Backoff-Utils
Python Library for Backoff/Retry Strategies
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Backoff-Utils is a Python library that provides Python functions and decorators
that apply various backoff / retry strategies to your Python function and method
calls.
The library has a consistent syntax for easy use, and has been tested on
Python 2.7, 3.4, 3.5, 3.6, 3.7 and 3.8.
COMPLETE DOCUMENTATION ON READTHEDOCS: http://backoff-utils.readthedocs.io/en/latest
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Installation
To install Backoff-Utils, just execute:
.. code:: bash
$ pip install backoff-utils
Importing
Once installed, to import Backoff-Utils into your project you can use:
.. code-block:: python
#: Import the backoff() function.
from backoff_utils import backoff
#: Import the @apply_backoff() decorator.
from backoff_utils import apply_backoff
#: Import backoff strategies.
from backoff_utils import strategies
Dependencies
By design, Backoff-Utils are designed to rely on minimal dependencies.
The only dependency they have outside of the Python standard library is:
-
validator-collection <https://github.com/insightindustry/validator-collection/>
_
which provides for robust validation functionality.
This library in turn has one external dependency when installed under Python 2.7:
regex <https://pypi.python.org/pypi/regex>
_ which is a drop-in replacement for
Python's (buggy) standard re
module.
Hello, World Example
.. code:: python
from backoff_utils import strategies
Using a Function Call
from backoff_utils import backoff
def some_function(arg1, arg2, kwarg1 = None):
# your code goes here
pass
result = backoff(some_function,
args = ['value1', 'value2'],
kwargs = { 'kwarg1': 'value3' },
max_tries = 3,
max_delay = 3600,
strategy = strategies.Exponential)
Using a Decorator
from backoff_utils import backoff
@apply_backoff(strategy = strategies.Exponential, max_tries = 3, max_delay = 3600)
def some_decorated_function(arg1, arg2, kwarg1 = None):
# your code goes here
pass
result = some_decorated_function('value1', 'value2', kwarg1 = 'value3')
Why Backoff-Utils?
.. epigraph::
Because now and again, stuff breaks.
Often, when making external API calls to third-party systems, something goes
wrong. The internet might glitch. The API we're calling might timeout. Gremlins
might eat your packets. Any number of things can go wrong, and Murphy's law tells
us that they will.
Which is why we need backoff strategies. Basically, these are techniques
that we can use to retry function calls after a given delay - and keep retrying
them until either the function call works, or until we've tried so many times that
we just give up and handle the error.
This library is meant to be an incredibly simple utility that provides a number
of easy-to-use backoff strategies. Its core API is to expose:
- the
backoff()
function, which lets you apply
a given backoff strategy to any Python function call, and; - the
@apply_backoff()
decorator, which lets
you decorate any function or method call so that a given backoff strategy is
always applied when the decorated function/method is called.
Library Features
Supported Strategies
The library supports five of the most-common backoff strategies that we've come
across:
- Exponential
- Fibonacci
- Fixed
- Linear
- Polynomial
In addtion, you can also create your own custom strategies as well.
For more information about the backoff strategies supported, please see:
Strategies Explained <https://backoff-utils.readthedocs.io/en/latest/strategies.html>
_
Additional Features
In addition to the basic strategies, the library also supports:
- random jitter
- argument-adjustment on retry
- selective exception capture
- chained backoff strategies
- failure handlers
- success handlers
- cut-off after max delay
- cut-off after max tries
- scaling
- minimum delay
For more information about the backoff strategies supported, please see:
Using the Library <https://backoff-utils.readthedocs.io/en/latest/using.html>
_
Feedback, Support, and Contributing
We're happy to maintain this library going forward, and would always love to
hear users' feedback - especially if you're running into issues.
Please report issues or questions on the
project's Github page <https://github.com/insightindustry/backoff-utils/issues>
_
For more information on contributing to the Backoff-Utils library, please see:
Contributor Guide <https://backoff-utils.readthedocs.io/en/latest/contributing.html>
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