Python Data Types and Data Structures for DevOps🚀

Data Types

• Data types are the classification or categorization of data items. It represents the kind of value that tells what operations can be performed on a particular data.

• Since everything is an object in Python programming, data types are actually classes and variables are instance (object) of these classes.

• Python has the following data types built-in by default: Numeric(Integer, complex, float), Sequential(string,lists, tuples), Boolean, Set, Dictionaries, etc

To check what is the data type of the variable used, we can simply write: your_variable=100 print(type(your_variable))

Data Structures

Data Structures are a way of organizing data so that it can be accessed more efficiently depending upon the situation. Data Structures are fundamentals of any programming language around which a program is built. Python helps to learn the fundamental of these data structures in a simpler way as compared to other programming languages.

• Lists: Python Lists are just like the arrays, declared in other languages which is an ordered collection of data. It is very flexible as the items in a list do not need to be of the same type

• Tuple: Python Tuple is a collection of Python objects much like a list but Tuples are immutable i.e. the elements in the tuple cannot be added or removed once created. Just like a List, a Tuple can also contain elements of various types.

• Dictionary: Python dictionary is like hash tables in any other language with the time complexity of O(1). It is an unordered collection of data values, used to store data values like a map, which, unlike other Data Types that hold only a single value as an element, Dictionary holds the key:value pair. Key-value is provided in the dictionary to make it more optimized

Tasks

Difference between List, Tuple and Set

	List	Set	Tuple
Collection	ordered	unordered	ordered
Items	similar or different types	unique	squence of similar or different types
Nature	mutable	mutable	immutable
Separated by	commas	commas	commas
Enclosed by	[ ]	{ }	()
Data structure	non-homogenous	non-homogenous	non-homogenous
Store various elements in	columns, multiple rows, and single rows	single row	columns, multiple rows, and single rows
Duplicate Items	allow	does not allow	allow
Empty List	l=[]	a=set() b=set(a)	t=()

Task :

1. Create the below Dictionary and use Dictionary methods to print your favorite tool just by using the keys of the Dictionary. fav_tools = {1:"Linux", 2:"Git", 3:"Docker", 4:"Kubernetes", 5:"Terraform", 6:"Ansible", 7:"Chef"}

First, create a dictionary and then print it. To execute write your code in file (fav_tools.py) a python file .py extension is necessary.

fav_tools = {1:"Linux", 2:"Git", 3:"Docker", 4:"Kubernetes", 5:"Terraform", 6:"Ansible", 7:"Chef"}
print(fav_tools[1])
#0utput Linux

1. Create a List of cloud service providers eg. cloud_providers = ["AWS","GCP","Azure"]

    #List of Cloud Providers
    cloud_providers = ["AWS","GCP","Azure"] 
    print(type(cloud_providers))
    #Output <class 'list'>
   

2. Write a program to add Digital Ocean to the list of cloud_providers and sort the list in alphabetical order.

    #List of Cloud Providers
    cloud_providers = ["AWS","GCP","Azure","Digital Ocean"] 
    cloud_providers.sort()
    print(cloud_providers)
    #Output ['AWS','Azure','Digital Ocean','GCP']