不，每次访问该属性时都将调用getter。

不，您需要添加一个memoize装饰器：

class memoized(object):
   """Decorator that caches a function's return value each time it is called.
   If called later with the same arguments, the cached value is returned, and
   not re-evaluated.
   """
   def __init__(self, func):
      self.func = func
      self.cache = {}
   def __call__(self, *args):
      try:
         return self.cache[args]
      except KeyError:
         value = self.func(*args)
         self.cache[args] = value
         return value
      except TypeError:
         # uncachable -- for instance, passing a list as an argument.
         # Better to not cache than to blow up entirely.
         return self.func(*args)
   def __repr__(self):
      """Return the function's docstring."""
      return self.func.__doc__
   def __get__(self, obj, objtype):
      """Support instance methods."""
      return functools.partial(self.__call__, obj)

@memoized
def fibonacci(n):
   "Return the nth fibonacci number."
   if n in (0, 1):
      return n
   return fibonacci(n-1) + fibonacci(n-2)

print fibonacci(12)

对于任何可能在2020年阅读这篇文章的人来说，从Python 3.8开始，functools模块作为标准库的一部分提供了这个功能。
https://docs.python.org/dev/library/functools.html#functools.cached_property
需要注意的是，定义自己的__dict__（或者根本不定义）或者使用__slots__的类可能无法按预期工作。

属性不会自动缓存它们的返回值。getter（和setter）用于在每次访问属性时调用。
然而，Denis Otkidach已经为此编写了一个很棒的缓存属性装饰器（发布在the Python Cookbook, 2nd edition中，最初也发布在ActiveState的PSF license下）：

class cache(object):    
    '''Computes attribute value and caches it in the instance.
    Python Cookbook (Denis Otkidach) https://stackoverflow.com/users/168352/denis-otkidach
    This decorator allows you to create a property which can be computed once and
    accessed many times. Sort of like memoization.

    '''
    def __init__(self, method, name=None):
        # record the unbound-method and the name
        self.method = method
        self.name = name or method.__name__
        self.__doc__ = method.__doc__
    def __get__(self, inst, cls):
        # self: <__main__.cache object at 0xb781340c>
        # inst: <__main__.Foo object at 0xb781348c>
        # cls: <class '__main__.Foo'>       
        if inst is None:
            # instance attribute accessed on class, return self
            # You get here if you write `Foo.bar`
            return self
        # compute, cache and return the instance's attribute value
        result = self.method(inst)
        # setattr redefines the instance's attribute so this doesn't get called again
        setattr(inst, self.name, result)
        return result

下面是一个演示其用法的示例：

def demo_cache():
    class Foo(object):
        @cache
        def bar(self):
            print 'Calculating self.bar'  
            return 42
    foo=Foo()
    print(foo.bar)
    # Calculating self.bar
    # 42
    print(foo.bar)    
    # 42
    foo.bar=1
    print(foo.bar)
    # 1
    print(Foo.bar)
    # __get__ called with inst = None
    # <__main__.cache object at 0xb7709b4c>

    # Deleting `foo.bar` from `foo.__dict__` re-exposes the property defined in `Foo`.
    # Thus, calling `foo.bar` again recalculates the value again.
    del foo.bar
    print(foo.bar)
    # Calculating self.bar
    # 42

demo_cache()

Python 3.2提供了一个内置的装饰器，你可以用它来创建LRU缓存：
@functools.lru_cache(maxsize=128, typed=False)
或者，如果您使用的是Flask / Werkzeug，则有@cached_property装饰器。
对于Django，尝试from django.utils.functional import cached_property

因为我也有同样的问题，所以我不得不查了一下。
来自标准库的functools包也会得到一个cached_property装饰器，不幸的是，它只在Python 3.8中可用（截至本文发表时，它是Python 3.8a0），替代等待的方法是使用一个定制的装饰器，比如this one as mentioned by 0xc0de）或Django的装饰器，现在，然后再切换：

from django.utils.functional import cached_property
# from functools import cached_property # Only 3.8+ :(

@unutbu的回答中提到的Denis Otkidach的decorator发表在O 'Reilly的Python Cookbook中，不幸的是，O' Reilly没有为代码示例指定任何许可证--就像重用代码的非正式许可一样。
如果你需要一个带有自由许可证的缓存属性装饰器，你可以使用Ken Seehof的@cached_property，它是在MIT license下显式发布的。

def cached_property(f):
    """returns a cached property that is calculated by function f"""
    def get(self):
        try:
            return self._property_cache[f]
        except AttributeError:
            self._property_cache = {}
            x = self._property_cache[f] = f(self)
            return x
        except KeyError:
            x = self._property_cache[f] = f(self)
            return x

    return property(get)

注：为了可用选项的完整性而添加。
不，property默认不缓存。但是有几个选项可以实现这种行为，我想再添加一个：
https://github.com/pydanny/cached-property