Book Image

Getting Started with Python

By : Fabrizio Romano, Benjamin Baka, Dusty Phillips
Book Image

Getting Started with Python

By: Fabrizio Romano, Benjamin Baka, Dusty Phillips

Overview of this book

This Learning Path helps you get comfortable with the world of Python. It starts with a thorough and practical introduction to Python. You’ll quickly start writing programs, building websites, and working with data by harnessing Python's renowned data science libraries. With the power of linked lists, binary searches, and sorting algorithms, you'll easily create complex data structures, such as graphs, stacks, and queues. After understanding cooperative inheritance, you'll expertly raise, handle, and manipulate exceptions. You will effortlessly integrate the object-oriented and not-so-object-oriented aspects of Python, and create maintainable applications using higher level design patterns. Once you’ve covered core topics, you’ll understand the joy of unit testing and just how easy it is to create unit tests. By the end of this Learning Path, you will have built components that are easy to understand, debug, and can be used across different applications. This Learning Path includes content from the following Packt products: • Learn Python Programming - Second Edition by Fabrizio Romano • Python Data Structures and Algorithms by Benjamin Baka • Python 3 Object-Oriented Programming by Dusty Phillips
Table of Contents (31 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
8
Stacks and Queues
10
Hashing and Symbol Tables
Index

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.