turf_saas/api_v1/routes/valuebets.py

#!/usr/bin/env python3
"""
Value bets route for API v1.

GET /api/v1/valuebets  — Value bets du jour (premium+)
"""

from datetime import datetime
from flask import Blueprint, jsonify, request

from api_v1.utils import (
    get_db,
    table_exists,
    internal_error,
    get_pagination_params,
    paginate_query,
)
from auth import jwt_required_middleware, plan_required

valuebets_bp = Blueprint("v1_valuebets", __name__, url_prefix="/api/v1")


@valuebets_bp.route("/valuebets", methods=["GET"])
@jwt_required_middleware
@plan_required("premium", "pro")
def valuebets():
    """
    Value bets du jour
    ---
    tags:
      - Value Bets
    summary: Value bets du jour — chevaux à cote surévaluée par le marché (premium+)
    security:
      - Bearer: []
    parameters:
      - name: date
        in: query
        type: string
        format: date
        description: Date YYYY-MM-DD (défaut aujourd'hui)
      - name: min_odds
        in: query
        type: number
        default: 2.0
        description: Cote minimale pour filtrer les value bets
      - name: limit
        in: query
        type: integer
        default: 20
      - name: offset
        in: query
        type: integer
        default: 0
    responses:
      200:
        description: Value bets du jour avec météo et terrain (HRT-83)
      401:
        description: Token invalide
      403:
        description: Plan insuffisant (premium ou pro requis)
    """
    date_param = request.args.get("date", datetime.now().strftime("%Y-%m-%d"))
    limit, offset = get_pagination_params(default_limit=20, max_limit=100)

    try:
        min_odds = float(request.args.get("min_odds", 2.0))
    except (ValueError, TypeError):
        min_odds = 2.0

    conn = get_db()
    try:
        rows_raw = []
        total = 0

        if table_exists(conn, "ml_predictions_cache"):
            count_row = conn.execute(
                """SELECT COUNT(*) as cnt
                   FROM ml_predictions_cache
                   WHERE date = ? AND is_value_bet = 1 AND odds >= ?""",
                (date_param, min_odds),
            ).fetchone()
            total = count_row["cnt"] if count_row else 0

            # 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)

        pagination = paginate_query(valuebets_list, total, limit, offset)

        return jsonify(
            {
                "status": "ok",
                "date": date_param,
                "min_odds": min_odds,
                "valuebets": valuebets_list,
                **pagination,
            }
        ), 200

    except Exception as e:
        return internal_error(str(e))
    finally:
        conn.close()