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rust-nodemap: automatically use the rust index for persistent nodemap...
rust-nodemap: automatically use the rust index for persistent nodemap The persistent nodemap requires the rust index to be used to provides any gains. So we automatically enable it for revlog using the persistent nodemap. We keep it off for other revset because now that the rust revlog fully initialise the nodemap using it everywhere introduce a fairly significant regression (eg: hg diff moving from 0.8s to 2.3s on mozilla-try) Differential Revision: https://phab.mercurial-scm.org/D8164

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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)