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Python Apps that Scale to Billions of Users

Episode #312, published Sun, Apr 18, 2021, recorded Thu, Apr 8, 2021.

This episode is carbon neutral.
How do you build Python applications that can handling literally billions of requests. I has certainly been done to great success with places like YouTube (handling 1M requests / sec) 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 language raw performance as it is about building an architecture for this scale. That's why it's great to have Julian Danjou on the show today. We'll dive into his book "The Hacker's Guide to Scaling Python" as well as some of his performance work he's doing over at Datadog.


Links from the show

Julian on Twitter: @juldanjou
Scaling Python Book: scaling-python.com

DD Trace production profiling code: github.com
Futurist package: pypi.org
Tenacity package: tenacity.readthedocs.io
Cotyledon package: cotyledon.readthedocs.io
Locust.io Load Testing: locust.io
Datadog: datadoghq.com
daiquiri package: daiquiri.readthedocs.io

YouTube Live Stream Video: youtube.com
Episode transcripts: talkpython.fm

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Julien Danjou
Julien Danjou
Julien is an open-source software engineer for the last 20 years. He contributed to multiple free software projects, from Debian to OpenStack. During the day, he works as a Staff Engineer at Datadog in the Profiling team, where he built the Python profiler.
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