annotate contrib/python-zstandard/tests/common.py @ 51580:b70628a9aa7e

phases: use revision number in new_heads

All graph operations will be done using revision numbers, so passing nodes only
means they will eventually get converted to revision numbers internally.

As part of an effort to align the code on using revision number we make the
`phases.newheads` function operated on revision number, taking them as input
and using them in returns, instead of the node-id it used to consume and
produce.

This is part of multiple changesets effort to translate more part of the logic,
but is done step by step to facilitate the identification of issue that might
arise in mercurial core and extensions.

To make the change simpler to handle for third party extensions, we also rename
the function, using a more modern form. This will help detecting the different
between the node-id version and the rev-num version.

I also take this as an opportunity to add some comment about possible
performance improvement for the future. They don't matter too much now, but they
are worse exploring in a while.

import imp
import inspect
import io
import os
import types
import unittest

try:
    import hypothesis
except ImportError:
    hypothesis = None


class TestCase(unittest.TestCase):
    if not getattr(unittest.TestCase, "assertRaisesRegex", False):
        assertRaisesRegex = unittest.TestCase.assertRaisesRegexp


def make_cffi(cls):
    """Decorator to add CFFI versions of each test method."""

    # The module containing this class definition should
    # `import zstandard as zstd`. Otherwise things may blow up.
    mod = inspect.getmodule(cls)
    if not hasattr(mod, "zstd"):
        raise Exception('test module does not contain "zstd" symbol')

    if not hasattr(mod.zstd, "backend"):
        raise Exception(
            'zstd symbol does not have "backend" attribute; did '
            "you `import zstandard as zstd`?"
        )

    # If `import zstandard` already chose the cffi backend, there is nothing
    # for us to do: we only add the cffi variation if the default backend
    # is the C extension.
    if mod.zstd.backend == "cffi":
        return cls

    old_env = dict(os.environ)
    os.environ["PYTHON_ZSTANDARD_IMPORT_POLICY"] = "cffi"
    try:
        try:
            mod_info = imp.find_module("zstandard")
            mod = imp.load_module("zstandard_cffi", *mod_info)
        except ImportError:
            return cls
    finally:
        os.environ.clear()
        os.environ.update(old_env)

    if mod.backend != "cffi":
        raise Exception(
            "got the zstandard %s backend instead of cffi" % mod.backend
        )

    # If CFFI version is available, dynamically construct test methods
    # that use it.

    for attr in dir(cls):
        fn = getattr(cls, attr)
        if not inspect.ismethod(fn) and not inspect.isfunction(fn):
            continue

        if not fn.__name__.startswith("test_"):
            continue

        name = "%s_cffi" % fn.__name__

        # Replace the "zstd" symbol with the CFFI module instance. Then copy
        # the function object and install it in a new attribute.
        if isinstance(fn, types.FunctionType):
            globs = dict(fn.__globals__)
            globs["zstd"] = mod
            new_fn = types.FunctionType(
                fn.__code__, globs, name, fn.__defaults__, fn.__closure__
            )
            new_method = new_fn
        else:
            globs = dict(fn.__func__.func_globals)
            globs["zstd"] = mod
            new_fn = types.FunctionType(
                fn.__func__.func_code,
                globs,
                name,
                fn.__func__.func_defaults,
                fn.__func__.func_closure,
            )
            new_method = types.UnboundMethodType(
                new_fn, fn.im_self, fn.im_class
            )

        setattr(cls, name, new_method)

    return cls


class NonClosingBytesIO(io.BytesIO):
    """BytesIO that saves the underlying buffer on close().

    This allows us to access written data after close().
    """

    def __init__(self, *args, **kwargs):
        super(NonClosingBytesIO, self).__init__(*args, **kwargs)
        self._saved_buffer = None

    def close(self):
        self._saved_buffer = self.getvalue()
        return super(NonClosingBytesIO, self).close()

    def getvalue(self):
        if self.closed:
            return self._saved_buffer
        else:
            return super(NonClosingBytesIO, self).getvalue()


class OpCountingBytesIO(NonClosingBytesIO):
    def __init__(self, *args, **kwargs):
        self._flush_count = 0
        self._read_count = 0
        self._write_count = 0
        return super(OpCountingBytesIO, self).__init__(*args, **kwargs)

    def flush(self):
        self._flush_count += 1
        return super(OpCountingBytesIO, self).flush()

    def read(self, *args):
        self._read_count += 1
        return super(OpCountingBytesIO, self).read(*args)

    def write(self, data):
        self._write_count += 1
        return super(OpCountingBytesIO, self).write(data)


_source_files = []


def random_input_data():
    """Obtain the raw content of source files.

    This is used for generating "random" data to feed into fuzzing, since it is
    faster than random content generation.
    """
    if _source_files:
        return _source_files

    for root, dirs, files in os.walk(os.path.dirname(__file__)):
        dirs[:] = list(sorted(dirs))
        for f in sorted(files):
            try:
                with open(os.path.join(root, f), "rb") as fh:
                    data = fh.read()
                    if data:
                        _source_files.append(data)
            except OSError:
                pass

    # Also add some actual random data.
    _source_files.append(os.urandom(100))
    _source_files.append(os.urandom(1000))
    _source_files.append(os.urandom(10000))
    _source_files.append(os.urandom(100000))
    _source_files.append(os.urandom(1000000))

    return _source_files


def generate_samples():
    inputs = [
        b"foo",
        b"bar",
        b"abcdef",
        b"sometext",
        b"baz",
    ]

    samples = []

    for i in range(128):
        samples.append(inputs[i % 5])
        samples.append(inputs[i % 5] * (i + 3))
        samples.append(inputs[-(i % 5)] * (i + 2))

    return samples


if hypothesis:
    default_settings = hypothesis.settings(deadline=10000)
    hypothesis.settings.register_profile("default", default_settings)

    ci_settings = hypothesis.settings(deadline=20000, max_examples=1000)
    hypothesis.settings.register_profile("ci", ci_settings)

    expensive_settings = hypothesis.settings(deadline=None, max_examples=10000)
    hypothesis.settings.register_profile("expensive", expensive_settings)

    hypothesis.settings.load_profile(
        os.environ.get("HYPOTHESIS_PROFILE", "default")
    )