解决方案是放入您自己的__eq__方法并设置eq=False，这样类就不会生成自己的方法（尽管检查文档，最后一步是不必要的，但我认为无论如何显式显示是很好的）。

import numpy as np

def array_eq(arr1, arr2):
    return (isinstance(arr1, np.ndarray) and
            isinstance(arr2, np.ndarray) and
            arr1.shape == arr2.shape and
            (arr1 == arr2).all())

@dataclass(eq=False)
class Instr:

    foo: np.ndarray
    bar: np.ndarray

    def __eq__(self, other):
        if not isinstance(other, Instr):
            return NotImplemented
        return array_eq(self.foo, other.foo) and array_eq(self.bar, other.bar)

编辑

一个通用的快速解决方案，用于一些值是numpy数组而另一些不是的通用类

import numpy as np
from dataclasses import dataclass, astuple

def array_safe_eq(a, b) -> bool:
    """Check if a and b are equal, even if they are numpy arrays"""
    if a is b:
        return True
    if isinstance(a, np.ndarray) and isinstance(b, np.ndarray):
        return a.shape == b.shape and (a == b).all()
    try:
        return a == b
    except TypeError:
        return NotImplemented

def dc_eq(dc1, dc2) -> bool:
   """checks if two dataclasses which hold numpy arrays are equal"""
   if dc1 is dc2:
        return True
   if dc1.__class__ is not dc2.__class__:
       return NotImplmeneted  # better than False
   t1 = astuple(dc1)
   t2 = astuple(dc2)
   return all(array_safe_eq(a1, a2) for a1, a2 in zip(t1, t2))

# usage
@dataclass(eq=False)
class T:

   a: int
   b: np.ndarray
   c: np.ndarray

   def __eq__(self, other):
        return dc_eq(self, other)

如果您使用attrs而不是xmlasses，则可以自定义：

from attrs import define, field
import numpy

@define
class C:
   an_array = field(eq=attr.cmp_using(eq=numpy.array_equal))