Summary:
The article provides a comprehensive comparison of two flavors of named tuples in Python, collections.namedtuple and typing.NamedTuple. It discusses their use cases, methods, performance, and trade-offs, giving insights into when to use each type. The author highlights the advantages of named tuples, cautioning against overuse in certain scenarios.
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PYTHON PROGRAMMING
Tuples are a powerful Python type — but named tuples even more so!
Named tuples join the strengths of names and tuples. Photo by Ainur Iman on Unsplash
The three most popular Python data types are the list, the dictionary, and the tuple. Lists and dictionaries are mutable, meaning that their elements can be altered after creation. Tuples, on the other hand, are immutable, so they cannot be changed after creation. If you do need to modify the contents of a tuple, you must create a new instance with the desired changes and assign it to the same variable.
This article focuses on Python named tuples, a specialized type of tuple that combines the power of regular tuples with the added flexibility of named fields. Compared to regular tuples, named tuples can make code simpler, more readable and more maintainable — and even more Pythonic. However, you must be careful, as sometimes using named tuples excessively can inadvertently reduce code readability rather than enhance it.
Read on to learn more!
What named tuples are
The term “named tuple” neatly encapsulates this data structure’s essence: a tuple with named elements, or more formally, a tuple with named fields — or named attributes.
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List of Useful Links:
- AI Lab in Telegram @aiscrumbot – free consultation
- Python “Tuple+”: Named Tuples
- Towards Data Science – Medium
- Twitter – @itinaicom
