This explains how to configure Flask, Celery, RabbitMQ and Redis, together with Docker to build a web service that dynamically uploads the content and loads this content when it is ready to be displayed. We’ll focus mainly on Celery and the services that surround it. Docker is a bit more straightforward.

Project Structure

The finished project structure will be as follows:

├── Dockerfile
├── docker-compose.yml
├── README.md
├── app
│ ├── app.py
│ ├── tasks.py
│ └── templates
│ ├── download.html
│ └── index.html
├── scripts
│ ├── run_celery.sh
│ └── run_web.sh
└── requirements.txt

Creating the Flask application 🌶

First, we create a folder for our app. For this example, our folder is called app. Within this folder, create an app.py file and an empty folder named templates where our HTML templates will be stored.

For our app, we first include some basic Flask libraries and create an instance of the app:

from io import BytesIO

from flask import Flask, request
from flask import render_template, make_response
APP = Flask(__name__)

We define three routes for Flask to implement: a landing page, a secondary page that embeds and image, and a route for the image itself. Our image route crops an image dynamically. For this example, it crops an image using pillow, and some delays are also included so that the time taken to create the image is more apparent.

@APP.route(‘/’)

def index():
   return render_template(‘index.html’)
@APP.route(‘/image_page’)
def image_page():
   job = tasks.get_data_from_strava.delay()
   return render_template(‘home.html’)
@APP.route('/result.png')
def result():
   '''
   Pull our generated .png binary from redis and return it
   '''
   jobid = request.values.get('jobid')
   if jobid:
      job = tasks.get_job(jobid)
      png_output = job.get()
      png_output="../"+png_output
      return png_output
   else:
      return 404

#rabbitmq #celery #flask #docker #redis