如何使用flask和jsonify在json响应中添加嵌套的数组和对象

如何解决如何使用flask和jsonify在json响应中添加嵌套的数组和对象

我目前正在遵循此example来启动并运行API（下面的代码）

@JsonIgnore
@JsonProperty(value = "user_password")
public String getUserPassword() {
    return userPassword;
}
        

最后，我想得到一个嵌套数组from flask import Flask,request,jsonify from flask_restful import Resource,Api from sqlalchemy import create_engine from json import dumps import mysql.connector db_connect = create_engine('mysql+pymysql://root:pass@localhost/news') app = Flask(__name__) api = Api(app) class Events(Resource): def get(self): conn = db_connect.connect() # connect to database query = conn.execute("select id,title,description,date,scheduled,favourite,count_audio,count_video,count_articles from events;") result = [dict(zip(tuple (query.keys()),i)) for i in query.cursor] return jsonify(result) api.add_resource(Events,'/events') # Route_1 if __name__ == '__main__': app.run(port='5002') 和一个嵌套对象tags，如下所示

location

像这样甚至有可能吗？我是否需要重新考虑API以使端点覆盖每个嵌套对象？

[{
    "description": "TEST DESCRIPTION","id": 1,"title": "TEST TITLE","date": "2020-09-02","scheduled":"true","favourite":"true","tags": ["celebration","national holiday"],"location": {
        "state": {
            "name": "new zealand","affiliation": ["United Nations"]
        },"province": "","urbanisation": "Wellington"
        }
},{
    "description": "LONG DESCRIPTION","id": 2,"title": "SECOND ENTRY","date": "2020-09-03","scheduled":"false","favourite":"false","tags": ["election","location": {
        "state": {
            "name": "Brazil","affiliation": [""]
        },"urbanisation": ""
        }
}]

或者，我是否像this answer一样嵌套字典。

解决方法

是的，它可能并且完全有效。但是我不会直接查询数据库。我会使用SQLAlchemy之类的ORM，因为烧瓶使用可以使用flask-sqlalchemy扩展名。可以使用flask-marshmallow

实现序列化

使用SQLAlchemy创建模型：

from flask import Flask
from flask_sqlalchemy import SQLAlchemy

app = Flask(__name__)
app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:////tmp/test.db'
db = SQLAlchemy(app)

class EventModel(db.Model):
    __tablename__ = "event"

    id = db.Column(db.Integer,primary_key=True)
    title = db.Column(db.String,nullable=True)


class LocationModel(db.Model):
    __tablename__ = "location"

    id = db.Column(db.Integer,primary_key=True)
    province = db.Column(db.String,nullable=True)

    event_id = db.Column(db.Integer,db.ForeignKey("event.id",ondelete="CASCADE"),nullable=False)

    event = db.relationship("EventModel",backref=db.backref("locations",lazy=True))

然后，您需要序列化程序类（使用flask-marshmallow）来处理序列化：

from marshmallow_sqlalchemy import SQLAlchemyAutoSchema,fields
from marshmallow_sqlalchemy import auto_field
class LocationSchema(SQLAlchemyAutoSchema):
    class Meta:
        model = LocationModel
        load_instance = True
        include_fk = False

    id = auto_field(load_only=True)

class EventSchema(SQLAlchemyAutoSchema):
    class Meta:
        model = EventModel
        load_instance = True
        include_fk = False

    id = auto_field(load_only=True)
    locations = fields.Nested(LocationSchema,many=True)

最后，您可以如下序列化为json：

db.drop_all()
db.create_all()
event = EventModel(title="Summer Show")
db.session.add(event)
db.session.commit()
location1 = LocationModel(province="Upper Austria",event_id=event.id)
db.session.add(location1)
location2 = LocationModel(province="Tirol",event_id=event.id)
db.session.add(location2)
db.session.commit()


schema = EventSchema()
result = db.session.query(EventModel).all()
print(schema.dump(result,many=True))

可以找到完整的教程here。