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 requests url_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 requests from concurrent.futures import ThreadPoolExecutor def 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 ThreadPoolExecutor import requests def fetch_async(url): response = requests.get(url) return response def 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 requests from concurrent.futures import ProcessPoolExecutor def 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 ProcessPoolExecutor import requests def fetch_async(url): response = requests.get(url) return response def 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
- asyncio
- gevent
- Twisted
- Tornado
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.coroutine def 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/1.0\r\nHost: %s\r\n\r\n""" % (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 aiohttp import asyncio @asyncio.coroutine def 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 asyncio import requests @asyncio.coroutine def 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 gevent import requests from gevent import monkey monkey.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 grequests request_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, defer from twisted.internet import reactor def 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 AsyncHTTPClient from tornado.httpclient import HTTPRequest from tornado import ioloop def 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()
所有的努力都值得期许，每一份梦想都应该灌溉！
