PEAR Patient Service

Overview

PEAR Patient Service is a microservice for managing patient-related data. This repository provides the setup and development instructions to get the service running locally.

Getting Started

Prerequisites

1. Git: Ensure Git is installed on your system.
2. Conda: Install Conda for managing virtual environments.
3. NTU VPN: Install the NTU VPN to access internal resources.

Connect to NTU VPN

To connect to the NTU VPN, follow these steps:

Network Connection: Ensure you are connected to the NTUSECURE Wi-Fi network or connect through the NTU VPN.

VPN Setup: Follow the installation guide for detailed instructions on setting up and connecting to the VPN.

Cloning the Repository

Clone the repository using the following command:

git clone https://github.com/ntu-pear/PEAR_patient_service.git
cd PEAR_patient_service

Setting Up Your Environment

1. Create a Conda Virtual Environment:

# This is to set the python version in your conda environment to 3.9.19
conda create -n pear_patient_service python=3.9.19
conda activate pear_patient_service

Install the required dependencies

#install the necessary requirements in the conda environment
pip install -r requirements.txt

Environment Configuration

Make sure to create a .env file in the PEAR_patient_service folder. For instructions on how to configure this file, refer to the Confluence page:

Click on the link to be redirect to the confluence page -->Confluence page

Running the Application

After the installation is completed, run the application on your machine

uvicorn app.main:app --reload

This will start the microservice, which should be accessible at http://localhost:8000.

Notes for Windows Users

Ensure that Visual Studio Code uses LF (Line Feed) instead of CRLF (Carriage Return Line Feed) for line endings.

Notes for Mac Users

There will be a lot of unresolved troubleshooting. If the application does not work, run this command in the current directory

#install the necessary requirements in the conda environment
pip install -r requirements.txt

#After the installation is completed, run the application on your machine
uvicorn app.main:app --reload

Troubleshooting

If you encounter issues with Docker Compose, such as missing .sh files, you may need to adjust Git's line ending settings:

git config core.autocrlf false
git rm --cached -r .
git reset --hard

After running these commands, you should see:

Uvicorn running on http://0.0.0.0:8000 (Press CTRL+C to quit)

This indicates that the service is running successfully.

Versions Used

For consistency and reproducibility, the following versions of packages are used in this project:

• Python: 3.9.19
• FastAPI: 0.111.1
• Pydantic: 2.8.2
• Psycopg2-binary: 2.9.9
• Databases: 0.9.0
• SQLAlchemy: 2.0.31
• PyODBC: 5.1.0
• Uvicorn: 0.30.3
• Python-dotenv: 1.0.1

Additional Information

• MSSQL Database Name: fyp_patient_service_dev
• Microservice Name: patient_service