🐍Day 14- Python Data Types and Data Structures for DevOps

📍Python 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:

# Let us take some example to understand briefly
apples = 20  #Integer(int)
marks = 60.5 #Float(float)
name = "Vivek" #String(str)
is_raining = False #boolean Note: this is case sensetive
list_var = [1, 2, 3]
tuple_var = (1, 2, 3)
dict_var = {"key": "value"}

# To check the data type
print(type(apples)) # Output: <class 'int'>
print(type(marks))  # Output: <class 'float'>
print(type(name))   # Output: <class 'str'>
print(type(is_raining)) # Output: <class 'bool'>
print(type(list_var)) # Output: <class 'list'>
print(type(tuple_var)) # Output: <class 'tuple'>
print(type(dict_var)) # Output: <class 'dict'>

📍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.

1. 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.

   • Mutable (able to modified after creation).

   • Allows duplicate elements.

   • Accessed by index.

   • Syntax: [item1, item2].

2. Tuple

   • Python Tuple is a collection of Python objects much like a list but Tuples are immutable in nature 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.

   • Immutable (can't be modified once created).

   • Allows duplicate elements.

   • Accessed by index.

   • Syntax: (item1, item2) .

3. Dictionaries

   • 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.

   • Mutable (able to modified after creation).

   • can Accessed by key.

   • Any datatype can be used.

   • Syntax: {key1: value1, key2: value2}.

✔Tasks

1. Give the Difference between List, Tuple and set. Do Hands-on and put screenshots as per your understanding.

   1. Lists 📜:

      • 📋 Ordered collections of items.

      • 🔄 Mutable: You can add, remove, or modify elements after creation.

      • 🔧 Created using square brackets [].

        

   2. Sets 🎭:

      • 🎈 Unordered collections of unique items.

      • 🔄 Mutable: You can add or remove elements after creation, but you cannot modify individual elements.

      • 🛠️ Created using curly braces {} or the set() function.

        

   3. Tuples 🔄:

      • 📦 Ordered collections of items.

      • 🔒 Immutable: Once created, you cannot add, remove, or modify elements.

      • 🔒 Created using parentheses ().

        

In summary:

1. 📜 Lists are like dynamic checklists where you can change, add, or remove items as needed.

2. 🎭 Sets are like a bag of unique items where you can throw in new ones or take them out, ensuring each item is unique.

3. 🔄 Tuples are like fixed-size packages where once sealed, the contents cannot be changed.

   1. Task2- Create 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"
        }

        # Print your favorite tool using its corresponding key
        favorite_tool_key = 2  # Assuming your favorite tool is Git and its key is 2
        favorite_tool = fav_tools.get(favorite_tool_key)

        if favorite_tool:
            print("My favorite tool is:", favorite_tool)
        else:
            print("Sorry, your favorite tool is not found in the dictionary.")

3. Task -3 Create a List of cloud service providers eg. cloud_providers = ["AWS","GCP","Azure"] & Write a program to add Digital Ocean to the list of cloud_providers and sort the list in alphabetical order.

        # List of cloud service providers
        cloud_providers = ["AWS", "GCP", "Azure"]

        # Add Digital Ocean to the list
        cloud_providers.append("Digital Ocean")

        # Sort the list in alphabetical order
        cloud_providers.sort()

        # Print the sorted list
        print("Sorted list of cloud service providers:")
        for provider in cloud_providers:
            print(provider)

This code will output the list of cloud service providers sorted alphabetically, with "Digital Ocean" included:

        Sorted list of cloud service providers:
        AWS
        Azure
        Digital Ocean
        GCP

🚧Conclusion

Python's data types and data structures empower DevOps practitioners with efficient tools for managing and manipulating data, enhancing productivity.

Happy Learning 😊