实现简单的多线程下载,需要关注如下几点:
1.文件的大小:可以从reponse header中提取,如“Content-Length:911”表示大小是911字节
2.任务拆分:指定各个线程下载的文件的哪一块,可以通过request header中添加“Range: bytes=300-400”(表示下载300~400byte的内容),注意可以请求的文件的range是[0, size-1]字节的。
3.下载文件的聚合:各个线程将自己下载的文件块保存为临时文件,所有线程都完成后,再将这些临时文件按顺序聚合写入到最终的一个文件中。
实现代码:
#!/usr/bin/python
# -*- coding: utf-8 -*-
# filename: paxel.py
# FROM: http://jb51.net/code/view/58/full/
# Jay modified it a little and save for further potential usage.
'''It is a multi-thread downloading tool
It was developed following axel.
Author: volans
E-mail: volansw [at] gmail.com
'''
import sys
import os
import time
import urllib
from threading import Thread
# in case you want to use http_proxy
local_proxies = {'http': 'http://131.139.58.200:8080'}
class AxelPython(Thread, urllib.FancyURLopener):
'''Multi-thread downloading class.
run() is a vitural method of Thread.
'''
def __init__(self, threadname, url, filename, ranges=0, proxies={}):
Thread.__init__(self, name=threadname)
urllib.FancyURLopener.__init__(self, proxies)
self.name = threadname
self.url = url
self.filename = filename
self.ranges = ranges
self.downloaded = 0
def run(self):
'''vertual function in Thread'''
try:
self.downloaded = os.path.getsize(self.filename)
except OSError:
#print 'never downloaded'
self.downloaded = 0
# rebuild start poind
self.startpoint = self.ranges[0] + self.downloaded
# This part is completed
if self.startpoint >= self.ranges[1]:
print 'Part %s has been downloaded over.' % self.filename
return
self.oneTimeSize = 16384 # 16kByte/time
print 'task %s will download from %d to %d' % (self.name, self.startpoint, self.ranges[1])
self.addheader("Range", "bytes=%d-%d" % (self.startpoint, self.ranges[1]))
self.urlhandle = self.open(self.url)
data = self.urlhandle.read(self.oneTimeSize)
while data:
filehandle = open(self.filename, 'ab+')
filehandle.write(data)
filehandle.close()
self.downloaded += len(data)
#print "%s" % (self.name)
#progress = u'\r...'
data = self.urlhandle.read(self.oneTimeSize)
def GetUrlFileSize(url, proxies={}):
urlHandler = urllib.urlopen(url, proxies=proxies)
headers = urlHandler.info().headers
length = 0
for header in headers:
if header.find('Length') != -1:
length = header.split(':')[-1].strip()
length = int(length)
return length
def SpliteBlocks(totalsize, blocknumber):
blocksize = totalsize / blocknumber
ranges = []
for i in range(0, blocknumber - 1):
ranges.append((i * blocksize, i * blocksize + blocksize - 1))
ranges.append((blocksize * (blocknumber - 1), totalsize - 1))
return ranges
def islive(tasks):
for task in tasks:
if task.isAlive():
return True
return False
def paxel(url, output, blocks=6, proxies=local_proxies):
''' paxel
'''
size = GetUrlFileSize(url, proxies)
ranges = SpliteBlocks(size, blocks)
threadname = ["thread_%d" % i for i in range(0, blocks)]
filename = ["tmpfile_%d" % i for i in range(0, blocks)]
tasks = []
for i in range(0, blocks):
task = AxelPython(threadname[i], url, filename[i], ranges[i])
task.setDaemon(True)
task.start()
tasks.append(task)
time.sleep(2)
while islive(tasks):
downloaded = sum([task.downloaded for task in tasks])
process = downloaded / float(size) * 100
show = u'\rFilesize:%d Downloaded:%d Completed:%.2f%%' % (size, downloaded, process)
sys.stdout.write(show)
sys.stdout.flush()
time.sleep(0.5)
filehandle = open(output, 'wb+')
for i in filename:
f = open(i, 'rb')
filehandle.write(f.read())
f.close()
try:
os.remove(i)
pass
except:
pass
filehandle.close()
if __name__ == '__main__':
url = 'http://dldir1.qq.com/qqfile/QQforMac/QQ_V3.1.1.dmg'
output = 'download.file'
paxel(url, output, blocks=4, proxies={})

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.

Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

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.


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