annotate contrib/python-zstandard/tests/test_data_structures_fuzzing.py @ 37495:b1fb341d8a61

zstandard: vendor python-zstandard 0.9.0

This was just released. It features a number of goodies. More info at
https://gregoryszorc.com/blog/2018/04/09/release-of-python-zstandard-0.9/.

The clang-format ignore list was updated to reflect the new source
of files.

The project contains a vendored copy of zstandard 1.3.4. The old
version was 1.1.3. One of the changes between those versions is that
zstandard is now dual licensed BSD + GPLv2 and the patent rights grant
has been removed. Good riddance.

The API should be backwards compatible. So no changes in core
should be needed. However, there were a number of changes in the
library that we'll want to adapt to. Those will be addressed in
subsequent commits.

Differential Revision: https://phab.mercurial-scm.org/D3198

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_searchlength = strategies.integers(min_value=zstd.SEARCHLENGTH_MIN,
                                     max_value=zstd.SEARCHLENGTH_MAX)
s_targetlength = strategies.integers(min_value=zstd.TARGETLENGTH_MIN,
                                     max_value=2**32)
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))


@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_searchlength, s_targetlength, s_strategy)
    def test_valid_init(self, windowlog, chainlog, hashlog, searchlog,
                        searchlength, targetlength, strategy):
        zstd.ZstdCompressionParameters(window_log=windowlog,
                                       chain_log=chainlog,
                                       hash_log=hashlog,
                                       search_log=searchlog,
                                       min_match=searchlength,
                                       target_length=targetlength,
                                       compression_strategy=strategy)

    @hypothesis.given(s_windowlog, s_chainlog, s_hashlog, s_searchlog,
                        s_searchlength, s_targetlength, s_strategy)
    def test_estimated_compression_context_size(self, windowlog, chainlog,
                                                hashlog, searchlog,
                                                searchlength, targetlength,
                                                strategy):
        if searchlength == zstd.SEARCHLENGTH_MIN and strategy in (zstd.STRATEGY_FAST, zstd.STRATEGY_GREEDY):
            searchlength += 1
        elif searchlength == zstd.SEARCHLENGTH_MAX and strategy != zstd.STRATEGY_FAST:
            searchlength -= 1

        p = zstd.ZstdCompressionParameters(window_log=windowlog,
                                           chain_log=chainlog,
                                           hash_log=hashlog,
                                           search_log=searchlog,
                                           min_match=searchlength,
                                           target_length=targetlength,
                                           compression_strategy=strategy)
        size = p.estimated_compression_context_size()