A template repository for backend Python REST API server with a database

Stack: Flask Server, Gunicorn WSGI, Postgres DB, Docker, Shell

• Python 3.6
• Docker

Setup and activate a virtual environment (optional but recommended)

pip install -r requirements.txt

# Run unit tests with PyTest python setup.py test

# Install application python setup.py install # Start server locally sh scripts/start_server.sh

To start server locally with custom settings:

• Number of workers
• Threads per worker
• Worker timeout
• Gunicorn log level

sh scripts/start_server.sh workers=3 threads=2 timeout=30 log-level=DEBUG

# Build docker image python setup.py build_docker # Start server sh scripts/run_docker.sh

For custom settings, update Dockerfile before building image

Runs the entire setup using docker-compose:

• Flask API server
• Postgres database
• Postgres admin

Make sure you have DATA_DIR environment variable set. This directory will be used as persistent volume mount for Postgres database.

# Start all services (will always create new backend-api image) sh scripts/run_all.sh # Use existing backend-api image as per the VERSION file sh scripts/run_all.sh false # Stop all services sh scripts/stop_all.sh

This will start three containers on the same virtual network. Database will run on port5432, admin console will be available on http://localhost:5433 and API server will be available on http://localhost:8000

# Health check curl localhost:8000/health # Sample POST endpoint curl -X POST http://localhost:8000/postendpoint -H 'Content-Type: application/json' -d '{"param": "value"}'

To run the app on a Kubernetes cluster:

• Install kubernetes-cli (kubectl)
• Build and push the docker image to a registry accessible on the cluster
• Replace the placeholders in the deployment files under kubernetes directory and run the following commands

kubectl apply -f kubernetes/deployment.yaml kubectl apply -f kubernetes/service.yaml