config_examples.py

#!/usr/bin/env python3
# -*- coding: utf-8 -*-

"""
参数配置使用示例
演示如何在Lambda函数中使用参数管理器
"""

import os
import sys
from pathlib import Path

# 添加项目根目录到Python路径
project_root = Path(__file__).parent
sys.path.insert(0, str(project_root))

from src.utils.parameter_manager import get_config_manager, get_config

def example_video_processor():
    """视频处理器中的配置使用示例"""
    print("📹 视频处理器配置示例")
    print("-" * 40)
    
    # 方法1: 使用全局配置管理器
    config_manager = get_config_manager('prod')
    video_config = config_manager.get_video_processing_config()
    
    print(f"每段帧数: {video_config['frames_per_segment']}")
    print(f"帧间隔: {video_config['frame_interval']}秒")
    print(f"分段时长: {video_config['segment_duration']}秒 (自动计算)")
    print(f"支持格式: {video_config['supported_formats']}")
    
    # 方法2: 直接获取单个配置
    frames_per_segment = get_config('video/frames_per_segment', 30)
    frame_interval = get_config('video/frame_interval', 2)
    
    # 在实际处理中使用
    segment_duration = frames_per_segment * frame_interval
    print(f"\n实际使用:")
    print(f"将视频分割为 {segment_duration} 秒的段")
    print(f"每段包含 {frames_per_segment} 帧")
    print(f"每 {frame_interval} 秒提取一帧")

def example_ai_analyzer():
    """AI分析器中的配置使用示例"""
    print("\n🤖 AI分析器配置示例")
    print("-" * 40)
    
    config_manager = get_config_manager('prod')
    ai_config = config_manager.get_ai_config()
    
    print(f"模型ID: {ai_config['model_id']}")
    print(f"最大Token: {ai_config['max_tokens']}")
    print(f"温度: {ai_config['temperature']}")
    print(f"置信度阈值: {ai_config['confidence_threshold']}")
    print(f"最大重试: {ai_config['max_retries']}")
    
    # 模拟AI分析调用
    def analyze_frame(frame_data):
        """模拟帧分析"""
        # 使用配置中的参数
        model_params = {
            'model_id': ai_config['model_id'],
            'max_tokens': ai_config['max_tokens'],
            'temperature': ai_config['temperature'],
            'top_p': ai_config['top_p']
        }
        
        # 模拟分析结果
        confidence = 0.85
        hands_on_wheel = confidence > ai_config['confidence_threshold']
        
        return {
            'hands_on_wheel': hands_on_wheel,
            'confidence': confidence,
            'model_params': model_params
        }
    
    # 示例调用
    result = analyze_frame("frame_data")
    print(f"\n分析结果示例:")
    print(f"手在方向盘上: {result['hands_on_wheel']}")
    print(f"置信度: {result['confidence']}")

def example_lambda_config():
    """Lambda配置使用示例"""
    print("\n🔧 Lambda配置示例")
    print("-" * 40)
    
    config_manager = get_config_manager('prod')
    lambda_config = config_manager.get_lambda_config()
    
    print(f"并发限制: {lambda_config['concurrency_limit']}")
    print(f"超时时间: {lambda_config['timeout']}秒")
    print(f"视频处理器内存: {lambda_config['video_processor_memory']}MB")
    print(f"AI分析器内存: {lambda_config['ai_analyzer_memory']}MB")
    
    # 在CDK中使用这些配置
    cdk_config_example = f"""
# 在CDK堆栈中使用配置
lambda_function = lambda_.Function(
    self, "VideoProcessor",
    memory_size={lambda_config['video_processor_memory']},
    timeout=Duration.seconds({lambda_config['timeout']}),
    reserved_concurrent_executions={lambda_config['concurrency_limit']},
    # ... 其他配置
)
"""
    print(f"\nCDK使用示例:")
    print(cdk_config_example)

def example_environment_specific():
    """不同环境配置示例"""
    print("\n🌍 不同环境配置示例")
    print("-" * 40)
    
    environments = ['dev', 'test', 'prod']
    
    for env in environments:
        config_manager = get_config_manager(env)
        
        # 获取关键配置
        concurrency = config_manager.get_config('lambda/concurrency_limit', 20)
        frames_per_segment = config_manager.get_config('video/frames_per_segment', 30)
        log_level = config_manager.get_config('monitoring/log_level', 'INFO')
        
        print(f"{env.upper()} 环境:")
        print(f"  并发数: {concurrency}")
        print(f"  每段帧数: {frames_per_segment}")
        print(f"  日志级别: {log_level}")

def example_dynamic_config_update():
    """动态配置更新示例"""
    print("\n🔄 动态配置更新示例")
    print("-" * 40)
    
    config_manager = get_config_manager('dev')
    
    # 获取当前配置
    current_interval = config_manager.get_config('video/frame_interval', 2)
    print(f"当前帧间隔: {current_interval}秒")
    
    # 更新配置
    new_interval = 3
    if config_manager.update_config('video/frame_interval', str(new_interval)):
        print(f"✅ 已更新帧间隔为: {new_interval}秒")
        
        # 重新计算分段时长
        frames_per_segment = config_manager.get_config('video/frames_per_segment', 30)
        new_segment_duration = frames_per_segment * new_interval
        print(f"新的分段时长: {new_segment_duration}秒")
    else:
        print("❌ 配置更新失败")

def example_config_validation():
    """配置验证示例"""
    print("\n🔍 配置验证示例")
    print("-" * 40)
    
    config_manager = get_config_manager('prod')
    validation_result = config_manager.validate_config()
    
    print(f"配置有效: {validation_result['valid']}")
    
    if validation_result['errors']:
        print("错误:")
        for error in validation_result['errors']:
            print(f"  ❌ {error}")
    
    if validation_result['warnings']:
        print("警告:")
        for warning in validation_result['warnings']:
            print(f"  ⚠️  {warning}")
    
    if validation_result['recommendations']:
        print("建议:")
        for rec in validation_result['recommendations']:
            print(f"  💡 {rec}")

def main():
    """主函数 - 运行所有示例"""
    print("🎯 驾驶员手部检测系统 - 参数配置使用示例")
    print("=" * 60)
    
    try:
        example_video_processor()
        example_ai_analyzer()
        example_lambda_config()
        example_environment_specific()
        example_dynamic_config_update()
        example_config_validation()
        
        print("\n" + "=" * 60)
        print("✅ 所有示例运行完成")
        print("\n💡 提示:")
        print("1. 在实际Lambda函数中，只需导入 get_config 函数")
        print("2. 配置会自动从Parameter Store读取")
        print("3. 支持缓存，避免重复读取")
        print("4. 可以在AWS控制台直接修改配置")
        
    except Exception as e:
        print(f"❌ 示例运行失败: {e}")
        import traceback
        traceback.print_exc()

if __name__ == "__main__":
    main()