import logging

import pandas as pd
from odps import ODPS


class ODPSUtils:
    """ODPS操作工具类，封装常用的ODPS操作"""

    # 默认配置
    DEFAULT_ACCESS_ID = 'LTAIWYUujJAm7CbH'
    DEFAULT_ACCESS_KEY = 'RfSjdiWwED1sGFlsjXv0DlfTnZTG1P'
    DEFAULT_PROJECT = 'loghubods'
    DEFAULT_ENDPOINT = 'http://service.cn.maxcompute.aliyun.com/api'
    DEFAULT_LOG_LEVEL = logging.INFO
    DEFAULT_LOG_FILE = None

    def __init__(self,
                 access_id='LTAIWYUujJAm7CbH',
                 access_key='RfSjdiWwED1sGFlsjXv0DlfTnZTG1P',
                 project='loghubods',
                 endpoint='http://service.cn.maxcompute.aliyun.com/api'):
        """
        初始化ODPS连接

        参数:
            access_id: ODPS访问ID
            access_key: ODPS访问密钥
            project: ODPS项目名
            endpoint: ODPS服务地址
            log_level: 日志级别，默认为INFO
            log_file: 日志文件路径，默认为None(不写入文件)
        """
        # 使用默认值或用户提供的值
        self.access_id = access_id
        self.access_key = access_key
        self.project = project
        self.endpoint = endpoint

        # 初始化ODPS连接
        self.odps = None
        self.connect()

    def connect(self):
        """建立ODPS连接"""
        try:
            self.odps = ODPS(self.access_id, self.access_key,
                             project=self.project, endpoint=self.endpoint)
            return True
        except Exception as e:
            return False

    def execute_sql(self, sql, max_wait_time=3600, tunnel=True):
        """
        执行SQL查询并返回结果

        参数:
            sql: SQL查询语句
            max_wait_time: 最大等待时间(秒)
            tunnel: 是否使用Tunnel下载结果，默认为True

        返回:
            pandas DataFrame包含查询结果
        """
        if not self.odps:
            return None

        try:
            with self.odps.execute_sql(sql).open_reader(tunnel=tunnel) as reader:
                # 转换结果为DataFrame
                records = []
                for record in reader:
                    records.append(dict(record))

                if records:
                    df = pd.DataFrame(records)
                    return df
                else:
                    return pd.DataFrame()
        except Exception as e:
            return None