Centos5.x下升级python到python2.7版本教程
首先到官网下载python2.7.3版本,编译安装
$wget http://www.python.org/ftp/python/2.7.3/Python-2.7.3.tgz
$tar zxvf Python-2.7.3.tgz
$cd Python-2.7.3
$./configure
$make && make install
然后备份原来的python,并把python2.7做软连接到新的位置
$mv /usr/bin/python /usr/bin/python.bak
$ln -s /usr/local/bin/python2.7 /usr/bin/python
$python -V
版本提示为2.7.3
更改yum,使其能正常运行
$vim vim /usr/bin/yum
把#/usr/bin/python改成#/usr/bin/python2.4 这样yum可以正常运行了
安装easy_install
$yum install python-setuptools
然后安装python-setuptools 到pypi网站下载python-setuptools,版本要和yum的时候版本一致,不然运行的时候会出现:
$ easy_install rsa
Traceback (most recent call last):
File "/usr/bin/easy_install", line 5, in
from pkg_resources import load_entry_point
ImportError: No module named pkg_resources
然后:
$wget http://pypi.python.org/packages/source/s/setuptools/setuptools-0.6c5.tar.gz
$tar zxvf setuptools-0.6c5.tar.gz
$cd setuptools-0.6c5
$python setup.py install
安装成功 这样就可以方便的使用easy_install来安装python的库了

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics











Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.

To maximize the efficiency of learning Python in a limited time, you can use Python's datetime, time, and schedule modules. 1. The datetime module is used to record and plan learning time. 2. The time module helps to set study and rest time. 3. The schedule module automatically arranges weekly learning tasks.

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.

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.

Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Pythonlistsarepartofthestandardlibrary,whilearraysarenot.Listsarebuilt-in,versatile,andusedforstoringcollections,whereasarraysareprovidedbythearraymoduleandlesscommonlyusedduetolimitedfunctionality.

Python excels in automation, scripting, and task management. 1) Automation: File backup is realized through standard libraries such as os and shutil. 2) Script writing: Use the psutil library to monitor system resources. 3) Task management: Use the schedule library to schedule tasks. Python's ease of use and rich library support makes it the preferred tool in these areas.

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
