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narrow: reuse narrowspec.updateworkingcopy() when narrowing...
narrow: reuse narrowspec.updateworkingcopy() when narrowing Similar to the previous patch for widening, but here we also need to teach updateworkingcopy() to forcefully delete files that are not recorded in the dirstate as clean. That should be safe because the narrowing command (e.g. `hg tracked --removeinclude`) has already checked that the working copy is clean. Differential Revision: https://phab.mercurial-scm.org/D5511

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test_train_dictionary.py
88 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,
)
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, generate_samples())
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)