Django & Mongo ORM mapping - django

I have a Django project with a MongoDB, connecting through pymongo.
I've looked into several ORM(-like) layers, but none of them seem well maintained or supporting the Django 1.8 (mongo-engine only supports Django 1.5, mongokit is no longer maintained, and the other libraries seem to have no real community behind them).
So I think I'll be just using pymongo, which means that there is quite some things I'll need to implement myself, for example validation (checking that every document inserted in a collection has the required fields and field types).
How would I go about this?
Are there any example projects that I can take a look at?
I found this project which connects from Django directly to Mongo, but there is not much structure in it.

Use PyMODM. As the docs you linked to say, "PyMODM is an ORM-like framework on top of PyMongo. PyMODM is maintained by engineers at MongoDB, Inc. and is quick to adopt new MongoDB features. PyMODM is a “core” ODM, meaning that it provides simple, extensible functionality that can be leveraged by other libraries to target platforms like Django. At the same time, PyMODM is powerful enough to be used for developing applications on its own. Complete documentation is available on readthedocs in addition to a Gitter channel for discussing the project."
https://api.mongodb.com/python/3.4.0/tools.html

Related

Wagtail and Django-Tenants, does it work together?

Does anyone have experience in this topic? Is it fully incompatible or might it be possible to customize certain parts of the app to make it work.
multi-tenancy is not yet fully supported by Wagtail.
Although, as mentioned here in docs, there are some features that are supported.
You may find this blog helpful. Also here is a repository that implements basic features of multi tenancy with django and wagtail and you can play around with it.
Here are some other CMS (build on top of Django) you can try.
I think as long as there are no raw sql queries in wagtail's source code we are good to use django-tenents, the layer that django-tenets is working on is on top of django orm it self.
see wagtail-tenents

Library enabling to use triple store with Django

I need to create quickly a simple web application - an interface for querying a triple store. Previously I made such an application with Django for querying a graph database Neo4j, I used the Neomodel package for binding Django and Neo4j.
Is there such a package for using Django with a triple store? I have already installed Fuseki and have my data in turtle format.
On this page: http://csarven.ca/how-to-create-a-linked-data-site it is explained how to to do what I need but using PHP, which I have no notion of. Since I don't have much time to waste, I would prefer to work with the pythonic Django, already familiar to me.
If you want to work with Django, you're lucky, because Python has a libary that helps you to work with triple store, called RDFlib, based on RDF. RDFlib Docs
The Resource Description Framework (RDF) is a family of World Wide Web Consortium (W3C) specifications originally designed as a metadata data model. It has come to be used as a general method for conceptual description or modeling of information that is implemented in web resources, using a variety of syntax notations and data serialization formats. It is also used in knowledge management applications. Wikipedia
Working specifically in Django, it's hard to give a guideline because the question is wide. Maybe you can find some packages to help you in Django Packages

Is porting a Django app to GAE still an option?

I have started a month ago with GAE and have successfully deployed our current startup via Flask on GAE. It works fantastically well. Now being all too exited about GAE, I am thinking about porting a couple of my older Django apps on GAE as well.
To my surprise the documentation of it is surprisingly inconsistent and partially contradicting.
The official google page recommends using django-nonrel, which itself is already disconstinued.
Django 1.5.1 seems not even to be supported yet on GAE, neither is it clear to me how to use Django 1.4.3 on GAE.
I also found this more recent solution that utilizes Django and Google Cloud (Mysql on cloud) instead of the high replication datastore. Not sure if this is a good way to go since its still experimental and subject to "breaking changes" in future. (It also doesn't seem to include any free tier, unlike high replication datastore)
I was expecting Django - as perhaps the biggest python web frameworks - to have a far better documentation or tutorials about how to do deploy it on GAE. So I wonder if its even worth it sticking with Django on GAE anymore.
If I am meant to make manually my own models and adjust my queries in Views by utilizing ndb anyway, I could as well stick with flask+Jinja2, why should I use Django, where I can't even use it's ORM anymore? Or am I overlooking something?
Thanks,
There's nothing on the link to the allbuttonspressed blog that implies it is discontinued. On the contrary, the page says that even though they (as the original maintainers) are pulling out of the project, it has been taken over by a new maintainer. That's what often happens in open-source projects.
As for Cloud SQL, there is a dedicated page on the App Engine documentation which explains in detail how to get this up and running. The Cloud SQL API itself is, it's true, still in "experimental" status, but again that's just what Google does. App Engine itself only came out of "experimental" last year.
As for why you should stick with Django, that's up to you of course, but both of the above solutions will give you Django forms, the admin interface, templates, and URL routing, and some or all of the ORM syntax.
There's some work going on in maintaining django-nonrel, though the Allbuttonspressed blog is starting to get pretty out of date. You'll find more up-to-date info in the django-nonrel mailing list on Google Groups.
I believe it's been updated to at least Django 1.5, but I'm personally still running on 1.4. The documentation is extremely lacking. You'll have to figure out from the mailing list the appropriate branch to use to get support for the latest django version. However, it's there and it's working.
Django + CloudSQL will likely be the least-coding route to port your app to GAE.
Django-nonrel gets to take advantage of the HRD, however, many apps written expecting SQL behavior will need to be extensively rewritten to support the HRD behavior properly.
As an example, I've tried running django-registration on django-nonrel. On first look, it seems to work fine. But on deeper inspection, there's issues like being able to register the same email address to more than one user on HRD. You may find similar issues with other apps, or just the inability to run at all, given that the HRD doesn't support many-to-many relations, as well as slightly-more-complex queries.

How to migrate Django project to Google App Engine

I am looking for a guide to migrate Django project to Google App Engine and use Google's datastore. The most of the guides I found were linked to Django-Appengine using Django-nonrel (but I want to use GAE's native support).
Going through GAE getting started guide, it says:
Google App Engine supports any framework written in pure Python that speaks CGI (and any WSGI-compliant framework using a CGI adaptor), including Django, CherryPy, Pylons, web.py, and web2py. You can bundle a framework of your choosing with your application code by copying its code into your application directory.
I understand that I won't be able to use some features of Django in that case (majorly the admin feature) and would also need to restructure the models.
From other reading, I also found that latest SDK of GAE now includes Django 1.3 on Python 2.5.
I tried to put all files from my Django application to a GAE project, but couldn't get it all to work together.
Please provide some basic guide using which I may migrate my Django project to Google App Engine's code.
Thanks.
For an existing Django app, using django-nonrel is the simplest approach; it is very popular so you should be able to find help with specific errors you get quickly.
Another approach is written up in this article: http://code.google.com/appengine/articles/pure_django.html -- it goes the other way, taking an App Engine app that uses Django for dispatch, templates, and forms, but not for models, and describes how to make it run in a native Django environment. Maybe you can glean some useful hints for your situation from it.
I've used django-nonrel, which behaves pretty much like django, except that operations with JOINs will return errors. I've basically worked around this by avoiding ManyToMany fields, and essentially building that functionality manually with an intermediate table.
So far I've ran into two problems with Django-nonrel:
1. No access to ancestor queries, which can be run in a transaction. There's a pending pull request for this feature though.
2. You can't specify fields that are not indexed. This could significantly increase your write costs. I have an idea to fix this, but I haven't done so yet.
(Edit: You CAN specify fields that are not indexed, and I've verified this works well).
2 (new). Google is pushing a new database backend called ndb that does automatic caching and batching, which will not be available with django-nonrel.
If you decide not to use django-nonrel, the main differences are that Django models do not run under App Engine. You'll have to rewrite your models to inherit from App Engine's db.Model. Your forms that use Django's ModelForm will need to inherit from google.appengine.ext.db.djangoforms instead. Once you're on App Engine, you'd have to port back Django if you ever take your app somewher else.
If you already have a Django application you might want to check this out. You won't work with App Engine's datastore but Google Cloud SQL might fit your needs.

Django RESTful API - django-piston vs. django-tastypie

We're looking for a general RESTful API solution for our Django project. We would use the API at first for Ajax calls on the web site and later for mobile apps, external apps and things like that.
I found two modules which seem to be widely used. django-piston and django-tastypie
From what I read, piston seems to be older and thus more mature but maybe a bit outdated?!
While tastypie is relatively new and nicely documented.
What would be the best thing to go with? django-piston or django-tastypie?
Important for us (ordered by priority): Continuous maintenance of the source, documentation, stability, ease of use.
EDIT (2013 Jul 16th):
Now over a year later we have a clear winner. At first we went with tastypie. Which we kinda liked. But after half a year or so we switched to the then upcoming django-rest-framework and never looked back.
What we like most about it:
Nice documentation
Active community
Clean design (build upon django's class based views)
Browsable API for development and debugging
We rely on the API heavily so support (in the future) is one of our main concerns. We met the maintainer - Tom Christie - (on and offline) and he seems very committed to the project. So we feel very comfortable using the django-rest-framework.
A good resource to compare them is http://www.djangopackages.com/grids/g/api/
Django-tastypie sure is the save choice right now.
Personally I'd advocate a look at django-rest-framework if you use django 1.3, because it uses the new class based views. djangopackages.com's comparison page shows it has good participation and activity. And, wow, it sure has a nice browsable interface to the API.
I have no experience with this, but I trust Pydanny in this:
django-piston has been barely supported for nearly two years. That is
an eternity, and the number of forks to address multiple issues is a
cause for alarm. Because of that, in it's place at this time I
recommend django-tastypie. It is up-to-date, has very good
documentation, supports OAUTH, and scored second place in the Django
Packages thunderdome (it got nearly 3x as many points!). Another tool
to consider is Django Rest Framework, which is as good as
django-tastypie but lacks the OAUTH support.
On the django-piston front, Joshua Ginsberg has taken over the reins
and we should hopefully see some movement again. In which case I'll be
able to remove this section of the blog post.
from Pydanny's blog.
Having implemented API's with django Piston, tastypie and django webmachine Django tastypie rocks! Having said that, I think that while tastypie is really good when your API is modelled close to your models, it's a little bit more complicated to do things once you want to move out of the box. There are workarounds to some issues, with others you have to do more bending than building. It will, probably, still cover 90% of django use cases.
Afaik Webmachine was modelled after the popular erlang webmachine, but hasn't been very active lately. So that leaves piston, which is picking up some activity, and tastypie, that has a lot of momentum and activity. Piston is a bit more flexible, but tastypie is moving very fast and in my opinion has a really easy API.
My recommendation would be to quicky implement a prototype of the API in tastypie, and see if it covers what you want to do.
Django REST framework 2.0 was anounced in Oct 2012 and now supports OAuth out of the box. What I really like is the Web browseable API, which is really helpful when developing your API, but also when someone implements your API. It's kind of comparable with using the Django admin site for inspecting your models' structure and data, but then for your API. Also the documentation is very good.
From their website:
Django REST framework is a powerful and flexible toolkit that makes it
easy to build Web APIs.
Some reasons you might want to use REST framework:
The Web browseable API is a huge usability win for your developers.
Authentication policies including OAuth1a and OAuth2 out of the box.
Serialization that supports both ORM and non-ORM data sources.
Customizable all the way down - just use regular function-based views if you don't need the more powerful features.
Extensive documentation, and great community support.
Check out their Quickstart guide to get a quick idea of how it works.