Python 爬虫性能相关总结

这里我们通过请求网页例子来一步步理解爬虫性能

当我们有一个列表存放了一些url需要我们获取相关数据，我们首先想到的是循环

简单的循环串行

这一种方法相对来说是最慢的，因为一个一个循环，耗时是最长的，是所有的时间总和代码如下：

import requestsurl_list = [ ’http://www.baidu.com’, ’http://www.pythonsite.com’, ’http://www.cnblogs.com/’]for url in url_list: result = requests.get(url) print(result.text)

通过线程池

通过线程池的方式访问，这样整体的耗时是所有连接里耗时最久的那个，相对循环来说快了很多

import requestsfrom concurrent.futures import ThreadPoolExecutordef fetch_request(url): result = requests.get(url) print(result.text)url_list = [ ’http://www.baidu.com’, ’http://www.bing.com’, ’http://www.cnblogs.com/’]pool = ThreadPoolExecutor(10)for url in url_list: #去线程池中获取一个线程，线程去执行fetch_request方法 pool.submit(fetch_request,url)pool.shutdown(True)

线程池+回调函数

这里定义了一个回调函数callback

from concurrent.futures import ThreadPoolExecutorimport requestsdef fetch_async(url): response = requests.get(url) return responsedef callback(future): print(future.result().text)url_list = [ ’http://www.baidu.com’, ’http://www.bing.com’, ’http://www.cnblogs.com/’]pool = ThreadPoolExecutor(5)for url in url_list: v = pool.submit(fetch_async,url) #这里调用回调函数 v.add_done_callback(callback)pool.shutdown()

通过进程池

通过进程池的方式访问，同样的也是取决于耗时最长的，但是相对于线程来说，进程需要耗费更多的资源，同时这里是访问url时IO操作，所以这里线程池比进程池更好

import requestsfrom concurrent.futures import ProcessPoolExecutordef fetch_request(url): result = requests.get(url) print(result.text)url_list = [ ’http://www.baidu.com’, ’http://www.bing.com’, ’http://www.cnblogs.com/’]pool = ProcessPoolExecutor(10)for url in url_list: #去进程池中获取一个线程，子进程程去执行fetch_request方法 pool.submit(fetch_request,url)pool.shutdown(True)

进程池+回调函数

这种方式和线程+回调函数的效果是一样的，相对来说开进程比开线程浪费资源

from concurrent.futures import ProcessPoolExecutorimport requestsdef fetch_async(url): response = requests.get(url) return responsedef callback(future): print(future.result().text)url_list = [ ’http://www.baidu.com’, ’http://www.bing.com’, ’http://www.cnblogs.com/’]pool = ProcessPoolExecutor(5)for url in url_list: v = pool.submit(fetch_async, url) # 这里调用回调函数 v.add_done_callback(callback)pool.shutdown()

主流的单线程实现并发的几种方式

下面分别是这四种代码的实现例子：

asyncio例子1：

import asyncio@asyncio.coroutine #通过这个装饰器装饰def func1(): print(’before...func1......’) # 这里必须用yield from，并且这里必须是asyncio.sleep不能是time.sleep yield from asyncio.sleep(2) print(’end...func1......’)tasks = [func1(), func1()]loop = asyncio.get_event_loop()loop.run_until_complete(asyncio.gather(*tasks))loop.close()

上述的效果是同时会打印两个before的内容，然后等待2秒打印end内容这里asyncio并没有提供我们发送http请求的方法，但是我们可以在yield from这里构造http请求的方法。

asyncio例子2：

import asyncio@asyncio.coroutinedef fetch_async(host, url=’/’): print('----',host, url) reader, writer = yield from asyncio.open_connection(host, 80) #构造请求头内容 request_header_content = '''GET %s HTTP/1.0rnHost: %srnrn''' % (url, host,) request_header_content = bytes(request_header_content, encoding=’utf-8’) #发送请求 writer.write(request_header_content) yield from writer.drain() text = yield from reader.read() print(host, url, text) writer.close()tasks = [ fetch_async(’www.cnblogs.com’, ’/zhaof/’), fetch_async(’dig.chouti.com’, ’/pic/show?nid=4073644713430508&lid=10273091’)]loop = asyncio.get_event_loop()results = loop.run_until_complete(asyncio.gather(*tasks))loop.close()

asyncio + aiohttp 代码例子：

import aiohttpimport asyncio@asyncio.coroutinedef fetch_async(url): print(url) response = yield from aiohttp.request(’GET’, url) print(url, response) response.close()tasks = [fetch_async(’http://baidu.com/’), fetch_async(’http://www.chouti.com/’)]event_loop = asyncio.get_event_loop()results = event_loop.run_until_complete(asyncio.gather(*tasks))event_loop.close()

asyncio+requests代码例子

import asyncioimport requests@asyncio.coroutinedef fetch_async(func, *args): loop = asyncio.get_event_loop() future = loop.run_in_executor(None, func, *args) response = yield from future print(response.url, response.content)tasks = [ fetch_async(requests.get, ’http://www.cnblogs.com/wupeiqi/’), fetch_async(requests.get, ’http://dig.chouti.com/pic/show?nid=4073644713430508&lid=10273091’)]loop = asyncio.get_event_loop()results = loop.run_until_complete(asyncio.gather(*tasks))loop.close()

gevent+requests代码例子

import geventimport requestsfrom gevent import monkeymonkey.patch_all()def fetch_async(method, url, req_kwargs): print(method, url, req_kwargs) response = requests.request(method=method, url=url, **req_kwargs) print(response.url, response.content)# ##### 发送请求 #####gevent.joinall([ gevent.spawn(fetch_async, method=’get’, url=’https://www.python.org/’, req_kwargs={}), gevent.spawn(fetch_async, method=’get’, url=’https://www.yahoo.com/’, req_kwargs={}), gevent.spawn(fetch_async, method=’get’, url=’https://github.com/’, req_kwargs={}),])# ##### 发送请求（协程池控制最大协程数量） ###### from gevent.pool import Pool# pool = Pool(None)# gevent.joinall([# pool.spawn(fetch_async, method=’get’, url=’https://www.python.org/’, req_kwargs={}),# pool.spawn(fetch_async, method=’get’, url=’https://www.yahoo.com/’, req_kwargs={}),# pool.spawn(fetch_async, method=’get’, url=’https://www.github.com/’, req_kwargs={}),# ])

grequests代码例子这个是讲requests+gevent进行了封装

import grequestsrequest_list = [ grequests.get(’http://httpbin.org/delay/1’, timeout=0.001), grequests.get(’http://fakedomain/’), grequests.get(’http://httpbin.org/status/500’)]# ##### 执行并获取响应列表 ###### response_list = grequests.map(request_list)# print(response_list)# ##### 执行并获取响应列表（处理异常） ###### def exception_handler(request, exception):# print(request,exception)# print('Request failed')# response_list = grequests.map(request_list, exception_handler=exception_handler)# print(response_list)

twisted代码例子

#getPage相当于requets模块，defer特殊的返回值，rector是做事件循环from twisted.web.client import getPage, deferfrom twisted.internet import reactordef all_done(arg): reactor.stop()def callback(contents): print(contents)deferred_list = []url_list = [’http://www.bing.com’, ’http://www.baidu.com’, ]for url in url_list: deferred = getPage(bytes(url, encoding=’utf8’)) deferred.addCallback(callback) deferred_list.append(deferred)#这里就是进就行一种检测，判断所有的请求知否执行完毕dlist = defer.DeferredList(deferred_list)dlist.addBoth(all_done)reactor.run()

tornado代码例子

from tornado.httpclient import AsyncHTTPClientfrom tornado.httpclient import HTTPRequestfrom tornado import ioloopdef handle_response(response): ''' 处理返回值内容（需要维护计数器，来停止IO循环），调用 ioloop.IOLoop.current().stop() :param response: :return: ''' if response.error: print('Error:', response.error) else: print(response.body)def func(): url_list = [ ’http://www.baidu.com’, ’http://www.bing.com’, ] for url in url_list: print(url) http_client = AsyncHTTPClient() http_client.fetch(HTTPRequest(url), handle_response)ioloop.IOLoop.current().add_callback(func)ioloop.IOLoop.current().start()

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