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Mastering Retries in Python with the Tenacity Library
Latest   Machine Learning

Mastering Retries in Python with the Tenacity Library

Last Updated on August 29, 2025 by Editorial Team

Author(s): Ganesh Bajaj

Originally published on Towards AI.

Mastering Retries in Python with the Tenacity Library

When writing production-ready software, one of the most common challenges developers face is unreliable operations. Maybe your API request fails because of a temporary network issue. Or your database query times out. Or an external service throttles you with a 429 error.

Mastering Retries in Python with the Tenacity Library

Photo by the blowup on Unsplash

The article delves into the importance of implementing retry logic in production-ready applications using the Tenacity library in Python. It explains how Tenacity simplifies the process of executing retries for unreliable operations such as API requests and database queries, discusses various configurations like stopping conditions and wait strategies, and emphasizes building resilience in applications. Practical examples illustrate its usage, concluding with suggestions for real-world scenarios and when not to use retries.

Read the full blog for free on Medium.

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