在打字。在Python 3.6.1+中，您可以为NamedTuple字段提供默认值和类型注释。使用打字。如果你只需要前者:

from typing import Any, NamedTuple


class Node(NamedTuple):
    val: Any
    left: 'Node' = None
    right: 'Node' = None

用法:

>>> Node(1)
Node(val=1, left=None, right=None)
>>> n = Node(1)
>>> Node(2, left=n)
Node(val=2, left=Node(val=1, left=None, right=None), right=None)

Also, in case you need both default values and optional mutability, Python 3.7 is going to have data classes (PEP 557) that can in some (many?) cases replace namedtuples. Sidenote: one quirk of the current specification of annotations (expressions after : for parameters and variables and after -> for functions) in Python is that they are evaluated at definition time*. So, since "class names become defined once the entire body of the class has been executed", the annotations for 'Node' in the class fields above must be strings to avoid NameError.

这种类型提示被称为“前向引用”([1]，[2])，在PEP 563中，Python 3.7+将有__future__导入(在4.0中默认启用)，允许使用不带引号的前向引用，推迟它们的计算。

* AFAICT只有局部变量注释不计算在运行时。(来源:PEP 526)

在python3.7+中，有一个全新的defaults= keyword参数。

defaults可以是None或包含默认值的可迭代对象。由于具有默认值的字段必须出现在任何没有默认值的字段之后，因此默认值应用于最右边的参数。例如，如果字段名是['x'， 'y'， 'z']，并且默认值是(1,2)，那么x将是必选参数，y将默认值为1,z将默认值为2。

使用示例:

$ ./python
Python 3.7.0b1+ (heads/3.7:4d65430, Feb  1 2018, 09:28:35) 
[GCC 5.4.0 20160609] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> from collections import namedtuple
>>> nt = namedtuple('nt', ('a', 'b', 'c'), defaults=(1, 2))
>>> nt(0)
nt(a=0, b=1, c=2)
>>> nt(0, 3)  
nt(a=0, b=3, c=2)
>>> nt(0, c=3)
nt(a=0, b=1, c=3)

Python 3.7

使用默认参数。

>>> from collections import namedtuple
>>> fields = ('val', 'left', 'right')
>>> Node = namedtuple('Node', fields, defaults=(None,) * len(fields))
>>> Node()
Node(val=None, left=None, right=None)

或者更好的是，使用新的数据类库，它比namedtuple要好得多。

>>> from dataclasses import dataclass
>>> from typing import Any
>>> @dataclass
... class Node:
...     val: Any = None
...     left: 'Node' = None
...     right: 'Node' = None
>>> Node()
Node(val=None, left=None, right=None)

Python 3.7之前

设置Node.__new__。__defaults__为默认值。

>>> from collections import namedtuple
>>> Node = namedtuple('Node', 'val left right')
>>> Node.__new__.__defaults__ = (None,) * len(Node._fields)
>>> Node()
Node(val=None, left=None, right=None)

Python 2.6之前

设置Node.__new__。Func_defaults为默认值。

>>> from collections import namedtuple
>>> Node = namedtuple('Node', 'val left right')
>>> Node.__new__.func_defaults = (None,) * len(Node._fields)
>>> Node()
Node(val=None, left=None, right=None)

订单

在所有版本的Python中，如果您设置的默认值少于namedtuple中存在的默认值，则默认值将应用于最右边的形参。这允许您保留一些参数作为必需的参数。

>>> Node.__new__.__defaults__ = (1,2)
>>> Node()
Traceback (most recent call last):
  ...
TypeError: __new__() missing 1 required positional argument: 'val'
>>> Node(3)
Node(val=3, left=1, right=2)

Python 2.6至3.6的包装器

这里有一个包装器，它甚至允许您(可选地)将默认值设置为None以外的值。这并不支持所需的参数。

import collections
def namedtuple_with_defaults(typename, field_names, default_values=()):
    T = collections.namedtuple(typename, field_names)
    T.__new__.__defaults__ = (None,) * len(T._fields)
    if isinstance(default_values, collections.Mapping):
        prototype = T(**default_values)
    else:
        prototype = T(*default_values)
    T.__new__.__defaults__ = tuple(prototype)
    return T

例子:

>>> Node = namedtuple_with_defaults('Node', 'val left right')
>>> Node()
Node(val=None, left=None, right=None)
>>> Node = namedtuple_with_defaults('Node', 'val left right', [1, 2, 3])
>>> Node()
Node(val=1, left=2, right=3)
>>> Node = namedtuple_with_defaults('Node', 'val left right', {'right':7})
>>> Node()
Node(val=None, left=None, right=7)
>>> Node(4)
Node(val=4, left=None, right=7)

你也可以用这个:

import inspect

def namedtuple_with_defaults(type, default_value=None, **kwargs):
    args_list = inspect.getargspec(type.__new__).args[1:]
    params = dict([(x, default_value) for x in args_list])
    params.update(kwargs)

    return type(**params)

这基本上让你有可能构造任何带有默认值的命名元组，并只覆盖你需要的参数，例如:

import collections

Point = collections.namedtuple("Point", ["x", "y"])
namedtuple_with_defaults(Point)
>>> Point(x=None, y=None)

namedtuple_with_defaults(Point, x=1)
>>> Point(x=1, y=None)

结合@Denis和@Mark的方法:

from collections import namedtuple
import inspect

class Node(namedtuple('Node', 'left right val')):
    __slots__ = ()
    def __new__(cls, *args, **kwargs):
        args_list = inspect.getargspec(super(Node, cls).__new__).args[len(args)+1:]
        params = {key: kwargs.get(key) for key in args_list + kwargs.keys()}
        return super(Node, cls).__new__(cls, *args, **params) 

这应该支持使用位置参数和混合情况创建元组。 测试用例:

>>> print Node()
Node(left=None, right=None, val=None)

>>> print Node(1,2,3)
Node(left=1, right=2, val=3)

>>> print Node(1, right=2)
Node(left=1, right=2, val=None)

>>> print Node(1, right=2, val=100)
Node(left=1, right=2, val=100)

>>> print Node(left=1, right=2, val=100)
Node(left=1, right=2, val=100)

>>> print Node(left=1, right=2)
Node(left=1, right=2, val=None)

但也支持TypeError:

>>> Node(1, left=2)
TypeError: __new__() got multiple values for keyword argument 'left'

我子类化了namedtuple并重写了__new__方法:

from collections import namedtuple

class Node(namedtuple('Node', ['value', 'left', 'right'])):
    __slots__ = ()
    def __new__(cls, value, left=None, right=None):
        return super(Node, cls).__new__(cls, value, left, right)

这保留了直观的类型层次结构，而创建伪装成类的工厂函数则无法做到这一点。