contrib/python-zstandard/tests/test_data_structures_fuzzing.py

wireproto: support for pullbundles

Pullbundles are similar to clonebundles, but served as normal inline
bundle streams. They are almost transparent to the client -- the only
visible effect is that the client might get less changes than what it
asked for, i.e. not all requested head revisions are provided.

The client announces support for the necessary retries with the
partial-pull capability. After receiving a partial bundle, it updates
the set of revisions shared with the server and drops all now-known
heads from the request list. It will then rerun getbundle until
no changes are received or all remote heads are present.

Extend badserverext to support per-socket limit, i.e. don't assume that
the same limits should be applied to all sockets.

Differential Revision: https://phab.mercurial-scm.org/D1856

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()