Home Backend Development Python Tutorial python连接MySQL、MongoDB、Redis、memcache等数据库的方法

python连接MySQL、MongoDB、Redis、memcache等数据库的方法

Jun 16, 2016 am 08:46 AM
python connect to mysql

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】

复制代码 代码如下:

#!/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:

复制代码 代码如下:

[client]
user=root
password=123456

二,python 操作 MongoDB:

复制代码 代码如下:

#!/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:

复制代码 代码如下:

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:

复制代码 代码如下:

#!/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:

复制代码 代码如下:

import memcache
mc = memcache.Client(['127.0.0.1:11211'],debug=1)

复制代码 代码如下:

#!/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)

Statement of this Website
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

AI Hentai Generator

AI Hentai Generator

Generate AI Hentai for free.

Hot Article

R.E.P.O. Energy Crystals Explained and What They Do (Yellow Crystal)
2 weeks ago By 尊渡假赌尊渡假赌尊渡假赌
Repo: How To Revive Teammates
4 weeks ago By 尊渡假赌尊渡假赌尊渡假赌
Hello Kitty Island Adventure: How To Get Giant Seeds
3 weeks ago By 尊渡假赌尊渡假赌尊渡假赌

Hot Tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

Dreamweaver CS6

Dreamweaver CS6

Visual web development tools

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

How to Use Python to Find the Zipf Distribution of a Text File How to Use Python to Find the Zipf Distribution of a Text File Mar 05, 2025 am 09:58 AM

This tutorial demonstrates how to use Python to process the statistical concept of Zipf's law and demonstrates the efficiency of Python's reading and sorting large text files when processing the law. You may be wondering what the term Zipf distribution means. To understand this term, we first need to define Zipf's law. Don't worry, I'll try to simplify the instructions. Zipf's Law Zipf's law simply means: in a large natural language corpus, the most frequently occurring words appear about twice as frequently as the second frequent words, three times as the third frequent words, four times as the fourth frequent words, and so on. Let's look at an example. If you look at the Brown corpus in American English, you will notice that the most frequent word is "th

How Do I Use Beautiful Soup to Parse HTML? How Do I Use Beautiful Soup to Parse HTML? Mar 10, 2025 pm 06:54 PM

This article explains how to use Beautiful Soup, a Python library, to parse HTML. It details common methods like find(), find_all(), select(), and get_text() for data extraction, handling of diverse HTML structures and errors, and alternatives (Sel

Image Filtering in Python Image Filtering in Python Mar 03, 2025 am 09:44 AM

Dealing with noisy images is a common problem, especially with mobile phone or low-resolution camera photos. This tutorial explores image filtering techniques in Python using OpenCV to tackle this issue. Image Filtering: A Powerful Tool Image filter

How to Download Files in Python How to Download Files in Python Mar 01, 2025 am 10:03 AM

Python provides a variety of ways to download files from the Internet, which can be downloaded over HTTP using the urllib package or the requests library. This tutorial will explain how to use these libraries to download files from URLs from Python. requests library requests is one of the most popular libraries in Python. It allows sending HTTP/1.1 requests without manually adding query strings to URLs or form encoding of POST data. The requests library can perform many functions, including: Add form data Add multi-part file Access Python response data Make a request head

How to Work With PDF Documents Using Python How to Work With PDF Documents Using Python Mar 02, 2025 am 09:54 AM

PDF files are popular for their cross-platform compatibility, with content and layout consistent across operating systems, reading devices and software. However, unlike Python processing plain text files, PDF files are binary files with more complex structures and contain elements such as fonts, colors, and images. Fortunately, it is not difficult to process PDF files with Python's external modules. This article will use the PyPDF2 module to demonstrate how to open a PDF file, print a page, and extract text. For the creation and editing of PDF files, please refer to another tutorial from me. Preparation The core lies in using external module PyPDF2. First, install it using pip: pip is P

How to Cache Using Redis in Django Applications How to Cache Using Redis in Django Applications Mar 02, 2025 am 10:10 AM

This tutorial demonstrates how to leverage Redis caching to boost the performance of Python applications, specifically within a Django framework. We'll cover Redis installation, Django configuration, and performance comparisons to highlight the bene

Introducing the Natural Language Toolkit (NLTK) Introducing the Natural Language Toolkit (NLTK) Mar 01, 2025 am 10:05 AM

Natural language processing (NLP) is the automatic or semi-automatic processing of human language. NLP is closely related to linguistics and has links to research in cognitive science, psychology, physiology, and mathematics. In the computer science

How to Perform Deep Learning with TensorFlow or PyTorch? How to Perform Deep Learning with TensorFlow or PyTorch? Mar 10, 2025 pm 06:52 PM

This article compares TensorFlow and PyTorch for deep learning. It details the steps involved: data preparation, model building, training, evaluation, and deployment. Key differences between the frameworks, particularly regarding computational grap

See all articles