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- #
- # Copyright (c) 2001 - 2017 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.
- #
- from __future__ import print_function
-
- __revision__ = "src/engine/SCons/Memoize.py rel_3.0.0:4395:8972f6a2f699 2017/09/18 12:59:24 bdbaddog"
-
- __doc__ = """Memoizer
-
- A decorator-based 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. In particular, it requires that the class uses a
- dictionary named "_memo" to store the cached values.
-
- Here is an example of wrapping a method that returns a computed value,
- with no input parameters::
-
- @SCons.Memoize.CountMethodCall
- 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
-
- @SCons.Memoize.CountDictCall(_bar_key)
- 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
-
- 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.
-
- """
-
- # A flag controlling whether or not we actually use memoization.
- use_memoizer = None
-
- # Global list of counter objects
- CounterList = {}
-
- class Counter(object):
- """
- Base class for counting memoization hits and misses.
-
- We expect that the initialization in a matching decorator will
- fill in the correct class name and method name that represents
- the name of the function being counted.
- """
- def __init__(self, cls_name, method_name):
- """
- """
- self.cls_name = cls_name
- self.method_name = method_name
- self.hit = 0
- self.miss = 0
- def key(self):
- return self.cls_name+'.'+self.method_name
- def display(self):
- print(" {:7d} hits {:7d} misses {}()".format(self.hit, self.miss, self.key()))
- def __eq__(self, other):
- try:
- return self.key() == other.key()
- except AttributeError:
- return True
-
- class CountValue(Counter):
- """
- A counter class for simple, atomic memoized values.
-
- A CountValue object should be instantiated in a decorator for each of
- the class's methods that memoizes its return value by simply storing
- the return value in its _memo dictionary.
- """
- def count(self, *args, **kw):
- """ Counts whether the memoized value has already been
- set (a hit) or not (a miss).
- """
- obj = args[0]
- if self.method_name in obj._memo:
- self.hit = self.hit + 1
- else:
- self.miss = self.miss + 1
-
- 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 decorator 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.
- """
- def __init__(self, cls_name, method_name, keymaker):
- """
- """
- Counter.__init__(self, cls_name, method_name)
- self.keymaker = keymaker
- def count(self, *args, **kw):
- """ Counts whether the computed key value is already present
- in the memoization dictionary (a hit) or not (a miss).
- """
- 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
-
- def Dump(title=None):
- """ Dump the hit/miss count for all the counters
- collected so far.
- """
- if title:
- print(title)
- for counter in sorted(CounterList):
- CounterList[counter].display()
-
- def EnableMemoization():
- global use_memoizer
- use_memoizer = 1
-
- def CountMethodCall(fn):
- """ Decorator for counting memoizer hits/misses while retrieving
- a simple value in a class method. It wraps the given method
- fn and uses a CountValue object to keep track of the
- caching statistics.
- Wrapping gets enabled by calling EnableMemoization().
- """
- if use_memoizer:
- def wrapper(self, *args, **kwargs):
- global CounterList
- key = self.__class__.__name__+'.'+fn.__name__
- if key not in CounterList:
- CounterList[key] = CountValue(self.__class__.__name__, fn.__name__)
- CounterList[key].count(self, *args, **kwargs)
- return fn(self, *args, **kwargs)
- wrapper.__name__= fn.__name__
- return wrapper
- else:
- return fn
-
- def CountDictCall(keyfunc):
- """ Decorator for counting memoizer hits/misses while accessing
- dictionary values with a key-generating function. Like
- CountMethodCall above, it wraps the given method
- fn and uses a CountDict object to keep track of the
- caching statistics. The dict-key function keyfunc has to
- get passed in the decorator call and gets stored in the
- CountDict instance.
- Wrapping gets enabled by calling EnableMemoization().
- """
- def decorator(fn):
- if use_memoizer:
- def wrapper(self, *args, **kwargs):
- global CounterList
- key = self.__class__.__name__+'.'+fn.__name__
- if key not in CounterList:
- CounterList[key] = CountDict(self.__class__.__name__, fn.__name__, keyfunc)
- CounterList[key].count(self, *args, **kwargs)
- return fn(self, *args, **kwargs)
- wrapper.__name__= fn.__name__
- return wrapper
- else:
- return fn
- return decorator
-
- # Local Variables:
- # tab-width:4
- # indent-tabs-mode:nil
- # End:
- # vim: set expandtab tabstop=4 shiftwidth=4:
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