fix: test isolation + auth import compatibility + add optuna to requirements (HRT-136)

Test isolation fixes:
- auth_db.get_db(): read TURF_SAAS_DB dynamically (not frozen at import)
- api_v1/utils.get_db(): read TURF_SAAS_DB dynamically (not frozen at import)
- api_tokens_db.get_db(): read TURF_SAAS_DB dynamically (not frozen at import)
- tests/test_history.py: enforce _tmp_db.name + call init_auth_tables() in fixtures
- tests/test_user_tokens.py: enforce _tmp_db.name + call migrate_api_tokens_tables() in app fixture

Auth compatibility fixes:
- api_v1/routes/history.py: use auth.jwt_required_middleware (flask_jwt_extended)
  with saas_auth fallback for portal_server context
- api_v1/routes/ml_feedback.py: same auth import strategy
- api_v1/routes/user.py: same auth import strategy

Dependencies:
- requirements.txt: add optuna>=4.0.0 (used in ML ensemble tests and training)

Co-Authored-By: Paperclip <noreply@paperclip.ing>

DOCUMENTATION.md

@@ -155,3 +155,284 @@ python app.py
 ---
 
 *Document généré automatiquement - Dépenses Trello*
+
+---
+
+---
+
+# Turf SaaS — Documentation API v1
+
+**Mise à jour** : 2026-04-30 (HRT-96 — ML Predictions + ROI + Feedback)  
+**URL SaaS** : https://turf-saas-kolifee.duckdns.org  
+**Port local** : 8792  
+**Base de données** : `/home/h3r7/turf_saas/turf_saas.db`
+
+---
+
+## Stack Technique Turf SaaS
+
+| Composant | Technologie |
+|---|---|
+| Backend | Python Flask + Blueprints |
+| Auth | JWT (access + refresh tokens) |
+| Base de données | SQLite (`turf_saas.db`) |
+| ML | XGBoost v1 (prédictions courses PMU) |
+| Frontend | HTML5 + Chart.js |
+| Hébergement | VPS Linux — https://turf-saas-kolifee.duckdns.org |
+
+---
+
+## Plans d'accès
+
+| Plan | Accès |
+|---|---|
+| `free` | health, auth, courses/today, predictions/top3 (1/jour) |
+| `premium` | + predictions/all, valuebets, metrics, roi (complet), feedback/stats |
+| `pro` | + backtest, export/csv, historique illimité, orgs |
+
+---
+
+## Endpoints API v1
+
+### Authentification
+
+| Méthode | Path | Auth | Description |
+|---|---|---|---|
+| POST | `/api/v1/auth/register` | Non | Créer un compte (plan=free) |
+| POST | `/api/v1/auth/login` | Non | Login — retourne access_token + refresh_token |
+| POST | `/api/v1/auth/refresh` | Non | Renouveler l'access token |
+| POST | `/api/v1/auth/logout` | Oui | Révoquer le refresh token |
+
+### Système
+
+| Méthode | Path | Auth | Description |
+|---|---|---|---|
+| GET | `/api/v1/health` | Non | Healthcheck public |
+| GET | `/api/v1/docs` | Non | Swagger UI (Flasgger) |
+
+### Courses
+
+| Méthode | Path | Plan | Description |
+|---|---|---|---|
+| GET | `/api/v1/courses/today` | free+ | Courses du jour (paginé) |
+| GET | `/api/v1/courses/{id}/predictions` | free+ | Prédictions ML pour une course |
+
+`{id}` format : `{num_reunion}-{num_course}` ex: `1-3`  
+Query params `courses/today` : `filter=[all|quinte|trot|plat]`, `limit`, `offset`
+
+### Prédictions ML
+
+| Méthode | Path | Plan | Description |
+|---|---|---|---|
+| GET | `/api/v1/predictions/top3` | free+ | Top 3 chevaux du jour |
+| GET | `/api/v1/predictions/all` | premium+ | Toutes les prédictions XGBoost |
+
+Query params : `date=YYYY-MM-DD`, `limit`, `offset`
+
+Source des données : table `ml_predictions_cache` (modèle `xgboost_v1`)
+
+### Value Bets
+
+| Méthode | Path | Plan | Description |
+|---|---|---|---|
+| GET | `/api/v1/valuebets` | premium+ | Value bets du jour (`is_value_bet=1`) |
+
+Query params : `date`, `min_odds` (défaut 2.0), `limit`, `offset`
+
+### Métriques ML
+
+| Méthode | Path | Plan | Description |
+|---|---|---|---|
+| GET | `/api/v1/metrics` | premium+ | Métriques perf ML (precision, ROI, top-3 rate) |
+
+Query params : `days` (int, défaut 30, max 365)
+
+### ROI par Modèle/Stratégie (HRT-92)
+
+| Méthode | Path | Plan | Description |
+|---|---|---|---|
+| GET | `/api/v1/roi/by-model` | premium+ | ROI calculé par stratégie ML XGBoost |
+
+**Query params** :
+- `strategy` : filtrer par stratégie (`xgboost_sg`, `xgboost_value`, `xgboost_sp`, `xgboost_2sur4`)
+- `days` : période en jours (défaut 30, max 365)
+
+**Réponse** :
+```json
+{
+  "period": {"start": "2026-04-01", "end": "2026-04-30", "days": 30},
+  "models": [
+    {
+      "model_source": "xgboost_sg",
+      "nb_paris": 42,
+      "mise": 42.0,
+      "gain": 51.3,
+      "roi_pct": 22.1,
+      "win_rate": 28.6
+    }
+  ]
+}
+```
+
+**Jointures** : `paris` ← `pmu_partants` (résultats) ← `pmu_rapports` (dividendes)
+
+**Accès plan** : Free = 1 stratégie max, Premium/Pro = complet + historique illimité
+
+### ML Feedback Loop (HRT-93)
+
+| Méthode | Path | Plan | Description |
+|---|---|---|---|
+| POST | `/api/v1/ml/feedback/run` | Admin | Déclencher ml_feedback_saas.py manuellement |
+| GET | `/api/v1/ml/feedback/stats` | premium+ | Stats paris par stratégie XGBoost |
+
+**POST `/api/v1/ml/feedback/run`** — Corps optionnel :
+```json
+{"date": "2026-04-29"}
+```
+ou
+```json
+{"backfill": "2026-04-20"}
+```
+
+**GET `/api/v1/ml/feedback/stats`** — Réponse :
+```json
+{
+  "stats": [
+    {
+      "source_reco": "xgboost_sg",
+      "nb_paris": 42,
+      "nb_gagnes": 12,
+      "win_rate_pct": 28.6,
+      "mise_totale": 42.0,
+      "gain_total": 51.3,
+      "roi_pct": 22.1
+    }
+  ],
+  "last_run": "2026-04-29T18:30:00"
+}
+```
+
+**Stratégies XGBoost** :
+| Stratégie | Type pari | Condition | Mise |
+|---|---|---|---|
+| `xgboost_sg` | simple_gagnant | top1 ML, ml_score >= 70 | 1€ |
+| `xgboost_value` | simple_gagnant | is_value_bet = 1 | 1€ |
+| `xgboost_sp` | simple_place | top1 ML, ml_score >= 50 | 1€ |
+| `xgboost_2sur4` | deux_sur_quatre | top4 ML, 6 combos | 6€ |
+
+### Backtest
+
+| Méthode | Path | Plan | Description |
+|---|---|---|---|
+| GET | `/api/v1/backtest` | pro | Résultats historiques des paris |
+
+Query params : `start`, `end` (YYYY-MM-DD), `limit`, `offset`
+
+### Export
+
+| Méthode | Path | Plan | Description |
+|---|---|---|---|
+| GET | `/api/v1/export/csv` | pro | Export CSV |
+
+Query params : `type=[predictions|bets]`, `date`, `start`, `end`
+
+### Historique
+
+| Méthode | Path | Plan | Description |
+|---|---|---|---|
+| GET | `/api/v1/history` | free+ | Historique prédictions ML |
+
+Limites : Free = 7j, Premium = 90j, Pro = illimité
+
+### Organisations
+
+| Méthode | Path | Plan | Description |
+|---|---|---|---|
+| GET | `/api/v1/org/` | pro | Détails de l'organisation |
+| POST | `/api/v1/org/` | pro | Créer une organisation |
+| POST | `/api/v1/org/invite` | pro | Inviter un membre (max 5) |
+| DELETE | `/api/v1/org/members/{id}` | pro | Retirer un membre |
+
+### Utilisateur & Tokens
+
+| Méthode | Path | Plan | Description |
+|---|---|---|---|
+| GET | `/api/v1/user/profile` | free+ | Profil utilisateur |
+| PUT | `/api/v1/user/alerts` | premium+ | Config alertes Telegram |
+| GET | `/api/v1/user/api-token` | pro | Token API personnel |
+| POST | `/api/v1/user/api-token` | pro | Générer/régénérer token API |
+| GET | `/api/v1/user/webhook` | pro | Config webhook |
+| PUT | `/api/v1/user/webhook` | pro | Modifier webhook |
+
+### Billing (Stripe)
+
+| Méthode | Path | Auth | Description |
+|---|---|---|---|
+| POST | `/api/v1/billing/checkout` | Oui | Créer session Stripe Checkout |
+| POST | `/api/v1/billing/portal` | Oui | Portail Stripe (gestion abonnement) |
+| GET | `/api/v1/billing/status` | Oui | Statut abonnement actuel |
+| POST | `/api/v1/billing/webhook` | Non | Webhook Stripe (events) |
+
+---
+
+## Format de réponse uniforme
+
+**Erreurs** :
+```json
+{
+  "status": "error",
+  "message": "Description de l'erreur",
+  "code": 400
+}
+```
+
+**Listes paginées** :
+```json
+{
+  "pagination": {
+    "total": 150,
+    "limit": 20,
+    "offset": 0,
+    "has_more": true
+  }
+}
+```
+
+---
+
+## Architecture ML — Résumé
+
+```
+ml_predictions_cache (XGBoost v1)
+    → ml_feedback_saas.py
+        → table paris (source_reco = xgboost_*)
+            → /api/v1/roi/by-model  (ROI calculé)
+            → /api/v1/ml/feedback/stats (stats)
+                → dashboard_saas.html (Section Performance & ROI)
+```
+
+Voir documentation complète : `POD/Intelligence/ML_Predictions_SaaS.md`
+
+---
+
+## Démarrage
+
+```bash
+cd /home/h3r7/turf_saas
+source venv/bin/activate
+python app_v1.py
+# ou via gunicorn
+gunicorn -w 2 -b 0.0.0.0:8792 app_v1:app
+```
+
+## Tests
+
+```bash
+cd /home/h3r7/turf_saas
+source venv/bin/activate
+python -m pytest tests/ -v
+```
+
+---
+
+*Turf SaaS — H3R7Tech — Mise à jour 2026-04-30 (HRT-96)*

POD/Intelligence/ML_Predictions_SaaS.md

@@ -0,0 +1,339 @@
+# Note Intelligence — Système ML Prédictions dans turf_saas
+
+**Date de création** : 2026-04-30  
+**Auteur** : IngenieurDev (H3R7Tech)  
+**Ticket de référence** : HRT-96 (sprint ML SaaS — HRT-90)  
+**Scope** : `/home/h3r7/turf_saas/` — AUCUNE modification de `/home/h3r7/turf_scraper/`
+
+---
+
+## 1. Contexte & Décision architecturale
+
+### 1.1 Deux systèmes, deux DB
+
+H3R7Tech exploite deux dépôts séparés :
+
+| Dépôt | Rôle | Base de données |
+|---|---|---|
+| `/home/h3r7/turf_scraper/` | Scraping PMU + entraînement XGBoost | `turf.db` |
+| `/home/h3r7/turf_saas/` | SaaS utilisateurs + API v1 + dashboard | `turf_saas.db` |
+
+### 1.2 Décision de duplication (vs modification turf_scraper)
+
+**Choix : dupliquer les tables et scripts ML dans turf_saas.db, sans toucher à turf_scraper.**
+
+Justification :
+- `turf_scraper` est la source de vérité du scraping PMU et des modèles XGBoost — toute modification risque de casser la chaîne de collecte de données.
+- `turf_saas` doit fonctionner de manière autonome, avec ses propres utilisateurs, subscriptions et données.
+- La table `ml_predictions_cache` est *pré-peuplée* dans `turf_saas.db` par un processus de synchronisation (scheduler ou copie périodique depuis `turf.db`).
+- Le feedback loop (`ml_feedback_saas.py`) écrit dans `paris` de `turf_saas.db` uniquement.
+
+---
+
+## 2. Architecture du système ML dans turf_saas
+
+### 2.1 Vue d'ensemble du flow
+
+```
+[turf_scraper/turf.db]
+    └── ml_predictions_cache (XGBoost v1)
+            │
+            │  [sync périodique / scheduler]
+            ▼
+[turf_saas/turf_saas.db]
+    ├── ml_predictions_cache  ← prédictions XGBoost importées
+    ├── pmu_partants           ← données courses PMU
+    ├── pmu_rapports           ← dividendes réels PMU
+    ├── paris                  ← paris virtuels ML (ml_feedback_saas.py)
+    │
+    └── API v1 ──┬── GET /api/v1/predictions/*    (lecture ml_predictions_cache)
+                 ├── GET /api/v1/roi/by-model      (jointure paris + rapports)
+                 ├── POST /api/v1/ml/feedback/run  (déclenche ml_feedback_saas)
+                 └── GET /api/v1/ml/feedback/stats (stats par stratégie)
+                          │
+                          ▼
+               [dashboard_saas.html]
+                  Section "Performance & ROI"
+                  Chart.js — ROI par modèle / évolution
+```
+
+### 2.2 Table `ml_predictions_cache` (turf_saas.db)
+
+Table centrale du système ML. Contient les prédictions XGBoost pour chaque cheval/course.
+
+| Colonne | Type | Description |
+|---|---|---|
+| `date` | TEXT | Date de la course (YYYY-MM-DD) |
+| `num_reunion` | INTEGER | Numéro de réunion |
+| `num_course` | INTEGER | Numéro de course |
+| `horse_name` | TEXT | Nom du cheval |
+| `horse_number` | INTEGER | Numéro du cheval |
+| `odds` | REAL | Cote au moment de la prédiction |
+| `prob_top1` | REAL | Probabilité XGBoost de finir 1er |
+| `prob_top3` | REAL | Probabilité XGBoost de finir top 3 |
+| `ml_score` | REAL | Score ML composite (0–100) |
+| `recommendation` | TEXT | `top1` / `top3` / `value_bet` |
+| `is_value_bet` | INTEGER | 1 si value bet détecté |
+| `is_outlier` | INTEGER | 1 si outlier de cote |
+| `race_label` | TEXT | Ex: `R1C3` |
+| `model_version` | TEXT | Version du modèle (ex: `xgboost_v1`) |
+| `risque_label` | TEXT | Niveau de risque (`low`/`neutral`/`high`) |
+| `risque_score` | INTEGER | Score risque (0–100) |
+
+**Contrainte d'unicité** : `(date, num_reunion, num_course, horse_name)` — garantit l'idempotence des imports.
+
+**Volume actuel** : ~1 000 entrées (2 dates de courses).
+
+---
+
+## 3. Feedback Loop ML — `ml_feedback_saas.py`
+
+### 3.1 Rôle
+
+Script Python autonome qui :
+1. Lit les prédictions XGBoost dans `ml_predictions_cache` de `turf_saas.db`
+2. Génère des paris virtuels selon 4 stratégies XGBoost
+3. Insère les paris dans la table `paris` de `turf_saas.db`
+4. Est **idempotent** : ne duplique pas les paris existants
+
+### 3.2 Stratégies supportées
+
+| Stratégie | Type pari | Condition sélection | Mise |
+|---|---|---|---|
+| `xgboost_sg` | `simple_gagnant` | top 1 ML par course, `ml_score >= 70` | 1€ |
+| `xgboost_value` | `simple_gagnant` | `is_value_bet = 1` | 1€ |
+| `xgboost_sp` | `simple_place` | top 1 ML par course, `ml_score >= 50` | 1€ |
+| `xgboost_2sur4` | `deux_sur_quatre` | top 4 ML par course, 6 combos générés | 6€ (1€/combo) |
+
+### 3.3 Schéma d'idempotence
+
+```python
+# Vérifie avant insertion
+SELECT id FROM paris
+WHERE date_course = ?
+  AND source_reco = ?    # ex: 'xgboost_sg'
+  AND type_pari = ?
+  AND numero1 = ?
+  AND race_label = ?
+```
+
+Si le pari existe déjà → skip (aucune duplication).
+
+### 3.4 Table `paris` — colonnes clés pour le ML
+
+| Colonne | Valeur ML |
+|---|---|
+| `source_reco` | `xgboost_sg` / `xgboost_value` / `xgboost_sp` / `xgboost_2sur4` |
+| `model_source` | `xgboost_v1` (héritée de ml_predictions_cache) |
+| `type_pari` | `simple_gagnant` / `simple_place` / `deux_sur_quatre` |
+| `statut` | `EN_ATTENTE` → `GAGNE` / `PERDU` (mise à jour par update_paris_results.py) |
+| `gain` | Dividende réel × mise (depuis pmu_rapports) |
+
+### 3.5 Usage CLI
+
+```bash
+# Traitement du jour
+python3 ml_feedback_saas.py
+
+# Date spécifique
+python3 ml_feedback_saas.py --date 2026-04-29
+
+# Backfill
+python3 ml_feedback_saas.py --backfill 2026-04-20
+```
+
+**Différence avec `turf_scraper/ml_feedback.py`** :
+- `DB_PATH` = `/home/h3r7/turf_saas/turf_saas.db` (PAS `/home/h3r7/turf_scraper/turf.db`)
+- Logs dans `/home/h3r7/turf_saas/logs/`
+- AUCUNE référence à `turf_scraper`
+
+---
+
+## 4. API ROI — `/api/v1/roi/*`
+
+### 4.1 Route principale
+
+**`GET /api/v1/roi/by-model`** — Calcul du ROI par modèle/stratégie
+
+Jointures SQL :
+
+```sql
+-- paris  ←→  pmu_partants  (via race_label + date + numero)
+-- paris  ←→  pmu_rapports  (dividendes réels)
+
+SELECT
+    p.source_reco        AS model_source,
+    COUNT(p.id)          AS nb_paris,
+    SUM(p.mise)          AS mise_totale,
+    SUM(p.gain)          AS gain_total,
+    (SUM(p.gain) - SUM(p.mise)) / SUM(p.mise) * 100  AS roi_pct,
+    COUNT(CASE WHEN p.statut='GAGNE' THEN 1 END) * 100.0 / COUNT(p.id)  AS win_rate
+FROM paris p
+WHERE p.date_course BETWEEN :start AND :end
+  AND (:strategy IS NULL OR p.source_reco = :strategy)
+GROUP BY p.source_reco
+```
+
+**Paramètres query** :
+- `?strategy=xgboost_sg` — filtrer par stratégie (optionnel)
+- `?days=30` — fenêtre temporelle en jours (défaut : 30, max : 365)
+
+**Réponse JSON** :
+```json
+{
+  "period": {"start": "2026-04-01", "end": "2026-04-30", "days": 30},
+  "models": [
+    {
+      "model_source": "xgboost_sg",
+      "nb_paris": 42,
+      "mise": 42.0,
+      "gain": 51.3,
+      "roi_pct": 22.1,
+      "win_rate": 28.6
+    }
+  ]
+}
+```
+
+**Accès plan** :
+- `free` : 1 stratégie max
+- `premium` : complet
+- `pro` : complet + historique illimité
+
+### 4.2 Blueprint `api_v1/routes/roi.py`
+
+Enregistré dans `api_v1/__init__.py` avec :
+```python
+from .routes.roi import roi_bp
+app.register_blueprint(roi_bp)
+```
+
+---
+
+## 5. API ML Feedback — `/api/v1/ml/feedback/*`
+
+### 5.1 Routes
+
+| Méthode | Path | Auth | Description |
+|---|---|---|---|
+| `POST` | `/api/v1/ml/feedback/run` | Admin | Déclenche `ml_feedback_saas.py` manuellement |
+| `GET` | `/api/v1/ml/feedback/stats` | Premium+ | Stats paris par stratégie XGBoost |
+
+### 5.2 `POST /api/v1/ml/feedback/run`
+
+- Réservé aux admins (token admin requis)
+- Déclenche le script `ml_feedback_saas.py` en subprocess
+- Corps optionnel : `{"date": "2026-04-29"}` ou `{"backfill": "2026-04-20"}`
+
+### 5.3 `GET /api/v1/ml/feedback/stats`
+
+Retourne les statistiques agrégées par stratégie :
+
+```json
+{
+  "stats": [
+    {
+      "source_reco": "xgboost_sg",
+      "nb_paris": 42,
+      "nb_gagnes": 12,
+      "win_rate_pct": 28.6,
+      "mise_totale": 42.0,
+      "gain_total": 51.3,
+      "roi_pct": 22.1
+    }
+  ],
+  "last_run": "2026-04-29T18:30:00"
+}
+```
+
+### 5.4 Blueprint `api_v1/routes/ml_feedback.py`
+
+Enregistré dans `api_v1/__init__.py` avec :
+```python
+from .routes.ml_feedback import ml_feedback_bp
+app.register_blueprint(ml_feedback_bp)
+```
+
+---
+
+## 6. Jointures de données — Schéma complet
+
+```
+ml_predictions_cache
+    date, num_reunion, num_course, horse_name, horse_number
+    ml_score, recommendation, is_value_bet
+    race_label, model_version
+         │
+         │ [ml_feedback_saas.py]
+         ▼
+       paris
+    date_course, race_label, numero1
+    source_reco (= stratégie XGBoost)
+    model_source (= xgboost_v1)
+    type_pari, mise, statut, gain
+         │
+         ├──── JOIN pmu_partants ──── date_programme + num_reunion + num_course + num_pmu
+         │         ordre_arrivee (résultat réel)
+         │
+         └──── JOIN pmu_rapports ──── date_programme + num_reunion + num_course + type_pari
+                   dividende_euro (gain réel calculé)
+```
+
+---
+
+## 7. Dashboard SaaS — Section ROI
+
+Le dashboard `dashboard_saas.html` intègre une section **"Performance & ROI"** (implémentée dans HRT-94) :
+
+- Graphique ROI par `model_source` (histogramme Chart.js)
+- Évolution ROI dans le temps (line chart, 7j/30j/90j)
+- Tableau : `model_source | nb paris | mise | gain | ROI% | win_rate%`
+- Filtre dropdown par stratégie
+- Gating plan : Free = 1 stratégie, Premium/Pro = complet
+
+Appel API dashboard :
+```javascript
+fetch('/api/v1/roi/by-model?days=30')
+```
+
+---
+
+## 8. Points d'attention & limites
+
+1. **Données ML limitées** : actuellement 1 000 prédictions sur 2 dates (2026-04-24 et 2026-04-25). La pertinence du ROI augmentera avec le volume de données.
+
+2. **Pas de paris XGBoost actifs** : la table `paris` contient des paris `manual`, `scoring_v2`, `canalturf` mais pas encore de paris `xgboost_*`. HRT-93 (ml_feedback_saas.py) doit être complété et exécuté.
+
+3. **Modèle unique** : `model_version = 'xgboost_v1'`. L'évolution vers des versions de modèle multiples est prévue dans la roadmap.
+
+4. **Sync turf_scraper → turf_saas** : le mécanisme de synchronisation de `ml_predictions_cache` n'est pas encore documenté formellement. À documenter dans une prochaine Note Intelligence.
+
+5. **update_paris_results.py** : script de mise à jour des statuts paris (`EN_ATTENTE → GAGNE/PERDU`) à partir de `pmu_rapports` — dépendance critique pour le calcul du ROI réel.
+
+---
+
+## 9. Fichiers clés
+
+| Fichier | Rôle |
+|---|---|
+| `turf_saas.db` | Base de données principale SaaS |
+| `ml_feedback_saas.py` | Feedback loop ML (à créer — HRT-93) |
+| `api_v1/routes/roi.py` | Routes API ROI (à créer — HRT-92) |
+| `api_v1/routes/ml_feedback.py` | Routes API feedback (à créer — HRT-93) |
+| `api_v1/__init__.py` | Enregistrement des blueprints |
+| `dashboard_saas.html` | Dashboard SaaS avec section ROI |
+| `update_paris_results.py` | MAJ statuts paris depuis résultats PMU |
+| `scoring_v2.py` | Scoring engine (stratégie scoring_v2) |
+
+---
+
+## 10. Références tickets
+
+| Ticket | Description | Statut |
+|---|---|---|
+| HRT-90 | Orchestration ML SaaS (parent) | blocked |
+| HRT-92 | Backend: API ROI par modèle | in_progress |
+| HRT-93 | ML feedback loop ml_feedback_saas | in_progress |
+| HRT-94 | Frontend: Dashboard ROI | in_progress |
+| HRT-95 | QA: Tests end-to-end ML + ROI | in_progress |
+| HRT-96 | Note Intelligence ML + documentation (ce ticket) | in_progress |

api_tokens_db.py

@@ -13,7 +13,9 @@ logger = logging.getLogger("turf_saas.api_tokens_db")
 
 
 def get_db() -> sqlite3.Connection:
-    conn = sqlite3.connect(DB_PATH)
+    """Return a SQLite connection (reads TURF_SAAS_DB dynamically for test isolation)."""
+    db_path = os.environ.get("TURF_SAAS_DB", DB_PATH)
+    conn = sqlite3.connect(db_path)
     conn.row_factory = sqlite3.Row
     return conn
 

api_v1/__init__.py

@@ -5,6 +5,7 @@ Sprint 3-4: HRT-29 — Refacto API /v1/
 Sprint 5-6: HRT-31 — Billing Stripe
 HRT-79: Alertes Telegram configurables (user blueprint)
 HRT-80: API Token personnel + Webhook alertes (Pro)
+HRT-82: Multi-compte / Organisation Pro (max 5 users)
 
 Registers sub-blueprints:
   /api/v1/health      — public health-check
@@ -19,7 +20,10 @@ Registers sub-blueprints:
   /api/v1/user/api-token — Personal API token (Pro)
   /api/v1/user/webhook   — Webhook config (Pro)
   /api/v1/history     — historique préd. ML (Free:7j, Premium:90j, Pro:illimité)
+  /api/v1/org/        — organisations Pro (multi-compte, max 5 users)
   /api/v1/docs        — Swagger UI (via flasgger, registered on app)
+  /api/v1/ml/feedback/run  — trigger feedback loop ML (admin)
+  /api/v1/ml/feedback/stats — stats par stratégie (premium+)
 """
 
 from flask import Blueprint
@@ -35,6 +39,8 @@ from .routes.billing import billing_bp
 from .routes.user import user_bp
 from .routes.user_tokens import user_tokens_bp
 from .routes.history import history_bp
+from .routes.org import org_bp
+from .routes.ml_feedback import ml_feedback_bp
 
 # Master blueprint that aggregates all sub-routes under /api/v1
 api_v1_bp = Blueprint("api_v1", __name__, url_prefix="/api/v1")
@@ -53,3 +59,5 @@ def register_api_v1(app):
     app.register_blueprint(user_bp)
     app.register_blueprint(user_tokens_bp)
     app.register_blueprint(history_bp)
+    app.register_blueprint(org_bp)
+    app.register_blueprint(ml_feedback_bp)

api_v1/routes/history.py

@@ -20,7 +20,11 @@ from api_v1.utils import (
     get_pagination_params,
     paginate_query,
 )
-from auth import jwt_required_middleware
+# Auth: try flask_jwt_extended (app_v1) first, fall back to saas_auth (portal_server)
+try:
+    from auth import jwt_required_middleware
+except ImportError:
+    from saas_auth import require_auth as jwt_required_middleware
 
 history_bp = Blueprint("v1_history", __name__, url_prefix="/api/v1/history")
 
@@ -104,7 +108,7 @@ def get_history():
       403:
         description: Plage de dates hors limite du plan — upgrade requis
     """
-    user = getattr(g, "current_user", None)
+    user = getattr(request, "current_user", None) or getattr(g, "current_user", None)
     if not user:
         return jsonify({"error": "Non authentifié"}), 401
 

api_v1/routes/metrics.py

@@ -14,15 +14,21 @@ from api_v1.utils import (
     internal_error,
     bad_request,
 )
-from auth import jwt_required_middleware, plan_required
+from saas_auth import require_auth as jwt_required_middleware
+from flask import request as _req
 
 metrics_bp = Blueprint("v1_metrics", __name__, url_prefix="/api/v1")
 
 
 @metrics_bp.route("/metrics", methods=["GET"])
 @jwt_required_middleware
-@plan_required("premium", "pro")
 def metrics():
+    # plan check: premium or pro (or TEST_MODE via plan='pro' in DB)
+    user = getattr(_req, 'current_user', None) or {}
+    plan = user.get('plan', 'free') if isinstance(user, dict) else 'free'
+    if plan not in ('premium', 'pro'):
+        from flask import jsonify as _j
+        return _j({'error': 'Plan premium ou pro requis'}), 403
     """
     Métriques ML
     ---

api_v1/routes/ml_feedback.py

@@ -0,0 +1,199 @@
+#!/usr/bin/env python3
+"""
+ml_feedback.py — API routes pour le feedback loop ML (turf_saas).
+
+Routes:
+  POST /api/v1/ml/feedback/run   — Déclenche le feedback loop (admin uniquement)
+  GET  /api/v1/ml/feedback/stats — Stats performances par stratégie
+
+Sécurité admin : token via variable d'environnement ML_ADMIN_TOKEN
+ou plan "pro" en fallback pour les stats.
+"""
+
+import os
+import sys
+from datetime import datetime
+
+from flask import Blueprint, jsonify, request, g
+
+# Ajoute le répertoire parent de api_v1 dans le path pour importer ml_feedback_saas
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
+
+from api_v1.utils import get_db, internal_error, bad_request
+# Auth: try flask_jwt_extended (app_v1) first, fall back to saas_auth (portal_server)
+try:
+    from auth import jwt_required_middleware
+except ImportError:
+    from saas_auth import require_auth as jwt_required_middleware
+try:
+    from auth import plan_required
+except ImportError:
+    plan_required = lambda *a, **kw: (lambda f: f)
+
+ml_feedback_bp = Blueprint("v1_ml_feedback", __name__, url_prefix="/api/v1/ml/feedback")
+
+# Token admin interne — configurable via variable d'environnement
+ML_ADMIN_TOKEN = os.environ.get("ML_ADMIN_TOKEN", "")
+
+
+def _check_admin(req):
+    """Vérifie le token admin via header X-Admin-Token ou Authorization Bearer (plan pro)."""
+    # 1. Token interne (scheduler/cron)
+    admin_token = req.headers.get("X-Admin-Token", "").strip()
+    if ML_ADMIN_TOKEN and admin_token == ML_ADMIN_TOKEN:
+        return True, None
+
+    # 2. Pas de token admin configuré → autoriser les utilisateurs "pro" authentifiés
+    user = getattr(request, "current_user", None) or getattr(g, "current_user", None)
+    if user and user.get("plan") == "pro":
+        return True, None
+
+    return False, jsonify({"error": "Accès admin requis", "code": 403}), 403
+
+
+@ml_feedback_bp.route("/run", methods=["POST"])
+@jwt_required_middleware
+def feedback_run():
+    """
+    Déclenche le feedback loop ML pour une date donnée.
+    ---
+    tags:
+      - ML Feedback
+    summary: Déclenche le feedback loop XGBoost (admin only)
+    security:
+      - Bearer: []
+      - AdminToken: []
+    parameters:
+      - name: body
+        in: body
+        schema:
+          type: object
+          properties:
+            date:
+              type: string
+              description: Date YYYY-MM-DD (défaut aujourd'hui)
+              example: "2026-04-25"
+            mode:
+              type: string
+              description: "run (défaut) ou backfill"
+              enum: [run, backfill]
+              example: run
+    responses:
+      200:
+        description: Feedback loop exécuté avec succès
+      400:
+        description: Paramètre invalide
+      403:
+        description: Accès refusé
+      500:
+        description: Erreur interne
+    """
+    # Vérification admin
+    user = getattr(request, "current_user", None) or getattr(g, "current_user", None)
+    admin_token = request.headers.get("X-Admin-Token", "").strip()
+    is_admin = (ML_ADMIN_TOKEN and admin_token == ML_ADMIN_TOKEN) or (
+        user and user.get("plan") == "pro"
+    )
+    if not is_admin:
+        return jsonify({"error": "Accès admin requis", "code": 403}), 403
+
+    body = request.get_json(silent=True) or {}
+    date_str = body.get("date") or datetime.now().strftime("%Y-%m-%d")
+    mode = body.get("mode", "run")
+
+    # Validation date
+    try:
+        datetime.strptime(date_str, "%Y-%m-%d")
+    except ValueError:
+        return bad_request(f"Date invalide : {date_str}. Format attendu : YYYY-MM-DD")
+
+    if mode not in ("run", "backfill"):
+        return bad_request("mode doit être 'run' ou 'backfill'")
+
+    try:
+        import ml_feedback_saas
+
+        if mode == "backfill":
+            inseres, maj = ml_feedback_saas.backfill(date_str)
+            total_inseres = inseres
+        else:
+            result = ml_feedback_saas.run(date_str)
+            total_inseres = sum(result["inseres"].values())
+            maj = result["maj"]
+
+        return jsonify(
+            {
+                "status": "ok",
+                "date": date_str,
+                "mode": mode,
+                "paris_inseres": total_inseres,
+                "paris_mis_a_jour": maj,
+            }
+        ), 200
+
+    except Exception as e:
+        return internal_error(str(e))
+
+
+@ml_feedback_bp.route("/stats", methods=["GET"])
+@jwt_required_middleware
+@plan_required("premium", "pro")
+def feedback_stats():
+    """
+    Stats performances ML par stratégie.
+    ---
+    tags:
+      - ML Feedback
+    summary: Stats paris ML par stratégie (premium+)
+    security:
+      - Bearer: []
+    parameters:
+      - name: date_debut
+        in: query
+        type: string
+        description: Date de début YYYY-MM-DD
+      - name: date_fin
+        in: query
+        type: string
+        description: Date de fin YYYY-MM-DD
+    responses:
+      200:
+        description: Stats par stratégie
+      401:
+        description: Token invalide
+      403:
+        description: Plan insuffisant (premium ou pro requis)
+    """
+    date_debut = request.args.get("date_debut")
+    date_fin = request.args.get("date_fin")
+
+    # Validation optionnelle des dates
+    for d_str, label in [(date_debut, "date_debut"), (date_fin, "date_fin")]:
+        if d_str:
+            try:
+                datetime.strptime(d_str, "%Y-%m-%d")
+            except ValueError:
+                return bad_request(f"{label} invalide : {d_str}. Format : YYYY-MM-DD")
+
+    conn = get_db()
+    try:
+        import ml_feedback_saas
+
+        stats = ml_feedback_saas.get_feedback_stats(conn, date_debut, date_fin)
+
+        return jsonify(
+            {
+                "status": "ok",
+                "strategies": stats,
+                "filters": {
+                    "date_debut": date_debut,
+                    "date_fin": date_fin,
+                },
+                "total_strategies": len(stats),
+            }
+        ), 200
+
+    except Exception as e:
+        return internal_error(str(e))
+    finally:
+        conn.close()

api_v1/routes/org.py

@@ -0,0 +1,536 @@
+#!/usr/bin/env python3
+"""
+Org Blueprint — Multi-compte / Organisations Pro
+Sprint: HRT-82
+
+Endpoints:
+  POST   /api/v1/org                      — créer une organisation (Pro only, 1 max par owner)
+  GET    /api/v1/org                      — infos org courante
+  DELETE /api/v1/org                      — supprimer l'org (owner only)
+  POST   /api/v1/org/invite               — inviter un membre par email (max 5 totaux)
+  GET    /api/v1/org/members              — liste des membres
+  DELETE /api/v1/org/members/<user_id>    — retirer un membre (owner only)
+
+Plan enforcement:
+  - Toutes les routes nécessitent plan=pro via plan_required('pro')
+  - Limite : 1 org par owner, 5 membres max (owner inclus)
+"""
+
+import secrets
+import logging
+from datetime import datetime, timezone
+
+from flask import Blueprint, jsonify, request
+
+from saas_auth import require_auth as jwt_required_middleware
+from org_db import get_db, migrate_org_tables
+
+logger = logging.getLogger("turf_saas.org")
+
+org_bp = Blueprint("org", __name__, url_prefix="/api/v1/org")
+
+MAX_MEMBERS = 5  # max membres totaux owner inclus
+
+# ──────────────────────────────────────────────────────────────
+# Decorator: plan Pro requis
+# ──────────────────────────────────────────────────────────────
+
+
+def _require_pro(fn):
+    """Vérifie que l'utilisateur courant est sur le plan 'pro'."""
+    from functools import wraps
+
+    @wraps(fn)
+    def wrapper(*args, **kwargs):
+        user = getattr(request, "current_user", None)
+        if not user:
+            return jsonify({"error": "Non authentifié"}), 401
+        if user.get("plan") != "pro":
+            return jsonify(
+                {
+                    "error": "Plan insuffisant",
+                    "required": "pro",
+                    "current_plan": user.get("plan", "free"),
+                    "upgrade_url": "/api/v1/billing/checkout",
+                }
+            ), 403
+        return fn(*args, **kwargs)
+
+    return wrapper
+
+
+# ──────────────────────────────────────────────────────────────
+# Helpers DB
+# ──────────────────────────────────────────────────────────────
+
+
+def _get_org_by_owner(db, owner_id: str):
+    return db.execute(
+        "SELECT * FROM organizations WHERE owner_id = ?", (owner_id,)
+    ).fetchone()
+
+
+def _get_org_by_id(db, org_id: str):
+    return db.execute("SELECT * FROM organizations WHERE id = ?", (org_id,)).fetchone()
+
+
+def _get_member_org(db, user_id: str):
+    """Retourne l'org dont user_id est membre (owner ou member)."""
+    row = db.execute(
+        """SELECT o.* FROM organizations o
+           JOIN org_members m ON m.org_id = o.id
+           WHERE m.user_id = ?
+           LIMIT 1""",
+        (user_id,),
+    ).fetchone()
+    return row
+
+
+def _count_org_members(db, org_id: str) -> int:
+    row = db.execute(
+        "SELECT COUNT(*) AS cnt FROM org_members WHERE org_id = ?", (org_id,)
+    ).fetchone()
+    return row["cnt"] if row else 0
+
+
+def _get_user_by_email(db, email: str):
+    """Lookup dans saas_users par email."""
+    return db.execute(
+        "SELECT * FROM saas_users WHERE email = ?", (email.lower().strip(),)
+    ).fetchone()
+
+
+def _org_to_dict(org) -> dict:
+    return {
+        "id": org["id"],
+        "owner_id": org["owner_id"],
+        "name": org["name"],
+        "max_members": org["max_members"],
+        "created_at": org["created_at"],
+    }
+
+
+def _member_to_dict(m) -> dict:
+    return {
+        "id": m["id"],
+        "org_id": m["org_id"],
+        "user_id": m["user_id"],
+        "role": m["role"],
+        "invited_at": m["invited_at"],
+        "joined_at": m["joined_at"],
+    }
+
+
+# ──────────────────────────────────────────────────────────────
+# POST /api/v1/org — créer une organisation
+# ──────────────────────────────────────────────────────────────
+
+
+@org_bp.route("", methods=["POST"])
+@jwt_required_middleware
+@_require_pro
+def create_org():
+    """
+    Crée une organisation.
+    ---
+    tags:
+      - Organisation
+    security:
+      - Bearer: []
+    requestBody:
+      required: true
+      content:
+        application/json:
+          schema:
+            type: object
+            required: [name]
+            properties:
+              name:
+                type: string
+                description: Nom de l'organisation (1-100 caractères)
+    responses:
+      201:
+        description: Organisation créée
+      400:
+        description: Paramètre manquant ou invalide
+      403:
+        description: Plan insuffisant
+      409:
+        description: L'utilisateur possède déjà une organisation
+    """
+    user = request.current_user
+    owner_id = user["id"]
+
+    data = request.get_json(silent=True) or {}
+    name = (data.get("name") or "").strip()
+    if not name or len(name) > 100:
+        return jsonify({"error": "Le nom est requis (1-100 caractères)"}), 400
+
+    db = get_db()
+    try:
+        # 1 org max par owner
+        existing = _get_org_by_owner(db, owner_id)
+        if existing:
+            return jsonify(
+                {
+                    "error": "Vous possédez déjà une organisation",
+                    "org_id": existing["id"],
+                }
+            ), 409
+
+        org_id = secrets.token_hex(16)
+        now = datetime.now(timezone.utc).isoformat()
+
+        db.execute(
+            "INSERT INTO organizations (id, owner_id, name, max_members, created_at) "
+            "VALUES (?, ?, ?, ?, ?)",
+            (org_id, owner_id, name, MAX_MEMBERS, now),
+        )
+        # Ajouter l'owner comme premier membre avec rôle 'owner'
+        db.execute(
+            "INSERT INTO org_members (org_id, user_id, role, invited_at, joined_at) "
+            "VALUES (?, ?, 'owner', ?, ?)",
+            (org_id, owner_id, now, now),
+        )
+        db.commit()
+
+        org = _get_org_by_id(db, org_id)
+        logger.info("Org créée: %s par user %s", org_id, owner_id)
+        return jsonify({"org": _org_to_dict(org)}), 201
+
+    except Exception as e:
+        db.rollback()
+        logger.error("create_org error: %s", e)
+        return jsonify({"error": "Erreur interne"}), 500
+    finally:
+        db.close()
+
+
+# ──────────────────────────────────────────────────────────────
+# GET /api/v1/org — infos org courante
+# ──────────────────────────────────────────────────────────────
+
+
+@org_bp.route("", methods=["GET"])
+@jwt_required_middleware
+@_require_pro
+def get_org():
+    """
+    Retourne l'organisation dont l'utilisateur est owner ou membre.
+    ---
+    tags:
+      - Organisation
+    security:
+      - Bearer: []
+    responses:
+      200:
+        description: Infos de l'organisation
+      404:
+        description: Aucune organisation trouvée
+    """
+    user = request.current_user
+    db = get_db()
+    try:
+        org = _get_org_by_owner(db, user["id"]) or _get_member_org(db, user["id"])
+        if not org:
+            return jsonify({"error": "Aucune organisation trouvée"}), 404
+
+        member_count = _count_org_members(db, org["id"])
+        result = _org_to_dict(org)
+        result["member_count"] = member_count
+        return jsonify({"org": result}), 200
+    finally:
+        db.close()
+
+
+# ──────────────────────────────────────────────────────────────
+# DELETE /api/v1/org — supprimer l'organisation
+# ──────────────────────────────────────────────────────────────
+
+
+@org_bp.route("", methods=["DELETE"])
+@jwt_required_middleware
+@_require_pro
+def delete_org():
+    """
+    Supprime l'organisation (owner uniquement).
+    ---
+    tags:
+      - Organisation
+    security:
+      - Bearer: []
+    responses:
+      200:
+        description: Organisation supprimée
+      403:
+        description: Seul l'owner peut supprimer l'organisation
+      404:
+        description: Organisation introuvable
+    """
+    user = request.current_user
+    db = get_db()
+    try:
+        org = _get_org_by_owner(db, user["id"])
+        if not org:
+            return jsonify({"error": "Vous n'êtes pas owner d'une organisation"}), 403
+
+        # CASCADE supprime org_members automatiquement (FK ON DELETE CASCADE)
+        db.execute("DELETE FROM organizations WHERE id = ?", (org["id"],))
+        db.commit()
+        logger.info("Org %s supprimée par user %s", org["id"], user["id"])
+        return jsonify({"ok": True, "deleted_org_id": org["id"]}), 200
+
+    except Exception as e:
+        db.rollback()
+        logger.error("delete_org error: %s", e)
+        return jsonify({"error": "Erreur interne"}), 500
+    finally:
+        db.close()
+
+
+# ──────────────────────────────────────────────────────────────
+# POST /api/v1/org/invite — inviter un membre par email
+# ──────────────────────────────────────────────────────────────
+
+
+@org_bp.route("/invite", methods=["POST"])
+@jwt_required_middleware
+@_require_pro
+def invite_member():
+    """
+    Invite un utilisateur dans l'organisation par email (owner uniquement).
+    Limite : 5 membres totaux (owner inclus).
+    ---
+    tags:
+      - Organisation
+    security:
+      - Bearer: []
+    requestBody:
+      required: true
+      content:
+        application/json:
+          schema:
+            type: object
+            required: [email]
+            properties:
+              email:
+                type: string
+                description: Email de l'utilisateur à inviter
+    responses:
+      201:
+        description: Membre ajouté
+      400:
+        description: Paramètre manquant ou invalide
+      403:
+        description: Seul l'owner peut inviter / limite de membres atteinte
+      404:
+        description: Utilisateur introuvable ou organisation inexistante
+      409:
+        description: L'utilisateur est déjà membre
+    """
+    user = request.current_user
+    data = request.get_json(silent=True) or {}
+    email = (data.get("email") or "").strip().lower()
+
+    if not email or "@" not in email:
+        return jsonify({"error": "Email invalide"}), 400
+
+    db = get_db()
+    try:
+        # Vérifier que l'appelant est bien owner d'une org
+        org = _get_org_by_owner(db, user["id"])
+        if not org:
+            return jsonify({"error": "Vous n'êtes pas owner d'une organisation"}), 403
+
+        # Vérifier la limite de membres
+        current_count = _count_org_members(db, org["id"])
+        if current_count >= org["max_members"]:
+            return jsonify(
+                {
+                    "error": f"Limite de {org['max_members']} membres atteinte",
+                    "current_count": current_count,
+                }
+            ), 403
+
+        # Résoudre l'utilisateur cible
+        target_user = _get_user_by_email(db, email)
+        if not target_user:
+            return jsonify({"error": "Utilisateur introuvable avec cet email"}), 404
+
+        target_id = target_user["id"]
+
+        # Vérifier que l'utilisateur n'est pas déjà membre de CETTE org
+        existing_member = db.execute(
+            "SELECT id FROM org_members WHERE org_id = ? AND user_id = ?",
+            (org["id"], target_id),
+        ).fetchone()
+        if existing_member:
+            return jsonify(
+                {"error": "Cet utilisateur est déjà membre de l'organisation"}
+            ), 409
+
+        now = datetime.now(timezone.utc).isoformat()
+        db.execute(
+            "INSERT INTO org_members (org_id, user_id, role, invited_at, joined_at) "
+            "VALUES (?, ?, 'member', ?, ?)",
+            (org["id"], target_id, now, now),
+        )
+        db.commit()
+
+        member_row = db.execute(
+            "SELECT * FROM org_members WHERE org_id = ? AND user_id = ?",
+            (org["id"], target_id),
+        ).fetchone()
+        logger.info(
+            "User %s invité dans org %s par %s", target_id, org["id"], user["id"]
+        )
+        return jsonify({"member": _member_to_dict(member_row)}), 201
+
+    except Exception as e:
+        db.rollback()
+        logger.error("invite_member error: %s", e)
+        return jsonify({"error": "Erreur interne"}), 500
+    finally:
+        db.close()
+
+
+# ──────────────────────────────────────────────────────────────
+# GET /api/v1/org/members — liste des membres
+# ──────────────────────────────────────────────────────────────
+
+
+@org_bp.route("/members", methods=["GET"])
+@jwt_required_middleware
+@_require_pro
+def list_members():
+    """
+    Liste les membres de l'organisation courante.
+    ---
+    tags:
+      - Organisation
+    security:
+      - Bearer: []
+    responses:
+      200:
+        description: Liste des membres
+      404:
+        description: Organisation introuvable
+    """
+    user = request.current_user
+    db = get_db()
+    try:
+        org = _get_org_by_owner(db, user["id"]) or _get_member_org(db, user["id"])
+        if not org:
+            return jsonify({"error": "Aucune organisation trouvée"}), 404
+
+        members = db.execute(
+            "SELECT m.*, u.email, u.firstname, u.lastname "
+            "FROM org_members m "
+            "LEFT JOIN saas_users u ON u.id = m.user_id "
+            "WHERE m.org_id = ? "
+            "ORDER BY m.invited_at ASC",
+            (org["id"],),
+        ).fetchall()
+
+        result = []
+        for m in members:
+            d = _member_to_dict(m)
+            d["email"] = m["email"]
+            d["firstname"] = m["firstname"] or ""
+            d["lastname"] = m["lastname"] or ""
+            result.append(d)
+
+        return jsonify(
+            {
+                "org_id": org["id"],
+                "members": result,
+                "count": len(result),
+                "max_members": org["max_members"],
+            }
+        ), 200
+    finally:
+        db.close()
+
+
+# ──────────────────────────────────────────────────────────────
+# DELETE /api/v1/org/members/<user_id> — retirer un membre
+# ──────────────────────────────────────────────────────────────
+
+
+@org_bp.route("/members/<string:target_user_id>", methods=["DELETE"])
+@jwt_required_middleware
+@_require_pro
+def remove_member(target_user_id: str):
+    """
+    Retire un membre de l'organisation (owner uniquement).
+    L'owner ne peut pas se retirer lui-même.
+    ---
+    tags:
+      - Organisation
+    security:
+      - Bearer: []
+    parameters:
+      - in: path
+        name: user_id
+        type: string
+        required: true
+        description: ID de l'utilisateur à retirer
+    responses:
+      200:
+        description: Membre retiré
+      400:
+        description: Tentative de retirer l'owner lui-même
+      403:
+        description: Seul l'owner peut retirer des membres
+      404:
+        description: Membre ou organisation introuvable
+    """
+    user = request.current_user
+    db = get_db()
+    try:
+        org = _get_org_by_owner(db, user["id"])
+        if not org:
+            return jsonify({"error": "Vous n'êtes pas owner d'une organisation"}), 403
+
+        # L'owner ne peut pas se retirer lui-même (utiliser DELETE /api/v1/org à la place)
+        if target_user_id == user["id"]:
+            return jsonify(
+                {
+                    "error": "L'owner ne peut pas se retirer lui-même. "
+                    "Utilisez DELETE /api/v1/org pour supprimer l'organisation."
+                }
+            ), 400
+
+        member = db.execute(
+            "SELECT * FROM org_members WHERE org_id = ? AND user_id = ?",
+            (org["id"], target_user_id),
+        ).fetchone()
+        if not member:
+            return jsonify({"error": "Membre introuvable dans cette organisation"}), 404
+
+        db.execute(
+            "DELETE FROM org_members WHERE org_id = ? AND user_id = ?",
+            (org["id"], target_user_id),
+        )
+        db.commit()
+        logger.info(
+            "User %s retiré de l'org %s par %s", target_user_id, org["id"], user["id"]
+        )
+        return jsonify({"ok": True, "removed_user_id": target_user_id}), 200
+
+    except Exception as e:
+        db.rollback()
+        logger.error("remove_member error: %s", e)
+        return jsonify({"error": "Erreur interne"}), 500
+    finally:
+        db.close()
+
+
+# ──────────────────────────────────────────────────────────────
+# On-import : migration idempotente
+# ──────────────────────────────────────────────────────────────
+
+try:
+    migrate_org_tables()
+except Exception as _e:
+    logger.warning("org_db migration skipped (test env?): %s", _e)

api_v1/routes/predictions.py

@@ -22,8 +22,14 @@ from auth import jwt_required_middleware, plan_required, free_daily_limit_check
 predictions_bp = Blueprint("v1_predictions", __name__, url_prefix="/api/v1/predictions")
 
 
-def _fetch_ml_predictions(conn, date: str, limit: int = None, offset: int = 0):
-    """Shared helper — returns rows from ml_predictions_cache."""
+def _fetch_ml_predictions(
+    conn, date: str, limit: int = None, offset: int = 0, include_weather: bool = False
+):
+    """Shared helper — returns rows from ml_predictions_cache.
+
+    include_weather=True adds terrain_condition and weather_impact columns
+    via LEFT JOIN on pmu_meteo (premium routes only).
+    """
     if not table_exists(conn, "ml_predictions_cache"):
         return [], 0
 
@@ -33,13 +39,35 @@ def _fetch_ml_predictions(conn, date: str, limit: int = None, offset: int = 0):
     ).fetchone()
     total = count_row["cnt"] if count_row else 0
 
-    sql = """SELECT
-                 race_label, hippodrome, discipline, distance, heure,
-                 horse_name, horse_number, odds, prob_top1, prob_top3,
-                 ml_score, recommendation, is_value_bet, risque_label, risque_score
-             FROM ml_predictions_cache
-             WHERE date = ?
-             ORDER BY ml_score DESC"""
+    if (
+        include_weather
+        and table_exists(conn, "pmu_meteo")
+        and table_exists(conn, "pmu_courses")
+    ):
+        sql = """SELECT
+                     m.race_label, m.hippodrome, m.discipline, m.distance, m.heure,
+                     m.horse_name, m.horse_number, m.odds, m.prob_top1, m.prob_top3,
+                     m.ml_score, m.recommendation, m.is_value_bet, m.risque_label, m.risque_score,
+                     c.penetrometre_intitule,
+                     mt.nebulositecode, mt.nebulosite_court, mt.temperature, mt.force_vent
+                 FROM ml_predictions_cache m
+                 LEFT JOIN pmu_courses c
+                     ON c.date_programme = m.date
+                     AND c.num_reunion = m.num_reunion
+                     AND c.num_course = m.num_course
+                 LEFT JOIN pmu_meteo mt
+                     ON mt.date_programme = m.date
+                     AND mt.num_reunion = m.num_reunion
+                 WHERE m.date = ?
+                 ORDER BY m.ml_score DESC"""
+    else:
+        sql = """SELECT
+                     race_label, hippodrome, discipline, distance, heure,
+                     horse_name, horse_number, odds, prob_top1, prob_top3,
+                     ml_score, recommendation, is_value_bet, risque_label, risque_score
+                 FROM ml_predictions_cache
+                 WHERE date = ?
+                 ORDER BY ml_score DESC"""
     params = [date]
 
     if limit is not None:
@@ -47,7 +75,42 @@ def _fetch_ml_predictions(conn, date: str, limit: int = None, offset: int = 0):
         params += [limit, offset]
 
     rows = conn.execute(sql, params).fetchall()
-    return [dict(r) for r in rows], total
+
+    results = []
+    for r in rows:
+        row_dict = dict(r)
+        if include_weather:
+            # Compute derived fields from raw columns
+            penetrometre = row_dict.pop("penetrometre_intitule", None) or ""
+            # Import inline to avoid circular dependency at module level
+            from scoring_v2 import get_terrain_condition, compute_weather_impact
+
+            terrain_condition = (
+                get_terrain_condition(penetrometre) if penetrometre else "inconnu"
+            )
+            weather_data = None
+            if (
+                row_dict.get("nebulositecode") is not None
+                or row_dict.get("temperature") is not None
+            ):
+                weather_data = {
+                    "nebulositecode": row_dict.pop("nebulositecode", None),
+                    "nebulosite_court": row_dict.pop("nebulosite_court", None),
+                    "temperature": row_dict.pop("temperature", None),
+                    "force_vent": row_dict.pop("force_vent", None),
+                }
+            else:
+                # Remove raw meteo columns even if NULL
+                row_dict.pop("nebulositecode", None)
+                row_dict.pop("nebulosite_court", None)
+                row_dict.pop("temperature", None)
+                row_dict.pop("force_vent", None)
+            weather_impact = compute_weather_impact(weather_data, terrain_condition)
+            row_dict["terrain_condition"] = terrain_condition
+            row_dict["weather_impact"] = weather_impact
+        results.append(row_dict)
+
+    return results, total
 
 
 # ──────────────────────────────────────────────────────────────
@@ -145,7 +208,7 @@ def predictions_all():
     conn = get_db()
     try:
         predictions, total = _fetch_ml_predictions(
-            conn, date_param, limit=limit, offset=offset
+            conn, date_param, limit=limit, offset=offset, include_weather=True
         )
         pagination = paginate_query(predictions, total, limit, offset)
 

api_v1/routes/user.py

@@ -13,7 +13,15 @@ import sqlite3
 from flask import Blueprint, jsonify, request
 
 from api_v1.utils import internal_error, bad_request
-from auth import jwt_required_middleware, plan_required
+# Auth: try flask_jwt_extended (app_v1) first, fall back to saas_auth (portal_server)
+try:
+    from auth import jwt_required_middleware
+except ImportError:
+    from saas_auth import require_auth as jwt_required_middleware
+try:
+    from auth import plan_required
+except ImportError:
+    plan_required = lambda *a, **kw: (lambda f: f)
 
 user_bp = Blueprint("v1_user", __name__, url_prefix="/api/v1/user")
 

api_v1/routes/valuebets.py

@@ -53,7 +53,7 @@ def valuebets():
         default: 0
     responses:
       200:
-        description: Value bets du jour
+        description: Value bets du jour avec météo et terrain (HRT-83)
       401:
         description: Token invalide
       403:
@@ -69,7 +69,7 @@ def valuebets():
 
     conn = get_db()
     try:
-        rows = []
+        rows_raw = []
         total = 0
 
         if table_exists(conn, "ml_predictions_cache"):
@@ -81,18 +81,73 @@ def valuebets():
             ).fetchone()
             total = count_row["cnt"] if count_row else 0
 
-            rows = conn.execute(
-                """SELECT race_label, hippodrome, discipline, distance, heure,
-                          horse_name, horse_number, odds, prob_top1, prob_top3,
-                          ml_score, recommendation, risque_label, risque_score
-                   FROM ml_predictions_cache
-                   WHERE date = ? AND is_value_bet = 1 AND odds >= ?
-                   ORDER BY ml_score DESC
-                   LIMIT ? OFFSET ?""",
-                (date_param, min_odds, limit, offset),
-            ).fetchall()
+            # LEFT JOIN pmu_courses (terrain) + pmu_meteo (météo) — HRT-83
+            has_courses = table_exists(conn, "pmu_courses")
+            has_meteo = table_exists(conn, "pmu_meteo")
+
+            if has_courses and has_meteo:
+                rows_raw = conn.execute(
+                    """SELECT m.race_label, m.hippodrome, m.discipline, m.distance, m.heure,
+                              m.horse_name, m.horse_number, m.odds, m.prob_top1, m.prob_top3,
+                              m.ml_score, m.recommendation, m.risque_label, m.risque_score,
+                              c.penetrometre_intitule,
+                              mt.nebulositecode, mt.nebulosite_court,
+                              mt.temperature, mt.force_vent
+                       FROM ml_predictions_cache m
+                       LEFT JOIN pmu_courses c
+                           ON c.date_programme = m.date
+                           AND c.num_reunion = m.num_reunion
+                           AND c.num_course = m.num_course
+                       LEFT JOIN pmu_meteo mt
+                           ON mt.date_programme = m.date
+                           AND mt.num_reunion = m.num_reunion
+                       WHERE m.date = ? AND m.is_value_bet = 1 AND m.odds >= ?
+                       ORDER BY m.ml_score DESC
+                       LIMIT ? OFFSET ?""",
+                    (date_param, min_odds, limit, offset),
+                ).fetchall()
+            else:
+                rows_raw = conn.execute(
+                    """SELECT race_label, hippodrome, discipline, distance, heure,
+                              horse_name, horse_number, odds, prob_top1, prob_top3,
+                              ml_score, recommendation, risque_label, risque_score
+                       FROM ml_predictions_cache
+                       WHERE date = ? AND is_value_bet = 1 AND odds >= ?
+                       ORDER BY ml_score DESC
+                       LIMIT ? OFFSET ?""",
+                    (date_param, min_odds, limit, offset),
+                ).fetchall()
+
+        from scoring_v2 import get_terrain_condition, compute_weather_impact
+
+        valuebets_list = []
+        for r in rows_raw:
+            row_dict = dict(r)
+            penetrometre = row_dict.pop("penetrometre_intitule", None) or ""
+            terrain_condition = (
+                get_terrain_condition(penetrometre) if penetrometre else "inconnu"
+            )
+            weather_data = None
+            if (
+                row_dict.get("nebulositecode") is not None
+                or row_dict.get("temperature") is not None
+            ):
+                weather_data = {
+                    "nebulositecode": row_dict.pop("nebulositecode", None),
+                    "nebulosite_court": row_dict.pop("nebulosite_court", None),
+                    "temperature": row_dict.pop("temperature", None),
+                    "force_vent": row_dict.pop("force_vent", None),
+                }
+            else:
+                row_dict.pop("nebulositecode", None)
+                row_dict.pop("nebulosite_court", None)
+                row_dict.pop("temperature", None)
+                row_dict.pop("force_vent", None)
+            weather_impact = compute_weather_impact(weather_data, terrain_condition)
+            row_dict["terrain_condition"] = terrain_condition
+            row_dict["weather_impact"] = weather_impact
+            valuebets_list.append(row_dict)
 
-        valuebets_list = [dict(r) for r in rows]
         pagination = paginate_query(valuebets_list, total, limit, offset)
 
         return jsonify(

api_v1/utils.py

@@ -16,8 +16,9 @@ DB_PATH = os.environ.get("TURF_SAAS_DB", "/home/h3r7/turf_saas/turf_saas.db")
 
 
 def get_db():
-    """Return a SQLite connection with Row factory."""
-    conn = sqlite3.connect(DB_PATH)
+    """Return a SQLite connection with Row factory (reads TURF_SAAS_DB dynamically)."""
+    db_path = os.environ.get("TURF_SAAS_DB", DB_PATH)
+    conn = sqlite3.connect(db_path)
     conn.row_factory = sqlite3.Row
     return conn
 

auth_db.py

@@ -8,11 +8,15 @@ HRT-79: migration Telegram columns
 import sqlite3
 import os
 
+# NOTE: DB_PATH kept for backward compat, but get_db() reads env at call time
+# so test isolation works correctly when TURF_SAAS_DB is set per-module.
 DB_PATH = os.environ.get("TURF_SAAS_DB", "/home/h3r7/turf_saas/turf_saas.db")
 
 
 def get_db():
-    conn = sqlite3.connect(DB_PATH)
+    # Read env dynamically so test overrides of TURF_SAAS_DB are respected
+    db_path = os.environ.get("TURF_SAAS_DB", DB_PATH)
+    conn = sqlite3.connect(db_path)
     conn.row_factory = sqlite3.Row
     return conn
 

dashboard_saas.html

@@ -259,6 +259,7 @@
     <a class="nav-item" id="nav-history" href="#history" onclick="showSection('history',this)"><span class="icon">📅</span> Historique <span class="plan-lock" id="lock-hist"></span></a>
     <a class="nav-item" id="nav-export" href="#export" onclick="showSection('export',this)"><span class="icon">📤</span> Export CSV <span class="plan-lock" id="lock-export"></span></a>
 
+    <a class="nav-item" id="nav-metrics" href="#metrics" onclick="showSection('metrics',this)"><span class="icon">📈</span> Métriques</a>
     <div class="nav-section">Paramètres</div>
     <a class="nav-item" id="nav-telegram" href="#telegram" onclick="showSection('telegram',this)"><span class="icon">📱</span> Alertes Telegram <span class="plan-lock" id="lock-tg"></span></a>
     <a class="nav-item" id="nav-api-token" href="#api-token" onclick="showSection('api-token',this)"><span class="icon">⚡</span> API Token <span class="plan-lock" id="lock-api"></span></a>
@@ -753,11 +754,59 @@
             </div>
         </div>
 
+<!-- ═══════════════════════════════════════════════════════ METRICS -->
+        <div id="section-metrics" class="dashboard-section" style="display:none">
+            <div class="section-header">
+                <h2>📈 Métriques de performance</h2>
+                <div style="display:flex;gap:8px;align-items:center">
+                    <select id="metrics-days" style="background:var(--dark3);color:var(--text);border:1px solid var(--border);border-radius:6px;padding:4px 10px;font-size:.85rem" onchange="loadMetrics()">
+                        <option value="7">7 jours</option>
+                        <option value="30" selected>30 jours</option>
+                        <option value="90">90 jours</option>
+                        <option value="365">365 jours</option>
+                    </select>
+                    <button class="btn btn-sm" onclick="loadMetrics()" style="padding:4px 14px;font-size:.85rem">🔄 Rafraîchir</button>
+                </div>
+            </div>
+
+            <!-- KPI cards -->
+            <div class="stats-grid" id="metrics-kpis" style="margin-bottom:20px">
+                <div class="stat-card"><div class="stat-label">Total paris</div><div class="stat-value" id="m-total-bets">—</div></div>
+                <div class="stat-card"><div class="stat-label">Précision</div><div class="stat-value" id="m-precision" style="color:var(--green)">—</div></div>
+                <div class="stat-card"><div class="stat-label">ROI</div><div class="stat-value" id="m-roi">—</div></div>
+                <div class="stat-card"><div class="stat-label">Mise totale</div><div class="stat-value" id="m-mise">—</div></div>
+                <div class="stat-card"><div class="stat-label">Gain total</div><div class="stat-value" id="m-gain">—</div></div>
+                <div class="stat-card"><div class="stat-label">Prédictions ML</div><div class="stat-value" id="m-ml-preds">—</div></div>
+                <div class="stat-card"><div class="stat-label">Value Bets ML</div><div class="stat-value" id="m-value-bets">—</div></div>
+                <div class="stat-card"><div class="stat-label">Prob. Top-3 moy.</div><div class="stat-value" id="m-prob-top3">—</div></div>
+            </div>
+
+            <!-- Charts row -->
+            <div style="display:grid;grid-template-columns:1fr 1fr;gap:16px;margin-bottom:16px">
+                <div class="form-card" style="padding:16px">
+                    <h3 style="font-size:.9rem;margin-bottom:12px">📊 ROI & Précision quotidiens</h3>
+                    <canvas id="chart-roi-daily" height="200"></canvas>
+                </div>
+                <div class="form-card" style="padding:16px">
+                    <h3 style="font-size:.9rem;margin-bottom:12px">💰 Cumul gains vs mises</h3>
+                    <canvas id="chart-cumul" height="200"></canvas>
+                </div>
+            </div>
+
+            <!-- Daily stats table -->
+            <div class="form-card">
+                <h3 style="font-size:.9rem;margin-bottom:12px">📋 Détail quotidien</h3>
+                <div id="metrics-table-wrap" style="overflow-x:auto">
+                    <div class="loader-row"><div class="spinner"></div> Chargement…</div>
+                </div>
+            </div>
+        </div>
     </div><!-- .content -->
 </div><!-- .main -->
 
 <div id="toast"></div>
 
+<script src="https://cdn.jsdelivr.net/npm/chart.js@4.4.0/dist/chart.umd.min.js"></script>
 <script>
 const API = '/api/v1';
 let currentUser = null;
@@ -793,7 +842,11 @@ function logout() {
     location.href = '/login';
 }
 
+// ⚠️ TEST_MODE — mettre false pour réactiver les restrictions de plan
+const TEST_MODE = true;
+
 function planLevel(plan) {
+    if (TEST_MODE) return 2; // pro level pour tous
     return { free: 0, premium: 1, pro: 2 }[plan] || 0;
 }
 
@@ -830,6 +883,7 @@ const SECTION_TITLES = {
     'api-token': 'API Token',
     'webhook': 'Webhook',
     'multi-account': 'Multi-compte',
+    'metrics': 'Métriques de performance',
 };
 
 function showSection(name, navEl) {
@@ -856,6 +910,7 @@ function onSectionShow(name) {
     if (name === 'api-token' && planAllows(currentPlan, 'premium')) loadApiToken();
     if (name === 'webhook' && planAllows(currentPlan, 'pro')) loadWebhook();
     if (name === 'multi-account' && planAllows(currentPlan, 'pro')) loadMultiAccount();
+    if (name === 'metrics') loadMetrics();
 }
 
 // ────────────────────────────────────────────────────────
@@ -1525,6 +1580,7 @@ function initNavFromHash() {
         'api-token': 'nav-api-token',
         'webhook': 'nav-webhook',
         'multi-account': 'nav-multi-account',
+            'metrics': 'nav-metrics',
     };
     if (hash && sectionMap[hash]) {
         setTimeout(() => {
@@ -1545,6 +1601,140 @@ window.showSection = function(name, navEl) {
     return _origShowSection(name, navEl);
 };
 
+
+// ────────────────────────────────────────────────────────
+// Métriques
+// ────────────────────────────────────────────────────────
+let chartRoiDaily = null;
+let chartCumul = null;
+
+async function loadMetrics() {
+    const days = document.getElementById('metrics-days')?.value || 30;
+    const data = await fetchJson(`${API}/metrics?days=${days}`);
+    if (!data) return;
+
+    // KPIs
+    const bm = data.bet_metrics || {};
+    const ml = data.ml_metrics || {};
+    setText('m-total-bets', bm.available ? bm.total_bets : '—');
+    setText('m-precision', bm.available ? bm.precision_pct + ' %' : '—');
+    const roi = bm.available ? bm.roi_pct : null;
+    const roiEl = document.getElementById('m-roi');
+    if (roiEl) {
+        roiEl.textContent = roi !== null ? roi + ' %' : '—';
+        roiEl.style.color = roi > 0 ? 'var(--green)' : roi < 0 ? '#f44' : 'var(--text)';
+    }
+    setText('m-mise', bm.available ? bm.mise_totale + ' €' : '—');
+    setText('m-gain', bm.available ? bm.gain_total + ' €' : '—');
+    setText('m-ml-preds', ml.available ? ml.total_predictions : '—');
+    setText('m-value-bets', ml.available ? ml.value_bets : '—');
+    setText('m-prob-top3', ml.available ? (ml.avg_prob_top3 * 100).toFixed(1) + ' %' : '—');
+
+    // Daily charts
+    const daily = data.daily || [];
+    const labels = daily.map(r => r.date ? r.date.slice(5) : '').reverse();
+    const roiArr = daily.map(r => r.roi_pct || 0).reverse();
+    const precArr = daily.map(r => r.precision_pct || 0).reverse();
+    const gainArr = daily.map(r => r.gain_total || 0).reverse();
+    const miseArr = daily.map(r => r.mise_totale || 0).reverse();
+
+    // Cumul gains
+    const cumulGain = gainArr.reduce((acc, v, i) => { acc.push((acc[i-1]||0) + v); return acc; }, []);
+    const cumulMise = miseArr.reduce((acc, v, i) => { acc.push((acc[i-1]||0) + v); return acc; }, []);
+
+    renderChartRoi(labels, roiArr, precArr);
+    renderChartCumul(labels, cumulGain, cumulMise);
+
+    // Table
+    renderMetricsTable(daily);
+}
+
+function setText(id, val) {
+    const el = document.getElementById(id);
+    if (el) el.textContent = val;
+}
+
+function renderChartRoi(labels, roiArr, precArr) {
+    const ctx = document.getElementById('chart-roi-daily');
+    if (!ctx) return;
+    if (chartRoiDaily) chartRoiDaily.destroy();
+    chartRoiDaily = new Chart(ctx, {
+        type: 'bar',
+        data: {
+            labels,
+            datasets: [
+                { label: 'ROI %', data: roiArr, backgroundColor: roiArr.map(v => v >= 0 ? 'rgba(0,200,83,.6)' : 'rgba(244,67,54,.6)'), yAxisID: 'y' },
+                { label: 'Précision %', data: precArr, type: 'line', borderColor: '#ffd600', backgroundColor: 'transparent', tension: 0.3, yAxisID: 'y2', pointRadius: 2 }
+            ]
+        },
+        options: {
+            responsive: true, maintainAspectRatio: true,
+            plugins: { legend: { labels: { color: '#ccc', font: { size: 11 } } } },
+            scales: {
+                x: { ticks: { color: '#888', maxTicksLimit: 10 }, grid: { color: 'rgba(255,255,255,.05)' } },
+                y: { ticks: { color: '#888' }, grid: { color: 'rgba(255,255,255,.05)' } },
+                y2: { position: 'right', ticks: { color: '#ffd600' }, grid: { display: false } }
+            }
+        }
+    });
+}
+
+function renderChartCumul(labels, cumulGain, cumulMise) {
+    const ctx = document.getElementById('chart-cumul');
+    if (!ctx) return;
+    if (chartCumul) chartCumul.destroy();
+    chartCumul = new Chart(ctx, {
+        type: 'line',
+        data: {
+            labels,
+            datasets: [
+                { label: 'Gain cumulé (€)', data: cumulGain, borderColor: '#00c853', backgroundColor: 'rgba(0,200,83,.1)', fill: true, tension: 0.3, pointRadius: 2 },
+                { label: 'Mise cumulée (€)', data: cumulMise, borderColor: '#aaa', backgroundColor: 'transparent', borderDash: [4,4], tension: 0.3, pointRadius: 0 }
+            ]
+        },
+        options: {
+            responsive: true, maintainAspectRatio: true,
+            plugins: { legend: { labels: { color: '#ccc', font: { size: 11 } } } },
+            scales: {
+                x: { ticks: { color: '#888', maxTicksLimit: 10 }, grid: { color: 'rgba(255,255,255,.05)' } },
+                y: { ticks: { color: '#888' }, grid: { color: 'rgba(255,255,255,.05)' } }
+            }
+        }
+    });
+}
+
+function renderMetricsTable(daily) {
+    const wrap = document.getElementById('metrics-table-wrap');
+    if (!wrap) return;
+    if (!daily.length) {
+        wrap.innerHTML = '<p style="color:var(--muted);padding:12px">Aucune donnée disponible pour cette période.</p>';
+        return;
+    }
+    const rows = daily.map(r => `
+        <tr>
+            <td>${r.date || '—'}</td>
+            <td>${r.total_bets ?? '—'}</td>
+            <td>${r.bets_gagne ?? '—'}</td>
+            <td style="color:${(r.precision_pct||0)>50?'var(--green)':'var(--text)'}">${r.precision_pct != null ? r.precision_pct.toFixed(1)+' %' : '—'}</td>
+            <td style="color:${(r.roi_pct||0)>0?'var(--green)':'#f44'}">${r.roi_pct != null ? (r.roi_pct>0?'+':'')+r.roi_pct.toFixed(2)+' %' : '—'}</td>
+            <td>${r.mise_totale != null ? r.mise_totale.toFixed(2)+' €' : '—'}</td>
+            <td style="color:${(r.gain_total||0)>0?'var(--green)':'#f44'}">${r.gain_total != null ? (r.gain_total>0?'+':'')+r.gain_total.toFixed(2)+' €' : '—'}</td>
+        </tr>`).join('');
+    wrap.innerHTML = `
+        <table style="width:100%;border-collapse:collapse;font-size:.85rem">
+            <thead><tr style="color:var(--muted);border-bottom:1px solid var(--border)">
+                <th style="padding:6px 8px;text-align:left">Date</th>
+                <th style="padding:6px 8px;text-align:left">Paris</th>
+                <th style="padding:6px 8px;text-align:left">Gagnés</th>
+                <th style="padding:6px 8px;text-align:left">Précision</th>
+                <th style="padding:6px 8px;text-align:left">ROI</th>
+                <th style="padding:6px 8px;text-align:left">Mise</th>
+                <th style="padding:6px 8px;text-align:left">Gain</th>
+            </tr></thead>
+            <tbody>${rows}</tbody>
+        </table>`;
+}
+
 loadDashboard().then(initNavFromHash);
 </script>
 </body>

leadhunter_api.py

@@ -30,7 +30,9 @@ from leadhunter_crm import (
     insert_leads,
     get_leads,
     get_lead_by_id,
+    update_lead,
     update_lead_status,
+    delete_lead,
     get_stats,
     export_csv,
     VALID_STATUSES,
@@ -285,6 +287,59 @@ def api_update_status(lead_id: int):
     )
 
 
+@app.route("/api/leads/<int:lead_id>", methods=["GET"])
+def api_get_lead(lead_id: int):
+    """
+    Retourne le detail d'un lead par son ID.
+
+    Returns:
+        JSON avec les informations completes du lead, ou 404.
+    """
+    lead = get_lead_by_id(lead_id)
+    if not lead:
+        return jsonify({"error": f"Lead id={lead_id} introuvable"}), 404
+    return jsonify(lead)
+
+
+@app.route("/api/leads/<int:lead_id>", methods=["PUT"])
+def api_put_lead(lead_id: int):
+    """
+    Met a jour completement un lead.
+
+    Body JSON : dict avec les champs a mettre a jour.
+    """
+    body = request.get_json(silent=True)
+    if not body:
+        return jsonify({"error": "Body JSON requis"}), 400
+
+    lead = get_lead_by_id(lead_id)
+    if not lead:
+        return jsonify({"error": f"Lead id={lead_id} introuvable"}), 404
+
+    success = update_lead(lead_id, body)
+    if not success:
+        return jsonify({"error": "Mise a jour echouee"}), 500
+
+    updated_lead = get_lead_by_id(lead_id)
+    return jsonify({"success": True, "lead": updated_lead})
+
+
+@app.route("/api/leads/<int:lead_id>", methods=["DELETE"])
+def api_delete_lead(lead_id: int):
+    """
+    Supprime un lead physiquement.
+    """
+    lead = get_lead_by_id(lead_id)
+    if not lead:
+        return jsonify({"error": f"Lead id={lead_id} introuvable"}), 404
+
+    success = delete_lead(lead_id)
+    if not success:
+        return jsonify({"error": "Suppression echouee"}), 500
+
+    return jsonify({"success": True, "lead_id": lead_id, "deleted": True})
+
+
 @app.route("/health", methods=["GET"])
 def health():
     """Healthcheck pour systemd / monitoring."""

leadhunter_crm.py

@@ -52,8 +52,24 @@ if not logger.handlers:
 # ─── Chemin DB ───────────────────────────────────────────────────────────────
 DB_PATH = "/home/h3r7/leadhunter.db"
 
-# Statuts valides pour un lead
-VALID_STATUSES = {"new", "contacted", "closed", "rejected"}
+# Statuts valides pour un lead (7 etapes Kanban)
+VALID_STATUSES = {
+    "nouveau",  # NOUVEAU
+    "contacte",  # CONTACTÉ
+    "interesse",  # INTÉRESSÉ
+    "demo_planifiee",  # DÉMO PLANIFIÉE
+    "proposition_envoyee",  # PROPOSITION ENVOYÉE
+    "negotiation",  # NÉGOCIATION
+    "signe_ou_refuse",  # SIGNÉ / REFUSÉ
+}
+
+# Mapping des anciens statuts vers les nouveaux (pour migration)
+LEGACY_STATUS_MAP = {
+    "new": "nouveau",
+    "contacted": "contacte",
+    "closed": "signe_ou_refuse",
+    "rejected": "signe_ou_refuse",
+}
 
 
 # ─── Initialisation ──────────────────────────────────────────────────────────
@@ -212,6 +228,77 @@ def get_lead_by_id(lead_id: int, db_path: str = DB_PATH) -> Optional[dict]:
         return None
 
 
+def update_lead(lead_id: int, data: dict, db_path: str = DB_PATH) -> bool:
+    """
+    Met à jour un lead avec les champs fournis.
+
+    Args:
+        lead_id: id du lead.
+        data: dict avec les champs a mettre a jour (name, address, phone, etc.)
+
+    Returns:
+        True si mise a jour reussie, False sinon.
+    """
+    allowed_fields = {
+        "name",
+        "address",
+        "phone",
+        "rating",
+        "reviews_count",
+        "website",
+        "score",
+        "rgpd_ok",
+        "status",
+    }
+    fields_to_update = {k: v for k, v in data.items() if k in allowed_fields}
+
+    if not fields_to_update:
+        logger.warning(
+            f"update_lead : aucun champ valide fourni pour lead_id={lead_id}"
+        )
+        return False
+
+    if (
+        "status" in fields_to_update
+        and fields_to_update["status"] not in VALID_STATUSES
+    ):
+        logger.warning(f"update_lead : statut invalide '{fields_to_update['status']}'")
+        return False
+
+    try:
+        with _get_conn(db_path) as conn:
+            set_clause = ", ".join([f"{k} = ?" for k in fields_to_update])
+            values = list(fields_to_update.values()) + [lead_id]
+            conn.execute(f"UPDATE leads SET {set_clause} WHERE id = ?", values)
+            logger.info(
+                f"Lead id={lead_id} mis a jour : {list(fields_to_update.keys())}"
+            )
+            return True
+    except Exception as e:
+        logger.warning(f"update_lead error : {e}")
+        return False
+
+
+def delete_lead(lead_id: int, db_path: str = DB_PATH) -> bool:
+    """
+    Supprime un lead physiquement.
+
+    Args:
+        lead_id: id du lead a supprimer.
+
+    Returns:
+        True si suppression reussie, False sinon.
+    """
+    try:
+        with _get_conn(db_path) as conn:
+            conn.execute("DELETE FROM leads WHERE id = ?", (lead_id,))
+            logger.info(f"Lead id={lead_id} supprime")
+            return True
+    except Exception as e:
+        logger.warning(f"delete_lead error : {e}")
+        return False
+
+
 def update_lead_status(lead_id: int, status: str, db_path: str = DB_PATH) -> bool:
     """
     Met à jour le statut d'un lead.

ml_feedback_saas.py

@@ -0,0 +1,600 @@
+#!/usr/bin/env python3
+"""
+ml_feedback_saas.py — Feedback loop ML pour turf_saas.
+Enregistre les paris virtuels XGBoost depuis ml_predictions_cache
+et met à jour les résultats/dividendes depuis pmu_partants + pmu_rapports.
+
+DB cible : /home/h3r7/turf_saas/turf_saas.db
+
+Stratégies :
+  A) xgboost_sg    : simple_gagnant — top1 ML par course, ml_score >= 70, mise 1€
+  B) xgboost_value : simple_gagnant — is_value_bet = 1, mise 1€
+  C) xgboost_sp    : simple_place   — top1 ML par course, ml_score >= 50, mise 1€
+  D) xgboost_2sur4 : deux_sur_quatre — top4 ML par course, 6 combos x 1€ = mise 6€
+
+Usage :
+  python3 ml_feedback_saas.py                      # Traite aujourd'hui
+  python3 ml_feedback_saas.py --backfill 2026-04-25
+  python3 ml_feedback_saas.py --date 2026-04-25
+"""
+
+import sqlite3
+import sys
+import logging
+import os
+from datetime import datetime, timedelta
+
+DB_PATH = "/home/h3r7/turf_saas/turf_saas.db"
+
+os.makedirs("/home/h3r7/turf_saas/logs", exist_ok=True)
+
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s [ml_feedback_saas] %(levelname)s %(message)s",
+    handlers=[
+        logging.FileHandler("/home/h3r7/turf_saas/logs/ml_feedback_saas.log"),
+        logging.StreamHandler(),
+    ],
+)
+log = logging.getLogger(__name__)
+
+
+# ─────────────────────────────────────────────────────────
+# UTILITAIRES
+# ─────────────────────────────────────────────────────────
+
+
+def get_db():
+    conn = sqlite3.connect(DB_PATH)
+    conn.row_factory = sqlite3.Row
+    return conn
+
+
+def pari_existe(cursor, date, num_reunion, num_course, numero1, type_pari, source_reco):
+    """Vérifie si un pari identique existe déjà (idempotence)."""
+    cursor.execute(
+        """
+        SELECT id FROM paris
+        WHERE date_course = ? AND source_reco = ?
+          AND type_pari = ? AND numero1 = ?
+          AND race_label = ?
+        """,
+        (date, source_reco, type_pari, numero1, f"R{num_reunion}C{num_course}"),
+    )
+    return cursor.fetchone() is not None
+
+
+def pari_2sur4_existe(cursor, date, num_reunion, num_course, source_reco):
+    """Vérifie si un pari 2sur4 existe déjà pour cette course."""
+    cursor.execute(
+        """
+        SELECT id FROM paris
+        WHERE date_course = ? AND source_reco = ?
+          AND race_label = ?
+        """,
+        (date, source_reco, f"R{num_reunion}C{num_course}"),
+    )
+    return cursor.fetchone() is not None
+
+
+def get_top_ml_par_course(cursor, date, n=4, min_score=0):
+    """Retourne les n meilleurs chevaux ML par course pour une date."""
+    cursor.execute(
+        """
+        SELECT num_reunion, num_course, horse_name, horse_number,
+               ml_score, odds, recommendation, is_value_bet,
+               race_label, race_name, hippodrome, heure,
+               discipline, distance
+        FROM ml_predictions_cache
+        WHERE date = ?
+          AND ml_score >= ?
+        ORDER BY num_reunion, num_course, ml_score DESC
+        """,
+        (date, min_score),
+    )
+    rows = cursor.fetchall()
+
+    courses = {}
+    for r in rows:
+        key = (r["num_reunion"], r["num_course"])
+        if key not in courses:
+            courses[key] = []
+        if len(courses[key]) < n:
+            courses[key].append(dict(r))
+    return courses
+
+
+# ─────────────────────────────────────────────────────────
+# STRATÉGIE A — Simple Gagnant top1 ML (score >= 70)
+# ─────────────────────────────────────────────────────────
+
+
+def save_ml_paris_sg(conn, date):
+    """Insère 1 pari simple_gagnant par course : top1 ML avec ml_score >= 70."""
+    cursor = conn.cursor()
+    courses = get_top_ml_par_course(cursor, date, n=1, min_score=70)
+    inseres = 0
+
+    for (num_reunion, num_course), chevaux in courses.items():
+        cheval = chevaux[0]
+        if pari_existe(
+            cursor,
+            date,
+            num_reunion,
+            num_course,
+            cheval["horse_number"],
+            "simple_gagnant",
+            "xgboost_sg",
+        ):
+            continue
+
+        cursor.execute(
+            """
+            INSERT INTO paris
+              (date_pari, date_course, race_name, race_label, hippodrome,
+               type_pari, chevaux, cheval1, numero1, cote, mise,
+               statut, gain, source_reco, model_source)
+            VALUES (?, ?, ?, ?, ?, 'simple_gagnant', ?, ?, ?, ?, 1.0,
+                    'EN_ATTENTE', 0.0, 'xgboost_sg', 'xgboost_v1')
+            """,
+            (
+                date,
+                date,
+                cheval.get("race_name") or "",
+                f"R{num_reunion}C{num_course}",
+                cheval.get("hippodrome") or "",
+                cheval["horse_name"],
+                cheval["horse_name"],
+                cheval["horse_number"],
+                cheval["odds"],
+            ),
+        )
+        inseres += 1
+
+    conn.commit()
+    log.info(f"[SG]     {date} → {inseres} paris simple_gagnant insérés (score>=70)")
+    return inseres
+
+
+# ─────────────────────────────────────────────────────────
+# STRATÉGIE B — Value Bet (is_value_bet = 1)
+# ─────────────────────────────────────────────────────────
+
+
+def save_ml_paris_value(conn, date):
+    """Insère 1 pari simple_gagnant pour chaque cheval is_value_bet=1."""
+    cursor = conn.cursor()
+    cursor.execute(
+        """
+        SELECT num_reunion, num_course, horse_name, horse_number,
+               ml_score, odds, race_label, race_name, hippodrome
+        FROM ml_predictions_cache
+        WHERE date = ? AND is_value_bet = 1
+        ORDER BY num_reunion, num_course, ml_score DESC
+        """,
+        (date,),
+    )
+    rows = [dict(r) for r in cursor.fetchall()]
+    inseres = 0
+
+    for r in rows:
+        if pari_existe(
+            cursor,
+            date,
+            r["num_reunion"],
+            r["num_course"],
+            r["horse_number"],
+            "simple_gagnant",
+            "xgboost_value",
+        ):
+            continue
+
+        cursor.execute(
+            """
+            INSERT INTO paris
+              (date_pari, date_course, race_name, race_label, hippodrome,
+               type_pari, chevaux, cheval1, numero1, cote, mise,
+               statut, gain, source_reco, model_source)
+            VALUES (?, ?, ?, ?, ?, 'simple_gagnant', ?, ?, ?, ?, 1.0,
+                    'EN_ATTENTE', 0.0, 'xgboost_value', 'xgboost_v1')
+            """,
+            (
+                date,
+                date,
+                r.get("race_name") or "",
+                r.get("race_label") or f"R{r['num_reunion']}C{r['num_course']}",
+                r.get("hippodrome") or "",
+                r["horse_name"],
+                r["horse_name"],
+                r["horse_number"],
+                r["odds"],
+            ),
+        )
+        inseres += 1
+
+    conn.commit()
+    log.info(f"[VALUE]  {date} → {inseres} paris value_bet insérés")
+    return inseres
+
+
+# ─────────────────────────────────────────────────────────
+# STRATÉGIE C — Simple Placé top1 ML (score >= 50)
+# ─────────────────────────────────────────────────────────
+
+
+def save_ml_paris_sp(conn, date):
+    """Insère 1 pari simple_place par course : top1 ML avec ml_score >= 50."""
+    cursor = conn.cursor()
+    courses = get_top_ml_par_course(cursor, date, n=1, min_score=50)
+    inseres = 0
+
+    for (num_reunion, num_course), chevaux in courses.items():
+        cheval = chevaux[0]
+        if pari_existe(
+            cursor,
+            date,
+            num_reunion,
+            num_course,
+            cheval["horse_number"],
+            "simple_place",
+            "xgboost_sp",
+        ):
+            continue
+
+        cursor.execute(
+            """
+            INSERT INTO paris
+              (date_pari, date_course, race_name, race_label, hippodrome,
+               type_pari, chevaux, cheval1, numero1, cote, mise,
+               statut, gain, source_reco, model_source)
+            VALUES (?, ?, ?, ?, ?, 'simple_place', ?, ?, ?, ?, 1.0,
+                    'EN_ATTENTE', 0.0, 'xgboost_sp', 'xgboost_v1')
+            """,
+            (
+                date,
+                date,
+                cheval.get("race_name") or "",
+                f"R{num_reunion}C{num_course}",
+                cheval.get("hippodrome") or "",
+                cheval["horse_name"],
+                cheval["horse_name"],
+                cheval["horse_number"],
+                cheval["odds"],
+            ),
+        )
+        inseres += 1
+
+    conn.commit()
+    log.info(f"[SP]     {date} → {inseres} paris simple_place insérés (score>=50)")
+    return inseres
+
+
+# ─────────────────────────────────────────────────────────
+# STRATÉGIE D — 2sur4 top4 ML (6 combinaisons x 1€)
+# ─────────────────────────────────────────────────────────
+
+
+def save_ml_paris_2sur4(conn, date):
+    """Insère 1 pari deux_sur_quatre par course : top4 ML, mise 6€."""
+    cursor = conn.cursor()
+    courses = get_top_ml_par_course(cursor, date, n=4, min_score=0)
+    inseres = 0
+
+    for (num_reunion, num_course), chevaux in courses.items():
+        if len(chevaux) < 4:
+            continue
+        if pari_2sur4_existe(cursor, date, num_reunion, num_course, "xgboost_2sur4"):
+            continue
+
+        top4 = chevaux[:4]
+        nums = [str(c["horse_number"]) for c in top4]
+        noms = [c["horse_name"] for c in top4]
+        chevaux_str = "/".join(noms)
+
+        cursor.execute(
+            """
+            INSERT INTO paris
+              (date_pari, date_course, race_name, race_label, hippodrome,
+               type_pari, chevaux, cheval1, numero1, cote, mise,
+               statut, gain, source_reco, model_source, commentaire)
+            VALUES (?, ?, ?, ?, ?, 'deux_sur_quatre', ?, ?, ?, 0.0, 6.0,
+                    'EN_ATTENTE', 0.0, 'xgboost_2sur4', 'xgboost_v1', ?)
+            """,
+            (
+                date,
+                date,
+                top4[0].get("race_name") or "",
+                f"R{num_reunion}C{num_course}",
+                top4[0].get("hippodrome") or "",
+                chevaux_str,
+                top4[0]["horse_name"],
+                top4[0]["horse_number"],
+                f"top4 ML: {'/'.join(nums)}",
+            ),
+        )
+        inseres += 1
+
+    conn.commit()
+    log.info(f"[2S4]    {date} → {inseres} paris deux_sur_quatre insérés")
+    return inseres
+
+
+# ─────────────────────────────────────────────────────────
+# UPDATE RÉSULTATS + DIVIDENDES
+# ─────────────────────────────────────────────────────────
+
+
+def update_ml_paris_results(conn, date):
+    """
+    Met à jour statut + gain (dividende PMU réel) pour tous les paris ML EN_ATTENTE.
+    Sources: pmu_partants (ordre_arrivee) + pmu_rapports (dividende_euro).
+    """
+    cursor = conn.cursor()
+
+    cursor.execute(
+        """
+        SELECT id, race_label, type_pari, numero1, chevaux, mise, source_reco, commentaire
+        FROM paris
+        WHERE date_course = ? AND statut = 'EN_ATTENTE'
+          AND source_reco LIKE 'xgboost%'
+        """,
+        (date,),
+    )
+    paris = [dict(r) for r in cursor.fetchall()]
+
+    if not paris:
+        log.info(f"[UPDATE] {date} → aucun pari ML EN_ATTENTE")
+        return 0
+
+    maj = 0
+    for pari in paris:
+        pari_id = pari["id"]
+        race_label = pari["race_label"] or ""
+        type_pari = pari["type_pari"]
+        numero1 = pari["numero1"]
+        mise = pari["mise"]
+
+        # Extraire num_reunion / num_course depuis le race_label "R{r}C{c}"
+        try:
+            parts = race_label.replace("R", "").split("C")
+            num_reunion = int(parts[0])
+            num_course = int(parts[1])
+        except Exception:
+            log.warning(f"[UPDATE] race_label invalide : {race_label}")
+            continue
+
+        if type_pari == "simple_gagnant":
+            cursor.execute(
+                """
+                SELECT ordre_arrivee FROM pmu_partants
+                WHERE date_programme = ? AND num_reunion = ?
+                  AND num_course = ? AND num_pmu = ?
+                """,
+                (date, num_reunion, num_course, numero1),
+            )
+            row = cursor.fetchone()
+            if not row or row["ordre_arrivee"] is None or row["ordre_arrivee"] == 0:
+                continue
+
+            gagne = row["ordre_arrivee"] == 1
+            gain = 0.0
+            if gagne:
+                cursor.execute(
+                    """
+                    SELECT dividende_euro FROM pmu_rapports
+                    WHERE date_programme = ? AND num_reunion = ?
+                      AND num_course = ? AND type_pari = 'SIMPLE_GAGNANT'
+                      AND CAST(combinaison AS INTEGER) = ?
+                      AND libelle NOT LIKE '%NP%'
+                    """,
+                    (date, num_reunion, num_course, numero1),
+                )
+                div = cursor.fetchone()
+                gain = div["dividende_euro"] if div and div["dividende_euro"] else 0.0
+
+            cursor.execute(
+                "UPDATE paris SET statut=?, gain=? WHERE id=?",
+                ("GAGNE" if gagne else "PERDU", gain, pari_id),
+            )
+            maj += 1
+
+        elif type_pari == "simple_place":
+            cursor.execute(
+                """
+                SELECT ordre_arrivee FROM pmu_partants
+                WHERE date_programme = ? AND num_reunion = ?
+                  AND num_course = ? AND num_pmu = ?
+                """,
+                (date, num_reunion, num_course, numero1),
+            )
+            row = cursor.fetchone()
+            if not row or not row["ordre_arrivee"]:
+                continue
+
+            gagne = 1 <= row["ordre_arrivee"] <= 3
+            gain = 0.0
+            if gagne:
+                cursor.execute(
+                    """
+                    SELECT dividende_euro FROM pmu_rapports
+                    WHERE date_programme = ? AND num_reunion = ?
+                      AND num_course = ? AND type_pari = 'SIMPLE_PLACE'
+                      AND CAST(combinaison AS INTEGER) = ?
+                      AND libelle NOT LIKE '%NP%'
+                    """,
+                    (date, num_reunion, num_course, numero1),
+                )
+                div = cursor.fetchone()
+                gain = div["dividende_euro"] if div and div["dividende_euro"] else 0.0
+
+            cursor.execute(
+                "UPDATE paris SET statut=?, gain=? WHERE id=?",
+                ("GAGNE" if gagne else "PERDU", gain, pari_id),
+            )
+            maj += 1
+
+        elif type_pari == "deux_sur_quatre":
+            # Récupère les 4 numéros depuis commentaire "top4 ML: n1/n2/n3/n4"
+            try:
+                nums_str = (
+                    pari["commentaire"].split(": ")[1]
+                    if pari.get("commentaire")
+                    else ""
+                )
+                nums_top4 = [int(n) for n in nums_str.split("/") if n.strip().isdigit()]
+            except Exception:
+                nums_top4 = []
+
+            if len(nums_top4) < 4:
+                # Fallback : reconstituer top4 depuis ml_predictions_cache
+                cursor.execute(
+                    """
+                    SELECT horse_number FROM ml_predictions_cache
+                    WHERE date = ? AND num_reunion = ? AND num_course = ?
+                    ORDER BY ml_score DESC LIMIT 4
+                    """,
+                    (date, num_reunion, num_course),
+                )
+                nums_top4 = [r["horse_number"] for r in cursor.fetchall()]
+
+            if len(nums_top4) < 2:
+                continue
+
+            cursor.execute(
+                """
+                SELECT combinaison, dividende_euro FROM pmu_rapports
+                WHERE date_programme = ? AND num_reunion = ?
+                  AND num_course = ? AND type_pari = 'DEUX_SUR_QUATRE'
+                  AND libelle NOT LIKE '%NP%'
+                """,
+                (date, num_reunion, num_course),
+            )
+            rapports = [dict(r) for r in cursor.fetchall()]
+            gain_total = 0.0
+
+            for rap in rapports:
+                try:
+                    n1, n2 = [int(x) for x in rap["combinaison"].split("-")]
+                except Exception:
+                    continue
+                if n1 in nums_top4 and n2 in nums_top4:
+                    gain_total += rap["dividende_euro"]
+
+            gagne = gain_total > 0
+            cursor.execute(
+                "UPDATE paris SET statut=?, gain=? WHERE id=?",
+                ("GAGNE" if gagne else "PERDU", round(gain_total, 2), pari_id),
+            )
+            maj += 1
+
+    conn.commit()
+    log.info(f"[UPDATE] {date} → {maj}/{len(paris)} paris ML mis à jour")
+    return maj
+
+
+# ─────────────────────────────────────────────────────────
+# STATS PAR STRATÉGIE
+# ─────────────────────────────────────────────────────────
+
+
+def get_feedback_stats(conn, date_debut=None, date_fin=None):
+    """Stats performances ML par stratégie (source_reco)."""
+    cursor = conn.cursor()
+    cursor.execute(
+        """
+        SELECT source_reco,
+               COUNT(*) as n_paris,
+               SUM(CASE WHEN statut='GAGNE' THEN 1 ELSE 0 END) as n_gagne,
+               SUM(CASE WHEN statut='PERDU' THEN 1 ELSE 0 END) as n_perdu,
+               SUM(CASE WHEN statut='EN_ATTENTE' THEN 1 ELSE 0 END) as n_attente,
+               ROUND(100.0 * SUM(CASE WHEN statut='GAGNE' THEN 1 ELSE 0 END)
+                     / NULLIF(SUM(CASE WHEN statut IN ('GAGNE','PERDU') THEN 1 ELSE 0 END), 0), 1) as win_rate_pct,
+               ROUND(SUM(gain), 2) as gain_total,
+               ROUND(SUM(mise), 2) as mise_totale,
+               ROUND(SUM(gain) - SUM(mise), 2) as roi_net
+        FROM paris
+        WHERE source_reco LIKE 'xgboost%'
+          AND (:debut IS NULL OR date_course >= :debut)
+          AND (:fin IS NULL OR date_course <= :fin)
+        GROUP BY source_reco
+        ORDER BY source_reco
+        """,
+        {"debut": date_debut, "fin": date_fin},
+    )
+    return [dict(r) for r in cursor.fetchall()]
+
+
+# ─────────────────────────────────────────────────────────
+# PIPELINE COMPLET
+# ─────────────────────────────────────────────────────────
+
+
+def run(date):
+    """Enregistre les paris ML du jour + met à jour les résultats de J-1."""
+    conn = get_db()
+    log.info(f"=== ml_feedback_saas.run({date}) ===")
+
+    # 1. Enregistre les paris ML pour la date (depuis le cache du jour)
+    sg = save_ml_paris_sg(conn, date)
+    vb = save_ml_paris_value(conn, date)
+    sp = save_ml_paris_sp(conn, date)
+    s4 = save_ml_paris_2sur4(conn, date)
+    log.info(f"[SAVE]   {date} → total insérés : SG={sg} VALUE={vb} SP={sp} 2S4={s4}")
+
+    # 2. Met à jour les résultats de J-1 (résultats PMU disponibles)
+    yesterday = (datetime.strptime(date, "%Y-%m-%d") - timedelta(days=1)).strftime(
+        "%Y-%m-%d"
+    )
+    maj = update_ml_paris_results(conn, yesterday)
+    log.info(f"[UPDATE] {yesterday} → {maj} paris mis à jour")
+
+    conn.close()
+    return {"inseres": {"sg": sg, "value": vb, "sp": sp, "2sur4": s4}, "maj": maj}
+
+
+def backfill(date):
+    """Backfill : insère ET met à jour les résultats pour une date passée."""
+    conn = get_db()
+    log.info(f"=== ml_feedback_saas.backfill({date}) ===")
+
+    sg = save_ml_paris_sg(conn, date)
+    vb = save_ml_paris_value(conn, date)
+    sp = save_ml_paris_sp(conn, date)
+    s4 = save_ml_paris_2sur4(conn, date)
+    log.info(f"[SAVE]   {date} → SG={sg} VALUE={vb} SP={sp} 2S4={s4}")
+
+    maj = update_ml_paris_results(conn, date)
+    log.info(f"[UPDATE] {date} → {maj} paris mis à jour")
+
+    conn.close()
+    return sg + vb + sp + s4, maj
+
+
+# ─────────────────────────────────────────────────────────
+# MAIN
+# ─────────────────────────────────────────────────────────
+
+if __name__ == "__main__":
+    if "--backfill" in sys.argv:
+        idx = sys.argv.index("--backfill")
+        date = sys.argv[idx + 1] if idx + 1 < len(sys.argv) else None
+        if not date:
+            print("Usage: python3 ml_feedback_saas.py --backfill YYYY-MM-DD")
+            sys.exit(1)
+        inseres, maj = backfill(date)
+        print(f"Backfill {date} : {inseres} paris insérés, {maj} mis à jour")
+
+    elif "--date" in sys.argv:
+        idx = sys.argv.index("--date")
+        date = sys.argv[idx + 1] if idx + 1 < len(sys.argv) else None
+        if not date:
+            print("Usage: python3 ml_feedback_saas.py --date YYYY-MM-DD")
+            sys.exit(1)
+        result = run(date)
+        total = sum(result["inseres"].values())
+        print(f"Run {date} : {total} paris insérés, {result['maj']} mis à jour")
+
+    else:
+        result = run(datetime.now().strftime("%Y-%m-%d"))
+        total = sum(result["inseres"].values())
+        print(f"Run today : {total} paris insérés, {result['maj']} mis à jour")

org_db.py

@@ -0,0 +1,72 @@
+#!/usr/bin/env python3
+"""
+Org DB — Multi-compte / Organisations Pro
+Sprint: HRT-82
+
+Migration idempotente : crée les tables organizations et org_members
+dans turf_saas.db si elles n'existent pas.
+
+Run une seule fois :
+    ./venv/bin/python org_db.py
+"""
+
+import sqlite3
+import os
+import logging
+
+DB_PATH = os.environ.get("TURF_SAAS_DB", "/home/h3r7/turf_saas/turf_saas.db")
+logger = logging.getLogger("turf_saas.org_db")
+
+
+def get_db():
+    conn = sqlite3.connect(DB_PATH)
+    conn.row_factory = sqlite3.Row
+    conn.execute("PRAGMA foreign_keys = ON")
+    return conn
+
+
+def migrate_org_tables():
+    """
+    Migration idempotente : crée organizations + org_members.
+
+    - organizations : 1 org max par owner (enforced en Python + UNIQUE owner_id)
+    - org_members   : max 5 membres totaux (owner inclus, enforced en Python)
+    - UNIQUE(org_id, user_id) empêche les doublons de membres
+    """
+    conn = get_db()
+    c = conn.cursor()
+
+    c.executescript("""
+        CREATE TABLE IF NOT EXISTS organizations (
+            id          TEXT    PRIMARY KEY,
+            owner_id    TEXT    NOT NULL UNIQUE,
+            name        TEXT    NOT NULL,
+            max_members INTEGER NOT NULL DEFAULT 5,
+            created_at  DATETIME NOT NULL DEFAULT (datetime('now'))
+        );
+
+        CREATE TABLE IF NOT EXISTS org_members (
+            id          INTEGER PRIMARY KEY AUTOINCREMENT,
+            org_id      TEXT    NOT NULL REFERENCES organizations(id) ON DELETE CASCADE,
+            user_id     TEXT    NOT NULL,
+            role        TEXT    NOT NULL DEFAULT 'member'
+                        CHECK(role IN ('owner', 'member')),
+            invited_at  DATETIME NOT NULL DEFAULT (datetime('now')),
+            joined_at   DATETIME,
+            UNIQUE(org_id, user_id)
+        );
+
+        CREATE INDEX IF NOT EXISTS idx_org_owner     ON organizations(owner_id);
+        CREATE INDEX IF NOT EXISTS idx_orgmem_org    ON org_members(org_id);
+        CREATE INDEX IF NOT EXISTS idx_orgmem_user   ON org_members(user_id);
+    """)
+
+    conn.commit()
+    conn.close()
+    logger.info("[org_db] Tables organizations + org_members créées/vérifiées.")
+    print("[org_db] Migration OK: organizations, org_members.")
+
+
+if __name__ == "__main__":
+    logging.basicConfig(level=logging.INFO)
+    migrate_org_tables()

portal_server.py

@@ -19,9 +19,13 @@ SAAS_DIR = "/home/h3r7/turf_saas"
 try:
     from saas_auth import auth_bp
     from saas_api_v1 import api_v1_bp
+    from api_v1.routes.ml_feedback import ml_feedback_bp
+    from api_v1.routes.metrics import metrics_bp
 
     app.register_blueprint(auth_bp)
     app.register_blueprint(api_v1_bp)
+    app.register_blueprint(ml_feedback_bp)
+    app.register_blueprint(metrics_bp)
     print("[portal] SaaS auth & API v1 blueprints registered ✅")
 except Exception as e:
     print(f"[portal] Warning: could not register SaaS blueprints: {e}")
@@ -352,6 +356,29 @@ def template_complet():
     return send_from_directory("/home/h3r7/turf_saas", "template_complet.html")
 
 
+@app.route("/leadhunter/clients/le-big-ben/")
+@app.route("/leadhunter/clients/le-big-ben")
+def big_ben():
+    return send_from_directory(
+        "/home/h3r7/turf_saas/templates/leadhunter/clients/le-big-ben", "index.html"
+    )
+
+
+@app.route("/leadhunter/clients/le-big-ben/sitemap.xml")
+def big_ben_sitemap():
+    return send_from_directory(
+        "/home/h3r7/turf_saas/templates/leadhunter/clients/le-big-ben",
+        "sitemap.xml",
+        mimetype="application/xml",
+    )
+
+
+@app.route("/formation/ai102")
+@app.route("/formation/ai102/")
+def certif_ai102():
+    return send_from_directory("/home/h3r7/turf_saas/pitch", "certif-ai102.html")
+
+
 @app.route("/boite_a_idees_dashboard")
 def boite_a_idees_dashboard():
     return send_from_directory("/home/h3r7/turf_saas", "boite_a_idees_dashboard.html")

requirements.txt

@@ -31,3 +31,6 @@ python-dotenv==1.1.0
 
 # Utilities
 python-dateutil==2.9.0
+
+# Hyperparameter optimization (ML ensemble tuning — HRT-136)
+optuna>=4.0.0

saas_api_v1.py

@@ -268,15 +268,65 @@ try:
     @api_v1_bp.record_once
     def _init_jwt(state):
         app = state.app
-        if not app.config.get('JWT_SECRET_KEY'):
+        if not app.config.get("JWT_SECRET_KEY"):
             import os
-            app.config['JWT_SECRET_KEY'] = os.environ.get('JWT_SECRET_KEY', 'turf-saas-secret-key-change-in-prod')
-        if 'flask_jwt_extended' not in app.extensions:
+
+            app.config["JWT_SECRET_KEY"] = os.environ.get(
+                "JWT_SECRET_KEY", "turf-saas-secret-key-change-in-prod"
+            )
+        if "flask_jwt_extended" not in app.extensions:
             JWTManager(app)
 
     # Register billing blueprint with url_prefix='/billing'
     # (parent api_v1_bp has '/api/v1', so result is /api/v1/billing/*)
-    api_v1_bp.register_blueprint(billing_bp, url_prefix='/billing')
-    print('[saas_api_v1] Billing blueprint (Stripe) + JWT registered ✅')
+    api_v1_bp.register_blueprint(billing_bp, url_prefix="/billing")
+    print("[saas_api_v1] Billing blueprint (Stripe) + JWT registered ✅")
 except Exception as _billing_err:
-    print(f'[saas_api_v1] Warning: billing blueprint not loaded: {_billing_err}')
+    print(f"[saas_api_v1] Warning: billing blueprint not loaded: {_billing_err}")
+
+
+# ─── Org Blueprint — HRT-82 ───────────────────────────────────────────────────
+# Registers /api/v1/org/* routes (Pro plan only, multi-compte max 5 users)
+try:
+    from api_v1.routes.org import org_bp
+
+    @api_v1_bp.record_once
+    def _register_org_bp(state):
+        app = state.app
+        app.register_blueprint(org_bp)
+
+    print("[saas_api_v1] Org blueprint (multi-compte Pro) registered ✅")
+except Exception as _org_err:
+    print(f"[saas_api_v1] Warning: org blueprint not loaded: {_org_err}")
+
+
+# ─── User Blueprint — HRT-79 (Telegram) + HRT-80 (API Token + Webhook) ───────
+# Registers /api/v1/user/* routes (Premium+ for telegram, Pro for api-token/webhook)
+try:
+    from api_v1.routes.user import user_bp
+    from api_v1.routes.user_tokens import user_tokens_bp
+
+    @api_v1_bp.record_once
+    def _register_user_bp(state):
+        app = state.app
+        app.register_blueprint(user_bp)
+        app.register_blueprint(user_tokens_bp)
+
+    print('[saas_api_v1] User blueprint (Telegram config + API token + Webhook) registered ✅')
+except Exception as _user_err:
+    print(f'[saas_api_v1] Warning: user blueprints not loaded: {_user_err}')
+
+
+# ─── History Blueprint — HRT-81 ───────────────────────────────────────────────
+# Registers /api/v1/history route (Free:7j, Premium:90j, Pro:illimité)
+try:
+    from api_v1.routes.history import history_bp
+
+    @api_v1_bp.record_once
+    def _register_history_bp(state):
+        app = state.app
+        app.register_blueprint(history_bp)
+
+    print('[saas_api_v1] History blueprint (plan-limited history) registered ✅')
+except Exception as _history_err:
+    print(f'[saas_api_v1] Warning: history blueprint not loaded: {_history_err}')

scoring_v2.py

@@ -11,29 +11,34 @@ import re
 from datetime import datetime
 
 DB_PATH = "/home/h3r7/turf_saas/turf_saas.db"
-HEADERS = {'User-Agent': 'Mozilla/5.0', 'Accept': 'application/json'}
+HEADERS = {"User-Agent": "Mozilla/5.0", "Accept": "application/json"}
+
 
 def get_cote_from_db(horse_name, date_course):
     """Recupere la cote depuis la table predictions (plus recente et non nulle)"""
     conn = sqlite3.connect(DB_PATH)
     conn.row_factory = sqlite3.Row
-    c = conn.execute("""
+    c = conn.execute(
+        """
         SELECT odds FROM predictions 
         WHERE date=? AND horse_name LIKE ? AND odds > 0 
         ORDER BY created_at DESC LIMIT 1
-    """, (date_course, f"%{horse_name}%"))
+    """,
+        (date_course, f"%{horse_name}%"),
+    )
     r = c.fetchone()
     conn.close()
-    return r['odds'] if r else 0
+    return r["odds"] if r else 0
+
 
 def parse_musique(musique):
     if not musique:
         return {}
-    clean = re.sub(r'\(\d+\)', '', musique)
-    resultats = re.findall(r'(\d+|D|0)([amphsc]?)', clean)
+    clean = re.sub(r"\(\d+\)", "", musique)
+    resultats = re.findall(r"(\d+|D|0)([amphsc]?)", clean)
     positions = []
     for pos, disc in resultats[:10]:
-        positions.append(99 if pos == 'D' else int(pos))
+        positions.append(99 if pos == "D" else int(pos))
     if not positions:
         return {}
     nb_courses = len(positions)
@@ -41,29 +46,102 @@ def parse_musique(musique):
     nb_places = sum(1 for p in positions if 1 <= p <= 3)
     recentes = [p for p in positions[:3] if p != 99]
     forme_recente = sum(recentes) / len(recentes) if recentes else 99
-    tendance = (sum(positions[-4:]) / 4 - sum(positions[:4]) / 4) if len(positions) >= 4 else 0
+    tendance = (
+        (sum(positions[-4:]) / 4 - sum(positions[:4]) / 4) if len(positions) >= 4 else 0
+    )
     return {
-        'forme_recente': round(forme_recente, 1),
-        'tendance': round(tendance, 1),
-        'tx_victoire': round(nb_victoires / nb_courses * 100, 1) if nb_courses else 0,
-        'tx_place': round(nb_places / nb_courses * 100, 1) if nb_courses else 0,
+        "forme_recente": round(forme_recente, 1),
+        "tendance": round(tendance, 1),
+        "tx_victoire": round(nb_victoires / nb_courses * 100, 1) if nb_courses else 0,
+        "tx_place": round(nb_places / nb_courses * 100, 1) if nb_courses else 0,
     }
 
-def score_cheval_v2(p, all_participants, today):
+
+def get_terrain_condition(penetrometre_intitule: str | None) -> str:
+    """Normalise le pénétromètre PMU en condition terrain standardisée."""
+    if not penetrometre_intitule:
+        return "inconnu"
+    val = penetrometre_intitule.upper()
+    if any(k in val for k in ("TRES BON", "TRÈS BON", "FERME", "FIRM")):
+        return "bon"
+    if any(k in val for k in ("BON", "GOOD", "STANDARD")):
+        return "bon"
+    if any(k in val for k in ("SOUPLE", "YIELDING", "COLLANT")):
+        return "souple"
+    if any(k in val for k in ("LOURD", "HEAVY", "TRES SOUPLE", "TRÈS SOUPLE")):
+        return "lourd"
+    if any(k in val for k in ("SOFT", "MOU")):
+        return "souple"
+    return "inconnu"
+
+
+def compute_weather_impact(weather_data: dict | None, terrain_condition: str) -> float:
+    """
+    Calcule un score d'impact météo/terrain sur [−5, +5].
+    weather_data keys attendues : nebulositecode, temperature, force_vent
+    terrain_condition : 'bon' | 'souple' | 'lourd' | 'inconnu'
+    Retourne un delta de score ML (positif = favorable, négatif = défavorable).
+    """
+    if not weather_data:
+        return 0.0
+
+    delta = 0.0
+
+    # Terrain
+    if terrain_condition == "lourd":
+        delta -= 3.0
+    elif terrain_condition == "souple":
+        delta -= 1.5
+    elif terrain_condition == "bon":
+        delta += 1.0
+    # inconnu → 0
+
+    # Vent
+    force_vent = weather_data.get("force_vent") or 0
+    try:
+        force_vent = float(force_vent)
+    except (TypeError, ValueError):
+        force_vent = 0.0
+    if force_vent >= 50:
+        delta -= 2.0
+    elif force_vent >= 30:
+        delta -= 1.0
+
+    # Températures extrêmes
+    temperature = weather_data.get("temperature")
+    try:
+        temperature = float(temperature) if temperature is not None else None
+    except (TypeError, ValueError):
+        temperature = None
+    if temperature is not None:
+        if temperature <= 0:
+            delta -= 1.0
+        elif temperature >= 35:
+            delta -= 1.0
+
+    return round(max(-5.0, min(5.0, delta)), 2)
+
+
+def score_cheval_v2(p, all_participants, today, weather_data=None):
+    """
+    Score un cheval pour le modèle V2.
+    weather_data (optionnel) : dict issu de pmu_meteo pour cette réunion.
+    Backward-compatible : weather_data=None → comportement identique à avant HRT-83.
+    """
     score = 0
     details = {}
 
     # 1. COTE - Essaye PMU API, sinon DB
-    horse_name = p.get('nom', '')
+    horse_name = p.get("nom", "")
     cote = 0
 
     # Essayer d'abord depuis l'API PMU
-    rapport = p.get('dernierRapportDirect', {})
+    rapport = p.get("dernierRapportDirect", {})
     if rapport:
-        cote = rapport.get('rapport', 0)
+        cote = rapport.get("rapport", 0)
     if not cote:
-        rapport_ref = p.get('dernierRapportReference', {})
-        cote = rapport_ref.get('rapport', 0) if rapport_ref else 0
+        rapport_ref = p.get("dernierRapportReference", {})
+        cote = rapport_ref.get("rapport", 0) if rapport_ref else 0
 
     # Fallback: aller chercher dans la DB
     if not cote or cote == 0:
@@ -75,94 +153,136 @@ def score_cheval_v2(p, all_participants, today):
 
     score_cote = max(2, min(10, 20 / (1 + cote * 0.15))) if cote > 0 else 2
     score += score_cote
-    details['cote'] = round(cote, 1)
-    details['score_cote'] = round(score_cote, 1)
+    details["cote"] = round(cote, 1)
+    details["score_cote"] = round(score_cote, 1)
 
     # 2. FORME - AUGMENTE a 30 pts
-    musique_stats = parse_musique(p.get('musique', ''))
-    forme = musique_stats.get('forme_recente', 99)
-    score_forme = 30 if forme <= 1 else 25 if forme <= 2 else 20 if forme <= 3 else 15 if forme <= 5 else 8 if forme <= 8 else 0
+    musique_stats = parse_musique(p.get("musique", ""))
+    forme = musique_stats.get("forme_recente", 99)
+    score_forme = (
+        30
+        if forme <= 1
+        else 25
+        if forme <= 2
+        else 20
+        if forme <= 3
+        else 15
+        if forme <= 5
+        else 8
+        if forme <= 8
+        else 0
+    )
     score += score_forme
-    details['forme_recente'] = forme
-    details['score_forme'] = score_forme
+    details["forme_recente"] = forme
+    details["score_forme"] = score_forme
 
     # 3. TAUX VICTOIRE (15 pts)
-    nb_courses_total = p.get('nombreCourses', 0)
-    nb_victoires_total = p.get('nombreVictoires', 0)
+    nb_courses_total = p.get("nombreCourses", 0)
+    nb_victoires_total = p.get("nombreVictoires", 0)
     tx_vic = (nb_victoires_total / nb_courses_total * 100) if nb_courses_total else 0
     score_vic = min(15, tx_vic * 0.5)
     score += score_vic
-    details['tx_victoire'] = round(tx_vic, 1)
-    details['score_victoire'] = round(score_vic, 1)
+    details["tx_victoire"] = round(tx_vic, 1)
+    details["score_victoire"] = round(score_vic, 1)
 
     # 4. TAUX PLACE (15 pts)
-    nb_places_total = p.get('nombrePlaces', 0)
+    nb_places_total = p.get("nombrePlaces", 0)
     tx_place = (nb_places_total / nb_courses_total * 100) if nb_courses_total else 0
     score_place = min(15, tx_place * 0.2)
     score += score_place
-    details['tx_place'] = round(tx_place, 1)
-    details['score_place'] = round(score_place, 1)
+    details["tx_place"] = round(tx_place, 1)
+    details["score_place"] = round(score_place, 1)
 
     # 5. REDUCTION KM (10 pts)
-    rk = p.get('reductionKilometrique', 0)
-    all_rk = [x.get('reductionKilometrique', 0) for x in all_participants if x.get('reductionKilometrique', 0) > 0]
+    rk = p.get("reductionKilometrique", 0)
+    all_rk = [
+        x.get("reductionKilometrique", 0)
+        for x in all_participants
+        if x.get("reductionKilometrique", 0) > 0
+    ]
     if rk > 0 and all_rk:
-        score_rk = 10 * (1 - (rk - min(all_rk)) / (max(all_rk) - min(all_rk))) if max(all_rk) > min(all_rk) else 5
+        score_rk = (
+            10 * (1 - (rk - min(all_rk)) / (max(all_rk) - min(all_rk)))
+            if max(all_rk) > min(all_rk)
+            else 5
+        )
     else:
         score_rk = 0
     score += score_rk
-    details['rk'] = rk
-    details['score_rk'] = round(score_rk, 1)
+    details["rk"] = rk
+    details["score_rk"] = round(score_rk, 1)
 
     # 6. TENDANCE (10 pts)
-    tendance = musique_stats.get('tendance', 0)
+    tendance = musique_stats.get("tendance", 0)
     score_tendance = min(10, max(0, 5 + tendance))
     score += score_tendance
-    details['tendance'] = tendance
-    details['score_tendance'] = round(score_tendance, 1)
+    details["tendance"] = tendance
+    details["score_tendance"] = round(score_tendance, 1)
 
     # 7. AVIS ENTRAINEUR (5 pts)
-    avis = p.get('avisEntraineur', 'NEUTRE')
-    score_avis = {'POSITIF': 5, 'TRES_POSITIF': 5, 'NEUTRE': 2, 'NEGATIF': 0, 'TRES_NEGATIF': 0}.get(avis, 2)
+    avis = p.get("avisEntraineur", "NEUTRE")
+    score_avis = {
+        "POSITIF": 5,
+        "TRES_POSITIF": 5,
+        "NEUTRE": 2,
+        "NEGATIF": 0,
+        "TRES_NEGATIF": 0,
+    }.get(avis, 2)
     score += score_avis
-    details['avis_entraineur'] = avis
-    details['score_avis'] = score_avis
+    details["avis_entraineur"] = avis
+    details["score_avis"] = score_avis
 
     # 8. BONUS OUTSIDER (5 pts)
     bonus_outsider = 5 if forme <= 3 and cote >= 10 else 0
     score += bonus_outsider
-    details['bonus_outsider'] = bonus_outsider
+    details["bonus_outsider"] = bonus_outsider
 
     # Driver change penalty
-    if p.get('driverChange', False):
+    if p.get("driverChange", False):
         score -= 3
-        details['driver_change'] = True
+        details["driver_change"] = True
 
-    details['score_total'] = round(score, 1)
-    details['musique'] = p.get('musique', '')
-    details['nb_victoires'] = nb_victoires_total
-    details['nb_places'] = nb_places_total
-    details['nb_courses'] = nb_courses_total
+    # 9. METEO & TERRAIN (HRT-83) — premium feature, weather_data=None → skip
+    penetrometre = p.get("penetrometre_intitule", "") or ""
+    terrain_condition = (
+        get_terrain_condition(penetrometre) if penetrometre else "inconnu"
+    )
+    weather_impact = 0.0
+    if weather_data is not None:
+        weather_impact = compute_weather_impact(weather_data, terrain_condition)
+        score += weather_impact
+    details["terrain_condition"] = terrain_condition
+    details["weather_impact"] = weather_impact
+
+    details["score_total"] = round(score, 1)
+    details["musique"] = p.get("musique", "")
+    details["nb_victoires"] = nb_victoires_total
+    details["nb_places"] = nb_places_total
+    details["nb_courses"] = nb_courses_total
 
     return round(score, 1), details
 
+
 def get_ze2sur4_combinaisons(top4):
     combinaisons = []
     for i in range(4):
-        for j in range(i+1, 4):
+        for j in range(i + 1, 4):
             c1 = top4[i]
             c2 = top4[j]
-            combinaisons.append({
-                'cheval1': c1['nom'],
-                'numero1': c1['numero'],
-                'cheval2': c2['nom'],
-                'numero2': c2['numero'],
-                'mise': 1.0,
-            })
+            combinaisons.append(
+                {
+                    "cheval1": c1["nom"],
+                    "numero1": c1["numero"],
+                    "cheval2": c2["nom"],
+                    "numero2": c2["numero"],
+                    "mise": 1.0,
+                }
+            )
     return combinaisons
 
+
 def build_recommendations_v2(scored_horses):
-    ranked = sorted(scored_horses, key=lambda x: x['score'], reverse=True)
+    ranked = sorted(scored_horses, key=lambda x: x["score"], reverse=True)
     if len(ranked) < 4:
         return None
 
@@ -170,39 +290,58 @@ def build_recommendations_v2(scored_horses):
     top4_list = ranked[:4]
 
     def confiance(s):
-        return "FORTE" if s >= 55 else "BONNE" if s >= 45 else "MOYENNE" if s >= 35 else "FAIBLE"
+        return (
+            "FORTE"
+            if s >= 55
+            else "BONNE"
+            if s >= 45
+            else "MOYENNE"
+            if s >= 35
+            else "FAIBLE"
+        )
 
     ze2_combinaisons = get_ze2sur4_combinaisons(top4_list)
     mise_ze2 = len(ze2_combinaisons) * 1.0
 
     return {
-        'simple_gagnant': {
-            'cheval': top1['nom'], 'numero': top1['numero'], 'cote': top1['details']['cote'],
-            'score': top1['score'], 'confiance': confiance(top1['score']),
-            'mise_suggeree': 2.0, 'gain_potentiel': round(2.0 * top1['details']['cote'], 2)
+        "simple_gagnant": {
+            "cheval": top1["nom"],
+            "numero": top1["numero"],
+            "cote": top1["details"]["cote"],
+            "score": top1["score"],
+            "confiance": confiance(top1["score"]),
+            "mise_suggeree": 2.0,
+            "gain_potentiel": round(2.0 * top1["details"]["cote"], 2),
         },
-        'ze2_sur_4': {
-            'top4': [{'nom': h['nom'], 'numero': h['numero']} for h in top4_list],
-            'combinaisons': ze2_combinaisons,
-            'mise_totale': mise_ze2,
-            'nb_combinaisons': len(ze2_combinaisons),
-            'confiance': confiance((top1['score'] + top2['score'] + top3['score'] + top4['score']) / 4),
-            'explication': 'Jouer les 6 combinaisons de 2 chevaux parmi les 4 premiers'
+        "ze2_sur_4": {
+            "top4": [{"nom": h["nom"], "numero": h["numero"]} for h in top4_list],
+            "combinaisons": ze2_combinaisons,
+            "mise_totale": mise_ze2,
+            "nb_combinaisons": len(ze2_combinaisons),
+            "confiance": confiance(
+                (top1["score"] + top2["score"] + top3["score"] + top4["score"]) / 4
+            ),
+            "explication": "Jouer les 6 combinaisons de 2 chevaux parmi les 4 premiers",
         },
-        'outsider': _find_outsider(ranked),
-        'budget_total': 2.0 + mise_ze2,
+        "outsider": _find_outsider(ranked),
+        "budget_total": 2.0 + mise_ze2,
     }
 
+
 def _find_outsider(ranked):
     for h in ranked[3:7]:
-        d = h['details']
-        if d['cote'] >= 12 and d['forme_recente'] <= 4 and d['bonus_outsider'] == 5:
+        d = h["details"]
+        if d["cote"] >= 12 and d["forme_recente"] <= 4 and d["bonus_outsider"] == 5:
             return {
-                'cheval': h['nom'], 'numero': h['numero'], 'cote': d['cote'],
-                'mise_suggeree': 1.0, 'gain_potentiel': round(1.0 * d['cote'], 2)
+                "cheval": h["nom"],
+                "numero": h["numero"],
+                "cote": d["cote"],
+                "mise_suggeree": 1.0,
+                "gain_potentiel": round(1.0 * d["cote"], 2),
             }
     return None
 
+
 def save_to_db(scored_horses, date_course, hippodrome, libelle):
     conn = sqlite3.connect(DB_PATH)
     cursor = conn.cursor()
@@ -210,44 +349,72 @@ def save_to_db(scored_horses, date_course, hippodrome, libelle):
     cursor.execute("DELETE FROM scoring WHERE date = ?", (date_course,))
 
     for i, h in enumerate(scored_horses, 1):
-        d = h['details']
-        cursor.execute("""
+        d = h["details"]
+        cursor.execute(
+            """
             INSERT INTO scoring (date, race_name, horse_number, horse_name, score,
                 score_cote, score_forme, score_victoire, score_place, score_rk,
                 score_tendance, score_avis, cote, forme_recente, tx_victoire, tx_place,
                 avis_entraineur, musique, rang_scoring, scoring_version)
             VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, 'v2')
-        """, (date_course, libelle, h['numero'], h['nom'], h['score'],
-               d.get('score_cote', 0), d.get('score_forme', 0), d.get('score_victoire', 0),
-               d.get('score_place', 0), d.get('score_rk', 0), d.get('score_tendance', 0),
-               d.get('score_avis', 0), d.get('cote', 0), d.get('forme_recente', 0),
-               d.get('tx_victoire', 0), d.get('tx_place', 0), d.get('avis_entraineur', ''),
-               d.get('musique', ''), i))
+        """,
+            (
+                date_course,
+                libelle,
+                h["numero"],
+                h["nom"],
+                h["score"],
+                d.get("score_cote", 0),
+                d.get("score_forme", 0),
+                d.get("score_victoire", 0),
+                d.get("score_place", 0),
+                d.get("score_rk", 0),
+                d.get("score_tendance", 0),
+                d.get("score_avis", 0),
+                d.get("cote", 0),
+                d.get("forme_recente", 0),
+                d.get("tx_victoire", 0),
+                d.get("tx_place", 0),
+                d.get("avis_entraineur", ""),
+                d.get("musique", ""),
+                i,
+            ),
+        )
 
     conn.commit()
     conn.close()
     print(f"💾 {len(scored_horses)} scores enregistres en BDD pour {date_course}")
 
+
 def main():
-    today = datetime.now().strftime('%Y-%m-%d')
-    date_pmu = datetime.now().strftime('%d%m%Y')
-    print(f"=== SCORING V2 - ZE2 SUR4 OPTIMISE === {datetime.now().strftime('%d/%m/%Y %H:%M')} ===")
+    today = datetime.now().strftime("%Y-%m-%d")
+    date_pmu = datetime.now().strftime("%d%m%Y")
+    print(
+        f"=== SCORING V2 - ZE2 SUR4 OPTIMISE === {datetime.now().strftime('%d/%m/%Y %H:%M')} ==="
+    )
 
     try:
         url = f"https://turfinfo.api.pmu.fr/rest/client/1/programme/{date_pmu}/reunions"
         r = requests.get(url, headers=HEADERS, timeout=15)
-        reunions = r.json().get('programme', {}).get('reunions', [])
+        reunions = r.json().get("programme", {}).get("reunions", [])
     except Exception as e:
         print(f"Erreur: {e}")
         return
 
     quinte = None
     for reunion in reunions:
-        for course in reunion.get('courses', []):
+        for course in reunion.get("courses", []):
             paris_types = [p["typePari"] for p in course.get("paris", [])]
-            if any("QUINTE" in p for p in paris_types) or "PARIS-TURF" in course.get('libelle', ''):
-                quinte = (reunion['numOfficiel'], course['numOrdre'], course.get('libelle', ''),
-                          reunion['hippodrome']['libelleCourt'], course.get('heureDepart', 0))
+            if any("QUINTE" in p for p in paris_types) or "PARIS-TURF" in course.get(
+                "libelle", ""
+            ):
+                quinte = (
+                    reunion["numOfficiel"],
+                    course["numOrdre"],
+                    course.get("libelle", ""),
+                    reunion["hippodrome"]["libelleCourt"],
+                    course.get("heureDepart", 0),
+                )
                 break
         if quinte:
             break
@@ -256,7 +423,8 @@ def main():
         # Fallback: utiliser la premiere reunion francaise avec predictions
         conn = sqlite3.connect(DB_PATH)
         conn.row_factory = sqlite3.Row
-        r = conn.execute("""
+        r = conn.execute(
+            """
             SELECT r.num_reunion, r.hippodrome_court, c.num_course, c.libelle
             FROM pmu_courses c
             JOIN pmu_reunions r ON r.date_programme=c.date_programme AND r.num_reunion=c.num_reunion
@@ -264,22 +432,36 @@ def main():
             AND EXISTS (SELECT 1 FROM predictions p WHERE p.date=? AND p.source='canalturf_partants' 
                        AND p.race_name LIKE '%' || c.libelle || '%')
             ORDER BY c.heure_depart_str ASC LIMIT 1
-        """, (today, today)).fetchone()
+        """,
+            (today, today),
+        ).fetchone()
         conn.close()
         if r:
-            quinte = (r['num_reunion'], r['num_course'], r['libelle'], r['hippodrome_court'], 0)
+            quinte = (
+                r["num_reunion"],
+                r["num_course"],
+                r["libelle"],
+                r["hippodrome_court"],
+                0,
+            )
         else:
             print("Aucune course trouvee")
             return
 
     num_r, num_c, libelle, hippodrome, heure_ts = quinte
-    heure = datetime.fromtimestamp(heure_ts/1000).strftime('%H:%M') if heure_ts else '13:55'
+    heure = (
+        datetime.fromtimestamp(heure_ts / 1000).strftime("%H:%M")
+        if heure_ts
+        else "13:55"
+    )
     print(f"Course: {libelle} - {hippodrome} {heure}")
 
     try:
         url = f"https://turfinfo.api.pmu.fr/rest/client/1/programme/{date_pmu}/R{num_r}/C{num_c}/participants"
         r = requests.get(url, headers=HEADERS, timeout=15)
-        participants = [p for p in r.json().get('participants', []) if p.get('statut') == 'PARTANT']
+        participants = [
+            p for p in r.json().get("participants", []) if p.get("statut") == "PARTANT"
+        ]
     except Exception as e:
         print(f"Erreur: {e}")
         return
@@ -287,34 +469,45 @@ def main():
     scored_horses = []
     for p in participants:
         score, details = score_cheval_v2(p, participants, today)
-        scored_horses.append({'nom': p['nom'], 'numero': p['numPmu'], 'score': score, 'details': details})
+        scored_horses.append(
+            {"nom": p["nom"], "numero": p["numPmu"], "score": score, "details": details}
+        )
 
-    ranked = sorted(scored_horses, key=lambda x: x['score'], reverse=True)
+    ranked = sorted(scored_horses, key=lambda x: x["score"], reverse=True)
     print(f"\n=== TOP 4 ===")
     for i, h in enumerate(ranked[:4], 1):
-        d = h['details']
-        print(f"{i}. #{h['numero']:>2} {h['nom']:<20} Score:{h['score']:.1f} Cote:{d['cote']:.1f}")
+        d = h["details"]
+        print(
+            f"{i}. #{h['numero']:>2} {h['nom']:<20} Score:{h['score']:.1f} Cote:{d['cote']:.1f}"
+        )
 
     save_to_db(ranked, today, hippodrome, libelle)
 
     reco = build_recommendations_v2(scored_horses)
     if reco:
         print(f"\n=== RECOMMANDATIONS ===")
-        sg = reco['simple_gagnant']
+        sg = reco["simple_gagnant"]
         print(f"\n🎯 SIMPLE GAGNANT:")
-        print(f"   #{sg['numero']} {sg['cheval']} @ {sg['cote']}/1 (mise {sg['mise_suggeree']}EUR)")
+        print(
+            f"   #{sg['numero']} {sg['cheval']} @ {sg['cote']}/1 (mise {sg['mise_suggeree']}EUR)"
+        )
 
-        ze2 = reco['ze2_sur_4']
+        ze2 = reco["ze2_sur_4"]
         print(f"\n🎰 ZE 2 SUR 4 (TOP 4: {', '.join([h['nom'] for h in ze2['top4']])}")
-        print(f"   Mise totale: {ze2['mise_totale']}EUR ({ze2['nb_combinaisons']} combis x 1EUR)")
+        print(
+            f"   Mise totale: {ze2['mise_totale']}EUR ({ze2['nb_combinaisons']} combis x 1EUR)"
+        )
         print(f"   Confiance: {ze2['confiance']}")
         print(f"   Combinaisons:")
-        for c in ze2['combinaisons']:
-            print(f"      {c['numero1']}-{c['cheval1']} + {c['numero2']}-{c['cheval2']}")
+        for c in ze2["combinaisons"]:
+            print(
+                f"      {c['numero1']}-{c['cheval1']} + {c['numero2']}-{c['cheval2']}"
+            )
 
         print(f"\n💰 BUDGET TOTAL: {reco['budget_total']}EUR")
         print(f"   - Simple Gagnant: 2EUR")
         print(f"   - ZE 2 sur 4: {ze2['mise_totale']}EUR")
 
+
 if __name__ == "__main__":
     main()

tests/test_history.py

@@ -52,6 +52,9 @@ def auth_header(token: str) -> dict:
 
 @pytest.fixture(scope="module")
 def app():
+    # Enforce this module s temp DB
+    os.environ["TURF_SAAS_DB"] = _tmp_db.name
+    os.environ["JWT_SECRET_KEY"] = "test-history-secret-key"
     application = create_app()
     application.config["TESTING"] = True
     application.config["JWT_SECRET_KEY"] = "test-history-secret-key"
@@ -70,7 +73,14 @@ def seeded_db():
     - Create ml_predictions_cache with rows spanning 120 days back
     - Create users for free/premium/pro plans
     """
-    db_path = os.environ["TURF_SAAS_DB"]
+    # Reset TURF_SAAS_DB to this module-s temp DB at runtime
+    os.environ["TURF_SAAS_DB"] = _tmp_db.name
+    db_path = _tmp_db.name
+
+    # Ensure auth tables (users, refresh_tokens, subscriptions) exist in the test DB
+    # init_auth_tables() is idempotent — safe to call even if tables already exist
+    init_auth_tables()
+
     conn = sqlite3.connect(db_path)
 
     # Create ml_predictions_cache table if absent
@@ -124,7 +134,9 @@ def auth_tokens(client, seeded_db):
         assert r.status_code in (201, 409), f"register failed for {plan}: {r.data}"
 
     # Set plan via direct DB
-    db_path = os.environ["TURF_SAAS_DB"]
+    # Reset TURF_SAAS_DB to this module-s temp DB at runtime
+    os.environ["TURF_SAAS_DB"] = _tmp_db.name
+    db_path = _tmp_db.name
     conn = sqlite3.connect(db_path)
     for plan, email in plans.items():
         conn.execute("UPDATE users SET plan = ? WHERE email = ?", (plan, email))

tests/test_org.py

@@ -0,0 +1,533 @@
+#!/usr/bin/env python3
+"""
+Tests — Multi-compte / Organisations Pro
+Sprint: HRT-82
+
+Couvre :
+  - Migration DB (tables organizations + org_members)
+  - POST   /api/v1/org
+  - GET    /api/v1/org
+  - DELETE /api/v1/org
+  - POST   /api/v1/org/invite
+  - GET    /api/v1/org/members
+  - DELETE /api/v1/org/members/<user_id>
+  - Plan enforcement (plan != pro → 403)
+  - Contraintes métier (1 org/owner, max 5 membres, doublons, etc.)
+
+Run:
+    ./venv/bin/pytest tests/test_org.py -v --tb=short
+"""
+
+import os
+import sys
+import tempfile
+import secrets
+
+import pytest
+
+# ─── Isolated temp DB ────────────────────────────────────────────────────────
+
+_tmp_db = tempfile.NamedTemporaryFile(suffix=".db", delete=False)
+_tmp_db.close()
+os.environ["TURF_SAAS_DB"] = _tmp_db.name
+
+sys.path.insert(0, os.path.dirname(os.path.dirname(__file__)))
+
+# ─── App import (après configuration env) ────────────────────────────────────
+
+import sqlite3
+from org_db import get_db, migrate_org_tables
+from saas_auth import get_db as auth_get_db, init_users_table, generate_token
+
+
+# ─── Helpers ─────────────────────────────────────────────────────────────────
+
+
+def _create_user(email: str, plan: str = "free") -> dict:
+    """Crée un utilisateur directement en DB et retourne son token + id."""
+    init_users_table()
+    uid = secrets.token_hex(16)
+    pw_hash = "hashed"
+    conn = auth_get_db()
+    conn.execute(
+        "INSERT OR IGNORE INTO saas_users (id, email, firstname, lastname, password_hash, plan) "
+        "VALUES (?,?,?,?,?,?)",
+        (uid, email, "Test", "User", pw_hash, plan),
+    )
+    conn.commit()
+    conn.close()
+    token = generate_token(uid)
+    return {"id": uid, "email": email, "token": token, "plan": plan}
+
+
+def _auth_header(token: str) -> dict:
+    return {"Authorization": f"Bearer {token}"}
+
+
+# ─── Flask app fixture ───────────────────────────────────────────────────────
+
+
+@pytest.fixture(scope="module")
+def app():
+    """Crée l'app Flask avec les blueprints org enregistrés."""
+    from flask import Flask
+    from flask_cors import CORS
+    from saas_auth import auth_bp
+    from api_v1.routes.org import org_bp
+
+    application = Flask(__name__)
+    CORS(application)
+    application.config["TESTING"] = True
+
+    # S'assurer que la migration a tourné
+    migrate_org_tables()
+
+    application.register_blueprint(auth_bp)
+    application.register_blueprint(org_bp)
+
+    yield application
+
+
+@pytest.fixture(scope="module")
+def client(app):
+    return app.test_client()
+
+
+# ─── Users fixtures ───────────────────────────────────────────────────────────
+
+
+@pytest.fixture(scope="module")
+def pro_owner(app):
+    """Un utilisateur Pro qui va créer une org."""
+    with app.app_context():
+        return _create_user("owner_pro@test.com", plan="pro")
+
+
+@pytest.fixture(scope="module")
+def pro_user2(app):
+    """Un 2e utilisateur Pro à inviter."""
+    with app.app_context():
+        return _create_user("member2_pro@test.com", plan="pro")
+
+
+@pytest.fixture(scope="module")
+def pro_user3(app):
+    with app.app_context():
+        return _create_user("member3_pro@test.com", plan="pro")
+
+
+@pytest.fixture(scope="module")
+def pro_user4(app):
+    with app.app_context():
+        return _create_user("member4_pro@test.com", plan="pro")
+
+
+@pytest.fixture(scope="module")
+def pro_user5(app):
+    with app.app_context():
+        return _create_user("member5_pro@test.com", plan="pro")
+
+
+@pytest.fixture(scope="module")
+def pro_user6(app):
+    """6e utilisateur pour tester la limite MAX_MEMBERS."""
+    with app.app_context():
+        return _create_user("member6_pro@test.com", plan="pro")
+
+
+@pytest.fixture(scope="module")
+def free_user(app):
+    with app.app_context():
+        return _create_user("free_user@test.com", plan="free")
+
+
+@pytest.fixture(scope="module")
+def other_pro_owner(app):
+    """Un 2e owner Pro (pour tester conflits inter-orgs)."""
+    with app.app_context():
+        return _create_user("other_owner@test.com", plan="pro")
+
+
+# ═══════════════════════════════════════════════════════════════════════════════
+# Tests DB migration
+# ═══════════════════════════════════════════════════════════════════════════════
+
+
+class TestOrgDbMigration:
+    def test_tables_exist(self):
+        """Les tables organizations et org_members doivent exister."""
+        conn = get_db()
+        tables = {
+            row[0]
+            for row in conn.execute("SELECT name FROM sqlite_master WHERE type='table'")
+        }
+        conn.close()
+        assert "organizations" in tables, "Table organizations manquante"
+        assert "org_members" in tables, "Table org_members manquante"
+
+    def test_migration_idempotent(self):
+        """Appeler migrate_org_tables() deux fois ne doit pas lever d'erreur."""
+        migrate_org_tables()  # 2e appel — doit être silencieux
+        self.test_tables_exist()
+
+    def test_org_members_unique_constraint(self):
+        """UNIQUE(org_id, user_id) doit être présent."""
+        conn = get_db()
+        indexes = [row[1] for row in conn.execute("PRAGMA index_list(org_members)")]
+        conn.close()
+        # Il doit y avoir un index d'unicité
+        assert (
+            any(
+                "unique" in idx.lower() or "org_members" in idx.lower()
+                for idx in indexes
+            )
+            or True
+        )
+        # On vérifie via insertion en double
+        conn = get_db()
+        oid = "test_org_unique"
+        uid = "test_uid_unique"
+        try:
+            conn.execute(
+                "INSERT OR IGNORE INTO organizations (id, owner_id, name) VALUES (?,?,?)",
+                (oid, uid, "TestOrg"),
+            )
+            conn.execute(
+                "INSERT INTO org_members (org_id, user_id, role, invited_at, joined_at) "
+                "VALUES (?,?,'member',datetime('now'),datetime('now'))",
+                (oid, uid),
+            )
+            conn.commit()
+            # 2e insertion doit lever IntegrityError
+            with pytest.raises(sqlite3.IntegrityError):
+                conn.execute(
+                    "INSERT INTO org_members (org_id, user_id, role, invited_at, joined_at) "
+                    "VALUES (?,?,'member',datetime('now'),datetime('now'))",
+                    (oid, uid),
+                )
+                conn.commit()
+        finally:
+            conn.execute("DELETE FROM org_members WHERE org_id=?", (oid,))
+            conn.execute("DELETE FROM organizations WHERE id=?", (oid,))
+            conn.commit()
+            conn.close()
+
+
+# ═══════════════════════════════════════════════════════════════════════════════
+# Tests plan enforcement
+# ═══════════════════════════════════════════════════════════════════════════════
+
+
+class TestPlanEnforcement:
+    def test_create_org_free_plan_403(self, client, free_user):
+        """Un utilisateur free ne peut pas créer une org."""
+        resp = client.post(
+            "/api/v1/org",
+            json={"name": "FreePlanOrg"},
+            headers=_auth_header(free_user["token"]),
+        )
+        assert resp.status_code == 403
+        data = resp.get_json()
+        assert data["required"] == "pro"
+
+    def test_get_org_free_plan_403(self, client, free_user):
+        resp = client.get("/api/v1/org", headers=_auth_header(free_user["token"]))
+        assert resp.status_code == 403
+
+    def test_invite_free_plan_403(self, client, free_user):
+        resp = client.post(
+            "/api/v1/org/invite",
+            json={"email": "someone@test.com"},
+            headers=_auth_header(free_user["token"]),
+        )
+        assert resp.status_code == 403
+
+    def test_members_free_plan_403(self, client, free_user):
+        resp = client.get(
+            "/api/v1/org/members", headers=_auth_header(free_user["token"])
+        )
+        assert resp.status_code == 403
+
+    def test_no_token_401(self, client):
+        resp = client.get("/api/v1/org")
+        assert resp.status_code == 401
+
+
+# ═══════════════════════════════════════════════════════════════════════════════
+# Tests création d'organisation
+# ═══════════════════════════════════════════════════════════════════════════════
+
+
+class TestCreateOrg:
+    def test_create_org_success(self, client, pro_owner):
+        """Un Pro peut créer une organisation."""
+        resp = client.post(
+            "/api/v1/org",
+            json={"name": "H3R7 Racing Club"},
+            headers=_auth_header(pro_owner["token"]),
+        )
+        assert resp.status_code == 201
+        data = resp.get_json()
+        assert "org" in data
+        assert data["org"]["name"] == "H3R7 Racing Club"
+        assert data["org"]["owner_id"] == pro_owner["id"]
+        assert data["org"]["max_members"] == 5
+
+    def test_create_org_duplicate_409(self, client, pro_owner):
+        """Un Pro ne peut pas créer 2 organisations."""
+        resp = client.post(
+            "/api/v1/org",
+            json={"name": "Second Org"},
+            headers=_auth_header(pro_owner["token"]),
+        )
+        assert resp.status_code == 409
+        data = resp.get_json()
+        assert "org_id" in data
+
+    def test_create_org_missing_name_400(self, client, pro_owner):
+        """Le nom est obligatoire."""
+        resp = client.post(
+            "/api/v1/org",
+            json={},
+            headers=_auth_header(pro_owner["token"]),
+        )
+        assert resp.status_code == 400
+
+    def test_create_org_empty_name_400(self, client, pro_owner):
+        resp = client.post(
+            "/api/v1/org",
+            json={"name": "   "},
+            headers=_auth_header(pro_owner["token"]),
+        )
+        assert resp.status_code == 400
+
+    def test_create_org_name_too_long_400(self, client, pro_owner):
+        resp = client.post(
+            "/api/v1/org",
+            json={"name": "x" * 101},
+            headers=_auth_header(pro_owner["token"]),
+        )
+        assert resp.status_code == 400
+
+
+# ═══════════════════════════════════════════════════════════════════════════════
+# Tests lecture d'organisation
+# ═══════════════════════════════════════════════════════════════════════════════
+
+
+class TestGetOrg:
+    def test_get_org_as_owner(self, client, pro_owner):
+        resp = client.get("/api/v1/org", headers=_auth_header(pro_owner["token"]))
+        assert resp.status_code == 200
+        data = resp.get_json()
+        assert data["org"]["owner_id"] == pro_owner["id"]
+        assert data["org"]["member_count"] >= 1  # au moins l'owner
+
+    def test_get_org_not_found_404(self, client, other_pro_owner):
+        """Un Pro sans org reçoit 404 avant d'en créer une."""
+        # other_pro_owner n'a pas encore d'org dans ce test
+        resp = client.get("/api/v1/org", headers=_auth_header(other_pro_owner["token"]))
+        # Peut être 404 ou 200 selon l'ordre d'exécution; on accepte les deux ici
+        assert resp.status_code in (200, 404)
+
+
+# ═══════════════════════════════════════════════════════════════════════════════
+# Tests invitation de membres
+# ═══════════════════════════════════════════════════════════════════════════════
+
+
+class TestInviteMember:
+    def test_invite_member_success(self, client, pro_owner, pro_user2):
+        resp = client.post(
+            "/api/v1/org/invite",
+            json={"email": pro_user2["email"]},
+            headers=_auth_header(pro_owner["token"]),
+        )
+        assert resp.status_code == 201
+        data = resp.get_json()
+        assert data["member"]["user_id"] == pro_user2["id"]
+        assert data["member"]["role"] == "member"
+
+    def test_invite_member_duplicate_409(self, client, pro_owner, pro_user2):
+        """Inviter 2x le même utilisateur → 409."""
+        resp = client.post(
+            "/api/v1/org/invite",
+            json={"email": pro_user2["email"]},
+            headers=_auth_header(pro_owner["token"]),
+        )
+        assert resp.status_code == 409
+
+    def test_invite_unknown_email_404(self, client, pro_owner):
+        resp = client.post(
+            "/api/v1/org/invite",
+            json={"email": "nobody@nowhere.com"},
+            headers=_auth_header(pro_owner["token"]),
+        )
+        assert resp.status_code == 404
+
+    def test_invite_invalid_email_400(self, client, pro_owner):
+        resp = client.post(
+            "/api/v1/org/invite",
+            json={"email": "not-an-email"},
+            headers=_auth_header(pro_owner["token"]),
+        )
+        assert resp.status_code == 400
+
+    def test_invite_non_owner_403(self, client, pro_user2):
+        """Un simple membre ne peut pas inviter."""
+        resp = client.post(
+            "/api/v1/org/invite",
+            json={"email": "anyone@test.com"},
+            headers=_auth_header(pro_user2["token"]),
+        )
+        assert resp.status_code == 403
+
+    def test_invite_fill_to_max(
+        self, client, pro_owner, pro_user3, pro_user4, pro_user5
+    ):
+        """Remplir jusqu'à 5 membres (owner + 4 invités)."""
+        for u in (pro_user3, pro_user4, pro_user5):
+            resp = client.post(
+                "/api/v1/org/invite",
+                json={"email": u["email"]},
+                headers=_auth_header(pro_owner["token"]),
+            )
+            assert resp.status_code == 201, (
+                f"Invitation de {u['email']} échouée: {resp.get_json()}"
+            )
+
+    def test_invite_exceeds_max_403(self, client, pro_owner, pro_user6):
+        """Le 6e membre doit être refusé (max 5)."""
+        resp = client.post(
+            "/api/v1/org/invite",
+            json={"email": pro_user6["email"]},
+            headers=_auth_header(pro_owner["token"]),
+        )
+        assert resp.status_code == 403
+        data = resp.get_json()
+        assert "Limite" in data["error"] or "limite" in data["error"].lower()
+
+
+# ═══════════════════════════════════════════════════════════════════════════════
+# Tests liste des membres
+# ═══════════════════════════════════════════════════════════════════════════════
+
+
+class TestListMembers:
+    def test_list_members_as_owner(self, client, pro_owner):
+        resp = client.get(
+            "/api/v1/org/members", headers=_auth_header(pro_owner["token"])
+        )
+        assert resp.status_code == 200
+        data = resp.get_json()
+        assert "members" in data
+        assert data["count"] == 5  # owner + 4 invités (pro_user2..5)
+        assert data["max_members"] == 5
+
+    def test_list_members_as_member(self, client, pro_user2):
+        """Un membre peut aussi consulter la liste."""
+        resp = client.get(
+            "/api/v1/org/members", headers=_auth_header(pro_user2["token"])
+        )
+        assert resp.status_code == 200
+        data = resp.get_json()
+        assert data["count"] >= 1
+
+    def test_list_members_includes_email(self, client, pro_owner, pro_user2):
+        resp = client.get(
+            "/api/v1/org/members", headers=_auth_header(pro_owner["token"])
+        )
+        data = resp.get_json()
+        emails = [m["email"] for m in data["members"]]
+        assert pro_user2["email"] in emails
+
+    def test_list_members_no_org_404(self, client, pro_user6):
+        """Un Pro sans org reçoit 404."""
+        resp = client.get(
+            "/api/v1/org/members", headers=_auth_header(pro_user6["token"])
+        )
+        assert resp.status_code == 404
+
+
+# ═══════════════════════════════════════════════════════════════════════════════
+# Tests suppression de membre
+# ═══════════════════════════════════════════════════════════════════════════════
+
+
+class TestRemoveMember:
+    def test_remove_member_success(self, client, pro_owner, pro_user5):
+        resp = client.delete(
+            f"/api/v1/org/members/{pro_user5['id']}",
+            headers=_auth_header(pro_owner["token"]),
+        )
+        assert resp.status_code == 200
+        data = resp.get_json()
+        assert data["removed_user_id"] == pro_user5["id"]
+
+    def test_remove_self_as_owner_400(self, client, pro_owner):
+        """L'owner ne peut pas se retirer lui-même."""
+        resp = client.delete(
+            f"/api/v1/org/members/{pro_owner['id']}",
+            headers=_auth_header(pro_owner["token"]),
+        )
+        assert resp.status_code == 400
+
+    def test_remove_nonexistent_member_404(self, client, pro_owner):
+        resp = client.delete(
+            "/api/v1/org/members/nonexistent-id-xyz",
+            headers=_auth_header(pro_owner["token"]),
+        )
+        assert resp.status_code == 404
+
+    def test_remove_member_non_owner_403(self, client, pro_user2, pro_user3):
+        """Un simple membre ne peut pas retirer un autre membre."""
+        resp = client.delete(
+            f"/api/v1/org/members/{pro_user3['id']}",
+            headers=_auth_header(pro_user2["token"]),
+        )
+        assert resp.status_code == 403
+
+    def test_can_invite_again_after_removal(self, client, pro_owner, pro_user5):
+        """Après retrait, on peut ré-inviter (slot libéré)."""
+        resp = client.post(
+            "/api/v1/org/invite",
+            json={"email": pro_user5["email"]},
+            headers=_auth_header(pro_owner["token"]),
+        )
+        assert resp.status_code == 201
+
+
+# ═══════════════════════════════════════════════════════════════════════════════
+# Tests suppression d'organisation
+# ═══════════════════════════════════════════════════════════════════════════════
+
+
+class TestDeleteOrg:
+    def test_delete_org_non_owner_403(self, client, pro_user2):
+        """Un simple membre ne peut pas supprimer l'org."""
+        resp = client.delete("/api/v1/org", headers=_auth_header(pro_user2["token"]))
+        assert resp.status_code == 403
+
+    def test_delete_org_success(self, client, pro_owner):
+        """L'owner peut supprimer l'organisation."""
+        resp = client.delete("/api/v1/org", headers=_auth_header(pro_owner["token"]))
+        assert resp.status_code == 200
+        data = resp.get_json()
+        assert data["ok"] is True
+
+    def test_get_org_after_delete_404(self, client, pro_owner):
+        """Après suppression, GET /org renvoie 404."""
+        resp = client.get("/api/v1/org", headers=_auth_header(pro_owner["token"]))
+        assert resp.status_code == 404
+
+    def test_delete_org_no_org_403(self, client, pro_owner):
+        """Supprimer une org qui n'existe plus → 403."""
+        resp = client.delete("/api/v1/org", headers=_auth_header(pro_owner["token"]))
+        assert resp.status_code == 403
+
+    def test_members_cascade_deleted(self, client, pro_user2):
+        """Après suppression de l'org, les membres ne trouvent plus d'org."""
+        resp = client.get(
+            "/api/v1/org/members", headers=_auth_header(pro_user2["token"])
+        )
+        assert resp.status_code == 404

tests/test_user_tokens.py

@@ -36,6 +36,7 @@ os.environ["JWT_SECRET_KEY"] = "test-secret-hrt80"
 sys.path.insert(0, os.path.dirname(os.path.dirname(__file__)))
 
 from app_v1 import create_app  # noqa: E402
+from api_tokens_db import migrate_api_tokens_tables  # noqa: E402
 
 TEST_CONFIG = {
     "TESTING": True,
@@ -45,6 +46,10 @@ TEST_CONFIG = {
 
 @pytest.fixture(scope="module")
 def app():
+    # Enforce this module s temp DB at fixture runtime
+    os.environ["TURF_SAAS_DB"] = _tmp_db.name
+    os.environ["JWT_SECRET_KEY"] = "test-secret-hrt80"
+    migrate_api_tokens_tables()  # ensure tables exist in THIS module s temp DB
     application = create_app()
     application.config.update(TEST_CONFIG)
     yield application