TFTracker

TFTracker is a full-stack transformer (toy) collection tracking website with a React.js frontend and a Django backend (via the Django REST Framework).

Features

• Session Authentication
• User Accounts
• Registration
• Login
• Redux State Management
• Database Search Interface
  • Trigram Similarity Searching
  • Sorting
  • Filtering
• Saved Collections (implemented in backend)
• User Preferences (model implemented in backend)
• User Settings (model implemented in backend)
• Docker Image

Getting Started

Currently, TFTracker can only be run in a development environment

System Requirements

💡 Before you begin, make sure you have the following installed:

• Node.js v16 or above
• Git
• Python

Getting Started With Local Development

Follow these simple instructions to set up a local development environment.

1. Clone the repository:

git clone https://github.com/dagleaves/tftracker.git
cd tftracker

2. (optional) Create a Python virtual environment:

python -m venv env
source env/Scripts/activate

3. Install dependencies:

pip install -r requirements.txt
cd frontend/client
npm i

4. TODO: Run Docker image

5. Apply database migrations:

python backend/django-app/manage.py migrate

5. Start development servers:

# Backend server - open localhost:8000 to manage
python backend/django-app/manage.py runserver

# Frontend sever - open localhost:3000 to manage
cd frontend/client
npm start

Notes

There are API keys (S3, Firebase) in the git history from before I made this repository public. These were all regenerated.

Motivation

I plan on putting this website into production when it reaches a usable state. However, this project has consumed a significant enough amount of time and has reached a size that I have to include it in my portfolio.