Final UCOSP Gin update for the Fall term!

These last weeks have found our team putting together the front and backend components of the Gin prototype. Our efforts have centred on establishing a single repository on Github, currently administered by Michelle, where Vincent and Leemor’s frontend code has been integrated. We now have a platform for future developers to start from.
For a future UCOSP team getting started with this project I would recommend establishing a work flow with github as soon as possible. We have found that an effective model involves using a single repository to avoid drift between team member’s work that can grow into headaches when it comes time to merge code. A live voice or text chat open across team members during planned work sessions is also valuable in addition to weekly meetings and an actively used mailing list.
Hosting on a public repository such as Github will be essential as this project matures into a proper open source endeavour. Remember that this project is designed to be adopted by anybody; it is vital that all work be maintained in one public location.
To get started should be a matter of installing Django and cloning the Gin repository. Keep in mind that we have not been publishing all essential files for a complete Django project! The most glaring omissions to resolve before running the server from the repo will be settings.py and manage.py (For a complete list view the .gitignore file.) The best way to generate these is to create a new Django project and copy over what’s missing as a template.
You will also need a database, which we do not include on github. These can be initialized from the project’s schema using django’s built-in utilities. I recommend creating a seed file to distribute among the team for the sake of testing or demonstrating features. There is a shell script in the github repo to assist with this.
Some other tools we have found useful are ArgoUML and Balsamique to share visualizations of project goals. A UML diagram for the backend API, for example, is a lifesaver. Above all, I highly recommend working through a Git and Django tutorial:
http://progit.org/book/

Welcome

A solid platform on which a range of data collection and retrieval strategies remains open will continue to inspire contributors as this project matures. Following VC news aggregators is a great source of inspiration for social media analysis because many startups and social media ventures tend to encounter similar issues we have with planning ahead for scale (cf. http://www.slideshare.net/dibau_naum_h/large-scale-processing-with-django) and deciding on which database technologies are best suited for our purpose. This recent blog post discusses using Google chrome’s open source n-gram model based language detection feature, with python bindings: http://blog.mikemccandless.com/2011/10/language-detection-with-googles-compact.html and don’t forget to follow Google’s chart API (http://code.google.com/apis/chart/interactive/docs/more_charts.html) to remember what interesting visualizations can be integrated with your working Gin dataset with some careful planning.
Good luck!

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