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Diffstat (limited to 'engine/SCons/Memoize.py')
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diff --git a/engine/SCons/Memoize.py b/engine/SCons/Memoize.py new file mode 100644 index 0000000..de4b558 --- /dev/null +++ b/engine/SCons/Memoize.py @@ -0,0 +1,244 @@ +# +# Copyright (c) 2001 - 2014 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 2014/09/27 12:51:43 garyo" + +__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 types + +# A flag controlling whether or not we actually use memoization. +use_memoizer = None + +CounterList = [] + +class Counter(object): + """ + 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 self.method_name in obj._memo: + self.hit = self.hit + 1 + else: + self.miss = self.miss + 1 + return 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 = self.keymaker(*args, **kw) + if key in memo_dict: + self.hit = self.hit + 1 + else: + self.miss = self.miss + 1 + return self.underlying_method(*args, **kw) + +class Memoizer(object): + """Object which performs caching of method calls for its 'primary' + instance.""" + + def __init__(self): + pass + +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 = types.MethodType(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: |