view contrib/python-zstandard/tests/common.py @ 40021:c537144fdbef

wireprotov2: support response caching

One of the things I've learned from managing VCS servers over the
years is that they are hard to scale. It is well known that some
companies have very beefy (read: very expensive) servers to power
their VCS needs. It is also known that specialized servers for
various VCS exist in order to facilitate scaling servers. (Mercurial
is in this boat.)

One of the aspects that make a VCS server hard to scale is the
high CPU load incurred by constant client clone/pull operations.

To alleviate the scaling pain associated with data retrieval
operations, I want to integrate caching into the Mercurial wire
protocol server as robustly as possible such that servers can
aggressively cache responses and defer as much server load as
possible.

This commit represents the initial implementation of a general
caching layer in wire protocol version 2.

We define a new interface and behavior for a wire protocol cacher
in repository.py. (This is probably where a reviewer should look
first to understand what is going on.)

The bulk of the added code is in wireprotov2server.py, where we
define how a command can opt in to being cached and integrate
caching into command dispatching.

From a very high-level:

* A command can declare itself as cacheable by providing a callable
  that can be used to derive a cache key.
* At dispatch time, if a command is cacheable, we attempt to
  construct a cacher and use it for serving the request and/or
  caching the request.
* The dispatch layer handles the bulk of the business logic for
  caching, making cachers mostly "dumb content stores."
* The mechanism for invalidating cached entries (one of the harder
  parts about caching in general) is by varying the cache key when
  state changes. As such, cachers don't need to be concerned with
  cache invalidation.

Initially, we've hooked up support for caching "manifestdata" and
"filedata" commands. These are the simplest to cache, as they should
be immutable over time. Caching of commands related to changeset
data is a bit harder (because cache validation is impacted by
changes to bookmarks, phases, etc). This will be implemented later.
(Strictly speaking, censoring a file should invalidate caches. I've
added an inline TODO to track this edge case.)

To prove it works, this commit implements a test-only extension
providing in-memory caching backed by an lrucachedict. A new test
showing this extension behaving properly is added. FWIW, the
cacher is ~50 lines of code, demonstrating the relative ease with
which a cache can be added to a server.

While the test cacher is not suitable for production workloads, just
for kicks I performed a clone of just the changeset and manifest data
for the mozilla-unified repository. With a fully warmed cache (of just
the manifest data since changeset data is not cached), server-side
CPU usage dropped from ~73s to ~28s. That's pretty significant and
demonstrates the potential that response caching has on server
scalability!

Differential Revision: https://phab.mercurial-scm.org/D4773

import imp
import inspect
import io
import os
import types

try:
    import hypothesis
except ImportError:
    hypothesis = None


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 OpCountingBytesIO(io.BytesIO):
    def __init__(self, *args, **kwargs):
        self._read_count = 0
        self._write_count = 0
        return super(OpCountingBytesIO, self).__init__(*args, **kwargs)

    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

    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()
    hypothesis.settings.register_profile('default', default_settings)

    ci_settings = hypothesis.settings(max_examples=2500,
                                      max_iterations=2500)
    hypothesis.settings.register_profile('ci', ci_settings)

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