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automation: schedule an EC2Launch run on next boot...
automation: schedule an EC2Launch run on next boot Without this, launching EC2 instances constructed from the AMI won't go through the normal EC2 instance launch machinery. This missing machinery does important things like set up network routes to use the instance metadata service and process any UserData. Since EC2Launch now runs on subsequent boots and UserData is processed, we needed to make setting of UserData conditional on bootstrapping mode. Differential Revision: https://phab.mercurial-scm.org/D7113

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test_data_structures_fuzzing.py
76 lines | 3.5 KiB | text/x-python | PythonLexer
/ contrib / python-zstandard / tests / test_data_structures_fuzzing.py
import io
import os
import sys
import unittest
try:
import hypothesis
import hypothesis.strategies as strategies
except ImportError:
raise unittest.SkipTest('hypothesis not available')
import zstandard as zstd
from .common import (
make_cffi,
)
s_windowlog = strategies.integers(min_value=zstd.WINDOWLOG_MIN,
max_value=zstd.WINDOWLOG_MAX)
s_chainlog = strategies.integers(min_value=zstd.CHAINLOG_MIN,
max_value=zstd.CHAINLOG_MAX)
s_hashlog = strategies.integers(min_value=zstd.HASHLOG_MIN,
max_value=zstd.HASHLOG_MAX)
s_searchlog = strategies.integers(min_value=zstd.SEARCHLOG_MIN,
max_value=zstd.SEARCHLOG_MAX)
s_minmatch = strategies.integers(min_value=zstd.MINMATCH_MIN,
max_value=zstd.MINMATCH_MAX)
s_targetlength = strategies.integers(min_value=zstd.TARGETLENGTH_MIN,
max_value=zstd.TARGETLENGTH_MAX)
s_strategy = strategies.sampled_from((zstd.STRATEGY_FAST,
zstd.STRATEGY_DFAST,
zstd.STRATEGY_GREEDY,
zstd.STRATEGY_LAZY,
zstd.STRATEGY_LAZY2,
zstd.STRATEGY_BTLAZY2,
zstd.STRATEGY_BTOPT,
zstd.STRATEGY_BTULTRA,
zstd.STRATEGY_BTULTRA2))
@make_cffi
@unittest.skipUnless('ZSTD_SLOW_TESTS' in os.environ, 'ZSTD_SLOW_TESTS not set')
class TestCompressionParametersHypothesis(unittest.TestCase):
@hypothesis.given(s_windowlog, s_chainlog, s_hashlog, s_searchlog,
s_minmatch, s_targetlength, s_strategy)
def test_valid_init(self, windowlog, chainlog, hashlog, searchlog,
minmatch, targetlength, strategy):
zstd.ZstdCompressionParameters(window_log=windowlog,
chain_log=chainlog,
hash_log=hashlog,
search_log=searchlog,
min_match=minmatch,
target_length=targetlength,
strategy=strategy)
@hypothesis.given(s_windowlog, s_chainlog, s_hashlog, s_searchlog,
s_minmatch, s_targetlength, s_strategy)
def test_estimated_compression_context_size(self, windowlog, chainlog,
hashlog, searchlog,
minmatch, targetlength,
strategy):
if minmatch == zstd.MINMATCH_MIN and strategy in (zstd.STRATEGY_FAST, zstd.STRATEGY_GREEDY):
minmatch += 1
elif minmatch == zstd.MINMATCH_MAX and strategy != zstd.STRATEGY_FAST:
minmatch -= 1
p = zstd.ZstdCompressionParameters(window_log=windowlog,
chain_log=chainlog,
hash_log=hashlog,
search_log=searchlog,
min_match=minmatch,
target_length=targetlength,
strategy=strategy)
size = p.estimated_compression_context_size()