I wondered if it is possible to query documents in MongoDB by computed properties using mongoengine in python.
Currently, my model looks like this:
class SnapshotIndicatorKeyValue(db.Document):
meta = {"collection": "snapshot_indicator_key_values"}
snapshot_id = db.ObjectIdField(nullable=False)
indicator_key_id = db.ObjectIdField(nullable=False)
value = db.FloatField(nullable=False)
created_at = db.DateTimeField()
updated_at = db.DateTimeField()
#property
def snapshot(self):
return Snapshot.objects(id=self.snapshot_id).first()
def indicator_key(self):
return IndicatorKey.objects(id=self.indicator_key_id).first()
When I do for example SnapshotIndicatorKeyValue .objects().first().snapshot, I can access the snapshotproperty.
But when I try to query it, it doesn't work. For example:
SnapshotIndicatorKeyValue.objects(snapshot__date_time__lte=current_date_time)
I get the error `mongoengine.errors.InvalidQueryError: Cannot resolve field "snapshot"``
Is there any way to get this working with queries?
I need to query SnapshotIndicatorKeyValue based on a property of snapshot.
In order to query the snapshot property directly through mongoengine, you can reference the related snapshot object rather than the snapshot_id in your SnapshotIndicatorKeyValue document definition.
An amended model using a Reference field would be like this:
from mongoengine import Document, ReferenceField
class Snapshot(Document)
property_abc = RelevantPropertyHere() # anything you need
class SnapshotIndicatorKeyValue(Document):
snapshot = ReferenceField(Snapshot)
You would sucessively save an instance of Snapshot and an instance of SnapshotIndicatorKeyValue like this:
sample_snapshot = Snapshot(property_abc=relevant_value_here) # anything you need
sample_snapshot.save()
sample_indicatorkeyvalue = SnapshotIndicatorKeyValue()
sample_indicatorkeyvalue.snapshot = sample_snapshot
sample_indicatorkeyvalue.save()
You can then refer to any of the snapshot's properties through:
SnapshotIndicatorKeyValue.objects.first().snapshot.property_abc
I start to use mongoengine in Python as a Document-Object Mappe on an already established collection. The documents are schema less. Now for development, debugging and might within the application the question what fields/keys the object User has is of interest.
Is there a different approach to achieve the same, may be without querying the document every time?
class User(DynamicDocument):
field_one = StringField()
def keys(self):
return type(self).objects.as_pymongo().filter(id=self.id).first().keys()
You can use instance._data.keys() for this, it will combine both known and dynamic fields.
from mongoengine import *
connect()
class TestDoc(DynamicDocument):
f1 = StringField()
# simulate document with dynamic fields
td1 = TestDoc(f1='garbage1')
td1.other_field = 'garbage2'
td1.other_field2 = 'garbage99'
td1.save()
# show how it looks in the database
print(TestDoc.objects.as_pymongo()) # [{'_id': ObjectId('...'), 'f1': 'garbage1', 'other_field': 'garbage2', 'other_field2': 'garbage99'}]
doc = TestDoc.objects.first()
print(doc._data.keys()) # ['f1', 'id', 'other_field', 'other_field2']
You can also look at instance._dynamic_fields.keys() which will list only the dynamic ones.
The basic problem is that in a Flask application trying to return a MongoDB document I get the error
TypeError: Object of type 'BaseQuerySet' is not JSON serializable
the get method is the following:
def get(self, projectId):
response = MyObject.objects(project=projectId)
return response , 200, None
There may be multiple objects with the same projectId so a BaseQuerySet is returned.
I tried using BSON json_util (as suggested here: JSON serializing Mongodb) but the code below:
response=bson.json_util.dumps(response)
returns just the list of the document's fields without any value.
The only workaround I figure is to return a naive string concatenation of the fields I need.
The same code was working fine few time ago, have anyone got a similar problem?
EDIT
The Class MyObject is like to the one below:
from flask_mongoengine import MongoEngine
from mongoengine.fields import *
db = MongoEngine()
class User(db.Document):
email = db.StringField(max_length=120)
project = db.StringField(db.StringField(max_length=64))
creation_date = db.DateTimeField(default=datetime.datetime.now)
modified_date = db.DateTimeField(default=datetime.datetime.now)
I'm using Flask, Flask-SQLAlchemy, Flask-Marshmallow + marshmallow-sqlalchemy, trying to implement REST api PUT method. I haven't found any tutorial using SQLA and Marshmallow implementing update.
Here is the code:
class NodeSchema(ma.Schema):
# ...
class NodeAPI(MethodView):
decorators = [login_required, ]
model = Node
def get_queryset(self):
if g.user.is_admin:
return self.model.query
return self.model.query.filter(self.model.owner == g.user)
def put(self, node_id):
json_data = request.get_json()
if not json_data:
return jsonify({'message': 'Invalid request'}), 400
# Here is part which I can't make it work for me
data, errors = node_schema.load(json_data)
if errors:
return jsonify(errors), 422
queryset = self.get_queryset()
node = queryset.filter(Node.id == node_id).first_or_404()
# Here I need some way to update this object
node.update(data) #=> raises AttributeError: 'Node' object has no attribute 'update'
# Also tried:
# node = queryset.filter(Node.id == node_id)
# node.update(data) <-- It doesn't if know there is any object
# Wrote testcase, when user1 tries to modify node of user2. Node doesn't change (OK), but user1 gets status code 200 (NOT OK).
db.session.commit()
return jsonify(), 200
UPDATED, 2022-12-08
Extending the ModelSchema from marshmallow-sqlalchemy instead of Flask-Marshmallow you can use the load method, which is defined like this:
load(data, *, session=None, instance=None, transient=False, **kwargs)
Putting that to use, it should look like that (or similar query):
node_schema.load(json_data, session= current_app.session, instance=Node().query.get(node_id))
And if you want to load without all required fields of Model, you can add the partial=True argument, like this:
node_schema.load(json_data, instance=Node().query.get(node_id), partial=True)
See the docs for more info (does not include definition of ModelSchema.load).
See the code for the load definition.
I wrestled with this issue for some time, and in consequence came back again and again to this post. In the end what made my situation difficult was that there was a confounding issue involving SQLAlchemy sessions. I figure this is common enough to Flask, Flask-SQLAlchemy, SQLAlchemy, and Marshmallow, to put down a discussion. I certainly, do not claim to be an expert on this, and yet I believe what I state below is essentially correct.
The db.session is, in fact, closely tied to the process of updating the DB with Marshmallow, and because of that decided to to give the details, but first the short of it.
Short Answer
Here is the answer I arrived at for updating the database using Marshmallow. It is a different approach from the very helpful post of Jair Perrut. I did look at the Marshmallow API and yet was unable to get his solution working in the code presented, because at the time I was experimenting with his solution I was not managing my SQLAlchemy sessions properly. To go a bit further, one might say that I wasn't managing them at all. The model can be updated in the following way:
user_model = user_schema.load(user)
db.session.add(user_model.data)
db.session.commit()
Give the session.add() a model with primary key and it will assume an update, leave the primary key out and a new record is created instead. This isn't all that surprising since MySQL has an ON DUPLICATE KEY UPDATE clause which performs an update if the key is present and creates if not.
Details
SQLAlchemy sessions are handled by Flask-SQLAlchemy during a request to the application. At the beginning of the request the session is opened, and when the request is closed that session is also closed. Flask provides hooks for setting up and tearing down the application where code for managing sessions and connections may be found. In the end, though, the SQLAlchemy session is managed by the developer, and Flask-SQLAlchemy just helps. Here is a particular case that illustrates the management of sessions.
Consider a function that gets a user dictionary as an argument and uses that with Marshmallow() to load the dictionary into a model. In this case, what is required is not the creation of a new object, but the update of an existing object. There are 2 things to keep in mind at the start:
The model classes are defined in a python module separate from any code, and these models require the session. Often the developer (Flask documentation) will put a line db = SQLAlchemy() at the head of this file to meet this requirement. This in fact, creates a session for the model.
from flask_sqlalchemy import SQLAlchemy
db = SQLAlchemy()
In some other separate file there may be a need for a SQLAlchemy session as well. For example, the code may need to update the model, or create a new entry, by calling a function there. Here is where one might find db.session.add(user_model) and db.session.commit(). This session is created in the same way as in the bullet point above.
There are 2 SQLAlchemy sessions created. The model sits in one (SignallingSession) and the module uses its own (scoped_session). In fact, there are 3. The Marshmallow UserSchema has sqla_session = db.session: a session is attached to it. This then is the third, and the details are found in the code below:
from marshmallow_sqlalchemy import ModelSchema
from donate_api.models.donation import UserModel
from flask_sqlalchemy import SQLAlchemy
db = SQLAlchemy()
class UserSchema(ModelSchema):
class Meta(object):
model = UserModel
strict = True
sqla_session = db.session
def some_function(user):
user_schema = UserSchema()
user['customer_id'] = '654321'
user_model = user_schema.load(user)
# Debug code:
user_model_query = UserModel.query.filter_by(id=3255161).first()
print db.session.object_session(user_model_query)
print db.session.object_session(user_model.data)
print db.session
db.session.add(user_model.data)
db.session.commit()
return
At the head of this module the model is imported, which creates its session, and then the module will create its own. Of course, as pointed out there is also the Marshmallow session. This is entirely acceptable to some degree because SQLAlchemy allows the developer to manage the sessions. Consider what happens when some_function(user) is called where user['id'] is assigned some value that exists in the database.
Since the user includes a valid primary key then db.session.add(user_model.data) knows that it is not creating a new row, but updating an existing one. This behavior should not be surprising, and is to be at least somewhat expected since from the MySQL documentation:
13.2.5.2 INSERT ... ON DUPLICATE KEY UPDATE Syntax
If you specify an ON DUPLICATE KEY UPDATE clause and a row to be inserted would cause a duplicate value in a UNIQUE index or PRIMARY KEY, an UPDATE of the old row occurs.
The snippet of code is then seen to be updating the customer_id on the dictionary for the user with primary key 32155161. The new customer_id is '654321'. The dictionary is loaded with Marshmallow and a commit done to the database. Examining the database it can be found that it was indeed updated. You might try two ways of verifying this:
In the code: db.session.query(UserModel).filter_by(id=325516).first()
In MySQL: select * from user
If you were to consider the following:
In the code: UserModel.query.filter_by(id=3255161).customer_id
You would find that the query brings back None. The model is not synchronized with the database. I have failed to manage our SQLAlchemy sessions correctly. In an attempt to bring clarity to this consider the output of the print statements when separate imports are made:
<sqlalchemy.orm.session.SignallingSession object at 0x7f81b9107b90>
<sqlalchemy.orm.session.SignallingSession object at 0x7f81b90a6150>
<sqlalchemy.orm.scoping.scoped_session object at 0x7f81b95eac50>
In this case the UserModel.query session is different from the Marshmallow session. The Marshmallow session is what gets loaded and added. This means that querying the model will not show our changes. In fact, if we do:
db.session.object_session(user_model.data).commit()
The model query will now bring back the updated customer_id! Consider the second alternative where the imports are done through flask_essentials:
from flask_sqlalchemy import SQLAlchemy
from flask_marshmallow import Marshmallow
db = SQLAlchemy()
ma = Marshmallow()
<sqlalchemy.orm.session.SignallingSession object at 0x7f00fe227910>
<sqlalchemy.orm.session.SignallingSession object at 0x7f00fe227910>
<sqlalchemy.orm.scoping.scoped_session object at 0x7f00fed38710>
And the UserModel.query session is now the same as the user_model.data (Marshmallow) session. Now the UserModel.query does reflect the change in the database: the Marshmallow and UserModel.query sessions are the same.
A note: the signalling session is the default session that Flask-SQLAlchemy uses. It extends the default session system with bind selection and modification tracking.
I have rolled out own solution. Hope it helps someone else. Solution implements update method on Node model.
Solution:
class Node(db.Model):
# ...
def update(self, **kwargs):
# py2 & py3 compatibility do:
# from six import iteritems
# for key, value in six.iteritems(kwargs):
for key, value in kwargs.items():
setattr(self, key, value)
class NodeAPI(MethodView):
decorators = [login_required, ]
model = Node
def get_queryset(self):
if g.user.is_admin:
return self.model.query
return self.model.query.filter(self.model.owner == g.user)
def put(self, node_id):
json_data = request.get_json()
if not json_data:
abort(400)
data, errors = node_schema.load(json_data) # validate with marshmallow
if errors:
return jsonify(errors), 422
queryset = self.get_queryset()
node = queryset.filter(self.model.id == node_id).first_or_404()
node.update(**data)
db.session.commit()
return jsonify(message='Successfuly updated'), 200
Latest Update [2020]:
You might facing the issue of mapping keys to the database models. Your request body have only updated fields so, you want to change only those without affecting others. There is an option to write multiple if conditions but that's not a good approach.
Solution
You can implement patch or put methods using sqlalchemy library only.
For example:
YourModelName.query.filter_by(
your_model_column_id = 12 #change 12: where condition to find particular row
).update(request_data)
request_data should be dict object. For ex.
{
"your_model_column_name_1": "Hello",
"your_model_column_name_2": "World",
}
In above case, only two columns will be updated that is: your_model_column_name_1 and your_model_column_name_2
Update function maps request_data to the database models and creates update query for you. Checkout this: https://docs.sqlalchemy.org/en/13/core/dml.html#sqlalchemy.sql.expression.update
Previous answer seems to be outdated as ModelSchema is now deprecated.
You should instead SQLAlchemyAutoSchema with the proper options.
class NodeSchema(SQLAlchemyAutoSchema):
class Meta:
model = Node
load_instance = True
sqla_session = db.session
node_schema = NodeSchema()
# then when you need to update a Node orm instance :
node_schema.load(node_data, instance=node, partial=True)
db.session.update()
Below is my solution with Flask-Marshmallow + marshmallow-sqlalchemy bundle as the author requested initially.
schemas.py
from flask import current_app
from flask_marshmallow import Marshmallow
from app.models import Node
ma = Marshmallow(current_app)
class NodeSchema(ma.SQLAlchemyAutoSchema):
class Meta:
model = Node
load_instance = True
load_instance is a key point here to make an update further.
routes.py
from flask import jsonify, request
from marshmallow import ValidationError
from app import db
#bp.route("/node/<node_uuid>/edit", methods=["POST"])
def edit_node(node_uuid):
json_data = request.get_json(force=True, silent=True)
node = Node.query.filter_by(
node_uuid=node_uuid
).first()
if node:
try:
schema = NodeSchema()
json_data["node_uuid"] = node_uuid
node = schema.load(json_data, instance=node)
db.session.commit()
return schema.jsonify(node)
except ValidationError as err:
return jsonify(err.messages), 422
else:
return jsonify("Not found"), 404
You have to check for existence of Node first, otherwise the new instance will be created.
Is it possible to store a mongo_id as an ObjectId object in a MongoAlchemy field? I've been able to store an ObjectId inside of a document I defined manually, but it seems as though I'm restricted to storing the string value of the id in the context of the MongoAlchemy ORM.
Here's some of my code:
class Group(db.Document):
name = db.StringField()
trial_id = db.StringField(required=False)
participants = db.ListField(
db.DictField(db.AnythingField()), default_empty=True, required=False)
def add_participant(self, participant):
self.participants.append({
'participant_id': participant.mongo_id,
'start': datetime.utcnow(),
})
class Trial(db.Document):
name = db.StringField()
groups = db.ListField(
db.DocumentField(Group), default_empty=True, required=False)
def add_group(self, group):
group.trial_id = str(self.mongo_id)
group.save()
def get_group(self, group):
return Group.query.filter(
{'name': group, 'trial_id': str(self.mongo_id)}).first()
You'll see that I'm able to store a mongo_id as an ObjectId object in the Group method add_participant (since it's creating document manually, not through the MongoAlchemy ORM), but am forced to convert the mongo_id to a string in order to store it in a db.StringField.
I tried storing the original ObjectId in a db.AnythingField, but was then unable to filter by it.
Does anyone know if it's possible to store an ObjectId in a MongoAlchemy field and then filter by it in a database query?
Thank you!
You want an ObjectIdField: http://www.mongoalchemy.org/api/schema/fields.html#mongoalchemy.fields.ObjectIdField
This is the type of field which is used for mongo_id (although that one is special-cased)
try
id = db.ObjectIdField().gen()
This would automatically generate the object id for each instance of the mongo db object/document - as would id's in relational dbs