Beating Google With CouchDB, Celery and Whoosh (Part 3) « Andrew Wilkinson. In this series I’ll show you how to build a search engine using standard Python tools like Django, Whoosh and CouchDB.
In this post we’ll start crawling the web and filling our database with the contents of pages. One of the rules we set down was to not request a page too often. If, by accident, we try to retrieve a page more than once a week then don’t want that request to actually make it to the internet. To help prevent this we’ll extend the Page class we created in the last post with a function called get_by_url. This static method will take a url and return the Page object that represents it, retrieving the page if we don’t already have a copy. We only actually want to retrieve the page from the internet in one of the three tasks the we’re going to create so we’ll give get_by_url a parameter, update that enables us to return None if we don’t have a copy of the page. The key line in the static method is doc.update(). Django MongoDB Engine. Estou testando o módulo Django MongoDB Engine, um backend para Django bastante completo.
O grande diferencial desse módulo é permitir uma integração total e transparente do Django com o MongoDB, inclusive trabalhando no models da mesma forma que em um banco relacional. Além disso, o módulo também permite utilizar GridFS, Map Reduce, Agregadores e Atomic Updates em apps do Django, mantendo total compatibilidade com Admin, Sessões e Autenticação padrão do Django. Como ainda não existe uma solução oficial para trabalhar com NoSQL no Django, esse módulo — até agora — é o mais completo e parece bastante estável. Ainda não instalei em aplicações em produção, mas ao realizar testes em laboratório, o módulo promete ter um grande potencial.
Instalação. [PostgreSQL] Obter locais próximos (fórmula de Haversine) « Blog do Bragil. Sabe aquele recurso que algumas redes sociais têm, de exibir os pontos próximos à sua localização? Build a simple GIS web application using GeoDjango and Google Maps — Tutorials v0.9.0 documentation. By the end of this tutorial you will have built a simple GIS web application for viewing, editing, searching and uploading GIS data.
We first presented this tutorial as part of a three-hour session on Working with Geographic Information Systems in Python during the 2009 Python Conference in Chicago, Illinois. This tutorial has been updated to work with Django 1.3. Example Make sure that the latest version of GeoDjango is installed; see Install GeoDjango. Django data visualization with graphviz. Overview Django data visualization with graphviz.
The django_graphviz django project provides 2 applications: graphviz: the main component, embeddable in any project testapp: a sample application Example The models of the testapp application: A typical diagram that may be generated: How to ? Commands Moreover, the_graphviz application provides the modelviz command that generates a dot file describing models. Django REST framework. App engine - django. Project Deprecated As of Nov 2010, this helper is no longer the recommended way to run Django projects on Google App Engine.
Please see the note at the top of for links to the recommended solutions. The project continues in maintenance mode only (bugfixes and patch merging only). Django on Google App Engine in 13 simple steps : Thomas Brox Røst. In this tutorial I will show you how to get a simple datastore-backed Django application up and running on the Google App Engine.
I will assume that you are somewhat familiar with Django. Update 1: You can download the full set of files from here. Django App Engine. Djangoappengine contains all App Engine backends for Django-nonrel, e.g. the database and email backends.
In addition we provide a testapp which contains minimal settings for running Django-nonrel on App Engine. Use it as a starting point if you want to use App Engine as your database for Django-nonrel. We've also published some details in the Django on App Engine blog post. Installation Make sure you've installed the App Engine SDK. Clone the following (on those pages you can also download a zip file): If you downloaded zip files then now's the time to unzip everything. Integrating Django with Nose at DISQUS by David Cramer. About a month ago we decided to make the transition off of Django’s test suite over to the Nose runners.
Our main selling point was the extensibility, and the existing ecosystem of plugins. Four weeks later I’m happy to say we’re running (basically) Nose with some minor extensions, and it’s working great. Getting Django running on Nose is no small feat. Luckily, someone else has already put in a lot of that effort, and packaged it up all nice and neat as django-nose. I won’t go through setting up the package, but it’s pretty straight forward. A few of the big highlights for us: Xunit integration (XML output of test results) Skipped and deprecated test hooks The ability to organize tests outside of the Django standards I’m wanted to talk a bit about how we solved some of our problems, and the other benefits we’ve seen since adopting it. Test Organization The biggest win for us was definitely being able to reorganize our test suite.
Unittest Compatibility Test Case Selection Bisecting Tests. Voando com o Django no Google App Engine.