##// END OF EJS Templates
fuzz: use a more standard approach to allow local builds of fuzzers...
fuzz: use a more standard approach to allow local builds of fuzzers This is taken from the (improved since we started fuzzing) guide on ideal integrations. Rather than have our own wonky targets for building outside the fuzzer universe, we have a driver program we carry along and use when we're not using LibFuzzer. This will let us jettison a fair amount of goo. contrib/fuzz/standalone_fuzz_target_runner.cc is https://github.com/google/oss-fuzz/ file projects/example/my-api-repo/standalone from git revision c4579d9358a73ea5dbcc99cb985de1f2bf76dcf7, reformatted with out clang-format settings and a no-check-code comment added. It allows running a single test input through a fuzzer, rather than performing ongoing fuzzing as libfuzzer would. contrib/fuzz/FuzzedDataProvider.h is https://github.com/llvm/llvm-project/ file /compiler-rt/include/fuzzer/FuzzedDataProvider.h from git revision a44ef027ebca1598892ea9b104d6189aeb3bc2f0, reformatted with our clang-format settings and a no-check-code comment added. We can discard this if we instead want to add an hghave check for a new enough llvm that includes FuzzedDataProvder.h in the fuzzer headers. Differential Revision: https://phab.mercurial-scm.org/D7564

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test_train_dictionary.py
89 lines | 2.8 KiB | text/x-python | PythonLexer
import struct
import sys
import unittest
import zstandard as zstd
from . common import (
generate_samples,
make_cffi,
random_input_data,
)
if sys.version_info[0] >= 3:
int_type = int
else:
int_type = long
@make_cffi
class TestTrainDictionary(unittest.TestCase):
def test_no_args(self):
with self.assertRaises(TypeError):
zstd.train_dictionary()
def test_bad_args(self):
with self.assertRaises(TypeError):
zstd.train_dictionary(8192, u'foo')
with self.assertRaises(ValueError):
zstd.train_dictionary(8192, [u'foo'])
def test_no_params(self):
d = zstd.train_dictionary(8192, random_input_data())
self.assertIsInstance(d.dict_id(), int_type)
# The dictionary ID may be different across platforms.
expected = b'\x37\xa4\x30\xec' + struct.pack('<I', d.dict_id())
data = d.as_bytes()
self.assertEqual(data[0:8], expected)
def test_basic(self):
d = zstd.train_dictionary(8192, generate_samples(), k=64, d=16)
self.assertIsInstance(d.dict_id(), int_type)
data = d.as_bytes()
self.assertEqual(data[0:4], b'\x37\xa4\x30\xec')
self.assertEqual(d.k, 64)
self.assertEqual(d.d, 16)
def test_set_dict_id(self):
d = zstd.train_dictionary(8192, generate_samples(), k=64, d=16,
dict_id=42)
self.assertEqual(d.dict_id(), 42)
def test_optimize(self):
d = zstd.train_dictionary(8192, generate_samples(), threads=-1, steps=1,
d=16)
# This varies by platform.
self.assertIn(d.k, (50, 2000))
self.assertEqual(d.d, 16)
@make_cffi
class TestCompressionDict(unittest.TestCase):
def test_bad_mode(self):
with self.assertRaisesRegexp(ValueError, 'invalid dictionary load mode'):
zstd.ZstdCompressionDict(b'foo', dict_type=42)
def test_bad_precompute_compress(self):
d = zstd.train_dictionary(8192, generate_samples(), k=64, d=16)
with self.assertRaisesRegexp(ValueError, 'must specify one of level or '):
d.precompute_compress()
with self.assertRaisesRegexp(ValueError, 'must only specify one of level or '):
d.precompute_compress(level=3,
compression_params=zstd.CompressionParameters())
def test_precompute_compress_rawcontent(self):
d = zstd.ZstdCompressionDict(b'dictcontent' * 64,
dict_type=zstd.DICT_TYPE_RAWCONTENT)
d.precompute_compress(level=1)
d = zstd.ZstdCompressionDict(b'dictcontent' * 64,
dict_type=zstd.DICT_TYPE_FULLDICT)
with self.assertRaisesRegexp(zstd.ZstdError, 'unable to precompute dictionary'):
d.precompute_compress(level=1)