Duplicate Keys in Python Dictionaries
In the programming realm, dictionaries prove invaluable for organizing data by mapping unique keys to corresponding values. However, the standard Python dictionary implementation adheres to a strict principle: each key must remain unique within the dictionary. This constraint poses a challenge when dealing with scenarios involving duplicate keys in a dataset.
Creating a Dictionary with Duplicate Keys
Suppose we encounter a text file containing duplicate car registration numbers, each associated with different information such as driver names, phone extensions, and parking locations. The task is to construct a dictionary with registration numbers as keys and the corresponding data as values. The following snippet illustrates a common approach:
However, this code faces a limitation due to Python's default dictionary behavior: duplicate keys result in overwriting previous values. To circumvent this, a solution is to store lists or sets within the dictionary.
Using Collections.defaultdict
The Python standard library provides a useful tool for this purpose: collections.defaultdict. This class initializes a dictionary with a default factory, ensuring that a non-existent key will create a new list or set (depending on the factory argument).
To populate the dictionary with duplicate keys, simply replace the original assignment statement:
with:
This strategy effectively creates a dictionary of lists, where each key corresponds to a list of associated values. By leveraging collections.defaultdict, you can successfully handle duplicate keys in your Python dictionaries.
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