./python.exe
Python 3.8.0a4+ (heads/master:9ee2c264c3, May 28 2019, 17:44:24)
[Clang 10.0.0 (clang-1000.11.45.5)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
> from functools import cached_property
> class Foo:
...   @cached_property
...   def bar(self):
...     print('calculate somethings')
...     return 42
...
> f = Foo()
> f.bar
calculate somethings
42
> f.bar
42

import time
from threading import Thread
from werkzeug.utils import cached_property
class Foo:
  def __init__(self):
    self.count = 0
  @cached_property
  def bar(self):
    time.sleep(1) # 模仿耗时的逻辑，让多线程启动后能执行一会而不是直接结束
    self.count += 1
    return self.count
threads = []
f = Foo()
for x in range(10):
  t = Thread(target=lambda: f.bar)
  t.start()
  threads.append(t)
for t in threads:
  t.join()

 ipython -i threaded_cached_property.py
Python 3.7.1 (default, Dec 13 2018, 22:28:16)
Type 'copyright', 'credits' or 'license' for more information
IPython 7.5.0 -- An enhanced Interactive Python. Type '"htmlcode">

./python.exe
Python 3.8.0a4+ (heads/master:8cd5165ba0, May 27 2019, 22:28:15)
[Clang 10.0.0 (clang-1000.11.45.5)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
> import time
> from threading import Thread
> from functools import cached_property
>
>
> class Foo:
...   def __init__(self):
...     self.count = 0
...   @cached_property
...   def bar(self):
...     time.sleep(1)
...     self.count += 1
...     return self.count
...
>
> threads = []
> f = Foo()
>
> for x in range(10):
...   t = Thread(target=lambda: f.bar)
...   t.start()
...   threads.append(t)
...
> for t in threads:
...   t.join()
...
> f.bar


可以看到，由于加了线程锁， f.bar 的结果是正确的1。
cached_property不支持异步
除了 pydanny/cached-property 这个包以外，其他的包都不支持异步函数：


./python.exe -m asyncio
asyncio REPL 3.8.0a4+ (heads/master:8cd5165ba0, May 27 2019, 22:28:15)
[Clang 10.0.0 (clang-1000.11.45.5)] on darwin
Use "await" directly instead of "asyncio.run()".
Type "help", "copyright", "credits" or "license" for more information.
> import asyncio
> from functools import cached_property
>
>
> class Foo:
...   def __init__(self):
...     self.count = 0
...   @cached_property
...   async def bar(self):
...     await asyncio.sleep(1)
...     self.count += 1
...     return self.count
...
> f = Foo()
> await f.bar
1
> await f.bar
Traceback (most recent call last):
 File "/Users/dongwm/cpython/Lib/concurrent/futures/_base.py", line 439, in result
  return self.__get_result()
 File "/Users/dongwm/cpython/Lib/concurrent/futures/_base.py", line 388, in __get_result
  raise self._exception
 File "<console>", line 1, in <module>
RuntimeError: cannot reuse already awaited coroutine
pydanny/cached-property的异步支持实现的很巧妙，我把这部分逻辑抽出来：
try:
  import asyncio
except (ImportError, SyntaxError):
  asyncio = None
class cached_property:
  def __get__(self, obj, cls):
    ...
    if asyncio and asyncio.iscoroutinefunction(self.func):
      return self._wrap_in_coroutine(obj)
    ...
  def _wrap_in_coroutine(self, obj):
    @asyncio.coroutine
    def wrapper():
      future = asyncio.ensure_future(self.func(obj))
      obj.__dict__[self.func.__name__] = future
      return future
    return wrapper()


我解析一下这段代码：
对 import asyncio 的异常处理主要为了处理Python 2和Python3.4之前没有asyncio的问题
__get__ 里面会判断方法是不是协程函数，如果是会 return self._wrap_in_coroutine(obj)

_wrap_in_coroutine 里面首先会把方法封装成一个Task，并把Task对象缓存在 obj.__dict__ 里，wrapper通过装饰器 asyncio.coroutine 包装最后返回。
为了方便理解，在IPython运行一下：

In : f = Foo()
In : f.bar  # 由于用了`asyncio.coroutine`装饰器，这是一个生成器对象

Out: <generator object cached_property._wrap_in_coroutine.<locals>.wrapper at 0x10a26f0c0>
In : await f.bar  # 第一次获得f.bar的值，会sleep 1秒然后返回结果

Out: 1
In : f.__dict__['bar']  # 这样就把Task对象缓存到了f.__dict__里面了，Task状态是finished

Out: <Task finished coro=<Foo.bar() done, defined at <ipython-input-54-7f5df0e2b4e7>:4> result=1>
In : f.bar  # f.bar已经是一个task了

Out: <Task finished coro=<Foo.bar() done, defined at <ipython-input-54-7f5df0e2b4e7>:4> result=1>
In : await f.bar  # 相当于 await task

Out: 1

可以看到多次await都可以获得正常结果。如果一个Task对象已经是finished状态，直接返回结果而不会重复执行了。
总结
以上所述是小编给大家介绍的Python 3.8中实现functools.cached_property功能,希望对大家有所帮助，如果大家有任何疑问请给我留言，小编会及时回复大家的。在此也非常感谢大家对网站的支持！

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