python自动下载图片

#抓取爱小姐姐网图片保存到本地

import requests

from lxml import etree as et

import os

#请求头

headers = {

#用户代理

'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.108 Safari/537.36'

}

#待抓取网页基地址

base_url = ''

#保存图片基本路径

base_dir = 'D:/python/code/aixjj/'

#保存图片

def savePic(pic_url):

#如果目录不存在，则新建

if not os.path.exists(base_dir):

os.makedirs(base_dir)

arr = pic_url.split('/')

file_name = base_dir+arr[-2]+arr[-1]

print(file_name)

#获取图片内容

response = requests.get(pic_url, headers = headers)

#写入图片

with open(file_name,'wb') as fp:

for data in response.iter_content(128):

fp.write(data)

#观察此网站总共只有62页，所以循环62次

for k in range(1,63):

#请求页面地址

url = base_url+str(k)

response = requests.get(url = url, headers = headers)

#请求状态码

code = response.status_code

if code == 200:

html = et.HTML(response.text)

#获取页面所有图片地址

r = html.xpath('//li/a/img/@src')

#获取下一页url

#t = html.xpath('//div[@class="page"]/a[@class="ch"]/@href')[-1]

for pic_url in r:

a = 'http:'+pic_url

savePic(a)

print('第%d页图片下载完成' % (k))

print('The End!')

撸个多进程版本试试。然后就产生了下面这个多进程版本

#多进程版——抓取爱小姐姐网图片保存到本地

import requests

from lxml import etree as et

import os

import time

from multiprocessing import Pool

#请求头

headers = {

#用户代理

'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.108 Safari/537.36'

}

#待抓取网页基地址

base_url = ''

#保存图片基本路径

base_dir = 'D:/python/code/aixjj1/'

#保存图片

def savePic(pic_url):

#如果目录不存在，则新建

if not os.path.exists(base_dir):

os.makedirs(base_dir)

arr = pic_url.split('/')

file_name = base_dir+arr[-2]+arr[-1]

print(file_name)

#获取图片内容

response = requests.get(pic_url, headers = headers)

#写入图片

with open(file_name,'wb') as fp:

for data in response.iter_content(128):

fp.write(data)

def geturl(url):

#请求页面地址

#url = base_url+str(k)

response = requests.get(url = url, headers = headers)

#请求状态码

code = response.status_code

if code == 200:

html = et.HTML(response.text)

#获取页面所有图片地址

r = html.xpath('//li/a/img/@src')

#获取下一页url

#t = html.xpath('//div[@class="page"]/a[@class="ch"]/@href')[-1]

for pic_url in r:

a = 'http:'+pic_url

savePic(a)

if __name__ == '__main__':

#获取要爬取的链接列表外汇返佣

url_list = [base_url+format(i) for i in range(1,100)]

a1 = time.time()

#利用进程池方式创建进程，默认创建进程数量=电脑核数

#自己定义进程数量方式 pool = Pool(4)

pool = Pool()

pool.map(geturl,url_list)

pool.close()

pool.join()

b1 = time.time()

print('运行时间：',b1-a1)

诞生了第三款：

import threading # 导入threading模块

from queue import Queue #导入queue模块

import time #导入time模块

import requests

import os

from lxml import etree as et

#请求头

headers = {

#用户代理

'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.108 Safari/537.36'

}

#待抓取网页基地址

base_url = ''

#保存图片基本路径

base_dir = 'D:/python/code/aixjj/'

#保存图片

def savePic(pic_url):

#如果目录不存在，则新建

if not os.path.exists(base_dir):

os.makedirs(base_dir)

arr = pic_url.split('/')

file_name = base_dir+arr[-2]+arr[-1]

print(file_name)

#获取图片内容

response = requests.get(pic_url, headers = headers)

#写入图片

with open(file_name,'wb') as fp:

for data in response.iter_content(128):

fp.write(data)

# 爬取文章详情页

def get_detail_html(detail_url_list, id):

while True:

url = detail_url_list.get() #Queue队列的get方法用于从队列中提取元素

response = requests.get(url = url, headers = headers)

#请求状态码

code = response.status_code

if code == 200:

html = et.HTML(response.text)

#获取页面所有图片地址

r = html.xpath('//li/a/img/@src')

#获取下一页url

#t = html.xpath('//div[@class="page"]/a[@class="ch"]/@href')[-1]

for pic_url in r:

a = 'http:'+pic_url

savePic(a)

# 爬取文章列表页

def get_detail_url(queue):

for i in range(1,100):

#time.sleep(1) # 延时1s，模拟比爬取文章详情要快

#Queue队列的put方法用于向Queue队列中放置元素，由于Queue是先进先出队列，所以先被Put的URL也就会被先get出来。

page_url = base_url+format(i)

queue.put(page_url)

print("put page url {id} end".format(id = page_url))#打印出得到了哪些文章的url

#主函数

if __name__ == "__main__":

detail_url_queue = Queue(maxsize=1000) #用Queue构造一个大小为1000的线程安全的先进先出队列

#A线程负责抓取列表url

thread = threading.Thread(target=get_detail_url, args=(detail_url_queue,))

html_thread= []

#另外创建三个线程负责抓取图片

for i in range(20):

thread2 = threading.Thread(target=get_detail_html, args=(detail_url_queue,i))

html_thread.append(thread2)#B C D 线程抓取文章详情

start_time = time.time()

# 启动四个线程

thread.start()

for i in range(20):

html_thread[i].start()

# 等待所有线程结束，thread.join()函数代表子线程完成之前，其父进程一直处于阻塞状态。

thread.join()

for i in range(20):

html_thread[i].join()

print("last time: {} s".format(time.time()-start_time))#等ABCD四个线程都结束后，在主进程中计算总爬取时间。