The 311 Dashboard helps you visualize and analyze 311 service request data. It is powered by the Open311 API.

The following instructions are known to work on a machine running Ubuntu 11.10 (Oneiric).

Let's create a PostGIS-enabled database and import San Francisco's neighborhood data.

1. sudo apt-get update
2. sudo apt-get install binutils gdal-bin libproj-dev postgresql-9.1-postgis postgresql-server-dev-9.1 python-psycopg2
3. You will also need pip if you don't have it:
   • sudo apt-get install python-pip
   • sudo pip install --upgrade pip
4. Install Flask with:
   • sudo pip install Flask
5. If you want to use Memcached with this application:
   • sudo apt-get install memcached
   • sudo pip install python-memcached

1. sudo vim /etc/postgresql/9.1/main/pg_hba.conf
2. Change lines 85, 90, 92, 94: first two methods were "peer", last two were "md5", changes both to "trust"
3. sudo /etc/init.d/postgresql restart

1. sudo -u postgres createuser sf_311
2. In the postgres database: ALTER user sf_311 WITH password 'CHOOSE_PASSWORD';

1. sudo -u postgres createdb -O sf_311 -E utf8 sf_311 (Create a database called sf_311 with owner sf_311)

1. psql -U sf_311 -d sf_311 -f /usr/share/postgresql/9.1/contrib/postgis-1.5/postgis.sql
2. psql -U sf_311 -d sf_311 -f /usr/share/postgresql/9.1/contrib/postgis-1.5/spatial_ref_sys.sql

1. Download the neighborhood shapes from San Francisco here:

   http://apps.sfgov.org/datafiles/view.php?file=sfgis/planning_neighborhoods.zip

2. Unzip planning_neighborhoods.zip.

0. ogrinfo -so planning_neighborhoods.shp
1. ogr2ogr -f 'ESRI Shapefile' -t_srs EPSG:4326 planning_neighborhoods_4326.shp planning_neighborhoods.shp

1. shp2pgsql -dID -g geom -s 4326 -W latin1 planning_neighborhoods_4326.shp pn_geoms | psql -U sf_311

Note: The neighborhoods should already be indexed. This is how you would index the geometries: CREATE INDEX pn_geoms_gist ON pn_geoms USING GIST (geom);

Now we're ready to create a table for all of our 311 request data and populate the table.

1. Run the db_setup shell script: sh db_setup.sh

1. Edit the db_config_sample.json to reflect the host, user, password, and database name of your setup
2. Initially, try to get the last two week's worth of data with the update_postgres_sf.py script. If today's date is August 1st, 2013, run python update_postgres_sf.py -e 2013-08-01 -n 14
3. Remember that you can use this same script to update the data in the future.

1. You can find the core of the application, dashboard.py, in the app directory. Once you're in the app directory, simply type sudo python dashboard.py --port 80

   If you want to run the application on port 5000, you can type python dashboard.py --port 5000