example-in-django-waiting-room-for-asynchronous-tasks/waiting_room/tasks.py

from django.conf import settings
import redis
from huey.contrib.djhuey import task, lock_task
import operator
from django.template.loader import render_to_string
from itertools import permutations
from collections import Counter
from functools import reduce
from math import factorial
from channels.layers import get_channel_layer
from asgiref.sync import async_to_sync


def render_progress_bar(group_name, progress, result=None):
    channel_layer = get_channel_layer()
    async_to_sync(channel_layer.group_send)(
        group_name,
        {
            'type': 'channel_message',
            'message': render_to_string('components/tasks/update.html', {
                'progress': progress,
                'result': result,
            }),
        }
    )

def render_location_in_the_queue(group_name, location):
    channel_layer = get_channel_layer()
    async_to_sync(channel_layer.group_send)(
        group_name,
        {
            'type': 'channel_message',
            'message': render_to_string('components/tasks/location.html', {
                'location': location,
            }),
        }
    )

@task()
def calculate_min_distance(group_name):
    # Distance matrix between cities
    distances = [
        [0, 29, 20, 21, 16, 31, 100, 12, 5, 78],
        [29, 0, 15, 29, 28, 40, 72, 21, 29, 41],
        [20, 15, 0, 15, 14, 25, 81, 9, 23, 27],
        [21, 29, 15, 0, 4, 12, 92, 12, 25, 13],
        [16, 28, 14, 4, 0, 16, 94, 9, 20, 16],
        [31, 40, 25, 12, 16, 0, 95, 24, 36, 3],
        [100, 72, 81, 92, 94, 95, 0, 90, 101, 99],
        [12, 21, 9, 12, 9, 24, 90, 0, 15, 25],
        [5, 29, 23, 25, 20, 36, 101, 15, 0, 35],
        [78, 41, 27, 13, 16, 3, 99, 25, 35, 0],
    ]

    num_cities = len(distances)
    cities = list(range(num_cities))

    def count_permutations(sequence):
        total = factorial(len(sequence))
        duplicates = Counter(sequence).values()
        divisor = reduce(operator.mul, (factorial(v) for v in duplicates), 1)
        return total / divisor

    def calculate_shortest_route(distances):
        shortest_route = float("inf")
        city_count = 0

        # Calculate all possible permutations of cities (routes)
        total_permutations = count_permutations(cities)

        percentaje = 0
        for perm in permutations(cities):
            # Send progress to the group
            temp_percentaje = int(city_count / total_permutations * 100)
            if temp_percentaje != percentaje:
                percentaje = temp_percentaje
                render_progress_bar(group_name, percentaje)
            city_count += 1
            # Calculate the distance of the route
            route_distance = 0
            for i in range(num_cities - 1):
                route_distance += distances[perm[i]][perm[i + 1]]
            route_distance += distances[perm[-1]][perm[0]]  # Back to the start city
            shortest_route = min(shortest_route, route_distance)

        render_progress_bar(group_name, 100, shortest_route)
        return shortest_route

    return calculate_shortest_route(distances)

@task()
@lock_task('run-queue-lock')
def run_tasks_from_queue():
    notify_of_new_position()
    # Get the first task from the queue
    redis_conn = redis.StrictRedis(host=settings.REDIS_HOST, port=settings.REDIS_PORT, db=0)
    task = redis_conn.lindex('enqueue', 0)
    if task:
        # Run task
        r = calculate_min_distance(task.decode('utf-8'))
        # Wait for task to finish
        r(blocking=True)
        # Run the next task
        redis_conn.lpop('enqueue')
        run_tasks_from_queue()

@task()
def notify_of_new_position():
    redis_conn = redis.StrictRedis(host=settings.REDIS_HOST, port=settings.REDIS_PORT, db=0)
    for index, group_name in enumerate(redis_conn.lrange('enqueue', 0, -1)):
        render_location_in_the_queue(group_name.decode('utf-8'), index )