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Python Data Structures and Algorithms

You're reading from   Python Data Structures and Algorithms Improve application performance with graphs, stacks, and queues

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Product type Paperback
Published in May 2017
Publisher Packt
ISBN-13 9781786467355
Length 310 pages
Edition 1st Edition
Languages
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Author (1):
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Benjamin Baka Benjamin Baka
Author Profile Icon Benjamin Baka
Benjamin Baka
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Table of Contents (14) Chapters Close

Preface 1. Python Objects, Types, and Expressions 2. Python Data Types and Structures FREE CHAPTER 3. Principles of Algorithm Design 4. Lists and Pointer Structures 5. Stacks and Queues 6. Trees 7. Hashing and Symbol Tables 8. Graphs and Other Algorithms 9. Searching 10. Sorting 11. Selection Algorithms 12. Design Techniques and Strategies 13. Implementations, Applications, and Tools

A faster append operation


There is a big problem with the append method in the previous section: it has to traverse the entire list to find the insertion point. This may not be a problem when there are just a few items in the list, but wait until you need to add thousands of items. Each append will be slightly slower than the previous one. A O(n) goes to prove how slow our current implementation of the append method will actually be.

To fix this, we will store, not only a reference to the first node in the list, but also a reference to the last node. That way, we can quickly append a new node at the end of the list. The worst case running time of the append operation is now reduced from O(n) to O(1). All we have to do is make sure the previous last node points to the new node, that is about to be appended to the list. Here is our updated code:

    class SinglyLinkedList:
         def __init__(self): 
             # ...
             self.tail = None

         def append(self, data):
      ...
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