Lal Zada BuildWithLal

	Python RQ	Celery
	Purely based on Redis	works with Redis Rabbitmq SQS and Zookeeper (experimental)
	RQ does not use an advanced broker to do the message routing	Celery does this thing very well
	Does not speak a portable protocol since it depends on pickle to serialize the jobs so its a Python only system	supports json yaml pickle msgpack which makes it able to produce task from any programming language
	Workers can also be started in burst mode to finish all currently available work and quit as soon as all given queues are emptied	Nothing similar in Celery
	only run on systems that implement fork(). Each worker will process a single job at a time. Within a worker there is no concurrent processing going on. If you want to perform jobs concurrently simply start more workers (using supervisor or systemd)	Celery works with fork gevent eventlet and solo and does auto scaling process within a single worker process
	RQ need supervisor to scale up processes(workers)	Celery has built-in option to auto scale processes

	html file(index.html)



	{% extends 'base.html' %}
	{% block content %}


	<button type="button" class="btn btn-info btn-lg" data-toggle="modal" data-target="#image_Modal">Add Image</button>

	# image create view

	if form.is_valid():
	images = Image.objects.order_by('-_id').all()
	if len(images)>0:
	# get latest image scene number
	scene_number = Images.first().scene_number + 1
	else:
	# creating first image so set scene_number =1
	scene_number = 1

	# add this js file /static/js/image_edit.js

	$(document).ready(function(){
	var width = window.innerWidth;
	var height = window.innerHeight;

	function update(activeAnchor) {
	var group = activeAnchor.getParent();

	var topLeft = group.get('.topLeft')[0];