Initial commit: SejeteralO water tarification platform

Full-stack app for participatory water pricing using Bezier curves.
- Backend: FastAPI + SQLAlchemy + SQLite with JWT auth
- Frontend: Nuxt 4 + TypeScript with interactive SVG editor
- Math engine: cubic Bezier tarification with Cardano solver
- Admin: commune management, household import, vote monitoring, CMS
- Citizen: interactive curve editor, vote submission
- Docker-compose deployment ready

Includes fixes for:
- Impact table snake_case/camelCase property mismatch
- CMS content backend API + frontend editor (was stub)
- Admin route protection middleware
- Public content display on commune page
- Vote confirmation page link fix

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

backend/app/services/import_service.py

@@ -0,0 +1,143 @@
+"""Service for importing household data from CSV/XLSX files."""
+
+import io
+import secrets
+import string
+
+import pandas as pd
+from sqlalchemy.ext.asyncio import AsyncSession
+from sqlalchemy import select
+
+from app.models import Household
+
+# Characters without ambiguous ones (O/0/I/1/l)
+SAFE_CHARS = string.ascii_uppercase.replace("O", "").replace("I", "") + string.digits.replace("0", "").replace("1", "")
+
+
+def generate_auth_code(length: int = 8) -> str:
+    return "".join(secrets.choice(SAFE_CHARS) for _ in range(length))
+
+
+VALID_STATUSES = {"RS", "RP", "PRO"}
+REQUIRED_COLUMNS = {"identifier", "status", "volume_m3", "price_eur"}
+
+
+def parse_import_file(file_bytes: bytes, filename: str) -> tuple[pd.DataFrame | None, list[str]]:
+    """
+    Parse a CSV or XLSX file and validate its contents.
+
+    Returns (dataframe, errors). If errors is non-empty, dataframe may be None.
+    """
+    errors = []
+
+    try:
+        if filename.endswith(".csv"):
+            df = pd.read_csv(io.BytesIO(file_bytes))
+        elif filename.endswith((".xlsx", ".xls")):
+            df = pd.read_excel(io.BytesIO(file_bytes))
+        else:
+            return None, ["Format non supporté. Utilisez CSV ou XLSX."]
+    except Exception as e:
+        return None, [f"Erreur de lecture du fichier: {e}"]
+
+    # Normalize column names
+    df.columns = [c.strip().lower().replace(" ", "_") for c in df.columns]
+
+    missing = REQUIRED_COLUMNS - set(df.columns)
+    if missing:
+        return None, [f"Colonnes manquantes: {', '.join(missing)}"]
+
+    # Validate rows
+    for idx, row in df.iterrows():
+        line = idx + 2  # Excel line number (1-indexed + header)
+        status = str(row["status"]).strip().upper()
+        if status not in VALID_STATUSES:
+            errors.append(f"Ligne {line}: statut '{row['status']}' invalide (attendu: RS, RP, PRO)")
+
+        try:
+            vol = float(row["volume_m3"])
+            if vol < 0:
+                errors.append(f"Ligne {line}: volume négatif ({vol})")
+        except (ValueError, TypeError):
+            errors.append(f"Ligne {line}: volume invalide '{row['volume_m3']}'")
+
+        price = row.get("price_eur")
+        if pd.notna(price):
+            try:
+                p = float(price)
+                if p < 0:
+                    errors.append(f"Ligne {line}: prix négatif ({p})")
+            except (ValueError, TypeError):
+                errors.append(f"Ligne {line}: prix invalide '{price}'")
+
+    # Normalize
+    df["status"] = df["status"].str.strip().str.upper()
+    df["identifier"] = df["identifier"].astype(str).str.strip()
+
+    return df, errors
+
+
+async def import_households(
+    db: AsyncSession,
+    commune_id: int,
+    df: pd.DataFrame,
+) -> tuple[int, list[str]]:
+    """
+    Import validated households into the database.
+
+    Returns (created_count, errors).
+    """
+    created = 0
+    errors = []
+
+    # Get existing auth codes to avoid collisions
+    existing_codes = set()
+    result = await db.execute(select(Household.auth_code))
+    for row in result.scalars():
+        existing_codes.add(row)
+
+    for idx, row in df.iterrows():
+        identifier = str(row["identifier"]).strip()
+        status = str(row["status"]).strip().upper()
+        volume = float(row["volume_m3"])
+        price = float(row["price_eur"]) if pd.notna(row.get("price_eur")) else 0.0
+
+        # Check for duplicate
+        existing = await db.execute(
+            select(Household).where(
+                Household.commune_id == commune_id,
+                Household.identifier == identifier,
+            )
+        )
+        if existing.scalar_one_or_none():
+            errors.append(f"Foyer '{identifier}' existe déjà, ignoré.")
+            continue
+
+        # Generate unique auth code
+        code = generate_auth_code()
+        while code in existing_codes:
+            code = generate_auth_code()
+        existing_codes.add(code)
+
+        household = Household(
+            commune_id=commune_id,
+            identifier=identifier,
+            status=status,
+            volume_m3=volume,
+            price_paid_eur=price,
+            auth_code=code,
+        )
+        db.add(household)
+        created += 1
+
+    await db.commit()
+    return created, errors
+
+
+def generate_template_csv() -> bytes:
+    """Generate a template CSV file for household import."""
+    content = "identifier,status,volume_m3,price_eur\n"
+    content += "DUPONT Jean,RS,85.5,189.50\n"
+    content += "MARTIN Pierre,RP,120.0,245.00\n"
+    content += "SARL Boulangerie,PRO,350.0,\n"
+    return content.encode("utf-8")