下面的代码将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) 

叫有趣,

def all_products():
    all_products = Products.query.all()
    return to_array(all_products)

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

出于安全考虑，您不应该返回模型的所有字段。我更喜欢有选择性地选择他们。

Flask的json编码现在支持UUID, datetime和relationships(并为flask_sqlalchemy db添加了query和query_class。模型类)。编码器我更新如下:

app / 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，返回我希望编码的字段列表:

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']

我添加@jsonapi到我的视图，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"
}

]

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

也许你可以使用这样的类

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!

所有对象都有to_dict方法

虽然最初的问题可以追溯到很久以前，但这里的答案数量(以及我自己的经验)表明，这是一个不平凡的问题，有许多不同的方法，不同的复杂性和不同的权衡。

这就是为什么我构建了SQLAthanor库，它扩展了SQLAlchemy的声明性ORM，支持可配置的序列化/反序列化，您可能想看看。

该库支持:

Python 2.7, 3.4, 3.5, and 3.6. SQLAlchemy versions 0.9 and higher serialization/de-serialization to/from JSON, CSV, YAML, and Python dict serialization/de-serialization of columns/attributes, relationships, hybrid properties, and association proxies enabling and disabling of serialization for particular formats and columns/relationships/attributes (e.g. you want to support an inbound password value, but never include an outbound one) pre-serialization and post-deserialization value processing (for validation or type coercion) a pretty straightforward syntax that is both Pythonic and seamlessly consistent with SQLAlchemy's own approach

你可以在这里查看(我希望!)全面的文档:https://sqlathanor.readthedocs.io/en/latest

希望这能有所帮助!