https://github.com/delsner/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
https://github.com/delsner/flask-angular-data-science

angular data-science docker flask machine-learning python sklearn typescript

Last synced: 3 months ago
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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

• Host: GitHub
• URL: https://github.com/delsner/flask-angular-data-science
• Owner: delsner
• Created: 2018-02-06T08:54:30.000Z (almost 7 years ago)
• Default Branch: master
• Last Pushed: 2018-07-04T14:03:09.000Z (over 6 years ago)
• Last Synced: 2024-09-26T14:24:10.829Z (4 months ago)
• Topics: angular, data-science, docker, flask, machine-learning, python, sklearn, typescript
• Language: TypeScript
• Homepage:
• Size: 116 KB
• Stars: 88
• Watchers: 4
• Forks: 77
• Open Issues: 1
• Metadata Files:
  • Readme: README.md

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README

        
# 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](https://medium.com/@dvelsner/deploying-a-simple-machine-learning-model-in-a-modern-web-application-flask-angular-docker-a657db075280).

## 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](https://www.getpostman.com/).

  

## 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](https://nodejs.org/en/), [Yarn](https://yarnpkg.com/en/docs/install) and the [angular-cli](https://cli.angular.io/) 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`.