Python Assignments

Collection of Python programming assignments covering fundamental to advanced concepts including basic operations, data structures, functions, object-oriented programming, and data visualization across 7 comprehensive assignment sets.

About The Project

Python Assignments is a structured learning resource with practical programming problems:

• What it covers: 60+ Python problems spanning basics (variables, operators, conditionals), intermediate (loops, functions, strings), advanced (OOP, data structures), and data visualization
• What makes it useful: Sequential assignments with progressive difficulty; each assignment folder contains 6-12 focused questions with complete solutions
• What was learned: Core Python syntax, algorithm implementation, OOP principles, data structure manipulation, mathematical computations, and library usage

The project includes 7 assignment folders with detailed solutions for common interview and course problems, ideal for learning and interview prep.

Built With

• Python 3.8+
• Standard Library (math, statistics, visualization libraries in later assignments)

Getting Started

Prerequisites

• Python 3.8 or higher installed
• Any code editor or IDE (VS Code, PyCharm, Jupyter)
• Optional: matplotlib, numpy, pandas (for Assignment 7)

Installation

1. Clone the repo

   git clone https://github.com/tumansutradhar/python-assignments.git
   cd python-assignments

2. Navigate to an assignment

   cd Assignment_1

3. Run a question file

   python question_1.py

Usage

Assignment Structure: Each assignment folder contains numbered question files (question_1.py, question_2.py, etc.)

• Assignment_1 (12 questions): Basics - number comparison, Armstrong check, binary conversion, geometric calculations
• Assignment_2 (11 questions): Intermediate - complex numbers, primes, patterns, leap years, factorial, Fibonacci
• Assignment_3 (8 questions): Functions - factorial (multiple approaches), Fibonacci, list operations, string manipulation
• Assignment_4 (12 questions): Lists & Data Structures - sorting, searching, matrix operations, list comprehensions
• Assignment_5 (12 questions): String Operations - indexing, character counting, reversal, pattern matching, string methods
• Assignment_6 (6 questions): OOP - class definitions, inheritance, encapsulation, method overriding
• Assignment_7 (10 questions): Data Visualization & Statistics - plotting, graph analysis, statistical computations

Example workflow:

# Run Assignment 1, Question 1
cd Assignment_1
python question_1.py
# Enter numbers when prompted

# Run all assignments sequentially
for i in {1..7}; do
  cd Assignment_$i
  python question_1.py
  cd ..
done

Features

• Progressive Learning Path: Assignments increase in difficulty and complexity
• Diverse Problem Types: Number operations, string manipulation, data structures, OOP, data visualization
• Well-Commented Code: Each solution includes explanations of logic
• Multiple Approaches: Some problems show iterative, recursive, and optimized solutions
• User Input Support: Interactive programs that accept user input
• Real-World Scenarios: Problems based on common interview and coursework questions
• Library Usage: Introduction to Python standard library and third-party libraries

Project Structure

python-assignments/
├── Assignment_1/        # 12 - Basic operations
│   ├── question_1.py
│   ├── question_2.py
│   └── ...
├── Assignment_2/        # 11 - Intermediate
├── Assignment_3/        # 8  - Functions
├── Assignment_4/        # 12 - Data structures
├── Assignment_5/        # 12 - Strings
├── Assignment_6/        # 6  - OOP
├── Assignment_7/        # 10 - Visualization
└── README.md

Roadmap

• Basic Python programming
• Intermediate problem-solving
• Function implementations (recursive, iterative)
• List and data structure operations
• String manipulation techniques
• Object-oriented programming
• Data visualization basics
• Unit tests for all solutions
• Performance benchmarking
• Algorithm complexity analysis
• Web scraping examples
• Database interaction examples

Contributing

Contributions are what make the open-source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE.md for more information.

Contact

Tuman Sutradhar

• GitHub: @tumansutradhar
• Email: connect.tuman@gmail.com
• LinkedIn: Tuman Sutradhar

Project Link: https://github.com/tumansutradhar/python-assignments

Acknowledgments

• Python documentation and tutorials
• Problem-solving and algorithm resources
• Learning platforms (LeetCode, HackerRank patterns)
• Interview preparation guides