apps4nsw
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资源说明:Apps For NSW hack day
Is Bondi Full Of Poodles?
=========================

Introduction
------------

This project was done (poorly) as part of the Apps4NSW hack day on
Saturday 19 Feb 2011. It aggregates data on domestic animals from
the NSW state government with public information from numerous other
sources, including wikipedia, and renders it all on a rather fetching
google map.

The project team included:

* Diana Mounter
* Chris Oates
* Dylan Jay
* Bo Daley

Installation
------------

We assume you already have working python, virtualenv and pip.

To install a dev instance of IBFOP, follow these steps::

  mkdir apps4nsw
  virtualenv apps4nsw
  cd apps4nsw
  git clone git@github.com:bodico/apps4nsw.git
  source bin/activate
  cd apps4nsw
  pip install -r requirements.txt


Start dev server
----------------

To run a development server on your local instance::

  cd project/
  ./manage.py runserver

You should then see the site running at http://127.0.0.1:8000


pyCharm config
--------------

If you're using pyCharm (or some other fancy IDE) then you need to 
configure it to refer to the python binary in your virtualenv.

i.e. Preferences > Python Interpreter

* remove any interpreter pyCharm found by itself
* add /YOURWORKSPACE/apps4nsw/bin/python

then click 'Apply'

Go to 'Django Support' and 'Enable Django Support'.

* set Django project root as /YOURWORKSPACE/apps4nsw/apps4nsw/project

pyCharm should now find settings.py and manage.py.

Add /YOURWORKSPACE/apps4nsw/apps4nsw/templates as a templates directory.

then click 'Apply'


Create site database
--------------------

Create the db::

  cd project/
  ./manage.py syncdb
  ./manage.py migrate


Load in data
------------

If you want to get off the ground quickly, simply load the pets data
fixtures::

  ./manage.py loaddata pets/fixtures/pets.json

Or if you need to recreate the data from scratch, run these scripts in
sequence::

  ./manage.py geocode_postcodes
  ./manage.py load_dogs_by_suburb
  ./manage.py flatten_postcodes
  ./manage.py aggregate_totals


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