I have a python project setup with Django 1.8.0 and POSTGRESQL. My model look like this:
class poll_db(models.Model):
p_pk = models.AutoField(primary_key=True)
p_name = models.CharField(max_length=256)
p_desc = models.CharField(max_length=512)
I have a post url registered to router on urls.py:
router.register(r'newpoll', views.createPoll)
I am trying to make a default POST call with the following URL
http://localhost:8080/newpoll/
And my postBody looks like:
{
"name": "What's the weekend plan?",
"desc": "Poll to decide on the weekend plan"
}
The request hits the server and there is a new entry created on the DB. But when I look at the created entry, it has empty values except for the p_pk
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which means the values are passed as empty. But when I try to override the default create method on the views.py, I see the values as part of the request and add to the db is fine.
All I am trying is to skip writing a method for adding it to the DB and use the default create method.
Any help is much appreciated. Thanks!
My bad. I had read-only fields on serializer.
I have a Django app with models accessible by both Django REST Framework and a regular form interface. The form interface has some validation checks before saving changes to the model, but not using any special Django framework, just a simple local change in the view.
I'd like to apply the same validation to forms and REST calls, so I want to move my validation into the model. I can see how to do that for simple cases using the validators field of the Field, but in one case I have a name/type/value model where the acceptable values for 'value' change depending on which type is selected. The validator doesn't get sent any information about the model that the field is in, so it doesn't have access to other fields.
How can I perform this validation, without having essentially the same code in a serializer for DRF and my POST view for the form?
I dug around codebase of drf a little bit. You can get values of all fields using following approach. Doing so, you can throw serialization error as
{'my_field':'error message} instead of {'non_field_error':'error message'}.
def validate_myfield(self, value):
data = self.get_initial() # data for all the fields
#do your validation
However, if you wish to do it for ListSerializer, i.e for serializer = serializer_class(many=True), this won't work. You will get list of empty values.
In that scenario, you could write your validations in def validate function and to avoid non_field_errors in your serialization error, you can raise ValidationError with error message as a dictionary instead of string.
def validate(self, data):
# do your validation
raise serializers.ValidationError({"your_field": "error_message"})
The validation per-field doesn't get sent any information about other fields, when it is defined like this:
def validate_myfield(self, value):
...
However, if you have a method defined like this:
def validate(self, data):
...
Then you get all the data in a dict, and you can do cross-field validation.
You can use the required package for your cross-field validation. It allows you to express your validation rules declaratively in python. You would have something like this with DRF:
class MySerializer(serializers.Serializer):
REQUIREMENTS = (
Requires("end_date", "start_date") +
Requires("end_date", R("end_date") > R("start_date")) +
Requires("end_date", R("end_date") < today.date() + one_year) +
Requires("start_date", R("start_date") < today.date() + one_year)
)
start_date = serializers.DateField(required=False, null=True, blank=True)
end_date = serializers.DateField(required=False, null=True, blank=True)
def validate(self, data):
self.REQUIREMENTS.validate(data) # handle validation error
You could put the REQUIREMENTS on your Model and have both your DRF and Django Form validate your data using it.
Here is a blog post explaining more
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.
I am using Tastypie for non-ORM data source (Amazon Dynamodb). I have gone through the official documentation for non-ORM source and found the following code:
class MessageResource(Resource):
# Just like a Django ``Form`` or ``Model``, we're defining all the
# fields we're going to handle with the API here.
uuid = fields.CharField(attribute='uuid')
user_uuid = fields.CharField(attribute='user_uuid')
message = fields.CharField(attribute='message')
created = fields.IntegerField(attribute='created')
I am new to Tastypie and what I understand is that fields uuid, message, created.. which are returned by API are defined over here. Is there any way that I return those fields that are not defined here i.e. all those fields returned by the dictionary in obj_get_list or obj_get.
You can use the dehydrade method. Simply add a new key to bundle.data.
def dehydrate(self, bundle):
for item in bundle.obj.iteritems():
bundle.data["new_key"] = "new_value"
return bundle
Hello i am doing a very small application in google appengine and i use python.
My problem is that i have two tables using de db.model ("clients" and "requests"). The table "client" has got the email and name fields and the table "requests" has got the email and issue fields. I want to do a query that returns for each request the email, issue and client name, if the email is the same in the two tables. Can anyone help, please?
The app engine datastore does not support joins, so you will not be able to solve this problem with GQL. You can use two gets, one for client and one for request, or you can use a ReferenceProperty to establish a relationship between the two entities.
If you need to model a one-to-many relationship, you can do it with a reference property. For your case, it would look something like this:
class Client(db.Model):
email = db.UserProperty()
name = db.StringProperty()
class Request(db.Model):
client = db.ReferencePrpoerty(Client, collection_name='requests')
issue = db.StringProperty()
Any Client entity that has a Request associated with it will automatically get a property called requests which is a Query object that will return all Request entities that have a client field set to the particular Client entity you are dealing with.
You might also want to make sure that the code that creates Request entities set each new entity to have the Client entity for the particular user as its ancestor. Keeping these associated items in the same entity group could be helpful for performance reasons and transactions.
using this models:
class Client(db.Model):
email = db.StringProperty()
name = db.StringProperty()
class Request(db.Model):
client = db.ReferenceProperty(Client, collection_name='requests')
issue = db.StringProperty()
With this code can query the data
from modelos import Client,Request
ctes=Client.all().filter("email =","somemail#mailbox.com.mx")
for ct in ctes:
allRequest4ThisUser=Request.all().filter("client =",ct)
for req in allRequest4ThisUser:
print req.issue