你可以像这样使用SqlAlchemy的自省:

mysql = SQLAlchemy()
from sqlalchemy import inspect

class Contacts(mysql.Model):  
    __tablename__ = 'CONTACTS'
    id = mysql.Column(mysql.Integer, primary_key=True)
    first_name = mysql.Column(mysql.String(128), nullable=False)
    last_name = mysql.Column(mysql.String(128), nullable=False)
    phone = mysql.Column(mysql.String(128), nullable=False)
    email = mysql.Column(mysql.String(128), nullable=False)
    street = mysql.Column(mysql.String(128), nullable=False)
    zip_code = mysql.Column(mysql.String(128), nullable=False)
    city = mysql.Column(mysql.String(128), nullable=False)
    def toDict(self):
        return { c.key: getattr(self, c.key) for c in inspect(self).mapper.column_attrs }

@app.route('/contacts',methods=['GET'])
def getContacts():
    contacts = Contacts.query.all()
    contactsArr = []
    for contact in contacts:
        contactsArr.append(contact.toDict()) 
    return jsonify(contactsArr)

@app.route('/contacts/<int:id>',methods=['GET'])
def getContact(id):
    contact = Contacts.query.get(id)
    return jsonify(contact.toDict())

从下面的答案中得到启发: 将sqlalchemy行对象转换为python dict

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。

Flask-JsonTools包为您的模型提供了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了。

如果你的框架不是Flask，你可以抓取代码

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

如果你正在使用Flask并且只想快速查询:

def get_cats():
    sql = text("select * from cat")
    sql_params = {}
    result = db.session.execute(sql, sql_params)
    row_list = result.fetchall()
    data = [dict(r) for r in row_list]

    response = jsonify({
        'data': [{
            'categorias': data
        }]
    })
    
    return response

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)