Python 鼻炎在线预约挂号评价系统微信小程序设计与开发

核心代码参考示例

预测算法代码如下（示例）：

def appointment_forecast():
    import datetime
    if request.method in ["POST", "GET"]:
        msg = {'code': normal_code, 'message': 'success'}
        req_dict = session.get("req_dict")
        connection = pymysql.connect(**mysql_config)
        query = "SELECT patient_id, doctor_id, status, visit_time, rating FROM appointment_info"
        data = pd.read_sql(query, connection).dropna()
        id = req_dict.pop('id', None)
        req_dict.pop('addtime', None)
        df = to_forecast(data, req_dict, None)
        connection_string = f"mysql+pymysql://{mysql_config['user']}:{mysql_config['password']}@{mysql_config['host']}:{mysql_config['port']}/{mysql_config['database']}"
        engine = create_engine(connection_string)
        try:
            if req_dict:
                with engine.connect() as connection:
                    for index, row in df.iterrows():
                        sql = """ INSERT INTO appointment_forecast (id, visit_time) VALUES (%(id)s, %(visit_time)s) ON DUPLICATE KEY UPDATE visit_time = VALUES(visit_time) """
                        connection.execute(sql, {'id': id, 'visit_time': row['visit_time']})
            else:
                df.to_sql('appointment_forecast', con=engine, if_exists='append', index=False)
            print("数据更新成功！")
        except Exception as e:
            print(f"发生错误：{e}")
        finally:
            engine.dispose()
        return jsonify(msg)

结论

本系统通过整合 Python 后端技术与微信小程序前端，实现了高效的医疗预约与评价体系。大数据技术的战略意义在于专业处理有意义的医疗数据，优化患者行为分析与服务推荐。系统涵盖数据获取、预处理、存储、分析及可视化全流程，确保了数据的准确性与可用性，为医疗信息化提供了可行方案。