装饰器检查类中的输入类型

Question

通过使用装饰器，我可以检查函数的变量类型。像这样的：

def accepts(*types):
    def check_accepts(f):
        assert len(types) == f.__code__.co_argcount
        def new_f(*args, **kwds):
            for (a, t) in zip(args, types):
                assert isinstance(a, t), \
                       "arg %r does not match %s" % (a,t)
            return f(*args, **kwds)
        new_f.__name__ = f.__name__
        return new_f
    return check_accepts

@accepts(int, (int,float))
def func(arg1, arg2):
    return arg1 * arg2

func(3, 2) # -> 6
func('3', 2) # -> AssertionError: arg '3' does not match <type 'int'>

它适用于普通的简单。但我不知道如何在课堂上使用它：

class Test()
   @accepts(pd.DataFrame)
   def print_dataframe(df):
        print(df)

我无法初始化新课程并使用它。 请教我如何使用它

Answer 1

正如所写，print_dataframe 是一个实例方法，因此您需要考虑到这一点：

NO_CHECK = object()

def accepts(*types):
    def check_accepts(f):
        assert len(types) == f.__code__.co_argcount
        def new_f(*args, **kwds):
            for (a, t) in zip(args, types):
                if t is NO_CHECK:
                    continue
                assert isinstance(a, t), \
                       "arg %r does not match %s" % (a,t)
            return f(*args, **kwds)
        new_f.__name__ = f.__name__
        return new_f
    return check_accepts

# Using NO_CHECK because it's easier to skip checking the self argument
# than it is to handle a check for that as-yet-undefined class Test
class Test():
   @accepts(NO_CHECK, pd.DataFrame)
   def print_dataframe(self, df):
        print(df)

或将print_dataframe 重新定义为静态方法：

   class Test():
       @staticmethod
       @accepts(pd.DataFrame)
       def print_dataframe(df):
            print(df)