I have a following table in sqlalchemy:
class FieldType(enum.Enum):
INT_FIELD = 0
FLOAT_FIELD = 1
STRING_FIELD = 2
class EAVTable(Base):
__tablename__ = 'EAVTable'
field_name = Column(Stirng, primary_key=True)
field_type = Column(Enum(FieldType))
int_field = Column(Integer)
float_field = Column(Float)
string_field = Column(String)
This is to model the EAV model which fits my business purpose.
Now to use it easily in the code I have the following hybrid_property.
#hybrid_propderty
def value(self):
if self.field_type == FieldType.INT_FIELD:
return self.int_field
...
#value.setter
def value(self, value):
if type(value) == int:
self.field_type = FieldType.INT_FIELD
self.int_field = value
...
This works fine when I try to get and set the fields in Python code. But I still have a problem:
session.query(EAVTable).filter(EAVTable.value == 123)
This does not work out of the box but I had an idea of using hybrid.expression where we use a case statement:
#value.expression
def value(cls):
return case(
[
(cls.field_type == FieldType.INT_FIELD, cls.int_field),
(cls.field_type == FieldType.FLOAT_FIELD, cls.float_field),
...
]
)
This in theory works, for example, the SQL generated for query session.query(EAVTable.value = 123 looks like:
select * from where case
when field_type = INT_FIELD then int_field
when field_type = FLOAT_FIELD then float_field
when field_type = STRING_FIELD then string_field
end = 123;
Which semantically looks like what I like, but later I find that the case expression requires all the cases have the same type, or they are cast into the same type.
I understand this is a requirement from the SQL language and has nothing to do with sqlachemy, but for more seasoned sqlalchemy user, is there any easy way to do what I want to achieve? Is there a way to walk around this constraint?
You could move the comparison inside the CASE expression using a custom comparator:
from sqlalchemy.ext.hybrid import Comparator
class PolymorphicComparator(Comparator):
def __init__(self, cls):
self.cls = cls
def __clause_element__(self):
# Since SQL doesn't allow polymorphism here, don't bother trying.
raise NotImplementedError(
f"{type(self).__name__} cannot be used as a clause")
def operate(self, op, other):
cls = self.cls
return case(
[
(cls.field_type == field_type, op(field, other))
for field_type, field in [
(FieldType.INT_FIELD, cls.int_field),
(FieldType.FLOAT_FIELD, cls.float_field),
(FieldType.STRING_FIELD, cls.string_field),
]
],
else_=False
)
class EAVTable(Base):
...
# This replaces #value.expression
#value.comparator
def value(cls):
return PolymorphicComparator(cls)
This way the common type is just boolean.
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.
I'm using SQLAlchemy (0.9.4) in my Flask application. There are two tables with soft delete support in application.
class A(SoftDeleteMixin, db.Model):
id = db.Column(db.BigInteger, primary_key=True)
b_id = db.Column(db.BigInteger, db.ForeignKey('b.id'), nullable=False)
b = soft_delete_relationship('B.id', 'A.b_id')
class B(SoftDeleteMixin, db.Model):
id = db.Column(db.BigInteger, primary_key=True)
parent_id = db.Column(db.BigInteger, db.ForeignKey('b.id'))
parent = soft_delete_relationship(remote(id), parent_id, 'B.id', 'B.parent_id')
children = soft_delete_relationship(remote(parent_id), id, 'B.parent_id', 'B.id')
SoftDeleteMixin is based on LimitingQuery (https://bitbucket.org/zzzeek/sqlalchemy/wiki/UsageRecipes/PreFilteredQuery)
from sqlalchemy.orm.query import Query
class NonDeletedQuery(Query):
def get(self, ident):
return Query.get(self.populate_existing(), ident)
def __iter__(self):
return Query.__iter__(self.private())
def from_self(self, *ent):
return Query.from_self(self.private(), *ent)
def private(self):
mzero = self._mapper_zero()
if mzero is not None and hasattr(mzero, 'class_'):
soft_deleted = getattr(mzero.class_, 'soft_deleted', None)
return self.enable_assertions(False).filter(soft_deleted.is_(False)) if soft_deleted else self
else:
return self
And soft_delete_relationship constructs relationship with custom primaryjoin (for join on non-soft_deleted).
def soft_delete_relationship(first, second, *args, **kwargs):
if isinstance(first, str) and isinstance(second, str):
other, other_column = first.split('.')
_this, this_column = second.split('.')
primaryjoin = ' & '.join(['({} == {})'.format(first, second), '{}.soft_deleted.is_(False)'.format(other)])
else:
other, other_column = args[0].split('.')
_this, this_column = args[1].split('.')
primaryjoin = lambda: (first == second) & getattr(second.table.c, 'soft_deleted').is_(False)
kwargs['primaryjoin'] = primaryjoin
return relationship(other, **kwargs)
The problem occurs when I write query with aliased B:
b_parent = aliased(B)
A.query.join(A.b).outerjoin(b_parent, B.parent)
I get following SQL:
SELECT ... FROM a JOIN b ON b.id = a.b_id LEFT OUTER JOIN b AS b_1 ON b_1.id = b.parent_id AND *b*.soft_deleted IS False
But I expect following:
SELECT ... FROM a JOIN b ON b.id = a.b_id LEFT OUTER JOIN b AS b_1 ON b_1.id = b.parent_id AND *b_1*.soft_deleted IS False
When I explicitly write:
A.query.join(A.b).outerjoin(b_parent, (b_parent.id == B.parent_id) & b_parent.soft_deleted.is_(False))
I got right query.
How can I get proper alias to b_1 in query without explicit join condition?
Btw, there was expected SQL in SQLAlchemy 0.7.9.
OK, I figured it out.
getattr(second.table.c, 'soft_deleted') must be also with remote() annotation.
In other words primaryjoin of relationship in B.parent should look like:
(remote(B.id) == B.parent_id) & remote(B.soft_deleted).is_(False)
I am using: SQLAlchemy 0.7.9 and Python 2.7.3 with Bottle 0.11.4. I am an amateur at python.
I have a class (with many columns) derived from declarative base like this:
class Base(object):
#declared_attr
def __tablename__(cls):
return cls.__name__.lower()
id = Column(Integer, primary_key = True)
def to_dict(self):
serialized = dict((column_name, getattr(self, column_name))
for column_name in self.__table__.c.keys())
return serialized
Base = declarative_base(cls=Base)
class Case(Base):
version = Column(Integer)
title = Column(String(32))
plausible_dd = Column(Text)
frame = Column(Text)
primary_task = Column(Text)
secondary_task = Column(Text)
eval_objectives = Column(Text)
...
I am currently using this 'route' in Bottle to dump out a row/class in json like this:
#app.route('/<name>/:record')
def default(name, record, db):
myClass = getattr(sys.modules[__name__], name)
parms = db.query(myClass).filter(myClass.id == record)
result = json.dumps(([parm.to_dict() for parm in parms]))
return result
My first question is: How can I have each column have some static text that I can use as a proper name such that I can iterate over the columns and get their values AND proper names? For example:
class Case(Base):
version = Column(Integer)
version.pn = "Version Number"
My second question is: Does the following do what I am looking for? I have seen examples of this, but I don't understand the explanation.
Example from sqlalchemy.org:
id = Column("some_table_id", Integer)
My interpretation of the example:
version = Column("Version Number", Integer)
Obviously I don't want a table column to be created. I just want the column to have an "attribute" in the generic sense. Thank you in advance.
info dictionary could be used for that. In your model class define it like this:
class Case(Base):
version = Column(Integer, info={'description': 'Version Number'})
Then it can accessed as the table column property:
desc = Case.__table__.c.version.info.get('description', '<no description>')
Update
Here's one way to iterate through all the columns in the table and get their names, values and descriptions. This example uses dict comprehension, which is available since Python 2.7.
class Case(Base):
# Column definitions go here...
def as_dict(self):
return {c.name: (getattr(self, c.name), c.info.get('description'))
for c in self.__table__.c}