Python实现数据类的方法集合

当前Python最新稳定版为3.6。主流Linux发行版官方仓库提供Python版本的有2.7和3.5,默认依然是坚强的2.7。

1、dataclass装饰器。正规军,需要Python 3.7+,还在路上。dataclass装饰器会给类添加__init__、__str__、__repr__等方法。

@dataclass
class InventoryItem:
    '''Class for keeping track of an item in inventory.'''
    name: str
    unit_price: float
    quantity_on_hand: int = 0
 
    def total_cost(self) -> float:
        return self.unit_price * self.quantity_on_hand

2、collections.namedtupletyping.NamedTuple。要求不多的用这两个最合适了。Python 3.6+的typing.NamedTuple才支持默认参数。

class Employee(NamedTuple):
    name: str
    id: int = 3
 
employee = Employee('Guido')
assert employee.id == 3
Employee = namedtuple('Employee', 'name, age, title, department, paygrade')

3、autoassign装饰器,和auto_assign装饰器。算是奇技淫巧,前者支持Python2,后者支持Python 3.5+。

4、collections.namedtuple + functools.partial。通过partial实现默认参数,也是我当前采用的方案。

fields = ("name", "age", "title")
defaults = OrderedDict({"title": None})
Employee = partial(namedtuple("Employee", fields), **defaults)
employee = Employee("Guido", "18")

网上还有一些相对麻烦点的方案,比如重写namedtuple的__new__方法,就不一一列举了

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