0: 30}

      2. Try to add three data elements when the size is two
      >>> dh = DoubleHash(2)
      >>> dh.insert_data(10)
      >>> dh.insert_data(20)
      >>> dh.insert_data(30)
      >>> dh.keys()
      {10: 10, 9: 20, 8: 30}

      3. Try to add three data elements when the size is four
      >>> dh = DoubleHash(4)
      >>> dh.insert_data(10)
      >>> dh.insert_data(20)
      >>> dh.insert_data(30)
      >>> dh.keys()
      {9: 20, 10: 10, 8: 30}