import-camp-menus
GitHub将SGDF营地HTML页面转换为scout-menu食谱。流程包括解析HTML、拆分菜品、生成单人食材清单、匹配Agribalyse数据，并最终导入Supabase数据库。
Trigger Scenarios
Install
npx skills add NeverSight/learn-skills.dev --skill import-camp-menus -g -y
SKILL.md
Frontmatter
{
"name": "import-camp-menus",
"description": "Use when the user has new SGDF camp HTML files to import into scout-menu, or wants to re-run the menu extraction pipeline (parse HTML → split dishes → generate ingredients → import to Supabase)."
}
Import Camp Menus from SGDF HTML
Overview
Pipeline that turns saved SGDF camp pages (monprojet.sgdf.fr) into scout-menu recipes with per-person ingredient lists.
Prerequisites
# Python venv with dependencies (already committed)
uv venv scripts/.venv
uv pip install anthropic supabase python-dotenv --python scripts/.venv
# Required env vars in .env
ANTHROPIC_API_KEY=... # already set in shell
Pipeline Steps
1. Add HTML files
Place saved SGDF camp HTML pages (File → Save As in browser) into ideas/.
2. Parse HTML → JSON
# One file
scripts/.venv/bin/python scripts/parse_camp_html.py "ideas/Camp n°XXXXX - Mon Projet SGDF.html"
# All files → merge
mkdir -p scripts/output
for f in ideas/*.html; do
name=$(basename "$f" ".html")
scripts/.venv/bin/python scripts/parse_camp_html.py "$f" > "scripts/output/${name}.json" 2>/dev/null
done
# Merge into raw_menus.json (skip empty/errored files)
python3 -c "
import json, glob
camps = []
for f in sorted(glob.glob('scripts/output/Camp*.json')):
try:
d = json.load(open(f))
if d.get('days'): camps.append(d)
except: pass
json.dump(camps, open('scripts/output/raw_menus.json','w'), ensure_ascii=False, indent=2)
print(f'{len(camps)} camps')
"
Output: scripts/output/raw_menus.json
2.5. Seed Agribalyse foods table (run once, idempotent)
Reads scripts/data/agribalyse_food_products.xlsx (download from dataverse ID 641911 if missing):
curl -L -o scripts/data/agribalyse_food_products.xlsx \
"https://entrepot.recherche.data.gouv.fr/api/access/datafile/641911"
Then generate and import the seed SQL:
scripts/.venv/bin/python scripts/seed_agribalyse.py
# → scripts/output/seed_agribalyse.sql
Paste into the Supabase SQL editor. Uses ON CONFLICT DO NOTHING — safe to re-run.
3. Split meal descriptions into dishes
Uses Claude Sonnet. Deduplicates across all camps.
scripts/.venv/bin/python scripts/split_dishes.py
Output: scripts/output/unique_dishes.json
4. Generate ingredients per dish
Uses Claude Haiku in parallel (10 workers). Quantities are for 1 person.
scripts/.venv/bin/python scripts/generate_ingredients.py
Output: scripts/output/dishes_with_ingredients.json
3.5. Match ingredients to Agribalyse entries
Uses Claude Haiku (batches of 20) to match each unique ingredient name to the closest Agribalyse food. Reads dishes_with_ingredients.json and the Agribalyse XLSX.
scripts/.venv/bin/python scripts/match_agribalyse.py
# → scripts/output/ingredient_agribalyse_map.json
~94% match rate. null entries mean no reasonable Agribalyse match found.
5. Generate SQL and import to Supabase
Generates a SQL script that inserts is_default=true menus. Idempotent (skips existing dishes by name).
scripts/.venv/bin/python scripts/generate_sql.py
# → scripts/output/import_menus.sql
Name the output file with an incrementing suffix before committing (e.g. import_menus_2.sql, import_menus_3.sql) so each batch is traceable.
Paste the contents into the Supabase SQL editor: https://supabase.com/dashboard/project/yjbrzyjdapvfaknjltxm/sql/new
The final SELECT COUNT(*) at the end confirms how many default menus exist after the import.
Previously imported batches
| File | Dishes | Agribalyse | Date |
|---|---|---|---|
scripts/output/import_menus_1.sql |
165 | no | 2026-04-30 |
scripts/output/import_menus_2.sql |
165 | yes (377/402 ingredients linked) | 2026-04-30 |
Agribalyse seed batches
| File | Rows | Date |
|---|---|---|
scripts/output/seed_agribalyse_1.sql |
2458 | 2026-04-30 |
Notes
- Camps with no menus filled in (empty Menus tab) are silently skipped by the parser.
- Descriptions that are activity names (
concours cuisine,cocu goûter,X,N.A) produce 0 ingredients — expected. - The Haiku model sometimes wraps JSON in
```json ```fences — the script strips them automatically. - Re-running import is safe: existing dishes (matched by name, case-insensitive) are skipped.
Output File Locations
| File | Contents |
|---|---|
scripts/output/raw_menus.json |
All camps → days → meals with raw descriptions |
scripts/output/unique_dishes.json |
Deduplicated dish names with source descriptions |
scripts/output/dishes_with_ingredients.json |
Final: dishes + per-person ingredients |
scripts/output/ingredient_agribalyse_map.json |
Ingredient name → Agribalyse food name (or null) |
scripts/output/seed_agribalyse.sql |
Latest Agribalyse seed SQL (version with suffix before committing) |
scripts/data/agribalyse_food_products.xlsx |
Agribalyse 3.2 XLSX (not committed, download from dataverse) |
Version History
- e0220ca Current 2026-07-05 23:31
