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Introduction:
On a very bright friday, I don't have any specific hard task in my hands and therefore decided to explore a linkedin learning course. I would like to thank my current employer at the time of writing this blog; IQuanti for availing us the free linkedin learning.
In this post, we are going to review and provide key points from the course about learning python data structures. It is designed and created by Erin allard. Now, let's dive in.
First concept: Abstract data types:
What is abstract data types?
"abstract data types are abstract theoretical computer science concept which defines what type of data a data structure can hold and how can we interact with that data."
In case of creating new abstract data types, we have to therefore define both the data and ways to interact with it. But in the course, we are going to explore stack, queues and other well established structures; for which the formats are already well known.
It is also important to understand that abstract data types, being a concept; is not language specific. And the main point of using these is to understand how to interact with it.
Second concept: How to describe an abstract data type:
There are two main styles:
(1) imperative style (2) functional style
In imperative style we consider the abstract data type or ADT (we will refer to ADT in the rest of this document) to be mutable; i.e. changes can be made to ADT and the ADT can exist in different states on result of applying different operations. Therefore in the imperative style; operations, and their orders matter.
In functional style we consider the ADT to be immutable and therefore different states of it refer to different ADT. Having that, no operations can change an ADT; but can transform one ADT to another; and therefore the orders don't matter as none of the ADT's change actually.
In the course we are following ADT's imperative style.
Now, you may ask, why is the concept of abstract data types necessary and what are the advantages of using such thing?
The answer is that abstraction is a bliss. As long as you know the ADT from user perspective; you can use its allowable operations; handle its different states and you are ok. You don't need to know how or why the operations work; when the states occur in what way inside that abstract data type.
It's quite like using a black box, with few buttons outside which gives you what you want without you being concerned with inner function of the box. Therefore, abstraction is the main advantage in using such structures.
The next thing we explore is the concept of data structures.
What is data structure?
data structure is the realization of an ADT. An ADT is coded into data structure classes, with each of its allowed operations realized as class methods or functions. Data structures help us store and use ADTs in real computer memory.
Now that the theoretical mindset is established, we actually get into the course material of creating data structures and working with them.
Part 1: Stacks
Stacks is the first ADT we are going to work with. As it is part of linkedin learning paid content, I will not share the codes and structures she created, but will give an overall idea about it and move on.
Stacks is what we call LIFO structure (last in first out); where we can only access the data from the top of the stack. The name last in, first out refers to the fact that in a stack the element which is inserted last is the first one to come out.
For implementing stack in python, a list is the best item. We actually write the class for stack using a python list, considering its left to be the bottom of the stack and right to be the top of the stack. And for push ( data insertion) we can use append, and for pop (data deletion from top of stack) we can use the pop method for a list. I will not share the code here but you can follow the course slide to get the code.
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