python-botocore/tests/unit/retries/test_adaptive.py
2021-09-22 13:53:42 -07:00

172 lines
6.5 KiB
Python

from tests import mock
from tests import unittest
from botocore.retries import adaptive
from botocore.retries import standard
from botocore.retries import bucket
from botocore.retries import throttling
class FakeClock(bucket.Clock):
def __init__(self, timestamp_sequences):
self.timestamp_sequences = timestamp_sequences
self.sleep_call_amounts = []
def sleep(self, amount):
self.sleep_call_amounts.append(amount)
def current_time(self):
return self.timestamp_sequences.pop(0)
class TestCanCreateRetryHandler(unittest.TestCase):
def test_can_register_retry_handler(self):
client = mock.Mock()
limiter = adaptive.register_retry_handler(client)
self.assertEqual(
client.meta.events.register.call_args_list,
[mock.call('before-send', limiter.on_sending_request),
mock.call('needs-retry', limiter.on_receiving_response)]
)
class TestClientRateLimiter(unittest.TestCase):
def setUp(self):
self.timestamp_sequences = [0]
self.clock = FakeClock(self.timestamp_sequences)
self.token_bucket = mock.Mock(spec=bucket.TokenBucket)
self.rate_adjustor = mock.Mock(spec=throttling.CubicCalculator)
self.rate_clocker = mock.Mock(spec=adaptive.RateClocker)
self.throttling_detector = mock.Mock(
spec=standard.ThrottlingErrorDetector)
def create_client_limiter(self):
rate_limiter = adaptive.ClientRateLimiter(
rate_adjustor=self.rate_adjustor,
rate_clocker=self.rate_clocker,
token_bucket=self.token_bucket,
throttling_detector=self.throttling_detector,
clock=self.clock,
)
return rate_limiter
def test_bucket_bucket_acquisition_only_if_enabled(self):
rate_limiter = self.create_client_limiter()
rate_limiter.on_sending_request(request=mock.sentinel.request)
self.assertFalse(self.token_bucket.acquire.called)
def test_token_bucket_enabled_on_throttling_error(self):
rate_limiter = self.create_client_limiter()
self.throttling_detector.is_throttling_error.return_value = True
self.rate_clocker.record.return_value = 21
self.rate_adjustor.error_received.return_value = 17
rate_limiter.on_receiving_response()
# Now if we call on_receiving_response we should try to acquire
# token.
self.timestamp_sequences.append(1)
rate_limiter.on_sending_request(request=mock.sentinel.request)
self.assertTrue(self.token_bucket.acquire.called)
def test_max_rate_updated_on_success_response(self):
rate_limiter = self.create_client_limiter()
self.throttling_detector.is_throttling_error.return_value = False
self.rate_adjustor.success_received.return_value = 20
self.rate_clocker.record.return_value = 21
rate_limiter.on_receiving_response()
self.assertEqual(self.token_bucket.max_rate, 20)
def test_max_rate_cant_exceed_20_percent_max(self):
rate_limiter = self.create_client_limiter()
self.throttling_detector.is_throttling_error.return_value = False
# So if our actual measured sending rate is 20 TPS
self.rate_clocker.record.return_value = 20
# But the rate adjustor is telling us to go up to 100 TPS
self.rate_adjustor.success_received.return_value = 100
# The most we should go up is 2.0 * 20
rate_limiter.on_receiving_response()
self.assertEqual(self.token_bucket.max_rate, 2.0 * 20)
class TestRateClocker(unittest.TestCase):
def setUp(self):
self.timestamp_sequences = [0]
self.clock = FakeClock(self.timestamp_sequences)
self.rate_measure = adaptive.RateClocker(self.clock)
self.smoothing = 0.8
def test_initial_rate_is_0(self):
self.assertEqual(self.rate_measure.measured_rate, 0)
def test_time_updates_if_after_bucket_range(self):
self.timestamp_sequences.append(1)
# This should be 1 * 0.8 + 0 * 0.2, or just 0.8
self.assertEqual(self.rate_measure.record(), 0.8)
def test_can_measure_constant_rate(self):
# Timestamps of 1 every second indicate a rate of 1 TPS.
self.timestamp_sequences.extend(range(1, 21))
for _ in range(20):
self.rate_measure.record()
self.assertAlmostEqual(self.rate_measure.measured_rate, 1)
def test_uses_smoothing_to_favor_recent_weights(self):
self.timestamp_sequences.extend([
1,
1.5,
2,
2.5,
3,
3.5,
4,
# If we now wait 10 seconds (.1 TPS),
# our rate is somewhere between 2 TPS and .1 TPS.
14,
])
for _ in range(7):
self.rate_measure.record()
# We should almost be at 2.0 but not quite.
self.assertGreaterEqual(self.rate_measure.measured_rate, 1.99)
self.assertLessEqual(self.rate_measure.measured_rate, 2.0)
# With our last recording we now drop down between 0.1 and 2
# depending on our smoothing factor.
self.rate_measure.record()
self.assertGreaterEqual(self.rate_measure.measured_rate, 0.1)
self.assertLessEqual(self.rate_measure.measured_rate, 2.0)
def test_noop_when_delta_t_is_0(self):
self.timestamp_sequences.extend([
1,
1,
1,
2,
3
])
for _ in range(5):
self.rate_measure.record()
self.assertGreaterEqual(self.rate_measure.measured_rate, 1.0)
def test_times_are_grouped_per_time_bucket(self):
# Using our default of 0.5 time buckets, we have:
self.timestamp_sequences.extend([
0.1,
0.2,
0.3,
0.4,
0.49,
])
for _ in range(len(self.timestamp_sequences)):
self.rate_measure.record()
# This is showing the tradeoff we're making with measuring rates.
# we're currently in the window from 0 <= x < 0.5, which means
# we use the rate from the previous bucket, which is 0:
self.assertEqual(self.rate_measure.measured_rate, 0)
# However if we now add a new measurement that's in the next
# time bucket 0.5 <= x < 1.0
# we'll use the range from the previous bucket:
self.timestamp_sequences.append(0.5)
self.rate_measure.record()
# And our previous bucket will be:
# 12 * 0.8 + 0.2 * 0
self.assertEqual(self.rate_measure.measured_rate, 12 * 0.8)