Master Flaky Systems With Retries in Python 🐍 (avoid self-DDoS)

Every system fails eventually and your Python app is no different. And while failure is inevitable, downtime isn't. One of the key reliability tools in distributed systems are retries – so let's look how they can do more harm than good, and how to retry safely and easily in Python by using the stamina and httpx packages as examples. Both using a decorator and a smart loop-context manager combo!

🔗 Links

► https://stamina.hynek.me/
► https://tenacity.readthedocs.io/
► https://www.structlog.org/
► https://en.wikipedia.org/wiki/Thunder...
► https://en.wikipedia.org/wiki/Denial-...
► https://www.bbc.com/news/business-646...
► https://www.w3.org/Provider/Style/URI
► https://sre.google/books/
► https://how.complexsystems.fail
► https://en.wikipedia.org/wiki/Three_M...
► https://longform.asmartbear.com/scale...
►    • Hynek Schlawack   Solid Snakes or How to T...  

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🙏 CREDITS

Outro Music: ‪@RPLKTR‬ / https://rplktr.com/
Other music and material licensed from Envato.

📖 Chapters

00:00 Failures are a fact of life.
01:03 Who's talking?
01:54 Why retries?
02:46 Dangers of retries.
03:23 Backoffs
04:38 Timeouts
05:00 Jitters ☕️
05:20 A brief glimpse at advanced problems (feat. elementary school math)
06:44 Python: Tenacity
08:02 Introducing stamina
08:43 stamina: decorator
10:35 stamina: loop + context manager
11:03 stamina: RetryingCaller / AsyncRetryingCaller
12:02 stamina: testing helpers
13:04 stamina: instrumentation
14:29 Summary & takeaways
15:18 Thank you & goodbye! ❤️