Initial commit: existing turf_saas codebase
Co-Authored-By: Paperclip <noreply@paperclip.ing>
This commit is contained in:
ML Engineer
347
agent_turf.py
Executable file
347
agent_turf.py
Executable file
@@ -0,0 +1,347 @@
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#!/usr/bin/env python3
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"""
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Agent Turf Autonome - Prédictions quotidiennes
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Usage: python3 agent_turf.py [--dry-run]
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"""
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import sqlite3
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import subprocess
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import sys
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import json
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import os
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from datetime import datetime, timedelta
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from pathlib import Path
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DB_PATH = "/home/h3r7/turf_scraper/turf.db"
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LOG_FILE = "/home/h3r7/turf_scraper/logs/agent_turf.log"
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VPS_HOST = "10.0.1.1"
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def log(msg: str):
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"""Log avec timestamp"""
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timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
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line = f"[{timestamp}] {msg}"
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print(line)
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os.makedirs(os.path.dirname(LOG_FILE), exist_ok=True)
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with open(LOG_FILE, "a") as f:
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f.write(line + "\n")
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def sync_database():
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"""Sync base de données depuis VPS"""
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log("=== SYNC DATABASE ===")
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# Check remote size
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cmd = f"sshpass -p 'Cronstadt35*' ssh -o StrictHostKeyChecking=no h3r7@{VPS_HOST} stat -c %s {DB_PATH}"
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result = subprocess.run(cmd, shell=True, capture_output=True, text=True)
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if result.returncode != 0:
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log(f"ERROR: Cannot connect to VPS")
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return False
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remote_size = int(result.stdout.strip())
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local_size = os.path.getsize(DB_PATH) if os.path.exists(DB_PATH) else 0
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if remote_size == local_size:
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log(f"Database up to date ({remote_size} bytes)")
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return True
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log(f"Syncing database (remote: {remote_size}, local: {local_size})...")
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cmd = f"sshpass -p 'Cronstadt35*' scp -o StrictHostKeyChecking=no h3r7@{VPS_HOST}:{DB_PATH} {DB_PATH}.tmp"
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result = subprocess.run(cmd, shell=True, capture_output=True)
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if result.returncode == 0:
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os.rename(DB_PATH + ".tmp", DB_PATH)
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log(f"Database synced successfully")
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return True
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else:
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log(f"ERROR: Sync failed")
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return False
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def generate_predictions():
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"""Génère les prédictions du jour"""
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log("=== GENERATE PREDICTIONS ===")
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conn = sqlite3.connect(DB_PATH)
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conn.row_factory = sqlite3.Row
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cursor = conn.cursor()
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today = datetime.now().strftime("%Y-%m-%d")
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# Get today's races
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cursor.execute(
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"""
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SELECT DISTINCT c.date_programme, c.num_reunion, c.num_course,
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c.libelle, c.heure_depart_str, r.hippodrome_court
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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'
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ORDER BY c.heure_depart_str
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""",
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(today,),
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)
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races = cursor.fetchall()
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log(f"Found {len(races)} races today")
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predictions = []
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for race in races:
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date, num_reunion, num_course, libelle, heure, hippodrome = race
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# Get scoring
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cursor.execute(
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"""
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SELECT horse_name, horse_number, score, cote, rang_scoring
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FROM scoring
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WHERE date = ? AND race_name LIKE ?
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ORDER BY rang_scoring
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LIMIT 4
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""",
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(date, f"%{libelle}%"),
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)
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scores = cursor.fetchall()
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if scores:
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pred = {
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"race": f"{heure} - {hippodrome} - {libelle}",
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"top4": [dict(s) for s in scores],
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}
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predictions.append(pred)
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log(
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f" {pred['race'][:50]} -> {', '.join([s['horse_name'] for s in scores[:3]])}"
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)
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conn.close()
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return predictions
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def save_recommendations(predictions):
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"""Sauvegarde les recommandations en base"""
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log("=== SAVE RECOMMENDATIONS ===")
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conn = sqlite3.connect(DB_PATH)
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cursor = conn.cursor()
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today = datetime.now().strftime("%Y-%m-%d")
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# Clear today's recommendations
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cursor.execute("DELETE FROM recommendations WHERE date = ?", (today,))
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for pred in predictions:
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race_name = pred["race"]
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# Add top 4
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for i, horse in enumerate(pred["top4"]):
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if i < 4: # TOP 4
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cursor.execute(
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"""
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INSERT INTO recommendations
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(date, race_name, type_pari, cheval1, numero1, cote, mise, confiance, justification)
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VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)
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""",
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(
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today,
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race_name,
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f"top{i + 1}",
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horse["horse_name"],
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horse["horse_number"],
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horse["cote"],
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2.0,
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f"TOP {i + 1}",
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f"Score: {horse['score']}, Rang scoring: {horse['rang_scoring']}",
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),
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)
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# Add simple winner (top 1)
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top1 = pred["top4"][0]
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cursor.execute(
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"""
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INSERT INTO recommendations
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(date, race_name, type_pari, cheval1, numero1, cote, mise, confiance, justification)
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VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)
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""",
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(
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today,
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race_name,
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"simple_gagnant",
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top1["horse_name"],
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top1["horse_number"],
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top1["cote"],
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2.0,
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"🔥 FORTE" if top1["score"] > 60 else "✅ BONNE",
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f"Score: {top1['score']}, Favorite prediction",
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),
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)
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conn.commit()
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conn.close()
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log(f"Saved {len(predictions)} race recommendations")
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def notify_telegram(predictions):
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"""Envoie les prédictions du jour via Telegram"""
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import urllib.request
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config_path = "/home/h3r7/turf_scraper/config_telegram.json"
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if not os.path.exists(config_path):
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log("No Telegram config found, skipping notification")
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return
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try:
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with open(config_path, "r") as f:
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cfg = json.load(f)
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token = cfg.get("token", "")
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chat_id = cfg.get("chat_id", "")
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if not token or not chat_id:
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log("Telegram config missing token or chat_id")
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return
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except Exception as e:
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log(f"Error reading Telegram config: {e}")
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return
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today = datetime.now().strftime("%d/%m/%Y")
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lines = [f"🏇 *Prédictions Turf — {today}*", ""]
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if not predictions:
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lines.append("Aucune prédiction disponible aujourd'hui.")
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else:
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for pred in predictions:
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race_label = pred.get("race", "Course inconnue")
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top4 = pred.get("top4", [])
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lines.append(f"📍 *{race_label}*")
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for i, horse in enumerate(top4, 1):
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name = horse.get("horse_name", "?")
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score = horse.get("score", 0)
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cote = horse.get("cote", "?")
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icon = "🥇" if i == 1 else ("🥈" if i == 2 else ("🥉" if i == 3 else "4️⃣"))
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lines.append(f" {icon} {name} — score: {score} — cote: {cote}")
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lines.append("")
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text = "\n".join(lines)
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url = f"https://api.telegram.org/bot{token}/sendMessage"
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payload = json.dumps({
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"chat_id": chat_id,
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"text": text,
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"parse_mode": "Markdown"
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}).encode("utf-8")
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try:
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req = urllib.request.Request(
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url,
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data=payload,
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headers={"Content-Type": "application/json"},
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method="POST"
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)
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with urllib.request.urlopen(req, timeout=10) as resp:
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result = json.loads(resp.read().decode("utf-8"))
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if result.get("ok"):
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log(f"Telegram notification sent ({len(predictions)} races)")
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else:
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log(f"Telegram API error: {result}")
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except Exception as e:
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log(f"Error sending Telegram notification: {e}")
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def run_backtest_yesterday():
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"""Lance le backtest sur les résultats d'hier"""
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log("=== RUN BACKTEST ===")
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yesterday = (datetime.now() - timedelta(days=1)).strftime("%Y-%m-%d")
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# Check if we have results for yesterday
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conn = sqlite3.connect(DB_PATH)
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cursor = conn.cursor()
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cursor.execute(
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"""
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SELECT COUNT(*) FROM pmu_partants
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WHERE date_programme = ? AND ordre_arrivee > 0
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""",
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(yesterday,),
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)
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count = cursor.fetchone()[0]
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conn.close()
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if count > 0:
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log(f"Running backtest for {yesterday}...")
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# Run backtest script
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cmd = f"cd /home/h3r7/turf_scraper && python3 backtest_analyzer.py --date {yesterday}"
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result = subprocess.run(cmd, shell=True, capture_output=True, text=True)
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if result.returncode == 0:
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log("Backtest completed")
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else:
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log(f"Backtest failed: {result.stderr}")
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else:
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log(f"No results for {yesterday}, skipping backtest")
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def update_paris_results():
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"""Met à jour les paris avec les résultats PMU"""
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log("=== UPDATE PARIS RESULTS ===")
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today = datetime.now().strftime("%Y-%m-%d")
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cmd = (
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f"cd /home/h3r7/turf_scraper && python3 update_paris_results.py --date {today}"
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)
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result = subprocess.run(cmd, shell=True, capture_output=True, text=True)
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if result.returncode == 0:
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log(f"Paris updated: {result.stdout.strip()}")
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else:
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log(f"Paris update failed: {result.stderr}")
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def main():
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"""Point d'entrée principal"""
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dry_run = "--dry-run" in sys.argv
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log("=" * 50)
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log("🤖 AGENT TURF AUTONOME - DEMARRAGE")
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log("=" * 50)
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try:
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# 1. Sync database
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if not dry_run:
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sync_database()
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# 2. Generate predictions
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predictions = generate_predictions()
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# 3. Save recommendations
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if not dry_run and predictions:
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save_recommendations(predictions)
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# 3b. Send Telegram notification
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if not dry_run:
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notify_telegram(predictions)
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# 4. Create paris from recommendations
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if not dry_run and predictions:
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update_paris_results()
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# 5. Run backtest on yesterday
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if not dry_run:
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run_backtest_yesterday()
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log("=" * 50)
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log("✅ AGENT TURF - TERMINÉ")
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log("=" * 50)
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except Exception as e:
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log(f"❌ ERREUR: {e}")
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import traceback
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traceback.print_exc()
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sys.exit(1)
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if __name__ == "__main__":
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main()
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