多线程爬虫(完善版)

import threading

from queue import Queue

import time

from lxml import etree

import requests

import json

# 判断解析线程何时退出的标记位

g_parse_flag = True

class CrawlThread(threading.Thread):

def __init__(self, name, page_queue, data_queue):

super().__init__()

self.name = name

# 保存页码队列

self.page_queue = page_queue

self.data_queue = data_queue

# url

self.url = 'http://www.fanjian.net/duanzi-{}'

self.headers = {

'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/67.0.3396.99 Safari/537.36',

}

def run(self):

print('%s线程开始启动' % self.name)

# 这里面的思路是什么?

while 1:

if self.page_queue.empty():

break

# 1、从页码队列中获取页码

page = self.page_queue.get()

# 2、将url和页码进行拼接

url = self.url.format(page)

# 3、发送请求,获取响应

r = requests.get(url=url, headers=self.headers)

time.sleep(1)

# 4、将响应内容放入到数据队列中

self.data_queue.put(r.text)

print('%s线程结束' % self.name)

class ParseThread(threading.Thread):

def __init__(self, name, data_queue, lock, fp):

super().__init__()

self.name = name

# 保存数据队列

self.data_queue = data_queue

self.lock = lock

self.fp = fp

def run(self):

# time.sleep(3)

print('%s线程开始启动' % self.name)

# 解析线程解析步骤

while 1:

# 1、从数据队列中取出一个数据

content = self.data_queue.get()

# 2、解析这个数据

items = self.parse_content(content)

# 3、写入到文件中

string = json.dumps(items, ensure_ascii=False)

# 加锁

self.lock.acquire()

self.fp.write(string + '====\n')

# 释放锁

self.lock.release()

time.sleep(2)

if g_parse_flag == False:

break

print('%s线程结束' % self.name)

# 解析数据函数

def parse_content(self, content):

# 生成tree对象

tree = etree.HTML(content)

# 先找到所有的li标签

li_list = tree.xpath('//li[@class="cont-item"]')

items = []

for oli in li_list:

# 获取头像

face = oli.xpath('.//div[@class="cont-list-reward"]//img/@data-src')[0]

# 获取名字

name = oli.xpath('.//div[@class="cont-list-head"]/a/text()')[0]

# 获取内容

text = oli.xpath('.//div[@class="cont-list-main"]/p/text()')[0]

# 获取时间

shijian = oli.xpath('.//div[@class="cont-list-info fc-gray"]/text()')[-1]

item = {

'头像': face,

'名字': name,

'内容': text,

'时间': shijian,

}

# 将字典添加到列表中

items.append(item)

return items

def create_queue():

page_queue = Queue()

data_queue = Queue()

# 向页码队列中添加页码

for page in range(1, 11):

page_queue.put(page)

return page_queue, data_queue

def main():

# 做什么?

# 创建锁

lock = threading.Lock()

# 打开文件

fp = open('duanzi.txt', 'w', encoding='utf8')

# 创建两个队列

page_queue, data_queue = create_queue()

# 创建采集、解析线程

crawlname_list = ['采集线程1', '采集线程2', '采集线程3']

parsename_list = ['解析线程1', '解析线程2', '解析线程3']

# 列表,用来保存所有的采集线程和解析线程

t_crawl_list = []

t_parse_list = []

for crawlname in crawlname_list:

t_crawl = CrawlThread(crawlname, page_queue, data_queue)

t_crawl.start()

# 将对应的采集线程保存起来

t_crawl_list.append(t_crawl)

for parsename in parsename_list:

t_parse = ParseThread(parsename, data_queue, lock, fp)

# 将对应的解析线程保存起来

t_parse_list.append(t_parse)

t_parse.start()

# 一直在判断解析线程何时推出

while 1:

if page_queue.empty():

break

time.sleep(3)

while 1:

if data_queue.empty():

global g_parse_flag

g_parse_flag = False

break

# 让主线程等待子线程结束之后再结束

for t_crawl in t_crawl_list:

t_crawl.join()

for t_parse in t_parse_list:

t_parse.join()

fp.close()

print('主线程、子线程全部结束')

if __name__ == '__main__':

main()

# 留给大家了,为什么里面没有写数据呢?

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