如果blhsing的条件不适用，可以递归地深入字典，并将任何np.int64转换为int：

def cast_type(container, from_types, to_types):
    if isinstance(container, dict):
        # cast all contents of dictionary 
        return {cast_type(k, from_types, to_types): cast_type(v, from_types, to_types) for k, v in container.items()}
    elif isinstance(container, list):
        # cast all contents of list 
        return [cast_type(item, from_types, to_types) for item in container]
    else:
        for f, t in zip(from_types, to_types):
            # if item is of a type mentioned in from_types,
            # cast it to the corresponding to_types class
            if isinstance(container, f):
                return t(container)
        # None of the above, return without casting 
        return container

from_types和to_types是容器，其中相应的元素给予了要转换的源类型和要转换的目标类型。通过此函数运行字典，然后将其转储到json：

import numpy as np
import json

d = {
  "str_data": "foo bar",
  "lst": [ np.int64(1000), np.float64(1.234) ],
  "dct": {"foo": "bar", "baz": np.float64(6.789), "boo": np.int64(10)}
}

print(json.dumps(d, indent=2)) # throws error

print(json.dumps(
         cast_type(d, 
             [np.int64, np.float64],
             [int,      float]), 
         indent=2))

将字典打印为JSON：

{
  "str_data": "foo bar",
  "lst": [
    1000,
    1.234
  ],
  "dct": {
    "foo": "bar",
    "baz": 6.789,
    "boo": 10
  }
}

在线试用

如果您的dict中唯一不能进行JSON序列化的对象都是int64类型，那么您可以通过将int设置为默认函数来转换JSON不能序列化的对象，从而轻松地将它们序列化：

json.dumps(unserialized_data, indent=2, default=int)