"""
直接测试阵容推荐功能，不通过HTTP请求
"""
from src.data_provider import DataQueryAPI
from src.scoring.scoring_system import TeamScorer
from src.recommendation import RecommendationEngine
import copy

def test_direct_recommendation():
    """直接测试阵容推荐功能"""
    # 创建自定义配置
    config = {
        "base_weights": {
            "synergy_level_weight": 1.5,
            "synergy_count_weight": 0.8,
            "chess_cost_weight": 0.3
        },
        "synergy_weights": {
            "重装战士": 2.0,
            "斗士": 1.8
        },
        "chess_weights": {
            "盖伦": 2.0,
            "赛娜": 2.5
        },
        "synergy_level_weights": {
            "1": 1.0,
            "2": 1.2,
            "3": 1.5,
            "4": 1.8,
            "5": 2.0,
            "6": 2.3,
            "7": 2.6,
            "8": 3.0,
            "9": 3.3,
            "10": 3.5
        },
        "cost_weights": {
            "1": 1.0,
            "2": 1.2,
            "3": 1.5,
            "4": 1.8,
            "5": 2.0
        }
    }
    
    # 初始化组件
    data_api = DataQueryAPI()
    scorer = TeamScorer(api=data_api, config_obj=copy.deepcopy(config))
    engine = RecommendationEngine(api=data_api, scorer=scorer, config_obj=copy.deepcopy(config))
    
    # 定义参数
    population = 9
    required_synergies = []  # 这里可以添加必选羁绊
    required_chess = []  # 这里可以添加必选棋子
    max_results = 3
    
    # 生成阵容推荐
    print("正在生成阵容推荐...")
    teams = engine.recommend_team(
        population=population,
        required_synergies=required_synergies,
        required_chess=required_chess,
        max_results=max_results
    )
    
    # 打印结果
    print(f"生成了 {len(teams)} 个推荐阵容")
    
    for i, team in enumerate(teams):
        print(f"\n阵容 #{i+1} (评分: {team.score:.2f})")
        
        print("\n棋子列表:")
        for chess in team.chess_list:
            print(f"  {chess.get('displayName')} ({chess.get('price')}费)")
        
        print("\n激活的职业羁绊:")
        for job in team.synergy_levels['job']:
            print(f"  {job['name']} (等级 {job['level']})")
        
        print("\n激活的特质羁绊:")
        for race in team.synergy_levels['race']:
            print(f"  {race['name']} (等级 {race['level']})")
        
        print("\n" + "-"*50)

if __name__ == "__main__":
    test_direct_recommendation()