python讀寫mysql

 

• 讀取mysql數據

# -*- coding: utf-8 -*-
# 導入必要模塊
import pandas as pd
from sqlalchemy import create_engine
# 初始化數據庫鏈接，使用pymysql模塊
# MySQL的用戶：root, 密碼:XXXXXX, 端口：3306,數據庫：mydb
engine = create_engine('mysql+pymysql://root:123456@localhost:3306/student')

# 查詢語句，選出employee表中的全部數據
sql = '''select * from data;'''
# read_sql_query的兩個參數: sql語句， 數據庫鏈接
df = pd.read_sql_query(sql, engine,index_col='index')
# 輸出employee表的查詢結果
print(df.shape)

• pandas寫入數據庫

# coding:utf-8
import pandas as pd
from sqlalchemy import create_engine
# 初始化數據庫鏈接，使用pymysql模塊
# MySQL的用戶：root, 密碼:147369, 端口：3306,數據庫：mydb
engine = create_engine('mysql+pymysql://root:123456@localhost:3306/student')
import datetime
start = datetime.datetime.now().strftime('%Y-%m-%d')
end = (datetime.datetime.now()+datetime.timedelta(days=100)).strftime('%Y-%m-%d')
# 新建pandas中的DataFrame, 只有id,num兩列
# df = pd.DataFrame(data=np.random.randint(-100,100,(100,100)),index=pd.date_range('2018-1-1',periods=100,dtype='datetime64[ns]', freq='D'),columns=None,dtype=int)
# print(df.shape)
# 將新建的DataFrame儲存爲MySQL中的數據表，不儲存index列
# df.to_sql('data', engine, if_exists='append',index= True)

def write_sql(name,data=pd.DataFrame()):
    global engine
    data.to_sql(name,engine,if_exists='fail',index=True)

調用上面封裝方法：

# coding:utf-8
from mysql操做.write_SQL import write_sql
import os
import pandas as pd


path = r'your data path'

name_list = os.listdir(path)[0]

for item in [name_list]:
    name = item.split('.')[0]
    path_ = os.path.join(path,item)
    print(path_)
    with open(path_, 'rb') as f:
        data = pd.read_csv(f, sep=',', header=None, index_col=None, na_values=['NULL'], na_filter=True, encoding='utf8')
        write_sql(name,data)

print('打完收工！')