英文:
"TypeError: Object of type int64 is not JSON serializable" while trying to convert a nested dict to JSON
问题
这是您要翻译的内容的翻译部分：
我有一个嵌套字典，我试图使用`json.dumps(unserialized_data), indent=2)`将其转换为JSON。该字典当前如下所示：{"status": "SUCCESS","data": {"cal": [{"year": 2022,"month": 8,"a": [{"a_id": 1,"b": [{"abc_id": 1,"val": 2342}]}]},{"year": 2022,"month": 9,"a": [{"a_id": 2,"b": [{"abc_id": 3,"val": 2342}]}]}]}}
如何将所有int64类型的整数转换为int，同时保持字典的结构和其他数据类型的值不受影响？
英文:
I have a nested dictionary that I am trying to convert to JSON using json.dumps(unserialized_data), indent=2). The dictionary currently looks like this:
{"status": "SUCCESS","data": {"cal": [{"year": 2022,"month": 8,"a": [{"a_id": 1,"b": [{"abc_id": 1,"val": 2342}]}]},{"year": 2022,"month": 9,"a": [{"a_id": 2,"b": [{"abc_id": 3,"val": 2342}]}]}]}}
How can I convert all integers of type int64 to int while leaving the structure of the dict and values of any other data type unaffected?
答案1
得分: 3
如果您的字典中唯一无法进行JSON序列化的对象都是类型为int64，您可以通过将int作为默认函数来将它们轻松序列化，以便JSON无法序列化的对象：
json.dumps(unserialized_data, indent=2, default=int)
英文:
If the only objects in your dict that aren't JSON-serializable are all of type int64, you can easily serialize them by making int the default function for converting objects that JSON can't serialize:
json.dumps(unserialized_data, indent=2, default=int)
答案2
得分: 1
如果blhsing的条件不适用，您可以递归地将字典中的任何np.int64转换为int：
def cast_type(container, from_types, to_types):if isinstance(container, dict):# 转换字典中的所有内容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):# 转换列表中的所有内容return [cast_type(item, from_types, to_types) for item in container]else:for f, t in zip(from_types, to_types):# 如果项目属于from_types中提到的类型之一，# 则将其转换为相应的to_types类if isinstance(container, f):return t(container)# 除此以外，不进行转换返回return container
from_types和to_types是容器，其中相应的元素提供要从哪种类型转换以及要转换为哪种类型。将您的字典通过此函数运行，然后将其转储为JSON：
import numpy as npimport jsond = {"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)) # 报错print(json.dumps(cast_type(d,[np.int64, np.float64],[int, float]),indent=2))
以JSON格式打印字典：
{"str_data": "foo bar","lst": [1000,1.234],"dct": {"foo": "bar","baz": 6.789,"boo": 10}}
英文:
If blhsing's condition doesn't apply, you can drill down recursively into the dictionary and cast any np.int64 to int:
def cast_type(container, from_types, to_types):if isinstance(container, dict):# cast all contents of dictionaryreturn {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 listreturn [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 classif isinstance(container, f):return t(container)# None of the above, return without castingreturn container
from_types and to_types are containers where corresponding elements give the type to convert from, and the type to convert to.
Run your dictionary through this function, then dump it to json:
import numpy as npimport jsond = {"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 errorprint(json.dumps(cast_type(d,[np.int64, np.float64],[int, float]),indent=2))
Prints the dictionary as JSON:
{"str_data": "foo bar","lst": [1000,1.234],"dct": {"foo": "bar","baz": 6.789,"boo": 10}}
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