Django对从DB转换为JSON格式的ORM模型有一些很好的自动序列化。
如何将SQLAlchemy查询结果序列化为JSON格式？
我尝试了jsonpickle.encode，但它对查询对象本身进行了编码。
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真的很难吗？它没有默认的序列化器吗？现在序列化ORM查询结果是非常常见的任务。
我需要的只是返回SQLAlchemy查询结果的JSON或XML数据表示。
需要在javascript datagird（JQGrid http://www.trirand.com/blog/）
中使用JSON / XML格式的SQLAlchemy对象查询结果答案 0 :(得分：215)
您可以将对象输出为dict：
class User:
def as_dict(self):
return {c.name: getattr(self, c.name) for c in self.__table__.columns}
然后使用User.as_dict（）来序列化您的对象。
中所述答案 1 :(得分：109)
您可以使用以下内容：
from sqlalchemy.ext.declarative import DeclarativeMeta
class AlchemyEncoder(json.JSONEncoder):
def default(self, obj):
if isinstance(obj.__class__, DeclarativeMeta):
# an SQLAlchemy class
fields = {}
for field in [x for x in dir(obj) if not x.startswith('_') and x != 'metadata']:
data = obj.__getattribute__(field)
try:
json.dumps(data) # this will fail on non-encodable values, like other classes
fields[field] = data
except TypeError:
fields[field] = None
# a json-encodable dict
return fields
return json.JSONEncoder.default(self, obj)
然后使用：
转换为JSONc = YourAlchemyClass()
print json.dumps(c, cls=AlchemyEncoder)
它将忽略不可编码的字段（将它们设置为“无”）。
它不会自动扩展关系（因为这可能会导致自我引用，并永远循环）。
但是，如果你宁愿循环，你可以使用：
from sqlalchemy.ext.declarative import DeclarativeMeta
def new_alchemy_encoder():
_visited_objs = []
class AlchemyEncoder(json.JSONEncoder):
def default(self, obj):
if isinstance(obj.__class__, DeclarativeMeta):
# don't re-visit self
if obj in _visited_objs:
return None
_visited_objs.append(obj)
# an SQLAlchemy class
fields = {}
for field in [x for x in dir(obj) if not x.startswith('_') and x != 'metadata']:
fields[field] = obj.__getattribute__(field)
# a json-encodable dict
return fields
return json.JSONEncoder.default(self, obj)
return AlchemyEncoder
然后使用：
编码对象print json.dumps(e, cls=new_alchemy_encoder(), check_circular=False)
这会编码所有孩子，他们所有的孩子以及他们所有的孩子......基本上可能会对整个数据库进行编码。当它达到之前编码的内容时，它会将其编码为“无”。
另一种可能更好的选择是能够指定要扩展的字段：
def new_alchemy_encoder(revisit_self = False, fields_to_expand = []):
_visited_objs = []
class AlchemyEncoder(json.JSONEncoder):
def default(self, obj):
if isinstance(obj.__class__, DeclarativeMeta):
# don't re-visit self
if revisit_self:
if obj in _visited_objs:
return None
_visited_objs.append(obj)
# go through each field in this SQLalchemy class
fields = {}
for field in [x for x in dir(obj) if not x.startswith('_') and x != 'metadata']:
val = obj.__getattribute__(field)
# is this field another SQLalchemy object, or a list of SQLalchemy objects?
if isinstance(val.__class__, DeclarativeMeta) or (isinstance(val, list) and len(val) > 0 and isinstance(val[0].__class__, DeclarativeMeta)):
# unless we're expanding this field, stop here
if field not in fields_to_expand:
# not expanding this field: set it to None and continue
fields[field] = None
continue
fields[field] = val
# a json-encodable dict
return fields
return json.JSONEncoder.default(self, obj)
return AlchemyEncoder
您现在可以通过以下方式调用它：
print json.dumps(e, cls=new_alchemy_encoder(False, ['parents']), check_circular=False)
仅扩展名为“parents”的SQLAlchemy字段，例如。
答案 2 :(得分：45)
您可以将RowProxy转换为这样的字典：
d = dict(row.items())
然后将其序列化为JSON（您必须为datetime值之类的内容指定编码器）
如果您只想要一条记录（而不是相关记录的完整层次结构），那并不难。
json.dumps([(dict(row.items())) for row in rs])
答案 3 :(得分：38)
我建议使用最近的浮出水面库marshmallow。它允许您创建序列化程序来表示模型实例，并支持关系和嵌套对象。
看看他们SQLAlchemy Example。
答案 4 :(得分：14)
Flask-JsonTools包具有适用于您的模型的JsonSerializableBase基类的实现。
用法：
from sqlalchemy.ext.declarative import declarative_base
from flask.ext.jsontools import JsonSerializableBase
Base = declarative_base(cls=(JsonSerializableBase,))
class User(Base):
#...
现在User模型可以神奇地序列化。
如果您的框架不是Flask，那么您可以grab the code
答案 5 :(得分：14)
from dataclasses import dataclass
from datetime import datetime
from flask import Flask, jsonify
from flask_sqlalchemy import SQLAlchemy
app = Flask(__name__)
db = SQLAlchemy(app)
@dataclass
class User(db.Model):
id: int
email: str
id = db.Column(db.Integer, primary_key=True, auto_increment=True)
email = db.Column(db.String(200), unique=True)
@app.route('/users/')
def users():
users = User.query.all()
return jsonify(users)
if __name__ == "__main__":
users = User(email="user1@gmail.com"), User(email="user2@gmail.com")
db.create_all()
db.session.add_all(users)
db.session.commit()
app.run()
/users/路由现在将返回用户列表。
[
{"email": "user1@gmail.com", "id": 1},
{"email": "user2@gmail.com", "id": 2}
]
@dataclass
class Account(db.Model):
id: int
users: User
id = db.Column(db.Integer)
users = db.relationship(User) # User model would need a db.ForeignKey field
jsonify(account)的响应就是这样。
{
"id":1,
"users":[
{
"email":"user1@gmail.com",
"id":1
},
{
"email":"user2@gmail.com",
"id":2
}
]
}
from flask.json import JSONEncoder
class CustomJSONEncoder(JSONEncoder):
"Add support for serializing timedeltas"
def default(o):
if type(o) == datetime.timedelta:
return str(o)
elif type(o) == datetime.datetime:
return o.isoformat()
else:
return super().default(o)
app.json_encoder = CustomJSONEncoder
答案 6 :(得分：12)
出于安全考虑，您永远不应该返回所有模型的字段。我更愿意有选择地选择它们。
Flask的json编码现在支持UUID，日期时间和关系（并为flask_sqlalchemy query类添加了query_class和db.Model。我按如下方式更新了编码器：
应用程序/ json_encoder.py
from sqlalchemy.ext.declarative import DeclarativeMeta
from flask import json
class AlchemyEncoder(json.JSONEncoder):
def default(self, o):
if isinstance(o.__class__, DeclarativeMeta):
data = {}
fields = o.__json__() if hasattr(o, '__json__') else dir(o)
for field in [f for f in fields if not f.startswith('_') and f not in ['metadata', 'query', 'query_class']]:
value = o.__getattribute__(field)
try:
json.dumps(value)
data[field] = value
except TypeError:
data[field] = None
return data
return json.JSONEncoder.default(self, o)
app/__init__.py
# json encoding
from app.json_encoder import AlchemyEncoder
app.json_encoder = AlchemyEncoder
有了这个，我可以选择添加一个__json__属性，返回我想编码的字段列表：
app/models.py
class Queue(db.Model):
id = db.Column(db.Integer, primary_key=True)
song_id = db.Column(db.Integer, db.ForeignKey('song.id'), unique=True, nullable=False)
song = db.relationship('Song', lazy='joined')
type = db.Column(db.String(20), server_default=u'audio/mpeg')
src = db.Column(db.String(255), nullable=False)
created_at = db.Column(db.DateTime, server_default=db.func.now())
updated_at = db.Column(db.DateTime, server_default=db.func.now(), onupdate=db.func.now())
def __init__(self, song):
self.song = song
self.src = song.full_path
def __json__(self):
return ['song', 'src', 'type', 'created_at']
我将@jsonapi添加到我的视图中，返回结果列表，然后我的输出如下：
[
{
"created_at": "Thu, 23 Jul 2015 11:36:53 GMT",
"song":
{
"full_path": "/static/music/Audioslave/Audioslave [2002]/1 Cochise.mp3",
"id": 2,
"path_name": "Audioslave/Audioslave [2002]/1 Cochise.mp3"
},
"src": "/static/music/Audioslave/Audioslave [2002]/1 Cochise.mp3",
"type": "audio/mpeg"
}
]
答案 7 :(得分：10)
您可以使用SqlAlchemy的内省：
import { Router, ActivatedRoute, NavigationEnd } from "@angular/router";
...
constructor(
private _router: Router ,
private _activatedRoute: ActivatedRoute
) {}
ngOnInit() {
this._router.events
.filter((event) => event instanceof NavigationEnd)
.map(() => this._activatedRoute)
.map((route) => {
while (route.firstChild) route = route.firstChild;
return route;
})
.filter((route) => route.outlet === 'primary')
.mergeMap((route) => route.data)
.subscribe((event) => this.pageTitle = event['title']);
}
从这里的答案中获得灵感： Convert sqlalchemy row object to python dict
答案 8 :(得分：3)
不是那么直截了当。我写了一些代码来做到这一点。我还在努力，它使用MochiKit框架。它基本上使用代理和注册的JSON转换器在Python和Javascript之间转换复合对象。
数据库对象的浏览器端是db.js 它需要proxy.js中的基本Python代理源。
在Python端有基础proxy module。 最后是webserver.py中的SqlAlchemy对象编码器。 它还取决于models.py文件中的元数据提取器。
答案 9 :(得分：2)
自定义序列化和反序列化。
“from_json”（类方法）基于json数据构建Model对象。
“反序列化”只能在实例上调用，并将所有数据从json合并到Model实例中。
“序列化” - 递归序列化
需要__ write_only __ 属性来定义只写属性（例如“password_hash”）。
class Serializable(object):
__exclude__ = ('id',)
__include__ = ()
__write_only__ = ()
@classmethod
def from_json(cls, json, selfObj=None):
if selfObj is None:
self = cls()
else:
self = selfObj
exclude = (cls.__exclude__ or ()) + Serializable.__exclude__
include = cls.__include__ or ()
if json:
for prop, value in json.iteritems():
# ignore all non user data, e.g. only
if (not (prop in exclude) | (prop in include)) and isinstance(
getattr(cls, prop, None), QueryableAttribute):
setattr(self, prop, value)
return self
def deserialize(self, json):
if not json:
return None
return self.__class__.from_json(json, selfObj=self)
@classmethod
def serialize_list(cls, object_list=[]):
output = []
for li in object_list:
if isinstance(li, Serializable):
output.append(li.serialize())
else:
output.append(li)
return output
def serialize(self, **kwargs):
# init write only props
if len(getattr(self.__class__, '__write_only__', ())) == 0:
self.__class__.__write_only__ = ()
dictionary = {}
expand = kwargs.get('expand', ()) or ()
prop = 'props'
if expand:
# expand all the fields
for key in expand:
getattr(self, key)
iterable = self.__dict__.items()
is_custom_property_set = False
# include only properties passed as parameter
if (prop in kwargs) and (kwargs.get(prop, None) is not None):
is_custom_property_set = True
iterable = kwargs.get(prop, None)
# loop trough all accessible properties
for key in iterable:
accessor = key
if isinstance(key, tuple):
accessor = key[0]
if not (accessor in self.__class__.__write_only__) and not accessor.startswith('_'):
# force select from db to be able get relationships
if is_custom_property_set:
getattr(self, accessor, None)
if isinstance(self.__dict__.get(accessor), list):
dictionary[accessor] = self.__class__.serialize_list(object_list=self.__dict__.get(accessor))
# check if those properties are read only
elif isinstance(self.__dict__.get(accessor), Serializable):
dictionary[accessor] = self.__dict__.get(accessor).serialize()
else:
dictionary[accessor] = self.__dict__.get(accessor)
return dictionary
答案 10 :(得分：2)
这是一个解决方案，可让您根据自己的意愿选择要包含在输出中的关系。 注意：这是一个完整的重写，将dict / str作为arg而不是列表。修复了一些东西..
def deep_dict(self, relations={}):
"""Output a dict of an SA object recursing as deep as you want.
Takes one argument, relations which is a dictionary of relations we'd
like to pull out. The relations dict items can be a single relation
name or deeper relation names connected by sub dicts
Example:
Say we have a Person object with a family relationship
person.deep_dict(relations={'family':None})
Say the family object has homes as a relation then we can do
person.deep_dict(relations={'family':{'homes':None}})
OR
person.deep_dict(relations={'family':'homes'})
Say homes has a relation like rooms you can do
person.deep_dict(relations={'family':{'homes':'rooms'}})
and so on...
"""
mydict = dict((c, str(a)) for c, a in
self.__dict__.items() if c != '_sa_instance_state')
if not relations:
# just return ourselves
return mydict
# otherwise we need to go deeper
if not isinstance(relations, dict) and not isinstance(relations, str):
raise Exception("relations should be a dict, it is of type {}".format(type(relations)))
# got here so check and handle if we were passed a dict
if isinstance(relations, dict):
# we were passed deeper info
for left, right in relations.items():
myrel = getattr(self, left)
if isinstance(myrel, list):
mydict[left] = [rel.deep_dict(relations=right) for rel in myrel]
else:
mydict[left] = myrel.deep_dict(relations=right)
# if we get here check and handle if we were passed a string
elif isinstance(relations, str):
# passed a single item
myrel = getattr(self, relations)
left = relations
if isinstance(myrel, list):
mydict[left] = [rel.deep_dict(relations=None)
for rel in myrel]
else:
mydict[left] = myrel.deep_dict(relations=None)
return mydict
所以对于一个使用人/家庭/家庭/房间的例子......把它变成json所有你需要的是
json.dumps(person.deep_dict(relations={'family':{'homes':'rooms'}}))
答案 11 :(得分：2)
step1:
class CNAME:
...
def as_dict(self):
return {item.name: getattr(self, item.name) for item in self.__table__.columns}
step2:
list = []
for data in session.query(CNAME).all():
list.append(data.as_dict())
step3:
return jsonify(list)
答案 12 :(得分：2)
虽然最初的问题可以追溯到一段时间，但这里的答案（以及我的经验）表明，这是一个不平凡的问题，它具有许多不同的方法，具有不同的复杂性，需要权衡取舍。
这就是为什么我构建了SQLAthanor库的原因，该库扩展了SQLAlchemy的声明性ORM，并提供了您可能要看的可配置序列化/反序列化支持。
该库支持：
dict的串行化/反串行化password值，但不要包含 outbound 一）您可以在这里查看（我希望！）全面的文档：https://sqlathanor.readthedocs.io/en/latest
希望这会有所帮助！
答案 13 :(得分：1)
通过以下方式安装simplejson
pip install simplejson并创建一个类
class Serialise(object):
def _asdict(self):
"""
Serialization logic for converting entities using flask's jsonify
:return: An ordered dictionary
:rtype: :class:`collections.OrderedDict`
"""
result = OrderedDict()
# Get the columns
for key in self.__mapper__.c.keys():
if isinstance(getattr(self, key), datetime):
result["x"] = getattr(self, key).timestamp() * 1000
result["timestamp"] = result["x"]
else:
result[key] = getattr(self, key)
return result
并将该类继承到每个orm类，以便将此_asdict函数注册到每个ORM类和繁荣时期。
并在任何地方使用jsonify
答案 14 :(得分：1)
当使用sqlalchemy连接到数据库时，这是一个高度可配置的简单解决方案。使用大熊猫。
import pandas as pd
import sqlalchemy
#sqlalchemy engine configuration
engine = sqlalchemy.create_engine....
def my_function():
#read in from sql directly into a pandas dataframe
#check the pandas documentation for additional config options
sql_DF = pd.read_sql_table("table_name", con=engine)
# "orient" is optional here but allows you to specify the json formatting you require
sql_json = sql_DF.to_json(orient="index")
return sql_json
答案 15 :(得分：1)
AlchemyEncoder很棒，但有时会失败，并使用十进制值。这是解决小数点问题的改进编码器-
class AlchemyEncoder(json.JSONEncoder):
# To serialize SQLalchemy objects
def default(self, obj):
if isinstance(obj.__class__, DeclarativeMeta):
model_fields = {}
for field in [x for x in dir(obj) if not x.startswith('_') and x != 'metadata']:
data = obj.__getattribute__(field)
print data
try:
json.dumps(data) # this will fail on non-encodable values, like other classes
model_fields[field] = data
except TypeError:
model_fields[field] = None
return model_fields
if isinstance(obj, Decimal):
return float(obj)
return json.JSONEncoder.default(self, obj)
答案 16 :(得分：1)
以下代码会将sqlalchemy结果序列化为json。
import json
from collections import OrderedDict
def asdict(self):
result = OrderedDict()
for key in self.__mapper__.c.keys():
if getattr(self, key) is not None:
result[key] = str(getattr(self, key))
else:
result[key] = getattr(self, key)
return result
def to_array(all_vendors):
v = [ ven.asdict() for ven in all_vendors ]
return json.dumps(v)
打电话，
def all_products():
all_products = Products.query.all()
return to_array(all_products)
答案 17 :(得分：1)
（对 Sasha B's 的微小调整非常出色的答案）
这专门将日期时间对象转换为字符串，在原始答案中将转换为 None：
# Standard library imports
from datetime import datetime
import json
# 3rd party imports
from sqlalchemy.ext.declarative import DeclarativeMeta
class JsonEncoder(json.JSONEncoder):
def default(self, obj):
if isinstance(obj.__class__, DeclarativeMeta):
dict = {}
# Remove invalid fields and just get the column attributes
columns = [x for x in dir(obj) if not x.startswith("_") and x != "metadata"]
for column in columns:
value = obj.__getattribute__(column)
try:
json.dumps(value)
dict[column] = value
except TypeError:
if isinstance(value, datetime):
dict[column] = value.__str__()
else:
dict[column] = None
return dict
return json.JSONEncoder.default(self, obj)
答案 18 :(得分：1)
def alc2json(row):
return dict([(col, str(getattr(row,col))) for col in row.__table__.columns.keys()])
我以为我会用这个打高尔夫球。
仅供参考：我使用的是automap_base，因为根据业务需求我们有一个单独设计的架构。我今天刚开始使用SQLAlchemy，但是文档声明automap_base是declarative_base的扩展，这似乎是SQLAlchemy ORM中的典型范例，所以我相信这应该有效。
每个Tjorriemorrie的解决方案都没有使用以下外键，但它只是将列与值匹配，并通过str（）处理Python类型 - 列值。我们的值包括Python datetime.time和decimal.Decimal类类型结果，因此它可以完成工作。
希望这可以帮助任何路人！
答案 19 :(得分：0)
即使是老文章，也许我没有回答上面的问题，但是我想谈谈我的序列化，至少对我有用。
我使用FastAPI，SqlAlchemy和MySQL，但不使用orm模型；
# from sqlalchemy import create_engine
# from sqlalchemy.orm import sessionmaker
# engine = create_engine(config.SQLALCHEMY_DATABASE_URL, pool_pre_ping=True)
# SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
序列化代码
import decimal
import datetime
def alchemy_encoder(obj):
"""JSON encoder function for SQLAlchemy special classes."""
if isinstance(obj, datetime.date):
return obj.strftime("%Y-%m-%d %H:%M:%S")
elif isinstance(obj, decimal.Decimal):
return float(obj)
import json
from sqlalchemy import text
# db is SessionLocal() object
app_sql = 'SELECT * FROM app_info ORDER BY app_id LIMIT :page,:page_size'
# The next two are the parameters passed in
page = 1
page_size = 10
# execute sql and return a <class 'sqlalchemy.engine.result.ResultProxy'> object
app_list = db.execute(text(app_sql), {'page': page, 'page_size': page_size})
# serialize
res = json.loads(json.dumps([dict(r) for r in app_list], default=alchemy_encoder))
如果它不起作用，请忽略我的回答。我在这里参考
https://codeandlife.com/2014/12/07/sqlalchemy-results-to-json-the-easy-way/
答案 20 :(得分：0)
这是一个 JSONEncoder 版本，它保留模型列顺序并且只保留递归定义的列和关系字段。它还格式化大多数 JSON 不可序列化类型：
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)
答案 21 :(得分：0)
使用一些原始sql和未定义的对象时，使用cursor.description似乎可以得到我想要的东西：
with connection.cursor() as cur:
print(query)
cur.execute(query)
for item in cur.fetchall():
row = {column.name: item[i] for i, column in enumerate(cur.description)}
print(row)
答案 22 :(得分：0)
也许您可以使用这样的类
from sqlalchemy.ext.declarative import declared_attr
from sqlalchemy import Table
class Custom:
"""Some custom logic here!"""
__table__: Table # def for mypy
@declared_attr
def __tablename__(cls): # pylint: disable=no-self-argument
return cls.__name__ # pylint: disable= no-member
def to_dict(self) -> Dict[str, Any]:
"""Serializes only column data."""
return {c.name: getattr(self, c.name) for c in self.__table__.columns}
Base = declarative_base(cls=Custom)
class MyOwnTable(Base):
#COLUMNS!
所有对象都具有to_dict方法
答案 23 :(得分：0)
带有utf-8的内置串行器扼流圈无法解码某些输入的无效起始字节。相反，我去了：
def row_to_dict(row):
temp = row.__dict__
temp.pop('_sa_instance_state', None)
return temp
def rows_to_list(rows):
ret_rows = []
for row in rows:
ret_rows.append(row_to_dict(row))
return ret_rows
@website_blueprint.route('/api/v1/some/endpoint', methods=['GET'])
def some_api():
'''
/some_endpoint
'''
rows = rows_to_list(SomeModel.query.all())
response = app.response_class(
response=jsonplus.dumps(rows),
status=200,
mimetype='application/json'
)
return response
答案 24 :(得分：0)
在Flask下，它可以处理和处理数据时间字段，转换类型为
的字段
'time': datetime.datetime(2018, 3, 22, 15, 40)进入
"time": "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)
答案 25 :(得分：0)
使用SQLAlchemy中的built-in serializer：
from sqlalchemy.ext.serializer import loads, dumps
obj = MyAlchemyObject()
# serialize object
serialized_obj = dumps(obj)
# deserialize object
obj = loads(serialized_obj)
如果您要在会话之间传输对象，请记住使用session.expunge(obj)从当前会话中分离对象。
要再次附加，请执行session.add(obj)。
答案 26 :(得分：0)
我知道这是一篇相当老的帖子。我接受了@SashaB给出的解决方案并根据我的需要进行了修改。
我添加了以下内容：
我的代码如下：
def alchemy_json_encoder(revisit_self = False, fields_to_expand = [], fields_to_ignore = [], fields_to_replace = {}):
"""
Serialize SQLAlchemy result into JSon
:param revisit_self: True / False
:param fields_to_expand: Fields which are to be expanded for including their children and all
:param fields_to_ignore: Fields to be ignored while encoding
:param fields_to_replace: Field keys to be replaced by values assigned in dictionary
:return: Json serialized SQLAlchemy object
"""
_visited_objs = []
class AlchemyEncoder(json.JSONEncoder):
def default(self, obj):
if isinstance(obj.__class__, DeclarativeMeta):
# don't re-visit self
if revisit_self:
if obj in _visited_objs:
return None
_visited_objs.append(obj)
# go through each field in this SQLalchemy class
fields = {}
for field in [x for x in dir(obj) if not x.startswith('_') and x != 'metadata' and x not in fields_to_ignore]:
val = obj.__getattribute__(field)
# is this field method defination, or an SQLalchemy object
if not hasattr(val, "__call__") and not isinstance(val, BaseQuery):
field_name = fields_to_replace[field] if field in fields_to_replace else field
# is this field another SQLalchemy object, or a list of SQLalchemy objects?
if isinstance(val.__class__, DeclarativeMeta) or \
(isinstance(val, list) and len(val) > 0 and isinstance(val[0].__class__, DeclarativeMeta)):
# unless we're expanding this field, stop here
if field not in fields_to_expand:
# not expanding this field: set it to None and continue
fields[field_name] = None
continue
fields[field_name] = val
# a json-encodable dict
return fields
return json.JSONEncoder.default(self, obj)
return AlchemyEncoder
希望它有所帮助！
答案 27 :(得分：-2)
我的利用（太多？）词典：
def serialize(_query):
#d = dictionary written to per row
#D = dictionary d is written to each time, then reset
#Master = dictionary of dictionaries; the id Key (int, unique from database)
from D is used as the Key for the dictionary D entry in Master
Master = {}
D = {}
x = 0
for u in _query:
d = u.__dict__
D = {}
for n in d.keys():
if n != '_sa_instance_state':
D[n] = d[n]
x = d['id']
Master[x] = D
return Master
使用flask（包括jsonify）和flask_sqlalchemy运行以将输出打印为JSON。
使用jsonify（serialize（））调用该函数。
适用于我迄今为止尝试的所有SQLAlchemy查询（运行SQLite3）