---
id: retrying
version: "1.4.2"
license: Apache-2.0
license_treatment: permissive
maintenance: active
---

# retrying — Retrying

License: permissive · Maintenance: active · Popularity: top 1,000 on PyPI

## Install

pip install retrying
uv add retrying
poetry add retrying

## Description

# Retrying

Retrying is an Apache 2.0 licensed general-purpose retrying library, written in
Python, to simplify the task of adding retry behavior to just about anything.

The simplest use case is retrying a flaky function whenever an Exception occurs
until a value is returned.

```python
import random
from retrying import retry

@retry
def do_something_unreliable():
    if random.randint(0, 10) > 1:
        raise IOError("Broken sauce, everything is hosed!!!111one")
    else:
        return "Awesome sauce!"

print(do_something_unreliable())
```

## Features

- Generic Decorator API
- Specify stop condition (i.e. limit by number of attempts)
- Specify wait condition (i.e. exponential backoff sleeping between attempts)
- Customize retrying on Exceptions
- Customize retrying on expected returned result

## Examples

As you saw above, the default behavior is to retry forever without waiting.

```python
@retry
def never_give_up_never_surrender():
    print("Retry forever ignoring Exceptions, don't wait between retries")
```

Let's be a little less persistent and set some boundaries, such as the number of attempts before giving up.

```python
@retry(stop_max_attempt_number=7)
def...

## AI interpretation — verify before relying

Retrying is a decorator-based library that adds automatic retry logic to functions, supporting configurable stop conditions (attempt limits, time bounds), wait strategies (fixed delays, exponential backoff, random intervals), and exception/result-based retry decisions.

Verdict: Retrying is a lightweight, actively maintained retry utility with zero dependencies, permissive licensing, and broad Python version support. No known vulnerabilities and top-1000 popularity make it a low-risk choice for adding resilience to flaky operations.

[View on SkillFed](https://skillfed.io/packages/retrying) · [View on PyPI](https://pypi.org/project/retrying/)