Retrying in Python using tenacity

UpdatedMarch 2, 2026

•1 min read

Retrying in Python using tenacity

Constantin Lungu

Part of seriesPython for Data Engineers

title: "Retrying in Python using tenacity" seoTitle: "Python Retry Logic with Tenacity" seoDescription: "Learn how to simplify retry logic in Python using the tenacity package for handling exceptions and implementing back-off strategies" datePublished: Tue Aug 06 2024 20:59:59 GMT+0000 (Coordinated Universal Time) cuid: clziwm4x1000108l9bq2c3r32 slug: retrying-in-python-using-tenacity cover: https://cdn.hashnode.com/res/hashnode/image/stock/unsplash/Zn7MIaTSUSk/upload/204f62a31f25884d418184fc79f4353c.jpeg tags: python, data-engineering

tenacity - (noun) the quality or fact of continuing to exist; persistence.

If you ever need to retry something that might fail in Python, take a look at a specialized package like tenacity.

It helps you properly cover common scenarios like retrying only a particular type of exception, exponential back-off or even jitter (adding random variance in the retrying cadence so clients don't all retry at the same time).

Otherwise it's important to leverage great packages like these in our workflows and not reinvent the wheel when faced with problems many other people face day to day.

Check out a quick example of it in action below.

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Data Engineer with a passion for transforming complex data landscapes into insightful stories. Here on my blog, I share insights, challenges, and the ever-evolving dance of technology and business.