《进击的虫师》百度贴吧通用抓图脚本

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多进程优势:单个进程的崩溃,不会影响其它进程 随之而来的问题是,进程之间,资源不共享,信息不共享,所以进程通讯的问题,是实现多进程协作,必须解决的问题

为解决进程间的通讯,人们常用的方法是 --> 创建一个中间人(队列),作为他们交流的中介...

###以爬取某贴吧帖子中的所有图片为例:

大致需要四步

一. 获取所有的 帖子的目录

二. 根据帖子的目录,获取 帖子详情页

三. 根据 帖子详情页 的源码,获取内嵌的 图片url信息

四. 根据 图片url信息,下载图片到本地

通信图

动图_脚本运行效果

运行中

from multiprocessing import Process, Queue
import time
from time import sleep
import requests
from lxml import etree
import os, sys
import re

class BaiduTb(object):
	def __init__(self, tb_name):
		self.start_url = "https://tieba.baidu.com/f?ie=utf-8&kw=" + tb_name
		self.q_list = Queue()
		self.q_detail = Queue()
		self.q_image = Queue()
		self.headers = {
			"User-Agent": "Mozilla/4.0 (compatible; MSIE 5.01; Windows NT 5.0) "
		}
		self.p1 = None
		self.p2 = None
		self.p3 = None
		self.p4 = None
	# 获取响应内容
	def get_response_content(self, url):
		response = requests.get(url, headers = self.headers)
		print("-->",response)
		return response.content
	# 获取下一个网页url
	def get_next_url(self, now_url):
		content = self.get_response_content(now_url)
		# 将响应信息转换为element对象
		html = etree.HTML(content)
		# 通过xpath获取下一页的链接
		next_url = "http:" + html.xpath('//a[@class="next pagination-item "]/@href')[0]
		return next_url

	def get_list_page_urls(self, q_list):
		while True:
			try:
				sleep(1)
				q_list.put(self.start_url)
				self.start_url = self.get_next_url(self.start_url)
			except:
				print("主程序..")

	def get_detail_page_urls(self, q_list, q_detail):
		while True:
			sleep(1)
			try:
				if not q_list.empty():
					list_url = q_list.get(True)
				else:
					continue

			except:
				print("第二进程已完成..")

			content = self.get_response_content(list_url)
			# 将响应信息转换为element对象
			html = etree.HTML(content)

			# 获取 标题 和url 列表
			detail_titles_list = html.xpath('//*[@id="thread_list"]//div/div[2]/div[1]/div[1]/a/text()')
			detail_urls_list = html.xpath('//*[@id="thread_list"]//div/div[2]/div[1]/div[1]/a/@href')

			# 将"标题"和 url 增加到 详情页队列中
			for i in range(len(detail_titles_list)):
				detail_title = detail_titles_list[i]
				detail_url = "https://tieba.baidu.com" + detail_urls_list[i]
				temp_tuple = (detail_title, detail_url)
				q_detail.put(temp_tuple)

	def get_image_urls (self, q_detail, q_image):
		while True:
			sleep(3)
			try:
				detail = q_detail.get()
				detail_title = detail[0]
				detail_url = detail[1]
			except Exception as e:
				print("第三进程已完成")
			# 获取详情页所有图片的url
			content = self.get_response_content(detail_url)
			# 将响应信息转换为element对象
			html = etree.HTML(content)
			# 通过xpath获取下一页的链接
			image_urls = html.xpath('//cc//img/@src')
			for i in range(len(image_urls)):
				image_url = image_urls[i]
				temp_image_info = (detail_title, image_url)
				q_image.put(temp_image_info)

	def save_image(self, q_image):

		while True:
			sleep(3)
			try:
				if not q_image.empty():
					image_info = q_image.get()
					image_name = re.match(r".*(.{10})", image_info[1]).group(1)
					print("图片名称为:", image_name, "图片地址为:", image_info[1], "帖子标题为:", image_info[0])
					# 尝试根据帖子名称,创建新文件夹
					try:
						os.mkdir("./%s"%(image_info[0]))
					except:
						pass
					new_file_path = "./%s/%s"%(image_info[0],image_name)
					with open(new_file_path, "wb") as f:
						data = self.get_response_content(image_info[1])
						f.write(data)
					if (self.q_list.empty()) and (self.q_detail.empty()) and (self.q_image.empty()):
						exit()
			except:
				print("第四进程已完成")

	def run(self):
		print("开始执行")

		self.p1 = Process(target = self.get_list_page_urls, args=(self.q_list,))
		self.p2 = Process(target = self.get_detail_page_urls, args=(self.q_list, self.q_detail,))	
		self.p3 = Process(target = self.get_image_urls, args=(self.q_detail, self.q_image,))
		self.p4 = Process(target = self.save_image, args=(self.q_image,))

		self.p1.start()
		self.p2.start()
		self.p3.start()
		self.p4.start()

		self.p1.join()
		self.p2.join()
		self.p3.join()
		self.p4.join()


def main():
	name = input("请输入贴吧名称:")
	beautiful_girl = BaiduTb(name)
	beautiful_girl.run()


if __name__ == '__main__':
	main()


多进程和和多线程哪个更好用? 追求资源利用率,考虑多线程 追求程序稳定性,考虑多进程

搞专业爬虫的话,先保证网速够好,再考虑多进程还是多线程~