在Linux上有个常用的命令 curl(非常好用),支持curl的就是大名鼎鼎的libcurl库;libcurl是功能强大的,而且是非常高效的函数库。libcurl除了提供本身的C API之外,还有多达40种编程语言的Binding,这里介绍的PycURL就是libcurl的Python binding。
在Python中对网页进行GET/POST等请求,当需要考虑高性能的时候,libcurl是非常不错的选择,一般来说会比liburl、liburl2快不少,可能也会比Requests的效率更高。特别是使用PycURL的多并发请求时,更是效率很高的。个人感觉,其唯一的缺点是,由于是直接调用的是libcurl C库,PycURL的函数接口之类的还和C中的东西很像,可能不是那么的Pythonic,写代码的学习曲线稍微比liburl高一点儿。
还是看个简单的例子吧:
#! /usr/bin/env python
# -*- coding: utf-8 -*-
'''
Created on Dec 15, 2013
@author: Jay
'''
import sys
import pycurl
import time
class Test:
def __init__(self):
self.contents = ''
def body_callback(self, buf):
self.contents = self.contents + buf
sys.stderr.write("Testing %s\n" % pycurl.version)
start_time = time.time()
url = 'http://www.dianping.com/shanghai'
t = Test()
c = pycurl.Curl()
c.setopt(c.URL, url)
c.setopt(c.WRITEFUNCTION, t.body_callback)
c.perform()
end_time = time.time()
duration = end_time - start_time
print c.getinfo(pycurl.HTTP_CODE), c.getinfo(pycurl.EFFECTIVE_URL)
c.close()
print 'pycurl takes %s seconds to get %s ' % (duration, url)
print 'lenth of the content is %d' % len(t.contents)
#print(t.contents)

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.

Python is suitable for rapid development and data processing, while C is suitable for high performance and underlying control. 1) Python is easy to use, with concise syntax, and is suitable for data science and web development. 2) C has high performance and accurate control, and is often used in gaming and system programming.

The time required to learn Python varies from person to person, mainly influenced by previous programming experience, learning motivation, learning resources and methods, and learning rhythm. Set realistic learning goals and learn best through practical projects.

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.

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 excels in gaming and GUI development. 1) Game development uses Pygame, providing drawing, audio and other functions, which are suitable for creating 2D games. 2) GUI development can choose Tkinter or PyQt. Tkinter is simple and easy to use, PyQt has rich functions and is suitable for professional development.


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