Python 메모 / 지연 조회 속성 데코레이터

Python 메모 / 지연 조회 속성 데코레이터

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최근에 인스턴스 속성이 데이터베이스에 저장된 값을 반영하는 많은 클래스를 포함하는 기존 코드베이스를 살펴 보았습니다. 데이터베이스 조회가 지연되도록 이러한 속성을 많이 리팩터링했습니다. 생성자에서 초기화되지 않고 처음 읽을 때만 초기화됩니다. 이러한 속성은 인스턴스의 수명 동안 변경되지 않지만 처음 계산하는 데에는 실제 병목 현상이 발생하고 특수한 경우에만 실제로 액세스됩니다. 따라서 데이터베이스에서 검색된 후에도 캐시 될 수 있습니다 (따라서 입력이 단순히 "입력 없음" 인 메모 화 정의에 적합 ).

다양한 클래스의 다양한 속성에 대해 다음 코드 스 니펫을 반복해서 입력합니다.

class testA(object):

  def __init__(self):
    self._a = None
    self._b = None

  @property
  def a(self):
    if self._a is None:
      # Calculate the attribute now
      self._a = 7
    return self._a

  @property
  def b(self):
    #etc

내가 알지 못하는 파이썬에서 이미 이것을 수행하는 기존 데코레이터가 있습니까? 아니면 이것을 수행하는 데코레이터를 정의하는 합리적으로 간단한 방법이 있습니까?

저는 Python 2.5에서 작업하고 있지만 2.6 답변이 크게 다르면 여전히 흥미로울 수 있습니다.

노트

이 질문은 파이썬이이를 위해 많은 기성 데코레이터를 포함하기 전에 요청되었습니다. 용어를 수정하기 위해서만 업데이트했습니다.

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모든 종류의 훌륭한 유틸리티를 위해 볼튼을 사용 하고 있습니다.

해당 라이브러리의 일부로 cachedproperty 있습니다 .

from boltons.cacheutils import cachedproperty

class Foo(object):
    def __init__(self):
        self.value = 4

    @cachedproperty
    def cached_prop(self):
        self.value += 1
        return self.value


f = Foo()
print(f.value)  # initial value
print(f.cached_prop)  # cached property is calculated
f.value = 1
print(f.cached_prop)  # same value for the cached property - it isn't calculated again
print(f.value)  # the backing value is different (it's essentially unrelated value)

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다음은 lazy 속성 데코레이터의 구현 예입니다.

import functools

def lazyprop(fn):
    attr_name = '_lazy_' + fn.__name__

    @property
    @functools.wraps(fn)
    def _lazyprop(self):
        if not hasattr(self, attr_name):
            setattr(self, attr_name, fn(self))
        return getattr(self, attr_name)

    return _lazyprop


class Test(object):

    @lazyprop
    def a(self):
        print 'generating "a"'
        return range(5)

대화식 세션 :

>>> t = Test()
>>> t.__dict__
{}
>>> t.a
generating "a"
[0, 1, 2, 3, 4]
>>> t.__dict__
{'_lazy_a': [0, 1, 2, 3, 4]}
>>> t.a
[0, 1, 2, 3, 4]

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I wrote this one for myself... To be used for true one-time calculated lazy properties. I like it because it avoids sticking extra attributes on objects, and once activated does not waste time checking for attribute presence, etc.:

import functools

class lazy_property(object):
    '''
    meant to be used for lazy evaluation of an object attribute.
    property should represent non-mutable data, as it replaces itself.
    '''

    def __init__(self, fget):
        self.fget = fget

        # copy the getter function's docstring and other attributes
        functools.update_wrapper(self, fget)

    def __get__(self, obj, cls):
        if obj is None:
            return self

        value = self.fget(obj)
        setattr(obj, self.fget.__name__, value)
        return value


class Test(object):

    @lazy_property
    def results(self):
        calcs = 1  # Do a lot of calculation here
        return calcs

Note: The lazy_property class is a non-data descriptor, which means it is read-only. Adding a __set__ method would prevent it from working correctly.

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Here's a callable that takes an optional timeout argument, in the __call__ you could also copy over the __name__, __doc__, __module__ from func's namespace:

import time

class Lazyproperty(object):

    def __init__(self, timeout=None):
        self.timeout = timeout
        self._cache = {}

    def __call__(self, func):
        self.func = func
        return self

    def __get__(self, obj, objcls):
        if obj not in self._cache or \
          (self.timeout and time.time() - self._cache[key][1] > self.timeout):
            self._cache[obj] = (self.func(obj), time.time())
        return self._cache[obj]

ex:

class Foo(object):

    @Lazyproperty(10)
    def bar(self):
        print('calculating')
        return 'bar'

>>> x = Foo()
>>> print(x.bar)
calculating
bar
>>> print(x.bar)
bar
...(waiting 10 seconds)...
>>> print(x.bar)
calculating
bar

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property is a class. A descriptor to be exact. Simply derive from it and implement the desired behavior.

class lazyproperty(property):
   ....

class testA(object):
   ....
  a = lazyproperty('_a')
  b = lazyproperty('_b')

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What you really want is the reify (source linked!) decorator from Pyramid:

Use as a class method decorator. It operates almost exactly like the Python @property decorator, but it puts the result of the method it decorates into the instance dict after the first call, effectively replacing the function it decorates with an instance variable. It is, in Python parlance, a non-data descriptor. The following is an example and its usage:

>>> from pyramid.decorator import reify

>>> class Foo(object):
...     @reify
...     def jammy(self):
...         print('jammy called')
...         return 1

>>> f = Foo()
>>> v = f.jammy
jammy called
>>> print(v)
1
>>> f.jammy
1
>>> # jammy func not called the second time; it replaced itself with 1
>>> # Note: reassignment is possible
>>> f.jammy = 2
>>> f.jammy
2

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There is a mix up of terms and/or confusion of concepts both in question and in answers so far.

Lazy evaluation just means that something is evaluated at runtime at the last possible moment when a value is needed. The standard @property decorator does just that.(*) The decorated function is evaluated only and every time you need the value of that property. (see wikipedia article about lazy evaluation)

(*)Actually a true lazy evaluation (compare e.g. haskell) is very hard to achieve in python (and results in code which is far from idiomatic).

Memoization is the correct term for what the asker seems to be looking for. Pure functions that do not depend on side effects for return value evaluation can be safely memoized and there is actually a decorator in functools @functools.lru_cache so no need for writing own decorators unless you need specialized behavior.

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You can do this nice and easily by building a class from Python native property:

class cached_property(property):
    def __init__(self, func, name=None, doc=None):
        self.__name__ = name or func.__name__
        self.__module__ = func.__module__
        self.__doc__ = doc or func.__doc__
        self.func = func

    def __set__(self, obj, value):
        obj.__dict__[self.__name__] = value

    def __get__(self, obj, type=None):
        if obj is None:
            return self
        value = obj.__dict__.get(self.__name__, None)
        if value is None:
            value = self.func(obj)
            obj.__dict__[self.__name__] = value
        return value

We can use this property class like regular class property ( It's also support item assignment as you can see)

class SampleClass():
    @cached_property
    def cached_property(self):
        print('I am calculating value')
        return 'My calculated value'


c = SampleClass()
print(c.cached_property)
print(c.cached_property)
c.cached_property = 2
print(c.cached_property)
print(c.cached_property)

Value only calculated first time and after that we used our saved value

Output:

I am calculating value
My calculated value
My calculated value
2
2

참고URL : https://stackoverflow.com/questions/3012421/python-memoising-deferred-lookup-property-decorator