structure saas with tools
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# Copyright 2022 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import asyncio
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import random
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import time
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from google.auth import exceptions
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# The default amount of retry attempts
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_DEFAULT_RETRY_TOTAL_ATTEMPTS = 3
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# The default initial backoff period (1.0 second).
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_DEFAULT_INITIAL_INTERVAL_SECONDS = 1.0
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# The default randomization factor (0.1 which results in a random period ranging
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# between 10% below and 10% above the retry interval).
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_DEFAULT_RANDOMIZATION_FACTOR = 0.1
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# The default multiplier value (2 which is 100% increase per back off).
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_DEFAULT_MULTIPLIER = 2.0
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"""Exponential Backoff Utility
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This is a private module that implements the exponential back off algorithm.
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It can be used as a utility for code that needs to retry on failure, for example
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an HTTP request.
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"""
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class _BaseExponentialBackoff:
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"""An exponential backoff iterator base class.
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Args:
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total_attempts Optional[int]:
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The maximum amount of retries that should happen.
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The default value is 3 attempts.
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initial_wait_seconds Optional[int]:
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The amount of time to sleep in the first backoff. This parameter
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should be in seconds.
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The default value is 1 second.
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randomization_factor Optional[float]:
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The amount of jitter that should be in each backoff. For example,
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a value of 0.1 will introduce a jitter range of 10% to the
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current backoff period.
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The default value is 0.1.
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multiplier Optional[float]:
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The backoff multipler. This adjusts how much each backoff will
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increase. For example a value of 2.0 leads to a 200% backoff
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on each attempt. If the initial_wait is 1.0 it would look like
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this sequence [1.0, 2.0, 4.0, 8.0].
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The default value is 2.0.
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"""
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def __init__(
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self,
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total_attempts=_DEFAULT_RETRY_TOTAL_ATTEMPTS,
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initial_wait_seconds=_DEFAULT_INITIAL_INTERVAL_SECONDS,
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randomization_factor=_DEFAULT_RANDOMIZATION_FACTOR,
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multiplier=_DEFAULT_MULTIPLIER,
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):
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if total_attempts < 1:
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raise exceptions.InvalidValue(
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f"total_attempts must be greater than or equal to 1 but was {total_attempts}"
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)
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self._total_attempts = total_attempts
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self._initial_wait_seconds = initial_wait_seconds
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self._current_wait_in_seconds = self._initial_wait_seconds
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self._randomization_factor = randomization_factor
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self._multiplier = multiplier
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self._backoff_count = 0
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@property
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def total_attempts(self):
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"""The total amount of backoff attempts that will be made."""
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return self._total_attempts
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@property
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def backoff_count(self):
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"""The current amount of backoff attempts that have been made."""
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return self._backoff_count
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def _reset(self):
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self._backoff_count = 0
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self._current_wait_in_seconds = self._initial_wait_seconds
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def _calculate_jitter(self):
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jitter_variance = self._current_wait_in_seconds * self._randomization_factor
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jitter = random.uniform(
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self._current_wait_in_seconds - jitter_variance,
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self._current_wait_in_seconds + jitter_variance,
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)
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return jitter
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class ExponentialBackoff(_BaseExponentialBackoff):
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"""An exponential backoff iterator. This can be used in a for loop to
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perform requests with exponential backoff.
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"""
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def __init__(self, *args, **kwargs):
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super(ExponentialBackoff, self).__init__(*args, **kwargs)
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def __iter__(self):
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self._reset()
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return self
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def __next__(self):
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if self._backoff_count >= self._total_attempts:
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raise StopIteration
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self._backoff_count += 1
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if self._backoff_count <= 1:
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return self._backoff_count
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jitter = self._calculate_jitter()
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time.sleep(jitter)
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self._current_wait_in_seconds *= self._multiplier
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return self._backoff_count
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class AsyncExponentialBackoff(_BaseExponentialBackoff):
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"""An async exponential backoff iterator. This can be used in a for loop to
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perform async requests with exponential backoff.
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"""
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def __init__(self, *args, **kwargs):
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super(AsyncExponentialBackoff, self).__init__(*args, **kwargs)
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def __aiter__(self):
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self._reset()
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return self
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async def __anext__(self):
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if self._backoff_count >= self._total_attempts:
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raise StopAsyncIteration
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self._backoff_count += 1
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if self._backoff_count <= 1:
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return self._backoff_count
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jitter = self._calculate_jitter()
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await asyncio.sleep(jitter)
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self._current_wait_in_seconds *= self._multiplier
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return self._backoff_count
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