I had NDB class before and added new property receive_news just now:
class User(ndb.Model):
'''
Index
Key: user_id
'''
lang = ndb.StringProperty(required=None, indexed=True)
receive_news = ndb.BooleanProperty(required=None, indexed=True)
I would like to get list of users, who would like to receive my news (all users currently). I tried the following options:
keys = User.query(User.receive_news != True).fetch(keys_only=True)
keys = User.query(User.receive_news == None).fetch(keys_only=True)
both returns 0. How should I work properly with this new property?
Datastore indexes are only updated when entities are being written to the datastore, so only entities written after the new index was created will be added to it.
To have the pre-existing entities added to the index (so that they can be found by the query) you'll have to get and then re-write them. Maybe using something along these lines (you'll have to split it in separate requests/tasks if they are too many)
keys = []
for user in ndb.get_multi(User.query().fetch(keys_only=True)):
if user.receive_news is None:
user.receive_news = True
keys.append(user.key)
ndb.put_multi(keys)
Related
I am using the google cloud datastore python client to write an entity into the datastore which contains an embedded entity. An example entity might look like:
data_type: 1
raw_bytes: <unindexed blob>
values: <indexed embedded entity>
I checked the data from the console and the data is getting saved correctly and the values are present.
Next, I need to run a query from a python app engine application. I have represented the above as the following entity in my app engine code:
class DataValues(ndb.Model):
param1 = ndb.BooleanProperty()
param2 = ndb.IntegerProperty()
param3 = ndb.IntegerProperty()
class MyEntity(ndb.Expando):
data_type = ndb.IntegerProperty(required=True)
raw_bytes = ndb.BlobProperty()
values = ndb.StructuredProperty(DataValues)
One of the filters in the query depends on a property in values. Sample query code is as below:
MyEntity.query().filter(MyEntity.data_type == 1).filter(MyEntity.values.param1 == True).get()
I have created the corresponding composite index in my index.yaml
The query runs successfully but the resulting entity contains the embedded entity values as None. All other property values are present.
What can be the issue here ?
Add properties of DataValues entity as properties of the MyEntity.
This is a bit of a guess, but since datastore attributes are kind of keyed by both their name (in this case values) and the name of the "field type/class" (i.e. StructuredProperty), this might fix your problem:
class EmbeddedProperty(ndb.StructuredProperty):
pass
class MyEntity(ndb.Expando):
data_type = ndb.IntegerProperty(required=True)
raw_bytes = ndb.BlobProperty()
values = EmbeddedProperty(DataValues)
Give it a shot and let me know if values starts coming back non-null.
I struggled with the same problem, wanting to convert the embedded entity into a Python dictionary. One possible solution, although not a very elegant one, is to use a GenericProperty:
class MyEntity(ndb.Model):
data_type = ndb.IntegerProperty(required=True)
raw_bytes = ndb.BlobProperty()
values = ndb.GenericProperty()
values will then be read as an "Expando" object: Expando(param1=False,...). You can access the individual values with values.param1, values.param2 etc. I would prefer having a custom model class, but this should do the job.
I have NDB model class like below:
class Contest(ndb.Model):
end_date = ndb.DateProperty(required=True, indexed=True)
ended = ndb.BooleanProperty(required=False, indexed=True)
...
I will have a daily cron job to mark contests with passed end_date with ended equal to True. I've written the following code to do it:
contests = Contest.query()
current_datetime = datetime.datetime.utcnow()
today = datetime.date(current_datetime.year, current_datetime.month, current_datetime.day)
contests = contests.filter(Contest.end_date < today)
contests = contests.filter(Contest.ended == False)
contests = contests.fetch(limit=10)
for contest in contests:
contest.ended = True
ndb.put_multi(contests)
But I don't like it, since I have to read all entities just to update one value. Is there any way to modify it to read keys_only?
The object data overwrites the existing entity. The entire object is sent to Datastore
https://cloud.google.com/datastore/docs/concepts/entities#Datastore_Updating_an_entity
So you cannot send only one field of an entity, it will "remove" all existing fields. To be more accurate - replace an entity with all fields with new version of entity that have only one field.
You have to load all entities you want to update, with all properties, not just keys, set new value of a property, and put back into database.
I think a Python property is a good solution here:
class Contest(ndb.Model):
end_date = ndb.DateProperty(required=True, indexed=True)
#property
def ended(self):
return self.end_date < date.today()
This way you don't ever need to update your entities. The value is automatically computed whenever you need it.
An NDB model contains two properties: email and password. How to avoid adding to the database two records with the same email? NDB doesn't have UNIQUE option for a property, like relational databases do.
Checking that new email is not in the database before adding—won't satisfy me, because two parallel processes can both simultaneously do the checking and each add the same email.
I'm not sure that transactions can help here, I am under this impression after reading some of the manuals. Maybe the synchronous transactions? Does it mean one at a time?
Create the key of the entity by email, then use get_or_insert to check if exists.
Also read about keys , entities. and models
#ADD
key_a = ndb.Key(Person, email);
person = Person(key=key_a)
person.put()
#Insert unique
a = Person.get_or_insert(email)
or if you want to just check
#ADD
key_a = ndb.Key(Person, email);
person = Person(key=key_a)
person.put()
#Check if it's added
new_key_a =ndb.Key(Person, email);
a = new_key_a.get()
if a is not None:
return
Take care. Changing email will be really difficult (need to create new entry and copy all entries to new parent).
For that thing maybe you need to store the email, in another entity and have the User be the parent of that.
Another way is to use Transactions and check the email property. Transaction's work in the way: First that commits is the First that wins. A concept which means that if 2 users check for email only the first (lucky) one will succeed, thus your data will be consistent.
Maybe you are looking for the webapp2-authentication module, that can handle this for you. It can be imported like this import webapp2_extras.appengine.auth.models. Look here for a complete example.
I also ran into this problem, and the solution above didn't solve my problem:
making it a key was unacceptable in my case (i need the property to be changeable in the future)
using transactions on the email property doesn't work AFAIK (you can't do queries on non-key names inside transactions, so you can't check whether the e-mail already exists).
I ended up creating a separate model with no properties, and the unique property (email address) as the key name. In the main model, I store a reference to the email model (instead of storing the email as a string). Then, I can make 'change_email' a transaction that checks for uniqueness by looking up the email by key.
This is something that I've come across as well and I settled on a variation of #Remko's solution. My main issue with checking for an existing entity with the given email is a potential race condition like op stated. I added a separate model that uses an email address as the key and has a property that holds a token. By using get_or_insert, the returned entities token can be checked against the token passed in and if they match then the model was inserted.
import os
from google.appengine.ext import ndb
class UniqueEmail(ndb.Model):
token = ndb.StringProperty()
class User(ndb.Model):
email = ndb.KeyProperty(kind=UniqueEmail, required=True)
password = ndb.StringProperty(required=True)
def create_user(email, password):
token = os.urandom(24)
unique_email = UniqueEmail.get_or_insert(email,
token=token)
if token == unique_email.token:
# If the tokens match, that means a UniqueEmail entity
# was inserted by this process.
# Code to create User goes here.
# The tokens do not match, therefore the UniqueEmail entity
# was retrieved, so the email is already in use.
raise ValueError('That user already exists.')
I implemented a generic structure to control unique properties. This solution can be used for several kinds and properties. Besides, this solution is transparent for other developers, they use NDB methods put and delete as usual.
1) Kind UniqueCategory: a list of unique properties in order to group information. Example:
‘User.nickname’
2) Kind Unique: it contains the values of each unique property. The key is the own property value which you want to control of. I save the urlsafe of the main entity instead of the key or key.id() because is more practical and it doesn’t have problem with parent and it can be used for different kinds. Example:
parent: User.nickname
key: AVILLA
reference_urlsafe: ahdkZXZ-c3RhcnQtb3BlcmF0aW9uLWRldnINCxIEVXNlciIDMTIzDA (User key)
3) Kind User: for instance, I want to control unique values for email and nickname. I created a list called ‘uniqueness’ with the unique properties. I overwritten method put in transactional mode and I wrote the hook _post_delete_hook when one entity is deleted.
4) Exception ENotUniqueException: custom exception class raised when some value is duplicated.
5) Procedure check_uniqueness: check whether a value is duplicated.
6) Procedure delete_uniqueness: delete unique values when the main entity is deleted.
Any tips or improvement are welcome.
class UniqueCategory(ndb.Model):
# Key = [kind name].[property name]
class Unique(ndb.Model):
# Parent = UniqueCategory
# Key = property value
reference_urlsafe = ndb.StringProperty(required=True)
class ENotUniqueException(Exception):
def __init__(self, property_name):
super(ENotUniqueException, self).__init__('Property value {0} is duplicated'.format(property_name))
self. property_name = property_name
class User(ndb.Model):
# Key = Firebase UUID or automatically generated
firstName = ndb.StringProperty(required=True)
surname = ndb.StringProperty(required=True)
nickname = ndb.StringProperty(required=True)
email = ndb.StringProperty(required=True)
#ndb.transactional(xg=True)
def put(self):
result = super(User, self).put()
check_uniqueness (self)
return result
#classmethod
def _post_delete_hook(cls, key, future):
delete_uniqueness(key)
uniqueness = [nickname, email]
def check_uniqueness(entity):
def get_or_insert_unique_category(qualified_name):
unique_category_key = ndb.Key(UniqueCategory, qualified_name)
unique_category = unique_category_key.get()
if not unique_category:
unique_category = UniqueCategory(id=qualified_name)
unique_category.put()
return unique_category_key
def del_old_value(key, attribute_name, unique_category_key):
old_entity = key.get()
if old_entity:
old_value = getattr(old_entity, attribute_name)
if old_value != new_value:
unique_key = ndb.Key(Unique, old_value, parent=unique_category_key)
unique_key.delete()
# Main flow
for unique_attribute in entity.uniqueness:
attribute_name = unique_attribute._name
qualified_name = type(entity).__name__ + '.' + attribute_name
new_value = getattr(entity, attribute_name)
unique_category_key = get_or_insert_unique_category(qualified_name)
del_old_value(entity.key, attribute_name, unique_category_key)
unique = ndb.Key(Unique, new_value, parent=unique_category_key).get()
if unique is not None and unique.reference_urlsafe != entity.key.urlsafe():
raise ENotUniqueException(attribute_name)
else:
unique = Unique(parent=unique_category_key,
id=new_value,
reference_urlsafe=entity.key.urlsafe())
unique.put()
def delete_uniqueness(key):
list_of_keys = Unique.query(Unique.reference_urlsafe == key.urlsafe()).fetch(keys_only=True)
if list_of_keys:
ndb.delete_multi(list_of_keys)
I recently came across a number of articles pointing out to flatten the data for NoSQL databases. Coming from traditional SQL databases I realized I am replicating a SQL db bahaviour in GAE. So I started to refactor code where possible.
We have e.g. a social media site where users can become friends with each other.
class Friendship(ndb.Model):
from_friend = ndb.KeyProperty(kind=User)
to_friend = ndb.KeyProperty(kind=User)
Effectively the app creates a friendship instance between both users.
friendshipA = Friendship(from_friend = UserA, to_friend = userB)
friendshipB = Friendship(from_friend = UserB, to_friend = userA)
How could I now move this to the actual user model to flatten it. I thought maybe I could use a StructuredProperty. I know it is limited to 5000 entries, but that should be enough for friends.
class User(UserMixin, ndb.Model):
name = ndb.StringProperty()
friends = ndb.StructuredProperty(User, repeated=True)
So I came up with this, however User can't point to itself, so it seems. Because I get a NameError: name 'User' is not defined
Any idea how I could flatten it so that a single User instance would contain all its friends, with all their properties?
You can't create a StructuredProperty that references itself. Also, use of StructuredProperty to store a copy of User has additional problem of needing to perform a manual cascade update if a user ever modifies a property that is stored.
However, as KeyProperty accept String as kind, you can easily store the list of Users using KeyProperty as suggested by #dragonx. You can further optimise read by using ndb.get_multi to avoid multiple round-trip RPC calls when retrieving friends.
Here is a sample code:
class User(ndb.Model):
name = ndb.StringProperty()
friends = ndb.KeyProperty(kind="User", repeated=True)
userB = User(name="User B")
userB_key = userB.put()
userC = User(name="User C")
userC_key = userC.put()
userA = User(name="User A", friends=[userB_key, userC_key])
userA_key = userA.put()
# To retrieve all friends
for user in ndb.get_multi(userA.friends):
print "user: %s" % user.name
Use a KeyProperty that stores the key for the User instance.
in an app i have an entity that contains a list of other entities (let's say an event holding a list of assigned employees)
using objectify - i need to find all the events a particular employee is assigned to.
is there a basic way to filter a query if it contains the parameter - kind of the opposite of the query in
... quick pseudocode
findAll(Employee employee) {
...
return ofy.query(Event.class).filter("employees.contains", employee).list();
}
any help would be greatly appreciated
i tried just doing filter("employees", employee) after seeing this http://groups.google.com/group/objectify-appengine/browse_thread/thread/77ba676192c08e20 - but unfortunately this returns me an empty list
currently i'm doing something really inefficient - going through each event, iterating through the employees and adding them to a new list if it contains the given employee just to have something that works - i know this is not right though
let me add one thing,
the above query is not actually what it is, i was just using that because i did not think this would make a difference.
The Employee and Events are in the same entity group with Business as a parent
the actual query i am using is the following
ofy.query(Event.class).ancestor(businessKey).filter("employees", employee).list();
unfortunately this is still returning an empty list - does having the ancestor(key) in there mess up the filter?
solution, the employees field was not indexed correctly.
I added the datastore-indexes file to create a composite index, but was testing originally on a value that I added before the employees field was indexed, this was something stupid i was doing - simply having an index on the "business" field and the "employees" field fixed everything. the datastore-indexes file did not appear to be necessary, after deleting it and trying again everything worked fine.
Generally, you do this one of two ways:
Put a property of Set<Key<Employee>> on the Event
or
Put a property of Set<Key<Event>> on the Employee
You could also create a relationship entity, but if you're just doing filtering on values with relatively low counts, usually it's easier to just put the set property on one entity or the other.
Then filter as you describe:
ofy.query(Event.class).filter("employees", employee).list()
or
ofy.query(Employee.class).filter("events", event).list()
The list property should hold a Keys to the target entity. If you pass in an entity to the filter() method, Objectify will understand that you want to filter by the key instead.
Example :
/***************************************************/
#Entity
#Cache
public class News {
#Id Long id;
String news ;
#Index List<Long> friend_list = new ArrayList<Long>();
// My friends who can see my news , exemele : friend_list.add(id_f1); friend_list.add(id_f2); friend_list.add(id_f3);
//To make an operation on "friend_list", it is obligatory to index it
}
/*************************************************/
public News(Long id_f){
List<Long> friend_id = new ArrayList<Long>();
friend_id.add(id_f);
Query<Nesw> query = ofy().load().type(News.class).filter("friend_list in",friend_id).limit(limit);
//To filter a list, just after the name of the field you want to filter, add "IN".
//here ==> .filter("friend_list in",friend_id);
// if friend_list contains "id_friend" ==> the query return value
.........
}