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  • python scrapy简单爬虫记录(实现简单爬取知乎)

    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 

    如果想要不喜欢用-o来导出数据,可以让scrapy自己保存数据,编辑pipelines

    import json
    import codecs
    
    
    class xxxPipeline(object):
        def __init__(self):
            self.file = codecs.open('xxx.csv', 'w', encoding='utf-8')
    
        def process_item(self, item, spider):
            datas = json.dumps(dict(item), ensure_ascii=False) + '
    '
            self.file.write(datas)
            return item
    
        def spider_closed(self, spider):
            self.file.close()

    然后在setting中启用

    ITEM_PIPELINES = {
       'tutorial.pipelines.xxxPipeline': 300, 
    }

    把对应的pipeline修改成自己的,最后那个数字表示启动顺序,越低顺序越快。

    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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  • 原文地址:https://www.cnblogs.com/lgh344902118/p/7027857.html
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