python 通过线程池实现更快的爬虫_multiprocessing.pool()结合queue实现python爬虫

1. 线程池使用方法介绍

1. 实例化线程池对象

    from multiprocessing.dummy import Pool
    pool = Pool(process=5) #默认大小是cup的个数
   

2. 把从发送请求，提取数据，到保存合并成一个函数，交给线程池异步执行

   使用方法pool.apply_async(func)

    def exetute_requests_item_save(self):
        url = self.queue.get()
        html_str = self.parse_url(url)
        content_list = self.get_content_list(html_str)
        self.save_content_list(content_list)
        self.total_response_num +=1
    
    pool.apply_async(self.exetute_requests_item_save)
   

3. 添加回调函数

   通过apply_async的方法能够让函数异步执行，但是只能够执行一次

   为了让其能够被反复执行，通过添加回调函数的方式能够让_callback 递归的调用自己

   同时需要指定递归退出的条件

    def _callback(self,temp):
        if self.is_running:
             pool.apply_async(self.exetute_requests_item_save,callback=self._callback)
    
    pool.apply_async(self.exetute_requests_item_save,callback=self._callback)
   

4. 确定程序结束的条件 程序在获取的响应和url数量相同的时候可以结束

    while True: #防止主线程结束
        time.sleep(0.0001)  #避免cpu空转，浪费资源
        if self.total_response_num>=self.total_requests_num:
            self.is_running= False
            break
    self.pool.close() #关闭线程池，防止新的线程开启
   # self.pool.join() #等待所有的子线程结束
   

2. 使用线程池实现爬虫的具体实现

# coding=utf-8
import requests
from lxml import etree
from queue import Queue
from multiprocessing.dummy import Pool
import time
 
 
class QiubaiSpider:
    def __init__(self):
        self.url_temp = "https://www.qiushibaike.com/8hr/page/{}/"
        self.headers = {"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X \
        10_13_3) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/64.0.3282.186 Safari/537.36"}
        self.queue = Queue()
        self.pool = Pool(5)
        self.is_running = True
        self.total_requests_num = 0
        self.total_response_num = 0
 
    def get_url_list(self):  # 获取url列表
        for i in range(1, 14):
            self.queue.put(self.url_temp.format(i))
            self.total_requests_num += 1
 
    def parse_url(self, url):  # 发送请求，获取响应
        return requests.get(url, headers=self.headers).content.decode()
 
    def get_content_list(self, html_str):  # 提取段子
        html = etree.HTML(html_str)
        div_list = html.xpath("//div[@id='content-left']/div")
        content_list = []
        for div in div_list:
            content = {}
            content["content"] = div.xpath(".//div[@class='content']/span/text()")
            print(content)
            content_list.append(content)
        return content_list
 
    def save_content_list(self, content_list):  # 保存数据
        pass
 
    def exetute_requests_item_save(self):
        url = self.queue.get()
        html_str = self.parse_url(url)
        content_list = self.get_content_list(html_str)
        self.save_content_list(content_list)
        self.total_response_num += 1
 
    def _callback(self, temp):
        if self.is_running:
            self.pool.apply_async(self.exetute_requests_item_save, callback=self._callback)
 
    def run(self):
        self.get_url_list()
 
        for i in range(2):  # 控制并发
            self.pool.apply_async(self.exetute_requests_item_save, callback=self._callback)
 
        while True:  # 防止主线程结束
            time.sleep(0.0001)  # 避免cpu空转，浪费资源
            if self.total_response_num >= self.total_requests_num:
                self.is_running = False
                break
 
        self.pool.close()  # 关闭线程池，防止新的线程开启
        # self.pool.join() #等待所有的子线程结束
 
if __name__ == '__main__':
    qiubai = QiubaiSpider()
    qiubai.run()

3. 使用协程池实现爬虫的具体实现

# coding=utf-8
import gevent.monky
gevent.monky.path_all()
from gevent.pool import Pool
 
 
import requests
from lxml import etree
from queue import Queue
import time
 
 
class QiubaiSpider:
    def __init__(self):
        self.url_temp = "https://www.qiushibaike.com/8hr/page/{}/"
        self.headers = {"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X \
        10_13_3) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/64.0.3282.186 Safari/537.36"}
        self.queue = Queue()
        self.pool = Pool(5)
        self.is_running = True
        self.total_requests_num = 0
        self.total_response_num = 0
 
    def get_url_list(self):  # 获取url列表
        for i in range(1, 14):
            self.queue.put(self.url_temp.format(i))
            self.total_requests_num += 1
 
    def parse_url(self, url):  # 发送请求，获取响应
        return requests.get(url, headers=self.headers).content.decode()
 
    def get_content_list(self, html_str):  # 提取段子
        html = etree.HTML(html_str)
        div_list = html.xpath("//div[@id='content-left']/div")
        content_list = []
        for div in div_list:
            content = {}
            content["content"] = div.xpath(".//div[@class='content']/span/text()")
            print(content)
            content_list.append(content)
        return content_list
 
    def save_content_list(self, content_list):  # 保存数据
        pass
 
    def exetute_requests_item_save(self):
        url = self.queue.get()
        html_str = self.parse_url(url)
        content_list = self.get_content_list(html_str)
        self.save_content_list(content_list)
        self.total_response_num += 1
 
    def _callback(self, temp):
        if self.is_running:
            self.pool.apply_async(self.exetute_requests_item_save, callback=self._callback)
 
    def run(self):
        self.get_url_list()
 
        for i in range(2):  # 控制并发
            self.pool.apply_async(self.exetute_requests_item_save, callback=self._callback)
 
        while True:  # 防止主线程结束
            time.sleep(0.0001)  # 避免cpu空转，浪费资源
            if self.total_response_num >= self.total_requests_num:
                self.is_running = False
                break
 
 
if __name__ == '__main__':
    qiubai = QiubaiSpider()
    qiubai.run()