爬虫入门（九）多线程and多进程爬虫

1. 爬取糗事百科段子

# coding=utf-8
import requests
from lxml import etree
import time

class QiuBai:
    def __init__(self):
        self.temp_url = "http://www.qiushibaike.com/8hr/page/{}"
        self.headers = {"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_13_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/66.0.3359.139 Safari/537.36"}

    def get_url_list(self):
        return [self.temp_url.format(i) for i in range(1,14)]

    def parse_url(self,url):
        response = requests.get(url,headers=self.headers)
        return response.content.decode()

    def get_content_list(self,html_str):#提取数据
        html = etree.HTML(html_str)
        div_list = html.xpath("//div[@id='content-left']/div")
        content_list = []
        for div in div_list:
            item = {}
            # strip去除字符中的空格
            item["user_name"] = div.xpath(".//h2/text()")[0].strip()
            item["content"] = [i.strip() for i in div.xpath(".//div[@class='content']/span/text()")]
            content_list.append(item)
        return content_list

    def save_content_list(self,content_list): #保存
        for content in content_list:
            print(content)

    def run(self):#实现做主要逻辑
        #1. 准备url列表
        url_list = self.get_url_list()
        #2. 遍历发送请求，获取响应
        for url in url_list:
            html_str = self.parse_url(url)
            #3. 提取数据
            content_list = self.get_content_list(html_str)
            #4. 保存
            self.save_content_list(content_list)


if __name__ == '__main__':
    t1 = time.time()
    qiubai = QiuBai()
    qiubai.run()
    print("total cost:",time.time()-t1)

写成多线程方式实现

在python3中，主线程主进程结束，子线程，子进程不会结束
为了能够让主线程回收子线程，可以把子线程设置为守护线程,即该线程不重要，主线程结束，子线程结束

t1 = threading.Thread(targe=func,args=(,))
t1.setDaemon(True)
t1.start() #此时线程才会启动

队列模块的使用

from queue import Queue
q = Queue(maxsize=100)
item = {}
q.put_nowait(item) #不等待直接放，队列满的时候会报错
q.put(item) #放入数据，队列满的时候回等待
q.get_nowait() #不等待直接取，队列空的时候会报错
q.get() #取出数据，队列为空的时候会等待
q.qsize() #获取队列中现存数据的个数 
q.join() #队列中维持了一个计数，计数不为0时候让主线程阻塞等待，队列计数为0的时候才会继续往后执行
q.task_done() 
# put的时候计数+1，get不会-1，get需要和task_done 一起使用才会-1

多线程思路的剖解
把爬虫中的每个步骤封装成函数，分别用线程去执行
不同的函数通过队列相互通信，函数间解耦

改写代码：

# coding=utf-8
import requests
from lxml import etree
from queue import Queue
import threading
import time


class QiuBai:
    def __init__(self):
        self.temp_url = "http://www.qiushibaike.com/8hr/page/{}"
        self.headers = {"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_13_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/66.0.3359.139 Safari/537.36"}
        self.url_queue = Queue()
        self.html_queue = Queue()
        self.content_list_queue = Queue()

    def get_url_list(self):
        # return [self.temp_url.format(i) for i in range(1,14)]
        for i in range(1,14):
            self.url_queue.put(self.temp_url.format(i))

    def parse_url(self):
        while True:
            url = self.url_queue.get()
            response = requests.get(url,headers=self.headers)
            print(response)

            if response.status_code != 200:
                self.url_queue.put(url)
            else:
                self.html_queue.put(response.content.decode())
            self.url_queue.task_done()  #让队列的计数-1

    def get_content_list(self):#提取数据
        while True:
            html_str = self.html_queue.get()
            html = etree.HTML(html_str)
            div_list = html.xpath("//div[@id='content-left']/div")
            content_list = []
            for div in div_list:
                item = {}
                item["user_name"] = div.xpath(".//h2/text()")[0].strip()
                item["content"] = [i.strip() for i in div.xpath(".//div[@class='content']/span/text()")]
                content_list.append(item)
            self.content_list_queue.put(content_list)
            self.html_queue.task_done()

    def save_content_list(self): #保存
        while True:
            content_list = self.content_list_queue.get()
            for content in content_list:
                # print(content)
                pass
            self.content_list_queue.task_done()

    def run(self):#实现做主要逻辑
        thread_list = []
        #1. 准备url列表
        t_url = threading.Thread(target=self.get_url_list)
        thread_list.append(t_url)
        #2. 遍历发送请求，获取响应
        for i in range(3):
            t_parse = threading.Thread(target=self.parse_url)
            thread_list.append(t_parse)
        #3. 提取数据
        t_content = threading.Thread(target=self.get_content_list)
        thread_list.append(t_content)
            #4. 保存
        t_save = threading.Thread(target=self.save_content_list)
        thread_list.append(t_save)

        for t in thread_list:
            t.setDaemon(True) #把子线程设置为守护线程
            t.start()

        for q in [self.url_queue,self.html_queue,self.content_list_queue]:
            q.join() #让主线程阻塞，等待队列计数为0


if __name__ == '__main__':
    t1 = time.time()
    qiubai = QiuBai()
    qiubai.run()
    print("total cost:",time.time()-t1)

写成多进程方式实现

使用的方法

from multiprocessing import Process
t1 = Process(targe=func,args=(,))
t1.daemon = True  #设置为守护进程
t1.start() #此时线程才会启动

多进程中使用普通的队列模块会发生阻塞，对应的需要使用multiprocessing提供的JoinableQueue模块，其使用过程和在线程中使用的queue方法相同
改写代码：

# coding=utf-8
import requests
from lxml import etree
# from queue import Queue
# import threading
from multiprocessing import Process
from multiprocessing import JoinableQueue as Queue
import time

class QiuBai:
    def __init__(self):
        self.temp_url = "http://www.qiushibaike.com/8hr/page/{}"
        self.headers = {"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_13_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/66.0.3359.139 Safari/537.36"}
        self.url_queue = Queue()
        self.html_queue = Queue()
        self.content_list_queue = Queue()

    def get_url_list(self):
        # return [self.temp_url.format(i) for i in range(1,14)]
        for i in range(1,14):
            self.url_queue.put(self.temp_url.format(i))

    def parse_url(self):
        while True:
            url = self.url_queue.get()
            response = requests.get(url,headers=self.headers)
            print(response)

            if response.status_code != 200:
                self.url_queue.put(url)
            else:
                self.html_queue.put(response.content.decode())
            self.url_queue.task_done()  #让队列的计数-1

    def get_content_list(self):#提取数据
        while True:
            html_str = self.html_queue.get()
            html = etree.HTML(html_str)
            div_list = html.xpath("//div[@id='content-left']/div")
            content_list = []
            for div in div_list:
                item = {}
                item["user_name"] = div.xpath(".//h2/text()")[0].strip()
                item["content"] = [i.strip() for i in div.xpath(".//div[@class='content']/span/text()")]
                content_list.append(item)
            self.content_list_queue.put(content_list)
            self.html_queue.task_done()

    def save_content_list(self): #保存
        while True:
            content_list = self.content_list_queue.get()
            for content in content_list:
                # print(content)
                pass
            self.content_list_queue.task_done()

    def run(self):#实现做主要逻辑
        thread_list = []
        #1. 准备url列表
        t_url = Process(target=self.get_url_list)
        thread_list.append(t_url)
        #2. 遍历发送请求，获取响应
        for i in range(13):
            t_parse = Process(target=self.parse_url)
            thread_list.append(t_parse)
        #3. 提取数据
        t_content = Process(target=self.get_content_list)
        thread_list.append(t_content)
        #4. 保存
        t_save = Process(target=self.save_content_list)
        thread_list.append(t_save)

        for p in thread_list:
            p.daemon = True #把子线程设置为守护线程
            p.start()

        for q in [self.url_queue,self.html_queue,self.content_list_queue]:
            q.join() #让主线程阻塞，等待队列计数为0


if __name__ == '__main__':
    t1 = time.time()
    qiubai = QiuBai()
    qiubai.run()
    print("total cost:",time.time()-t1)