- 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>
514 lines
16 KiB
Python
Executable File
514 lines
16 KiB
Python
Executable File
#!/usr/bin/env python3
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"""
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Scoring Engine V2 - ZE 2 sur 4 Optimise
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Cote: 10%, Forme: 30%, Bonus outsider
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"""
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import requests
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import sqlite3
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import json
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import re
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from datetime import datetime
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DB_PATH = "/home/h3r7/turf_saas/turf_saas.db"
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HEADERS = {"User-Agent": "Mozilla/5.0", "Accept": "application/json"}
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def get_cote_from_db(horse_name, date_course):
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"""Recupere la cote depuis la table predictions (plus recente et non nulle)"""
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conn = sqlite3.connect(DB_PATH)
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conn.row_factory = sqlite3.Row
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c = conn.execute(
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"""
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SELECT odds FROM predictions
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WHERE date=? AND horse_name LIKE ? AND odds > 0
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ORDER BY created_at DESC LIMIT 1
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""",
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(date_course, f"%{horse_name}%"),
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)
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r = c.fetchone()
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conn.close()
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return r["odds"] if r else 0
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def parse_musique(musique):
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if not musique:
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return {}
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clean = re.sub(r"\(\d+\)", "", musique)
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resultats = re.findall(r"(\d+|D|0)([amphsc]?)", clean)
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positions = []
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for pos, disc in resultats[:10]:
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positions.append(99 if pos == "D" else int(pos))
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if not positions:
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return {}
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nb_courses = len(positions)
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nb_victoires = positions.count(1)
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nb_places = sum(1 for p in positions if 1 <= p <= 3)
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recentes = [p for p in positions[:3] if p != 99]
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forme_recente = sum(recentes) / len(recentes) if recentes else 99
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tendance = (
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(sum(positions[-4:]) / 4 - sum(positions[:4]) / 4) if len(positions) >= 4 else 0
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)
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return {
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"forme_recente": round(forme_recente, 1),
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"tendance": round(tendance, 1),
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"tx_victoire": round(nb_victoires / nb_courses * 100, 1) if nb_courses else 0,
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"tx_place": round(nb_places / nb_courses * 100, 1) if nb_courses else 0,
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}
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def get_terrain_condition(penetrometre_intitule: str | None) -> str:
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"""Normalise le pénétromètre PMU en condition terrain standardisée."""
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if not penetrometre_intitule:
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return "inconnu"
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val = penetrometre_intitule.upper()
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if any(k in val for k in ("TRES BON", "TRÈS BON", "FERME", "FIRM")):
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return "bon"
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if any(k in val for k in ("BON", "GOOD", "STANDARD")):
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return "bon"
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if any(k in val for k in ("SOUPLE", "YIELDING", "COLLANT")):
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return "souple"
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if any(k in val for k in ("LOURD", "HEAVY", "TRES SOUPLE", "TRÈS SOUPLE")):
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return "lourd"
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if any(k in val for k in ("SOFT", "MOU")):
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return "souple"
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return "inconnu"
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def compute_weather_impact(weather_data: dict | None, terrain_condition: str) -> float:
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"""
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Calcule un score d'impact météo/terrain sur [−5, +5].
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weather_data keys attendues : nebulositecode, temperature, force_vent
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terrain_condition : 'bon' | 'souple' | 'lourd' | 'inconnu'
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Retourne un delta de score ML (positif = favorable, négatif = défavorable).
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"""
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if not weather_data:
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return 0.0
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delta = 0.0
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# Terrain
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if terrain_condition == "lourd":
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delta -= 3.0
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elif terrain_condition == "souple":
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delta -= 1.5
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elif terrain_condition == "bon":
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delta += 1.0
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# inconnu → 0
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# Vent
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force_vent = weather_data.get("force_vent") or 0
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try:
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force_vent = float(force_vent)
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except (TypeError, ValueError):
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force_vent = 0.0
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if force_vent >= 50:
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delta -= 2.0
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elif force_vent >= 30:
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delta -= 1.0
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# Températures extrêmes
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temperature = weather_data.get("temperature")
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try:
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temperature = float(temperature) if temperature is not None else None
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except (TypeError, ValueError):
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temperature = None
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if temperature is not None:
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if temperature <= 0:
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delta -= 1.0
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elif temperature >= 35:
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delta -= 1.0
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return round(max(-5.0, min(5.0, delta)), 2)
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def score_cheval_v2(p, all_participants, today, weather_data=None):
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"""
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Score un cheval pour le modèle V2.
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weather_data (optionnel) : dict issu de pmu_meteo pour cette réunion.
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Backward-compatible : weather_data=None → comportement identique à avant HRT-83.
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"""
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score = 0
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details = {}
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# 1. COTE - Essaye PMU API, sinon DB
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horse_name = p.get("nom", "")
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cote = 0
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# Essayer d'abord depuis l'API PMU
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rapport = p.get("dernierRapportDirect", {})
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if rapport:
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cote = rapport.get("rapport", 0)
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if not cote:
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rapport_ref = p.get("dernierRapportReference", {})
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cote = rapport_ref.get("rapport", 0) if rapport_ref else 0
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# Fallback: aller chercher dans la DB
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if not cote or cote == 0:
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cote = get_cote_from_db(horse_name, today)
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# Si toujours pas de cote, utiliser 99 comme valeur par defaut
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if not cote or cote == 0:
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cote = 99.0
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score_cote = max(2, min(10, 20 / (1 + cote * 0.15))) if cote > 0 else 2
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score += score_cote
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details["cote"] = round(cote, 1)
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details["score_cote"] = round(score_cote, 1)
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# 2. FORME - AUGMENTE a 30 pts
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musique_stats = parse_musique(p.get("musique", ""))
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forme = musique_stats.get("forme_recente", 99)
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score_forme = (
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30
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if forme <= 1
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else 25
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if forme <= 2
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else 20
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if forme <= 3
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else 15
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if forme <= 5
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else 8
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if forme <= 8
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else 0
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)
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score += score_forme
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details["forme_recente"] = forme
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details["score_forme"] = score_forme
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# 3. TAUX VICTOIRE (15 pts)
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nb_courses_total = p.get("nombreCourses", 0)
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nb_victoires_total = p.get("nombreVictoires", 0)
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tx_vic = (nb_victoires_total / nb_courses_total * 100) if nb_courses_total else 0
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score_vic = min(15, tx_vic * 0.5)
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score += score_vic
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details["tx_victoire"] = round(tx_vic, 1)
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details["score_victoire"] = round(score_vic, 1)
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# 4. TAUX PLACE (15 pts)
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nb_places_total = p.get("nombrePlaces", 0)
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tx_place = (nb_places_total / nb_courses_total * 100) if nb_courses_total else 0
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score_place = min(15, tx_place * 0.2)
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score += score_place
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details["tx_place"] = round(tx_place, 1)
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details["score_place"] = round(score_place, 1)
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# 5. REDUCTION KM (10 pts)
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rk = p.get("reductionKilometrique", 0)
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all_rk = [
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x.get("reductionKilometrique", 0)
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for x in all_participants
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if x.get("reductionKilometrique", 0) > 0
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]
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if rk > 0 and all_rk:
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score_rk = (
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10 * (1 - (rk - min(all_rk)) / (max(all_rk) - min(all_rk)))
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if max(all_rk) > min(all_rk)
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else 5
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)
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else:
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score_rk = 0
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score += score_rk
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details["rk"] = rk
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details["score_rk"] = round(score_rk, 1)
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# 6. TENDANCE (10 pts)
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tendance = musique_stats.get("tendance", 0)
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score_tendance = min(10, max(0, 5 + tendance))
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score += score_tendance
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details["tendance"] = tendance
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details["score_tendance"] = round(score_tendance, 1)
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# 7. AVIS ENTRAINEUR (5 pts)
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avis = p.get("avisEntraineur", "NEUTRE")
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score_avis = {
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"POSITIF": 5,
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"TRES_POSITIF": 5,
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"NEUTRE": 2,
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"NEGATIF": 0,
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"TRES_NEGATIF": 0,
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}.get(avis, 2)
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score += score_avis
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details["avis_entraineur"] = avis
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details["score_avis"] = score_avis
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# 8. BONUS OUTSIDER (5 pts)
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bonus_outsider = 5 if forme <= 3 and cote >= 10 else 0
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score += bonus_outsider
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details["bonus_outsider"] = bonus_outsider
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# Driver change penalty
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if p.get("driverChange", False):
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score -= 3
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details["driver_change"] = True
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# 9. METEO & TERRAIN (HRT-83) — premium feature, weather_data=None → skip
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penetrometre = p.get("penetrometre_intitule", "") or ""
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terrain_condition = (
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get_terrain_condition(penetrometre) if penetrometre else "inconnu"
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)
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weather_impact = 0.0
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if weather_data is not None:
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weather_impact = compute_weather_impact(weather_data, terrain_condition)
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score += weather_impact
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details["terrain_condition"] = terrain_condition
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details["weather_impact"] = weather_impact
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details["score_total"] = round(score, 1)
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details["musique"] = p.get("musique", "")
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details["nb_victoires"] = nb_victoires_total
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details["nb_places"] = nb_places_total
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details["nb_courses"] = nb_courses_total
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return round(score, 1), details
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def get_ze2sur4_combinaisons(top4):
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combinaisons = []
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for i in range(4):
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for j in range(i + 1, 4):
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c1 = top4[i]
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c2 = top4[j]
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combinaisons.append(
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{
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"cheval1": c1["nom"],
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"numero1": c1["numero"],
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"cheval2": c2["nom"],
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"numero2": c2["numero"],
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"mise": 1.0,
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}
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)
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return combinaisons
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def build_recommendations_v2(scored_horses):
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ranked = sorted(scored_horses, key=lambda x: x["score"], reverse=True)
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if len(ranked) < 4:
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return None
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top1, top2, top3, top4 = ranked[0], ranked[1], ranked[2], ranked[3]
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top4_list = ranked[:4]
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def confiance(s):
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return (
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"FORTE"
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if s >= 55
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else "BONNE"
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if s >= 45
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else "MOYENNE"
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if s >= 35
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else "FAIBLE"
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)
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ze2_combinaisons = get_ze2sur4_combinaisons(top4_list)
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mise_ze2 = len(ze2_combinaisons) * 1.0
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return {
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"simple_gagnant": {
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"cheval": top1["nom"],
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"numero": top1["numero"],
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"cote": top1["details"]["cote"],
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"score": top1["score"],
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"confiance": confiance(top1["score"]),
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"mise_suggeree": 2.0,
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"gain_potentiel": round(2.0 * top1["details"]["cote"], 2),
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},
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"ze2_sur_4": {
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"top4": [{"nom": h["nom"], "numero": h["numero"]} for h in top4_list],
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"combinaisons": ze2_combinaisons,
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"mise_totale": mise_ze2,
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"nb_combinaisons": len(ze2_combinaisons),
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"confiance": confiance(
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(top1["score"] + top2["score"] + top3["score"] + top4["score"]) / 4
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),
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"explication": "Jouer les 6 combinaisons de 2 chevaux parmi les 4 premiers",
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},
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"outsider": _find_outsider(ranked),
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"budget_total": 2.0 + mise_ze2,
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}
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def _find_outsider(ranked):
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for h in ranked[3:7]:
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d = h["details"]
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if d["cote"] >= 12 and d["forme_recente"] <= 4 and d["bonus_outsider"] == 5:
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return {
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"cheval": h["nom"],
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"numero": h["numero"],
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"cote": d["cote"],
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"mise_suggeree": 1.0,
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"gain_potentiel": round(1.0 * d["cote"], 2),
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}
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return None
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def save_to_db(scored_horses, date_course, hippodrome, libelle):
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conn = sqlite3.connect(DB_PATH)
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cursor = conn.cursor()
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cursor.execute("DELETE FROM scoring WHERE date = ?", (date_course,))
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for i, h in enumerate(scored_horses, 1):
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d = h["details"]
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cursor.execute(
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"""
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INSERT INTO scoring (date, race_name, horse_number, horse_name, score,
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score_cote, score_forme, score_victoire, score_place, score_rk,
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score_tendance, score_avis, cote, forme_recente, tx_victoire, tx_place,
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avis_entraineur, musique, rang_scoring, scoring_version)
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VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, 'v2')
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""",
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(
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date_course,
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libelle,
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h["numero"],
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h["nom"],
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h["score"],
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d.get("score_cote", 0),
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d.get("score_forme", 0),
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d.get("score_victoire", 0),
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d.get("score_place", 0),
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d.get("score_rk", 0),
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d.get("score_tendance", 0),
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d.get("score_avis", 0),
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d.get("cote", 0),
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d.get("forme_recente", 0),
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d.get("tx_victoire", 0),
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d.get("tx_place", 0),
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d.get("avis_entraineur", ""),
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d.get("musique", ""),
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i,
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),
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)
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conn.commit()
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conn.close()
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print(f"💾 {len(scored_horses)} scores enregistres en BDD pour {date_course}")
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def main():
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today = datetime.now().strftime("%Y-%m-%d")
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date_pmu = datetime.now().strftime("%d%m%Y")
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print(
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f"=== SCORING V2 - ZE2 SUR4 OPTIMISE === {datetime.now().strftime('%d/%m/%Y %H:%M')} ==="
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)
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try:
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url = f"https://turfinfo.api.pmu.fr/rest/client/1/programme/{date_pmu}/reunions"
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r = requests.get(url, headers=HEADERS, timeout=15)
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reunions = r.json().get("programme", {}).get("reunions", [])
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except Exception as e:
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print(f"Erreur: {e}")
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return
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quinte = None
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for reunion in reunions:
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for course in reunion.get("courses", []):
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paris_types = [p["typePari"] for p in course.get("paris", [])]
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if any("QUINTE" in p for p in paris_types) or "PARIS-TURF" in course.get(
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"libelle", ""
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):
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quinte = (
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reunion["numOfficiel"],
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course["numOrdre"],
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course.get("libelle", ""),
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reunion["hippodrome"]["libelleCourt"],
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course.get("heureDepart", 0),
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)
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break
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if quinte:
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break
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if not quinte:
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# Fallback: utiliser la premiere reunion francaise avec predictions
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conn = sqlite3.connect(DB_PATH)
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conn.row_factory = sqlite3.Row
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r = conn.execute(
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"""
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SELECT r.num_reunion, r.hippodrome_court, c.num_course, c.libelle
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FROM pmu_courses c
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JOIN pmu_reunions r ON r.date_programme=c.date_programme AND r.num_reunion=c.num_reunion
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WHERE c.date_programme=? AND r.pays_code='FRA' AND c.num_course=1
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AND EXISTS (SELECT 1 FROM predictions p WHERE p.date=? AND p.source='canalturf_partants'
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AND p.race_name LIKE '%' || c.libelle || '%')
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ORDER BY c.heure_depart_str ASC LIMIT 1
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""",
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(today, today),
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).fetchone()
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conn.close()
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if r:
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quinte = (
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r["num_reunion"],
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r["num_course"],
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r["libelle"],
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r["hippodrome_court"],
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0,
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)
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else:
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print("Aucune course trouvee")
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return
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num_r, num_c, libelle, hippodrome, heure_ts = quinte
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heure = (
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datetime.fromtimestamp(heure_ts / 1000).strftime("%H:%M")
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if heure_ts
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else "13:55"
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)
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print(f"Course: {libelle} - {hippodrome} {heure}")
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try:
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url = f"https://turfinfo.api.pmu.fr/rest/client/1/programme/{date_pmu}/R{num_r}/C{num_c}/participants"
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r = requests.get(url, headers=HEADERS, timeout=15)
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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)
|
||
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}"
|
||
)
|
||
|
||
save_to_db(ranked, today, hippodrome, libelle)
|
||
|
||
reco = build_recommendations_v2(scored_horses)
|
||
if reco:
|
||
print(f"\n=== RECOMMANDATIONS ===")
|
||
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"\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" Confiance: {ze2['confiance']}")
|
||
print(f" Combinaisons:")
|
||
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()
|