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widening: duplicate generateellipsesbundle2() for widening...
widening: duplicate generateellipsesbundle2() for widening The widening and the non-widening code are quite different. It will be clearer to have them as sepearate functions. To start with, I've just copied it exactly, so it's clearer over the next few patches how they're different. The new function should gradually become more similar to bundle2.widen_bundle(), and should perhaps eventually be merged with that function. However, I've left it in narrowbundle2.py for now since it still depends on constants like _KILLNODESIGNAL there. Differential Revision: https://phab.mercurial-scm.org/D7092

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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)