1. The ability to look at food truck options within .5 miles, 1 mile, 5 miles, etc. from exactly where I currently am.
2. The ability to procure a list of food trucks that serve the type of food that I want to eat right now. For example, today, I want tacos.

**Django REST Framework** for the service design. It scaffolds with boilerplate code and allows me to focus on important logic. I also chose it because it is written in Python and because it has a well-developed community of users.
**Heroku** for hosting. Django/Python is one of the main infrastructures/languages that it supports.
**SQLite** for development database. Queries are very fast and appropriate for development.
**PostgreSQL** for production database. This is provided for free by Heroku.

**name** CHAR from *Applicant* field
**address** CHAR from *Address* field
**fooditems** CHAR from *FoodItems* field
**longitude** DECIMAL from *Longitude* field
**latitude** DECIMAL from *Latitude* field
**foodtypes** MANYTOMANY foreign key into FoodTypes objects

**food** INTEGER choices

**quickstart/models.py**
Holds the FoodTrucks and FoodTypes model. Represents the schema of the database as well.

**quickstart/management/commands/populate.py**
Used to populate initial data in the databases using a json-loadable text file. I used DataSF's FoodTrucks endpoint. I only processed records where the facilities had 'APPROVED' permit statuses. There were a lot of duplicate food trucks but I kept them anyway since some do seem to have different addresses and coordinates.

Usage: python manage.py populate datasf.json


**quickstart/serializers.py**
Determines which FoodTrucks and FoodTypes fields are served when queried. 


**quickstart/tests.py**
Unit tests, written to test Views and Models which have custom functions in them.


**quickstart/views.py**
Determines the queryset that is returned for FoodTrucks and FoodTypes upon request.

FoodTrucksSerializer supports url query parameters to filter FoodTrucks based on longitude, latitude, and distance. For example, if given
https://desolate-eyrie-6590.herokuapp.com/foodtrucks?longitude=-122.394594036205000000000000000000&latitude=37.787900097818100000000000000000&distance=2
the results returned will be filtered so that food trucks fall within 2 miles north, south, east, and west. Results are essentially bounded by a square. I decided to use LatLon Python Package to do geocoordinate math, since it can be used to calculate distance between points as well as determine a destination point based on an origin, trajectory and distance.


**tutorial/urls.py**
Binds URI to the views.

1. Ability to search FoodTrucks for any keywords in the fooditems key
2. Front-end using bootstrap and AngularJS. I chose to keep the DEBUG option in the settings file on, so we have a minimal interface. As a result HTTP error codes are being replaced with run time errors instead.
3. Implement some machine learning to  determine FoodType based off of the fooditems key, rather than using pre-determined FoodTypes.
4. Support filtering FoodTrucks by circular radius instead of box radius.