笔记-pandas读取mysql数据

最新推荐文章于 2024-09-14 21:34:36 发布

原创最新推荐文章于 2024-09-14 21:34:36 发布 · 402 阅读

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文章标签：

#笔记 #pandas #mysql

目录
pandas读取mysql数据
pandas读取mysql数据到DataFrame
方法一
方法二

pandas读取mysql数据

def get_data():
    conn = pymysql.connect(host=RSYS_HOST,
                       port=RSYS_PORT,
                       user=RSYS_USER,
                       passwd=RSYS_PASSWORDD,
                       db=RSYS_DB_NAME,
                       charset='utf8')
    results = None
    try:
        read_result = pd.read_sql(sql, conn)
        result_json = json.loads(read_result.reset_index().to_json(orient='records', force_ascii=False))
        logger.info(sql)
        return result_json
    except Exception as e:
        # 发生错误时回滚
        logger.error("Error: unable to fecth data: %s,%s" % (repr(e), sql))
        conn.rollback()
    finally:
        conn.close()
  
    return results

pandas读取mysql数据到DataFrame
方法一

#-*- coding:utf-8 -*-
 
from sqlalchemy import create_engine
 
class mysql_engine():
    user='******'
    passwd='******'
    host='******'
    port = '******'
    db_name='******'
    engine = create_engine('mysql://{0}:{1}@{2}:{3}/{4}?charset=utf8'.format(user,passwd,host,port,db_name))
 
def get_data(sql):
    pg_enine=mysql_engine()
    try:
        with pg_enine.engine.connect() as con, con.begin():
            df=pd.read_sql(sql,con)# 获取数据
        con.close()
    except:
        df=None
    return df

方法二

conn = MySQLdb.connect(host="******",user="******",passwd="******",db='******',port = ******,charset="utf8")
sql = "select * from ****** limit 3"
df = pd.read_sql(sql,conn,index_col="id")
print df