爬虫学习（一）---爬取电影天堂下载链接

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爬虫学习
爬虫学习（一）—爬取电影天堂下载链接
爬虫学习（二）–爬取360应用市场app信息

主要利用了python3.5 requests，BeautifulSoup，eventlet三个库来实现。

1、解析单个电影的详细页面
例如这个网址：http://www.dy2018.com/i/98477.html。要获取这个电影的影片名和下载地址。我们先打开这个网页来分析下这个这个网页的源代码。

包含影片名字的字段：

<div class="title_all"><h1>2017年欧美7.0分科幻片《猩球崛起3：终极之战》HD中英双字</h1></div>

包含影片下载地址的 字段：

 <td style="WORD-WRAP: break-word" bgcolor="#fdfddf"><a href="ftp://d:[email protected]:12311/[电影天堂www.dy2018.com]猩球崛起3：终极之战HD中英双字.rmvb">ftp://d:[email protected]:12311/[电影天堂www.dy2018.com]猩球崛起3：终极之战HD中英双字.rmvb</a></td>

获取单个影片的影片名和下载链接

import re
import requests
from bs4 import BeautifulSoup

url = 'http://www.dy2018.com/i/98477.html'

headers = {'User-Agent':'Mozilla/5.0 (Windows NT 6.1; WOW64; rv:38.0) Gecko/20100101 Firefox/38.0'}


def get_one_film_detail(url):
    #print("one_film doing:%s" % url)
    r = requests.get(url, headers=headers)
    # print(r.text.encode(r.encoding).decode('gbk'))
    bsObj = BeautifulSoup(r.content.decode('gbk','ignore'), "html.parser")
    td = bsObj.find('td', attrs={'style': 'WORD-WRAP: break-word'})
    if td is None:#没有找到下载标签的返回None，个别网页格式不同
        return None, None
    url_a = td.find('a')
    url_a = url_a.string
    title = bsObj.find('h1')
    title = title.string
    # title = re.findall(r'[^《》]+', title)[1] #此处处理一下的话就只返回影片名 本例结果为：猩球崛起3：终极之战
    return title, url_a

print (get_one_film_detail(url))

2、解析页面列表中所有的影片链接
先打开一个影片列表链接，例如：http://www.dy2018.com/2/index_2.html
打开查看源码可以看到每部影片都是下面这样的信息开头，然后接上影片的简单介绍，介绍我们不关心，只关心下面这段含有影片详情页面的链接，主要获取这个页面所有这样列出的影片的详情页面的链接。

<td height="26">
    <b>
        <a class=ulink href='/html/gndy/dyzz/'>[最新电影]</a>
        <a href="/i/98256.html" class="ulink" title="2017年印度7.1分动作片《巴霍巴利王(下)：终结》BD中英双字">2017年印度7.1分动作片《巴霍巴利王(下)：终结》BD中英双字</a>
    </b>
</td>

import re
import requests
from bs4 import BeautifulSoup

page_url = 'http://www.dy2018.com/2/index_22.html'

headers = {'User-Agent':'Mozilla/5.0 (Windows NT 6.1; WOW64; rv:38.0) Gecko/20100101 Firefox/38.0'}


def get_one_page_urls(page_url):
    #print("one_page doing：%s" % page_url)
    urls = []
    base_url = "http://www.dy2018.com"
    r = requests.get(page_url, headers=headers)
    bsObj = BeautifulSoup(r.content, "html.parser")
    url_all = bsObj.find_all('a', attrs={'class': "ulink", 'title': re.compile('.*')})
    for a_url in url_all:
        a_url = a_url.get('href')
        a_url = base_url + a_url
        urls.append(a_url)
    return urls

print (get_one_page_urls(page_url))

3、多页面开始爬虫
有了前面两步骤的准备就可以进行多页面爬取数据了。

import eventlet
import re
import time
import requests
from bs4 import BeautifulSoup

headers = {'User-Agent':'Mozilla/5.0 (Windows NT 6.1; WOW64; rv:38.0) Gecko/20100101 Firefox/38.0'}


def get_one_film_detail(url):
    print("one_film doing:%s" % url)
    r = requests.get(url, headers=headers)
    # print(r.text.encode(r.encoding).decode('gbk'))
    bsObj = BeautifulSoup(r.content.decode('gbk','ignore'), "html.parser")
    td = bsObj.find('td', attrs={'style': re.compile('.*')})
    if td is None:
        return None, None
    url_a = td.find('a')
    url_a = url_a.string
    title = bsObj.find('h1')
    title = title.string
    # title = re.findall(r'[^《》]+', title)[1]
    return title, url_a


def get_one_page_urls(page_url):
    print("one_page doing：%s" % page_url)
    urls = []
    base_url = "http://www.dy2018.com"
    r = requests.get(page_url, headers=headers)
    bsObj = BeautifulSoup(r.content, "html.parser")
    url_all = bsObj.find_all('a', attrs={'class': "ulink", 'title': re.compile('.*')})
    for a_url in url_all:
        a_url = a_url.get('href')
        a_url = base_url + a_url
        urls.append(a_url)
    return urls
    # print(r.text.encode(r.encoding).decode('gbk'))


pool = eventlet.GreenPool()
f = open("download.txt", "w")
start = time.time()

for i in range(2, 100):
    page_url = 'http://www.dy2018.com/2/index_%s.html' % i
    for title, url_a in pool.imap(get_one_film_detail, get_one_page_urls(page_url)):
        # print("titel:%s,download url:%s"%(title,url_a))
        f.write("%s:%s\n\n" % (title, url_a))
end = time.time()
print('total time cost:')
print(end - start)

前面的这段代码估计是因为用了绿色线程爬取速度过快，爬去到了20多页之后会主动给我断开，报错如下：

 raise RemoteDisconnected("Remote end closed connection without"
http.client.RemoteDisconnected: Remote end closed connection without response

优化之后的代码

import eventlet
import re
import time
import requests
from bs4 import BeautifulSoup

result = []
headers={'User-Agent':'Mozilla/5.0 (Windows NT 6.1; WOW64; rv:38.0) Gecko/20100101 Firefox/38.0'}

def get_one_film_detail(urls):
    req = requests.session() #此处改用session，可以减少和服务器的 tcp链接次数。
    req.headers.update(headers)
    for url in urls:
        print("one_film doing:%s" % url)
        r = req.get(url)
        # print(r.text.encode(r.encoding).decode('gbk'))
        bsObj = BeautifulSoup(r.content.decode('gbk','ignore'), "html.parser")
        td = bsObj.find('td', attrs={'style': re.compile('.*')})
        if td is None:
            continue
        url_a = td.find('a')
        if url_a is None:
            continue
        url_a = url_a.string
        title = bsObj.find('h1')
        title = title.string
        # title = re.findall(r'[^《》]+', title)[1]
        f = open("download.txt", "a")
        f.write("%s:%s\n\n" % (title, url_a))



def get_one_page_urls(page_url):
    print("one_page doing：%s" % page_url)
    urls = []
    base_url = "http://www.dy2018.com"
    r = requests.get(page_url, headers=headers)
    bsObj = BeautifulSoup(r.content, "html.parser")
    url_all = bsObj.find_all('a', attrs={'class': "ulink", 'title': re.compile('.*')})
    for a_url in url_all:
        a_url = a_url.get('href')
        a_url = base_url + a_url
        urls.append(a_url)
    return urls
    # print(r.text.encode(r.encoding).decode('gbk'))


pool = eventlet.GreenPool()
start = time.time()
page_urls = ['http://www.dy2018.com/2/']
for i in range(2, 100):
    page_url = 'http://www.dy2018.com/2/index_%s.html' % i
    page_urls.append(page_url)

for urls in pool.imap(get_one_page_urls, page_urls):
        get_one_film_detail(urls)

end = time.time()
print('total time cost:')
print(end - start)

优化之后相当于多线程获取所有的影片的链接，再单线程去获取每个影片的下载地址。获取电影天堂上面的动作电影下载链接总共 花了

total time cost:
304.44839310646057

获取结果如下图所示

如果源码对你有用，请评论下博客说声谢谢吧~
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