stock/Chan241206/stock_processor.py

import pandas as pd
import pymysql

def get_stock_data(table_name, db_config):
    """
    从数据库中读取指定股票的数据并进行格式转换和清洗。
    :param table_name: 数据表名称
    :param db_config: 数据库配置信息，包含 host, port, user, password, database
    :return: 清洗后的 Pandas DataFrame
    """
    try:
        # 连接数据库
        connection = pymysql.connect(
            host=db_config['host'],
            port=db_config['port'],
            user=db_config['user'],
            password=db_config['password'],
            database=db_config['database']
        )
        print(f"开始读取表：{table_name}")

        # 查询数据
        query = f"SELECT time, open_back, high_back, low_back, close_back, volume_back FROM `{table_name}`"
        df = pd.read_sql(query, connection)  # 读取数据到 DataFrame,注意数据库连接方式
        connection.close()

        if df.empty:
            print(f"{table_name} 数据为空")
            return pd.DataFrame()

        # 格式转换和清洗
        df.rename(columns={
            'time': 'Date',
            'high_back': 'High',
            'low_back': 'Low',
            'open_back': 'Open',
            'close_back': 'Close',
            'volume_back': 'Volume'
        }, inplace=True)

        df['Date'] = pd.to_datetime(df['Date'])
        print(f"完成数据清洗：{table_name}")
        print(df.head())
        return df

    except Exception as e:
        print(f"读取 {table_name} 数据失败：{e}")
        return pd.DataFrame()