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
我们经常在日志文件中转储JSON格式的复杂字典。虽然大多数字段携带重要信息，但我们不太关心内置的类对象(例如子进程)。Popen对象)。由于存在这些不可序列化的对象，对json.dumps()的调用会失败。
为了解决这个问题，我构建了一个小函数来转储对象的字符串表示形式，而不是转储对象本身。如果您正在处理的数据结构嵌套太多，您可以指定嵌套的最大级别/深度。
from time import time
def safe_serialize(obj , max_depth = 2):
max_level = max_depth
def _safe_serialize(obj , current_level = 0):
nonlocal max_level
# If it is a list
if isinstance(obj , list):
if current_level >= max_level:
return "[...]"
result = list()
for element in obj:
result.append(_safe_serialize(element , current_level + 1))
return result
# If it is a dict
elif isinstance(obj , dict):
if current_level >= max_level:
return "{...}"
result = dict()
for key , value in obj.items():
result[f"{_safe_serialize(key , current_level + 1)}"] = _safe_serialize(value , current_level + 1)
return result
# If it is an object of builtin class
elif hasattr(obj , "__dict__"):
if hasattr(obj , "__repr__"):
result = f"{obj.__repr__()}_{int(time())}"
else:
try:
result = f"{obj.__class__.__name__}_object_{int(time())}"
except:
result = f"object_{int(time())}"
return result
# If it is anything else
else:
return obj
return _safe_serialize(obj)
由于字典也可以有不可序列化的键，转储它们的类名或对象表示将导致所有键都具有相同的名称，这将抛出错误，因为所有键都需要有唯一的名称，这就是为什么当前时间Since epoch被int(time())附加到对象名称。
可以使用以下具有不同级别/深度的嵌套字典来测试该函数
d = {
"a" : {
"a1" : {
"a11" : {
"a111" : "some_value" ,
"a112" : "some_value" ,
} ,
"a12" : {
"a121" : "some_value" ,
"a122" : "some_value" ,
} ,
} ,
"a2" : {
"a21" : {
"a211" : "some_value" ,
"a212" : "some_value" ,
} ,
"a22" : {
"a221" : "some_value" ,
"a222" : "some_value" ,
} ,
} ,
} ,
"b" : {
"b1" : {
"b11" : {
"b111" : "some_value" ,
"b112" : "some_value" ,
} ,
"b12" : {
"b121" : "some_value" ,
"b122" : "some_value" ,
} ,
} ,
"b2" : {
"b21" : {
"b211" : "some_value" ,
"b212" : "some_value" ,
} ,
"b22" : {
"b221" : "some_value" ,
"b222" : "some_value" ,
} ,
} ,
} ,
"c" : subprocess.Popen("ls -l".split() , stdout = subprocess.PIPE , stderr = subprocess.PIPE) ,
}
执行以下命令将会得到-
print("LEVEL 3")
print(json.dumps(safe_serialize(d , 3) , indent = 4))
print("\n\n\nLEVEL 2")
print(json.dumps(safe_serialize(d , 2) , indent = 4))
print("\n\n\nLEVEL 1")
print(json.dumps(safe_serialize(d , 1) , indent = 4))
结果:
LEVEL 3
{
"a": {
"a1": {
"a11": "{...}",
"a12": "{...}"
},
"a2": {
"a21": "{...}",
"a22": "{...}"
}
},
"b": {
"b1": {
"b11": "{...}",
"b12": "{...}"
},
"b2": {
"b21": "{...}",
"b22": "{...}"
}
},
"c": "<Popen: returncode: None args: ['ls', '-l']>"
}
LEVEL 2
{
"a": {
"a1": "{...}",
"a2": "{...}"
},
"b": {
"b1": "{...}",
"b2": "{...}"
},
"c": "<Popen: returncode: None args: ['ls', '-l']>"
}
LEVEL 1
{
"a": "{...}",
"b": "{...}",
"c": "<Popen: returncode: None args: ['ls', '-l']>"
}
[注意]:仅在不关心内置类对象的序列化时使用此选项。
其他回答
import json
class Foo(object):
def __init__(self):
self.bar = 'baz'
self._qux = 'flub'
def somemethod(self):
pass
def default(instance):
return {k: v
for k, v in vars(instance).items()
if not str(k).startswith('_')}
json_foo = json.dumps(Foo(), default=default)
assert '{"bar": "baz"}' == json_foo
print(json_foo)
为了给这场11年的大火再添一根柴，我想要一个满足以下条件的解决方案:
只允许使用json.dumps(obj)序列化类FileItem的实例 允许FileItem实例具有属性:FileItem .fname 允许FileItem实例提供给任何库，使用json.dumps(obj)序列化它 不需要将任何其他字段传递给json。转储(如自定义序列化器)
IE:
fileItem = FileItem('filename.ext')
assert json.dumps(fileItem) == '{"fname": "filename.ext"}'
assert fileItem.fname == 'filename.ext'
我的解决方案是:
obj的类是否继承自dict 将每个对象属性映射到底层字典
class FileItem(dict):
def __init__(self, fname):
self['fname'] = fname
#fname property
fname: str = property()
@fname.getter
def fname(self):
return self['fname']
@fname.setter
def fname(self, value: str):
self['fname'] = value
#Repeat for other properties
是的，如果你有很多属性，这有点冗长，但它是JSONSerializable，它的行为像一个对象，你可以把它给任何库，去json.dumps(obj)它。
我们经常在日志文件中转储JSON格式的复杂字典。虽然大多数字段携带重要信息，但我们不太关心内置的类对象(例如子进程)。Popen对象)。由于存在这些不可序列化的对象，对json.dumps()的调用会失败。
为了解决这个问题，我构建了一个小函数来转储对象的字符串表示形式，而不是转储对象本身。如果您正在处理的数据结构嵌套太多，您可以指定嵌套的最大级别/深度。
from time import time
def safe_serialize(obj , max_depth = 2):
max_level = max_depth
def _safe_serialize(obj , current_level = 0):
nonlocal max_level
# If it is a list
if isinstance(obj , list):
if current_level >= max_level:
return "[...]"
result = list()
for element in obj:
result.append(_safe_serialize(element , current_level + 1))
return result
# If it is a dict
elif isinstance(obj , dict):
if current_level >= max_level:
return "{...}"
result = dict()
for key , value in obj.items():
result[f"{_safe_serialize(key , current_level + 1)}"] = _safe_serialize(value , current_level + 1)
return result
# If it is an object of builtin class
elif hasattr(obj , "__dict__"):
if hasattr(obj , "__repr__"):
result = f"{obj.__repr__()}_{int(time())}"
else:
try:
result = f"{obj.__class__.__name__}_object_{int(time())}"
except:
result = f"object_{int(time())}"
return result
# If it is anything else
else:
return obj
return _safe_serialize(obj)
由于字典也可以有不可序列化的键，转储它们的类名或对象表示将导致所有键都具有相同的名称，这将抛出错误，因为所有键都需要有唯一的名称，这就是为什么当前时间Since epoch被int(time())附加到对象名称。
可以使用以下具有不同级别/深度的嵌套字典来测试该函数
d = {
"a" : {
"a1" : {
"a11" : {
"a111" : "some_value" ,
"a112" : "some_value" ,
} ,
"a12" : {
"a121" : "some_value" ,
"a122" : "some_value" ,
} ,
} ,
"a2" : {
"a21" : {
"a211" : "some_value" ,
"a212" : "some_value" ,
} ,
"a22" : {
"a221" : "some_value" ,
"a222" : "some_value" ,
} ,
} ,
} ,
"b" : {
"b1" : {
"b11" : {
"b111" : "some_value" ,
"b112" : "some_value" ,
} ,
"b12" : {
"b121" : "some_value" ,
"b122" : "some_value" ,
} ,
} ,
"b2" : {
"b21" : {
"b211" : "some_value" ,
"b212" : "some_value" ,
} ,
"b22" : {
"b221" : "some_value" ,
"b222" : "some_value" ,
} ,
} ,
} ,
"c" : subprocess.Popen("ls -l".split() , stdout = subprocess.PIPE , stderr = subprocess.PIPE) ,
}
执行以下命令将会得到-
print("LEVEL 3")
print(json.dumps(safe_serialize(d , 3) , indent = 4))
print("\n\n\nLEVEL 2")
print(json.dumps(safe_serialize(d , 2) , indent = 4))
print("\n\n\nLEVEL 1")
print(json.dumps(safe_serialize(d , 1) , indent = 4))
结果:
LEVEL 3
{
"a": {
"a1": {
"a11": "{...}",
"a12": "{...}"
},
"a2": {
"a21": "{...}",
"a22": "{...}"
}
},
"b": {
"b1": {
"b11": "{...}",
"b12": "{...}"
},
"b2": {
"b21": "{...}",
"b22": "{...}"
}
},
"c": "<Popen: returncode: None args: ['ls', '-l']>"
}
LEVEL 2
{
"a": {
"a1": "{...}",
"a2": "{...}"
},
"b": {
"b1": "{...}",
"b2": "{...}"
},
"c": "<Popen: returncode: None args: ['ls', '-l']>"
}
LEVEL 1
{
"a": "{...}",
"b": "{...}",
"c": "<Popen: returncode: None args: ['ls', '-l']>"
}
[注意]:仅在不关心内置类对象的序列化时使用此选项。
任何人都想在没有外部库的情况下使用基本转换，这只是如何使用以下方式覆盖自定义类的__iter__ & __str__函数。
class JSONCustomEncoder(json.JSONEncoder):
def default(self, obj):
return obj.__dict__
class Student:
def __init__(self, name: str, slug: str):
self.name = name
self.age = age
def __iter__(self):
yield from {
"name": self.name,
"age": self.age,
}.items()
def __str__(self):
return json.dumps(
self.__dict__, cls=JSONCustomEncoder, ensure_ascii=False
)
通过在dict()中进行包装来使用该对象，从而保留数据。
s = Student("aman", 24)
dict(s)
基于Quinten Cabo的回答:
def sterilize(obj):
"""Make an object more ameniable to dumping as json
"""
if type(obj) in (str, float, int, bool, type(None)):
return obj
elif isinstance(obj, dict):
return {k: sterilize(v) for k, v in obj.items()}
list_ret = []
dict_ret = {}
for a in dir(obj):
if a == '__iter__' and callable(obj.__iter__):
list_ret.extend([sterilize(v) for v in obj])
elif a == '__dict__':
dict_ret.update({k: sterilize(v) for k, v in obj.__dict__.items() if k not in ['__module__', '__dict__', '__weakref__', '__doc__']})
elif a not in ['__doc__', '__module__']:
aval = getattr(obj, a)
if type(aval) in (str, float, int, bool, type(None)):
dict_ret[a] = aval
elif a != '__class__' and a != '__objclass__' and isinstance(aval, type):
dict_ret[a] = sterilize(aval)
if len(list_ret) == 0:
if len(dict_ret) == 0:
return repr(obj)
return dict_ret
else:
if len(dict_ret) == 0:
return list_ret
return (list_ret, dict_ret)
区别在于
Works for any iterable instead of just list and tuple (it works for NumPy arrays, etc.) Works for dynamic types (ones that contain a __dict__). Includes native types float and None so they don't get converted to string. Classes that have __dict__ and members will mostly work (if the __dict__ and member names collide, you will only get one - likely the member) Classes that are lists and have members will look like a tuple of the list and a dictionary Python3 (that isinstance() call may be the only thing that needs changing)
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