用Python写脚本也有一段时间了,经常操作数据库(MySQL),现在就整理下对各类数据库的操作,如后面有新的参数会补进来,慢慢完善。
一,python 操作 MySQL:详情见:
【apt-get install python-mysqldb】
#!/bin/env python
# -*- encoding: utf-8 -*-
#-------------------------------------------------------------------------------
# Purpose: example for python_to_mysql
# Author: zhoujy
# Created: 2013-06-14
# update: 2013-06-14
#-------------------------------------------------------------------------------
import MySQLdb
import os
#建立和数据库系统的连接,格式
#conn = MySQLdb.connect(host='localhost',user='root',passwd='123456',db='test',port=3306,charset='utf8')
#指定配置文件,确定目录,或则写绝对路径
cwd = os.path.realpath(os.path.dirname(__file__))
db_conf = os.path.join(cwd, 'db.conf')
conn = MySQLdb.connect(read_default_file=db_conf,host='localhost',db='test',port=3306,charset='utf8')
#要执行的sql语句
query = 'select id from t1'
#获取操作游标
cursor = conn.cursor()
#执行SQL
cursor.execute(query)
#获取一条记录,每条记录做为一个元组返回,返回3,游标指到第2条记录。
result1 = cursor.fetchone()
for i in result1:
print i
#返回影响的行数
print cursor.rowcount
#获取指定数量记录,每条记录做为一个元组返回,返回1,2,游标从第2条记录开始,游标指到第4条记录。
result2 = cursor.fetchmany(2)
for i in result2:
for ii in i:
print ii
#获取所有记录,每条记录做为一个元组返回,返回3,4,7,6,游标从第4条记录开始到最后。
result3 = cursor.fetchall()
for i in result3:
for ii in i:
print ii
#获取所有记录,每条记录做为一个元组返回,返回3,4,7,6,游标从第1条记录开始
#重置游标位置,0为偏移量,mode=absolute | relative,默认为relative
cursor.scroll(0,mode='absolute')
result3 = cursor.fetchall()
for i in result3:
for ii in i:
print ii
#以下2种方法都可以把数据插入数据库:
#(one)
for i in range (10,20):
query2 = 'insert into t1 values("%d",now())' %i
cursor.execute(query2)
#提交
conn.rollback()
#(two)
rows = []
for i in range (10,20):
rows.append(i)
query2 = 'insert into t1 values("%s",now())'
#executemany 2个参数,第2个参数是变量。
cursor.executemany(query2,rows)
#提交
conn.commit()
#选择数据库
query3 = 'select id from dba_hospital'
#重新选择数据库
conn.select_db('chushihua')
cursor.execute(query3)
result4 = cursor.fetchall()
for i in result4:
for ii in i:
print ii
#不定义query,直接执行:
cursor.execute("set session binlog_format='mixed'")
#关闭游标,释放资源
cursor.close()
'''
+------+---------------------+
| id | modifyT |
+------+---------------------+
| 3 | 2010-01-01 00:00:00 |
| 1 | 2010-01-01 00:00:00 |
| 2 | 2010-01-01 00:00:00 |
| 3 | 2010-01-01 00:00:00 |
| 4 | 2013-06-04 17:04:54 |
| 7 | 2013-06-04 17:05:36 |
| 6 | 2013-06-04 17:05:17 |
+------+---------------------+
'''
注意:在脚本中,密码写在脚本里面很容易暴露,这样可以用一个配置文件的方式来存密码,如db.conf:
[client]
user=root
password=123456
二,python 操作 MongoDB:
#!/bin/env python
# -*- encoding: utf-8 -*-
#-------------------------------------------------------------------------------
# Purpose: example for python_to_mongodb
# Author: zhoujy
# Created: 2013-06-14
# update: 2013-06-14
#-------------------------------------------------------------------------------
import pymongo
import os
#建立和数据库系统的连接,创建Connection时,指定host及port参数
conn = pymongo.Connection(host='127.0.0.1',port=27017)
#admin 数据库有帐号,连接-认证-切换库
db_auth = conn.admin
db_auth.authenticate('sa','sa')
#连接数据库
db = conn.abc
#连接表
collection = db.stu
#查看全部表名称
db.collection_names()
#print db.collection_names()
#访问表的数据,指定列
item = collection.find({},{"sname":1,"course":1,"_id":0})
for rows in item:
print rows.values()
#访问表的一行数据
print collection.find_one()
#得到所有的列
for rows in collection.find_one():
print rows
#插入
collection.insert({"sno":100,"sname":"jl","course":{"D":80,"S":85}})
#或
u = dict(sno=102,sname='zjjj',course={"D":80,"S":85})
collection.insert(u)
#得到行数
print collection.find().count()
print collection.find({"sno":100})
#排序,按照某一列的值。pymongo.DESCENDING:倒序;pymongo.ASCENDING:升序。按照sno倒序
item = collection.find().sort('sno',pymongo.DESCENDING)
for rows in item:
print rows.values()
#多列排序
item = collection.find().sort([('sno',pymongo.DESCENDING),('A',pymongo.ASCENDING)])
#更新,第一个参数是条件,第二个参数是更新操作,$set,%inc,$push,$ne,$addToSet,$rename 等
collection.update({"sno":100},{"$set":{"sno":101}})
#更新多行和多列
collection.update({"sno":102},{"$set":{"sno":105,"sname":"SSSS"}},multi=True)
#删除,第一个参数是条件,第二个参数是删除操作。
collection.remove({"sno":101})
'''
sno:学号;sname:姓名;course:科目
db.stu.insert({"sno":1,"sname":"张三","course":{"A":95,"B":90,"C":65,"D":74,"E":100}})
db.stu.insert({"sno":2,"sname":"李四","course":{"A":90,"B":85,"X":75,"Y":64,"Z":95}})
db.stu.insert({"sno":3,"sname":"赵五","course":{"A":70,"B":56,"F":85,"G":84,"H":80}})
db.stu.insert({"sno":4,"sname":"zhoujy","course":{"A":64,"B":60,"C":95,"T":94,"Y":85}})
db.stu.insert({"sno":5,"sname":"abc","course":{"A":87,"B":70,"Z":56,"G":54,"H":75}})
db.stu.insert({"sno":6,"sname":"杨六","course":{"A":65,"U":80,"C":78,"R":75,"N":90}})
db.stu.insert({"sno":7,"sname":"陈二","course":{"A":95,"M":68,"N":84,"S":79,"K":89}})
db.stu.insert({"sno":8,"sname":"zhoujj","course":{"P":90,"B":77,"J":85,"K":68,"L":80}})
db.stu.insert({"sno":9,"sname":"ccc","course":{"Q":85,"B":86,"C":90,"V":87,"U":85}})
'''
计算Mongodb文档中各集合的数目:
import pymongo
conn = pymongo.Connection(host='127.0.0.1',port=27017)
db = conn.abc #abc文档
for tb_name in db.collection_names(): #循环出各集合名
Count = db[tb_name].count() #计算各集合的数量
if Count > 2: #过滤条件
print tb_name + ':' + str(Count)
'''
conn = pymongo.Connection(host='127.0.0.1',port=27017)
db = conn.abc
for tb_name in db.collection_names():
print tb_name + ':'
exec('print ' + 'db.'+tb_name+'.count()') #变量当集合的处理方式
OR
conn = pymongo.Connection(host='127.0.0.1',port=27017)
db = conn.abc
for tb_name in db.collection_names():
mon_dic=db.command("collStats", tb_name) #以字典形式返回
print mon_dic.get('ns'),mon_dic.get('count')
'''
三,python 操作 Redis:
#!/bin/env python
# -*- encoding: utf-8 -*-
#-------------------------------------------------------------------------------
# Purpose: example for python_to_mongodb
# Author: zhoujy
# Created: 2013-06-14
# update: 2013-06-14
#-------------------------------------------------------------------------------
import redis
f = open('aa.txt')
while True:
line = f.readline().strip().split(' # ')
if line == ['']:
break
UserName,Pwd,Email = line
# print name.strip(),pwd.strip(),email.strip()
rc = redis.StrictRedis(host='127.0.0.1',port=6379,db=15)
rc.hset('Name:' + UserName,'Email',Email)
rc.hset('Name:' + UserName,'Password',Pwd)
f.close()
alluser = rc.keys('*')
#print alluser
print "===================================读出存进去的数据==================================="
for user in alluser:
print ' # '.join((user.split(':')[1],rc.hget(user,'Password'),rc.hget(user,'Email')))
四,python 操作 memcache:
import memcache
mc = memcache.Client(['127.0.0.1:11211'],debug=1)
#!/usr/bin/env python
#coding=utf-8
import MySQLdb
import memcache
import sys
import time
def get_data(mysql_conn):
# nn = raw_input("press string name:")
mc = memcache.Client(['127.0.0.1:11211'],debug=1)
t1 =time.time()
value = mc.get('zhoujinyia')
if value == None:
t1 = time.time()
print t1
query = "select company,email,sex,address from uc_user_offline where realName = 'zhoujinyia'"
cursor= mysql_conn.cursor()
cursor.execute(query)
item = cursor.fetchone()
t2 = time.time()
print t2
t = round(t2-t1)
print "from mysql cost %s sec" %t
print item
mc.set('zhoujinyia',item,60)
else :
t2 = time.time()
t=round(t2-t1)
print "from memcache cost %s sec" %t
print value
if __name__ =='__main__':
mysql_conn = MySQLdb.connect(host='127.0.0.1',user='root',passwd='123456',db='member',port=3306,charset='utf8')
get_data(mysql_conn)

Is it enough to learn Python for two hours a day? It depends on your goals and learning methods. 1) Develop a clear learning plan, 2) Select appropriate learning resources and methods, 3) Practice and review and consolidate hands-on practice and review and consolidate, and you can gradually master the basic knowledge and advanced functions of Python during this period.

Key applications of Python in web development include the use of Django and Flask frameworks, API development, data analysis and visualization, machine learning and AI, and performance optimization. 1. Django and Flask framework: Django is suitable for rapid development of complex applications, and Flask is suitable for small or highly customized projects. 2. API development: Use Flask or DjangoRESTFramework to build RESTfulAPI. 3. Data analysis and visualization: Use Python to process data and display it through the web interface. 4. Machine Learning and AI: Python is used to build intelligent web applications. 5. Performance optimization: optimized through asynchronous programming, caching and code

Python is better than C in development efficiency, but C is higher in execution performance. 1. Python's concise syntax and rich libraries improve development efficiency. 2.C's compilation-type characteristics and hardware control improve execution performance. When making a choice, you need to weigh the development speed and execution efficiency based on project needs.

Python's real-world applications include data analytics, web development, artificial intelligence and automation. 1) In data analysis, Python uses Pandas and Matplotlib to process and visualize data. 2) In web development, Django and Flask frameworks simplify the creation of web applications. 3) In the field of artificial intelligence, TensorFlow and PyTorch are used to build and train models. 4) In terms of automation, Python scripts can be used for tasks such as copying files.

Python is widely used in data science, web development and automation scripting fields. 1) In data science, Python simplifies data processing and analysis through libraries such as NumPy and Pandas. 2) In web development, the Django and Flask frameworks enable developers to quickly build applications. 3) In automated scripts, Python's simplicity and standard library make it ideal.

Python's flexibility is reflected in multi-paradigm support and dynamic type systems, while ease of use comes from a simple syntax and rich standard library. 1. Flexibility: Supports object-oriented, functional and procedural programming, and dynamic type systems improve development efficiency. 2. Ease of use: The grammar is close to natural language, the standard library covers a wide range of functions, and simplifies the development process.

Python is highly favored for its simplicity and power, suitable for all needs from beginners to advanced developers. Its versatility is reflected in: 1) Easy to learn and use, simple syntax; 2) Rich libraries and frameworks, such as NumPy, Pandas, etc.; 3) Cross-platform support, which can be run on a variety of operating systems; 4) Suitable for scripting and automation tasks to improve work efficiency.

Yes, learn Python in two hours a day. 1. Develop a reasonable study plan, 2. Select the right learning resources, 3. Consolidate the knowledge learned through practice. These steps can help you master Python in a short time.


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