text: #
  # Copyright (c) 2001 - 2017 The SCons Foundation
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  #
  from __future__ import print_function
  
  __revision__ = "src/engine/SCons/Memoize.py  2018/09/30 19:25:33 Sye"
  
  __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
  
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