#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!')

#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
  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)

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。