Asynchronous programming

Synchronous execution

Parallel and concurrent computing

Parallel data processing

Task parallelism

How we run our server


> poetry run daphne -b 0.0.0.0 -p $PORT boshi.asgi:application

In short

We use parallel task execution as horizontal scaling in order to serve more requests

at the same time

Problem

More running dynos
mean more money.

What else we can do?

Concurrency!

In short

With the help of asynchronous programming, we can utilise the idle time because of IO operations to process more requests at the same time in a concurrent fashion

This is why NodeJS is good at non-blocking I/O, but bad at CPU intensive operations

It is also possible

in Python!

Daphne is ASGI


> poetry run daphne -b 0.0.0.0 -p $PORT boshi.asgi:application

Django supports


async for author in Author.objects.filter(name__startswith="A"):
    book = await author.books.afirst()

async def make_book_with_tags(tags, *args, **kwargs):
    book = await Book.objects.acreate(...)
    await book.tags.aset(tags)

Even faster


> poetry run uvicorn --loop uvloop --port $PORT boshi.asgi:application

The combination of horizontal scaling (parallel task processing) and asynchronous programming (concurrency) is the best for higher request numbers.

Thanks!

Made with Slides.com