python scrapy简单爬虫记录(实现简单爬取知乎)
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之前写了个scrapy的学习记录,只是简单的介绍了下scrapy的一些内容,并没有实际的例子,现在开始记录例子
使用的环境是python2.7, scrapy1.2.0
首先创建项目
在要建立项目的目录下执行命令scrapy startproject tutorial
scrapy会帮你建立好项目,接着创建蜘蛛scrapy genspider zhuhuSpider zhihu.com
当前的文件结构是
--tutorial --spiders --__init__.py --zhihuSpider.py --__init__.py --items.py --pipelines.py
--settings.py
主要用到的文件有三个zhihuspider.py,items.py,settings.py
zhihuspider是用来写爬行的蜘蛛的,items用来保存爬取的数据,settings修改配置
# -*- coding: utf-8 -*- from scrapy.spiders import Spider from scrapy.selector import Selector from tutorial.items import ZhihuItem #蜘蛛的主体 class ZhihuSpider(Spider): name = "zhihuSpider" allowed_domains = [‘zhihu.com‘] start_urls = []
#获取要爬取的url,我把关键词放在zhihu.txt中 def start_requests(self): url_head = ‘https://www.zhihu.com/search?type=content&q=‘ with open(‘zhihu.txt‘, ‘r‘) as f: datas = f.readlines() for data in datas: url = url_head+data print url self.start_urls.append(url) for url in self.start_urls: yield self.make_requests_from_url(url)
#对返回的response进行解析,该步骤可以配合浏览器进行xpath的查找 def parse(self, response):
#删除所有的<em> response = response.replace(body=response.body.replace(‘<em>‘, ‘‘)) hxs = Selector(response) contents = hxs.xpath(‘//*[@class="zu-main-content"]//*[contains(@class, "list")]‘) item = ZhihuItem() for content in contents: item[‘search_title‘] = content.xpath(‘//*[@class="title"]/a/text()‘).extract() item[‘search_title_link‘] = content.xpath(‘//*[@class="title"]/a/@href‘).extract() item[‘search_answer‘] = content.xpath(‘//*[@class="content"]//*[contains(@class, "entry-content")]//*[contains(@class, "summary")]/text()‘).extract() item[‘search_answer_link‘] = content.xpath(‘//*[@class="content"]//*[contains(@class, "entry-content")]//*[contains(@class, "summary")]/a/@href‘).extract() item[‘search_answer_writer‘] = content.xpath(‘//*[@class="content"]//*[contains(@class, "entry-meta")]//a[contains(@class, "author")]/text()‘).extract() print item yield item
from scrapy.item import Item, Field class ZhihuItem(Item): search_title = Field() search_title_link = Field() search_answer = Field() search_answer_link = Field() search_answer_writer = Field()
该items文件存放数据
因为知乎对爬虫有限制,所以需要加入反爬虫机制
基本上有4种,添加useragent,添加代理,禁用cookie以及爬取时间限制
在当前项目下添加python包middlewares,和setttings在同一个目录下,下面只有一个__init__.py文件,新建一个RandomUserAgent.py文件
#coding:utf-8 import random class RandomUserAgent(object): def __init__(self, agents): self.agents = agents @classmethod def from_crawler(cls, crawler): return cls(crawler.settings.getlist(‘USER_AGENTS‘)) def process_request(self, request, spider): request.headers.setdefault(‘User-Agent‘, random.choice(self.agents))
简单的加入user-agent
最后在settings中设置
DOWNLOADER_MIDDLEWARES = { # ‘tutorial.middlewares.MyCustomDownloaderMiddleware‘: 543, ‘tutorial.middlewares.RandomUserAgent.RandomUserAgent‘: 1, } USER_AGENTS = [ "Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; AcooBrowser; .NET CLR 1.1.4322; .NET CLR 2.0.50727)", "Mozilla/4.0 (compatible; MSIE 7.0; Windows NT 6.0; Acoo Browser; SLCC1; .NET CLR 2.0.50727; Media Center PC 5.0; .NET CLR 3.0.04506)", "Mozilla/4.0 (compatible; MSIE 7.0; AOL 9.5; AOLBuild 4337.35; Windows NT 5.1; .NET CLR 1.1.4322; .NET CLR 2.0.50727)", "Mozilla/5.0 (Windows; U; MSIE 9.0; Windows NT 9.0; en-US)", "Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; Win64; x64; Trident/5.0; .NET CLR 3.5.30729; .NET CLR 3.0.30729; .NET CLR 2.0.50727; Media Center PC 6.0)", "Mozilla/5.0 (compatible; MSIE 8.0; Windows NT 6.0; Trident/4.0; WOW64; Trident/4.0; SLCC2; .NET CLR 2.0.50727; .NET CLR 3.5.30729; .NET CLR 3.0.30729; .NET CLR 1.0.3705; .NET CLR 1.1.4322)", "Mozilla/4.0 (compatible; MSIE 7.0b; Windows NT 5.2; .NET CLR 1.1.4322; .NET CLR 2.0.50727; InfoPath.2; .NET CLR 3.0.04506.30)", "Mozilla/5.0 (Windows; U; Windows NT 5.1; zh-CN) AppleWebKit/523.15 (KHTML, like Gecko, Safari/419.3) Arora/0.3 (Change: 287 c9dfb30)", "Mozilla/5.0 (X11; U; Linux; en-US) AppleWebKit/527+ (KHTML, like Gecko, Safari/419.3) Arora/0.6", "Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US; rv:1.8.1.2pre) Gecko/20070215 K-Ninja/2.1.1", "Mozilla/5.0 (Windows; U; Windows NT 5.1; zh-CN; rv:1.9) Gecko/20080705 Firefox/3.0 Kapiko/3.0", "Mozilla/5.0 (X11; Linux i686; U;) Gecko/20070322 Kazehakase/0.4.5", "Mozilla/5.0 (X11; U; Linux i686; en-US; rv:1.9.0.8) Gecko Fedora/1.9.0.8-1.fc10 Kazehakase/0.5.6", "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/535.11 (KHTML, like Gecko) Chrome/17.0.963.56 Safari/535.11", "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_7_3) AppleWebKit/535.20 (KHTML, like Gecko) Chrome/19.0.1036.7 Safari/535.20", "Opera/9.80 (Macintosh; Intel Mac OS X 10.6.8; U; fr) Presto/2.9.168 Version/11.52", "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.11 (KHTML, like Gecko) Chrome/20.0.1132.11 TaoBrowser/2.0 Safari/536.11", "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/21.0.1180.71 Safari/537.1 LBBROWSER", "Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; WOW64; Trident/5.0; SLCC2; .NET CLR 2.0.50727; .NET CLR 3.5.30729; .NET CLR 3.0.30729; Media Center PC 6.0; .NET4.0C; .NET4.0E; LBBROWSER)", "Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; QQDownload 732; .NET4.0C; .NET4.0E; LBBROWSER)", "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/535.11 (KHTML, like Gecko) Chrome/17.0.963.84 Safari/535.11 LBBROWSER", "Mozilla/4.0 (compatible; MSIE 7.0; Windows NT 6.1; WOW64; Trident/5.0; SLCC2; .NET CLR 2.0.50727; .NET CLR 3.5.30729; .NET CLR 3.0.30729; Media Center PC 6.0; .NET4.0C; .NET4.0E)", "Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; WOW64; Trident/5.0; SLCC2; .NET CLR 2.0.50727; .NET CLR 3.5.30729; .NET CLR 3.0.30729; Media Center PC 6.0; .NET4.0C; .NET4.0E; QQBrowser/7.0.3698.400)", "Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; QQDownload 732; .NET4.0C; .NET4.0E)", "Mozilla/4.0 (compatible; MSIE 7.0; Windows NT 5.1; Trident/4.0; SV1; QQDownload 732; .NET4.0C; .NET4.0E; 360SE)", "Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; QQDownload 732; .NET4.0C; .NET4.0E)", "Mozilla/4.0 (compatible; MSIE 7.0; Windows NT 6.1; WOW64; Trident/5.0; SLCC2; .NET CLR 2.0.50727; .NET CLR 3.5.30729; .NET CLR 3.0.30729; Media Center PC 6.0; .NET4.0C; .NET4.0E)", "Mozilla/5.0 (Windows NT 5.1) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/21.0.1180.89 Safari/537.1", "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/21.0.1180.89 Safari/537.1", "Mozilla/5.0 (iPad; U; CPU OS 4_2_1 like Mac OS X; zh-cn) AppleWebKit/533.17.9 (KHTML, like Gecko) Version/5.0.2 Mobile/8C148 Safari/6533.18.5", "Mozilla/5.0 (Windows NT 6.1; Win64; x64; rv:2.0b13pre) Gecko/20110307 Firefox/4.0b13pre", "Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:16.0) Gecko/20100101 Firefox/16.0", "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.11 (KHTML, like Gecko) Chrome/23.0.1271.64 Safari/537.11", "Mozilla/5.0 (X11; U; Linux x86_64; zh-CN; rv:1.9.2.10) Gecko/20100922 Ubuntu/10.10 (maverick) Firefox/3.6.10" ] COOKIES_ENABLED=False DOWNLOAD_DELAY=3
整个项目完成了,scrapy crawl zhihuSpider -o zhihu.json导出数据。就是这么简单
最后说一句,爬取数据时要注意对爬取时间的设置,别给服务器造成负担
项目已经提交到github上地址是https://github.com/lin344902118/doubanSpider.git
里面还有个对豆瓣的爬虫
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