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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

Recursion and backtracking


Recursion is particularly useful for divide and conquer problems; however, it can be difficult to understand exactly what is happening, since each recursive call is itself spinning off other recursive calls. At the core of a recursive function are two types of cases: base cases, which tell the recursion when to terminate, and recursive cases that call the function they are in. A simple problem that naturally lends itself to a recursive solution is calculating factorials. The recursive factorial algorithm defines two cases: the base case when n is zero, and the recursive case when n is greater than zero. A typical implementation is the following:

    def factorial(n):
        #test for a base case
        if n==0:
            return 1
            # make a calculation and a recursive call
            f= n*factorial(n-1)
        print(f)
        return(f)
        factorial(4)

This code prints out the digits 1, 2, 4, 24. To calculate 4 requires four recursive calls plus...

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