4.7. Decorator Stdlib Functools¶

4.7.1. Wraps¶

from functools import wraps
@wraps(func)

>>> def mydecorator(func):
...     def wrapper(*args, **kwargs):
...         """wrapper docstring"""
...         return func(*args, **kwargs)
...     return wrapper
>>>
>>>
>>> @mydecorator
... def myfunction(x):
...     """myfunction docstring"""
...     print(x)
>>>
>>>
>>> print(myfunction.__name__)
wrapper
>>>
>>> print(myfunction.__doc__)
wrapper docstring

>>> from functools import wraps
>>>
>>>
>>> def mydecorator(func):
...     @wraps(func)
...     def wrapper(*args, **kwargs):
...         """wrapper docstring"""
...         return func(*args, **kwargs)
...     return wrapper
>>>
>>>
>>> @mydecorator
... def myfunction(x):
...     """myfunction docstring"""
...     print(x)
>>>
>>>
>>> print(myfunction.__name__)
myfunction
>>>
>>> print(myfunction.__doc__)
myfunction docstring

4.7.2. Cached Property¶

from functools import cached_property
@cached_property(method)

>>> import statistics
>>> from functools import cached_property
>>>
>>>
>>> class Iris:
...     def __init__(self, *args):
...         self._measurements = args
...
...     @cached_property
...     def mean(self):
...         return statistics.mean(self._measurements)
...
...     @cached_property
...     def stdev(self):
...         return statistics.stdev(self._measurements)
>>>
>>>
>>> flower = Iris(5.1, 3.5, 1.4, 0.2)
>>> flower.stdev
2.1794494717703365
>>> flower.mean
2.55

4.7.3. LRU (least recently used) cache¶

from functools import lru_cache
@lru_cache(maxsize=None)

>>> from functools import lru_cache
>>>
>>>
>>> @lru_cache(maxsize=None)
... def fib(n):
...     if n < 2:
...         return n
...     return fib(n-1) + fib(n-2)
>>>
>>>
[fib(n) for n in range(16)]
>>> # [0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610]
>>>
fib.cache_info()
>>> # CacheInfo(hits=28, misses=16, maxsize=None, currsize=16)

4.7.4. Assignments¶

Code 4.17. Solution¶

"""
* Assignment: Decorator Functools Func
* Complexity: easy
* Lines of code: 1 lines
* Time: 2 min

English:
    1. Use `functools.wraps` in correct place
    2. Run doctests - all must succeed

Polish:
    1. Użyj `functools.wraps` w odpowiednim miejscu
    2. Uruchom doctesty - wszystkie muszą się powieść

Tests:
    >>> import sys; sys.tracebacklimit = 0

    >>> @mydecorator
    ... def hello():
    ...     '''Hello Docstring'''

    >>> hello.__name__
    'hello'
    >>> hello.__doc__
    'Hello Docstring'
"""

from functools import wraps


def mydecorator(func):
    def wrapper(*args, **kwargs):
        return func(*args, **kwargs)
    return wrapper

Code 4.18. Solution¶

"""
* Assignment: Decorator Functools Args
* Complexity: easy
* Lines of code: 1 lines
* Time: 2 min

English:
    1. Use `functools.wraps` in correct place
    2. Run doctests - all must succeed

Polish:
    1. Użyj `functools.wraps` w odpowiednim miejscu
    2. Uruchom doctesty - wszystkie muszą się powieść

Tests:
    >>> import sys; sys.tracebacklimit = 0

    >>> @mydecorator(happy=False)
    ... def hello():
    ...     '''Hello Docstring'''
    >>> hello.__name__
    'hello'
    >>> hello.__doc__
    'Hello Docstring'
"""

from functools import wraps


def mydecorator(happy=True):
    def decorator(func):
        def wrapper(*args, **kwargs):
            return func(*args, **kwargs)
        return wrapper
    return decorator

Code 4.19. Solution¶

"""
* Assignment: Decorator Functools Cls
* Complexity: easy
* Lines of code: 2 lines
* Time: 5 min

English:
    1. Modify code to restore docstring and name from decorated class
    2. Run doctests - all must succeed

Polish:
    1. Zmodyfikuj kod aby przywrócić docstring oraz nazwę z dekorowanej klasy
    2. Uruchom doctesty - wszystkie muszą się powieść

Tests:
    >>> import sys; sys.tracebacklimit = 0

    >>> @mydecorator
    ... class Hello:
    ...     '''Hello Docstring'''
    >>> hello = Hello()
    >>> hello.__name__
    'Hello'
    >>> hello.__doc__
    'Hello Docstring'
"""

def mydecorator(cls):
    class Wrapper(cls):
        pass
    return Wrapper