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Python Data Structures and Algorithms

Python Data Structures and Algorithms

By : Benjamin Baka
2.7 (11)
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Python Data Structures and Algorithms

Python Data Structures and Algorithms

2.7 (11)
By: Benjamin Baka

Overview of this book

Data structures allow you to organize data in a particular way efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. In this book, you will learn the essential Python data structures and the most common algorithms. With this easy-to-read book, you will be able to understand the power of linked lists, double linked lists, and circular linked lists. You will be able to create complex data structures such as graphs, stacks and queues. We will explore the application of binary searches and binary search trees. You will learn the common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. We will also discuss how to organize your code in a manageable, consistent, and extendable way. The book will explore in detail sorting algorithms such as bubble sort, selection sort, insertion sort, and merge sort. By the end of the book, you will learn how to build components that are easy to understand, debug, and use in different applications.
Table of Contents (14 chapters)
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5
Stacks and Queues
7
Hashing and Symbol Tables

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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