Algorithms need necessary in-memory data structures that can hold temporary data while executing. Choosing the right data structures is essential for their efficient implementation. Certain classes of algorithms are recursive or iterative in logic and need data structures that are specially designed for them. For example, a recursive algorithm may be more easily implemented, exhibiting better performance, if nested data structures are used. In this chapter, data structures are discussed in the context of algorithms. As we are using Python in this book, this chapter focuses on Python data structures, but the concepts presented in this chapter can be used in other languages such as Java and C++.
By the end of this chapter, you should be able to understand how Python handles complex data structures and which one should be used for a certain...
In any language, data structures are used to store and manipulate complex data. In Python, data structures are storage containers to manage, organize, and search data in an efficient way. They are used to store a group of data elements called collections that need to be stored and processed together. In Python, there are five various data structures that can be used to store collections:
Lists: Ordered mutable sequences of elements
Tuples: Ordered immutable sequences of elements
Sets: Unordered bags of elements
Dictionary: Unordered bags of key-value pairs
Data frames: Two-dimensional structures to store two-dimensional data
Let's look into them in more detail in the upcoming subsections.
Abstraction, in general, is a concept used to define complex systems in terms of their common core functions. The use of this concept to create generic data structures gives birth to Abstract Data Types (ADT). By hiding the implementation level details and giving the user a generic, implementation-independent data structure, the use of ADTs creates algorithms that result in simpler and cleaner code. ADTs can be implemented in any programming language such as C++, Java, and Scala. In this section, we shall implement ADTs using Python. Let's start with vectors first.
A vector is a single dimension structure to store data. They are one of the most popular data structures in Python...
In this chapter, we discussed data structures that can be used to implement various types of algorithms. After going through this chapter, I expect that you should be able to select the right data structure to be used to store and process data by an algorithm. You should also be able to understand the implications of our choice on the performance of the algorithm.
The next chapter is about sorting and searching algorithms, where we will be using some of the data structures presented in this chapter in the implementation of the algorithms.