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Getting Started with Python

You're reading from   Getting Started with Python Understand key data structures and use Python in object-oriented programming

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Product type Course
Published in Feb 2019
Publisher Packt
ISBN-13 9781838551919
Length 722 pages
Edition 1st Edition
Languages
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Authors (3):
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Benjamin Baka Benjamin Baka
Author Profile Icon Benjamin Baka
Benjamin Baka
Fabrizio Romano Fabrizio Romano
Author Profile Icon Fabrizio Romano
Fabrizio Romano
Dusty Phillips Dusty Phillips
Author Profile Icon Dusty Phillips
Dusty Phillips
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Table of Contents (31) Chapters Close

Title Page
Copyright and Credits
About Packt
Contributors
Preface
1. A Gentle Introduction to Python FREE CHAPTER 2. Built-in Data Types 3. Iterating and Making Decisions 4. Functions, the Building Blocks of Code 5. Files and Data Persistence 6. Principles of Algorithm Design 7. Lists and Pointer Structures 8. Stacks and Queues 9. Trees 10. Hashing and Symbol Tables 11. Graphs and Other Algorithms 12. Searching 13. Sorting 14. Selection Algorithms 15. Object-Oriented Design 16. Objects in Python 17. When Objects Are Alike 18. Expecting the Unexpected 19. When to Use Object-Oriented Programming 20. Python Object-Oriented Shortcuts 21. The Iterator Pattern 22. Python Design Patterns I 23. Python Design Patterns II 24. Testing Object-Oriented Programs 1. Other Books You May Enjoy Index

Randomized selection


In the previous chapter, we examined the quick sort algorithm. The quick sort algorithm allows us to sort an unordered list of items but has a way of preserving the index of elements as the sorting algorithm runs. Generally speaking, the quick sort algorithm does the following:

  1. Selects a pivot.
  2. Partitions the unsorted list around the pivot.
  3. Recursively sorts the two halves of the partitioned list using step 1 and step 2.

One interesting and important fact is that after every partitioning step, the index of the pivot will not change even after the list has become sorted. It is this property that enables us to be able to work with a not-so-fully sorted list to obtain the ith-smallest number. Because randomized selection is based on the quick sort algorithm, it is generally referred to as quick select.

Quick select

The quick select algorithm is used to obtain the ith-smallest element in an unordered list of items, in this case, numbers. We declare the main method of the algorithm...

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