Django可以很好地自动序列化从DB返回到JSON格式的ORM模型。
如何序列化SQLAlchemy查询结果为JSON格式?
我试过jsonpickle。编码,但它编码查询对象本身。
我尝试了json.dumps(items),但它返回
TypeError: <Product('3', 'some name', 'some desc')> is not JSON serializable
将SQLAlchemy ORM对象序列化为JSON /XML真的那么难吗?它没有任何默认序列化器吗?现在序列化ORM查询结果是非常常见的任务。
我所需要的只是返回SQLAlchemy查询结果的JSON或XML数据表示。
需要在javascript datagird中使用JSON/XML格式的SQLAlchemy对象查询结果(JQGrid http://www.trirand.com/blog/)
向任何模型添加一个_dict方法的动态方法
from sqlalchemy.inspection import inspect
def implement_as_dict(model):
if not hasattr(model,"as_dict"):
column_names=[]
imodel = inspect(model)
for c in imodel.columns:
column_names.append(c.key)
#define model.as_dict()
def as_dict(self):
d = {}
for c in column_names:
d[c] = getattr(self,c)
return d
setattr(model,"as_dict",as_dict)
#model definition
class User(Base):
__tablename__ = 'users'
id = Column(Integer, primary_key=True)
name = Column(String)
# adding as_dict definition to model
implement_as_dict(User)
然后你可以使用
user = session.query(User).filter_by(name='rick').first()
user.as_dict()
#sample output
{"id":1,"name":"rick"}
在Flask下,它工作并处理datatime字段,转换类型字段
“时间”:datetime。Datetime(2018, 3, 22, 15, 40)成
“时间”:“2018-03-22 15:40:00”:
obj = {c.name: str(getattr(self, c.name)) for c in self.__table__.columns}
# This to get the JSON body
return json.dumps(obj)
# Or this to get a response object
return jsonify(obj)
这是一个JSONEncoder版本,它保留了模型列的顺序,只保留递归定义的列和关系字段。它还格式化了大多数不可序列化的JSON类型:
import json
from datetime import datetime
from decimal import Decimal
import arrow
from sqlalchemy.ext.declarative import DeclarativeMeta
class SQLAlchemyJSONEncoder(json.JSONEncoder):
"""
SQLAlchemy ORM JSON Encoder
If you have a "backref" relationship defined in your SQLAlchemy model,
this encoder raises a ValueError to stop an infinite loop.
"""
def default(self, obj):
if isinstance(obj, datetime):
return arrow.get(obj).isoformat()
elif isinstance(obj, Decimal):
return float(obj)
elif isinstance(obj, set):
return sorted(obj)
elif isinstance(obj.__class__, DeclarativeMeta):
for attribute, relationship in obj.__mapper__.relationships.items():
if isinstance(relationship.__getattribute__("backref"), tuple):
raise ValueError(
f'{obj.__class__} object has a "backref" relationship '
"that would cause an infinite loop!"
)
dictionary = {}
column_names = [column.name for column in obj.__table__.columns]
for key in column_names:
value = obj.__getattribute__(key)
if isinstance(value, datetime):
value = arrow.get(value).isoformat()
elif isinstance(value, Decimal):
value = float(value)
elif isinstance(value, set):
value = sorted(value)
dictionary[key] = value
for key in [
attribute
for attribute in dir(obj)
if not attribute.startswith("_")
and attribute != "metadata"
and attribute not in column_names
]:
value = obj.__getattribute__(key)
dictionary[key] = value
return dictionary
return super().default(obj)
我已经成功地使用了这个包:https://github.com/n0nSmoker/SQLAlchemy-serializer
你可以在模型上这样做:
from sqlalchemy_serializer import SerializerMixin
class SomeModel(db.Model, SerializerMixin):
...
它添加了完全递归的to_dict:
item = SomeModel.query.filter(...).one()
result = item.to_dict()
它可以让你制定规则来避免无限递归:
result = item.to_dict(rules=('-somefield', '-some_relation.nested_one.another_nested_one'))
向任何模型添加一个_dict方法的动态方法
from sqlalchemy.inspection import inspect
def implement_as_dict(model):
if not hasattr(model,"as_dict"):
column_names=[]
imodel = inspect(model)
for c in imodel.columns:
column_names.append(c.key)
#define model.as_dict()
def as_dict(self):
d = {}
for c in column_names:
d[c] = getattr(self,c)
return d
setattr(model,"as_dict",as_dict)
#model definition
class User(Base):
__tablename__ = 'users'
id = Column(Integer, primary_key=True)
name = Column(String)
# adding as_dict definition to model
implement_as_dict(User)
然后你可以使用
user = session.query(User).filter_by(name='rick').first()
user.as_dict()
#sample output
{"id":1,"name":"rick"}