FoodyPy

Food nutrition library with array operations

FoodyPy makes diet tracking easy. It provides a simple interface to search for foods in USDA's FoodData Central database.

Nutrition results are like numerical arrays, so they can be operated upon with array arithmetic. This makes it easy to calculate how much of each nutrient you've eaten, given a list of foods and the amounts of each, by weight.

Build FoodyPy from source

Install Miniconda: instructions

Run the following to create and activate an environment with all dependencies.

conda env create -f environment.yaml -n foodypy && conda activate foodypy

Install FoodyPy.

pip install .

Install the FoodyPy database. The database is installed to ~/.foodypy, and it takes up about 1 MB.

python -c 'import foodypy; foodypy.install_database()'

Build FoodyPy docs.

python setup.py build_sphinx

Basic usage

Search for foods

You can search for foods by name, like so:

>>> import foodypy
>>> foodypy.search('peas', limit=10)
[('Cowpeas, leafy tips, raw', 90),
 ('Babyfood, peas and brown rice', 90),
 ('Peas, edible-podded, raw', 90),
 ('Pigeonpeas, immature seeds, raw', 90),
 ('Peas, green, raw', 90),
 ('Babyfood, peas, dices, toddler', 90),
 ('SMART SOUP, Moroccan Chick Pea', 77),
 ('Ice creams, vanilla, light', 68),
 ('Ice creams, vanilla, rich', 68),
 ('Ice creams, vanilla', 68)]

The results are sorted by a search relevance score.

Get food nutrition

You can obtain the nutrition of a food with it's exact name from the search results, like so:

>>> foodypy.get('Peas, green, raw')
Nutrients(fat=0.004, carbs=0.14400000000000002, protein=0.0542, calories=0.8288000000000001)

The nutrient results from foodypy.get give the nutrients for 1 gram of the food. So if you want to know the nutrients in 150 grams of peas, for instance, you can just multiply the result by 150:

>>> 150 * foodypy.get('Peas, green, raw')
Nutrients(fat=0.6, carbs=21.6, protein=8.129999999999999, calories=124.32000000000001)