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#515: Durable Python Execution with Temporal

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Manage episode 499622329 series 83399
Content provided by Michael Kennedy. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Michael Kennedy or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
What if your code was crash-proof? That's the value prop for a framework called Temporal. Temporal is a durable execution platform that enables developers to build scalable applications without sacrificing productivity or reliability. The Temporal server executes units of application logic called Workflows in a resilient manner that automatically handles intermittent failures, and retries failed operations. We have Mason Egger from Temporal on to dive into durable execution.
Episode sponsors
Posit
PyBay
Talk Python Courses

Links from the show

Just Enough Python for Data Scientists Course: talkpython.fm
Temporal Durable Execution Platform: temporal.io
Temporal Learn Portal: learn.temporal.io
Temporal GitHub Repository: github.com
Temporal Python SDK GitHub Repository: github.com
What Is Durable Execution, Temporal Blog: temporal.io
Mason on Bluesky Profile: bsky.app
Mason on Mastodon Profile: fosstodon.org
Mason on Twitter Profile: twitter.com
Mason on LinkedIn Profile: linkedin.com
X Post by @skirano: x.com
Temporal Docker Compose GitHub Repository: github.com
Building a distributed asyncio event loop (Chad Retz) - PyTexas 2025: youtube.com
Watch this episode on YouTube: youtube.com
Episode #515 deep-dive: talkpython.fm/515
Episode transcripts: talkpython.fm
Theme Song: Developer Rap
🥁 Served in a Flask 🎸: talkpython.fm/flasksong
---== Don't be a stranger ==---
YouTube: youtube.com/@talkpython
Bluesky: @talkpython.fm
Mastodon: @[email protected]
X.com: @talkpython
Michael on Bluesky: @mkennedy.codes
Michael on Mastodon: @[email protected]
Michael on X.com: @mkennedy
  continue reading

566 episodes

Artwork
iconShare
 
Manage episode 499622329 series 83399
Content provided by Michael Kennedy. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Michael Kennedy or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
What if your code was crash-proof? That's the value prop for a framework called Temporal. Temporal is a durable execution platform that enables developers to build scalable applications without sacrificing productivity or reliability. The Temporal server executes units of application logic called Workflows in a resilient manner that automatically handles intermittent failures, and retries failed operations. We have Mason Egger from Temporal on to dive into durable execution.
Episode sponsors
Posit
PyBay
Talk Python Courses

Links from the show

Just Enough Python for Data Scientists Course: talkpython.fm
Temporal Durable Execution Platform: temporal.io
Temporal Learn Portal: learn.temporal.io
Temporal GitHub Repository: github.com
Temporal Python SDK GitHub Repository: github.com
What Is Durable Execution, Temporal Blog: temporal.io
Mason on Bluesky Profile: bsky.app
Mason on Mastodon Profile: fosstodon.org
Mason on Twitter Profile: twitter.com
Mason on LinkedIn Profile: linkedin.com
X Post by @skirano: x.com
Temporal Docker Compose GitHub Repository: github.com
Building a distributed asyncio event loop (Chad Retz) - PyTexas 2025: youtube.com
Watch this episode on YouTube: youtube.com
Episode #515 deep-dive: talkpython.fm/515
Episode transcripts: talkpython.fm
Theme Song: Developer Rap
🥁 Served in a Flask 🎸: talkpython.fm/flasksong
---== Don't be a stranger ==---
YouTube: youtube.com/@talkpython
Bluesky: @talkpython.fm
Mastodon: @[email protected]
X.com: @talkpython
Michael on Bluesky: @mkennedy.codes
Michael on Mastodon: @[email protected]
Michael on X.com: @mkennedy
  continue reading

566 episodes

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