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14a7484 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 | """Build a per-100g macro lookup table from USDA FoodData Central.
Set FDC_API_KEY before running:
$env:FDC_API_KEY = "your-api-key"
Example:
python scripts/build_usda_macros.py
"""
from __future__ import annotations
import argparse
import csv
import os
import sys
from pathlib import Path
SCRIPT_DIR = Path(__file__).resolve().parent
if str(SCRIPT_DIR) not in sys.path:
sys.path.insert(0, str(SCRIPT_DIR))
from usda_fdc_client import FdcClient, extract_macros
PROJECT_ROOT = Path(__file__).resolve().parents[1]
DEFAULT_QUERIES = PROJECT_ROOT / "data" / "nutrition" / "usda_queries.csv"
DEFAULT_OUTPUT = PROJECT_ROOT / "data" / "nutrition" / "macros_per_100g.csv"
DEFAULT_CACHE = PROJECT_ROOT / "data" / "nutrition" / "fdc_cache.json"
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--queries", type=Path, default=DEFAULT_QUERIES)
parser.add_argument("--output", type=Path, default=DEFAULT_OUTPUT)
parser.add_argument("--cache", type=Path, default=DEFAULT_CACHE)
parser.add_argument("--api-key", default=os.getenv("FDC_API_KEY"))
parser.add_argument("--data-type", default="Foundation,SR Legacy,FNDDS")
return parser.parse_args()
def read_queries(path: Path) -> list[dict[str, str]]:
with path.open(newline="", encoding="utf-8") as f:
return list(csv.DictReader(f))
def main() -> None:
args = parse_args()
if not args.api_key:
raise SystemExit("Missing USDA API key. Set FDC_API_KEY or pass --api-key.")
rows = read_queries(args.queries)
client = FdcClient(
api_key=args.api_key,
cache_path=args.cache,
data_type=args.data_type,
)
output_rows = []
for row in rows:
class_name = row["class_name"]
query = row["fdc_query"]
food = client.search_first(query)
macros = extract_macros(food)
output_rows.append(
{
"class_name": class_name,
"fdc_query": query,
"fdc_id": food.get("fdcId") if food else "",
"fdc_description": food.get("description") if food else "",
**macros,
}
)
args.output.parent.mkdir(parents=True, exist_ok=True)
with args.output.open("w", newline="", encoding="utf-8") as f:
fieldnames = ["class_name", "fdc_query", "fdc_id", "fdc_description", "kcal", "protein", "fat", "carbs"]
writer = csv.DictWriter(f, fieldnames=fieldnames)
writer.writeheader()
writer.writerows(output_rows)
client.save_cache()
print(f"Wrote macro table: {args.output}")
print(f"Wrote USDA cache: {args.cache}")
if __name__ == "__main__":
main()
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