fuyuxiang Fitness & Nutrition
Exercise database and food nutrition lookup via free public APIs.
Exercise Search (wger API — free, no key)
# Search exercises
curl -s "https://wger.de/api/v2/exercise/search/?term=squat&language=english&format=json"
# List muscle groups
curl -s "https://wger.de/api/v2/muscle/?format=json" | python3 -c "
import sys,json; [print(f\"{m['id']}: {m['name_en']}\") for m in json.load(sys.stdin)['results']]"
# Exercises for specific muscle (e.g. chest=4)
curl -s "https://wger.de/api/v2/exercise/?muscles=4&language=2&format=json"
Muscle Groups
| ID | English | 中文 |
|---|---|---|
| 1 | Biceps | 肱二头肌 |
| 2 | Shoulders | 肩部 |
| 4 | Chest | 胸部 |
| 9 | Legs | 腿部 |
| 10 | Abs/Core | 核心/腹肌 |
| 12 | Back | 背部 |
| 5 | Triceps | 肱三头肌 |
Nutrition Lookup (USDA FoodData Central)
# Search food (free, DEMO_KEY works)
curl -s "https://api.nal.usda.gov/fdc/v1/foods/search?query=chicken+breast&pageSize=3&api_key=DEMO_KEY" | \
python3 -c "import sys,json; [print(f\"{f['description']}: {[n for n in f.get('foodNutrients',[]) if 'Energy' in n.get('nutrientName','')]}\") for f in json.load(sys.stdin)['foods']]"
Calculators
# BMI
bmi = weight_kg / (height_m ** 2)
# Categories: <18.5 underweight, 18.5-24.9 normal, 25-29.9 overweight, 30+ obese
# TDEE (Harris-Benedict)
bmr_male = 88.362 + (13.397 * weight_kg) + (4.799 * height_cm) - (5.677 * age)
bmr_female = 447.593 + (9.247 * weight_kg) + (3.098 * height_cm) - (4.330 * age)
# Activity multiplier: sedentary 1.2, light 1.375, moderate 1.55, active 1.725
Script
python3 scripts/health_query.py exercise "push up"
python3 scripts/health_query.py exercise-detail 123
python3 scripts/health_query.py food "鸡胸肉"
python3 scripts/health_query.py bmi 75 1.78