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-rw-r--r--3rdParty/SCons/scons-local/SCons/Memoize.py292
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diff --git a/3rdParty/SCons b/3rdParty/SCons
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+Subproject 3056da6ce23ced559497a07bd4444fb3a17b4db
diff --git a/3rdParty/SCons/scons-local/SCons/Memoize.py b/3rdParty/SCons/scons-local/SCons/Memoize.py
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-#
-# Copyright (c) 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009 The SCons Foundation
-#
-# Permission is hereby granted, free of charge, to any person obtaining
-# a copy of this software and associated documentation files (the
-# "Software"), to deal in the Software without restriction, including
-# without limitation the rights to use, copy, modify, merge, publish,
-# distribute, sublicense, and/or sell copies of the Software, and to
-# permit persons to whom the Software is furnished to do so, subject to
-# the following conditions:
-#
-# The above copyright notice and this permission notice shall be included
-# in all copies or substantial portions of the Software.
-#
-# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY
-# KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE
-# WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
-# NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
-# LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
-# OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
-# WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
-#
-
-__revision__ = "src/engine/SCons/Memoize.py 4043 2009/02/23 09:06:45 scons"
-
-__doc__ = """Memoizer
-
-A metaclass implementation to count hits and misses of the computed
-values that various methods cache in memory.
-
-Use of this modules assumes that wrapped methods be coded to cache their
-values in a consistent way. Here is an example of wrapping a method
-that returns a computed value, with no input parameters:
-
- memoizer_counters = [] # Memoization
-
- memoizer_counters.append(SCons.Memoize.CountValue('foo')) # Memoization
-
- def foo(self):
-
- try: # Memoization
- return self._memo['foo'] # Memoization
- except KeyError: # Memoization
- pass # Memoization
-
- result = self.compute_foo_value()
-
- self._memo['foo'] = result # Memoization
-
- return result
-
-Here is an example of wrapping a method that will return different values
-based on one or more input arguments:
-
- def _bar_key(self, argument): # Memoization
- return argument # Memoization
-
- memoizer_counters.append(SCons.Memoize.CountDict('bar', _bar_key)) # Memoization
-
- def bar(self, argument):
-
- memo_key = argument # Memoization
- try: # Memoization
- memo_dict = self._memo['bar'] # Memoization
- except KeyError: # Memoization
- memo_dict = {} # Memoization
- self._memo['dict'] = memo_dict # Memoization
- else: # Memoization
- try: # Memoization
- return memo_dict[memo_key] # Memoization
- except KeyError: # Memoization
- pass # Memoization
-
- result = self.compute_bar_value(argument)
-
- memo_dict[memo_key] = result # Memoization
-
- return result
-
-At one point we avoided replicating this sort of logic in all the methods
-by putting it right into this module, but we've moved away from that at
-present (see the "Historical Note," below.).
-
-Deciding what to cache is tricky, because different configurations
-can have radically different performance tradeoffs, and because the
-tradeoffs involved are often so non-obvious. Consequently, deciding
-whether or not to cache a given method will likely be more of an art than
-a science, but should still be based on available data from this module.
-Here are some VERY GENERAL guidelines about deciding whether or not to
-cache return values from a method that's being called a lot:
-
- -- The first question to ask is, "Can we change the calling code
- so this method isn't called so often?" Sometimes this can be
- done by changing the algorithm. Sometimes the *caller* should
- be memoized, not the method you're looking at.
-
- -- The memoized function should be timed with multiple configurations
- to make sure it doesn't inadvertently slow down some other
- configuration.
-
- -- When memoizing values based on a dictionary key composed of
- input arguments, you don't need to use all of the arguments
- if some of them don't affect the return values.
-
-Historical Note: The initial Memoizer implementation actually handled
-the caching of values for the wrapped methods, based on a set of generic
-algorithms for computing hashable values based on the method's arguments.
-This collected caching logic nicely, but had two drawbacks:
-
- Running arguments through a generic key-conversion mechanism is slower
- (and less flexible) than just coding these things directly. Since the
- methods that need memoized values are generally performance-critical,
- slowing them down in order to collect the logic isn't the right
- tradeoff.
-
- Use of the memoizer really obscured what was being called, because
- all the memoized methods were wrapped with re-used generic methods.
- This made it more difficult, for example, to use the Python profiler
- to figure out how to optimize the underlying methods.
-"""
-
-import new
-
-# A flag controlling whether or not we actually use memoization.
-use_memoizer = None
-
-CounterList = []
-
-class Counter:
- """
- Base class for counting memoization hits and misses.
-
- We expect that the metaclass initialization will have filled in
- the .name attribute that represents the name of the function
- being counted.
- """
- def __init__(self, method_name):
- """
- """
- self.method_name = method_name
- self.hit = 0
- self.miss = 0
- CounterList.append(self)
- def display(self):
- fmt = " %7d hits %7d misses %s()"
- print fmt % (self.hit, self.miss, self.name)
- def __cmp__(self, other):
- try:
- return cmp(self.name, other.name)
- except AttributeError:
- return 0
-
-class CountValue(Counter):
- """
- A counter class for simple, atomic memoized values.
-
- A CountValue object should be instantiated in a class for each of
- the class's methods that memoizes its return value by simply storing
- the return value in its _memo dictionary.
-
- We expect that the metaclass initialization will fill in the
- .underlying_method attribute with the method that we're wrapping.
- We then call the underlying_method method after counting whether
- its memoized value has already been set (a hit) or not (a miss).
- """
- def __call__(self, *args, **kw):
- obj = args[0]
- if obj._memo.has_key(self.method_name):
- self.hit = self.hit + 1
- else:
- self.miss = self.miss + 1
- return apply(self.underlying_method, args, kw)
-
-class CountDict(Counter):
- """
- A counter class for memoized values stored in a dictionary, with
- keys based on the method's input arguments.
-
- A CountDict object is instantiated in a class for each of the
- class's methods that memoizes its return value in a dictionary,
- indexed by some key that can be computed from one or more of
- its input arguments.
-
- We expect that the metaclass initialization will fill in the
- .underlying_method attribute with the method that we're wrapping.
- We then call the underlying_method method after counting whether the
- computed key value is already present in the memoization dictionary
- (a hit) or not (a miss).
- """
- def __init__(self, method_name, keymaker):
- """
- """
- Counter.__init__(self, method_name)
- self.keymaker = keymaker
- def __call__(self, *args, **kw):
- obj = args[0]
- try:
- memo_dict = obj._memo[self.method_name]
- except KeyError:
- self.miss = self.miss + 1
- else:
- key = apply(self.keymaker, args, kw)
- if memo_dict.has_key(key):
- self.hit = self.hit + 1
- else:
- self.miss = self.miss + 1
- return apply(self.underlying_method, args, kw)
-
-class Memoizer:
- """Object which performs caching of method calls for its 'primary'
- instance."""
-
- def __init__(self):
- pass
-
-# Find out if we support metaclasses (Python 2.2 and later).
-
-class M:
- def __init__(cls, name, bases, cls_dict):
- cls.use_metaclass = 1
- def fake_method(self):
- pass
- new.instancemethod(fake_method, None, cls)
-
-try:
- class A:
- __metaclass__ = M
-
- use_metaclass = A.use_metaclass
-except AttributeError:
- use_metaclass = None
- reason = 'no metaclasses'
-except TypeError:
- use_metaclass = None
- reason = 'new.instancemethod() bug'
-else:
- del A
-
-del M
-
-if not use_metaclass:
-
- def Dump(title):
- pass
-
- try:
- class Memoized_Metaclass(type):
- # Just a place-holder so pre-metaclass Python versions don't
- # have to have special code for the Memoized classes.
- pass
- except TypeError:
- class Memoized_Metaclass:
- # A place-holder so pre-metaclass Python versions don't
- # have to have special code for the Memoized classes.
- pass
-
- def EnableMemoization():
- import SCons.Warnings
- msg = 'memoization is not supported in this version of Python (%s)'
- raise SCons.Warnings.NoMetaclassSupportWarning, msg % reason
-
-else:
-
- def Dump(title=None):
- if title:
- print title
- CounterList.sort()
- for counter in CounterList:
- counter.display()
-
- class Memoized_Metaclass(type):
- def __init__(cls, name, bases, cls_dict):
- super(Memoized_Metaclass, cls).__init__(name, bases, cls_dict)
-
- for counter in cls_dict.get('memoizer_counters', []):
- method_name = counter.method_name
-
- counter.name = cls.__name__ + '.' + method_name
- counter.underlying_method = cls_dict[method_name]
-
- replacement_method = new.instancemethod(counter, None, cls)
- setattr(cls, method_name, replacement_method)
-
- def EnableMemoization():
- global use_memoizer
- use_memoizer = 1
-
-# Local Variables:
-# tab-width:4
-# indent-tabs-mode:nil
-# End:
-# vim: set expandtab tabstop=4 shiftwidth=4: