# Project Generation - Template
You can use a project generator to get started, as it includes a lot of the initial set up, security, database and some API endpoints already done for you.
A project generator will always have a very opinionated setup that you should update and adapt for your own needs, but it might be a good starting point for your project.
## Full Stack FastAPI PostgreSQL
GitHub: https://github.com/tiangolo/full-stack-fastapi-postgresql
### Full Stack FastAPI PostgreSQL - Features
* Full **Docker** integration (Docker based).
* Docker Swarm Mode deployment.
* **Docker Compose** integration and optimization for local development.
* **Production ready** Python web server using Uvicorn and Gunicorn.
* Python **FastAPI** backend:
* **Fast**: Very high performance, on par with **NodeJS** and **Go** (thanks to Starlette and Pydantic).
* **Intuitive**: Great editor support. Completion everywhere. Less time debugging.
* **Easy**: Designed to be easy to use and learn. Less time reading docs.
* **Short**: Minimize code duplication. Multiple features from each parameter declaration.
* **Robust**: Get production-ready code. With automatic interactive documentation.
* **Standards-based**: Based on (and fully compatible with) the open standards for APIs: OpenAPI and JSON Schema.
* **Many other features** including automatic validation, serialization, interactive documentation, authentication with OAuth2 JWT tokens, etc.
* **Secure password** hashing by default.
* **JWT token** authentication.
* **SQLAlchemy** models (independent of Flask extensions, so they can be used with Celery workers directly).
* Basic starting models for users (modify and remove as you need).
* **Alembic** migrations.
* **CORS** (Cross Origin Resource Sharing).
* **Celery** worker that can import and use models and code from the rest of the backend selectively.
* REST backend tests based on **Pytest**, integrated with Docker, so you can test the full API interaction, independent on the database. As it runs in Docker, it can build a new data store from scratch each time (so you can use ElasticSearch, MongoDB, CouchDB, or whatever you want, and just test that the API works).
* Easy Python integration with **Jupyter Kernels** for remote or in-Docker development with extensions like Atom Hydrogen or Visual Studio Code Jupyter.
* **Vue** frontend:
* Generated with Vue CLI.
* **JWT Authentication** handling.
* Login view.
* After login, main dashboard view.
* Main dashboard with user creation and edition.
* Self user edition.
* **Vuex**.
* **Vue-router**.
* **Vuetify** for beautiful material design components.
* **TypeScript**.
* Docker server based on **Nginx** (configured to play nicely with Vue-router).
* Docker multi-stage building, so you don't need to save or commit compiled code.
* Frontend tests ran at build time (can be disabled too).
* Made as modular as possible, so it works out of the box, but you can re-generate with Vue CLI or create it as you need, and re-use what you want.
* **PGAdmin** for PostgreSQL database, you can modify it to use PHPMyAdmin and MySQL easily.
* **Flower** for Celery jobs monitoring.
* Load balancing between frontend and backend with **Traefik**, so you can have both under the same domain, separated by path, but served by different containers.
* Traefik integration, including Let's Encrypt **HTTPS** certificates automatic generation.
* GitLab **CI** (continuous integration), including frontend and backend testing.
## Full Stack FastAPI Couchbase
GitHub: https://github.com/tiangolo/full-stack-fastapi-couchbase
⚠️ **WARNING** ⚠️
If you are starting a new project from scratch, check the alternatives here.
For example, the project generator Full Stack FastAPI PostgreSQL might be a better alternative, as it is actively maintained and used. And it includes all the new features and improvements.
You are still free to use the Couchbase-based generator if you want to, it should probably still work fine, and if you already have a project generated with it that's fine as well (and you probably already updated it to suit your needs).
You can read more about it in the docs for the repo.
## Full Stack FastAPI MongoDB
...might come later, depending on my time availability and other factors. 😅 🎉
## Machine Learning models with spaCy and FastAPI
GitHub: https://github.com/microsoft/cookiecutter-spacy-fastapi
### Machine Learning models with spaCy and FastAPI - Features
* **spaCy** NER model integration.
* **Azure Cognitive Search** request format built in.
* **Production ready** Python web server using Uvicorn and Gunicorn.
* **Azure DevOps** Kubernetes (AKS) CI/CD deployment built in.
* **Multilingual** Easily choose one of spaCy's built in languages during project setup.
* **Easily extensible** to other model frameworks (Pytorch, Tensorflow), not just spaCy.