Python實現bing必應壁紙下載

一、爬取分析

　　必應壁紙：https://bing.ioliu.cn/

　　　　這里共有1~84頁，每頁12張圖片

 

 

對於圖片的地址分析：

　　首先是首頁能獲取到圖片名稱：/photo/PoniesWales_EN-AU12228719072?force=home_2

 

 　　在通過對圖片詳情頁分析：通過對地址拼接就能得到圖片下載地址

 　　http://h1.ioliu.cn/bing/PoniesWales_EN-AU12228719072_1920x1080.jpg

 

二、源碼分享

import re
import sys
import os
import requests
import urllib.request
from bs4 import BeautifulSoup
# get all image pae 1~84
def allpage():
    for i in range(2,84):
        url = 'https://bing.ioliu.cn/?p=' + str(i)
        imageitem(url)
        # print (url)

# get each image item
def imageitem(url):
    # url = "https://bing.ioliu.cn/?p=2"
    html_doc = urllib.request.urlopen(url).read()
    # html_doc = html_doc.decode('utf-8')
    soup = BeautifulSoup(html_doc,"html.parser",from_encoding="UTF-8")
    links = soup.select('.container .item .mark')
    for link in links:
        s = link['href']
        down(strhandler(s))

def strhandler(s):
    # s = '/photo/PoniesWales_EN-AU12228719072?force=home_2'
    l = s.find('?')
    s = s[7:l]
    # print (s)
    return s
# download image
def down(name):
    url = 'http://h1.ioliu.cn//bing/'+str(name)+'_1920x1080.jpg'
    headers = {
    'Accept': '*/*',
    'Accept-Encoding': 'gzip, deflate, br',
    'Accept-Language': 'zh-CN,zh;q=0.8,zh-TW;q=0.7,zh-HK;q=0.5,en-US;q=0.3,en;q=0.2',
    'Connection': 'keep-alive',
    'Referer': url,
    'User-agent': 'Mozilla/5.0 (Windows NT 10.0; WOW 64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/55.0.2883.87 Safari/537.36 QIHU 360SE'
    }
    r = requests.get(url,headers=headers)
    path = 'photos/'+name+'.jpg'
    print (r)
    print (' downing.. '+path)
    with open(path, "wb") as code:
     code.write(r.content)
def main():
    allpage()

# Test
allpage()
# down('PoniesWales_EN-AU12228719072')

三、結果

成功下載，在photots下生成文件

 

四、注意

1、bing網站的反爬蟲

需要設置headers進行模擬，在requests中進行設置：

headers = {
    'Accept': '*/*',
    'Accept-Encoding': 'gzip, deflate, br',
    'Accept-Language': 'zh-CN,zh;q=0.8,zh-TW;q=0.7,zh-HK;q=0.5,en-US;q=0.3,en;q=0.2',
    'Connection': 'keep-alive',
    'Referer': url,
    'User-agent': 'Mozilla/5.0 (Windows NT 10.0; WOW 64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/55.0.2883.87 Safari/537.36 QIHU 360SE'
    }
    r = requests.get(url,headers=headers)

成功后:

 2、效率問題

由於未使用爬蟲優化，所以速度比較慢

　　單線程爬取

可以采用多線程進行同時爬取，以加快速度。