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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 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

Runtime analysis

It should be becoming clear that an important aspect to algorithm design is gauging the efficiency both in terms of space (memory) and time (number of operations). This second measure, called runtime performance, is the subject of this section. It should be mentioned that an identical metric is used to measure an algorithm's memory performance. There are a number of ways we could, conceivably, measure run time and probably the most obvious is simply to measure the time the algorithm takes to complete. The major problem with this approach is that the time it takes for an algorithm to run is very much dependent on the hardware it is run on. A platform-independent way to gauge an algorithm's runtime is to count the number of operations involved. However, this is also problematic in that there is no definitive way to quantify an operation. This is dependent...

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