Episode

Python Data Types and Data Structures for DevOps

Mayur S. Mutkekar's photo
Mayur S. Mutkekar
·

3 min read

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 instances (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 
type(your_variable)

Data Structure

In Python, data structures are like containers that help us store and manage information in a neat and efficient way. They are tools that make working with data simple and organized. Here are some common data structures in Python:

  1. Lists: Lists are like ordered shopping bags that can hold different things together. You can add, remove, or change items in the bag.

  2. Tuples: Tuples are similar to lists but more like sealed packages. Once you put things inside, you can't change them.

  3. Dictionaries: Dictionaries work like phone books, where you find names (keys) and their corresponding numbers (values). It helps you quickly find what you need.

  4. Sets: Sets are like collections of unique items, just like a group of friends without any duplicates.

  5. Strings: Strings are like sentences made up of letters. They help us work with text and words.

  6. Arrays: Arrays are specialized tools to work with numbers efficiently. They are helpful for advanced math and calculations.

Task 1: Give the Difference between List, Tuple, and Set.

1. List:

  • Lists are ordered collections of elements.

  • They are mutable, which means you can add, remove, or modify elements.

  • Lists are defined using square brackets [].

  • Elements in a list can be duplicates.

my_list = [1, 2, 3, 2, 4]

2. Tuple:

  • Tuples are ordered collections of elements, just like lists.

  • However, tuples are immutable, meaning that once created, their elements cannot be changed.

  • Tuples are defined using parentheses ().

  • Elements in a tuple can be duplicates.

my_tuple = (1, 2, 3, 2, 4)
  1. Set:

  • A set is an unordered collection of unique elements enclosed in curly braces {} or created using the set() function.

  • Sets are mutable, so you can add or remove elements after creating them.

  • Sets do not allow duplicate elements. If you try to add a duplicate element, it will be automatically removed.

  • Sets are typically used when you need to perform set operations like union, intersection, and difference.

my_set = {1, 2, 3, 4}

Task 2: Create the below Dictionary and use Dictionary methods to print your favourite tool just by using the keys of the Dictionary.

# Create the fav_tools dictionary
fav_tools = {1: "Linux", 2: "Git", 3: "Docker", 4: "Kubernetes", 5: "Terraform", 6: "Ansible", 7: "Chef"}

# Your favorite tool's key (assuming you like "Docker" in this example)
your_favorite_tool_key = 3

# Print your favorite tool using the dictionary method
favorite_tool = fav_tools[your_favorite_tool_key]
print("Your favorite tool is:", favorite_tool)