你可能需要isinstance内置函数:

self.data = data if isinstance(data, list) else self.parse(data)

你应该使用isinstance

isinstance(...)
    isinstance(object, class-or-type-or-tuple) -> bool

    Return whether an object is an instance of a class or of a subclass thereof.
    With a type as second argument, return whether that is the object's type.
    The form using a tuple, isinstance(x, (A, B, ...)), is a shortcut for
    isinstance(x, A) or isinstance(x, B) or ... (etc.).

你可能需要isinstance内置函数:

self.data = data if isinstance(data, list) else self.parse(data)

非常好的问题。我也解决了这个问题，虽然我同意“工厂”(类方法构造函数)是一个很好的方法，但我想建议另一个我也发现非常有用的方法:

下面是一个示例(这是一个read方法而不是构造函数，但思想是相同的):

def read(self, str=None, filename=None, addr=0):
    """ Read binary data and return a store object. The data
        store is also saved in the interal 'data' attribute.

        The data can either be taken from a string (str 
        argument) or a file (provide a filename, which will 
        be read in binary mode). If both are provided, the str 
        will be used. If neither is provided, an ArgumentError 
        is raised.
    """
    if str is None:
        if filename is None:
            raise ArgumentError('Please supply a string or a filename')

        file = open(filename, 'rb')
        str = file.read()
        file.close()
    ...
    ... # rest of code

这里的关键思想是使用Python对命名参数的出色支持来实现这一点。现在，如果我想从文件中读取数据，我说:

obj.read(filename="blob.txt")

为了从字符串中读取它，我说:

obj.read(str="\x34\x55")

这样用户就只有一个方法可以调用。如您所见，在内部处理它并不过于复杂

获得“交替构造函数”的一个更简洁的方法是使用类方法。例如:

>>> class MyData:
...     def __init__(self, data):
...         "Initialize MyData from a sequence"
...         self.data = data
...     
...     @classmethod
...     def fromfilename(cls, filename):
...         "Initialize MyData from a file"
...         data = open(filename).readlines()
...         return cls(data)
...     
...     @classmethod
...     def fromdict(cls, datadict):
...         "Initialize MyData from a dict's items"
...         return cls(datadict.items())
... 
>>> MyData([1, 2, 3]).data
[1, 2, 3]
>>> MyData.fromfilename("/tmp/foobar").data
['foo\n', 'bar\n', 'baz\n']
>>> MyData.fromdict({"spam": "ham"}).data
[('spam', 'ham')]

The reason it's neater is that there is no doubt about what type is expected, and you aren't forced to guess at what the caller intended for you to do with the datatype it gave you. The problem with isinstance(x, basestring) is that there is no way for the caller to tell you, for instance, that even though the type is not a basestring, you should treat it as a string (and not another sequence.) And perhaps the caller would like to use the same type for different purposes, sometimes as a single item, and sometimes as a sequence of items. Being explicit takes all doubt away and leads to more robust and clearer code.

好了,好了。我只是用一个元组拼凑了这个例子，而不是文件名，但这很简单。谢谢所有。

class MyData:
    def __init__(self, data):
        self.myList = []
        if isinstance(data, tuple):
            for i in data:
                self.myList.append(i)
        else:
            self.myList = data

    def GetData(self):
        print self.myList

A = [1,2]

B = (2,3)

c = MyData(a)

d = MyData(b)

c.GetData（）

d.GetData（）

[1, 2]

[2, 3]