如何使 python 数据类可哈希而不使其不可变？

Question

假设我在 python3 中有一个数据类。我希望能够散列和排序这些对象。我不希望这些是不可变的。

我只想要它们 ordered/hashed 在 id 上。

我在文档中看到我可以实现 _hash_ 以及所有这些，但我想让数据计算为我完成工作，因为它们旨在处理这个。

from dataclasses import dataclass, field

@dataclass(eq=True, order=True)
class Category:
    id: str = field(compare=True)
    name: str = field(default="set this in post_init", compare=False)

a = sorted(list(set([ Category(id='x'), Category(id='y')])))

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: unhashable type: 'Category'

Answer 1

TL;DR

将 frozen=True 与 eq=True 结合使用（这将使实例不可变）。

长答案

来自docs：

__hash__() is used by built-in hash(), and when objects are added to hashed collections such as dictionaries and sets. Having a __hash__() implies that instances of the class are immutable. Mutability is a complicated property that depends on the programmer’s intent, the existence and behavior of __eq__(), and the values of the eq and frozen flags in the dataclass() decorator.

By default, dataclass() will not implicitly add a __hash__() method unless it is safe to do so. Neither will it add or change an existing explicitly defined __hash__() method. Setting the class attribute __hash__ = None has a specific meaning to Python, as described in the __hash__()documentation.

If __hash__() is not explicit defined, or if it is set to None, then dataclass() may add an implicit __hash__() method. Although not recommended, you can force dataclass() to create a __hash__() method with unsafe_hash=True. This might be the case if your class is logically immutable but can nonetheless be mutated. This is a specialized use case and should be considered carefully.

Here are the rules governing implicit creation of a __hash__() method. Note that you cannot both have an explicit __hash__() method in your dataclass and set unsafe_hash=True; this will result in a TypeError.

If eq and frozen are both true, by default dataclass() will generate a __hash__() method for you. If eq is true and frozen is false, __hash__() will be set to None, marking it unhashable (which it is, since it is mutable). If eq is false, __hash__() will be left untouched meaning the __hash__() method of the superclass will be used (if the superclass is object, this means it will fall back to id-based hashing).

Answer 2

来自 the docs:

Here are the rules governing implicit creation of a __hash__() method:

[...]

If eq and frozen are both true, by default dataclass() will generate a __hash__() method for you. If eq is true and frozen is false, __hash__() will be set to None, marking it unhashable (which it is, since it is mutable). If eq is false, __hash__() will be left untouched meaning the __hash__() method of the superclass will be used (if the superclass is object, this means it will fall back to id-based hashing).

由于您设置了 eq=True 并保留了默认值 frozen (False)，因此您的数据class 无法散列。

您有 3 个选项：

设置 frozen=True（除了 eq=True），这将使您的 class 不可变且可散列。
设置 unsafe_hash=True，这将创建一个 __hash__ 方法但使您的 class 可变，因此如果您的 class 的实例存在问题在存储在字典或集合中时被修改：
```
cat = Category('foo', 'bar')
categories = {cat}
cat.id = 'baz'

print(cat in categories)  # False
```
手动实现一个 __hash__ 方法。

Answer 3

我想添加一个使用 unsafe_hash 的特别说明。

您可以通过设置 compare=False 或 hash=False 排除字段进行哈希比较。（hash 默认继承自 compare）。

如果您将节点存储在图中，但想在不破坏其散列的情况下将它们标记为已访问（例如，如果它们位于一组未访问的节点中......），这可能会很有用。

from dataclasses import dataclass, field
@dataclass(unsafe_hash=True)
class node:
    x:int
    visit_count: int = field(default=10, compare=False)  # hash inherits compare setting. So valid.
    # visit_count: int = field(default=False, hash=False)   # also valid. Arguably easier to read, but can break some compare code.
    # visit_count: int = False   # if mutated, hashing breaks. (3* printed)

s = set()
n = node(1)
s.add(n)
if n in s: print("1* n in s")
n.visit_count = 11
if n in s:
    print("2* n still in s")
else:
    print("3* n is lost to the void because hashing broke.")

我花了小时才弄清楚...我发现 python 文档是关于数据类的有用的进一步阅读。具体请参阅字段文档和数据类 arg 文档。 https://docs.python.org/3/library/dataclasses.html

如何使 python 数据类可哈希而不使其不可变？

How can I make a python dataclass hashable without making them immutable?

python

python-3.x

hash

python-dataclasses