Django has some good automatic serialization of ORM models returned from DB to JSON format.
How to serialize SQLAlchemy query result to JSON format?
I tried jsonpickle.encode but it encodes query object itself.
I tried json.dumps(items) but it returns
TypeError: <Product('3', 'some name', 'some desc')> is not JSON serializable
Is it really so hard to serialize SQLAlchemy ORM objects to JSON /XML? Isn't there any default serializer for it? It's very common task to serialize ORM query results nowadays.
What I need is just to return JSON or XML data representation of SQLAlchemy query result.
SQLAlchemy objects query result in JSON/XML format is needed to be used in javascript datagird (JQGrid http://www.trirand.com/blog/)
This question is related to
python
json
sqlalchemy
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])
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).
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
Flask-JsonTools package has an implementation of JsonSerializableBase Base class for your models.
Usage:
from sqlalchemy.ext.declarative import declarative_base
from flask.ext.jsontools import JsonSerializableBase
Base = declarative_base(cls=(JsonSerializableBase,))
class User(Base):
#...
Now the User model is magically serializable.
If your framework is not Flask, you can just grab the code
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"
}
]
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/
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:
dictpassword value, but never include an outbound one)You can check out the (I hope!) comprehensive docs here: https://sqlathanor.readthedocs.io/en/latest
Hope this helps!
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)
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
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
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)
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'}}))
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
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 Convert sqlalchemy row object to python dict
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.
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)
While using some raw sql and undefined objects, using cursor.description appeared to get what I was looking for:
with connection.cursor() as cur:
print(query)
cur.execute(query)
for item in cur.fetchall():
row = {column.name: item[i] for i, column in enumerate(cur.description)}
print(row)
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!
My take utilizing (too many?) dictionaries:
def serialize(_query):
#d = dictionary written to per row
#D = dictionary d is written to each time, then reset
#Master = dictionary of dictionaries; the id Key (int, unique from database)
from D is used as the Key for the dictionary D entry in Master
Master = {}
D = {}
x = 0
for u in _query:
d = u.__dict__
D = {}
for n in d.keys():
if n != '_sa_instance_state':
D[n] = d[n]
x = d['id']
Master[x] = D
return Master
Running with flask (including jsonify) and flask_sqlalchemy to print outputs as JSON.
Call the function with jsonify(serialize()).
Works with all SQLAlchemy queries I've tried so far (running SQLite3)
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
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.
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)
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}
]
@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
}
]
}
from flask.json import JSONEncoder
class CustomJSONEncoder(JSONEncoder):
"Add support for serializing timedeltas"
def default(o):
if type(o) == datetime.timedelta:
return str(o)
elif type(o) == datetime.datetime:
return o.isoformat()
else:
return super().default(o)
app.json_encoder = CustomJSONEncoder
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)
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
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:
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!
(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)
Source: Stackoverflow.com