Scrapy是Python開發的一個快速、高層次的屏幕抓取和web抓取框架,用於抓取Web站點並從頁面中提取結構化的數據.它最吸引人的地方在於任何人均可以根據需求方便的修改。
MongoDB是現下很是流行的開源的非關係型數據庫(NoSql),它是以「key-value」的形式存儲數據的,在大數據量、高併發、弱事務方面都有很大的優點。
當Scrapy與MongoDB二者相碰撞會產生怎樣的火花呢?與MongoDB二者相碰撞會產生怎樣的火花呢?如今讓咱們作一個簡單的爬取小說的TEST
1.安裝Scrapy
pip install scrapy
2.下載安裝MongoDB和MongoVUE可視化
[MongoDB下載地址](https://www.mongodb.org/)
下載安裝的步驟略過,在bin目錄下建立一個data文件夾用來存放數據的。vue
[MongoVUE下載地址](http://www.mongovue.com/)web
安裝完成後咱們須要建立一個數據庫。redis
3.建立一個Scrapy項目
scrapy startproject novelspider
目錄結構:其中的novspider.py是須要咱們手動建立的(contrloDB不須要理會)mongodb
4.編寫代碼數據庫
目標網站:http://www.daomubiji.com/併發
settings.py框架
BOT_NAME = 'novelspider' SPIDER_MODULES = ['novelspider.spiders'] NEWSPIDER_MODULE = 'novelspider.spiders' ITEM_PIPELINES = ['novelspider.pipelines.NovelspiderPipeline'] #導入pipelines.py中的方法 USER_AGENT = 'Mozilla/5.0 (Windows NT 6.1; WOW64; rv:39.0) Gecko/20100101 Firefox/39.0' COOKIES_ENABLED = True MONGODB_HOST = '127.0.0.1' MONGODB_PORT = 27017 MONGODB_DBNAME = 'zzl' #數據庫名 MONGODB_DOCNAME = 'Book' #表名
pipelines.pyscrapy
from scrapy.conf import settings import pymongo class NovelspiderPipeline(object): def __init__(self): host = settings['MONGODB_HOST'] port = settings['MONGODB_PORT'] dbName = settings['MONGODB_DBNAME'] client = pymongo.MongoClient(host=host, port=port) tdb = client[dbName] self.post = tdb[settings['MONGODB_DOCNAME']] def process_item(self, item, spider): bookInfo = dict(item) self.post.insert(bookInfo) return item
items.pyide
from scrapy import Item,Field class NovelspiderItem(Item): # define the fields for your item here like: # name = scrapy.Field() bookName = Field() bookTitle = Field() chapterNum = Field() chapterName = Field() chapterURL = Field()
在spiders目錄下建立novspider.py高併發
from scrapy.spiders import CrawlSpider from scrapy.selector import Selector from novelspider.items import NovelspiderItem class novSpider(CrawlSpider): name = "novspider" redis_key = 'novspider:start_urls' start_urls = ['http://www.daomubiji.com/'] def parse(self,response): selector = Selector(response) table = selector.xpath('//table') for each in table: bookName = each.xpath('tr/td[@colspan="3"]/center/h2/text()').extract()[0] content = each.xpath('tr/td/a/text()').extract() url = each.xpath('tr/td/a/@href').extract() for i in range(len(url)): item = NovelspiderItem() item['bookName'] = bookName item['chapterURL'] = url[i] try: item['bookTitle'] = content[i].split(' ')[0] item['chapterNum'] = content[i].split(' ')[1] except Exception,e: continue try: item['chapterName'] = content[i].split(' ')[2] except Exception,e: item['chapterName'] = content[i].split(' ')[1][-3:] yield item
5.啓動項目命令: scrapy crawl novspider.
抓取結果