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https://github.com/kurtamohler/foodypy
Food nutrition library with array operations
https://github.com/kurtamohler/foodypy
Last synced: 20 days ago
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Food nutrition library with array operations
- Host: GitHub
- URL: https://github.com/kurtamohler/foodypy
- Owner: kurtamohler
- Created: 2023-05-13T20:06:39.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2023-06-02T19:06:05.000Z (over 1 year ago)
- Last Synced: 2024-12-15T09:10:32.655Z (about 1 month ago)
- Language: Python
- Size: 34.2 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 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](https://fdc.nal.usda.gov/) 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](https://docs.conda.io/projects/conda/en/latest/user-guide/install/index.html)
Run the following to create and activate an environment with all dependencies.
```bash
conda env create -f environment.yaml -n foodypy && conda activate foodypy
```
Install FoodyPy.
```bash
pip install .
```
Install the FoodyPy database. The database is installed to `~/.foodypy`, and
it takes up about 1 MB.
```bash
python -c 'import foodypy; foodypy.install_database()'
```
Build FoodyPy docs.
```bash
python setup.py build_sphinx
```
## Basic usage
### Search for foods
You can search for foods by name, like so:
```python
>>> 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:
```python
>>> 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:
```python
>>> 150 * foodypy.get('Peas, green, raw')
Nutrients(fat=0.6, carbs=21.6, protein=8.129999999999999, calories=124.32000000000001)
```