python异步爬虫之多线程
多线程，多进程（不建议使用）
优点：可以为相关阻塞的操作单独开启线程或者进程，阻塞操作可以异步执行
弊端：无法无限制开启多线程或多进程。
原则：线程池处理的是阻塞且耗时的操作
单线爬虫示例：
import time
def get_page(str):
print("正在下载：",str)
time.sleep(2)
print('下载成功：',str)
name_list = ['aa','bb','cc','dd']
start_time = time.time()
for i in range(len(name_list)):
get_page(name_list[i])
end_time = time.time()
print('%d second'% (end_time-start_time))
多线程爬虫示例：
import time
# 导入线程池模块对应的类
from multiprocessing.dummy import Pool
start_time = time.time()
def get_page(str):
print("正在下载：",str)
time.sleep(2)
print('下载成功：',str)
name_list = ['aa','bb','cc','dd']
# 实例化一个线程池对象
pool = Pool(4)
# 将列表中每一个列表元素传递给get_page进行处理
pool.map(get_page,name_list)
end_time = time.time()
print(end_time-start_time)
案例：
# 多线爬虫示例
import requests
from lxml import etree
import re
from multiprocessing.dummy import Pool
headers = {
'User-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:80.0) Gecko/20100101 Firefox/80.0',
'Content-type':'application/json',
}
# 对下述url发起请求解析出视频详情页的url和视频的名称
url = "https://pearvideo.com/category_5"
page_text = requests.get(url=url,headers=headers).text
tree = etree.HTML(page_text)
li_list = tree.xpath('//ul[@id="listvideoListUl"]/li')
urls = [] #存储所有视频的链接
for li in li_list:
detail_url = 'https://pearvideo.com/' + li.xpath('./div/a/@href')[0]
name = li.xpath('./div/a/div[2]/text()')[0]+'.mp4'
# 对详情页的url发起请求
detail_page_text = requests.get(url=detail_url,headers=headers).text
# print(detail_url,name)
# 从详情页中解析出视频的地址（url）
id = re.findall(r'\d+', detail_url)[0]
# https://pearvideo.com/videoStatus.jsp?contId=1751458&mrd=0.32392817067398805
detail_vedio_url = 'https://pearvideo.com/videoStatus.jsp?contId='+id
header1s = {
'User-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:80.0) Gecko/20100101 Firefox/80.0',
'Content-type': 'application/json',
'referer':detail_url
}
vedio_text = requests.get(url=detail_vedio_url,headers=header1s).json()
# print(vedio_text)
vedio_url = vedio_text['videoInfo']['videos']['srcUrl']
dic = {
'name': name,
'url': vedio_url
}
urls.append(dic)
print(vedio_url)
def get_video_data(dic):
url = dic['url']
print(dic['name'],'正在下载......')
data = requests.get(url=url,headers=header1s).content
# 持久化存储操作
with open(dic['name'],'wb') as fp:
fp.write(data)
print(dic['name'],'下载成功')
# 使用线程池对视频数据进行请求(较为耗时的阻塞操作)
pool = Pool(4)
pool.map(get_video_data,urls)
pool.close()
pool.join()
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