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E-cercise Backend

E-cercise is a full-stack fitness equipment platform. This backend is built with Go (Fiber) and powered by PostgreSQL, Docker, and a Python-based Recommendation Service.

Features

  • Equipment management (CRUD)
  • Image upload via Cloudinary
  • Equipment options, features, attributes
  • User registration and goal tracking
  • Muscle group targeting
  • Personalized recommendation system
  • JWT-based authentication
  • Admin dashboard support
  • RESTful APIs
  • Dockerized environment

Technologies

  • Go (with Fiber, Gorm, UUID)
  • PostgreSQL
  • Docker + docker-compose
  • Cloudinary (for image upload)
  • Python (FastAPI) recommender
  • GitHub Actions for CI/CD

Getting Started

Prerequisites

  • Go 1.19+
  • Docker & Docker Compose
  • PostgreSQL (or use Docker)

Environment Setup

Copy the example environment file and configure your own:

cp .env.example .env

Run with Docker

docker-compose up --build

Run Locally

go mod tidy
go run main.go

Folder Structure

  • main.go – Entry point
  • /config – Config loaders
  • /controller – Route handlers
  • /model – GORM models
  • /repository – Data access
  • /service – Business logic
  • /data – Request/response types
  • /scripts – SQL seeders
  • /templates – Email or HTML templates
  • .github/workflows – GitHub CI/CD

API Documentation

Coming soon or available via Swagger/Postman (if provided).

Recommendation Service

Make sure your Python recommendation service is running and accessible at the configured URL (default: http://localhost:8000).

Deployment

The project supports deployment to Google Cloud Run or any Docker-compatible platform.

License

MIT – feel free to use and modify.

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  • Go 99.3%
  • Dockerfile 0.7%