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Tenacity

Please refer to the tenacity documentation for a better experience.

Tenacity 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. It originates from a fork of retrying which is sadly no longer maintained. Tenacity isn't api compatible with retrying but adds significant new functionality and fixes a number of longstanding bugs.

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

.. testcode::

    import random
    from tenacity 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())

.. testoutput::
   :hide:

   Awesome sauce!

.. toctree::
    :hidden:
    :maxdepth: 2

    changelog
    api

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
Retry on coroutines
Retry code block with context manager

Installation

To install tenacity, simply:

$ pip install tenacity

Examples

Basic Retry

.. testsetup::

    import logging
    #
    # Note the following import is used for demonstration convenience only.
    # Production code should always explicitly import the names it needs.
    #
    from tenacity import *

    class MyException(Exception):
        pass

As you saw above, the default behavior is to retry forever without waiting when an exception is raised.

.. testcode::

    @retry
    def never_gonna_give_you_up():
        print("Retry forever ignoring Exceptions, don't wait between retries")
        raise Exception

Stopping

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

.. testcode::

    @retry(stop=stop_after_attempt(7))
    def stop_after_7_attempts():
        print("Stopping after 7 attempts")
        raise Exception

We don't have all day, so let's set a boundary for how long we should be retrying stuff.

.. testcode::

    @retry(stop=stop_after_delay(10))
    def stop_after_10_s():
        print("Stopping after 10 seconds")
        raise Exception

If you're on a tight deadline, and exceeding your delay time isn't ok, then you can give up on retries one attempt before you would exceed the delay.

.. testcode::

    @retry(stop=stop_before_delay(10))
    def stop_before_10_s():
        print("Stopping 1 attempt before 10 seconds")
        raise Exception

You can combine several stop conditions by using the | operator:

.. testcode::

    @retry(stop=(stop_after_delay(10) | stop_after_attempt(5)))
    def stop_after_10_s_or_5_retries():
        print("Stopping after 10 seconds or 5 retries")
        raise Exception

Waiting before retrying

Most things don't like to be polled as fast as possible, so let's just wait 2 seconds between retries.

.. testcode::

    @retry(wait=wait_fixed(2))
    def wait_2_s():
        print("Wait 2 second between retries")
        raise Exception

Some things perform best with a bit of randomness injected.

.. testcode::

    @retry(wait=wait_random(min=1, max=2))
    def wait_random_1_to_2_s():
        print("Randomly wait 1 to 2 seconds between retries")
        raise Exception

Then again, it's hard to beat exponential backoff when retrying distributed services and other remote endpoints.

.. testcode::

    @retry(wait=wait_exponential(multiplier=1, min=4, max=10))
    def wait_exponential_1():
        print("Wait 2^x * 1 second between each retry starting with 4 seconds, then up to 10 seconds, then 10 seconds afterwards")
        raise Exception

Then again, it's also hard to beat combining fixed waits and jitter (to help avoid thundering herds) when retrying distributed services and other remote endpoints.

.. testcode::

    @retry(wait=wait_fixed(3) + wait_random(0, 2))
    def wait_fixed_jitter():
        print("Wait at least 3 seconds, and add up to 2 seconds of random delay")
        raise Exception

When multiple processes are in contention for a shared resource, exponentially increasing jitter helps minimise collisions.

.. testcode::

    @retry(wait=wait_random_exponential(multiplier=1, max=60))
    def wait_exponential_jitter():
        print("Randomly wait up to 2^x * 1 seconds between each retry until the range reaches 60 seconds, then randomly up to 60 seconds afterwards")
        raise Exception

Sometimes it's necessary to build a chain of backoffs.

.. testcode::

    @retry(wait=wait_chain(*[wait_fixed(3) for i in range(3)] +
                           [wait_fixed(7) for i in range(2)] +
                           [wait_fixed(9)]))
    def wait_fixed_chained():
        print("Wait 3s for 3 attempts, 7s for the next 2 attempts and 9s for all attempts thereafter")
        raise Exception

Whether to retry

We have a few options for dealing with retries that raise specific or general exceptions, as in the cases here.

.. testcode::

    class ClientError(Exception):
        """Some type of client error."""

    @retry(retry=retry_if_exception_type(IOError))
    def might_io_error():
        print("Retry forever with no wait if an IOError occurs, raise any other errors")
        raise Exception

    @retry(retry=retry_if_not_exception_type(ClientError))
    def might_client_error():
        print("Retry forever with no wait if any error other than ClientError occurs. Immediately raise ClientError.")
        raise Exception

We can also use the result of the function to alter the behavior of retrying.

.. testcode::

    def is_none_p(value):
        """Return True if value is None"""
        return value is None

    @retry(retry=retry_if_result(is_none_p))
    def might_return_none():
        print("Retry with no wait if return value is None")

Error Handling

Normally when your function fails its final time (and will not be retried again based on your settings), a RetryError is raised. The exception your code encountered will be shown somewhere in the middle of the stack trace.

If you would rather see the exception your code encountered at the end of the stack trace (where it is most visible), you can set reraise=True.

.. testcode::

    @retry(reraise=True, stop=stop_after_attempt(3))
    def raise_my_exception():
        raise MyException("Fail")

    try:
        raise_my_exception()
    except MyException:
        # timed out retrying
        pass

Before and After Retry, and Logging

It's possible to execute an action before any attempt of calling the function by using the before callback function:

.. testcode::

    import logging
    import sys

    logging.basicConfig(stream=sys.stderr, level=logging.DEBUG)

    logger = logging.getLogger(__name__)

    @retry(stop=stop_after_attempt(3), before=before_log(logger, logging.DEBUG))
    def raise_my_exception():
        raise MyException("Fail")

In the same spirit, It's possible to execute after a call that failed:

.. testcode::

    import logging
    import sys

    logging.basicConfig(stream=sys.stderr, level=logging.DEBUG)

    logger = logging.getLogger(__name__)

    @retry(stop=stop_after_attempt(3), after=after_log(logger, logging.DEBUG))
    def raise_my_exception():
        raise MyException("Fail")

It's also possible to only log failures that are going to be retried. Normally retries happen after a wait interval, so the keyword argument is called before_sleep:

.. testcode::

    import logging
    import sys

    logging.basicConfig(stream=sys.stderr, level=logging.DEBUG)

    logger = logging.getLogger(__name__)

    @retry(stop=stop_after_attempt(3),
           before_sleep=before_sleep_log(logger, logging.DEBUG))
    def raise_my_exception():
        raise MyException("Fail")

Statistics

You can access the statistics about the retry made over a function by using the statistics attribute attached to the function:

.. testcode::

    @retry(stop=stop_after_attempt(3))
    def raise_my_exception():
        raise MyException("Fail")

    try:
        raise_my_exception()
    except Exception:
        pass

    print(raise_my_exception.statistics)

.. testoutput::
   :hide:

   ...

Custom Callbacks

You can also define your own callbacks. The callback should accept one parameter called retry_state that contains all information about current retry invocation.

For example, you can call a custom callback function after all retries failed, without raising an exception (or you can re-raise or do anything really)

.. testcode::

    def return_last_value(retry_state):
        """return the result of the last call attempt"""
        return retry_state.outcome.result()

    def is_false(value):
        """Return True if value is False"""
        return value is False

    # will return False after trying 3 times to get a different result
    @retry(stop=stop_after_attempt(3),
           retry_error_callback=return_last_value,
           retry=retry_if_result(is_false))
    def eventually_return_false():
        return False

RetryCallState

retry_state argument is an object of :class:`~tenacity.RetryCallState` class.

Other Custom Callbacks

It's also possible to define custom callbacks for other keyword arguments.

.. function:: my_stop(retry_state)

   :param RetryCallState retry_state: info about current retry invocation
   :return: whether or not retrying should stop
   :rtype: bool

.. function:: my_wait(retry_state)

   :param RetryCallState retry_state: info about current retry invocation
   :return: number of seconds to wait before next retry
   :rtype: float

.. function:: my_retry(retry_state)

   :param RetryCallState retry_state: info about current retry invocation
   :return: whether or not retrying should continue
   :rtype: bool

.. function:: my_before(retry_state)

   :param RetryCallState retry_state: info about current retry invocation

.. function:: my_after(retry_state)

   :param RetryCallState retry_state: info about current retry invocation

.. function:: my_before_sleep(retry_state)

   :param RetryCallState retry_state: info about current retry invocation

Here's an example with a custom before_sleep function:

.. testcode::

    import logging

    logging.basicConfig(stream=sys.stderr, level=logging.DEBUG)

    logger = logging.getLogger(__name__)

    def my_before_sleep(retry_state):
        if retry_state.attempt_number < 1:
            loglevel = logging.INFO
        else:
            loglevel = logging.WARNING
        logger.log(
            loglevel, 'Retrying %s: attempt %s ended with: %s',
            retry_state.fn, retry_state.attempt_number, retry_state.outcome)

    @retry(stop=stop_after_attempt(3), before_sleep=my_before_sleep)
    def raise_my_exception():
        raise MyException("Fail")

    try:
        raise_my_exception()
    except RetryError:
        pass

Changing Arguments at Run Time

You can change the arguments of a retry decorator as needed when calling it by using the retry_with function attached to the wrapped function:

.. testcode::

    @retry(stop=stop_after_attempt(3))
    def raise_my_exception():
        raise MyException("Fail")

    try:
        raise_my_exception.retry_with(stop=stop_after_attempt(4))()
    except Exception:
        pass

    print(raise_my_exception.statistics)

.. testoutput::
   :hide:

   ...

If you want to use variables to set up the retry parameters, you don't have to use the retry decorator - you can instead use Retrying directly:

.. testcode::

    def never_good_enough(arg1):
        raise Exception('Invalid argument: {}'.format(arg1))

    def try_never_good_enough(max_attempts=3):
        retryer = Retrying(stop=stop_after_attempt(max_attempts), reraise=True)
        retryer(never_good_enough, 'I really do try')

You may also want to change the behaviour of a decorated function temporarily, like in tests to avoid unnecessary wait times. You can modify/patch the retry attribute attached to the function. Bear in mind this is a write-only attribute, statistics should be read from the function statistics attribute.

.. testcode::

    @retry(stop=stop_after_attempt(3), wait=wait_fixed(3))
    def raise_my_exception():
        raise MyException("Fail")

    from unittest import mock

    with mock.patch.object(raise_my_exception.retry, "wait", wait_fixed(0)):
        try:
            raise_my_exception()
        except Exception:
            pass

    print(raise_my_exception.statistics)

.. testoutput::
   :hide:

   ...

Retrying code block

Tenacity allows you to retry a code block without the need to wraps it in an isolated function. This makes it easy to isolate failing block while sharing context. The trick is to combine a for loop and a context manager.

.. testcode::

   from tenacity import Retrying, RetryError, stop_after_attempt

   try:
       for attempt in Retrying(stop=stop_after_attempt(3)):
           with attempt:
               raise Exception('My code is failing!')
   except RetryError:
       pass

You can configure every details of retry policy by configuring the Retrying object.

With async code you can use AsyncRetrying.

.. testcode::

   from tenacity import AsyncRetrying, RetryError, stop_after_attempt

   async def function():
      try:
          async for attempt in AsyncRetrying(stop=stop_after_attempt(3)):
              with attempt:
                  raise Exception('My code is failing!')
      except RetryError:
          pass

In both cases, you may want to set the result to the attempt so it's available in retry strategies like retry_if_result. This can be done accessing the retry_state property:

.. testcode::

    from tenacity import AsyncRetrying, retry_if_result

    async def function():
       async for attempt in AsyncRetrying(retry=retry_if_result(lambda x: x < 3)):
           with attempt:
               result = 1  # Some complex calculation, function call, etc.
           if not attempt.retry_state.outcome.failed:
               attempt.retry_state.set_result(result)
       return result

Async and retry

Finally, retry works also on asyncio, Trio, and Tornado (>= 4.5) coroutines. Sleeps are done asynchronously too.

@retry
async def my_asyncio_function(loop):
    await loop.getaddrinfo('8.8.8.8', 53)

@retry
async def my_async_trio_function():
    await trio.socket.getaddrinfo('8.8.8.8', 53)

@retry
@tornado.gen.coroutine
def my_async_tornado_function(http_client, url):
    yield http_client.fetch(url)

You can even use alternative event loops such as curio by passing the correct sleep function:

@retry(sleep=curio.sleep)
async def my_async_curio_function():
    await asks.get('https://example.org')

Contribute

Check for open issues or open a fresh issue to start a discussion around a feature idea or a bug.
Fork the repository on GitHub to start making your changes to the main branch (or branch off of it).
Write a test which shows that the bug was fixed or that the feature works as expected.
Add a changelog
Make the docs better (or more detailed, or more easier to read, or ...)

Changelogs

reno is used for managing changelogs. Take a look at their usage docs.

The doc generation will automatically compile the changelogs. You just need to add them.

# Opens a template file in an editor
tox -e reno -- new some-slug-for-my-change --edit

jd / tenacity Goto Github PK

tenacity's Introduction

Tenacity

Features

Installation

Examples

Basic Retry

Stopping

Waiting before retrying

Whether to retry

Error Handling

Before and After Retry, and Logging

Statistics

Custom Callbacks

RetryCallState

Other Custom Callbacks

Changing Arguments at Run Time

Retrying code block

Async and retry

Contribute

Changelogs

tenacity's People

Contributors

Stargazers

Watchers

Forkers

tenacity's Issues

pip install

Python version

pip list

Distribution used

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