本文章仅作为个人笔记
Scrpy官网
Scrpy官方文档
Scrpy中文文档
个人ScrapyDemo项目地址
python环境安装
- win下安装:
- python:下载python安装包直接安装即可
- pip: easy_install pip
- mac下安装:
- python:mac下自带python2.7
- pip: easy_install pip
- centos7下安装:
- python:centos7下自带python2.7
- pip: easy_install pip
scrapy 安装
pip install Scrapy
创建项目
scrapy startproject
创建爬虫
scrapy genspider
在文件夹根目录创建 requirements.txt文件并加入需要的组件,例如:
Scrapy==1.5.0
beautifulsoup4==4.6.0
requests==2.18.4
项目环境搭建
pip install -r requirements.txt
运行单个爬虫
scrapy crawl
运行多个爬虫(Scrapy本身并不支持命令行直接运行多个Spiders,创建一个新的python文件加入如下内容运行此python文件便可)(需按需更改)
# -*- coding: utf-8 -*-
import sys
from scrapy.crawler import CrawlerProcess
from scrapy.utils.project import get_project_settings
from ScrapyDemo.spiders.news_estadao import EstadaoSpider
from ScrapyDemo.spiders.news_gazetaesportiva import DemoSpider
from ScrapyDemo.spiders.news_megacurioso import MegacuriosoSpider
if sys.getdefaultencoding != 'utf-8':
reload(sys)
sys.setdefaultencoding('utf-8')
process = CrawlerProcess(get_project_settings())
process.crawl(EstadaoSpider)
process.crawl(DemoSpider)
process.crawl(MegacuriosoSpider)
process.start()
启用pipelines用于处理结果
- 打开settings.py文件在ITEM_PIPELINES选项下加入peline并赋值,0-1000,数字越小越优先
输出单个spider运行结果到文件
scrapy crawl demo -o /path/to/demo.json
多个spider的结果混合处理:
- 上面的运行多个爬虫脚本并不能将多个spider的结果混合处理
- 因为业务需要,只可退而求其次
思路:借助commands库运行linux命令顺序运行并输出结果到文件,最后读取文件内容解析为对象进行混合处理
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代码(需按需更改):
#!/usr/bin/env python # encoding: utf-8 import commands def test(): result = [] try: commands.getoutput("echo '' > /path/to/megacurioso.json") #清空上次运行结果 commands.getoutput("scrapy crawl demo -o /path/to/demo.json") # 运行结果并输出 result = json.loads(commands.getoutput("cat /path/to/megacurioso.json")) # 获取运行结果 except: print "Get megacurioso error." return result
解决结果爬虫信息乱码问题:
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在有乱码问题python文件顶部加入如下代码:
if sys.getdefaultencoding != 'utf-8': reload(sys) sys.setdefaultencoding('utf-8')
爬虫示例,也可以使用文顶给出的github链接:
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item示例(items.py):
# -*- coding: utf-8 -*- # Define here the models for your scraped items # # See documentation in: # https://doc.scrapy.org/en/latest/topics/items.html import scrapy class ScrapydemoItem(scrapy.Item): title = scrapy.Field() imageUrl = scrapy.Field() des = scrapy.Field() source = scrapy.Field() actionUrl = scrapy.Field() contentType = scrapy.Field() itemType = scrapy.Field() createTime = scrapy.Field() country = scrapy.Field() headUrl = scrapy.Field() pass
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pipelines示例(pipelines.py):
# -*- coding: utf-8 -*- # Define your item pipelines here # # Don't forget to add your pipeline to the ITEM_PIPELINES setting # See: https://doc.scrapy.org/en/latest/topics/item-pipeline.html from ScrapyDemo.items import ScrapydemoItem import json class ScrapydemoPipeline(object): DATA_LIST_NEWS = [] def open_spider(self, spider): DATA_LIST_NEWS = [] print 'Spider start.' def process_item(self, item, spider): if isinstance(item, ScrapydemoItem): self.DATA_LIST_NEWS.append(dict(item)) return item def close_spider(self, spider): print json.dumps(self.DATA_LIST_NEWS) print 'Spider end.'
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spider示例(demo.py):
# -*- coding: utf-8 -*- import scrapy from ScrapyDemo.items import ScrapydemoItem class DemoSpider(scrapy.Spider): name = 'news_gazetaesportiva' allowed_domains = ['www.gazetaesportiva.com'] start_urls = ['https://www.gazetaesportiva.com/noticias/'] headers = { 'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8', 'accept-language': 'zh-CN,zh;q=0.9,en-US;q=0.8,en;q=0.7', 'cache-control': 'max-age=0', 'upgrade-insecure-requests': '1', 'User-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_13_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/66.0.3359.139 Safari/537.36' } def parse(self, response): print('Start parse.') for element in response.xpath('//article'): title = element.xpath(".//h3[@class='entry-title no-margin']/a/text()").extract_first() imageUrl = [element.xpath(".//img[@class='medias-object wp-post-image']/@src").extract_first()] des = element.xpath(".//div[@class='entry-content space']/text()").extract_first() source = 'gazeta' actionUrl = element.xpath(".//a[@class='blog-image']/@href").extract_first() contentType = '' itemType = '' createTime = element.xpath(".//small[@class='updated']/text()").extract_first() country = 'PZ' headUrl = '' if title is not None and title != "" and actionUrl is not None and actionUrl != "" and imageUrl is not None and imageUrl != "": item = ScrapydemoItem() item['title'] = title item['imageUrl'] = imageUrl item['des'] = des item['source'] = source item['actionUrl'] = actionUrl item['contentType'] = contentType item['itemType'] = itemType item['createTime'] = createTime item['country'] = country item['headUrl'] = headUrl yield item print('End parse.')
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代码个人理解:
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settings可配置公共配置及配置pipelines对spiders结果进行汇总,例如(后面的数值越大优先级越低,取值0-1000):
ITEM_PIPELINES = { 'DemoScrapy.pipelines.ScrapydemoPipeline': 300, }
配置pipelines后命令行运行spiders是会先运行open_spider方法,然后每个结果解析时运行process_item方法,最后spider结束时运行close_spider方法
items文件是用来配置描述结果对象的
spiders文件夹里根据命令行创建的spiders文件配置需要抓取的数据的网页及需要伪装的请求头参数等,抓取数据后数据结果进入 parse方法进行解析,可使用xpath进行解析。xpath的具体使用可参考前文给出的链接,个人进行数据抓取前使用chrom定位标签,复制源码后根据规则找到标签位置最后进行规则匹配,因为每次数据规则匹配不可能一次性完成,建议使用debug功能来进行匹配,最后一次性完成规则书写。
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pycharm下debug spiders:
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打开pycharm后如果遇到部分插件无法安装的情况可使用虚拟环境:
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debug运行scrapy:
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运行到断点后右击选择 Evaluate Expresion
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