aboutsummaryrefslogtreecommitdiffstats
path: root/contrib/python/google-auth/py3/google/auth/_exponential_backoff.py
blob: 89853448f9fc71f47198d35607926361271d0dd1 (plain) (blame)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
# Copyright 2022 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#      http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import asyncio
import random
import time

from google.auth import exceptions

# The default amount of retry attempts
_DEFAULT_RETRY_TOTAL_ATTEMPTS = 3

# The default initial backoff period (1.0 second).
_DEFAULT_INITIAL_INTERVAL_SECONDS = 1.0

# The default randomization factor (0.1 which results in a random period ranging
# between 10% below and 10% above the retry interval).
_DEFAULT_RANDOMIZATION_FACTOR = 0.1

# The default multiplier value (2 which is 100% increase per back off).
_DEFAULT_MULTIPLIER = 2.0

"""Exponential Backoff Utility

This is a private module that implements the exponential back off algorithm.
It can be used as a utility for code that needs to retry on failure, for example
an HTTP request.
"""


class _BaseExponentialBackoff:
    """An exponential backoff iterator base class.

    Args:
        total_attempts Optional[int]:
            The maximum amount of retries that should happen.
            The default value is 3 attempts.
        initial_wait_seconds Optional[int]:
            The amount of time to sleep in the first backoff. This parameter
            should be in seconds.
            The default value is 1 second.
        randomization_factor Optional[float]:
            The amount of jitter that should be in each backoff. For example,
            a value of 0.1 will introduce a jitter range of 10% to the
            current backoff period.
            The default value is 0.1.
        multiplier Optional[float]:
            The backoff multipler. This adjusts how much each backoff will
            increase. For example a value of 2.0 leads to a 200% backoff
            on each attempt. If the initial_wait is 1.0 it would look like
            this sequence [1.0, 2.0, 4.0, 8.0].
            The default value is 2.0.
    """

    def __init__(
        self,
        total_attempts=_DEFAULT_RETRY_TOTAL_ATTEMPTS,
        initial_wait_seconds=_DEFAULT_INITIAL_INTERVAL_SECONDS,
        randomization_factor=_DEFAULT_RANDOMIZATION_FACTOR,
        multiplier=_DEFAULT_MULTIPLIER,
    ):
        if total_attempts < 1:
            raise exceptions.InvalidValue(
                f"total_attempts must be greater than or equal to 1 but was {total_attempts}"
            )

        self._total_attempts = total_attempts
        self._initial_wait_seconds = initial_wait_seconds

        self._current_wait_in_seconds = self._initial_wait_seconds

        self._randomization_factor = randomization_factor
        self._multiplier = multiplier
        self._backoff_count = 0

    @property
    def total_attempts(self):
        """The total amount of backoff attempts that will be made."""
        return self._total_attempts

    @property
    def backoff_count(self):
        """The current amount of backoff attempts that have been made."""
        return self._backoff_count

    def _reset(self):
        self._backoff_count = 0
        self._current_wait_in_seconds = self._initial_wait_seconds

    def _calculate_jitter(self):
        jitter_variance = self._current_wait_in_seconds * self._randomization_factor
        jitter = random.uniform(
            self._current_wait_in_seconds - jitter_variance,
            self._current_wait_in_seconds + jitter_variance,
        )

        return jitter


class ExponentialBackoff(_BaseExponentialBackoff):
    """An exponential backoff iterator. This can be used in a for loop to
    perform requests with exponential backoff.
    """

    def __init__(self, *args, **kwargs):
        super(ExponentialBackoff, self).__init__(*args, **kwargs)

    def __iter__(self):
        self._reset()
        return self

    def __next__(self):
        if self._backoff_count >= self._total_attempts:
            raise StopIteration
        self._backoff_count += 1

        if self._backoff_count <= 1:
            return self._backoff_count

        jitter = self._calculate_jitter()

        time.sleep(jitter)

        self._current_wait_in_seconds *= self._multiplier
        return self._backoff_count


class AsyncExponentialBackoff(_BaseExponentialBackoff):
    """An async exponential backoff iterator. This can be used in a for loop to
    perform async requests with exponential backoff.
    """

    def __init__(self, *args, **kwargs):
        super(AsyncExponentialBackoff, self).__init__(*args, **kwargs)

    def __aiter__(self):
        self._reset()
        return self

    async def __anext__(self):
        if self._backoff_count >= self._total_attempts:
            raise StopAsyncIteration
        self._backoff_count += 1

        if self._backoff_count <= 1:
            return self._backoff_count

        jitter = self._calculate_jitter()

        await asyncio.sleep(jitter)

        self._current_wait_in_seconds *= self._multiplier
        return self._backoff_count