diff --git a/class PageContentProducer(multiprocessin.py b/class PageContentProducer(multiprocessin.py
new file mode 100644
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+++ b/class PageContentProducer(multiprocessin.py	
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+class PageContentProducer(multiprocessing.Process):
+    def __init__(self, page_list:list, output_queue:multiprocessing.JoinableQueue):
+        multiprocessing.Process.__init__(self)
+        self.daemon = True
+        self.page_list = page_list
+        self.content_list = []
+        self.output_queue = output_queue
+    
+    def run(self):
+        '''
+        向队列中加入每一篇文章
+        '''
+        self.visit_all_page_to_get_content()
+        
+        for content in self.content_list:
+            print(f"已加入: {content['title']}")
+            self.output_queue.put(content)
+        
+    def visit_all_page_to_get_content(self):
+        '''
+        使用线程池处理所有的page, 并从每一页上提取所有的文章content
+        '''
+        # 在 3.8 版更改: max_workers 的默认值已改为 min(32, os.cpu_count() + 4)。这个默认值会
+        # 保留至少 5 个工作线程用于 I/O 密集型任务。对于那些释放了 GIL 的 CPU 密集型任务，它最多会
+        # 使用 32 个 CPU 核心。这样能够避免在多核机器上不知不觉地使用大量资源。
+        # 现在 ThreadPoolExecutor 在启动 max_workers 个工作线程之前也会重用空闲的工作线程。
+        
+        # We can use a with statement to ensure threads are cleaned up promptly
+        with concurrent.futures.ThreadPoolExecutor(max_workers=10) as executor:
+            # 向线程池提交任务
+            future_to_page = {executor.submit(self.get_page_content, page_url) : page_url for page_url in self.page_list}
+            for future in concurrent.futures.as_completed(future_to_page):
+                page = future_to_page[future]
+                try:
+                    # 获取任务执行结果
+                    result_list = future.result()
+                    self.content_list += result_list
+                except Exception as e:
+                    print(f'{page} generated an exception: {e}')
+        print(f'共提取到{len(self.content_list)}条content记录')
+        
+    def get_page_content(self, page_url) -> list:
+        '''
+        线程工作函数, 访问page_url, 并提取该页面上的所有文章, 以列表形式返回
+        '''
+        content_list = []
+        try:
+            res = requests.get(url=page_url)
+            if 200 == res.status_code:
+                page_html = res.content.decode('utf-8')
+                soup = bs(page_html, 'lxml')
+                items = soup.find_all('li', onclick=re.compile('.*content_[0-9]*.*'))
+                print(f'从page: {page_url} 上提取到了[{len(items)}]个content')
+
+                for item in items:
+                    content = {}
+                    # 提取标题
+                    item_title = item.find('a', href='#')
+                    content['title'] = item_title.text
+                    # 提取图片数目
+                    item_num = item.find('span')
+                    content['num'] = item_num.text
+                    # 提取url, 格式为location.href='content_48388.html';
+                    href = item['onclick']
+                    item_url = href.split("'")[1]
+                    content['url'] = 'https://xxxx.xyz/' + item_url
+                    content_list.append(content)
+        except Exception as e:
+            print(f'从page: {page_url} 上添加content失败')
+            print(repr(e))
+        return content_list
+
+
+class PageContentConsumer(multiprocessing.Process):
+    def __init__(self, dir, input_queue:multiprocessing.JoinableQueue):
+        multiprocessing.Process.__init__(self)
+        self.daemon = True
+        self.input_queue = input_queue
+        self.dir = dir
+        
+    def run(self):
+        while True:
+            try:
+                content = self.input_queue.get()
+                if content is None:
+                    # 如果收到结束标志, 就退出当前任务
+                    break
+                self.content_worker_func(self.dir, content)
+                print(f"已处理: {content['title']}")
+                # 发出信号通知任务完成
+                self.input_queue.task_done()
+            except Exception as e:
+                print(repr(e))
+                
+    def content_worker_func(self, dir, content):
+        title = content['title']
+        num = content['num']
+        content_url = content['url']
+        count = 0
+        img_url_list = []
+        pid = os.getpid()
+        
+        try:
+            folder_name = title + '_' + num
+            path = os.path.join(dir, folder_name)
+            if os.path.isdir(path):
+                pass
+            else:
+                os.makedirs(path)
+
+            content_parser = ContentPageParser(content_url)
+            content_parser.visit_content_page_with_firefox()
+            img_url_list = content_parser.get_img_src()
+        except Exception as e:
+            print(repr(e))
+
+        pic_download_threads = []
+        for img_url in img_url_list:
+            count += 1
+            file_name = 'img_' + str(count)
+            thread_name = str(pid) + ':' + str(count)
+            pic_download_threads.append(PicDownloader(thread_name, img_url, file_name, path))
+
+        for working_thread in pic_download_threads:
+            working_thread.start()
+        
+        for working_thread in pic_download_threads:
+            working_thread.join(3)
diff --git a/import multiprocessing.py b/import multiprocessing.py
new file mode 100644
index 0000000000000000000000000000000000000000..351ead4a97436079d8463d8235f98b33d5674b52
--- /dev/null
+++ b/import multiprocessing.py	
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+import multiprocessing
+import os
+from home_page_parser import HomePageParser
+from page_content_handler import PageContentConsumer, PageContentProducer
+
+def main(dir):
+    # 先解析出每一页的url, 生成一个page_list列表
+    home_page_parser = HomePageParser()
+    home_page_parser.parse_home_page()
+    page_list = home_page_parser.get_page_list()
+
+    # 创建一个队列, 用于生产者和消费者进行进程间同步
+    queue = multiprocessing.JoinableQueue()
+    
+    # 创建多个消费者, 消费者的个数取决于cpu的数目
+    consumer_num = os.cpu_count()
+    consumers = []
+
+    for i in range(0, consumer_num):
+        consumers.append(PageContentConsumer(dir, queue))
+    
+    print(f'total {consumer_num} consumers')
+    
+    # 启动消费者进程
+    for i in range(0, consumer_num):
+        consumers[i].start()
+    
+    # 启动生产者进程, 并等待它执行完毕
+    producer = PageContentProducer(page_list, queue)
+    producer.start()
+    producer.join()
+    
+    # 在队列上放置标志,这里我们使用None作为标志，发出完成信号
+    # 注意, 总共有多少个消费者,就需要放置多少个标志
+    for i in range(0, consumer_num):
+        queue.put(None)
+        
+    # 等待所有消费者进程关闭
+    for i in range(0, consumer_num):
+        consumers[i].join()
+    
+if __name__ == '__main__':
+    multiprocessing.freeze_support()
+    
+    dir = 'd:test/consumer2'
+    main(dir)
+