爬虫(二)

性能相关

在编写爬虫时,性能的消耗主要在IO请求中,当单进程单线程模式下请求URL时必然会引起等待,从而使得请求整体变慢。

import requests

def fetch_async(url):
    response = requests.get(url)
    return response


url_list = ['http://www.github.com', 'http://www.bing.com']

for url in url_list:
    fetch_async(url)
1.同步执行
from concurrent.futures import ThreadPoolExecutor
import requests


def fetch_async(url):
    response = requests.get(url)
    return response


url_list = ['http://www.github.com', 'http://www.bing.com']
pool = ThreadPoolExecutor(5)
for url in url_list:
    pool.submit(fetch_async, url)
pool.shutdown(wait=True)
2.多线程执行
from concurrent.futures import ThreadPoolExecutor
import requests

def fetch_async(url):
    response = requests.get(url)
    return response


def callback(future):
    print(future.result())


url_list = ['http://www.github.com', 'http://www.bing.com']
pool = ThreadPoolExecutor(5)
for url in url_list:
    v = pool.submit(fetch_async, url)
    v.add_done_callback(callback)
pool.shutdown(wait=True)
2.多线程+回调函数执行
from concurrent.futures import ProcessPoolExecutor
import requests

def fetch_async(url):
    response = requests.get(url)
    return response


url_list = ['http://www.github.com', 'http://www.bing.com']
pool = ProcessPoolExecutor(5)
for url in url_list:
    pool.submit(fetch_async, url)
pool.shutdown(wait=True)
3.多进程执行
from concurrent.futures import ProcessPoolExecutor
import requests


def fetch_async(url):
    response = requests.get(url)
    return response


def callback(future):
    print(future.result())


url_list = ['http://www.github.com', 'http://www.bing.com']
pool = ProcessPoolExecutor(5)
for url in url_list:
    v = pool.submit(fetch_async, url)
    v.add_done_callback(callback)
pool.shutdown(wait=True)
3.多进程+回调函数执行

通过上述代码均可以完成对请求性能的提高,对于多线程和多进行的缺点是在IO阻塞时会造成了线程和进程的浪费,所以异步IO应当是首选

 

 

自定义异步io请求模块

原理:非阻塞socket + io多路复用

import socket
import select
class HttpRequest():
    def __init__(self,sk,host,callback):
        self.socket = sk
        self.host = host
        self.callback = callback  #对sk进行host,对应回调函数的封装
    def fileno(self):
        return self.socket.fileno()


class AsyncRequest:
    def __init__(self):
        self.conn = []
        self.connection = []

    def add_request(self,host,callback):
        try:
            sk = socket.socket()
            sk.setblocking(0)    #非阻塞io socket 只管发送连接请求
            sk.connect((host,80))
        except BlockingIOError as e:  #链接无响应 就会报错
            pass
        request = HttpRequest(sk,host,callback)
        self.conn.append(request)
        self.connection.append(request)

    def run(self):
        while True:
            rlist,wlist,elist=select.select(self.conn,self.connection,[],0.05)  #监听socket对象
            # rlist 监听数据
            # wlist 监听socket链接响应
            # 不一定是socket对象,只要该对象包含fileno方法,并且返回一个文件描述符即可,所以可以是封装了socket(这才是重点)以及其他参数的对象
            for w in wlist:
                print('%s-链接响应'%(w.host))
                tpl = "GET / HTTP/1.0\r\nHost:%s\r\n\r\n"%(w.host) #构造http请求头
                w.socket.send(bytes(tpl,encoding='utf8'))  #开始发送http请求
                self.connection.remove(w)  #从监听中删除

            for r in rlist:
                print('%s-接收数据---'%(r.host))
                recv_data = bytes()
                while True: #循环接收数据
                    try:
                        chunck = r.socket.recv(8096)
                        recv_data += chunck
                    except Exception as e: # 非阻塞接收数据,没有数据会报错(表示数据接收完成)
                        break
                    #数据接收完成,就可以使用回调函数进行处理
                r.callback(recv_data)
                r.socket.close()
                self.conn.remove(r)
                #接收数据的监听对象列表为空时,结束整个监听
            if len(self.conn) == 0:
                 break


def f1(data):
    print('文件写入')
def f2(data):
    print('数据库写入')


url_list = [
    {'host':'www.baidu.com','callback':f1},
    {'host':'www.qq.com','callback':f1},
    {'host':'cn.bing.com','callback':f2}
]
req = AsyncRequest()
for item in url_list:
    req.add_request(item['host'],item['callback']) #创建socket对象,发送链接
req.run() #开始监听 + 后续数据操作 + 数据回调函数处理
自定义异步IO请求模块

 

Scrapy

链接:http://scrapy-chs.readthedocs.io/zh_CN/latest/index.html

#centos
pip3 install Incremental -i http://pypi.douban.com/simple --trusted-host pypi.douban.com
pip3 install -i http://pypi.douban.com/simple/ Twisted  --trusted-host pypi.douban.com  pip3 install -i http://pypi.douban.com/simple/ scrapy --trusted-host pypi.douban.com #windows 下载Twisted-17.1.0-cp35-cp35m-win_amd64.whl pip3 install Twisted-17.1.0-cp35-cp35m-win_amd64.whl pip3 install scrapy
安装pywin32

 

posted @ 2017-05-16 23:54  chenzhuo  阅读(99)  评论(0编辑  收藏  举报