Online food ordering system

Group project for DBMS lab course in IIT Kharagpur
The data for reviews, food items and restaurants was taken from an open source dataset : http://menus.nypl.org/data We used collaborative filtering for recomendation system from the following project : https://github.com/ocelma/python-recsys

Contributors

1. Apurv Kumar
2. Aniket Choudhary
3. Asket Agarwal
4. Rameshwar Bhaskaran
5. Shubham Sharma

You can check out our website : http://fastfood.pythonanywhere.com/

Requirements

First create a virtual environment and activate it.
Now , write the following two commands (required for recommendation system)

$ pip install scipy  	
$ pip install numpy  	
$ pip install csc-pysparse networkx divisi2  

We used the following project for the recommendation system which uses collaborative filtering :
https://github.com/ocelma/python-recsys

Now clone the above repository

$ git clone https://github.com/ocelma/python-recsys.git  

And run the setup.py to install it

	$ cd python-recsys  
	$ python setup.py install  

Install all other dependencies using :

$ pip install -r requirements.txt  

Usage

To prepare your database and recommendation system :
In your fastFood directory type the following, make sure the virtual environment is running

	$ python manage.py migrate  
	$ python manage.py loaddata usr.json  
	$ python manage.py loaddata res.json  
	$ python manage.py loaddata menu.json  
	$ python manage.py loaddata revi.json  
	$ python manage.py loaddata history.json  
	$ python script1.py   

Now, finally to run the webserver type :

$ python manage.py runserver   

and go to 127.0.0.1:8000 using preferably chrome browser