问题
I'm currently trying my hands on the new dataclass constructions introduced in Python 3.7. I am currently stuck on trying to do some inheritance of a parent class. It looks like the order of the arguments are botched by my current approach such that the bool parameter in the child class is passed before the other parameters. This is causing a type error.
from dataclasses import dataclass
@dataclass
class Parent:
name: str
age: int
ugly: bool = False
def print_name(self):
print(self.name)
def print_age(self):
print(self.age)
def print_id(self):
print(f'The Name is {self.name} and {self.name} is {self.age} year old')
@dataclass
class Child(Parent):
school: str
ugly: bool = True
jack = Parent('jack snr', 32, ugly=True)
jack_son = Child('jack jnr', 12, school = 'havard', ugly=True)
jack.print_id()
jack_son.print_id()
When I run this code I get this TypeError:
TypeError: non-default argument 'school' follows default argument
How do I fix this?
回答1:
The way dataclasses combines attributes prevents you from being able to use attributes with defaults in a base class and then use attributes without a default (positional attributes) in a subclass.
That's because the attributes are combined by starting from the bottom of the MRO, and building up an ordered list of the attributes in first-seen order; overrides are kept in their original location. So Parent starts out with ['name', 'age', 'ugly'], where ugly has a default, and then Child adds ['school'] to the end of that list (with ugly already in the list). This means you end up with ['name', 'age', 'ugly', 'school'] and because school doesn't have a default, this results in an invalid argument listing for __init__.
This is documented in PEP-557 Dataclasses, under inheritance:
When the Data Class is being created by the
@dataclassdecorator, it looks through all of the class's base classes in reverse MRO (that is, starting atobject) and, for each Data Class that it finds, adds the fields from that base class to an ordered mapping of fields. After all of the base class fields are added, it adds its own fields to the ordered mapping. All of the generated methods will use this combined, calculated ordered mapping of fields. Because the fields are in insertion order, derived classes override base classes.
and under Specification:
TypeErrorwill be raised if a field without a default value follows a field with a default value. This is true either when this occurs in a single class, or as a result of class inheritance.
You do have a few options here to avoid this issue.
The first option is to use separate base classes to force fields with defaults into a later position in the MRO order. At all cost, avoid setting fields directly on classes that are to be used as base classes, such as Parent.
The following class hierarchy works:
# base classes with fields; fields without defaults separate from fields with.
@dataclass
class _ParentBase:
name: str
age: int
@dataclass
class _ParentDefaultsBase:
ugly: bool = False
@dataclass
class _ChildBase(_ParentBase):
school: str
@dataclass
class _ChildDefaultsBase(_ParentDefaultsBase):
ugly: bool = True
# public classes, deriving from base-with, base-without field classes
# subclasses of public classes should put the public base class up front.
@dataclass
class Parent(_ParentDefaultsBase, _ParentBase):
def print_name(self):
print(self.name)
def print_age(self):
print(self.age)
def print_id(self):
print(f"The Name is {self.name} and {self.name} is {self.age} year old")
@dataclass
class Child(Parent, _ChildDefaultsBase, _ChildBase):
pass
By pulling out fields into separate base classes with fields without defaults and fields with defaults, and a carefully selected inheritance order, you can produce an MRO that puts all fields without defaults before those with defaults. The reversed MRO (ignoring object) for Child is:
_ParentBase
_ChildBase
_ParentDefaultsBase
_ChildDefaultsBase
Parent
Note that Parent doesn't set any new fields, so it doesn't matter here that it ends up 'last' in the field listing order. The classes with fields without defaults (_ParentBase and _ChildBase) precede the classes with fields with defaults (_ParentDefaultsBase and _ChildDefaultsBase).
The result is Parent and Child classes with a sane field older, while Child is still a subclass of Parent:
>>> from inspect import signature
>>> signature(Parent)
<Signature (name: str, age: int, ugly: bool = False) -> None>
>>> signature(Child)
<Signature (name: str, age: int, school: str, ugly: bool = True) -> None>
>>> issubclass(Child, Parent)
True
and so you can create instances of both classes:
>>> jack = Parent('jack snr', 32, ugly=True)
>>> jack_son = Child('jack jnr', 12, school='havard', ugly=True)
>>> jack
Parent(name='jack snr', age=32, ugly=True)
>>> jack_son
Child(name='jack jnr', age=12, school='havard', ugly=True)
Another option is to only use fields with defaults; you can still make in an error to not supply a school value, by raising one in __post_init__:
_no_default = object()
@dataclass
class Child(Parent):
school: str = _no_default
ugly: bool = True
def __post_init__(self):
if self.school is _no_default:
raise TypeError("__init__ missing 1 required argument: 'school'")
but this does alter the field order; school ends up after ugly:
<Signature (name: str, age: int, ugly: bool = True, school: str = <object object at 0x1101d1210>) -> None>
and a type hint checker will complain about _no_default not being a string.
You can also use the attrs project, which was the project that inspired dataclasses. It uses a different inheritance merging strategy; it pulls overridden fields in a subclass to the end of the fields list, so ['name', 'age', 'ugly'] in the Parent class becomes ['name', 'age', 'school', 'ugly'] in the Child class; by overriding the field with a default, attrs allows the override without needing to do a MRO dance.
attrs supports defining fields without type hints, but lets stick to the supported type hinting mode by setting auto_attribs=True:
import attr
@attr.s(auto_attribs=True)
class Parent:
name: str
age: int
ugly: bool = False
def print_name(self):
print(self.name)
def print_age(self):
print(self.age)
def print_id(self):
print(f"The Name is {self.name} and {self.name} is {self.age} year old")
@attr.s(auto_attribs=True)
class Child(Parent):
school: str
ugly: bool = True
回答2:
You're seeing this error because an argument without a default value is being added after an argument with a default value. The insertion order of inherited fields into the dataclass is the reverse of Method Resolution Order, which means that the Parent fields come first, even if they are over written later by their children.
An example from PEP-557 - Data Classes:
@dataclass class Base: x: Any = 15.0 y: int = 0 @dataclass class C(Base): z: int = 10 x: int = 15The final list of fields is, in order,
x, y, z. The final type ofxisint, as specified in classC.
Unfortunately, I don't think there's any way around this. My understanding is that if the parent class has a default argument, then no child class can have non-default arguments.
回答3:
based on Martijn Pieters solution I did the following:
1) Create a mixing implementing the post_init
from dataclasses import dataclass
no_default = object()
@dataclass
class NoDefaultAttributesPostInitMixin:
def __post_init__(self):
for key, value in self.__dict__.items():
if value is no_default:
raise TypeError(
f"__init__ missing 1 required argument: '{key}'"
)
2) Then in the classes with the inheritance problem:
from src.utils import no_default, NoDefaultAttributesChild
@dataclass
class MyDataclass(DataclassWithDefaults, NoDefaultAttributesPostInitMixin):
attr1: str = no_default
回答4:
The approach below deals with this problem while using pure python dataclasses and without much boilerplate code.
The ugly_init: dataclasses.InitVar[bool] serves as a pseudo-field just to help us do initialization and will be lost once the instance is created. While ugly: bool = field(init=False) is an instance member which will not be initialized by __init__ method but can be alternatively initialized using __post_init__ method (you can find more here.).
from dataclasses import dataclass, field
@dataclass
class Parent:
name: str
age: int
ugly: bool = field(init=False)
ugly_init: dataclasses.InitVar[bool]
def __post_init__(self, ugly_init: bool):
self.ugly = ugly_init
def print_name(self):
print(self.name)
def print_age(self):
print(self.age)
def print_id(self):
print(f'The Name is {self.name} and {self.name} is {self.age} year old')
@dataclass
class Child(Parent):
school: str
jack = Parent('jack snr', 32, ugly_init=True)
jack_son = Child('jack jnr', 12, school='havard', ugly_init=True)
jack.print_id()
jack_son.print_id()
回答5:
You can use attributes with defaults in parent classes if you exclude them from the init function. If you need the possibility to override the default at init, extend the code with the answer of Praveen Kulkarni.
from dataclasses import dataclass, field
@dataclass
class Parent:
name: str
age: int
ugly: bool = field(default=False, init=False)
@dataclass
class Child(Parent):
school: str
jack = Parent('jack snr', 32)
jack_son = Child('jack jnr', 12, school = 'havard')
jack_son.ugly = True
回答6:
A possible work-around is to use monkey-patching to append the parent fields
import dataclasses as dc
def add_args(parent):
def decorator(orig):
"Append parent's fields AFTER orig's fields"
# Aggregate fields
ff = [(f.name, f.type, f) for f in dc.fields(dc.dataclass(orig))]
ff += [(f.name, f.type, f) for f in dc.fields(dc.dataclass(parent))]
new = dc.make_dataclass(orig.__name__, ff)
new.__doc__ = orig.__doc__
return new
return decorator
class Animal:
age: int = 0
@add_args(Animal)
class Dog:
name: str
noise: str = "Woof!"
@add_args(Animal)
class Bird:
name: str
can_fly: bool = True
Dog("Dusty", 2) # --> Dog(name='Dusty', noise=2, age=0)
b = Bird("Donald", False, 40) # --> Bird(name='Donald', can_fly=False, age=40)
It's also possible to prepend non-default fields,
by checking if f.default is dc.MISSING,
but this is probably too dirty.
While monkey-patching lacks some features of inheritance, it can still be used to add methods to all pseudo-child classes.
For more fine-grained control, set the default values
using dc.field(compare=False, repr=True, ...)
来源：https://stackoverflow.com/questions/51575931/class-inheritance-in-python-3-7-dataclasses