Performance of Python Data Structures

It is important for you to understand the efficiency of these Python data structures because they are the building blocks we will use as we implement other data structure in the remainder of the book.


The designers of Python had many choices to make when they implemented the list data structure. Each of these choices could have an impact of how fast on how fast list operations perform. To help them make the right choices they looked at the ways that people would most commonly use the list data structure and they optimized their implementation of a list so that the most common operations were very fast. Of course they also tried to make the less common operations fast, but when a tradeoff and to be made the performance of a less common operation was often sacrificed in favor of the more common operation.

Two common operations are indexing and assigning to an index position. Bothe of these operations take the same amount of time no matter how large the list becomes. When an operation like this is independent of the size of the list they are O(1) .

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