[Findit] Factoring the gitiles (etc) stuff out into its own directory

appengine/findit/common/cache_decorator.py

Index: appengine/findit/common/cache_decorator.py
diff --git a/appengine/findit/common/cache_decorator.py b/appengine/findit/common/cache_decorator.py
deleted file mode 100644
index 6f1bb1efe42dc866aa7841e4df8eb84db698f26f..0000000000000000000000000000000000000000
--- a/appengine/findit/common/cache_decorator.py
+++ /dev/null
@@ -1,228 +0,0 @@
-# Copyright 2015 The Chromium Authors. All rights reserved.

[stgao, 2016/09/21 23:03:24]

As this file is not related to gitiles, I'd keep as is until we find a better
place for it (common/utils as in the new code layout I shared with you).

[wrengr, 2016/09/28 00:59:49]

I have to move it. Leaving it in ./common causes a "cyclic import" problem.
There's no actual cycle, but Python gets confused since it doesn't have a proper
module system. More concretely:

1. Every file that lives in $DIR depends on $DIR/__init__.py
2. For example, ./gitiles/git_repository.py depends on ./gitiles/__init__.py
3. Some files in ./common use git_repository.py, and thus transitively depend on
./gitiles/__init__.py
4. But git_repository.py uses cache_decorator.py, and thus transitively depends
on the __init__.py for where cache_decorator.py lives.
5. Thus, if cache_decorator.py lives in ./common, then Python crashes at
load-time due to the cyclic dependency between ./gitiles/__init__.py and
./common/__init__.py. To avoid this, cache_decorator.py must live in ./gitiles
or in some directory that's topologically "before" ./gitiles.

-# Use of this source code is governed by a BSD-style license that can be
-# found in the LICENSE file.
-
-"""This module provides a decorator to cache the results of a function.
-
-  Examples:
-  1. Decorate a function:
-    @cache_decorator.Cached()
-    def Test(a):
-      return a + a
-
-    Test('a')
-    Test('a')  # Returns the cached 'aa'.
-
-  2. Decorate a method in a class:
-    class Downloader(object):
-      def __init__(self, url, retries):
-        self.url = url
-        self.retries = retries
-
-      @property
-      def identifier(self):
-        return self.url
-
-      @cache_decorator.Cached():
-      def Download(self, path):
-        return urllib2.urlopen(self.url + '/' + path).read()
-
-      d1 = Downloader('http://url', 4)
-      d1.Download('path')
-
-      d2 = Downloader('http://url', 5)
-      d2.Download('path')  # Returned the cached downloaded data.
-"""
-
-import cStringIO
-import functools
-import hashlib
-import inspect
-import logging
-import pickle
-import zlib
-
-from google.appengine.api import memcache
-
-
-class Cacher(object):
-  """An interface to cache and retrieve data.
-
-  Subclasses should implement the Get/Set functions.
-  TODO: Add a Delete function (default to no-op) if needed later.
-  """
-  def Get(self, key):
-    """Returns the cached data for the given key if available.
-
-    Args:
-      key (str): The key to identify the cached data.
-    """
-    raise NotImplementedError()
-
-  def Set(self, key, data, expire_time=0):
-    """Cache the given data which is identified by the given key.
-
-    Args:
-      key (str): The key to identify the cached data.
-      data (object): The python object to be cached.
-      expire_time (int): Number of seconds from current time (up to 1 month).
-    """
-    raise NotImplementedError()
-
-
-class PickledMemCacher(Cacher):
-  """A memcache-backed implementation of the interface Cacher.
-
-  The data to be cached should be pickleable.
-  Limitation: size of the pickled data and key should be <= 1MB.
-  """
-  def Get(self, key):
-    return memcache.get(key)
-
-  def Set(self, key, data, expire_time=0):
-    return memcache.set(key, data, time=expire_time)
-
-
-class _CachedItemMetaData(object):
-  def __init__(self, number):
-    self.number = number
-
-
-class CompressedMemCacher(Cacher):
-  """A memcache-backed implementation of the interface Cacher with compression.
-
-  The data to be cached would be pickled and then compressed.
-  Data still > 1MB will be split into sub-piece and stored separately.
-  During retrieval, if any sub-piece is missing, None is returned.
-  """
-  CHUNK_SIZE = 990000
-
-  def Get(self, key):
-    data = memcache.get(key)
-    if isinstance(data, _CachedItemMetaData):
-      num = data.number
-      sub_keys = ['%s-%s' % (key, i) for i in range(num)]
-      all_data = memcache.get_multi(sub_keys)
-      if len(all_data) != num:  # Some data is missing.
-        return None
-
-      data_output = cStringIO.StringIO()
-      for sub_key in sub_keys:
-        data_output.write(all_data[sub_key])
-      data = data_output.getvalue()
-
-    return None if data is None else pickle.loads(zlib.decompress(data))
-
-  def Set(self, key, data, expire_time=0):
-    pickled_data = pickle.dumps(data)
-    compressed_data = zlib.compress(pickled_data)
-
-    all_data = {}
-    if len(compressed_data) > self.CHUNK_SIZE:
-      num = 0
-      for index in range(0, len(compressed_data), self.CHUNK_SIZE):
-        sub_key = '%s-%s' % (key, num)
-        all_data[sub_key] = compressed_data[index : index + self.CHUNK_SIZE]
-        num += 1
-
-      all_data[key] = _CachedItemMetaData(num)
-    else:
-      all_data[key] = compressed_data
-
-    keys_not_set = memcache.set_multi(all_data, time=expire_time)
-    return len(keys_not_set) == 0
-
-
-def _DefaultKeyGenerator(func, args, kwargs):
-  """Generates a key from the function and arguments passed to it.
-
-  Args:
-    func (function): An arbitrary function.
-    args (list): Positional arguments passed to ``func``.
-    kwargs (dict): Keyword arguments passed to ``func``.
-
-  Returns:
-    A string to represent a call to the given function with the given arguments.
-  """
-  params = inspect.getcallargs(func, *args, **kwargs)
-  for var_name in params:
-    if not hasattr(params[var_name], 'identifier'):
-      continue
-
-    if callable(params[var_name].identifier):
-      params[var_name] = params[var_name].identifier()
-    else:
-      params[var_name] = params[var_name].identifier
-
-  return hashlib.md5(pickle.dumps(params)).hexdigest()
-
-
-def Cached(namespace=None,
-           expire_time=0,
-           key_generator=_DefaultKeyGenerator,
-           cacher=PickledMemCacher()):
-  """Returns a decorator to cache the decorated function's results.
-
-  However, if the function returns None, empty list/dict, empty string, or other
-  value that is evaluated as False, the results won't be cached.
-
-  This decorator is to cache results of different calls to the decorated
-  function, and avoid executing it again if the calls are equivalent. Two calls
-  are equivalent, if the namespace is the same and the keys generated by the
-  ``key_generator`` are the same.
-
-  The usage of this decorator requires that:
-  - If the default key generator is used, parameters passed to the decorated
-    function should be pickleable, or each of the parameter has an identifier
-    property or method which returns pickleable results.
-  - If the default cacher is used, the returned results of the decorated
-    function should be pickleable.
-
-  Args:
-    namespace (str): A prefix to the key for the cache. Default to the
-        combination of module name and function name of the decorated function.
-    expire_time (int): Expiration time, relative number of seconds from current
-        time (up to 1 month). Defaults to 0 -- never expire.
-    key_generator (function): A function to generate a key to represent a call
-        to the decorated function. Defaults to :func:`_DefaultKeyGenerator`.
-    cacher (Cacher): An instance of an implementation of interface `Cacher`.
-        Defaults to one of `PickledMemCacher` which is based on memcache.
-
-  Returns:
-    The cached results or the results of a new run of the decorated function.
-  """
-  def GetPrefix(func, namespace):
-    return namespace or '%s.%s' % (func.__module__, func.__name__)
-
-  def Decorator(func):
-    """Decorator to cache a function's results."""
-    @functools.wraps(func)
-    def Wrapped(*args, **kwargs):
-      prefix = GetPrefix(func, namespace)
-      key = '%s-%s' % (prefix, key_generator(func, args, kwargs))
-
-      try:
-        result = cacher.Get(key)
-      except Exception:  # pragma: no cover.
-        result = None
-        logging.exception(
-            'Failed to get cached data for function %s.%s, args=%s, kwargs=%s',
-            func.__module__, func.__name__, repr(args), repr(kwargs))
-
-      if result is not None:
-        return result
-
-      result = func(*args, **kwargs)
-      if result:
-        try:
-          cacher.Set(key, result, expire_time=expire_time)
-        except Exception:  # pragma: no cover.
-          logging.exception(
-              'Failed to cache data for function %s.%s, args=%s, kwargs=%s',
-              func.__module__, func.__name__, repr(args), repr(kwargs))
-
-      return result
-
-    return Wrapped
-
-  return Decorator