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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

Summary


In this chapter, we have looked at hash tables. We looked at how to write a hashing function to turn string data into integer data. Then we looked at how we can use hashed keys to quickly and efficiently look up the value that corresponds to a key.

We also noticed how hashing functions are not perfect and that several strings can end up having the same hash value. This led us to look at collision resolution strategies.

We looked at growing a hash table and how to look at the load factor of the table in order to determine exactly when to grow the hash.

In the last section of the chapter, we studied symbol tables, which often are built using hash tables. Symbol tables allow a compiler or an interpreter to look up a symbol (variable, function, class, and so on) that has been defined and retrieve all information about it.

In the next chapter, we will talk about graphs and other algorithms.

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