如下所示：
# requests模块来请求页面
# lxml模块的html构建selector选择器(格式化响应response)
# from lxml import html
# import requests
# response = requests.get(url).content
# selector = html.formatstring(response)
# hrefs = selector.xpath('/html/body//div[@class='feed-item _j_feed_item']/a/@href')
# 以url = 'https://www.mafengwo.cn/gonglve/ziyouxing/2033.html'为例子
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# python 2.7import requestsfrom lxml import htmlimport os |
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# 获取首页中子页的url链接def get_page_urls(url): response = requests.get(url).content # 通过lxml的html来构建选择器 selector = html.fromstring(response) urls = [] for i in selector.xpath("/html/body//div[@class='feed-item _j_feed_item']/a/@href"): urls.append(i) return urls |
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# get title from a child's html(div[@class='title'])def get_page_a_title(url): '''url is ziyouxing's a@href''' response = requests.get(url).content selector = html.fromstring(response) # get xpath by chrome's tool --> /html/body//div[@class='title']/text() a_title = selector.xpath("/html/body//div[@class='title']/text()") return a_title |
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# 获取页面选择器(通过lxml的html构建)def get_selector(url): response = requests.get(url).content selector = html.fromstring(response) return selector |
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# 通过chrome的开发者工具分析html页面结构后发现，我们需要获取的文本内容主要显示在div[@class='l-topic']和div[@class='p-section']中 |
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# 获取所需的文本内容 def get_page_content(selector): # /html/body/div[2]/div[2]/div[1]/div[@class='l-topic']/p/text() page_title = selector.xpath("//div[@class='l-topic']/p/text()") # /html/body/div[2]/div[2]/div[1]/div[2]/div[15]/div[@class='p-section']/text() page_content = selector.xpath("//div[@class='p-section']/text()") return page_title,page_content |
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# 获取页面中的图片url地址def get_image_urls(selector): imagesrcs = selector.xpath("//img[@class='_j_lazyload']/@src") return imagesrcs |
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# 获取图片的标题def get_image_title(selector, num) # num 是从2开始的 url = "/html/body/div[2]/div[2]/div[1]/div[2]/div["+num+"]/span[@class='img-an']/text()" if selector.xpath(url) is not None: image_title = selector.xpath(url) else: image_title = "map"+str(num) # 没有就起一个 return image_title |
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# 下载图片def downloadimages(selector,number): '''number是用来计数的''' urls = get_image_urls() num = 2 amount = len(urls) for url in urls: image_title = get_image_title(selector, num) filename = "/home/WorkSpace/tour/words/result"+number+"/+"image_title+".jpg" if not os.path.exists(filename): os.makedirs(filename) print('downloading %s image %s' %(number, image_title)) with open(filename, 'wb') as f: f.write(requests.get(url).content) num += 1 print "已经下载了%s张图" %num |
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# 入口，启动并把获取的数据存入文件中if __name__ =='__main__': url = 'https://www.mafengwo.cn/gonglve/ziyouxing/2033.html' urls = get_page_urls(url) # turn to get response from html number = 1 for i in urls: selector = get_selector(i) # download images downloadimages(selector,number) # get text and write into a file page_title, page_content = get_page_content(selector) result = page_title+'\n'+page_content+'\n\n' path = "/home/WorkSpace/tour/words/result"+num+"/" if not os.path.exists(filename): os.makedirs(filename) filename = path + "num"+".txt" with open(filename,'wb') as f: f.write(result) print result |
到此就结束了该爬虫，爬取页面前一定要认真分析html结构，有些页面是由js生成，该页面比较简单，没涉及到js的处理，日后的随笔中会有相关分享
以上这篇requests和lxml实现爬虫的方法就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持服务器之家。
