How can a bidirectional hash table in Python enable efficient key- and value-based indexing?

Implementing an Efficient Bidirectional Hash Table

A hash table or dictionary data structure offers efficient indexing and retrieval of values by keys. However, sometimes it is desirable to index by values as well. A bidrectional hash table allows for both key-based and value-based indexing.

Custom Implementation Using a Bidirectional Class

The Python dict implementation provides a unidirectional mapping from keys to values. To create a bidirectional hash table, we can create our own class that inherits from the dict class:

<code class="python">class bidict(dict):
    def __init__(self, *args, **kwargs):
        super(bidict, self).__init__(*args, **kwargs)
        self.inverse = {}
        for key, value in self.items():
            self.inverse.setdefault(value, []).append(key)

    def __setitem__(self, key, value):
        if key in self:
            self.inverse[self[key]].remove(key)
        super(bidict, self).__setitem__(key, value)
        self.inverse.setdefault(value, []).append(key)

    def __delitem__(self, key):
        self.inverse.setdefault(self[key], []).remove(key)
        if self[key] in self.inverse and not self.inverse[self[key]]:
            del self.inverse[self[key]]
        super(bidict, self).__delitem__(key)</code>

Key Features:

• The inverse attribute maintains a mapping from values to a list of keys.
• When a key-value pair is added, the inverse mapping is updated automatically.
• When a key is deleted, the inverse mapping is also updated to remove the key.
• The bidirectional nature allows for both d[key] and d[value] access.
• It permits multiple keys to have the same value.

Example Usage:

<code class="python">bd = bidict({'a': 1, 'b': 2})

print(bd)  # {'a': 1, 'b': 2}
print(bd.inverse)  # {1: ['a'], 2: ['b']}

bd['c'] = 1  # Two keys have the same value
print(bd)  # {'a': 1, 'c': 1, 'b': 2}
print(bd.inverse)  # {1: ['a', 'c'], 2: ['b']}</code>

Advantages:

This implementation combines the efficiency of Python's dict data structure with the flexibility of bidirectional access. It is a powerful tool for various applications where value-based indexing is necessary.

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