Skip to content

IbrahimOrdo/motor-selection-backend

Repository files navigation

Motor Selection Backend

Motor Selection Backend is a .NET 8 Minimal API project designed to assist users in selecting the most suitable motorcycle based on various personal and technical criteria. The project leverages MSSQL with Entity Framework Core (Code-First), ensuring a scalable and structured database. It is designed with RESTful API principles and provides a clear and interactive documentation via Swagger.

🚀 Project Purpose

This project serves multiple objectives:

  • 📌 Showcase Skills: Demonstrates proficiency in .NET 8, MSSQL, Minimal API, Entity Framework Core, and REST API design.
  • 🔍 Active Development: Highlights continuous development and contributions to real-world applications.
  • 🏍️ Motorcycle Recommendation: Provides structured data and algorithms for intelligent motorcycle selection.

⚙️ Technologies & Tools

  • .NET 8 Minimal API
  • MSSQL & Entity Framework Core (Code-First)
  • Swagger for API Documentation
  • Serilog for Logging
  • Dependency Injection & Middleware Configuration

📌 Features

  • User & Motorcycle Management: CRUD operations for users and motorcycles.
  • Smart Selection Algorithm: Recommends motorcycles based on user preferences.
  • Secure API: Implements authentication & authorization mechanisms (to be added).
  • Logging & Monitoring: Uses Serilog for structured logging.

🔧 Setup & Installation

  1. Clone the Repository
git clone https://github.com/IbrahimOrdo/motor-selection-backend.git
cd motor-selection-backend
  1. Configure Database Connection
  • Update the appsettings.json file with your MSSQL connection string.
  1. Run the Application
dotnet run
  1. Access Swagger API Docs
  • Navigate to: http://localhost:5000/swagger/index.html

📌 Roadmap

  • ✅ Initial API Endpoints
  • 🔄 Motorcycle Selection Algorithm Improvement
  • 🔐 Authentication & Authorization
  • 📊 Data Visualization for User Insights

📫 Contribution & Contact

This project is actively maintained by Ibrahim Ordo. Contributions are welcome! Feel free to open issues or pull requests.


Note: This project is part of a broader initiative to build a full-fledged motorcycle recommendation system, combining ML models and real-world data in future iterations.

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors