Installation
The simplest way to install the latest release is as follows:
pip install pyfdc
To install the development version:
Open the Terminal/CMD/Git bash/shell and enter
pip install git+https://github.com/Nelson-Gon/pyfdc.git
# or for the less stable dev version
pip install git+https://github.com/Nelson-Gon/pyfdc.git@develop
Otherwise:
# clone the repo
git clone [email protected]:Nelson-Gon/pyfdc.git
cd pyfdc
python3 -m pip install .
Sample usage
There are two ways to use pydfc. In script mode, one does the following:
python -m pyfdc --method "info" --phrase "cheese" | head
#/pyfdc/pyfdc/pyfdc.py:109: UserWarning: No target_fields were provided, returning fdc_id, ingredients, and description.
# warn("No target_fields were provided, returning fdc_id, ingredients, and description.")
# fdc_id ... description
#0 816524 ... CHEESE
#1 1463368 ... CHEESE
#2 1597534 ... CHEESE
#3 1653804 ... CHEESE
#4 1660793 ... CHEESE
#5 1497465 ... CHEESE
#6 1465399 ... CHEESE
#7 515803 ... CHEESE
#8 500370 ... CHEESE
#
The above uses the get_food_info method. To use, the get_food_details method, one simply sets method to "details"
and provides the target FoodDataCentral ID.
python -m pyfdc --method "details" --phrase 816524 --fields "nutrients"
# id number name rank unitName
#0 1004 204 Total lipid (fat) 800 g
#1 1257 605 Fatty acids, total trans 15400 g
#2 1079 291 Fiber, total dietary 1200 g
#3 1003 203 Protein 600 g
#4 1005 205 Carbohydrate, by difference 1110 g
#5 1110 324 Vitamin D (D2 + D3), International Units 8650 IU
#6 1008 208 Energy 300 kcal
#7 2000 269 Sugars, total including NLEA 1510 g
#8 1089 303 Iron, Fe 5400 mg
#9 1087 301 Calcium, Ca 5300 mg
#10 1258 606 Fatty acids, total saturated 9700 g
#11 1093 307 Sodium, Na 5800 mg
#12 1253 601 Cholesterol 15700 mg
from pyfdc.pyfdc import FoodDataCentral
from pyfdc.utils import set_api_keySet session api key
To avoid providing an api key for each call, one can set a session api key as follows:
set_api_key("my_api_key_here")
Key Features
There is one major class FoodDataCentral.
See the changelog
for more details.:
To instantiate an object:
my_search = FoodDataCentral()To get details about foods for a given search term, one can do the following:
my_search.get_food_info(search_phrase="cheese").head(6)The above will result in the following output:
#
#UserWarning: No target_fields were provided, returning fdc_id, ingredients, and description.
# fdc_id ingredients description
#0 816524 BELLAVITANO CHEESE (PASTEURIZED MILK, CHEESE C... CHEESE
#1 1210322 BELLAVITANO CHEESE (PASTEURIZED MILK, CHEESE C... CHEESE
#2 1291586 CHEDDAR CHEESE (PASTEURIZED MILK, CHEESE CULTU... CHEESE
#3 1305389 PASTEURIZED COWS' MILK, SALT, CULTURES, ENZYMES. CHEESE
#4 1361608 CULTURED PASTEURIZED MILK, SALT, NON-ANIMAL EN... CHEESE
#5 1420013 FRESH PART-SKIM COW'S MILK, CHEESE CULTURE SAL... CHEESE
In the above, we got a warning message because we used defaults out-of-the-box. To customize, we can set
the target_fields we wish to have.
my_search.get_food_info(search_phrase="cheese", target_fields=["description"]).head(4)
# description
# 0 CHEESE
# 1 CHEESE
# 2 CHEESE
# 3 CHEESETo get full details about a given fdcId, one can do the following:
my_search.get_food_details(168977)
This will give us the following output(truncated):
# UserWarning: No target_field was provided, returning low level results.
# 0 1
#0 fdcId 168977
#1 description Agutuk, meat-caribou (Alaskan ice cream) (Alas...
#2 publicationDate 4/1/2019
#3 foodNutrients [{'nutrient': {'id': 2045, 'number': '951', 'n...
#4 dataType SR Legacy
The above is a low-level result that may be useful for development purpises.
To get nutrient details:
my_search.get_food_details(fdc_id= 496446,target_field="nutrients")
# nutrient.id nutrient.unitName nutrient.name \
#0 1089 mg Iron, Fe
#1 1258 g Fatty acids, total saturated
#2 1253 mg Cholesterol
#3 1162 mg Vitamin C, total ascorbic acid
#4 1087 mg Calcium, Ca
#5 1104 IU Vitamin A, IU
# foodNutrientDerivation.description id amount \
#0 Calculated from a daily value percentage per s... 3992103 3.39
#1 Calculated from a daily value percentage per s... 3992107 0.47
#2 Calculated from a daily value percentage per s... 3992106 0.00
#3 Calculated from a daily value percentage per s... 3992105 0.00
#4 Calculated from a daily value percentage per s... 3992102 118.00
#5 Calculated from a daily value percentage per s... 3992104 0.00
# nutrient.number nutrient.rank
#0 303 5400
#1 606 9700
#2 601 15700
#3 401 6300
One can also get label nutrients (if they exist):
my_search.get_food_details(504905, target_field="label_nutrients")
# fat saturatedFat transFat cholesterol sodium ... calcium iron potassium addedSugar calories
#0 15.0 4.5 0.0 84.5 1060.0 ... 80.6 1.08 70.2 1.04 179
#[1 rows x 14 columns]Credit
- Original Food Data Central API
The API interfaced is available here
Thank you very much.
To report any issues, suggestions or improvement, please do so at issues.
“Before software can be reusable it first has to be usable.” – Ralph Johnson
If you would like to cite this work, please use:
Nelson Gonzabato(2020) pyfdc: A python interface to FoodDataCentral, https://github.com/Nelson-Gon/pyfdc
BibTex:
@misc{Gonzabato2021,
author = {Gonzabato, N},
title = {pyfdc: A python interface to FoodDataCentral},
year = {2021},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/Nelson-Gon/pyfdc}},
commit = {20923d9dbea9dcf1b5cba741625b01f6637a6d7b}
}