#FCI

This is a python project to create an application that calculates a London area's Fried Chicken Index (FCI). The FCI is calculated based on instances of fried chicken shops in the area. The front-end of this app is done with flask and can be found in the khaleesicode repo

Installation with Anaconda

1. Install Anaconda

Follow instructions at http://docs.continuum.io/anaconda/install

2. Create your virtual environment with Conda

http://uoa-eresearch.github.io/eresearch-cookbook/recipe/2014/11/20/conda/

3. Clone this repository

Open your terminal, navigate to the directory where you want to save this project and execute:git clone https://github.com/ciacicode/fci.git

4. Install requirements

Activate your virtual environment, make sure you are in the fci folder and then execute from the terminal pip install -r requirements.txt This command tells pip to install recursively all the rows of the file requirements.txt which includes packages I use for my environment.

Running

While your environment is active, you can populate all databases with the necessary information with only one function. This is a lengthy process so leave the computer connected for a while (up to 1 hour) while the function executes. In your terminal now activate the python interpreter of your virtual environment: (myenv)user@mylinuxmachine:~ /MyPath/to/the/project$ python Then within your interpreter:

    >>>  from db_models import *
    >>>  fci_set_up()

Now let the function run. When the process is over you can query the value of teh fried chicken index for your London postcode as

    >>> fci_return("<london_postcode>")

Notes

This works only for London and Greater Londona areas