You could just output your object as a dictionary:

class User:
    def as_dict(self):
        return {c.name: getattr(self, c.name) for c in self.__table__.columns}

And then you use User.as_dict() to serialize your object.

As explained in How to convert SQLAlchemy row object to a Python dict?

Python 3.7+ and Flask 1.1+ can use the built-in dataclasses package

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="[email protected]"), User(email="[email protected]")
  db.create_all()
  db.session.add_all(users)
  db.session.commit()
  app.run()

The /users/ route will now return a list of users.

[
  {"email": "[email protected]", "id": 1},
  {"email": "[email protected]", "id": 2}
]

Auto-serialize related models

@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

The response from jsonify(account) would be this.

{  
   "id":1,
   "users":[  
      {  
         "email":"[email protected]",
         "id":1
      },
      {  
         "email":"[email protected]",
         "id":2
      }
   ]
}

Overwrite the default JSON Encoder

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      

You can convert a RowProxy to a dict like this:

 d = dict(row.items())

Then serialize that to JSON ( you will have to specify an encoder for things like datetime values ) It's not that hard if you just want one record ( and not a full hierarchy of related records ).

json.dumps([(dict(row.items())) for row in rs])

I recommend using marshmallow. It allows you to create serializers to represent your model instances with support to relations and nested objects.

Here is a truncated example from their docs. Take the ORM model, Author:

class Author(db.Model):
    id = db.Column(db.Integer, primary_key=True)
    first = db.Column(db.String(80))
    last = db.Column(db.String(80))

A marshmallow schema for that class is constructed like this:

class AuthorSchema(Schema):
    id = fields.Int(dump_only=True)
    first = fields.Str()
    last = fields.Str()
    formatted_name = fields.Method("format_name", dump_only=True)

    def format_name(self, author):
        return "{}, {}".format(author.last, author.first)

...and used like this:

author_schema = AuthorSchema()
author_schema.dump(Author.query.first())

...would produce an output like this:

{
        "first": "Tim",
        "formatted_name": "Peters, Tim",
        "id": 1,
        "last": "Peters"
}

Have a look at their full Flask-SQLAlchemy Example.

A library called marshmallow-sqlalchemy specifically integrates SQLAlchemy and marshmallow. In that library, the schema for the Author model described above looks like this:

class AuthorSchema(ModelSchema):
    class Meta:
        model = Author

The integration allows the field types to be inferred from the SQLAlchemy Column types.

marshmallow-sqlalchemy here.

You can use introspection of SqlAlchemy as this :

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())

Get inspired from an answer here : Convert sqlalchemy row object to python dict

For security reasons you should never return all the model's fields. I prefer to selectively choose them.

Flask's json encoding now supports UUID, datetime and relationships (and added query and query_class for flask_sqlalchemy db.Model class). I've updated the encoder as follows:

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

With this I can optionally add a __json__ property that returns the list of fields I wish to encode:

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']

I add @jsonapi to my view, return the resultlist and then my output is as follows:

[

{

    "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"
}

]

Here's one way to make your SqlAlchemy objects serializable: implement a custom JSONEncoder and add it to the base class:

Usage:

from sqlalchemy.ext.declarative import declarative_base
from flask.ext.jsontools import JsonSerializableBase

Base = declarative_base(cls=(DynamicJSONEncoder,))

class User(Base):
    #...

Now the User model is magically serializable.

Here's one way to implement a custom JSONEncoder: it will allow you to customize how an instance is represented in JSON by implementing the __json__() method:

from flask.json import JSONEncoder

class DynamicJSONEncoder(JSONEncoder):
    """ JSON encoder for custom classes:

        Uses __json__() method if available to prepare the object.
        Especially useful for SQLAlchemy models
    """

    def default(self, o):
        # Custom JSON-encodeable objects
        if hasattr(o, '__json__'):
            return o.__json__()

        # Default
        return super().default(o)

A more detailed explanation. In your model, add:

def as_dict(self):
       return {c.name: str(getattr(self, c.name)) for c in self.__table__.columns}

The str() is for python 3 so if using python 2 use unicode(). It should help deserialize dates. You can remove it if not dealing with those.

You can now query the database like this

some_result = User.query.filter_by(id=current_user.id).first().as_dict()

First() is needed to avoid weird errors. as_dict() will now deserialize the result. After deserialization, it is ready to be turned to json

jsonify(some_result)

While the original question goes back awhile, the number of answers here (and my own experiences) suggest it's a non-trivial question with a lot of different approaches of varying complexity with different trade-offs.

That's why I built the SQLAthanor library that extends SQLAlchemy's declarative ORM with configurable serialization/de-serialization support that you might want to take a look at.

The library supports:

• 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

You can check out the (I hope!) comprehensive docs here: https://sqlathanor.readthedocs.io/en/latest

Hope this helps!

Custom serialization and deserialization.

"from_json" (class method) builds a Model object based on json data.

"deserialize" could be called only on instance, and merge all data from json into Model instance.

"serialize" - recursive serialization

__write_only__ property is needed to define write only properties ("password_hash" for example).

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

Use the built-in serializer in SQLAlchemy:

from sqlalchemy.ext.serializer import loads, dumps
obj = MyAlchemyObject()
# serialize object
serialized_obj = dumps(obj)

# deserialize object
obj = loads(serialized_obj)

If you're transferring the object between sessions, remember to detach the object from the current session using session.expunge(obj). To attach it again, just do session.add(obj).

Here is a solution that lets you select the relations you want to include in your output as deep as you would like to go. NOTE: This is a complete re-write taking a dict/str as an arg rather than a list. fixes some stuff..

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

so for an example using person/family/homes/rooms... turning it into json all you need is

json.dumps(person.deep_dict(relations={'family':{'homes':'rooms'}}))

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)

Even though it's a old post, Maybe I didn't answer the question above, but I want to talk about my serialization, at least it works for me.

I use FastAPI,SqlAlchemy and MySQL, but I don't use orm model;

# 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)

Serialization code

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))

If it doesn't work, please ignore my answer. I refer to it here

https://codeandlife.com/2014/12/07/sqlalchemy-results-to-json-the-easy-way/

install simplejson by pip install simplejson and the create a class

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

and inherit this class to every orm classes so that this _asdict function gets registered to every ORM class and boom. And use jsonify anywhere

Python 3.7+ in 2023

You can add the dataclass decorator to your model and define a custom JSON serializer, then json.dumps will work (by providing the custom encoder to cls). In the example below, db_row is an instance of the DB class:

json.dumps(db_row, cls=models.CustomJSONEncoder)

{"id": 25, "name": "A component", "author": "Bob", "modified": "2023-02-08T11:49:15.675837"}

The custom JSON serializer can be easily modified to make it compatible with any type that isn't natively JSON serializable.

models.py

from datetime import datetime
import dataclasses
import json
from sqlalchemy import Column, Integer, String, DateTime
from database import Base


@dataclasses.dataclass # <<-- add this decorator 
class DB(Base):
    """Model used for SQLite database entries."""

    __tablename__ = "components"

    id: int = Column(Integer, primary_key=True, index=True)
    name: str = Column(String)
    author: str = Column(String)
    modified: datetime = Column(DateTime(timezone=True), default=datetime.utcnow)


class CustomJSONEncoder(json.JSONEncoder): # <<-- Add this custom encoder 
    """Custom JSON encoder for the DB class."""

    def default(self, o):
        if dataclasses.is_dataclass(o): # this serializes anything dataclass can handle  
            return dataclasses.asdict(o)
        if isinstance(o, datetime): # this adds support for datetime
            return o.isoformat()
        return super().default(o)

To further extend it for any non-serializable type you might use in your database, add another if statement to the custom encoder class that returns something serializable (e.g. str).

It is not so straighforward. I wrote some code to do this. I'm still working on it, and it uses the MochiKit framework. It basically translates compound objects between Python and Javascript using a proxy and registered JSON converters.

Browser side for database objects is db.js It needs the basic Python proxy source in proxy.js.

On the Python side there is the base proxy module. Then finally the SqlAlchemy object encoder in webserver.py. It also depends on metadata extractors found in the models.py file.

def alc2json(row):
    return dict([(col, str(getattr(row,col))) for col in row.__table__.columns.keys()])

I thought I'd play a little code golf with this one.

FYI: I am using automap_base since we have a separately designed schema according to business requirements. I just started using SQLAlchemy today but the documentation states that automap_base is an extension to declarative_base which seems to be the typical paradigm in the SQLAlchemy ORM so I believe this should work.

It does not get fancy with following foreign keys per Tjorriemorrie's solution, but it simply matches columns to values and handles Python types by str()-ing the column values. Our values consist Python datetime.time and decimal.Decimal class type results so it gets the job done.

Hope this helps any passers-by!

I know this is quite an older post. I took solution given by @SashaB and modified as per my need.

I added following things to it:

1. Field ignore list: A list of fields to be ignored while serializing
2. Field replace list: A dictionary containing field names to be replaced by values while serializing.
3. Removed methods and BaseQuery getting serialized

My code is as follows:

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

Hope it helps someone!

following code will serialize sqlalchemy result to 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) 

Calling fun,

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

The AlchemyEncoder is wonderful but sometimes fails with Decimal values. Here is an improved encoder that solves the decimal problem -

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)

When using sqlalchemy to connect to a db I this is a simple solution which is highly configurable. Use pandas.

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

(Tiny tweak on Sasha B's really excellent answer)

This specifically converts datetime objects to strings which in the original answer would be converted to 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)

class SqlToDict:
    def __init__(self, data) -> None:
        self.data = data

    def to_timestamp(self, date):
        if isinstance(date, datetime):
            return int(datetime.timestamp(date))
        else:
            return date

    def to_dict(self) -> List:
        arr = []
        for i in self.data:
            keys = [*i.keys()]
            values = [*i]
            values = [self.to_timestamp(d) for d in values]
            arr.append(dict(zip(keys, values)))
        return arr

For example:

SqlToDict(data).to_dict()

Very late 2023

but Faster than json method with: O[n] and 2n space req

My implementation also supports Type Checking and ability to hide some attributes which can trim unnecessary data. and optional debug flag to inspect contents. uses python 3.10 walrus operator.

def obj_to_dict(obj, remove=['_sa_instance_state'], debug=False):
    result = {}

    if type(obj).__name__ == "Row":
        return dict(obj)

    for k in (obj := obj.__dict__):
        if k not in remove:
            result[key] = obj[k]

    print(result) if debug else None
    return result

you can add as_dict method to your model

from sqlalchemy.inspection import inspect

def implement_as_dict(model):
    if not hasattr(model,"as_dict"):
        column_names=[]
        imodel = inspect(model)
        for c in imodel.columns:
            column_names.append(c.key)

        #define model.as_dict()
        def as_dict(self):
            d = {}
            for c in column_names:
                d[c] = getattr(self,c)
            return d

        setattr(model,"as_dict",as_dict)

#model definition
class User(Base):
    __tablename__ = 'users'

    id = Column(Integer, primary_key=True)
    name = Column(String)
# adding as_dict definition to model
implement_as_dict(User)

then you can use

user = session.query(User).filter_by(name='rick').first() 

user.as_dict()
#sample output 
{"id":1,"name":"rick"}

Under Flask, this works and handles datatime fields, transforming a field of type
'time': datetime.datetime(2018, 3, 22, 15, 40) into
"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)

The built in serializer chokes with utf-8 cannot decode invalid start byte for some inputs. Instead, I went with:

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

Maybe you can use a class like this

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!

With that all objects have the to_dict method