Python_for_interview_preparation

Algorithms, Data structures and problem solving (for interview & competitive programming)

This repository contains a collection of Python scripts that can be useful for interview preparation or general programming practice. The scripts cover various topics, such as data structures, algorithms, and problem-solving techniques.

Scripts

Here's a list of the scripts available in this repository along with their classification:

Data Structures

• LinkedList.py: A script that demonstrates the implementation of a singly linked list.
• Stack.py: A script that demonstrates the implementation of a stack data structure.
• Queue.py: A script that demonstrates the implementation of a queue data structure.
• PriorityQueue.py: A script that demonstrates the implementation of a priority queue data structure.

Algorithms

• Binary_Search.py: A script that performs a binary search on a sorted array.
• Bubble_Sort.py: A script that performs bubble sort on an array.
• Insertion_Sort.py: A script that performs insertion sort on an array.
• Merge_Sort.py: A script that performs merge sort on an array.
• Quick_Sort.py: A script that performs quick sort on an array.

Problem-Solving Techniques

• Anagram.py: A script that checks if two strings are anagrams of each other.
• Fibonacci.py: A script that generates the nth Fibonacci number recursively and iteratively.
• FizzBuzz.py: A script that prints numbers from 1 to 100, replacing multiples of 3 with "Fizz", multiples of 5 with "Buzz", and multiples of both with "FizzBuzz".

Usage

You can clone this repository to your local machine and run the scripts using Python 3. Each script is self-contained and can be executed independently. To run a script, navigate to the directory containing the script and execute the following command:

python script_name.py

Contribution

If you find a bug or want to suggest an improvement, feel free to submit a pull request. Before submitting a pull request, please make sure that your code is well-documented and follows the PEP 8 style guide.

License

This repository is licensed under the MIT License. You are free to use, modify, and distribute the code in any way you want, as long as you include the original license file in your distribution.

Disclaimer

The scripts in this repository are intended for educational purposes only. They may not be optimized for production use and should be used with caution. The author of this repository is not responsible for any damage or loss caused by the use of these scripts.