如何使一个Python类序列化?
class FileItem:
def __init__(self, fname):
self.fname = fname
尝试序列化为JSON:
>>> import json
>>> x = FileItem('/foo/bar')
>>> json.dumps(x)
TypeError: Object of type 'FileItem' is not JSON serializable
如何使一个Python类序列化?
class FileItem:
def __init__(self, fname):
self.fname = fname
尝试序列化为JSON:
>>> import json
>>> x = FileItem('/foo/bar')
>>> json.dumps(x)
TypeError: Object of type 'FileItem' is not JSON serializable
当前回答
Jsonweb似乎是我的最佳解决方案。参见http://www.jsonweb.info/en/latest/
from jsonweb.encode import to_object, dumper
@to_object()
class DataModel(object):
def __init__(self, id, value):
self.id = id
self.value = value
>>> data = DataModel(5, "foo")
>>> dumper(data)
'{"__type__": "DataModel", "id": 5, "value": "foo"}'
其他回答
除了Onur的答案,你可能想要处理如下的datetime类型。(以便处理:'datetime. time.)Datetime对象没有属性dict异常。)
def datetime_option(value):
if isinstance(value, datetime.date):
return value.timestamp()
else:
return value.__dict__
用法:
def toJSON(self):
return json.dumps(self, default=datetime_option, sort_keys=True, indent=4)
class DObject(json.JSONEncoder):
def delete_not_related_keys(self, _dict):
for key in ["skipkeys", "ensure_ascii", "check_circular", "allow_nan", "sort_keys", "indent"]:
try:
del _dict[key]
except:
continue
def default(self, o):
if hasattr(o, '__dict__'):
my_dict = o.__dict__.copy()
self.delete_not_related_keys(my_dict)
return my_dict
else:
return o
a = DObject()
a.name = 'abdul wahid'
b = DObject()
b.name = a
print(json.dumps(b, cls=DObject))
如果你能够安装一个软件包,我建议你试试dill,它在我的项目中工作得很好。这个包的一个优点是它具有与pickle相同的接口,因此如果您已经在项目中使用了pickle,则可以简单地替换为dill并查看脚本是否运行,而无需更改任何代码。所以这是一个非常便宜的解决方案!
(完全反披露:我与莳萝项目没有任何关联,也从未参与过。)
安装包:
pip install dill
然后编辑你的代码导入莳萝而不是pickle:
# import pickle
import dill as pickle
运行脚本,看看它是否有效。(如果是的话,你可能想要清理你的代码,这样你就不再隐藏pickle模块的名字了!)
关于dill可以和不能序列化的数据类型的一些细节,来自项目页面:
dill can pickle the following standard types: none, type, bool, int, long, float, complex, str, unicode, tuple, list, dict, file, buffer, builtin, both old and new style classes, instances of old and new style classes, set, frozenset, array, functions, exceptions dill can also pickle more ‘exotic’ standard types: functions with yields, nested functions, lambdas, cell, method, unboundmethod, module, code, methodwrapper, dictproxy, methoddescriptor, getsetdescriptor, memberdescriptor, wrapperdescriptor, xrange, slice, notimplemented, ellipsis, quit dill cannot yet pickle these standard types: frame, generator, traceback
你知道预期产量是多少吗?例如,这个可以吗?
>>> f = FileItem("/foo/bar")
>>> magic(f)
'{"fname": "/foo/bar"}'
在这种情况下,你只需调用json.dumps(f.__dict__)。
如果您想要更多自定义输出,那么您必须继承JSONEncoder并实现您自己的自定义序列化。
对于一个简单的例子,请参见下面。
>>> from json import JSONEncoder
>>> class MyEncoder(JSONEncoder):
def default(self, o):
return o.__dict__
>>> MyEncoder().encode(f)
'{"fname": "/foo/bar"}'
然后你把这个类作为cls kwarg传递给json.dumps()方法:
json.dumps(cls=MyEncoder)
如果还想解码,则必须向JSONDecoder类提供一个自定义object_hook。例如:
>>> def from_json(json_object):
if 'fname' in json_object:
return FileItem(json_object['fname'])
>>> f = JSONDecoder(object_hook = from_json).decode('{"fname": "/foo/bar"}')
>>> f
<__main__.FileItem object at 0x9337fac>
>>>
对于更复杂的类,您可以考虑使用jsonpickle工具:
jsonpickle is a Python library for serialization and deserialization of complex Python objects to and from JSON. The standard Python libraries for encoding Python into JSON, such as the stdlib’s json, simplejson, and demjson, can only handle Python primitives that have a direct JSON equivalent (e.g. dicts, lists, strings, ints, etc.). jsonpickle builds on top of these libraries and allows more complex data structures to be serialized to JSON. jsonpickle is highly configurable and extendable–allowing the user to choose the JSON backend and add additional backends.
(链接到PyPi上的jsonpickle)