stamina
Production-grade retries made easy.
Decision gist · record as of 2026-08-14
Yes. Stamina is actively maintained with no known vulnerabilities and low install friction. It solves a real problem—production-grade retries—with sensible defaults and a clean API. Use it when you need resilience in distributed systems and want to avoid copy-pasting retry logic.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- Low install friction; pure Python wheel with a single runtime dependency (tenacity).
- Actively maintained with recent commits and 1440 GitHub stars.
License · maintenance · safety
MIT (permissive) — MIT license (permissive) allows use in commercial and proprietary projects with minimal restrictions; attribution required but no copyleft obligations.
last release 2026-04-13 (123 days) · last repo commit 2026-08-04 · 1,440 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 5,786,245 downloads/mo, #2,037 on PyPI
Alternatives
Verify before relying
pip install stamina
import stamina
@stamina.retry(on=Exception, attempts=3)
def do_it():
pass- Whether Prometheus instrumentation requires additional dependencies beyond tenacity.
- How structlog integration behaves when structlog is not installed.
- Performance overhead of retry instrumentation in high-throughput scenarios.
- Specific exception types and filtering capabilities beyond what the description excerpt shows.
What it is and what it does
Stamina is a retry library built on top of Tenacity that simplifies resilience patterns in distributed systems. It provides a decorator-based API that handles transient failures with exponential backoff, jitter, and configurable attempt and timeout limits. The library is designed to do the right thing by default—retrying only specified exceptions, respecting both attempt counts and total time budgets, and automatically supporting async functions including Trio.
The package includes first-class support for instrumentation via Prometheus, structlog, and standard logging, plus dedicated testing utilities to globally disable or limit retries during test runs. Type hints are preserved on decorated functions, and the same API works for both sync and async callables as well as arbitrary code blocks, making it suitable for I/O-heavy workloads where transient failures are common.
Use it for
- Decorate functions to automatically retry on transient errors with exponential backoff and jitter.
- Retry async functions with the same API as sync functions, including Trio support.
- Instrument retry behavior with Prometheus metrics or structured logging for observability.
- Globally disable retries in test suites or limit retry attempts to speed up test execution.
- Configure both attempt count and total timeout limits to bound retry behavior.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Stamina is actively maintained with no known vulnerabilities and low install friction. It solves a real problem—production-grade retries—with sensible defaults and a clean API. Use it when you need resilience in distributed systems and want to avoid copy-pasting retry logic.
Install
stamina on PyPI
Before you install
Low install friction; pure Python wheel with a single runtime dependency (tenacity). Actively maintained with recent commits and 1440 GitHub stars. Supports Python 3.10 through 3.14.
Requires Python 3.10 or later.
License in practice
MIT license (permissive) allows use in commercial and proprietary projects with minimal restrictions; attribution required but no copyleft obligations.
Quickstart
pip install stamina
import stamina
@stamina.retry(on=Exception, attempts=3)
def do_it():
passVerify before relying
- Whether Prometheus instrumentation requires additional dependencies beyond tenacity.
- How structlog integration behaves when structlog is not installed.
- Performance overhead of retry instrumentation in high-throughput scenarios.
- Specific exception types and filtering capabilities beyond what the description excerpt shows.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagetenacity |
| Maintenance | Actively maintained 123 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 5,786,245 / month, #2,037 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableFramework :: AsyncIOFramework :: TrioLicense :: OSI Approved :: MIT LicenseProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Typing :: Typed |
Evidence: stamina-26.1.0-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “production retry handling”
- staminaStamina wraps Tenacity to provide a production-ready retry decorator…
- retryhttpRetryhttp wraps HTTP client calls to automatically retry transient…
- pyramid-retrypyramid_retry wraps Pyramid requests with configurable retry logic,…
Give your agent the search over MCP, or paste the wish link into any chat.
More Distributed Computing packages
gRPC Python is an HTTP/2-based RPC framework that enables you to define and call remote procedures across network boundaries using protocol buffers for serialization.
Install it if you need RPC communication in a distributed system or are integrating with existing gRPC services.
execnet lets you spawn and communicate with Python interpreters across local processes, remote hosts, and different platforms, using a simple API for task distribution and inter-process messaging.
However, the aging maintenance status (275 days since last release) means you should verify it meets your concurrency and performance needs before committing to a…
Cloudpickle extends Python's standard pickle module to serialize lambda functions, interactively-defined functions and classes, and other constructs that the default pickle cannot handle, making it suitable for cluster computing and remote code execution.
Install it if you need to serialize lambda functions, interactively-defined code, or non-standard Python constructs for cluster computing or distributed execution.
Provides a unified, open()-compatible Python API for streaming large files from remote storage (S3, GCS, Azure, HDFS, SFTP, HTTP) and local filesystems, with transparent compression support.
Install it if you work with large files on cloud storage or remote systems and want to avoid writing boilerplate around multiple SDKs.
Portalocker provides cross-platform file locking with support for exclusive and shared locks, plus Redis-based distributed locks and process-aware PID file locking.
Install it if you need file or process coordination; the optional extras (pywin32, redis) are only required for specific lock types.
Ray is a distributed computing framework that scales Python applications from a single machine to multi-node clusters, providing abstractions for parallel tasks, stateful actors, and shared objects.
See also tenacity · reretry · retryhttp · justbackoff · backoff · retry2 · python-backoff · robust-downloader · retrying · retry-requests