Module arvados.retry

Functions

def check_http_response_success(status_code)

Convert an HTTP status code to a loop control flag.

Pass this method a numeric HTTP status code. It returns True if the code indicates success, None if it indicates temporary failure, and False otherwise. You can use this as the success_check for a RetryLoop.

Implementation details: * Any 2xx result returns True. * A select few status codes, or any malformed responses, return None. 422 Unprocessable Entity is in this category. This may not meet the letter of the HTTP specification, but the Arvados API server will use it for various server-side problems like database connection errors. * Everything else returns False. Note that this includes 1xx and 3xx status codes. They don't indicate success, and you can't retry those requests verbatim.

def retry_method(orig_func)

Provide a default value for a method's num_retries argument.

This is a decorator for instance and class methods that accept a num_retries argument, with a None default. When the method is called without a value for num_retries, it will be set from the underlying instance or class' num_retries attribute.

Classes

class RetryLoop (num_retries, success_check=<function RetryLoop.<lambda>>, backoff_start=0, backoff_growth=2, save_results=1, max_wait=60)

Coordinate limited retries of code.

RetryLoop coordinates a loop that runs until it records a successful result or tries too many times, whichever comes first. Typical use looks like:

loop = RetryLoop(num_retries=2)
for tries_left in loop:
    try:
        result = do_something()
    except TemporaryError as error:
        log("error: {} ({} tries left)".format(error, tries_left))
    else:
        loop.save_result(result)
if loop.success():
    return loop.last_result()

Construct a new RetryLoop.

Arguments: * num_retries: The maximum number of times to retry the loop if it doesn't succeed. This means the loop could run at most 1+N times. * success_check: This is a function that will be called each time the loop saves a result. The function should return True if the result indicates loop success, False if it represents a permanent failure state, and None if the loop should continue. If no function is provided, the loop will end as soon as it records any result. * backoff_start: The number of seconds that must pass before the loop's second iteration. Default 0, which disables all waiting. * backoff_growth: The wait time multiplier after each iteration. Default 2 (i.e., double the wait time each time). * save_results: Specify a number to save the last N results that the loop recorded. These records are available through the results attribute, oldest first. Default 1. * max_wait: Maximum number of seconds to wait between retries.

Expand source code
class RetryLoop(object):
    """Coordinate limited retries of code.

    RetryLoop coordinates a loop that runs until it records a
    successful result or tries too many times, whichever comes first.
    Typical use looks like:

        loop = RetryLoop(num_retries=2)
        for tries_left in loop:
            try:
                result = do_something()
            except TemporaryError as error:
                log("error: {} ({} tries left)".format(error, tries_left))
            else:
                loop.save_result(result)
        if loop.success():
            return loop.last_result()
    """
    def __init__(self, num_retries, success_check=lambda r: True,
                 backoff_start=0, backoff_growth=2, save_results=1,
                 max_wait=60):
        """Construct a new RetryLoop.

        Arguments:
        * num_retries: The maximum number of times to retry the loop if it
          doesn't succeed.  This means the loop could run at most 1+N times.
        * success_check: This is a function that will be called each
          time the loop saves a result.  The function should return
          True if the result indicates loop success, False if it
          represents a permanent failure state, and None if the loop
          should continue.  If no function is provided, the loop will
          end as soon as it records any result.
        * backoff_start: The number of seconds that must pass before the
          loop's second iteration.  Default 0, which disables all waiting.
        * backoff_growth: The wait time multiplier after each iteration.
          Default 2 (i.e., double the wait time each time).
        * save_results: Specify a number to save the last N results
          that the loop recorded.  These records are available through
          the results attribute, oldest first.  Default 1.
        * max_wait: Maximum number of seconds to wait between retries.
        """
        self.tries_left = num_retries + 1
        self.check_result = success_check
        self.backoff_wait = backoff_start
        self.backoff_growth = backoff_growth
        self.max_wait = max_wait
        self.next_start_time = 0
        self.results = deque(maxlen=save_results)
        self._attempts = 0
        self._running = None
        self._success = None

    def __iter__(self):
        return self

    def running(self):
        return self._running and (self._success is None)

    def __next__(self):
        if self._running is None:
            self._running = True
        if (self.tries_left < 1) or not self.running():
            self._running = False
            raise StopIteration
        else:
            wait_time = max(0, self.next_start_time - time.time())
            time.sleep(wait_time)
            self.backoff_wait *= self.backoff_growth
            if self.backoff_wait > self.max_wait:
                self.backoff_wait = self.max_wait
        self.next_start_time = time.time() + self.backoff_wait
        self.tries_left -= 1
        return self.tries_left

    def save_result(self, result):
        """Record a loop result.

        Save the given result, and end the loop if it indicates
        success or permanent failure.  See __init__'s documentation
        about success_check to learn how to make that indication.
        """
        if not self.running():
            raise arvados.errors.AssertionError(
                "recorded a loop result after the loop finished")
        self.results.append(result)
        self._success = self.check_result(result)
        self._attempts += 1

    def success(self):
        """Return the loop's end state.

        Returns True if the loop obtained a successful result, False if it
        encountered permanent failure, or else None.
        """
        return self._success

    def last_result(self):
        """Return the most recent result the loop recorded."""
        try:
            return self.results[-1]
        except IndexError:
            raise arvados.errors.AssertionError(
                "queried loop results before any were recorded")

    def attempts(self):
        """Return the number of attempts that have been made.

        Includes successes and failures."""
        return self._attempts

    def attempts_str(self):
        """Human-readable attempts(): 'N attempts' or '1 attempt'"""
        if self._attempts == 1:
            return '1 attempt'
        else:
            return '{} attempts'.format(self._attempts)

Methods

def attempts(self)

Return the number of attempts that have been made.

Includes successes and failures.

def attempts_str(self)

Human-readable attempts(): 'N attempts' or '1 attempt'

def last_result(self)

Return the most recent result the loop recorded.

def running(self)
def save_result(self, result)

Record a loop result.

Save the given result, and end the loop if it indicates success or permanent failure. See init's documentation about success_check to learn how to make that indication.

def success(self)

Return the loop's end state.

Returns True if the loop obtained a successful result, False if it encountered permanent failure, or else None.