爬虫笔记八——Scrapy实战项目
（案例一）手机App抓包爬虫
1. items.py
import scrapy class DouyuspiderItem(scrapy.Item): # 存储照片的名字 nickName = scrapy.Field() # 照片的url路径 imageUrl = scrapy.Field() # 照片保存在本地的路径 imagePath = scrapy.Field()
2. spiders/douyu.py
# -*- coding: utf-8 -*- import scrapy from douyuSpider.items import DouyuspiderItem import json class DouyuSpider(scrapy.Spider): name = 'douyu' allowed_domains = ['capi.douyucdn.cn'] offset = 0 url = "http://capi.douyucdn.cn/api/v1/getVerticalRoom?limit=20&offset=" start_urls = [url + str(offset)] def parse(self, response): data = json.loads(response.body)["data"] for each in data: item = DouyuspiderItem() item["nickName"] = each["nickname"] item["imageUrl"] = each["vertical_src"] yield item self.offset += 20 nextUrl = re.sub('offset=\d+', 'offset='+str(self.offset), response.url) yield scrapy.Request(nextUrl, callback=self.parse)
3. 设置setting.py
DEFAULT_REQUEST_HEADERS = { 'User-Agent': 'News 6.6.5 rv:6.6.5.03 (iPhone; iOS 11.2.6; zh_CN) Cronet' } ITEM_PIPELINES = { 'douyuSpider.pipelines.DouyuspiderPipeline': 300, } IMAGES_STORE = 'E:\Python\Spider\day05\douyuSpider\images' # 日志文件名和处理等级 LOG_FILE = "douyu.log" LOG_LEVEL = "DEBUG"
4. pipelines.py
# -*- coding: utf-8 -*- import scrapy from scrapy.exceptions import DropItem from scrapy.utils.project import get_project_settings from scrapy.pipelines.images import ImagesPipeline import os class DouyuspiderPipeline(ImagesPipeline): IMAGES_STORE = get_project_settings().get("IMAGES_STORE") # 根据图片的url生成图片的Request def get_media_requests(self, item, info): image_url = item["imageUrl"] yield scrapy.Request(image_url) # 图片下载完毕之后，处理结果会以二元组的方式作为results参数传递给item_completed函数 # 这个二元组定义如下：(success, image_info_or_failure)，第一个元素表示图片是否下载成功，第二个元素是一个字典 # 字典的含义如下：{'url': 图片的url, 'path': 图片的存储地址，跟IMAGE_STORE相关, 'checksum': 图片的内容hash} def item_completed(self, results, item, info): # 如果图片下载成功，则获取图片的存储地址 image_path = [x["path"] for ok, x in results if ok] #print image_path if not image_path: raise DropItem("Item contains no images") # 修改图片的存储地址： os.rename(self.IMAGES_STORE + "\\" + image_path[0], self.IMAGES_STORE + "\\" + item["nickName"] + ".jpg") item["imagePath"] = self.IMAGES_STORE + "\\" + item["nickName"] #print item["imagePath"] return item
5. 运行
在项目根目录下新建main.py文件,用于调试 from scrapy import cmdline cmdline.execute("scrapy crawl douyu".split()) 执行程序 python main.py
5.2. （案例二）阳光热线问政平台爬虫
阳光热线问政平台
http://wz.sun0769.com/index.php/question/questionType?type=4
爬取投诉帖子的编号、帖子的url、帖子的标题，和帖子里的内容。
import scrapy class DongguanspiderItem(scrapy.Item): # 每个帖子的标题 title = scrapy.Field() # 每个帖子的编号 number = scrapy.Field() # 每个帖子的文字内容 content = scrapy.Field() # 每个帖子的url url = scrapy.Field()
spiders/sunwz.py
# -*- coding: utf-8 -*- import scrapy from dongguanSpider.items import DongguanspiderItem class DongguanSpider(scrapy.Spider): name = 'dongguan' allowed_domains = ['sun0769.com'] url = 'http://wz.sun0769.com/index.php/question/questionType?type=4&page=' headers = {"User-Agent": "Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; Trident/5.0;"} offset = 0 start_urls = [url + str(offset)] # 解析每个页面的响应 def parse(self, response): # 获取每页帖子的链接列表 links = response.xpath('//div[@class="greyframe"]/table//td/a[2]/@href').extract() for link in links: # 获取每个帖子的Request请求 yield scrapy.Request(link, headers=self.headers, callback=self.parse_item) # 设置页码终止条件为最后一页的page值， if self.offset <= 88560: self.offset += 30 # 获取每页的Request请求 yield scrapy.Request(self.url + str(self.offset), headers=self.headers, callback=self.parse) # 解析页面里的每个帖子的响应 def parse_item(self, response): item = DongguanspiderItem() titleList = response.xpath('//div[contains(@class, "pagecenter p3")]//strong/text()')[0].extract().strip().split() # 帖子的标题 item['title'] = titleList[0][3:] # 帖子的编号 item['number'] = titleList[1][3:] # 帖子的内容，先取出有图片帖子的内容，再取出没有图片帖子的内容 content = response.xpath('//div[@class="contentext"]/text()').extract() if len(content) == 0: content = response.xpath('//div[@class="c1 text14_2"]/text()').extract() item['content'] = "".join(content).strip() else: item['content'] = "".join(content).strip() # 帖子的链接地址 item['url'] = response.url yield item
# -*- coding: utf-8 -*- import scrapy from scrapy.linkextractors import LinkExtractor from scrapy.spiders import CrawlSpider, Rule from dongguanSpider.items import DongguanspiderItem class SunSpider(CrawlSpider): name = 'sun' allowed_domains = ['sun0769.com'] start_urls = ['http://wz.sun0769.com/index.php/question/questionType?type=4&page='] # 每页链接的匹配规则 pageLink = LinkExtractor(allow=('type=4')) # 每个帖子链接的匹配规则 contentLink = LinkExtractor(allow=r'/html/question/\d+/\d+.shtml') rules = ( Rule(pageLink), Rule(contentLink, callback='parse_item') ) def parse_item(self, response): item = DongguanspiderItem() titleList = response.xpath('//div[contains(@class, "pagecenter p3")]//strong/text()')[ 0].extract().strip().split() # 帖子的标题 item['title'] = titleList[0][3:] # 帖子的编号 item['number'] = titleList[1][3:] # 帖子的内容，先取出有图片帖子的内容，再取出没有图片帖子的内容 content = response.xpath('//div[@class="contentext"]/text()').extract() if len(content) == 0: content = response.xpath('//div[@class="c1 text14_2"]/text()').extract() # content为列表，通过join方法拼接字符串，并去除首尾空格 item['content'] = "".join(content).strip() else: item['content'] = "".join(content).strip() # 帖子的链接地址 item['url'] = response.url yield item
pipelines.py
# -*- coding: utf-8 -*- # 文件处理类库，可以指定编码格式 import codecs import json class DongguanspiderPipeline(object): def __init__(self): # 创建一个可写文件，指定编码格式为utf-8 self.filename = codecs.open('dongguan.json', 'w', encoding='utf-8') def process_item(self, item, spider): content = json.dumps(dict(item), ensure_ascii=False) + '\n' self.filename.write(content) return item def spider_closed(self, spider): self.filename.close()
settings.py
ITEM_PIPELINES = { 'dongguanSpider.pipelines.DongguanspiderPipeline': 300, } # 日志文件名和处理等级 LOG_FILE = "dg.log" LOG_LEVEL = "DEBUG"
在项目根目录下新建main.py文件,用于调试 from scrapy import cmdline cmdline.execute("scrapy crawl sun".split()) 执行程序 py2 main.py
5.3. （案例三）新浪网页分类资讯爬虫
爬取新浪网导航页所有分类下所有大类、小类、小类里的子链接，以及子链接页面的新闻内容。
效果演示图：
items.py
import scrapy class SinaspiderItem(scrapy.Item): # 大类的标题 parentTitle = scrapy.Field() # 大类的url parentUrl = scrapy.Field() # 小类的标题 subTitle = scrapy.Field() # 小类的url subUrl = scrapy.Field() # 小类的存储路径 subDir = scrapy.Field() # 文章的url fileUrl = scrapy.Field() # 文章的标题 title = scrapy.Field() # 文章的内容 content = scrapy.Field() spiders/sina.py # -*- coding: utf-8 -*- import scrapy from sinaSpider.items import SinaspiderItem import os class SinaSpider(scrapy.Spider): name = 'sina' allowed_domains = ['sina.com.cn'] start_urls = ['http://news.sina.com.cn/guide/'] # 解析首页 def parse(self, response): # 获取大类的标题列表 parentTitleList = response.xpath('//div[@id="tab01"]//h3/a/text()').extract() # 获取大类的url列表 parentUrlList = response.xpath('//div[@id="tab01"]//h3/a/@href').extract() # 遍历大类列表 for i in range(len(parentTitleList)): # 根据大类的标题名新建目录 parentDir = '.\\Data\\' + parentTitleList[i] if not os.path.exists(parentDir): os.makedirs(parentDir) # 获取每个大类下的小类的标题列表 subTitleList = response.xpath('//div[@id="tab01"]/div[{}]//li/a/text()'.format(i+1)).extract() # 获取每个大类下的小类的url列表 subUrlList = response.xpath('//div[@id="tab01"]/div[{}]//li/a/@href'.format(i+1)).extract() # 遍历某一个大类下的小类列表 for j in range(len(subTitleList)): # 根据小类的标题名新建目录 subDir = parentDir + '\\'+ subTitleList[j] if not os.path.exists(subDir): os.makedirs(subDir) item = SinaspiderItem() item['parentTitle'] = parentTitleList[i] item['parentUrl'] = parentUrlList[i] item['subTitle'] = subTitleList[j] item['subUrl'] = subUrlList[j] item['subDir'] = subDir # 发送每个小类的Request请求，在Request中加入meta，即可将meta传递给response作为参数给回调函数使用 yield scrapy.Request(item['subUrl'], meta={'meta_1': item}, callback=self.parse_news) # 解析每个小类的url，爬取每个小类下的文章标题和链接 def parse_news(self, response): # 获取Request请求发送的meta_1参数 meta_1 = response.meta['meta_1'] fileUrlList = response.xpath('//a/@href').re(r'.*\d+\.shtml') for i in range(len(fileUrlList)): item = SinaspiderItem() item['parentTitle'] = meta_1['parentTitle'] item['parentUrl'] = meta_1['parentUrl'] item['subTitle'] = meta_1['subTitle'] item['subUrl'] = meta_1['subUrl'] item['subDir'] = meta_1['subDir'] item['fileUrl'] = fileUrlList[i] # 发送每篇新闻的Request请求，在Request中加入meta，向回调函数parse_content传递参数meta2 yield scrapy.Request(item['fileUrl'], meta={'meta_2': item}, callback=self.parse_content) # 解析每个新闻页，获取新闻标题和内容 def parse_content(self, response): # 获取Request请求发送的meta_2参数 item = response.meta['meta_2'] # 获取新闻的标题 title = response.xpath('//h1[@class="main-title"]/text()')[0].extract() content = '' contentList = response.xpath('//div[@class="article"]/p/text()').extract() # 获取新闻的内容 for content_one in contentList: content += content_one item['title'] = title item['content'] = content yield item
pipelines.py
class SinaspiderPipeline(object): def process_item(self, item, spider): fileUrl = item['fileUrl'] # 根据新闻链接地址命名存储新闻的文件名 fileName = item['subDir'] + '\\' + fileUrl[7:-6].replace('/', '_') + '.txt' with open(fileName, 'w') as f: f.write(item['content'].encode('utf-8')) return item
settings.py
USER_AGENT = "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.99 Safari/537.36" ITEM_PIPELINES = { 'sinaSpider.pipelines.SinaspiderPipeline': 300, } # 日志文件名和处理等级 LOG_FILE = "sina.log" LOG_LEVEL = "DEBUG"
在项目根目录下新建main.py文件,用于调试 from scrapy import cmdline cmdline.execute("scrapy crawl sina".split()) 执行程序 py2 main.py
