Django single-file example for https://github.com/django/daphne/issues/170 (generates async data, streams over HTTP)

streaming_example.py

"""
To test this save this file in streaming_example.py and then:

python3 -m venv venv
. venv/bin/activate
pip3 install -e git+https://github.com/carltongibson/django.git@ea94a8ff95093d2c6925e41ac6b98a00c220d89f#egg=Django
pip3 install daphne==4.0.0
python3 streaming_example.py runserver
curl --no-buffer http://localhost:8000 # Expect memory usage to increase,
                                       # depending on asyncio.sleep() time
                                       # and speed of the consumer
                                       # (pause it to see faster memory
                                       # increase)

Structure of this file inspired by https://adamj.eu/tech/2019/04/03/django-versus-flask-with-single-file-applications/
"""
import asyncio
import os
import sys
from pathlib import Path

from django.conf import settings
from django.core.asgi import get_asgi_application
from django.core.exceptions import ImproperlyConfigured
from django.http import StreamingHttpResponse
from django.urls import path
from django.utils.crypto import get_random_string

try:
    getattr(settings, "ROOT_URLCONF")
except ImproperlyConfigured:
    settings.configure(
        DEBUG=(os.environ.get("DEBUG", "") == "1"),
        ALLOWED_HOSTS=["*"],
        ROOT_URLCONF=__name__,
        SECRET_KEY=get_random_string(
            50
        ),
        INSTALLED_APPS=["daphne"],
        ASGI_APPLICATION="{}.application".format(Path(__file__).stem)
    )

application = get_asgi_application()

async def generate_big_data():
    gb_to_send = 5
    chunk_size_mb = 5 * 1024 * 1024

    total_sent = 0
    count = 0

    while total_sent < gb_to_send * 1024 * 1024 * 1024:
        data = f"{count % 10}" * chunk_size_mb
        total_sent += len(data)
        count += 1
        # Change asyncio.sleep to generate data faster/slower
        await asyncio.sleep(0.0001)
        print("count", count, "Sent:", total_sent)
        yield data


def index(request):
    # Big data is streamed to the client
    # But if the client is slower to fetch than the generation
    # the memory usage will increase
    return StreamingHttpResponse(generate_big_data())


urlpatterns = [
    path("", index),
]

app = get_asgi_application()

if __name__ == "__main__":
    from django.core.management import execute_from_command_line

    execute_from_command_line(sys.argv)