我們的這個爬蟲設計來爬取京東圖書(jd.com)。
scrapy框架相信大家比較了解了。里面有很多復雜的機制,超出本文的范圍。
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京東爬蟲軟件。1、爬蟲spider
tips:
1、xpath的語法比較坑,但是你可以在chrome上裝一個xpath helper,輕松幫你搞定xpath正則表達式
2、動態內容,比如價格等是不能爬取到的
java 爬蟲框架?3、如本代碼中,評論爬取部分代碼涉及xpath對象的鏈式調用,可以參考
# -*- coding: utf-8 -*-# import scrapy # 可以用這句代替下面三句,但不推薦 from scrapy.spiders import Spider from scrapy.selector import Selector from scrapy import Request from scrapy.linkextractors.lxmlhtml import LxmlLinkExtractorfrom jdbook.items import JDBookItem # 如果報錯是pyCharm對目錄理解錯誤的原因,不影響class JDBookSpider(Spider):name = "jdbook"allowed_domains = ["jd.com"] # 允許爬取的域名,非此域名的網頁不會爬取start_urls = [# 起始url,這里設置為從最大tid開始,向0的方向迭代"http://item.jd.com/11678007.html"]# 用來保持登錄狀態,可把chrome上拷貝下來的字符串形式cookie轉化成字典形式,粘貼到此處cookies = {}# 發送給服務器的http頭信息,有的網站需要偽裝出瀏覽器頭進行爬取,有的則不需要headers = {# 'Connection': 'keep - alive','User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/52.0.2743.82 Safari/537.36'}# 對請求的返回進行處理的配置meta = {'dont_redirect': True, # 禁止網頁重定向'handle_httpstatus_list': [301, 302] # 對哪些異常返回進行處理 }def get_next_url(self, old_url):'''description: 返回下次迭代的url:param oldUrl: 上一個爬去過的url:return: 下次要爬取的url'''# 傳入的url格式:http://www.heartsong.top/forum.php?mod=viewthread&tid=34list = old_url.split('/') #用等號分割字符串old_item_id = int(list[3].split('.')[0])new_item_id = old_item_id - 1if new_item_id == 0: # 如果tid迭代到0了,說明網站爬完,爬蟲可以結束了returnnew_url = '/'.join([list[0], list[1], list[2], str(new_item_id)+ '.html']) # 構造出新的urlreturn str(new_url) # 返回新的urldef start_requests(self):"""這是一個重載函數,它的作用是發出第一個Request請求:return:"""# 帶著headers、cookies去請求self.start_urls[0],返回的response會被送到# 回調函數parse中yield Request(self.start_urls[0], callback=self.parse, headers=self.headers, cookies=self.cookies, meta=self.meta)def parse(self, response):"""用以處理主題貼的首頁:param response::return:"""selector = Selector(response)item = JDBookItem()extractor = LxmlLinkExtractor(allow=r'http://item.jd.com/\d.*html')link = extractor.extract_links(response)try:item['_id'] = response.url.split('/')[3].split('.')[0]item['url'] = response.urlitem['title'] = selector.xpath('/html/head/title/text()').extract()[0]item['keywords'] = selector.xpath('/html/head/meta[2]/@content').extract()[0]item['description'] = selector.xpath('/html/head/meta[3]/@content').extract()[0]item['img'] = 'http:' + selector.xpath('//*[@id="spec-n1"]/img/@src').extract()[0]item['channel'] = selector.xpath('//*[@id="root-nav"]/div/div/strong/a/text()').extract()[0]item['tag'] = selector.xpath('//*[@id="root-nav"]/div/div/span[1]/a[1]/text()').extract()[0]item['sub_tag'] = selector.xpath('//*[@id="root-nav"]/div/div/span[1]/a[2]/text()').extract()[0]item['value'] = selector.xpath('//*[@id="root-nav"]/div/div/span[1]/a[2]/text()').extract()[0]comments = list()node_comments = selector.xpath('//*[@id="hidcomment"]/div')for node_comment in node_comments:comment = dict()node_comment_attrs = node_comment.xpath('.//div[contains(@class, "i-item")]')for attr in node_comment_attrs:url = attr.xpath('.//div/strong/a/@href').extract()[0]comment['url'] = 'http:' + urlcontent = attr.xpath('.//div/strong/a/text()').extract()[0]comment['content'] = contenttime = attr.xpath('.//div/span[2]/text()').extract()[0]comment['time'] = timecomments.append(comment)item['comments'] = commentsexcept Exception, ex:print 'something wrong', str(ex)print 'success, go for next'yield itemnext_url = self.get_next_url(response.url) # response.url就是原請求的urlif next_url != None: # 如果返回了新的urlyield Request(next_url, callback=self.parse, headers=self.headers, cookies=self.cookies, meta=self.meta)
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2、存儲管道:pipelines
tips:
Python爬蟲框架、1、本pipelines將爬取的數據存入mongo,比寫本地文件靠譜,特別是多實例或者分布式情況。
# -*- coding: utf-8 -*-import pymongo from datetime import datetime from scrapy.exceptions import DropItemclass JDBookPipeline(object):def __init__(self, mongo_uri, mongo_db, mongo_coll):self.ids = set()self.mongo_uri = mongo_uriself.mongo_db = mongo_dbself.mongo_coll = mongo_coll@classmethoddef from_crawler(cls, crawler):return cls(mongo_uri=crawler.settings.get('MONGO_URI'),mongo_db=crawler.settings.get('MONGO_DB'),mongo_coll=crawler.settings.get('MONGO_COLL'))def open_spider(self, spider):self.client = pymongo.MongoClient(self.mongo_uri)# 數據庫登錄需要帳號密碼的話# self.client.admin.authenticate(settings['MINGO_USER'], settings['MONGO_PSW'])self.db = self.client[self.mongo_db]self.coll = self.db[self.mongo_coll]def close_spider(self, spider):self.client.close()def process_item(self, item, spider):if item['_id'] in self.ids:raise DropItem("Duplicate item found: %s" % item)if item['channel'] != u'圖書':raise Exception('not book')else:#self.coll.insert(dict(item))# 如果你不想鎖死collection名稱的話self.ids.add(item['_id'])collection_name = item.__class__.__name__ + '_' + str(datetime.now().date()).replace('-', '')self.db[collection_name].insert(dict(item))return item
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3、數據結構:items
tips:
通用爬蟲和聚焦爬蟲爬取網頁的流程、1、看到scrapy的item就笑了,這不是django么
# -*- coding: utf-8 -*-import scrapyclass JDBookItem(scrapy.Item):_id = scrapy.Field()title = scrapy.Field()url = scrapy.Field()keywords = scrapy.Field()description = scrapy.Field()img = scrapy.Field()channel = scrapy.Field()tag = scrapy.Field()sub_tag = scrapy.Field()value = scrapy.Field()comments = scrapy.Field()
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4、scrapyd部署
很多朋友想做分布式爬蟲,比如通過celery任務調起scarpy爬蟲任務。
scrapy爬蟲。但是很不幸,scrapy想實現這樣的方式并不簡單。一個比較好的辦法是用scrapyd管理爬蟲任務。
你需要保證你的python環境安裝了3個東西。
source kangaroo.env/bin/activate
pip install scrapy scrapyd scrapyd-client
在你的spider路徑下啟動scrapyd守護進程。
scrapyd
下面注冊你的spider,先寫配置文件scrapy.cfg?
# Automatically created by: scrapy startproject # # For more information about the [deploy] section see: # https://scrapyd.readthedocs.org/en/latest/deploy.html [settings] default = jdbook.settings[deploy:jdbook] url = http://localhost:6800/ project = jdbook
爬蟲框架scrapy。開始注冊
#注冊spider scrapyd-deploy -p jdbook -d jdbook #列出已注冊的spider scrapyd-deploy -l
輸出:jdbook ? ? ? ? ? ? ? http://localhost:6800/
這樣就已經注冊好了
開始/停止爬蟲:
curl -XPOST http://10.94.99.55:6800/schedule.json? -d project=jdbook -d spider=jdbook
輸出:{"status": "ok", "jobid": "9d50b3dcabfc11e69aa3525400128d39", "node_name": "kvm33093.sg"}
curl -XPOST http://10.94.99.55:6800/cancel.json? -d project=jdbook -d job=9d50b3dcabfc11e69aa3525400128d39
輸出:{"status": "ok", "prevstate": "running", "node_name": "kvm33093.sg"}
?至此,你可以在celery任務中調用爬蟲了,只需要發送如上url就可以。
scrapy 全網爬蟲,而各個爬蟲可以存放在不同的機器上,實現分布式爬取。
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