ffzmm / flask-angular-data-science

Repository for a data science starter app using Flask, Angular and Docker. https://medium.com/@dvelsner/deploying-a-simple-machine-learning-model-in-a-modern-web-application-flask-angular-docker-a657db075280

Data Science Web Application Tutorial

This repository is meant to demonstrate the use of Flask and Angular to build a simple, but state-of-the-art, web application which can be used for POCs. Read the corresponding Medium article here.

Clone/Fork repository

First fork or clone this repo:

e.g. git clone https://github.com/delsner/flask-angular-data-science.git

Build images and run containers with docker-compose

After cloning the repository go inside the project folder:

cd flask-angular-data-science

Run docker-compose up which will start a Flask web application for the backend API (default port 8081) and an Angular frontend served through a webpack development web server (default port 4200).

Access your app

In your browser navigate to: http://localhost:4200 (or whatever port you defined for the frontend in docker-compose.yml).

For testing your backend API I recommend using Postman.

Working without docker

I highly recommend the use of docker and docker-compose as it is far simpler to get started than to run all of the following manually.

Backend development

Navigate inside the backend directory: cd backend

Install pip dependencies: pip install -r requirements.txt

Run python app.py in backend root (will watch files and restart server on port 8081 on change).

Frontend development

Navigate inside the frontend directory: cd frontend

Assure you have Nodejs, Yarn and the angular-cli installed.

Install npm dependencies: yarn install --pure-lockfile

Run yarn start in frontend root (will watch files and restart dev-server on port 4200 on change). All calls made to /api will be proxied to backend server (default port for backend 8081), this can be changed in proxy.conf.json.