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ci: use the `v1.0` flavor of the docker images in the CI...
ci: use the `v1.0` flavor of the docker images in the CI This new versioning will help us to maintain backward compatibility in the docker image. This will be useful to deal with mismatch between default/stable in version and the re-run CI on older changesets in the future. Once this changeset land on stable, we will have to merge it in default. Then we can start make backward incompatible changes in a new image version. Differential Revision: https://phab.mercurial-scm.org/D12388

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test_train_dictionary.py
102 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,
TestCase,
)
if sys.version_info[0] >= 3:
int_type = int
else:
int_type = long
@make_cffi
class TestTrainDictionary(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(TestCase):
def test_bad_mode(self):
with self.assertRaisesRegex(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.assertRaisesRegex(
ValueError, "must specify one of level or "
):
d.precompute_compress()
with self.assertRaisesRegex(
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.assertRaisesRegex(
zstd.ZstdError, "unable to precompute dictionary"
):
d.precompute_compress(level=1)