Python多线程、异步＋多进程爬虫实现代码

安装Tornado
省事点可以直接用grequests库，下面用的是tornado的异步client。 异步用到了tornado，根据官方文档的例子修改得到一个简单的异步爬虫类。可以参考下最新的文档学习下。
pip install tornado

异步爬虫

    #!/usr/bin/env python
    # -*- coding:utf-8 -*-

    import time
    from datetime import timedelta
    from tornado import httpclient, gen, ioloop, queues
    import traceback


    class AsySpider(object):
      """A simple class of asynchronous spider."""
      def __init__(self, urls, concurrency=10, **kwargs):
        urls.reverse()
        self.urls = urls
        self.concurrency = concurrency
        self._q = queues.Queue()
        self._fetching = set()
        self._fetched = set()

      def fetch(self, url, **kwargs):
        fetch = getattr(httpclient.AsyncHTTPClient(), 'fetch')
        return fetch(url, **kwargs)

      def handle_html(self, url, html):
        """handle html page"""
        print(url)

      def handle_response(self, url, response):
        """inherit and rewrite this method"""
        if response.code == 200:
          self.handle_html(url, response.body)

        elif response.code == 599:  # retry
          self._fetching.remove(url)
          self._q.put(url)

      @gen.coroutine
      def get_page(self, url):
        try:
          response = yield self.fetch(url)
          print('######fetched %s' % url)
        except Exception as e:
          print('Exception: %s %s' % (e, url))
          raise gen.Return(e)
        raise gen.Return(response)

      @gen.coroutine
      def _run(self):
        @gen.coroutine
        def fetch_url():
          current_url = yield self._q.get()
          try:
            if current_url in self._fetching:
              return

            print('fetching****** %s' % current_url)
            self._fetching.add(current_url)

            response = yield self.get_page(current_url)
            self.handle_response(current_url, response)  # handle reponse

            self._fetched.add(current_url)

            for i in range(self.concurrency):
              if self.urls:
                yield self._q.put(self.urls.pop())

          finally:
            self._q.task_done()

        @gen.coroutine
        def worker():
          while True:
            yield fetch_url()

        self._q.put(self.urls.pop())  # add first url

        # Start workers, then wait for the work queue to be empty.
        for _ in range(self.concurrency):
          worker()

        yield self._q.join(timeout=timedelta(seconds=300000))
        assert self._fetching == self._fetched

      def run(self):
        io_loop = ioloop.IOLoop.current()
        io_loop.run_sync(self._run)


    class MySpider(AsySpider):

      def fetch(self, url, **kwargs):
        """重写父类fetch方法可以添加cookies，headers，timeout等信息"""
        cookies_str = "PHPSESSID=j1tt66a829idnms56ppb70jri4; pspt=%7B%22id%22%3A%2233153%22%2C%22pswd%22%3A%228835d2c1351d221b4ab016fbf9e8253f%22%2C%22_code%22%3A%22f779dcd011f4e2581c716d1e1b945861%22%7D; key=%E9%87%8D%E5%BA%86%E5%95%84%E6%9C%A8%E9%B8%9F%E7%BD%91%E7%BB%9C%E7%A7%91%E6%8A%80%E6%9C%89%E9%99%90%E5%85%AC%E5%8F%B8; think_language=zh-cn; SERVERID=a66d7d08fa1c8b2e37dbdc6ffff82d9e|1444973193|1444967835; CNZZDATA1254842228=1433864393-1442810831-%7C1444972138"  # 从浏览器拷贝cookie字符串
        headers = {
          'User-Agent': 'mozilla/5.0 (compatible; baiduspider/2.0; +http://www.baidu.com/search/spider.html)',
          'cookie': cookies_str
        }
        return super(MySpider, self).fetch(  # 参数参考tornado文档
          url, headers=headers, request_timeout=1
        )

      def handle_html(self, url, html):
        print(url, html)


    def main():
      urls = []
      for page in range(1, 100):
        urls.append('http://www.baidu.com?page=%s' % page)
      s = MySpider(urls)
      s.run()


    if __name__ == '__main__':
      main()

可以继承这个类，塞一些url进去，然后重写handle_page处理得到的页面。

异步＋多进程爬虫
还可以再变态点，加个进程池，使用了multiprocessing模块。效率飕飕的,

    #!/usr/bin/env python
    # -*- coding:utf-8 -*-

    import time
    from multiprocessing import Pool
    from datetime import timedelta
    from tornado import httpclient, gen, ioloop, queues


    class AsySpider(object):
      """A simple class of asynchronous spider."""
      def __init__(self, urls, concurrency):
        urls.reverse()
        self.urls = urls
        self.concurrency = concurrency
        self._q = queues.Queue()
        self._fetching = set()
        self._fetched = set()

      def handle_page(self, url, html):
        filename = url.rsplit('/', 1)[1]
        with open(filename, 'w+') as f:
          f.write(html)

      @gen.coroutine
      def get_page(self, url):
        try:
          response = yield httpclient.AsyncHTTPClient().fetch(url)
          print('######fetched %s' % url)
        except Exception as e:
          print('Exception: %s %s' % (e, url))
          raise gen.Return('')
        raise gen.Return(response.body)

      @gen.coroutine
      def _run(self):

        @gen.coroutine
        def fetch_url():
          current_url = yield self._q.get()
          try:
            if current_url in self._fetching:
              return

            print('fetching****** %s' % current_url)
            self._fetching.add(current_url)
            html = yield self.get_page(current_url)
            self._fetched.add(current_url)

            self.handle_page(current_url, html)

            for i in range(self.concurrency):
              if self.urls:
                yield self._q.put(self.urls.pop())

          finally:
            self._q.task_done()

        @gen.coroutine
        def worker():
          while True:
            yield fetch_url()

        self._q.put(self.urls.pop())

        # Start workers, then wait for the work queue to be empty.
        for _ in range(self.concurrency):
          worker()
        yield self._q.join(timeout=timedelta(seconds=300000))
        assert self._fetching == self._fetched

      def run(self):
        io_loop = ioloop.IOLoop.current()
        io_loop.run_sync(self._run)


    def run_spider(beg, end):
      urls = []
      for page in range(beg, end):
        urls.append('http://127.0.0.1/%s.htm' % page)
      s = AsySpider(urls, 10)
      s.run()


    def main():
      _st = time.time()
      p = Pool()
      all_num = 73000
      num = 4  # number of cpu cores
      per_num, left = divmod(all_num, num)
      s = range(0, all_num, per_num)
      res = []
      for i in range(len(s)-1):
        res.append((s[i], s[i+1]))
      res.append((s[len(s)-1], all_num))
      print res

      for i in res:
        p.apply_async(run_spider, args=(i[0], i[1],))
      p.close()
      p.join()

      print time.time()-_st


    if __name__ == '__main__':
      main()

多线程爬虫
线程池实现.

    #!/usr/bin/env python
    # -*- coding:utf-8 -*-
    import Queue
    import sys
    import requests
    import os
    import threading
    import time

    class Worker(threading.Thread):  # 处理工作请求
      def __init__(self, workQueue, resultQueue, **kwds):
        threading.Thread.__init__(self, **kwds)
        self.setDaemon(True)
        self.workQueue = workQueue
        self.resultQueue = resultQueue


      def run(self):
        while 1:
          try:
            callable, args, kwds = self.workQueue.get(False)  # get task
            res = callable(*args, **kwds)
            self.resultQueue.put(res)  # put result
          except Queue.Empty:
            break

    class WorkManager:  # 线程池管理,创建
      def __init__(self, num_of_workers=10):
        self.workQueue = Queue.Queue()  # 请求队列
        self.resultQueue = Queue.Queue()  # 输出结果的队列
        self.workers = []
        self._recruitThreads(num_of_workers)

      def _recruitThreads(self, num_of_workers):
        for i in range(num_of_workers):
          worker = Worker(self.workQueue, self.resultQueue)  # 创建工作线程
          self.workers.append(worker)  # 加入到线程队列


      def start(self):
        for w in self.workers:
          w.start()

      def wait_for_complete(self):
        while len(self.workers):
          worker = self.workers.pop()  # 从池中取出一个线程处理请求
          worker.join()
          if worker.isAlive() and not self.workQueue.empty():
            self.workers.append(worker)  # 重新加入线程池中
        print 'All jobs were complete.'


      def add_job(self, callable, *args, **kwds):
        self.workQueue.put((callable, args, kwds))  # 向工作队列中加入请求

      def get_result(self, *args, **kwds):
        return self.resultQueue.get(*args, **kwds)


    def download_file(url):
      #print 'beg download', url
      requests.get(url).text


    def main():
      try:
        num_of_threads = int(sys.argv[1])
      except:
        num_of_threads = 10
      _st = time.time()
      wm = WorkManager(num_of_threads)
      print num_of_threads
      urls = ['http://www.baidu.com'] * 1000
      for i in urls:
        wm.add_job(download_file, i)
      wm.start()
      wm.wait_for_complete()
      print time.time() - _st

    if __name__ == '__main__':
      main()

这三种随便一种都有很高的效率，但是这么跑会给网站服务器不小的压力，尤其是小站点，还是有点节操为好。