How do you build Python applications that can handle literally billions of requests?

It certainly has been done to great success with places like YouTube,

handling a million requests a second, and Instagram,

as well as internal pricing APIs at places like PayPal and other banks.

While Python can be fast at some operations and slow at others,

it's generally not so much about the language raw performance

as it is about building an architecture for that scale. That's why it's great to have Julian

Danjow on this show. We'll dive into his book, The Hacker's Guide to Scaling Python, as well as some

of his performance work he's been doing over at Datadog. This is Talk PythonMe, episode

312, recorded April 8th, 2021.

Welcome to Talk Python, a weekly podcast on Python, the language, the libraries, the ecosystem, and the personalities.

This is your host, Michael Kennedy. Follow me on Twitter where I'm at M. Kennedy, and keep up with the show and listen to past episodes at Talk Python.fm.

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This episode is brought you by 45 drives and us over at Talk Python Training.

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It really helps support the show.

Julian, welcome to Talk Python to me.

Thank you.

It's great to have you here.

I think we've got a bunch of fun stuff to talk about.

It's really interesting to think about how we go about building software

at scale. And one of the things that just, I don't know how you feel about it, reading your book,

...