Flask-serve-ML

This repository contains a simple implementation of a Flask app serving a machine learning model as JSON REST API.

The deployment uses CherryPy as WSGI server implementation. The project contains also a Dockerfile to create a containerized version of the application. The image is based on a Debian:latest-slim base image and once built, is around 120 MB (thanks to Michele Bologna for the suggestions).

Running

Start as Python Process

Just type ./start-server.sh.

Start as Docker Container

First build the Docker image and then run it.

docker build -t pyml_img .
docker run --name pyml_instance -p 5000:5000 -i -t pyml_img

References

• DigitalOcean guide on how to containerize Python web applications.