Related
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/)
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
A flat implementation
You could use something like this:
from sqlalchemy.ext.declarative import DeclarativeMeta
class AlchemyEncoder(json.JSONEncoder):
def default(self, obj):
if isinstance(obj.__class__, DeclarativeMeta):
# an SQLAlchemy class
fields = {}
for field in [x for x in dir(obj) if not x.startswith('_') and x != 'metadata']:
data = obj.__getattribute__(field)
try:
json.dumps(data) # this will fail on non-encodable values, like other classes
fields[field] = data
except TypeError:
fields[field] = None
# a json-encodable dict
return fields
return json.JSONEncoder.default(self, obj)
and then convert to JSON using:
c = YourAlchemyClass()
print json.dumps(c, cls=AlchemyEncoder)
It will ignore fields that are not encodable (set them to 'None').
It doesn't auto-expand relations (since this could lead to self-references, and loop forever).
A recursive, non-circular implementation
If, however, you'd rather loop forever, you could use:
from sqlalchemy.ext.declarative import DeclarativeMeta
def new_alchemy_encoder():
_visited_objs = []
class AlchemyEncoder(json.JSONEncoder):
def default(self, obj):
if isinstance(obj.__class__, DeclarativeMeta):
# don't re-visit self
if obj in _visited_objs:
return None
_visited_objs.append(obj)
# an SQLAlchemy class
fields = {}
for field in [x for x in dir(obj) if not x.startswith('_') and x != 'metadata']:
fields[field] = obj.__getattribute__(field)
# a json-encodable dict
return fields
return json.JSONEncoder.default(self, obj)
return AlchemyEncoder
And then encode objects using:
print json.dumps(e, cls=new_alchemy_encoder(), check_circular=False)
This would encode all children, and all their children, and all their children... Potentially encode your entire database, basically. When it reaches something its encoded before, it will encode it as 'None'.
A recursive, possibly-circular, selective implementation
Another alternative, probably better, is to be able to specify the fields you want to expand:
def new_alchemy_encoder(revisit_self = False, fields_to_expand = []):
_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']:
val = obj.__getattribute__(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] = None
continue
fields[field] = val
# a json-encodable dict
return fields
return json.JSONEncoder.default(self, obj)
return AlchemyEncoder
You can now call it with:
print json.dumps(e, cls=new_alchemy_encoder(False, ['parents']), check_circular=False)
To only expand SQLAlchemy fields called 'parents', for example.
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="user1#gmail.com"), User(email="user2#gmail.com")
db.create_all()
db.session.add_all(users)
db.session.commit()
app.run()
The /users/ route will now return a list of users.
[
{"email": "user1#gmail.com", "id": 1},
{"email": "user2#gmail.com", "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":"user1#gmail.com",
"id":1
},
{
"email":"user2#gmail.com",
"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
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"
}
]
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
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
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:
Field ignore list: A list of fields to be ignored while serializing
Field replace list: A dictionary containing field names to be replaced by values while serializing.
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!
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).
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)
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
My implementation
def obj_to_dict(obj, remove=['_sa_instance_state'], debug=False):
result = {}
if type(obj).__name__ == "Row":
return dict(obj)
obj = obj.__dict__
for key in obj:
if key in remove:
continue
result[key] = obj[key]
if debug:
print(result)
return result
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
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)
This is a JSONEncoder version that preserves model column order and only keeps recursively defined column and relationship fields. It also formats most JSON unserializable types:
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)
I'm trying to teach myself how to create a flask API. I've started with this outline template of how to structure the project. https://github.com/Zukkster/flask-restful
When I start working with dates and a PostgreSQL database I hit serialisation errors
The API works and it writes to the database, and I think I've eventually worked out that the error I'm getting is when Postman returns the json of the record that is written. So I think the issue is in the "def json(self)" of the "model" code. Until I added the DecoderDateTime I was getting a serialisation error, I'm failing to decode it properly and now the error is a little more cryptic
> File "C:\Python38\Lib\json\decoder.py", line 340, in decode
> raise JSONDecodeError("Extra data", s, end) json.decoder.JSONDecodeError: Extra data: line 1 column 5 (char 4)
Is this what Marshmallow is supposed to handle? and I just need to use that and define a schema. All this date serialisation looks nasty (dates always are) will Marshmallow just handle that complexity? I think it's just that I need to be looking at a newer tutorial? What I liked about the tutorial is that it focuses on how the project should be structured rather than just doing a single code file ... which most devs will look at and laugh you out of town.
resources\force_element_group.py
from flask_restful import Resource, reqparse
#from flask_jwt import jwt_required
from models.force_element_group import ForceElementGroupModel
import json
import datetime
from json import JSONEncoder
class DateTimeEncoder(JSONEncoder):
# Override the default method
def default(self, obj):
if isinstance(obj, (datetime.date, datetime.datetime)):
return obj.isoformat()
class ForceElementGroup(Resource):
parser = reqparse.RequestParser() # only allow price changes, no name changes allowed
parser.add_argument('created_user', type=str, required=True, help='The name of the user creating the group - if left blank created as admin')
# parser.add_argument('created_timestamp', type = lambda d: datetime.strptime(d, '%Y%m%d'))
parser.add_argument('created_timestamp', type=str, required=True, help='Need date')
# #jwt_required()
def post(self, force_element_group_name):
if ForceElementGroupModel.find_by_name(force_element_group_name):
return {'message': "An Force Element with name '{}' already exists.".format(force_element_group_name)}, 400
data = ForceElementGroup.parser.parse_args()
force_element_group = ForceElementGroupModel(force_element_group_name, data['created_user'], json.dumps(data['created_timestamp'], cls=DateTimeEncoder))
try:
force_element_group.save_to_db()
except:
return {"message": "An error occurred inserting the item."}, 500
return force_element_group.json(), 201
class ForceElementGroupList(Resource):
# #jwt_required()
def get(self):
return {'force_element_groups': [force_element_group.json() for force_element_group in
ForceElementGroupModel.query.all()]}
model\force_element_group.py
from db import db
from datetime import datetime
import json
import dateutil.parser
# custom Decoder
def DecodeDateTime(empDict):
if 'joindate' in empDict:
empDict["joindate"] = dateutil.parser.parse(empDict["joindate"])
return empDict
class ForceElementGroupModel(db.Model):
__tablename__ = 'force_element_group'
__table_args__ = {'schema': 'force_element'}
force_element_group_id = db.Column(db.Integer, primary_key=True)
force_element_group_name = db.Column(db.String(100), nullable=False)
created_user = db.Column(db.String(100), nullable=False, default='Admin')
created_timestamp = db.Column(db.DateTime, nullable=False, default=datetime.utcnow, onupdate=datetime.utcnow)# server_default=sqlalchemy.sql.func.now())#default=datetime.utcnow
def __init__(self, force_element_group_name, created_user, created_timestamp):
self.force_element_group_name = force_element_group_name
self.created_user = created_user
self.created_timestamp = created_timestamp
def json(self):
return {'force_element_group_name': self.force_element_group_name, 'created_user': self.created_user, 'created_timestamp': json.loads(str(self.created_timestamp), object_hook=DecodeDateTime)}
#classmethod
def find_by_name(cls, force_element_group_name):
return cls.query.filter_by(force_element_group_name=force_element_group_name).first() # simple TOP 1 select
def save_to_db(self): # Upserting data
db.session.add(self)
db.session.commit() # Balla
def delete_from_db(self):
db.session.delete(self)
db.session.commit()
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/)
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
A flat implementation
You could use something like this:
from sqlalchemy.ext.declarative import DeclarativeMeta
class AlchemyEncoder(json.JSONEncoder):
def default(self, obj):
if isinstance(obj.__class__, DeclarativeMeta):
# an SQLAlchemy class
fields = {}
for field in [x for x in dir(obj) if not x.startswith('_') and x != 'metadata']:
data = obj.__getattribute__(field)
try:
json.dumps(data) # this will fail on non-encodable values, like other classes
fields[field] = data
except TypeError:
fields[field] = None
# a json-encodable dict
return fields
return json.JSONEncoder.default(self, obj)
and then convert to JSON using:
c = YourAlchemyClass()
print json.dumps(c, cls=AlchemyEncoder)
It will ignore fields that are not encodable (set them to 'None').
It doesn't auto-expand relations (since this could lead to self-references, and loop forever).
A recursive, non-circular implementation
If, however, you'd rather loop forever, you could use:
from sqlalchemy.ext.declarative import DeclarativeMeta
def new_alchemy_encoder():
_visited_objs = []
class AlchemyEncoder(json.JSONEncoder):
def default(self, obj):
if isinstance(obj.__class__, DeclarativeMeta):
# don't re-visit self
if obj in _visited_objs:
return None
_visited_objs.append(obj)
# an SQLAlchemy class
fields = {}
for field in [x for x in dir(obj) if not x.startswith('_') and x != 'metadata']:
fields[field] = obj.__getattribute__(field)
# a json-encodable dict
return fields
return json.JSONEncoder.default(self, obj)
return AlchemyEncoder
And then encode objects using:
print json.dumps(e, cls=new_alchemy_encoder(), check_circular=False)
This would encode all children, and all their children, and all their children... Potentially encode your entire database, basically. When it reaches something its encoded before, it will encode it as 'None'.
A recursive, possibly-circular, selective implementation
Another alternative, probably better, is to be able to specify the fields you want to expand:
def new_alchemy_encoder(revisit_self = False, fields_to_expand = []):
_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']:
val = obj.__getattribute__(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] = None
continue
fields[field] = val
# a json-encodable dict
return fields
return json.JSONEncoder.default(self, obj)
return AlchemyEncoder
You can now call it with:
print json.dumps(e, cls=new_alchemy_encoder(False, ['parents']), check_circular=False)
To only expand SQLAlchemy fields called 'parents', for example.
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="user1#gmail.com"), User(email="user2#gmail.com")
db.create_all()
db.session.add_all(users)
db.session.commit()
app.run()
The /users/ route will now return a list of users.
[
{"email": "user1#gmail.com", "id": 1},
{"email": "user2#gmail.com", "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":"user1#gmail.com",
"id":1
},
{
"email":"user2#gmail.com",
"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
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"
}
]
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
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
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:
Field ignore list: A list of fields to be ignored while serializing
Field replace list: A dictionary containing field names to be replaced by values while serializing.
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!
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).
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)
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
My implementation
def obj_to_dict(obj, remove=['_sa_instance_state'], debug=False):
result = {}
if type(obj).__name__ == "Row":
return dict(obj)
obj = obj.__dict__
for key in obj:
if key in remove:
continue
result[key] = obj[key]
if debug:
print(result)
return result
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
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)
This is a JSONEncoder version that preserves model column order and only keeps recursively defined column and relationship fields. It also formats most JSON unserializable types:
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)
This question already has answers here:
How to serialize SqlAlchemy result to JSON?
(37 answers)
Closed 4 years ago.
I'm trying to jsonify a SQLAlchemy result set in Flask/Python.
The Flask mailing list suggested the following method http://librelist.com/browser//flask/2011/2/16/jsonify-sqlalchemy-pagination-collection-result/#04a0754b63387f87e59dda564bde426e :
return jsonify(json_list = qryresult)
However I'm getting the following error back:
TypeError: <flaskext.sqlalchemy.BaseQuery object at 0x102c2df90>
is not JSON serializable
What am I overlooking here?
I have found this question: How to serialize SqlAlchemy result to JSON? which seems very similar however I didn't know whether Flask had some magic to make it easier as the mailing list post suggested.
Edit: for clarification, this is what my model looks like
class Rating(db.Model):
__tablename__ = 'rating'
id = db.Column(db.Integer, primary_key=True)
fullurl = db.Column(db.String())
url = db.Column(db.String())
comments = db.Column(db.Text)
overall = db.Column(db.Integer)
shipping = db.Column(db.Integer)
cost = db.Column(db.Integer)
honesty = db.Column(db.Integer)
communication = db.Column(db.Integer)
name = db.Column(db.String())
ipaddr = db.Column(db.String())
date = db.Column(db.String())
def __init__(self, fullurl, url, comments, overall, shipping, cost, honesty, communication, name, ipaddr, date):
self.fullurl = fullurl
self.url = url
self.comments = comments
self.overall = overall
self.shipping = shipping
self.cost = cost
self.honesty = honesty
self.communication = communication
self.name = name
self.ipaddr = ipaddr
self.date = date
It seems that you actually haven't executed your query. Try following:
return jsonify(json_list = qryresult.all())
[Edit]: Problem with jsonify is, that usually the objects cannot be jsonified automatically. Even Python's datetime fails ;)
What I have done in the past, is adding an extra property (like serialize) to classes that need to be serialized.
def dump_datetime(value):
"""Deserialize datetime object into string form for JSON processing."""
if value is None:
return None
return [value.strftime("%Y-%m-%d"), value.strftime("%H:%M:%S")]
class Foo(db.Model):
# ... SQLAlchemy defs here..
def __init__(self, ...):
# self.foo = ...
pass
#property
def serialize(self):
"""Return object data in easily serializable format"""
return {
'id' : self.id,
'modified_at': dump_datetime(self.modified_at),
# This is an example how to deal with Many2Many relations
'many2many' : self.serialize_many2many
}
#property
def serialize_many2many(self):
"""
Return object's relations in easily serializable format.
NB! Calls many2many's serialize property.
"""
return [ item.serialize for item in self.many2many]
And now for views I can just do:
return jsonify(json_list=[i.serialize for i in qryresult.all()])
[Edit 2019]:
In case you have more complex objects or circular references, use a library like marshmallow).
Here's what's usually sufficient for me:
I create a serialization mixin which I use with my models. The serialization function basically fetches whatever attributes the SQLAlchemy inspector exposes and puts it in a dict.
from sqlalchemy.inspection import inspect
class Serializer(object):
def serialize(self):
return {c: getattr(self, c) for c in inspect(self).attrs.keys()}
#staticmethod
def serialize_list(l):
return [m.serialize() for m in l]
All that's needed now is to extend the SQLAlchemy model with the Serializer mixin class.
If there are fields you do not wish to expose, or that need special formatting, simply override the serialize() function in the model subclass.
class User(db.Model, Serializer):
id = db.Column(db.Integer, primary_key=True)
username = db.Column(db.String)
password = db.Column(db.String)
# ...
def serialize(self):
d = Serializer.serialize(self)
del d['password']
return d
In your controllers, all you have to do is to call the serialize() function (or serialize_list(l) if the query results in a list) on the results:
def get_user(id):
user = User.query.get(id)
return json.dumps(user.serialize())
def get_users():
users = User.query.all()
return json.dumps(User.serialize_list(users))
I had the same need, to serialize into json. Take a look at this question. It shows how to discover columns programmatically. So, from that I created the code below. It works for me, and I'll be using it in my web app. Happy coding!
def to_json(inst, cls):
"""
Jsonify the sql alchemy query result.
"""
convert = dict()
# add your coversions for things like datetime's
# and what-not that aren't serializable.
d = dict()
for c in cls.__table__.columns:
v = getattr(inst, c.name)
if c.type in convert.keys() and v is not None:
try:
d[c.name] = convert[c.type](v)
except:
d[c.name] = "Error: Failed to covert using ", str(convert[c.type])
elif v is None:
d[c.name] = str()
else:
d[c.name] = v
return json.dumps(d)
class Person(base):
__tablename__ = 'person'
id = Column(Integer, Sequence('person_id_seq'), primary_key=True)
first_name = Column(Text)
last_name = Column(Text)
email = Column(Text)
#property
def json(self):
return to_json(self, self.__class__)
Here's my approach:
https://github.com/n0nSmoker/SQLAlchemy-serializer
pip install SQLAlchemy-serializer
You can easily add mixin to your model and then just call
.to_dict() method on its instance.
You also can write your own mixin on base of SerializerMixin.
For a flat query (no joins) you can do this
#app.route('/results/')
def results():
data = Table.query.all()
result = [d.__dict__ for d in data]
return jsonify(result=result)
and if you only want to return certain columns from the database you can do this
#app.route('/results/')
def results():
cols = ['id', 'url', 'shipping']
data = Table.query.all()
result = [{col: getattr(d, col) for col in cols} for d in data]
return jsonify(result=result)
Ok, I've been working on this for a few hours, and I've developed what I believe to be the most pythonic solution yet. The following code snippets are python3 but shouldn't be too horribly painful to backport if you need.
The first thing we're gonna do is start with a mixin that makes your db models act kinda like dicts:
from sqlalchemy.inspection import inspect
class ModelMixin:
"""Provide dict-like interface to db.Model subclasses."""
def __getitem__(self, key):
"""Expose object attributes like dict values."""
return getattr(self, key)
def keys(self):
"""Identify what db columns we have."""
return inspect(self).attrs.keys()
Now we're going to define our model, inheriting the mixin:
class MyModel(db.Model, ModelMixin):
id = db.Column(db.Integer, primary_key=True)
foo = db.Column(...)
bar = db.Column(...)
# etc ...
That's all it takes to be able to pass an instance of MyModel() to dict() and get a real live dict instance out of it, which gets us quite a long way towards making jsonify() understand it. Next, we need to extend JSONEncoder to get us the rest of the way:
from flask.json import JSONEncoder
from contextlib import suppress
class MyJSONEncoder(JSONEncoder):
def default(self, obj):
# Optional: convert datetime objects to ISO format
with suppress(AttributeError):
return obj.isoformat()
return dict(obj)
app.json_encoder = MyJSONEncoder
Bonus points: if your model contains computed fields (that is, you want your JSON output to contain fields that aren't actually stored in the database), that's easy too. Just define your computed fields as #propertys, and extend the keys() method like so:
class MyModel(db.Model, ModelMixin):
id = db.Column(db.Integer, primary_key=True)
foo = db.Column(...)
bar = db.Column(...)
#property
def computed_field(self):
return 'this value did not come from the db'
def keys(self):
return super().keys() + ['computed_field']
Now it's trivial to jsonify:
#app.route('/whatever', methods=['GET'])
def whatever():
return jsonify(dict(results=MyModel.query.all()))
If you are using flask-restful you can use marshal:
from flask.ext.restful import Resource, fields, marshal
topic_fields = {
'title': fields.String,
'content': fields.String,
'uri': fields.Url('topic'),
'creator': fields.String,
'created': fields.DateTime(dt_format='rfc822')
}
class TopicListApi(Resource):
def get(self):
return {'topics': [marshal(topic, topic_fields) for topic in DbTopic.query.all()]}
You need to explicitly list what you are returning and what type it is, which I prefer anyway for an api. Serialization is easily taken care of (no need for jsonify), dates are also not a problem. Note that the content for the uri field is automatically generated based on the topic endpoint and the id.
Here's my answer if you're using the declarative base (with help from some of the answers already posted):
# in your models definition where you define and extend declarative_base()
from sqlalchemy.ext.declarative import declarative_base
...
Base = declarative_base()
Base.query = db_session.query_property()
...
# define a new class (call "Model" or whatever) with an as_dict() method defined
class Model():
def as_dict(self):
return { c.name: getattr(self, c.name) for c in self.__table__.columns }
# and extend both the Base and Model class in your model definition, e.g.
class Rating(Base, Model):
____tablename__ = 'rating'
id = db.Column(db.Integer, primary_key=True)
fullurl = db.Column(db.String())
url = db.Column(db.String())
comments = db.Column(db.Text)
...
# then after you query and have a resultset (rs) of ratings
rs = Rating.query.all()
# you can jsonify it with
s = json.dumps([r.as_dict() for r in rs], default=alchemyencoder)
print (s)
# or if you have a single row
r = Rating.query.first()
# you can jsonify it with
s = json.dumps(r.as_dict(), default=alchemyencoder)
# you will need this alchemyencoder where your are calling json.dumps to handle datetime and decimal format
# credit to Joonas # http://codeandlife.com/2014/12/07/sqlalchemy-results-to-json-the-easy-way/
def alchemyencoder(obj):
"""JSON encoder function for SQLAlchemy special classes."""
if isinstance(obj, datetime.date):
return obj.isoformat()
elif isinstance(obj, decimal.Decimal):
return float(obj)
Flask-Restful 0.3.6 the Request Parsing recommend marshmallow
marshmallow is an ORM/ODM/framework-agnostic library for converting
complex datatypes, such as objects, to and from native Python
datatypes.
A simple marshmallow example is showing below.
from marshmallow import Schema, fields
class UserSchema(Schema):
name = fields.Str()
email = fields.Email()
created_at = fields.DateTime()
from marshmallow import pprint
user = User(name="Monty", email="monty#python.org")
schema = UserSchema()
result = schema.dump(user)
pprint(result)
# {"name": "Monty",
# "email": "monty#python.org",
# "created_at": "2014-08-17T14:54:16.049594+00:00"}
The core features contain
Declaring Schemas
Serializing Objects (“Dumping”)
Deserializing Objects (“Loading”)
Handling Collections of Objects
Validation
Specifying Attribute Names
Specifying Serialization/Deserialization Keys
Refactoring: Implicit Field Creation
Ordering Output
“Read-only” and “Write-only” Fields
Specify Default Serialization/Deserialization Values
Nesting Schemas
Custom Fields
Here is a way to add an as_dict() method on every class, as well as any other method you want to have on every single class.
Not sure if this is the desired way or not, but it works...
class Base(object):
def as_dict(self):
return dict((c.name,
getattr(self, c.name))
for c in self.__table__.columns)
Base = declarative_base(cls=Base)
I've been looking at this problem for the better part of a day, and here's what I've come up with (credit to https://stackoverflow.com/a/5249214/196358 for pointing me in this direction).
(Note: I'm using flask-sqlalchemy, so my model declaration format is a bit different from straight sqlalchemy).
In my models.py file:
import json
class Serializer(object):
__public__ = None
"Must be implemented by implementors"
def to_serializable_dict(self):
dict = {}
for public_key in self.__public__:
value = getattr(self, public_key)
if value:
dict[public_key] = value
return dict
class SWEncoder(json.JSONEncoder):
def default(self, obj):
if isinstance(obj, Serializer):
return obj.to_serializable_dict()
if isinstance(obj, (datetime)):
return obj.isoformat()
return json.JSONEncoder.default(self, obj)
def SWJsonify(*args, **kwargs):
return current_app.response_class(json.dumps(dict(*args, **kwargs), cls=SWEncoder, indent=None if request.is_xhr else 2), mimetype='application/json')
# stolen from https://github.com/mitsuhiko/flask/blob/master/flask/helpers.py
and all my model objects look like this:
class User(db.Model, Serializer):
__public__ = ['id','username']
... field definitions ...
In my views I call SWJsonify wherever I would have called Jsonify, like so:
#app.route('/posts')
def posts():
posts = Post.query.limit(PER_PAGE).all()
return SWJsonify({'posts':posts })
Seems to work pretty well. Even on relationships. I haven't gotten far with it, so YMMV, but so far it feels pretty "right" to me.
Suggestions welcome.
I was looking for something like the rails approach used in ActiveRecord to_json and implemented something similar using this Mixin after being unsatisfied with other suggestions. It handles nested models, and including or excluding attributes of the top level or nested models.
class Serializer(object):
def serialize(self, include={}, exclude=[], only=[]):
serialized = {}
for key in inspect(self).attrs.keys():
to_be_serialized = True
value = getattr(self, key)
if key in exclude or (only and key not in only):
to_be_serialized = False
elif isinstance(value, BaseQuery):
to_be_serialized = False
if key in include:
to_be_serialized = True
nested_params = include.get(key, {})
value = [i.serialize(**nested_params) for i in value]
if to_be_serialized:
serialized[key] = value
return serialized
Then, to get the BaseQuery serializable I extended BaseQuery
class SerializableBaseQuery(BaseQuery):
def serialize(self, include={}, exclude=[], only=[]):
return [m.serialize(include, exclude, only) for m in self]
For the following models
class ContactInfo(db.Model, Serializer):
id = db.Column(db.Integer, primary_key=True)
user_id = db.Column(db.Integer, db.ForeignKey('user.id'))
full_name = db.Column(db.String())
source = db.Column(db.String())
source_id = db.Column(db.String())
email_addresses = db.relationship('EmailAddress', backref='contact_info', lazy='dynamic')
phone_numbers = db.relationship('PhoneNumber', backref='contact_info', lazy='dynamic')
class EmailAddress(db.Model, Serializer):
id = db.Column(db.Integer, primary_key=True)
email_address = db.Column(db.String())
type = db.Column(db.String())
contact_info_id = db.Column(db.Integer, db.ForeignKey('contact_info.id'))
class PhoneNumber(db.Model, Serializer):
id = db.Column(db.Integer, primary_key=True)
phone_number = db.Column(db.String())
type = db.Column(db.String())
contact_info_id = db.Column(db.Integer, db.ForeignKey('contact_info.id'))
phone_numbers = db.relationship('Invite', backref='phone_number', lazy='dynamic')
You could do something like
#app.route("/contact/search", methods=['GET'])
def contact_search():
contact_name = request.args.get("name")
matching_contacts = ContactInfo.query.filter(ContactInfo.full_name.like("%{}%".format(contact_name)))
serialized_contact_info = matching_contacts.serialize(
include={
"phone_numbers" : {
"exclude" : ["contact_info", "contact_info_id"]
},
"email_addresses" : {
"exclude" : ["contact_info", "contact_info_id"]
}
}
)
return jsonify(serialized_contact_info)
I was working with a sql query defaultdict of lists of RowProxy objects named jobDict
It took me a while to figure out what Type the objects were.
This was a really simple quick way to resolve to some clean jsonEncoding just by typecasting the row to a list and by initially defining the dict with a value of list.
jobDict = defaultdict(list)
def set_default(obj):
# trickyness needed here via import to know type
if isinstance(obj, RowProxy):
return list(obj)
raise TypeError
jsonEncoded = json.dumps(jobDict, default=set_default)
I just want to add my method to do this.
just define a custome json encoder to serilize your db models.
class ParentEncoder(json.JSONEncoder):
def default(self, obj):
# convert object to a dict
d = {}
if isinstance(obj, Parent):
return {"id": obj.id, "name": obj.name, 'children': list(obj.child)}
if isinstance(obj, Child):
return {"id": obj.id, "name": obj.name}
d.update(obj.__dict__)
return d
then in your view function
parents = Parent.query.all()
dat = json.dumps({"data": parents}, cls=ParentEncoder)
resp = Response(response=dat, status=200, mimetype="application/json")
return (resp)
it works well though the parent have relationships
It's been a lot of times and there are lots of valid answers, but the following code block seems to work:
my_object = SqlAlchemyModel()
my_serializable_obj = my_object.__dict__
del my_serializable_obj["_sa_instance_state"]
print(jsonify(my_serializable_object))
I'm aware that this is not a perfect solution, nor as elegant as the others, however for those who want o quick fix, they might try this.
This question already has answers here:
How to serialize SqlAlchemy result to JSON?
(37 answers)
Closed 4 years ago.
I'm trying to jsonify a SQLAlchemy result set in Flask/Python.
The Flask mailing list suggested the following method http://librelist.com/browser//flask/2011/2/16/jsonify-sqlalchemy-pagination-collection-result/#04a0754b63387f87e59dda564bde426e :
return jsonify(json_list = qryresult)
However I'm getting the following error back:
TypeError: <flaskext.sqlalchemy.BaseQuery object at 0x102c2df90>
is not JSON serializable
What am I overlooking here?
I have found this question: How to serialize SqlAlchemy result to JSON? which seems very similar however I didn't know whether Flask had some magic to make it easier as the mailing list post suggested.
Edit: for clarification, this is what my model looks like
class Rating(db.Model):
__tablename__ = 'rating'
id = db.Column(db.Integer, primary_key=True)
fullurl = db.Column(db.String())
url = db.Column(db.String())
comments = db.Column(db.Text)
overall = db.Column(db.Integer)
shipping = db.Column(db.Integer)
cost = db.Column(db.Integer)
honesty = db.Column(db.Integer)
communication = db.Column(db.Integer)
name = db.Column(db.String())
ipaddr = db.Column(db.String())
date = db.Column(db.String())
def __init__(self, fullurl, url, comments, overall, shipping, cost, honesty, communication, name, ipaddr, date):
self.fullurl = fullurl
self.url = url
self.comments = comments
self.overall = overall
self.shipping = shipping
self.cost = cost
self.honesty = honesty
self.communication = communication
self.name = name
self.ipaddr = ipaddr
self.date = date
It seems that you actually haven't executed your query. Try following:
return jsonify(json_list = qryresult.all())
[Edit]: Problem with jsonify is, that usually the objects cannot be jsonified automatically. Even Python's datetime fails ;)
What I have done in the past, is adding an extra property (like serialize) to classes that need to be serialized.
def dump_datetime(value):
"""Deserialize datetime object into string form for JSON processing."""
if value is None:
return None
return [value.strftime("%Y-%m-%d"), value.strftime("%H:%M:%S")]
class Foo(db.Model):
# ... SQLAlchemy defs here..
def __init__(self, ...):
# self.foo = ...
pass
#property
def serialize(self):
"""Return object data in easily serializable format"""
return {
'id' : self.id,
'modified_at': dump_datetime(self.modified_at),
# This is an example how to deal with Many2Many relations
'many2many' : self.serialize_many2many
}
#property
def serialize_many2many(self):
"""
Return object's relations in easily serializable format.
NB! Calls many2many's serialize property.
"""
return [ item.serialize for item in self.many2many]
And now for views I can just do:
return jsonify(json_list=[i.serialize for i in qryresult.all()])
[Edit 2019]:
In case you have more complex objects or circular references, use a library like marshmallow).
Here's what's usually sufficient for me:
I create a serialization mixin which I use with my models. The serialization function basically fetches whatever attributes the SQLAlchemy inspector exposes and puts it in a dict.
from sqlalchemy.inspection import inspect
class Serializer(object):
def serialize(self):
return {c: getattr(self, c) for c in inspect(self).attrs.keys()}
#staticmethod
def serialize_list(l):
return [m.serialize() for m in l]
All that's needed now is to extend the SQLAlchemy model with the Serializer mixin class.
If there are fields you do not wish to expose, or that need special formatting, simply override the serialize() function in the model subclass.
class User(db.Model, Serializer):
id = db.Column(db.Integer, primary_key=True)
username = db.Column(db.String)
password = db.Column(db.String)
# ...
def serialize(self):
d = Serializer.serialize(self)
del d['password']
return d
In your controllers, all you have to do is to call the serialize() function (or serialize_list(l) if the query results in a list) on the results:
def get_user(id):
user = User.query.get(id)
return json.dumps(user.serialize())
def get_users():
users = User.query.all()
return json.dumps(User.serialize_list(users))
I had the same need, to serialize into json. Take a look at this question. It shows how to discover columns programmatically. So, from that I created the code below. It works for me, and I'll be using it in my web app. Happy coding!
def to_json(inst, cls):
"""
Jsonify the sql alchemy query result.
"""
convert = dict()
# add your coversions for things like datetime's
# and what-not that aren't serializable.
d = dict()
for c in cls.__table__.columns:
v = getattr(inst, c.name)
if c.type in convert.keys() and v is not None:
try:
d[c.name] = convert[c.type](v)
except:
d[c.name] = "Error: Failed to covert using ", str(convert[c.type])
elif v is None:
d[c.name] = str()
else:
d[c.name] = v
return json.dumps(d)
class Person(base):
__tablename__ = 'person'
id = Column(Integer, Sequence('person_id_seq'), primary_key=True)
first_name = Column(Text)
last_name = Column(Text)
email = Column(Text)
#property
def json(self):
return to_json(self, self.__class__)
Here's my approach:
https://github.com/n0nSmoker/SQLAlchemy-serializer
pip install SQLAlchemy-serializer
You can easily add mixin to your model and then just call
.to_dict() method on its instance.
You also can write your own mixin on base of SerializerMixin.
For a flat query (no joins) you can do this
#app.route('/results/')
def results():
data = Table.query.all()
result = [d.__dict__ for d in data]
return jsonify(result=result)
and if you only want to return certain columns from the database you can do this
#app.route('/results/')
def results():
cols = ['id', 'url', 'shipping']
data = Table.query.all()
result = [{col: getattr(d, col) for col in cols} for d in data]
return jsonify(result=result)
Ok, I've been working on this for a few hours, and I've developed what I believe to be the most pythonic solution yet. The following code snippets are python3 but shouldn't be too horribly painful to backport if you need.
The first thing we're gonna do is start with a mixin that makes your db models act kinda like dicts:
from sqlalchemy.inspection import inspect
class ModelMixin:
"""Provide dict-like interface to db.Model subclasses."""
def __getitem__(self, key):
"""Expose object attributes like dict values."""
return getattr(self, key)
def keys(self):
"""Identify what db columns we have."""
return inspect(self).attrs.keys()
Now we're going to define our model, inheriting the mixin:
class MyModel(db.Model, ModelMixin):
id = db.Column(db.Integer, primary_key=True)
foo = db.Column(...)
bar = db.Column(...)
# etc ...
That's all it takes to be able to pass an instance of MyModel() to dict() and get a real live dict instance out of it, which gets us quite a long way towards making jsonify() understand it. Next, we need to extend JSONEncoder to get us the rest of the way:
from flask.json import JSONEncoder
from contextlib import suppress
class MyJSONEncoder(JSONEncoder):
def default(self, obj):
# Optional: convert datetime objects to ISO format
with suppress(AttributeError):
return obj.isoformat()
return dict(obj)
app.json_encoder = MyJSONEncoder
Bonus points: if your model contains computed fields (that is, you want your JSON output to contain fields that aren't actually stored in the database), that's easy too. Just define your computed fields as #propertys, and extend the keys() method like so:
class MyModel(db.Model, ModelMixin):
id = db.Column(db.Integer, primary_key=True)
foo = db.Column(...)
bar = db.Column(...)
#property
def computed_field(self):
return 'this value did not come from the db'
def keys(self):
return super().keys() + ['computed_field']
Now it's trivial to jsonify:
#app.route('/whatever', methods=['GET'])
def whatever():
return jsonify(dict(results=MyModel.query.all()))
If you are using flask-restful you can use marshal:
from flask.ext.restful import Resource, fields, marshal
topic_fields = {
'title': fields.String,
'content': fields.String,
'uri': fields.Url('topic'),
'creator': fields.String,
'created': fields.DateTime(dt_format='rfc822')
}
class TopicListApi(Resource):
def get(self):
return {'topics': [marshal(topic, topic_fields) for topic in DbTopic.query.all()]}
You need to explicitly list what you are returning and what type it is, which I prefer anyway for an api. Serialization is easily taken care of (no need for jsonify), dates are also not a problem. Note that the content for the uri field is automatically generated based on the topic endpoint and the id.
Here's my answer if you're using the declarative base (with help from some of the answers already posted):
# in your models definition where you define and extend declarative_base()
from sqlalchemy.ext.declarative import declarative_base
...
Base = declarative_base()
Base.query = db_session.query_property()
...
# define a new class (call "Model" or whatever) with an as_dict() method defined
class Model():
def as_dict(self):
return { c.name: getattr(self, c.name) for c in self.__table__.columns }
# and extend both the Base and Model class in your model definition, e.g.
class Rating(Base, Model):
____tablename__ = 'rating'
id = db.Column(db.Integer, primary_key=True)
fullurl = db.Column(db.String())
url = db.Column(db.String())
comments = db.Column(db.Text)
...
# then after you query and have a resultset (rs) of ratings
rs = Rating.query.all()
# you can jsonify it with
s = json.dumps([r.as_dict() for r in rs], default=alchemyencoder)
print (s)
# or if you have a single row
r = Rating.query.first()
# you can jsonify it with
s = json.dumps(r.as_dict(), default=alchemyencoder)
# you will need this alchemyencoder where your are calling json.dumps to handle datetime and decimal format
# credit to Joonas # http://codeandlife.com/2014/12/07/sqlalchemy-results-to-json-the-easy-way/
def alchemyencoder(obj):
"""JSON encoder function for SQLAlchemy special classes."""
if isinstance(obj, datetime.date):
return obj.isoformat()
elif isinstance(obj, decimal.Decimal):
return float(obj)
Flask-Restful 0.3.6 the Request Parsing recommend marshmallow
marshmallow is an ORM/ODM/framework-agnostic library for converting
complex datatypes, such as objects, to and from native Python
datatypes.
A simple marshmallow example is showing below.
from marshmallow import Schema, fields
class UserSchema(Schema):
name = fields.Str()
email = fields.Email()
created_at = fields.DateTime()
from marshmallow import pprint
user = User(name="Monty", email="monty#python.org")
schema = UserSchema()
result = schema.dump(user)
pprint(result)
# {"name": "Monty",
# "email": "monty#python.org",
# "created_at": "2014-08-17T14:54:16.049594+00:00"}
The core features contain
Declaring Schemas
Serializing Objects (“Dumping”)
Deserializing Objects (“Loading”)
Handling Collections of Objects
Validation
Specifying Attribute Names
Specifying Serialization/Deserialization Keys
Refactoring: Implicit Field Creation
Ordering Output
“Read-only” and “Write-only” Fields
Specify Default Serialization/Deserialization Values
Nesting Schemas
Custom Fields
Here is a way to add an as_dict() method on every class, as well as any other method you want to have on every single class.
Not sure if this is the desired way or not, but it works...
class Base(object):
def as_dict(self):
return dict((c.name,
getattr(self, c.name))
for c in self.__table__.columns)
Base = declarative_base(cls=Base)
I've been looking at this problem for the better part of a day, and here's what I've come up with (credit to https://stackoverflow.com/a/5249214/196358 for pointing me in this direction).
(Note: I'm using flask-sqlalchemy, so my model declaration format is a bit different from straight sqlalchemy).
In my models.py file:
import json
class Serializer(object):
__public__ = None
"Must be implemented by implementors"
def to_serializable_dict(self):
dict = {}
for public_key in self.__public__:
value = getattr(self, public_key)
if value:
dict[public_key] = value
return dict
class SWEncoder(json.JSONEncoder):
def default(self, obj):
if isinstance(obj, Serializer):
return obj.to_serializable_dict()
if isinstance(obj, (datetime)):
return obj.isoformat()
return json.JSONEncoder.default(self, obj)
def SWJsonify(*args, **kwargs):
return current_app.response_class(json.dumps(dict(*args, **kwargs), cls=SWEncoder, indent=None if request.is_xhr else 2), mimetype='application/json')
# stolen from https://github.com/mitsuhiko/flask/blob/master/flask/helpers.py
and all my model objects look like this:
class User(db.Model, Serializer):
__public__ = ['id','username']
... field definitions ...
In my views I call SWJsonify wherever I would have called Jsonify, like so:
#app.route('/posts')
def posts():
posts = Post.query.limit(PER_PAGE).all()
return SWJsonify({'posts':posts })
Seems to work pretty well. Even on relationships. I haven't gotten far with it, so YMMV, but so far it feels pretty "right" to me.
Suggestions welcome.
I was looking for something like the rails approach used in ActiveRecord to_json and implemented something similar using this Mixin after being unsatisfied with other suggestions. It handles nested models, and including or excluding attributes of the top level or nested models.
class Serializer(object):
def serialize(self, include={}, exclude=[], only=[]):
serialized = {}
for key in inspect(self).attrs.keys():
to_be_serialized = True
value = getattr(self, key)
if key in exclude or (only and key not in only):
to_be_serialized = False
elif isinstance(value, BaseQuery):
to_be_serialized = False
if key in include:
to_be_serialized = True
nested_params = include.get(key, {})
value = [i.serialize(**nested_params) for i in value]
if to_be_serialized:
serialized[key] = value
return serialized
Then, to get the BaseQuery serializable I extended BaseQuery
class SerializableBaseQuery(BaseQuery):
def serialize(self, include={}, exclude=[], only=[]):
return [m.serialize(include, exclude, only) for m in self]
For the following models
class ContactInfo(db.Model, Serializer):
id = db.Column(db.Integer, primary_key=True)
user_id = db.Column(db.Integer, db.ForeignKey('user.id'))
full_name = db.Column(db.String())
source = db.Column(db.String())
source_id = db.Column(db.String())
email_addresses = db.relationship('EmailAddress', backref='contact_info', lazy='dynamic')
phone_numbers = db.relationship('PhoneNumber', backref='contact_info', lazy='dynamic')
class EmailAddress(db.Model, Serializer):
id = db.Column(db.Integer, primary_key=True)
email_address = db.Column(db.String())
type = db.Column(db.String())
contact_info_id = db.Column(db.Integer, db.ForeignKey('contact_info.id'))
class PhoneNumber(db.Model, Serializer):
id = db.Column(db.Integer, primary_key=True)
phone_number = db.Column(db.String())
type = db.Column(db.String())
contact_info_id = db.Column(db.Integer, db.ForeignKey('contact_info.id'))
phone_numbers = db.relationship('Invite', backref='phone_number', lazy='dynamic')
You could do something like
#app.route("/contact/search", methods=['GET'])
def contact_search():
contact_name = request.args.get("name")
matching_contacts = ContactInfo.query.filter(ContactInfo.full_name.like("%{}%".format(contact_name)))
serialized_contact_info = matching_contacts.serialize(
include={
"phone_numbers" : {
"exclude" : ["contact_info", "contact_info_id"]
},
"email_addresses" : {
"exclude" : ["contact_info", "contact_info_id"]
}
}
)
return jsonify(serialized_contact_info)
I was working with a sql query defaultdict of lists of RowProxy objects named jobDict
It took me a while to figure out what Type the objects were.
This was a really simple quick way to resolve to some clean jsonEncoding just by typecasting the row to a list and by initially defining the dict with a value of list.
jobDict = defaultdict(list)
def set_default(obj):
# trickyness needed here via import to know type
if isinstance(obj, RowProxy):
return list(obj)
raise TypeError
jsonEncoded = json.dumps(jobDict, default=set_default)
I just want to add my method to do this.
just define a custome json encoder to serilize your db models.
class ParentEncoder(json.JSONEncoder):
def default(self, obj):
# convert object to a dict
d = {}
if isinstance(obj, Parent):
return {"id": obj.id, "name": obj.name, 'children': list(obj.child)}
if isinstance(obj, Child):
return {"id": obj.id, "name": obj.name}
d.update(obj.__dict__)
return d
then in your view function
parents = Parent.query.all()
dat = json.dumps({"data": parents}, cls=ParentEncoder)
resp = Response(response=dat, status=200, mimetype="application/json")
return (resp)
it works well though the parent have relationships
It's been a lot of times and there are lots of valid answers, but the following code block seems to work:
my_object = SqlAlchemyModel()
my_serializable_obj = my_object.__dict__
del my_serializable_obj["_sa_instance_state"]
print(jsonify(my_serializable_object))
I'm aware that this is not a perfect solution, nor as elegant as the others, however for those who want o quick fix, they might try this.