MenuGen is a school project that solves an eternal issue : What are we going to eat tonight?

To solve this issue, MenuGen asks you a few questions about your morphology, your food tastes and allergies or diets, before generating well-balanced meals for the next week!

First, we setup MenuGen:

• Scrape recipes on the internet, storing the ingredients along with the steps to cook it
• Match the ingredients to OpenFoodFacts to evaluate the nutritional value of each recipe
• Store these in a PostGreSQL database and wait for users

Then, when you want to generate a meal:

• Create an account, entering basic morphological informations that let us calculate your Basal Metabolic Rate
• Match this calorie count to the WHO nutritional recommendations to derive your needs in proteins/carbs/fats
• Run a Genetical Algorithm that will iterate on potential menus based on your tastes and diet to optimize the nutritional value of your meals
• Display the result in a nice dashboard where you can remove dishes, reorder meals, print a shopping list, etc.

For now there is no hosted instance of MenuGen. If you want to run it on your machine, follow these steps:

Install the following packages: python3 python3-pip

Then run from the root of the project:

sudo pip install virtualenv
virtualenv -p python3 .venv
source .venv/bin/activate
pip install -r requirements.txt

To disable the python virtual environment, run deactivate

cd application 

Install Bower + Grunt:

npm install -g grunt-cli bower

Install Assets:

npm install && bower install

Compile Assets:

grunt

Initialize and configure the development database:

./manage.py makemigrations
./manage.py migrate

Create your super user:

./manage.py createsuperuser

First check if you're using the virtualenv. If not, run

source .venv/bin/activate

Then you can run the server with

./manage.py runserver

• project root - http://127.0.0.1:8000
• administration interface - http://127.0.0.1:8000/admin

When models are edited, you must compute the necessary migrations from your database state, then migrate with

./manage.py makemigrations
./manage.py migrate

Load initial data (so far the ingredients):

./manage.py loaddata initial_data

Note: initial_data is reloaded every migration

Create a fixture (snapshot from the data currently in the database):

./manage.py dumpdata > menus/fixtures/myfixture.json

Load a fixture:

./manage.py loaddata myfixture

Fill ingredients directly from the csv:

./manage.py fill_db