Fastapi Patient CRUD

This project is a comprehensive example of a CRUD (Create, Read, Update, Delete) application with soft delete functionality for data listing. It features a ready-to-use API designed for microservices, built using FastAPI. This setup not only demonstrates the essential operations of a web service but also integrates advanced features like soft deletion, which allows for non-destructive data handling. The architecture is optimized for scalability and efficiency, making it an ideal starting point for developing microservices in Python with FastAPI.

Data Source

The data for this project is sourced from Synthea, an open-source synthetic patient generator that models the medical histories of synthetic patients. More information can be found on their website.

Sample data can be downloaded from the following URL: Synthea Sample Data.

Prerequisites

• Python 3.11
• Poetry for Python dependency management
• docker
• docker-compose

Installation

Docker-Compose Setup

To install and start PostgreSQL:

sudo curl -L "https://github.com/docker/compose/releases/download/1.29.2/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose
sudo chmod +x /usr/local/bin/docker-compose

Verify the result of installation

docker-compose --version

Application Setup

Install Dependencies

make dependencies

This will set up your Python environment and install necessary dependencies.

Usage

To start the tests, run:

make run

Running Tests

Only Tests

make unit

Full Tests Setup

To run tests, linting, and style checks:

make test

Coverage

To run coverage:

make cov

Building and Deploying with Docker

Deploying the Application

To deploy the application using Docker, execute:

make build

This will run the synthea-api image in a Docker container. The container will be named synthea-api, and the application will be accessible on the specified port set by the ${PORT} environment variable. Ensure that the PORT environment variable is set before running this command, or modify the Makefile to use a default port. The database will be placed in a container named postgres on the port ${DB_PORT}

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.