contrib/python-zstandard/tests/test_roundtrip.py

zstd: vendor python-zstandard 0.7.0

Commit 3054ae3a66112970a091d3939fee32c2d0c1a23e from
https://github.com/indygreg/python-zstandard is imported without
modifications (other than removing unwanted files).

The vendored zstd library within has been upgraded from 1.1.2 to
1.1.3. This version introduced new APIs for threads, thread
pools, multi-threaded compression, and a new dictionary
builder (COVER). These features are not yet used by
python-zstandard (or Mercurial for that matter). However,
that will likely change in the next python-zstandard release
(and I think there are opportunities for Mercurial to take
advantage of the multi-threaded APIs).

Relevant to Mercurial, the CFFI bindings are now fully
implemented. This means zstd should "just work" with PyPy
(although I haven't tried). The python-zstandard test suite also
runs all tests against both the C extension and CFFI bindings to
ensure feature parity.

There is also a "decompress_content_dict_chain()" API. This was
derived from discussions with Yann Collet on list about alternate
ways of encoding delta chains.

The change most relevant to Mercurial is a performance enhancement in
the simple decompression API to reuse a data structure across
operations. This makes decompression of multiple inputs significantly
faster. (This scenario occurs when reading revlog delta chains, for
example.)

Using python-zstandard's bench.py to measure the performance
difference...

On changelog chunks in the mozilla-unified repo:

decompress discrete decompress() reuse zctx
1.262243 wall; 1.260000 CPU; 1.260000 user; 0.000000 sys 170.43 MB/s (best of 3)
0.949106 wall; 0.950000 CPU; 0.950000 user; 0.000000 sys 226.66 MB/s (best of 4)

decompress discrete dict decompress() reuse zctx
0.692170 wall; 0.690000 CPU; 0.690000 user; 0.000000 sys 310.80 MB/s (best of 5)
0.437088 wall; 0.440000 CPU; 0.440000 user; 0.000000 sys 492.17 MB/s (best of 7)

On manifest chunks in the mozilla-unified repo:

decompress discrete decompress() reuse zctx
1.367284 wall; 1.370000 CPU; 1.370000 user; 0.000000 sys 274.01 MB/s (best of 3)
1.086831 wall; 1.080000 CPU; 1.080000 user; 0.000000 sys 344.72 MB/s (best of 3)

decompress discrete dict decompress() reuse zctx
0.993272 wall; 0.990000 CPU; 0.990000 user; 0.000000 sys 377.19 MB/s (best of 3)
0.678651 wall; 0.680000 CPU; 0.680000 user; 0.000000 sys 552.06 MB/s (best of 5)

That should make reads on zstd revlogs a bit faster ;)

# no-check-commit

import io

try:
    import unittest2 as unittest
except ImportError:
    import unittest

try:
    import hypothesis
    import hypothesis.strategies as strategies
except ImportError:
    raise unittest.SkipTest('hypothesis not available')

import zstd

from .common import (
    make_cffi,
)

compression_levels = strategies.integers(min_value=1, max_value=22)


@make_cffi
class TestRoundTrip(unittest.TestCase):
    @hypothesis.given(strategies.binary(), compression_levels)
    def test_compress_write_to(self, data, level):
        """Random data from compress() roundtrips via write_to."""
        cctx = zstd.ZstdCompressor(level=level)
        compressed = cctx.compress(data)

        buffer = io.BytesIO()
        dctx = zstd.ZstdDecompressor()
        with dctx.write_to(buffer) as decompressor:
            decompressor.write(compressed)

        self.assertEqual(buffer.getvalue(), data)

    @hypothesis.given(strategies.binary(), compression_levels)
    def test_compressor_write_to_decompressor_write_to(self, data, level):
        """Random data from compressor write_to roundtrips via write_to."""
        compress_buffer = io.BytesIO()
        decompressed_buffer = io.BytesIO()

        cctx = zstd.ZstdCompressor(level=level)
        with cctx.write_to(compress_buffer) as compressor:
            compressor.write(data)

        dctx = zstd.ZstdDecompressor()
        with dctx.write_to(decompressed_buffer) as decompressor:
            decompressor.write(compress_buffer.getvalue())

        self.assertEqual(decompressed_buffer.getvalue(), data)

    @hypothesis.given(strategies.binary(average_size=1048576))
    @hypothesis.settings(perform_health_check=False)
    def test_compressor_write_to_decompressor_write_to_larger(self, data):
        compress_buffer = io.BytesIO()
        decompressed_buffer = io.BytesIO()

        cctx = zstd.ZstdCompressor(level=5)
        with cctx.write_to(compress_buffer) as compressor:
            compressor.write(data)

        dctx = zstd.ZstdDecompressor()
        with dctx.write_to(decompressed_buffer) as decompressor:
            decompressor.write(compress_buffer.getvalue())

        self.assertEqual(decompressed_buffer.getvalue(), data)