Python 3.7+和Flask 1.1+可以使用内置的数据类包

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/路由现在将返回一个用户列表。

[
  {"email": "user1@gmail.com", "id": 1},
  {"email": "user2@gmail.com", "id": 2}
]

自动序列化相关模型

@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)的响应是这样的。

{  
   "id":1,
   "users":[  
      {  
         "email":"user1@gmail.com",
         "id":1
      },
      {  
         "email":"user2@gmail.com",
         "id":2
      }
   ]
}

覆盖默认的JSON编码器

from flask.json import JSONEncoder


class CustomJSONEncoder(JSONEncoder):
  "Add support for serializing timedeltas"

  def default(o):
    if type(o) == datetime.timedelta:
      return str(o)
    if type(o) == datetime.datetime:
      return o.isoformat()
    return super().default(o)

app.json_encoder = CustomJSONEncoder      

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)

https://flask-restplus.readthedocs.io/en/stable/marshalling.html

from flask_restplus import fields, Namespace, marshal
api = Namespace("Student data")
db_data = Student_details.query.all()
data_marshal_obj = api.model(" Data", {
    "id": fields.String(),
    "number": fields.Integer(),
    "house_name": fields.String(),
 })
data_in_json_serialize =  marshal(db_data, data_marshal_obj)}
print(type(data_in_json_serialize )) #  <class 'dict'>

定制序列化编组在烧瓶restpluse

这并不是那么简单。我写了一些代码来做这件事。我还在开发中，它使用了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代理源代码。

在Python方面，有基本代理模块。 最后是webserver.py中的SqlAlchemy对象编码器。 它还依赖于models.py文件中的元数据提取器。

当使用sqlalchemy连接到db I时，这是一个高度可配置的简单解决方案。使用熊猫。

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

AlchemyEncoder是很棒的，但有时会失败的十进制值。这是一个改进的编码器，解决十进制问题-

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)