Metadata-Version: 2.1
Name: redo
Version: 3.0.0
Summary: Utilities to retry Python callables.
Home-page: https://github.com/mozilla-releng/redo
Author: Ben Hearsum
Author-email: ben@hearsum.ca
License: MPL-2.0
Classifier: License :: OSI Approved :: Mozilla Public License 2.0 (MPL 2.0)
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
License-File: LICENSE
License-File: AUTHORS

Redo - Utilities to retry Python callables
==========================================

Introduction
************

Redo provides various means to add seamless ability to retry to any Python callable. Redo includes plain functions (``redo.retry``, ``redo.retry_async``), decorators (``redo.retriable``, ``redo.retriable_async``), and a context manager (``redo.retrying``) to enable you to integrate it in the best possible way for your project. As a bonus, a standalone interface is also included (``"retry"``).

Installation
************

For installing with pip, run following commands

::

    pip install redo

How To Use
**********

Below is the list of functions available

* retrier
* retry
* retry_async
* retriable
* retriable_async
* retrying (contextmanager)

retrier(attempts=5, sleeptime=10, max_sleeptime=300, sleepscale=1.5, jitter=1)
------------------------------------------------------------------------------

A generator function that sleeps between retries, handles exponential back off and jitter. The action you are retrying is meant to run after retrier yields. At each iteration, we sleep for ``sleeptime + random.randint(-jitter, jitter)``. Afterwards sleeptime is multiplied by sleepscale for the next iteration.

**Arguments Detail:**    

1. **attempts (int):** maximum number of times to try; defaults to 5
2. **sleeptime (float):** how many seconds to sleep between tries; defaults to 60s (one minute)
3. **max_sleeptime (float):** the longest we'll sleep, in seconds; defaults to 300s (five minutes)
4. **sleepscale (float):** how much to multiply the sleep time by each iteration; defaults to 1.5
5. **jitter (int):** random jitter to introduce to sleep time each iteration. the amount is chosen at random between ``[-jitter, +jitter]`` defaults to 1

**Output:** None, a maximum of ``attempts`` number of times

**Example:**

::

    >>> n = 0
    >>> for _ in retrier(sleeptime=0, jitter=0):
    ...     if n == 3:
    ...         # We did the thing!
    ...         break
    ...     n += 1
    >>> n
    3
    >>> n = 0
    >>> for _ in retrier(sleeptime=0, jitter=0):
    ...     if n == 6:
    ...         # We did the thing!
    ...         break
    ...     n += 1
    ... else:
    ...     print("max tries hit")
    max tries hit

retry(action, attempts=5, sleeptime=60, max_sleeptime=5 * 60, sleepscale=1.5, jitter=1, retry_exceptions=(Exception,), cleanup=None, args=(), kwargs={})  
--------------------------------------------------------------------------------------------------------------------------------------------------------

Calls an action function until it succeeds, or we give up.

**Arguments Detail:**  

1. **action (callable):** the function to retry
2. **attempts (int):** maximum number of times to try; defaults to 5
3. **sleeptime (float):** how many seconds to sleep between tries; defaults to 60s (one minute)
4. **max_sleeptime (float):** the longest we'll sleep, in seconds; defaults to 300s (five minutes)
5. **sleepscale (float):** how much to multiply the sleep time by each iteration; defaults to 1.5
6. **jitter (int):** random jitter to introduce to sleep time each iteration. The amount is chosen at random between ``[-jitter, +jitter]`` defaults to 1
7. **retry_exceptions (tuple):** tuple of exceptions to be caught. If other exceptions are raised by ``action()``, then these are immediately re-raised to the caller.
8. **cleanup (callable):** optional; called if one of ``retry_exceptions`` is caught. No arguments are passed to the cleanup function; if your cleanup requires arguments, consider using ``functools.partial`` or a ``lambda`` function.
9. **args (tuple):** positional arguments to call ``action`` with
10. **kwargs (dict):** keyword arguments to call ``action`` with

**Output:** Whatever action(\*args, \*\*kwargs) returns
 
**Output:** Whatever action(\*args, \*\*kwargs) raises. ``retry_exceptions`` are caught up until the last attempt, in which case they are re-raised.

**Example:**

::

    >>> count = 0
    >>> def foo():
    ...     global count
    ...     count += 1
    ...     print(count)
    ...     if count < 3:
    ...         raise ValueError("count is too small!")
    ...     return "success!"
    >>> retry(foo, sleeptime=0, jitter=0)
    1
    2
    3
    'success!'

retry_async(func, attempts=5, sleeptime_callback=calculate_sleep_time, retry_exceptions=Exception, args=(), kwargs={}, sleeptime_kwargs=None)
---------------------------------------------------------------------------------------------------------------------------------------------

An asynchronous function that retries a given async callable.

**Arguments Detail:**

1. **func (function):** an awaitable function to retry
2. **attempts (int):** maximum number of attempts; defaults to 5
3. **sleeptime_callback (function):** function to determine sleep time after each attempt; defaults to `calculateSleepTime`
4. **retry_exceptions (list or exception):** exceptions to retry on; defaults to `Exception`
5. **args (list):** arguments to pass to `func`
6. **kwargs (dict):** keyword arguments to pass to `func`
7. **sleeptime_kwargs (dict):** keyword arguments to pass to `sleeptime_callback`

**Output:** The value from a successful `func` call or raises an exception after exceeding attempts.

**Example:**

::

    >>> async def async_action():
    ...     # Your async code here
    >>> result = await retry_async(async_action)

retriable(\*retry_args, \*\*retry_kwargs)
-----------------------------------------

A decorator factory for ``retry()``. Wrap your function in ``@retriable(...)`` to give it retry powers!

**Arguments Detail:** Same as for ``retry``, with the exception of ``action``, ``args``, and ``kwargs``, which are left to the normal function definition.

**Output:** A function decorator

**Example:**

::

    >>> count = 0
    >>> @retriable(sleeptime=0, jitter=0)
    ... def foo():
    ...     global count
    ...     count += 1
    ...     print(count)
    ...     if count < 3:
    ...         raise ValueError("count too small")
    ...     return "success!"
    >>> foo()
    1
    2
    3
    'success!'

retriable_async(retry_exceptions=Exception, sleeptime_kwargs=None)
------------------------------------------------------------------

A decorator for asynchronously retrying a function.

**Arguments Detail:**

1. **retry_exceptions (list or exception):** exceptions to retry on; defaults to `Exception`
2. **sleeptime_kwargs (dict):** keyword arguments to pass to the sleeptime callback

**Output:** A function decorator that applies `retry_async` to the decorated function.

**Example:**

::

    >>> @retriable_async()
    ... async def async_action():
    ...     # Your async code here
    >>> result = await async_action()

retrying(func, \*retry_args, \*\*retry_kwargs)
----------------------------------------------

A context manager for wrapping functions with retry functionality.

**Arguments Detail:**   

1. **func (callable):** the function to wrap other arguments as per ``retry``

**Output:** A context manager that returns ``retriable(func)`` on ``__enter__``

**Example:**

::

    >>> count = 0
    >>> def foo():
    ...     global count
    ...     count += 1
    ...     print(count)
    ...     if count < 3:
    ...         raise ValueError("count too small")
    ...     return "success!"
    >>> with retrying(foo, sleeptime=0, jitter=0) as f:
    ...     f()
    1
    2
    3
    'success!'