只是补充:

dir() is the most powerful/fundamental tool. (Most recommended) Solutions other than dir() merely provide their way of dealing the output of dir(). Listing 2nd level attributes or not, it is important to do the sifting by yourself, because sometimes you may want to sift out internal vars with leading underscores __, but sometimes you may well need the __doc__ doc-string. __dir__() and dir() returns identical content. __dict__ and dir() are different. __dict__ returns incomplete content. IMPORTANT: __dir__() can be sometimes overwritten with a function, value or type, by the author for whatever purpose. Here is an example: \\...\\torchfun.py in traverse(self, mod, search_attributes) 445 if prefix in traversed_mod_names: 446 continue 447 names = dir(m) 448 for name in names: 449 obj = getattr(m,name) TypeError: descriptor __dir__ of 'object' object needs an argument The author of PyTorch modified the __dir__() method to something that requires an argument. This modification makes dir() fail. If you want a reliable scheme to traverse all attributes of an object, do remember that every pythonic standard can be overridden and may not hold, and every convention may be unreliable.

对于完整的属性列表，简短的回答是:不。问题是属性实际上被定义为getattr内置函数接受的参数。由于用户可以重新实现__getattr__，突然允许任何类型的属性，没有可能的通用方法来生成该列表。dir函数返回__dict__属性中的键，即，如果__getattr__方法没有重新实现，则所有可访问的属性。

至于第二个问题，其实没有什么意义。实际上，方法是可调用的属性，仅此而已。你可以过滤可调用的属性，并使用inspect模块确定类方法、方法或函数。

这就是为什么在python 2.6中添加了新的__dir__()方法

see:

http://docs.python.org/whatsnew/2.6.html#other-language-changes(向下滚动一点) http://bugs.python.org/issue1591665

这就是我怎么做的，对你不断添加属性的简单自定义对象很有用:

给定一个用obj = type(" obj "，(object，)，{})创建的对象，或者简单地通过:

class Obj: pass
obj = Obj()

添加一些属性:

obj.name = 'gary'
obj.age = 32

然后，获取一个只有自定义属性的字典:

{key: value for key, value in obj.__dict__.items() if not key.startswith("__")}

# {'name': 'gary', 'age': 32}

下面是对PierreBdR和Moe的回答的补充:

For Python >= 2.6 and new-style classes, dir() seems to be enough. For old-style classes, we can at least do what a standard module does to support tab completion: in addition to dir(), look for __class__, and then to go for its __bases__: # code borrowed from the rlcompleter module # tested under Python 2.6 ( sys.version = '2.6.5 (r265:79063, Apr 16 2010, 13:09:56) \n[GCC 4.4.3]' ) # or: from rlcompleter import get_class_members def get_class_members(klass): ret = dir(klass) if hasattr(klass,'__bases__'): for base in klass.__bases__: ret = ret + get_class_members(base) return ret def uniq( seq ): """ the 'set()' way ( use dict when there's no set ) """ return list(set(seq)) def get_object_attrs( obj ): # code borrowed from the rlcompleter module ( see the code for Completer::attr_matches() ) ret = dir( obj ) ## if "__builtins__" in ret: ## ret.remove("__builtins__") if hasattr( obj, '__class__'): ret.append('__class__') ret.extend( get_class_members(obj.__class__) ) ret = uniq( ret ) return ret

(为了简洁起见，删除了测试代码和输出，但基本上对于新样式的对象，我们似乎对get_object_attrs()得到了与dir()相同的结果，而对于旧样式的类，dir()输出的主要添加似乎是__class__属性。)

只是补充:

dir() is the most powerful/fundamental tool. (Most recommended) Solutions other than dir() merely provide their way of dealing the output of dir(). Listing 2nd level attributes or not, it is important to do the sifting by yourself, because sometimes you may want to sift out internal vars with leading underscores __, but sometimes you may well need the __doc__ doc-string. __dir__() and dir() returns identical content. __dict__ and dir() are different. __dict__ returns incomplete content. IMPORTANT: __dir__() can be sometimes overwritten with a function, value or type, by the author for whatever purpose. Here is an example: \\...\\torchfun.py in traverse(self, mod, search_attributes) 445 if prefix in traversed_mod_names: 446 continue 447 names = dir(m) 448 for name in names: 449 obj = getattr(m,name) TypeError: descriptor __dir__ of 'object' object needs an argument The author of PyTorch modified the __dir__() method to something that requires an argument. This modification makes dir() fail. If you want a reliable scheme to traverse all attributes of an object, do remember that every pythonic standard can be overridden and may not hold, and every convention may be unreliable.