Python Data Types and Data Structures for DevOps

||Python Data Types and Data Structures for DevOps||

Data Types:

Data types in Python define the type and behavior of values or variables. They determine the operations that can be performed on the data and how they are stored in memory. Python provides several built-in data types, including:

1. Numeric types: Integers (int), floating-point numbers (float), and complex numbers (complex).
2. Sequence types: Strings (str), lists (list), and tuples (tuple).
3. Mapping type: Dictionary (dict).
4. Set types: Set (set) and frozenset (frozenset).
5. Boolean type: Boolean values (True and False).
6. None type: A special type representing the absence of a value (None).

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.

Arrays: Arrays are a collection of elements stored in contiguous memory locations. They can hold a fixed number of elements of the same type. Elements in an array can be accessed using their index, which represents their position in the array.

Lists: Lists are similar to arrays but with more flexibility. They can store elements of different types and can grow or shrink dynamically as elements are added or removed. Elements in a list are ordered and can be accessed by their index.

Dictionaries: Dictionaries, also known as maps or hash maps, store data as key-value pairs. Each key is unique and associated with a value. Dictionaries allow for efficient lookup of values based on their keys, making them useful for tasks like data retrieval and mapping.

Linked Lists: Linked lists consist of nodes where each node holds a value and a reference to the next node. Unlike arrays, linked lists do not require contiguous memory and can grow or shrink dynamically. Linked lists provide efficient insertion and deletion operations, but accessing elements by index takes linear time.

Stacks: Stacks follow the Last-In-First-Out (LIFO) principle. Elements are added and removed from one end, known as the top. The last element added is the first one to be removed. Stacks are used in tasks that involve tracking function calls, undo/redo operations, and parsing expressions.

Queues: Queues follow the First-In-First-Out (FIFO) principle. Elements are added at one end, known as the rear, and removed from the other end, known as the front. Queues are used in scenarios where processing needs to be done in the order of arrival, such as handling print jobs or managing requests.

Trees: Trees are hierarchical data structures with a root node and child nodes. Each node can have multiple child nodes, forming a branching structure. Trees are used to represent hierarchical relationships, like file systems or organizational charts.

Graphs: Graphs consist of nodes connected by edges. They can represent complex relationships and networks. Graphs are used in applications like social networks, transportation networks, and recommendation systems.

Tasks:

1. Give the Difference between List, Tuple and Set. Do Handson and put screenshots as per your understanding:

List: Lists are versatile and mutable collections that can store elements of different types. They are enclosed in square brackets [] and allow for dynamic resizing, meaning you can add, remove, or modify elements after creation. Lists preserve the order of elements and support indexing and slicing operations. Due to their mutable nature, lists are suitable for situations where you need to modify the contents frequently, such as managing a to-do list or storing data that requires updates.

Tuple: Tuples, on the other hand, are immutable collections represented by parentheses (). Once created, the elements within a tuple cannot be modified. Tuples maintain the order of elements like lists and support indexing and slicing. However, due to their immutability, they provide data integrity and can be used to store values that should not be changed, such as coordinates or configuration settings. Tuples are also slightly more memory-efficient than lists.

Sets:Sets are unordered collections of unique elements enclosed in curly braces {}. They do not allow duplicate values, and the order of elements is not preserved. Sets are particularly useful when you need to perform mathematical operations like union, intersection, or difference between collections. They provide efficient membership testing, allowing you to quickly check if an element exists in a set. Additionally, sets can be modified by adding or removing elements as needed.

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

This code creates a dictionary called "fav_tools" with keys 1-7 and values representing various tools. It then uses the keys method to access the key of my favorite tool "Docker" and print its value.

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.

Happy Learning :)