一、向MySQL中插入CSV文件
1、首先安装本地MySQL
此步骤不再赘述
2、启动本地MySQL
在contana的搜索框张收入cmd，然后右键单击，并选择以管理员身份运行！
切换到C盘根目录：
C:\WINDOWS\system32>cd .. C:\Windows>cd .. C:\> C:\>D: D:\>cd D:\navicat\mysql-5.6.44-winx64\bin\ D:\navicat\mysql-5.6.44-winx64\bin>net start mysql MySQL 服务正在启动 . MySQL 服务已经启动成功。 D:\navicat\mysql-5.6.44-winx64\bin>mysql -uroot -p #这里直接enter键，进入MySQL
mysql>
进入MySQL后，进行以下操作：
创建数据库my_suppliers，选择创建的数据库，在新创建的数据库下新建一个数据表Suppliers，描述数据表，创建一个新用户clinton，向新用户授予所有权限。
CREATE DATABASE my_suppliers; Query OK, 1 row affected (0.05 sec) mysql> use my_suppliers; Database changed mysql> CREATE TABLE IF NOT EXISTS Suppliers -> (Suppliers VARCHAR(20), -> Invoice_Number VARCHAR(20), -> Part_Number VARCHAR(20), -> Cost FLOAT, -> Purchase_date date); Query OK, 0 rows affected (0.24 sec) mysql> describe Suppliers; +----------------+-------------+------+-----+---------+-------+ | Field | Type | Null | Key | Default | Extra | +----------------+-------------+------+-----+---------+-------+ | Suppliers | varchar(20) | YES | | NULL | | | Invoice_Number | varchar(20) | YES | | NULL | | | Part_Number | varchar(20) | YES | | NULL | | | Cost | float | YES | | NULL | | | Purchase_date | date | YES | | NULL | | +----------------+-------------+------+-----+---------+-------+ 5 rows in set (0.01 sec) mysql> CREATE USER \'clinton\'@\'localhost\' IDENTIFIED BY \'secret_password\'; Query OK, 0 rows affected (0.00 sec) mysql> GRANT ALL PRIVILEGES ON my_suppliers.* TO \'clinton\'@\'localhost\'; Query OK, 0 rows affected (0.00 sec) mysql> FLUSH PRIVILEGES; Query OK, 0 rows affected (0.00 sec)
3、使用python向MySQL表中插入新记录
该脚本会将CSV文件的数据插入到MySQL中的Suppliers表中：
#!/usr/bin/env python3
import csv
import MySQLdb
from datetime import datetime,date
input_file = "F://python入门//数据1//CSV测试数据.csv"
#连接到数据库
con = MySQLdb.connect(host=\'localhost\',port=3306,db=\'my_suppliers\',user=\'clinton\',\
passwd=\'secret_password\')
#创建了一个光标
c = con.cursor()
#从CSV格式的输入文件中读取要加载到数据库中的数据，创建file_reader对象，用于存储CSV中的数据集
file_reader = csv.reader(open(input_file,\'r\',newline=\'\'))
#从输入文件中读入第一行
header = next(file_reader)
#将输入的所有数据进行循环，先是每行循环，再是每列循环
for row in file_reader:
data = []
for column_index in range(len(header)):
if column_index < 4:
data.append(str(row[column_index]).lstrip(\'$\').replace(\',\',\'\').strip())
else:
a_date = datetime.date(datetime.strptime(str(row[column_index]),\'%Y/%m/%d\'))
a_date = a_date.strftime(\'%Y-%m-%d\')
data.append(a_date)
print(data)
c.execute("""INSERT INTO Suppliers VALUES(%s,%s,%s,%s,%s)""",data)
#将修改保存到数据库
con.commit()
print(\'………………\')
#执行选择所有数据的SQL
c.execute("SELECT * FROM Suppliers")
#返回结果集中的所有行,返回的是一个大的列表
rows = c.fetchall()
print(rows)
print(\'………………\')
for row in rows:
row_list_output = []
for column_index in range(len(row)):
row_list_output.append(str(row[column_index]))
print(row_list_output)
MySQL中的结果集：
mysql> select * from Suppliers; +-------------+----------------+-------------+------+---------------+ | Suppliers | Invoice_Number | Part_Number | Cost | Purchase_date | +-------------+----------------+-------------+------+---------------+ | Suppliers X | 001-1001 | 2341 | 500 | 2019-01-20 | | Suppliers X | 001-1001 | 2341 | 500 | 2019-01-20 | | Suppliers X | 001-1001 | 5467 | 750 | 2019-01-20 | | Suppliers X | 001-1001 | 5467 | 750 | 2019-01-20 | | Suppliers Y | 50-9501 | 7009 | 250 | 2019-01-30 | | Suppliers Y | 50-9501 | 7009 | 250 | 2019-01-30 | | Suppliers Y | 50-9505 | 6650 | 125 | 2019-02-03 | | Suppliers Y | 50-9505 | 6650 | 125 | 2019-02-03 | | Suppliers Z | 920-4803 | 3321 | 615 | 2019-02-03 | | Suppliers Z | 920-4804 | 3321 | 615 | 2019-02-10 | | Suppliers Z | 920-4805 | 3321 | 615 | 2019-02-17 | | Suppliers Z | 920-4806 | 3321 | 615 | 2019-02-24 | +-------------+----------------+-------------+------+---------------+ 12 rows in set (0.00 sec)
Spyder右下角的输出：
[\'Suppliers X\', \'001-1001\', \'2341\', \'500.00\', \'2019-01-20\'] [\'Suppliers X\', \'001-1001\', \'2341\', \'500.00\', \'2019-01-20\'] [\'Suppliers X\', \'001-1001\', \'5467\', \'750.00\', \'2019-01-20\'] [\'Suppliers X\', \'001-1001\', \'5467\', \'750.00\', \'2019-01-20\'] [\'Suppliers Y\', \'50-9501\', \'7009\', \'250.00\', \'2019-01-30\'] [\'Suppliers Y\', \'50-9501\', \'7009\', \'250.00\', \'2019-01-30\'] [\'Suppliers Y\', \'50-9505\', \'6650\', \'125.00\', \'2019-02-03\'] [\'Suppliers Y\', \'50-9505\', \'6650\', \'125.00\', \'2019-02-03\'] [\'Suppliers Z\', \'920-4803\', \'3321\', \'615.00\', \'2019-02-03\'] [\'Suppliers Z\', \'920-4804\', \'3321\', \'615.00\', \'2019-02-10\'] [\'Suppliers Z\', \'920-4805\', \'3321\', \'615.00\', \'2019-02-17\'] [\'Suppliers Z\', \'920-4806\', \'3321\', \'615.00\', \'2019-02-24\'] ……………… ((\'Suppliers X\', \'001-1001\', \'2341\', 500.0, datetime.date(2019, 1, 20)), (\'Suppliers X\', \'001-1001\', \'2341\', 500.0, datetime.date(2019, 1, 20)), (\'Suppliers X\', \'001-1001\', \'5467\', 750.0, datetime.date(2019, 1, 20)), (\'Suppliers X\', \'001-1001\', \'5467\', 750.0, datetime.date(2019, 1, 20)), (\'Suppliers Y\', \'50-9501\', \'7009\', 250.0, datetime.date(2019, 1, 30)), (\'Suppliers Y\', \'50-9501\', \'7009\', 250.0, datetime.date(2019, 1, 30)), (\'Suppliers Y\', \'50-9505\', \'6650\', 125.0, datetime.date(2019, 2, 3)), (\'Suppliers Y\', \'50-9505\', \'6650\', 125.0, datetime.date(2019, 2, 3)), (\'Suppliers Z\', \'920-4803\', \'3321\', 615.0, datetime.date(2019, 2, 3)), (\'Suppliers Z\', \'920-4804\', \'3321\', 615.0, datetime.date(2019, 2, 10)), (\'Suppliers Z\', \'920-4805\', \'3321\', 615.0, datetime.date(2019, 2, 17)), (\'Suppliers Z\', \'920-4806\', \'3321\', 615.0, datetime.date(2019, 2, 24))) ……………… [\'Suppliers X\', \'001-1001\', \'2341\', \'500.0\', \'2019-01-20\'] [\'Suppliers X\', \'001-1001\', \'2341\', \'500.0\', \'2019-01-20\'] [\'Suppliers X\', \'001-1001\', \'5467\', \'750.0\', \'2019-01-20\'] [\'Suppliers X\', \'001-1001\', \'5467\', \'750.0\', \'2019-01-20\'] [\'Suppliers Y\', \'50-9501\', \'7009\', \'250.0\', \'2019-01-30\'] [\'Suppliers Y\', \'50-9501\', \'7009\', \'250.0\', \'2019-01-30\'] [\'Suppliers Y\', \'50-9505\', \'6650\', \'125.0\', \'2019-02-03\'] [\'Suppliers Y\', \'50-9505\', \'6650\', \'125.0\', \'2019-02-03\'] [\'Suppliers Z\', \'920-4803\', \'3321\', \'615.0\', \'2019-02-03\'] [\'Suppliers Z\', \'920-4804\', \'3321\', \'615.0\', \'2019-02-10\'] [\'Suppliers Z\', \'920-4805\', \'3321\', \'615.0\', \'2019-02-17\'] [\'Suppliers Z\', \'920-4806\', \'3321\', \'615.0\', \'2019-02-24\']
4、关于报错
在脚本中导入import MySQLdb，会报错，ModuleNotFoundError: No module named \'MySQLdb\'
针对这一报错，解决方法：
打开anaconda prompt
pip install mysqlclient --安装mysqlclient
完成后，再执行以上脚本，就不会再报错了~
二、从MySQL表中将数据输出写入CSV文件
将目标数据写入CSV中：
#!/usr/bin/env python3 import csv import MySQLdb output_file = "F://python入门//数据1//CSV测试数据_yuan.csv" #连接到数据库 con = MySQLdb.connect(host=\'localhost\',port=3306,db=\'my_suppliers\',user=\'clinton\',\ passwd=\'secret_password\') #创建了一个光标 c = con.cursor() #打开将要写入的文件 filewriter = csv.writer(open(output_file,\'w\',newline=\'\'),delimiter=\',\') #设置CSV文件列标题 header = [\'Suppliers\',\'Invoice_Number\',\'Part_Number\',\'Cost\',\'Purchase_date\'] #将列标题写入文件中 filewriter.writerow(header) #查询Suppliers表，并大于600美元的目标数据取出 c.execute("""select * from Suppliers where Cost>600.00;""") #返回结果集中的所有行 rows = c.fetchall() #将每行写入到目标文件 for row in rows: filewriter.writerow(row)
"CSV测试数据_yuan.csv"结果集：
三、更新MySQL表中的记录
"CSV测试数据.csv"源数据：
以源数据更新MySQL表中的内容：
#!/usr/bin/env python3 import csv import MySQLdb input_file = "F://python入门//数据1//CSV测试数据.csv" #连接到数据库 con = MySQLdb.connect(host=\'localhost\',port=3306,db=\'my_suppliers\',user=\'clinton\',\ passwd=\'secret_password\') #创建了一个光标 c = con.cursor() #打开要读取的文件 file_reader = csv.reader(open(input_file,\'r\',newline=\'\'),delimiter=\',\') #读取标题行 header = next(file_reader,None) #遍历CSV文件的内容 for row in file_reader: data = [] for column_index in range(len(header)): data.append(str(row[column_index]).strip()) print(data) c.execute("""update Suppliers set Cost=%s,Purchase_Date=%s where Suppliers=%s;""",data) #将修改保存到数据库 con.commit() print(\'………………\') c.execute("""select * from Suppliers;""") #返回结果集中的所有行 rows = c.fetchall() #将修改后的内容打印出来 for row in rows: output = [] for column_index in range(len(row)): output.append(str(row[column_index])) print(output)
MySQL中的表内容：
mysql> select * from Suppliers; +-------------+----------------+-------------+------+---------------+ | Suppliers | Invoice_Number | Part_Number | Cost | Purchase_date | +-------------+----------------+-------------+------+---------------+ | Suppliers X | 001-1001 | 2341 | 600 | 2019-01-22 | | Suppliers X | 001-1001 | 2341 | 600 | 2019-01-22 | | Suppliers X | 001-1001 | 5467 | 600 | 2019-01-22 | | Suppliers X | 001-1001 | 5467 | 600 | 2019-01-22 | | Suppliers Y | 50-9501 | 7009 | 200 | 2019-02-01 | | Suppliers Y | 50-9501 | 7009 | 200 | 2019-02-01 | | Suppliers Y | 50-9505 | 6650 | 200 | 2019-02-01 | | Suppliers Y | 50-9505 | 6650 | 200 | 2019-02-01 | | Suppliers Z | 920-4803 | 3321 | 615 | 2019-02-03 | | Suppliers Z | 920-4804 | 3321 | 615 | 2019-02-10 | | Suppliers Z | 920-4805 | 3321 | 615 | 2019-02-17 | | Suppliers Z | 920-4806 | 3321 | 615 | 2019-02-24 | +-------------+----------------+-------------+------+---------------+ 12 rows in set (0.00 sec)
Spyder右下角打印的内容：
[\'600.00\', \'2019-01-22\', \'Suppliers X\'] [\'200.00\', \'2019-02-01\', \'Suppliers Y\'] ……………… [\'Suppliers X\', \'001-1001\', \'2341\', \'600.0\', \'2019-01-22\'] [\'Suppliers X\', \'001-1001\', \'2341\', \'600.0\', \'2019-01-22\'] [\'Suppliers X\', \'001-1001\', \'5467\', \'600.0\', \'2019-01-22\'] [\'Suppliers X\', \'001-1001\', \'5467\', \'600.0\', \'2019-01-22\'] [\'Suppliers Y\', \'50-9501\', \'7009\', \'200.0\', \'2019-02-01\'] [\'Suppliers Y\', \'50-9501\', \'7009\', \'200.0\', \'2019-02-01\'] [\'Suppliers Y\', \'50-9505\', \'6650\', \'200.0\', \'2019-02-01\'] [\'Suppliers Y\', \'50-9505\', \'6650\', \'200.0\', \'2019-02-01\'] [\'Suppliers Z\', \'920-4803\', \'3321\', \'615.0\', \'2019-02-03\'] [\'Suppliers Z\', \'920-4804\', \'3321\', \'615.0\', \'2019-02-10\'] [\'Suppliers Z\', \'920-4805\', \'3321\', \'615.0\', \'2019-02-17\'] [\'Suppliers Z\', \'920-4806\', \'3321\', \'615.0\', \'2019-02-24\']