reretry

library0.11.8pypypi✓ verified 87d ago

Reretry is a Python library providing an easy-to-use, yet functional decorator for retrying functions on exceptions. It is a fork of the `retry` package, enhancing it with features like logging of traceback, callbacks after each failure, and support for `async` functions. Currently at version 0.11.8, it is actively maintained with a focus on providing a robust retry mechanism with minimal dependencies.

testing devops observability

pip install reretry

github ↗package ↗

INSTALL

IMPORT

SIG · RERETRY

reretry

testingpythonv0.11.8

Install

1.5s avg

Import

205ms

Disk

16MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.11.8 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.920 runs

installs and imports cleanly · install 0.0s · import 0.220s · 17.8MB

glibc

py 3.10–3.920 runs

installs and imports cleanly · install 1.5s · import 0.190s · 18MB

16MB installed

● package 16MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

retry

✓ from reretry import retry

This quickstart demonstrates both synchronous and asynchronous usage of the `@retry` decorator. The `flaky_sync_function` will retry up to 3 times with a 1-second delay on `ValueError`, while `flaky_async_function` retries twice with a 0.5-second delay on `RuntimeError`. The `asyncio.run()` is used to execute the asynchronous example.

import random import asyncio from reretry import retry attempt_count = 0 @retry(exceptions=ValueError, tries=3, delay=1) def flaky_sync_function(): global attempt_count attempt_count += 1 print(f"Sync function attempt {attempt_count}...") if random.randint(1, 10) < 7: raise ValueError("Sync operation failed!") print("Sync operation succeeded!") return "Success" async_attempt_count = 0 @retry(exceptions=RuntimeError, tries=2, delay=0.5) async def flaky_async_function(): global async_attempt_count async_attempt_count += 1 print(f"Async function attempt {async_attempt_count}...") if random.randint(1, 10) < 8: raise RuntimeError("Async operation failed!") print("Async operation succeeded!") return "Async Success" if __name__ == "__main__": print("\n--- Running Synchronous Example ---") try: result_sync = flaky_sync_function() print(f"Final sync result: {result_sync}") except Exception as e: print(f"Sync function ultimately failed: {e}") print("\n--- Running Asynchronous Example ---") try: result_async = asyncio.run(flaky_async_function()) print(f"Final async result: {result_async}") except Exception as e: print(f"Async function ultimately failed: {e}")

Debug

Known issues

breakingPython 3.5 support was dropped in `reretry` version 0.11.2. If you are using Python 3.5 or older, you must either upgrade your Python environment or pin `reretry` to a version older than 0.11.2.

fix

Upgrade to Python 3.7+ or use `pip install 'reretry<0.11.2'`.

affects: >=0.11.2

gotchaBy default, the `@retry` decorator is configured with `tries=-1`, meaning it will attempt to retry indefinitely until the decorated function succeeds or another unhandled exception occurs. This can lead to hung processes if not explicitly controlled.

fix

Always set a finite `tries` parameter (e.g., `tries=5`) or a `max_delay` (e.g., `max_delay=60`) to prevent infinite retries, especially in production environments.

affects: All

gotchaReretry is a fork of the `retry` package. While it aims to be mostly compatible, some differences in API, defaults, or available features might exist. Direct migration from the original `retry` library may require minor adjustments.

fix

Review `reretry`'s documentation, especially the decorator parameters and their defaults, if migrating from the `retry` library.

affects: All

Errors

Common errors & fixes

ModuleNotFoundError: No module named 'reretry'

The `reretry` package is not installed in the current Python environment or the environment is not activated.

fix

Install the package using pip: `pip install reretry`.

My decorated function isn't retrying; it just fails immediately.

The `exceptions` argument in `@retry` is not catching the specific exception being raised, or the `tries` limit is too low and quickly exhausted.

fix

Ensure the `exceptions` argument is set to catch the relevant exception type (e.g., `exceptions=(MyCustomError, ConnectionError)`) or use `exceptions=Exception` for a broad catch. Also, verify that the `tries` parameter is set to a sufficient number or is left at its default for infinite retries (though this is not recommended for production).

My async function decorated with @retry is not working or is hanging.

`reretry` introduced async function support in version 0.11.0. This error might occur if you are using an older version or if the async function is not properly awaited or run.

fix

Upgrade `reretry` to version 0.11.0 or newer (`pip install --upgrade reretry`). Ensure your async function is correctly called and awaited within an `async` context or executed using `asyncio.run()`.

Upgrade

Version history

0.11.8latest on PyPI · released Dec 18, 2022

Audit

Dependencies

decoratoroptionalOptionally preserves function signatures, not strictly required for core functionality.

Agent activity

20 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/leshchenko1979/reretry ↗

packagehttps://pypi.org/project/reretry/ ↗