告别SQL语句,python操作mysql的贴心助手
Project description
更新历史
- v2版本
说明
- 从此告别SQL语句,直接调用方法就完事
- python3.10+
- 持续更新中...
如何安装?
pip install sqlman
拿什么吸引你这个靓仔?
-
使用方式简单暴力
-
不用写SQL就能进行增删改查
连接方式是如此简易
- 一个字典参数即可
插入数据是如此贴心
-
自动推导
- 传入dict是插入一条数据,传入list是插入多条数据
-
多种插入模式
- 模式1,插入时,数据冲突则报错
- 模式2,插入时,数据冲突则忽略
- 模式3,插入时,数据发生冲突,把数据进行更新操作
- 模式4,插入时,自动过滤掉冲突的数据,只插入不冲突的数据
等等等等...
操练起来
连接mysql
- 数据库对象
from sqlman import Connector
# 方式1
db = Connector(host="localhost", port=3306, username="root", password="root@0", db="test") # 数据库对象
# 方式2
MYSQL_CONF = {
'host': 'localhost',
'port': 3306,
'username': 'root',
'password': 'root@0',
'db': 'test'
}
db = Connector(**MYSQL_CONF) # 数据库对象
# 方式3
MYSQL_URL = "mysql://root:root@0@localhost:3306/test"
db = Connector.from_url(MYSQL_URL) # 数据库对象
- 表格对象
student = db['student']
student = db.pick_table('student')
准备测试数据
# 一条龙服务,创建people表并插入测试数据,每次插入一千条,累计插入一万条
db.gen_test_table('people', once=1000, total=10000)
people = db['people']
插入数据
单条插入
data = {'id': 10001, 'name': '小明', 'age': 10, 'gender': '男'}
# 插入一条数据
people.insert_data(data)
# 当插入的数据与表中的数据存在冲突时,直接插入会报错,如果补充<unique>参数,则不报错
people.insert_data(data, unique='id')
批量插入
data = [
{'id': 10002, 'name': '小红', 'age': 12, 'gender': '女'},
{'id': 10003, 'name': '小强', 'age': 13, 'gender': '男'},
{'id': 10004, 'name': '小白', 'age': 14, 'gender': '男'}
]
# 插入多条数据
people.insert_data(data)
插入数据时,如果数据冲突则进行更新
data = {'id': 10001, 'name': '小明', 'age': 10, 'gender': '男'}
# 当数据冲突时,也可以直接进行更新操作,下面是把age更新为11
people.insert_data(data, update='age=age+1')
删除数据
# delete from people where id=1
people.delete(id=1)
# delete from people where id in (1, 2, 3)
people.delete(id=[1, 2, 3])
# delete from people where age=18 limit 100
people.delete(age=18, limit=100)
更新数据
# update people set name='tony', job='理发师' where id=1
people.update(new={'name': 'tony', 'job': '理发师'}, id=1)
# update people set job='程序员' where name='thomas' and phone='18959176772'
people.update(new={'job': '程序员'}, name='thomas', phone='18959176772')
查询数据
# select * from people where id=1
people.query(id=1)
# select name, age from people where id=2
people.query(pick='name, age', id=2)
# select * from people where age=18 and gender in ('男', '女')
people.query(age=18, gender=['男', '女'])
# select name from people where age=18 and gender in ('男', '女') limit 5
people.query(pick='name', age=18, gender=['男', '女'], limit=5)
随机数据
# 随机返回1条数据<dict>
print(people.random())
# 随机返回5条数据<list>
print(people.random(limit=5))
遍历表
# 遍历整张表,默认每轮扫描1000条,默认只打印数据
people.scan()
def show(lines):
for some in enumerate(lines, start=1):
print('第{}条 {}'.format(*some))
# 限制id范围为101~222,每轮扫描100条,每轮的回调函数为show
people.scan(sort_field='id', start=101, end=222, once=100, dealer=show)
# 限制id范围的基础上,限制age=18
people.scan(sort_field='id', start=101, end=222, once=100, dealer=show, add_cond='age=18')
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