rdflib è una libreria python che fornisce una base di dati con vari back-end per le triple, dei parser, serializzatori, SPARQL è un'interfaccia in python per estrarre/inserire le triple. L'abbiamo integrata con Django tramite il riutilizzo della connessione alla base di dati fornendo un'interfaccia ORM e la capacità di fare ricerca full-text sui valori letterali. La presentazione contiene un studio di caso per django-rdflib con un back-end postgresql in Brain Architecture Management System (http://brancusi1.usc.edu) - un progetto neuroscientifico per University of Southern California. Si vedranno i benefici della struttura flessibile del RDF che permette ai ricercatori di introdurre dati in formatto libero, rendere i dati pubblici con una serializzazione personalizzata e usare la potente ricerca full-text fornita da postgresql.
Scopo: introdurre al pubblico una combinazione di RDF, la ricerca full-text di postgresql e l'ORM di Django tramite django-rdflib.
Requisiti: familiarità con Django.
Mobile apps are the hot item of the day -- and the best mobile apps are backed by a great website. Python web developer Nate Aune and iPhone developer Anna Callahan will show you how we built a simple music web app in Django with a native iPhone app that communicates with it. Attendees of this talk will see a concrete case study of building an application that exposes an API for mobile devices.
Our web app exposes a JSON API for sending and receiving data from the mobile device. We’ll talk about why we chose Django and the TastyPie API package, and discuss other Python-based frameworks that could be used to build the API such as Pyramid, Flask and Bottle. We’ll also compare REST and custom APIs to understand best practices for building APIs designed for mobile devices.
In this talk I'll describe our successful experience in introducing Python
into a system for blood collection tube labeling in laboratory and hospital
environments, based on IHE Technical Frameworks –the industry standard
for modeling and streamlining healthcare processes– and designed to avoid
human errors and ensure process traceability.
During the talk I will explain why we chose Python in the first place,
how we've been able to leverage the language's features and
characteristics for our specific field and what problems and limitations
I will show specific instances -showing code examples too– of Python
usage in different parts of the project, including a low-level driver
for laboratory automation machinery, an asynchronous messaging module,
the implementation of IHE-compliant actors and the inevitable end-user
web application, implemented with Django.
Using Python greatly helped us in building our system, allowing
very rapid prototyping cycles for both hardware and software, but during
the talk I'll also point out what we found was missing, and what
would be nice to have to ensure Python has its proper place as a viable
platform for designing streamlined healthcare workflows
based on established international standards.
20th–26th June 2011