#!/usr/bin/env python # encoding: utf-8 """Descriptor support for NIPY. Utilities to support special Python descriptors [1,2], in particular the use of a useful pattern for properties we call 'one time properties'. These are object attributes which are declared as properties, but become regular attributes once they've been read the first time. They can thus be evaluated later in the object's life cycle, but once evaluated they become normal, static attributes with no function call overhead on access or any other constraints. A special ResetMixin class is provided to add a .reset() method to users who may want to have their objects capable of resetting these computed properties to their 'untriggered' state. References ---------- [1] How-To Guide for Descriptors, Raymond Hettinger. http://users.rcn.com/python/download/Descriptor.htm [2] Python data model, http://docs.python.org/reference/datamodel.html Notes ----- This module is taken from the NiPy project (http://neuroimaging.scipy.org/site/index.html), and is BSD licensed. """ #----------------------------------------------------------------------------- # Classes and Functions #----------------------------------------------------------------------------- class ResetMixin(object): """A Mixin class to add a .reset() method to users of OneTimeProperty. By default, auto attributes once computed, become static. If they happen to depend on other parts of an object and those parts change, their values may now be invalid. This class offers a .reset() method that users can call *explicitly* when they know the state of their objects may have changed and they want to ensure that *all* their special attributes should be invalidated. Once reset() is called, all their auto attributes are reset to their OneTimeProperty descriptors, and their accessor functions will be triggered again. Example ------- >>> class A(ResetMixin): ... def __init__(self,x=1.0): ... self.x = x ... ... @auto_attr ... def y(self): ... print '*** y computation executed ***' ... return self.x / 2.0 ... >>> a = A(10) About to access y twice, the second time no computation is done: >>> a.y *** y computation executed *** 5.0 >>> a.y 5.0 Changing x >>> a.x = 20 a.y doesn't change to 10, since it is a static attribute: >>> a.y 5.0 We now reset a, and this will then force all auto attributes to recompute the next time we access them: >>> a.reset() About to access y twice again after reset(): >>> a.y *** y computation executed *** 10.0 >>> a.y 10.0 """ def reset(self): """Reset all OneTimeProperty attributes that may have fired already.""" instdict = self.__dict__ classdict = self.__class__.__dict__ # To reset them, we simply remove them from the instance dict. At that # point, it's as if they had never been computed. On the next access, # the accessor function from the parent class will be called, simply # because that's how the python descriptor protocol works. for mname, mval in classdict.items(): if mname in instdict and isinstance(mval, OneTimeProperty): delattr(self, mname) class OneTimeProperty(object): """A descriptor to make special properties that become normal attributes. This is meant to be used mostly by the auto_attr decorator in this module. """ def __init__(self,func): """Create a OneTimeProperty instance. Parameters ---------- func : method The method that will be called the first time to compute a value. Afterwards, the method's name will be a standard attribute holding the value of this computation. """ self.getter = func self.name = func.func_name def __get__(self,obj,type=None): """This will be called on attribute access on the class or instance. """ if obj is None: # Being called on the class, return the original function. This way, # introspection works on the class. #return func return self.getter val = self.getter(obj) #print "** auto_attr - loading '%s'" % self.name # dbg setattr(obj, self.name, val) return val def auto_attr(func): """Decorator to create OneTimeProperty attributes. Parameters ---------- func : method The method that will be called the first time to compute a value. Afterwards, the method's name will be a standard attribute holding the value of this computation. Examples -------- >>> class MagicProp(object): ... @auto_attr ... def a(self): ... return 99 ... >>> x = MagicProp() >>> 'a' in x.__dict__ False >>> x.a 99 >>> 'a' in x.__dict__ True """ return OneTimeProperty(func)