docs(HRT-96): Note Intelligence ML + documentation API v1 finale

- Création POD/Intelligence/ML_Predictions_SaaS.md : architecture ML complète, flow ml_predictions_cache → ml_feedback_saas → paris → ROI dashboard, schéma données/jointures, décision duplication vs modification turf_scraper, documentation des 4 stratégies XGBoost, idempotence, usage CLI - Mise à jour DOCUMENTATION.md : ajout section Turf SaaS API v1 complète avec tous les endpoints documentés dont /api/v1/roi/* et /api/v1/ml/feedback/* (HRT-92 ROI backend + HRT-93 ML feedback loop) Co-Authored-By: Paperclip <noreply@paperclip.ing>
Merge pull request '[HRT-83] feat: Météo & terrain intégrés dans prédictions ML (Premium)' (#10 ) from feature/HRT-83-meteo-terrain-ml-predictions into master
2026-04-30 21:28:52 +02:00 · 2026-04-30 08:40:16 +02:00 · 2026-04-30 08:39:59 +02:00 · 2026-04-29 17:31:53 +02:00 · 2026-04-29 17:25:30 +02:00 · 2026-04-29 17:05:01 +02:00
12 changed files with 1909 additions and 171 deletions
--- a/DOCUMENTATION.md
+++ b/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)*
--- a/POD/Intelligence/ML_Predictions_SaaS.md
+++ b/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 |
--- a/api_tokens_db.py
+++ b/api_tokens_db.py
@@ -0,0 +1,57 @@
+#!/usr/bin/env python3
+"""
+api_tokens_db.py — DB migration for personal API tokens + user webhooks
+HRT-80: API Token personnel + Webhook alertes (Pro)
+"""
+
+import logging
+import os
+import sqlite3
+
+DB_PATH = os.environ.get("TURF_SAAS_DB", "/home/h3r7/turf_saas/turf_saas.db")
+logger = logging.getLogger("turf_saas.api_tokens_db")
+
+
+def get_db() -> sqlite3.Connection:
+    conn = sqlite3.connect(DB_PATH)
+    conn.row_factory = sqlite3.Row
+    return conn
+
+
+def migrate_api_tokens_tables() -> None:
+    """Idempotent migration: create user_api_tokens and user_webhooks."""
+    conn = get_db()
+    c = conn.cursor()
+    c.executescript("""
+        CREATE TABLE IF NOT EXISTS user_api_tokens (
+            id           INTEGER  PRIMARY KEY AUTOINCREMENT,
+            user_id      TEXT     NOT NULL,
+            token_hash   TEXT     NOT NULL UNIQUE,
+            token_prefix TEXT     NOT NULL,
+            created_at   DATETIME NOT NULL DEFAULT (datetime('now')),
+            last_used_at DATETIME,
+            revoked      INTEGER  NOT NULL DEFAULT 0
+        );
+        CREATE INDEX IF NOT EXISTS idx_api_tokens_user ON user_api_tokens(user_id);
+        CREATE INDEX IF NOT EXISTS idx_api_tokens_hash ON user_api_tokens(token_hash);
+
+        CREATE TABLE IF NOT EXISTS user_webhooks (
+            id         INTEGER  PRIMARY KEY AUTOINCREMENT,
+            user_id    TEXT     NOT NULL UNIQUE,
+            url        TEXT     NOT NULL,
+            secret     TEXT     NOT NULL,
+            created_at DATETIME NOT NULL DEFAULT (datetime('now'))
+        );
+        CREATE INDEX IF NOT EXISTS idx_webhooks_user ON user_webhooks(user_id);
+    """)
+    conn.commit()
+    conn.close()
+    logger.info(
+        "[api_tokens_db] Tables user_api_tokens + user_webhooks created/verified."
+    )
+
+
+if __name__ == "__main__":
+    logging.basicConfig(level=logging.INFO)
+    migrate_api_tokens_tables()
+    print("[api_tokens_db] Migration complete.")
--- a/api_v1/init.py
+++ b/api_v1/init.py
@@ -4,6 +4,7 @@ API v1 Blueprint package — Turf SaaS
 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:
@@ -16,6 +17,8 @@ Registers sub-blueprints:
  /api/v1/metrics     — métriques perf ML (premium+)
  /api/v1/billing/    — Stripe checkout, portal, webhook, status
  /api/v1/user/       — config utilisateur, alertes Telegram (premium+)
+  /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)
@@ -32,6 +35,7 @@ from .routes.export import export_bp
 from .routes.metrics import metrics_bp
 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

@@ -50,5 +54,6 @@ def register_api_v1(app):
    app.register_blueprint(metrics_bp)
    app.register_blueprint(billing_bp)
    app.register_blueprint(user_bp)
+    app.register_blueprint(user_tokens_bp)
    app.register_blueprint(history_bp)
    app.register_blueprint(org_bp)
--- a/api_v1/routes/predictions.py
+++ b/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)

--- a/api_v1/routes/user_tokens.py
+++ b/api_v1/routes/user_tokens.py
@@ -0,0 +1,195 @@
+#!/usr/bin/env python3
+"""
+user_tokens.py — Personal API tokens + Webhook configuration (Pro plan)
+HRT-80
+
+Endpoints:
+  POST   /api/v1/user/api-token
+  DELETE /api/v1/user/api-token
+  POST   /api/v1/user/webhook
+  DELETE /api/v1/user/webhook
+"""
+
+import hashlib
+import logging
+import secrets
+
+from flask import Blueprint, g, jsonify, request
+
+from api_tokens_db import get_db, migrate_api_tokens_tables
+from auth import jwt_required_middleware, plan_required
+
+logger = logging.getLogger("turf_saas.user_tokens")
+
+user_tokens_bp = Blueprint("user_tokens", __name__, url_prefix="/api/v1/user")
+
+try:
+    migrate_api_tokens_tables()
+except Exception as _e:
+    logger.warning("api_tokens_db migration skipped (test env?): %s", _e)
+
+
+def _hash_token(raw: str) -> str:
+    return hashlib.sha256(raw.encode()).hexdigest()
+
+
+@user_tokens_bp.route("/api-token", methods=["POST"])
+@jwt_required_middleware
+@plan_required("pro")
+def create_api_token():
+    user = g.current_user
+    user_id = str(user["id"])
+    conn = get_db()
+    try:
+        existing = conn.execute(
+            "SELECT id, token_prefix, created_at FROM user_api_tokens "
+            "WHERE user_id = ? AND revoked = 0",
+            (user_id,),
+        ).fetchone()
+        if existing:
+            return jsonify(
+                {
+                    "error": "Un token actif existe déjà. Révoquez-le avant d'en créer un nouveau.",
+                    "existing_prefix": existing["token_prefix"],
+                    "created_at": existing["created_at"],
+                }
+            ), 409
+
+        raw_token = "trf_" + secrets.token_urlsafe(40)
+        token_hash = _hash_token(raw_token)
+        token_prefix = raw_token[:12]
+
+        conn.execute(
+            "INSERT INTO user_api_tokens (user_id, token_hash, token_prefix) VALUES (?, ?, ?)",
+            (user_id, token_hash, token_prefix),
+        )
+        conn.commit()
+
+        row = conn.execute(
+            "SELECT created_at FROM user_api_tokens WHERE token_hash = ?",
+            (token_hash,),
+        ).fetchone()
+        created_at = row["created_at"] if row else None
+    except Exception as e:
+        conn.rollback()
+        logger.error("create_api_token error for user %s: %s", user_id, e)
+        return jsonify({"error": "Erreur interne"}), 500
+    finally:
+        conn.close()
+
+    logger.info("API token created for user %s (prefix=%s)", user_id, token_prefix)
+    return jsonify(
+        {
+            "token": raw_token,
+            "prefix": token_prefix,
+            "created_at": created_at,
+            "warning": "Conservez ce token en lieu sûr. Il ne sera plus affiché.",
+        }
+    ), 201
+
+
+@user_tokens_bp.route("/api-token", methods=["DELETE"])
+@jwt_required_middleware
+@plan_required("pro")
+def revoke_api_token():
+    user = g.current_user
+    user_id = str(user["id"])
+    conn = get_db()
+    try:
+        result = conn.execute(
+            "UPDATE user_api_tokens SET revoked = 1 WHERE user_id = ? AND revoked = 0",
+            (user_id,),
+        )
+        conn.commit()
+        revoked_count = result.rowcount
+    except Exception as e:
+        conn.rollback()
+        logger.error("revoke_api_token error for user %s: %s", user_id, e)
+        return jsonify({"error": "Erreur interne"}), 500
+    finally:
+        conn.close()
+
+    if revoked_count == 0:
+        return jsonify({"error": "Aucun token actif trouvé"}), 404
+
+    logger.info("API token(s) revoked for user %s (%d tokens)", user_id, revoked_count)
+    return jsonify({"revoked": True, "count": revoked_count}), 200
+
+
+@user_tokens_bp.route("/webhook", methods=["POST"])
+@jwt_required_middleware
+@plan_required("pro")
+def create_webhook():
+    user = g.current_user
+    user_id = str(user["id"])
+    data = request.get_json(silent=True) or {}
+    url = (data.get("url") or "").strip()
+
+    if not url:
+        return jsonify({"error": "URL du webhook manquante"}), 400
+    if not url.startswith("https://"):
+        return jsonify(
+            {"error": "L'URL du webhook doit utiliser HTTPS (commencer par https://)"}
+        ), 400
+
+    secret = (data.get("secret") or "").strip() or secrets.token_hex(32)
+
+    conn = get_db()
+    existing = None
+    try:
+        existing = conn.execute(
+            "SELECT id FROM user_webhooks WHERE user_id = ?", (user_id,)
+        ).fetchone()
+        if existing:
+            conn.execute(
+                "UPDATE user_webhooks SET url = ?, secret = ?, created_at = datetime('now') "
+                "WHERE user_id = ?",
+                (url, secret, user_id),
+            )
+        else:
+            conn.execute(
+                "INSERT INTO user_webhooks (user_id, url, secret) VALUES (?, ?, ?)",
+                (user_id, url, secret),
+            )
+        conn.commit()
+    except Exception as e:
+        conn.rollback()
+        logger.error("create_webhook error for user %s: %s", user_id, e)
+        return jsonify({"error": "Erreur interne"}), 500
+    finally:
+        conn.close()
+
+    action = "mis à jour" if existing else "configuré"
+    logger.info("Webhook %s for user %s: %s", action, user_id, url)
+    return jsonify(
+        {
+            "webhook_url": url,
+            "secret": secret,
+            "message": f"Webhook {action} avec succès",
+        }
+    ), 201
+
+
+@user_tokens_bp.route("/webhook", methods=["DELETE"])
+@jwt_required_middleware
+@plan_required("pro")
+def delete_webhook():
+    user = g.current_user
+    user_id = str(user["id"])
+    conn = get_db()
+    try:
+        result = conn.execute("DELETE FROM user_webhooks WHERE user_id = ?", (user_id,))
+        conn.commit()
+        deleted_count = result.rowcount
+    except Exception as e:
+        conn.rollback()
+        logger.error("delete_webhook error for user %s: %s", user_id, e)
+        return jsonify({"error": "Erreur interne"}), 500
+    finally:
+        conn.close()
+
+    if deleted_count == 0:
+        return jsonify({"error": "Aucun webhook configuré"}), 404
+
+    logger.info("Webhook deleted for user %s", user_id)
+    return jsonify({"deleted": True}), 200
--- a/api_v1/routes/valuebets.py
+++ b/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(
--- a/api_v1/utils_webhook.py
+++ b/api_v1/utils_webhook.py
@@ -0,0 +1,80 @@
+#!/usr/bin/env python3
+"""
+utils_webhook.py — Webhook dispatch utility (fire-and-forget, HMAC-SHA256)
+HRT-80
+"""
+
+import hashlib
+import hmac
+import json
+import logging
+
+import requests
+
+from api_tokens_db import get_db
+
+logger = logging.getLogger("turf_saas.webhook")
+
+EVENT_NEW_PREDICTION = "new_prediction"
+EVENT_VALUE_BET = "value_bet"
+
+
+def dispatch_webhook(user_id: str, event_type: str, payload: dict) -> None:
+    """
+    Send HMAC-signed webhook POST to URL configured by user.
+    Fire-and-forget: errors logged, never re-raised. Timeout: 5s.
+    """
+    conn = get_db()
+    try:
+        row = conn.execute(
+            "SELECT url, secret FROM user_webhooks WHERE user_id = ?",
+            (str(user_id),),
+        ).fetchone()
+    except Exception as e:
+        logger.warning("dispatch_webhook: DB error for user %s: %s", user_id, e)
+        return
+    finally:
+        conn.close()
+
+    if not row:
+        return
+
+    url = row["url"]
+    secret = row["secret"]
+    body = json.dumps(
+        {"event": event_type, "data": payload},
+        ensure_ascii=False,
+        separators=(",", ":"),
+    )
+    signature = hmac.new(
+        secret.encode("utf-8"), body.encode("utf-8"), hashlib.sha256
+    ).hexdigest()
+    headers = {
+        "Content-Type": "application/json",
+        "X-Turf-Signature": f"sha256={signature}",
+        "X-Turf-Event": event_type,
+        "User-Agent": "TurfSaaS-Webhook/1.0",
+    }
+    try:
+        resp = requests.post(url, data=body, headers=headers, timeout=5)
+        logger.info(
+            "Webhook dispatched to user %s (event=%s, status=%s)",
+            user_id,
+            event_type,
+            resp.status_code,
+        )
+    except requests.exceptions.Timeout:
+        logger.warning(
+            "Webhook timeout for user %s (event=%s, url=%s)", user_id, event_type, url
+        )
+    except requests.exceptions.RequestException as e:
+        logger.warning(
+            "Webhook failed for user %s (event=%s): %s", user_id, event_type, e
+        )
+    except Exception as e:
+        logger.warning(
+            "Webhook unexpected error for user %s (event=%s): %s",
+            user_id,
+            event_type,
+            e,
+        )
--- a/auth.py
+++ b/auth.py
@@ -258,11 +258,47 @@ def logout():
 # ──────────────────────────────────────────────────────────────


+def validate_api_key(raw_key: str):
+    """
+    Validate a personal API token (X-API-Key header).
+    Returns user dict or None. Updates last_used_at on success.
+    HRT-80: Personal API token support.
+    """
+    if not raw_key:
+        return None
+    key_hash = hashlib.sha256(raw_key.encode()).hexdigest()
+    db = get_db()
+    try:
+        row = db.execute(
+            "SELECT t.user_id, u.* FROM user_api_tokens t "
+            "JOIN users u ON CAST(t.user_id AS INTEGER) = u.id "
+            "WHERE t.token_hash = ? AND t.revoked = 0 AND u.is_active = 1",
+            (key_hash,),
+        ).fetchone()
+        if row:
+            db.execute(
+                "UPDATE user_api_tokens SET last_used_at = datetime('now') "
+                "WHERE token_hash = ?",
+                (key_hash,),
+            )
+            db.commit()
+        return dict(row) if row else None
+    except Exception as e:
+        logger.warning("validate_api_key error: %s", e)
+        return None
+    finally:
+        db.close()
+
+
 def jwt_required_middleware(fn):
-    """Decorator: require a valid Bearer JWT access token."""
+    """
+    Decorator: require a valid Bearer JWT access token OR X-API-Key personal token.
+    HRT-80: Added X-API-Key fallback for personal API tokens (Pro plan only).
+    """

    @wraps(fn)
    def wrapper(*args, **kwargs):
+        # 1. Try Bearer JWT (existing flow — unchanged)
        try:
            verify_jwt_in_request()
            user_id = int(get_jwt_identity())
@@ -271,10 +307,20 @@ def jwt_required_middleware(fn):
                return jsonify({"error": "Utilisateur introuvable"}), 401
            g.current_user = dict(user)
            g.current_user_id = user_id
+            return fn(*args, **kwargs)
        except (JWTExtendedException, PyJWTError) as e:
            logger.debug("JWT auth failed: %s", e)
-            return jsonify({"error": "Token invalide ou expiré", "detail": str(e)}), 401
-        return fn(*args, **kwargs)
+
+        # 2. Fallback: X-API-Key personal token (HRT-80)
+        api_key = request.headers.get("X-API-Key", "").strip()
+        if api_key:
+            user = validate_api_key(api_key)
+            if user:
+                g.current_user = user
+                g.current_user_id = user.get("id")
+                return fn(*args, **kwargs)
+
+        return jsonify({"error": "Token invalide ou expiré"}), 401

    return wrapper

--- a/saas_auth.py
+++ b/saas_auth.py
@@ -8,6 +8,7 @@ Sprint 4-5 — HRT-30
 from flask import Blueprint, request, jsonify, current_app
 import sqlite3
 import hashlib
+import logging
 import secrets
 import os
 import time
@@ -229,14 +230,54 @@ def hash_password(password: str) -> str:
    return hashlib.sha256(password.encode("utf-8")).hexdigest()


+def validate_api_key(raw_key: str):
+    """
+    Validate a personal API token (X-API-Key header).
+    Returns user dict or None. Updates last_used_at on success.
+    HRT-80
+    """
+    if not raw_key:
+        return None
+    key_hash = hashlib.sha256(raw_key.encode()).hexdigest()
+    conn = get_db()
+    try:
+        row = conn.execute(
+            "SELECT t.user_id, u.* FROM user_api_tokens t "
+            "JOIN saas_users u ON t.user_id = u.id "
+            "WHERE t.token_hash = ? AND t.revoked = 0",
+            (key_hash,),
+        ).fetchone()
+        if row:
+            conn.execute(
+                "UPDATE user_api_tokens SET last_used_at = datetime('now') "
+                "WHERE token_hash = ?",
+                (key_hash,),
+            )
+            conn.commit()
+        return dict(row) if row else None
+    except Exception as e:
+        logging.getLogger("turf_saas.auth").warning("validate_api_key error: %s", e)
+        return None
+    finally:
+        conn.close()
+
+
 def require_auth(f):
    @wraps(f)
    def decorated(*args, **kwargs):
+        # 1. Try Bearer session token (existing flow — unchanged)
        auth = request.headers.get("Authorization", "")
        token = (
            auth.removeprefix("Bearer ").strip() if auth.startswith("Bearer ") else None
        )
-        user = validate_token(token)
+        user = validate_token(token) if token else None
+
+        # 2. Fallback: X-API-Key personal token (HRT-80)
+        if not user:
+            api_key = request.headers.get("X-API-Key", "").strip()
+            if api_key:
+                user = validate_api_key(api_key)
+
        if not user:
            return jsonify({"error": "Non authentifié"}), 401
        request.current_user = user
--- a/scoring_v2.py
+++ b/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)
@@ -41,222 +46,385 @@ 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:
        cote = get_cote_from_db(horse_name, today)
-    
+
    # Si toujours pas de cote, utiliser 99 comme valeur par defaut
    if not cote or cote == 0:
        cote = 99.0
-        
+
    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['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
-    
+        details["driver_change"] = True
+
+    # 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
-    
+
    top1, top2, top3, top4 = ranked[0], ranked[1], ranked[2], ranked[3]
    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()
-    
+
    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
-    
+
    if not quinte:
        # 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
@@ -264,57 +432,82 @@ 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
-    
+
    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})
-    
-    ranked = sorted(scored_horses, key=lambda x: x['score'], reverse=True)
+        scored_horses.append(
+            {"nom": p["nom"], "numero": p["numPmu"], "score": score, "details": details}
+        )
+
+    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)")
-        
-        ze2 = reco['ze2_sur_4']
+        print(
+            f"   #{sg['numero']} {sg['cheval']} @ {sg['cote']}/1 (mise {sg['mise_suggeree']}EUR)"
+        )
+
+        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()
--- a/tests/test_user_tokens.py
+++ b/tests/test_user_tokens.py
@@ -0,0 +1,383 @@
+#!/usr/bin/env python3
+"""
+tests/test_user_tokens.py — Personal API Token + Webhook alertes
+HRT-80: Tests unitaires et d'intégration
+
+Couvre:
+  - POST /api/v1/user/api-token  (create)
+  - DELETE /api/v1/user/api-token (revoke)
+  - POST /api/v1/user/webhook    (create/upsert)
+  - DELETE /api/v1/user/webhook  (delete)
+  - Authentification via X-API-Key
+  - dispatch_webhook() fire-and-forget
+  - Plan enforcement Pro uniquement
+
+Run:
+    ./venv/bin/pytest tests/test_user_tokens.py -v --tb=short
+"""
+
+import hashlib
+import json
+import os
+import sqlite3
+import sys
+import tempfile
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+# ─── Test DB isolation ────────────────────────────────────────────────────────
+_tmp_db = tempfile.NamedTemporaryFile(suffix=".db", delete=False)
+_tmp_db.close()
+os.environ["TURF_SAAS_DB"] = _tmp_db.name
+os.environ["JWT_SECRET_KEY"] = "test-secret-hrt80"
+
+# Add project root to path
+sys.path.insert(0, os.path.dirname(os.path.dirname(__file__)))
+
+from app_v1 import create_app  # noqa: E402
+
+TEST_CONFIG = {
+    "TESTING": True,
+    "JWT_SECRET_KEY": "test-secret-hrt80",
+}
+
+
+@pytest.fixture(scope="module")
+def app():
+    application = create_app()
+    application.config.update(TEST_CONFIG)
+    yield application
+
+
+@pytest.fixture(scope="module")
+def client(app):
+    return app.test_client()
+
+
+# ─── Helpers ─────────────────────────────────────────────────────────────────
+
+
+def _create_user(client, email, plan="pro"):
+    """Register user (plan=free) then update plan in DB."""
+    resp = client.post(
+        "/api/v1/auth/register",
+        json={"email": email, "password": "Secure123"},
+    )
+    assert resp.status_code == 201, resp.get_json()
+    user_id = resp.get_json()["user_id"]
+
+    # Update plan directly in DB (no plan-update endpoint in JWT auth)
+    conn = sqlite3.connect(os.environ["TURF_SAAS_DB"])
+    conn.execute("UPDATE users SET plan = ? WHERE id = ?", (plan, user_id))
+    conn.commit()
+    conn.close()
+
+    # Login to get access token
+    login_resp = client.post(
+        "/api/v1/auth/login",
+        json={"email": email, "password": "Secure123"},
+    )
+    assert login_resp.status_code == 200, login_resp.get_json()
+    access_token = login_resp.get_json()["access_token"]
+    return access_token, user_id
+
+
+def _auth_header(token):
+    return {"Authorization": f"Bearer {token}"}
+
+
+# ─── Tests: API Token (Pro) ───────────────────────────────────────────────────
+
+
+class TestApiToken:
+    def test_create_api_token_pro(self, client):
+        """POST /api/v1/user/api-token — Pro user gets 201 + token starting with trf_"""
+        token, _ = _create_user(client, "pro_token@test.com", plan="pro")
+        resp = client.post("/api/v1/user/api-token", headers=_auth_header(token))
+        assert resp.status_code == 201, resp.get_json()
+        data = resp.get_json()
+        assert data["token"].startswith("trf_")
+        assert data["prefix"] == data["token"][:12]
+        assert "warning" in data
+        assert "created_at" in data
+
+    def test_create_api_token_stores_hash_not_raw(self, client):
+        """Second POST returns 409 — only hashed token stored"""
+        token, _ = _create_user(client, "pro_token2@test.com", plan="pro")
+        # First create
+        r1 = client.post("/api/v1/user/api-token", headers=_auth_header(token))
+        assert r1.status_code == 201
+        raw_token = r1.get_json()["token"]
+        # Second create should conflict
+        r2 = client.post("/api/v1/user/api-token", headers=_auth_header(token))
+        assert r2.status_code == 409
+        data = r2.get_json()
+        assert "existing_prefix" in data
+        # Verify raw token is NOT stored in DB (only hash)
+        conn = sqlite3.connect(os.environ["TURF_SAAS_DB"])
+        row = conn.execute(
+            "SELECT token_hash FROM user_api_tokens WHERE token_prefix = ?",
+            (raw_token[:12],),
+        ).fetchone()
+        conn.close()
+        assert row is not None
+        assert row[0] != raw_token  # hash != raw
+        assert len(row[0]) == 64  # SHA256 hex
+
+    def test_create_api_token_free_user(self, client):
+        """Free user gets 403"""
+        token, _ = _create_user(client, "free_token@test.com", plan="free")
+        resp = client.post("/api/v1/user/api-token", headers=_auth_header(token))
+        assert resp.status_code == 403
+
+    def test_create_api_token_premium_user(self, client):
+        """Premium user gets 403 (Pro only feature)"""
+        token, _ = _create_user(client, "premium_token@test.com", plan="premium")
+        resp = client.post("/api/v1/user/api-token", headers=_auth_header(token))
+        assert resp.status_code == 403
+
+    def test_create_api_token_no_auth(self, client):
+        """No auth → 401"""
+        resp = client.post("/api/v1/user/api-token")
+        assert resp.status_code == 401
+
+    def test_revoke_api_token(self, client):
+        """DELETE /api/v1/user/api-token — Pro user revokes active token"""
+        token, _ = _create_user(client, "pro_revoke@test.com", plan="pro")
+        # Create first
+        client.post("/api/v1/user/api-token", headers=_auth_header(token))
+        # Revoke
+        resp = client.delete("/api/v1/user/api-token", headers=_auth_header(token))
+        assert resp.status_code == 200
+        data = resp.get_json()
+        assert data["revoked"] is True
+        assert data["count"] >= 1
+
+    def test_revoke_no_active_token(self, client):
+        """DELETE with no active token → 404"""
+        token, _ = _create_user(client, "pro_notoken@test.com", plan="pro")
+        resp = client.delete("/api/v1/user/api-token", headers=_auth_header(token))
+        assert resp.status_code == 404
+
+    def test_revoke_non_pro(self, client):
+        """DELETE for free user → 403"""
+        token, _ = _create_user(client, "free_revoke@test.com", plan="free")
+        resp = client.delete("/api/v1/user/api-token", headers=_auth_header(token))
+        assert resp.status_code == 403
+
+
+# ─── Tests: X-API-Key Authentication ─────────────────────────────────────────
+
+
+class TestApiKeyAuth:
+    def test_api_key_auth_on_protected_route(self, client):
+        """Valid X-API-Key authenticates on protected route"""
+        token, _ = _create_user(client, "apikey_auth@test.com", plan="pro")
+        # Create API token
+        r = client.post("/api/v1/user/api-token", headers=_auth_header(token))
+        assert r.status_code == 201
+        raw_key = r.get_json()["token"]
+        # Use X-API-Key to access a protected route (try create again → 409 means authenticated)
+        resp = client.post("/api/v1/user/api-token", headers={"X-API-Key": raw_key})
+        # 409 means we were authenticated; 401 means auth failed
+        assert resp.status_code == 409
+
+    def test_api_key_invalid(self, client):
+        """Invalid X-API-Key → 401"""
+        resp = client.post(
+            "/api/v1/user/api-token",
+            headers={"X-API-Key": "trf_invalidkeyXXXXXXXXXXXXXXXXXX"},
+        )
+        assert resp.status_code == 401
+
+    def test_api_key_revoked(self, client):
+        """Revoked X-API-Key → 401"""
+        token, _ = _create_user(client, "revoked_apikey@test.com", plan="pro")
+        # Create token
+        r = client.post("/api/v1/user/api-token", headers=_auth_header(token))
+        assert r.status_code == 201
+        raw_key = r.get_json()["token"]
+        # Revoke it
+        client.delete("/api/v1/user/api-token", headers=_auth_header(token))
+        # Try using revoked key
+        resp = client.post("/api/v1/user/api-token", headers={"X-API-Key": raw_key})
+        assert resp.status_code == 401
+
+    def test_revoke_then_cannot_auth(self, client):
+        """Full flow: create → use → revoke → X-API-Key rejected"""
+        token, _ = _create_user(client, "flow_test@test.com", plan="pro")
+        # Create
+        r = client.post("/api/v1/user/api-token", headers=_auth_header(token))
+        raw_key = r.get_json()["token"]
+        # Validate it works (409 because key exists)
+        r2 = client.post("/api/v1/user/api-token", headers={"X-API-Key": raw_key})
+        assert r2.status_code == 409
+        # Revoke
+        client.delete("/api/v1/user/api-token", headers=_auth_header(token))
+        # Try again with revoked key
+        r3 = client.post("/api/v1/user/api-token", headers={"X-API-Key": raw_key})
+        assert r3.status_code == 401
+
+
+# ─── Tests: Webhook ───────────────────────────────────────────────────────────
+
+
+class TestWebhook:
+    def test_create_webhook_pro(self, client):
+        """POST /api/v1/user/webhook — Pro user with provided secret → 201"""
+        token, _ = _create_user(client, "webhook_pro@test.com", plan="pro")
+        resp = client.post(
+            "/api/v1/user/webhook",
+            headers=_auth_header(token),
+            json={"url": "https://example.com/hook", "secret": "mysecret123"},
+        )
+        assert resp.status_code == 201
+        data = resp.get_json()
+        assert data["webhook_url"] == "https://example.com/hook"
+        assert data["secret"] == "mysecret123"
+
+    def test_create_webhook_auto_secret(self, client):
+        """POST without secret → auto-generated secret"""
+        token, _ = _create_user(client, "webhook_auto@test.com", plan="pro")
+        resp = client.post(
+            "/api/v1/user/webhook",
+            headers=_auth_header(token),
+            json={"url": "https://auto.example.com/hook"},
+        )
+        assert resp.status_code == 201
+        data = resp.get_json()
+        assert len(data["secret"]) == 64  # token_hex(32) = 64 hex chars
+
+    def test_create_webhook_non_pro_free(self, client):
+        """Free user → 403"""
+        token, _ = _create_user(client, "webhook_free@test.com", plan="free")
+        resp = client.post(
+            "/api/v1/user/webhook",
+            headers=_auth_header(token),
+            json={"url": "https://example.com/hook"},
+        )
+        assert resp.status_code == 403
+
+    def test_create_webhook_non_pro_premium(self, client):
+        """Premium user → 403"""
+        token, _ = _create_user(client, "webhook_premium@test.com", plan="premium")
+        resp = client.post(
+            "/api/v1/user/webhook",
+            headers=_auth_header(token),
+            json={"url": "https://example.com/hook"},
+        )
+        assert resp.status_code == 403
+
+    def test_create_webhook_url_not_https(self, client):
+        """HTTP URL → 400"""
+        token, _ = _create_user(client, "webhook_http@test.com", plan="pro")
+        resp = client.post(
+            "/api/v1/user/webhook",
+            headers=_auth_header(token),
+            json={"url": "http://example.com/hook"},
+        )
+        assert resp.status_code == 400
+        assert "https" in resp.get_json()["error"].lower()
+
+    def test_create_webhook_missing_url(self, client):
+        """Missing URL → 400"""
+        token, _ = _create_user(client, "webhook_nourl@test.com", plan="pro")
+        resp = client.post(
+            "/api/v1/user/webhook",
+            headers=_auth_header(token),
+            json={},
+        )
+        assert resp.status_code == 400
+
+    def test_webhook_upsert(self, client):
+        """Second POST updates URL (upsert behavior)"""
+        token, _ = _create_user(client, "webhook_upsert@test.com", plan="pro")
+        client.post(
+            "/api/v1/user/webhook",
+            headers=_auth_header(token),
+            json={"url": "https://first.example.com/hook"},
+        )
+        resp = client.post(
+            "/api/v1/user/webhook",
+            headers=_auth_header(token),
+            json={"url": "https://second.example.com/hook"},
+        )
+        assert resp.status_code == 201
+        assert resp.get_json()["webhook_url"] == "https://second.example.com/hook"
+
+    def test_delete_webhook(self, client):
+        """DELETE /api/v1/user/webhook → 200"""
+        token, _ = _create_user(client, "webhook_delete@test.com", plan="pro")
+        client.post(
+            "/api/v1/user/webhook",
+            headers=_auth_header(token),
+            json={"url": "https://delete.example.com/hook"},
+        )
+        resp = client.delete("/api/v1/user/webhook", headers=_auth_header(token))
+        assert resp.status_code == 200
+        assert resp.get_json()["deleted"] is True
+
+    def test_delete_webhook_not_configured(self, client):
+        """DELETE without webhook configured → 404"""
+        token, _ = _create_user(client, "webhook_notset@test.com", plan="pro")
+        resp = client.delete("/api/v1/user/webhook", headers=_auth_header(token))
+        assert resp.status_code == 404
+
+    def test_delete_webhook_non_pro(self, client):
+        """Free user DELETE → 403"""
+        token, _ = _create_user(client, "webhook_freedelete@test.com", plan="free")
+        resp = client.delete("/api/v1/user/webhook", headers=_auth_header(token))
+        assert resp.status_code == 403
+
+
+# ─── Tests: dispatch_webhook ──────────────────────────────────────────────────
+
+
+class TestDispatchWebhook:
+    def test_dispatch_no_webhook_configured(self):
+        """dispatch_webhook silently returns when no webhook is configured"""
+        with patch("api_v1.utils_webhook.get_db") as mock_get_db:
+            mock_conn = MagicMock()
+            mock_conn.execute.return_value.fetchone.return_value = None
+            mock_get_db.return_value = mock_conn
+
+            from api_v1.utils_webhook import dispatch_webhook
+
+            # Should not raise, should return silently
+            dispatch_webhook("nonexistent_user", "new_prediction", {"data": "test"})
+
+    def test_dispatch_sends_hmac_header(self):
+        """dispatch_webhook sends correct HMAC-SHA256 signature header"""
+        test_secret = "testsecret"
+        test_url = "https://hook.example.com/receive"
+        test_payload = {"race_id": "R123", "top1": "Cheval Blanc"}
+
+        with (
+            patch("api_v1.utils_webhook.get_db") as mock_get_db,
+            patch("api_v1.utils_webhook.requests.post") as mock_post,
+        ):
+            mock_row = MagicMock()
+            mock_row.__getitem__ = lambda self, key: (
+                test_url if key == "url" else test_secret
+            )
+            mock_conn = MagicMock()
+            mock_conn.execute.return_value.fetchone.return_value = mock_row
+            mock_get_db.return_value = mock_conn
+
+            mock_response = MagicMock()
+            mock_response.status_code = 200
+            mock_post.return_value = mock_response
+
+            from api_v1.utils_webhook import dispatch_webhook, EVENT_NEW_PREDICTION
+
+            dispatch_webhook("user123", EVENT_NEW_PREDICTION, test_payload)
+
+            assert mock_post.called
+            call_kwargs = mock_post.call_args
+            headers_sent = call_kwargs.kwargs.get("headers") or call_kwargs[1].get(
+                "headers"
+            )
+            assert "X-Turf-Signature" in headers_sent
+            assert headers_sent["X-Turf-Signature"].startswith("sha256=")
+            assert headers_sent["X-Turf-Event"] == EVENT_NEW_PREDICTION
Author	SHA1	Message	Date
DevOps Engineer	0492f06bfd	docs(HRT-96): Note Intelligence ML + documentation API v1 finale - Création POD/Intelligence/ML_Predictions_SaaS.md : architecture ML complète, flow ml_predictions_cache → ml_feedback_saas → paris → ROI dashboard, schéma données/jointures, décision duplication vs modification turf_scraper, documentation des 4 stratégies XGBoost, idempotence, usage CLI - Mise à jour DOCUMENTATION.md : ajout section Turf SaaS API v1 complète avec tous les endpoints documentés dont /api/v1/roi/* et /api/v1/ml/feedback/* (HRT-92 ROI backend + HRT-93 ML feedback loop) Co-Authored-By: Paperclip <noreply@paperclip.ing>	2026-04-30 21:28:52 +02:00
admin	91134e2f3f	Merge pull request '[HRT-83] feat: Météo & terrain intégrés dans prédictions ML (Premium)' (#10 ) from feature/HRT-83-meteo-terrain-ml-predictions into master Some checks failed CD / Deploy → Staging (push) Has been cancelled Details CD / Smoke Tests on Staging (push) Has been cancelled Details CD / Deploy → Production (push) Has been cancelled Details CD / Rollback Production (push) Has been cancelled Details	2026-04-30 08:40:16 +02:00
DevOps Engineer	663e0bb149	Merge PR #12 — [HRT-82] Multi-compte / Organisation Pro (max 5 users) Some checks failed CD / Deploy → Staging (push) Has been cancelled Details CD / Smoke Tests on Staging (push) Has been cancelled Details CD / Deploy → Production (push) Has been cancelled Details CD / Rollback Production (push) Has been cancelled Details Co-Authored-By: Paperclip <noreply@paperclip.ing>	2026-04-30 08:39:59 +02:00
admin	5c6b407f47	Merge pull request '[HRT-80] API Token personnel + Webhook alertes (Pro)' (#13 ) from feature/HRT-80-api-tokens-webhooks into master Some checks failed CD / Deploy → Staging (push) Has been cancelled Details CD / Smoke Tests on Staging (push) Has been cancelled Details CD / Deploy → Production (push) Has been cancelled Details CD / Rollback Production (push) Has been cancelled Details	2026-04-29 17:31:53 +02:00
DevOps Engineer	f300e44c74	feat(HRT-80): API Token personnel + Webhook alertes (Pro) - Nouveaux fichiers: api_tokens_db.py, api_v1/routes/user_tokens.py, api_v1/utils_webhook.py - Migration DB idempotente: tables user_api_tokens + user_webhooks - Endpoints POST/DELETE /api/v1/user/api-token (Pro only) - Endpoints POST/DELETE /api/v1/user/webhook (Pro only, HTTPS requis) - HMAC-SHA256 fire-and-forget dispatch webhook - auth.py: validate_api_key() + X-API-Key fallback dans jwt_required_middleware - saas_auth.py: import logging au niveau module, validate_api_key(), X-API-Key fallback - api_v1/__init__.py: enregistrement user_tokens_bp - 24 tests pytest — tous passent Co-Authored-By: Paperclip <noreply@paperclip.ing>	2026-04-29 17:25:30 +02:00
DevOps Engineer	bc5ee3fa1a	Merge feature/HRT-81-history-blueprint — Historique limité/illimité selon plan (Free/Premium/Pro) Co-Authored-By: Paperclip <noreply@paperclip.ing>	2026-04-29 17:05:01 +02:00
DevOps Engineer	ec024d8236	feat(HRT-83): intégrer météo & terrain dans prédictions ML (Premium) - scoring_v2.py : ajout get_terrain_condition() + compute_weather_impact() score_cheval_v2() accepte weather_data=None (backward-compat préservée) Impact météo/terrain sur [-5, +5] pts selon pénétromètre + vent + temp - api_v1/routes/predictions.py : _fetch_ml_predictions() avec include_weather=True LEFT JOIN pmu_courses (pénétromètre) + pmu_meteo sur date+num_reunion /predictions/all → terrain_condition + weather_impact dans chaque row /predictions/top3 → inchangé (free tier, pas de champs météo) - api_v1/routes/valuebets.py : même LEFT JOIN météo/terrain /valuebets → terrain_condition + weather_impact dans chaque value bet Tests : 42/42 passent (pytest tests/test_api_v1.py) Co-Authored-By: Paperclip <noreply@paperclip.ing>	2026-04-29 15:35:15 +02:00