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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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Toc

Table of Contents (14) Chapters Close

Preface 1. Python Objects, Types, and Expressions FREE CHAPTER 2. Python Data Types and Structures 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

Improving list traversal


If you notice how we traverse our list. That one place where we are still exposed to the node class. We need to use node.data to get the contents of the node and node.next to get the next node. But we mentioned earlier that client code should never need to interact with Node objects. We can achieve this by creating a method that returns a generator. It looks as follows:

    def iter(self):
        current = self.tail
        while current:
            val = current.data
            current = current.next
            yield val  

Now list traversal is much simpler and looks a lot better as well. We can completely ignore the fact that there is anything called a Node outside of the list:

    for word in words.iter():
        print(word) 

Notice that since the iter() method yields the data member of the node, our client code doesn't need to worry about that at all.

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