pip 安装 pip install scrapy
可能的问题: 问题/解决:error: Microsoft Visual C++ 14.0 is required.
实例demo教程 中文教程文档 第一步:创建项目目录
scrapy startproject tutorial
第二步:进入tutorial创建spider爬虫
scrapy genspider baidu www.baidu.com
第三步:创建存储容器,复制项目下的items.py重命名为BaiduItems
# -*- 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 BaiduItems(scrapy.Item):
# define the fields for your item here like:
# name = scrapy.Field()
title = scrapy.Field()
link = scrapy.Field()
desc = scrapy.Field()
pass
第四步:修改spiders/baidu.py xpath提取数据
# -*- coding: utf-8 -*-
import scrapy
# 引入数据容器
from tutorial.BaiduItems import BaiduItems
class BaiduSpider(scrapy.Spider):
name = 'baidu'
allowed_domains = ['www.readingbar.net']
start_urls = ['http://www.readingbar.net/']
def parse(self, response):
for sel in response.xpath('//ul/li'):
item = BaiduItems()
item['title'] = sel.xpath('a/text()').extract()
item['link'] = sel.xpath('a/@href').extract()
item['desc'] = sel.xpath('text()').extract()
yield item
pass
第五步:解决百度首页网站抓取空白问题,设置setting.py
# 设置用户代理
USER_AGENT = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/66.0.3359.139 Safari/537.36'
# 解决 robots.txt 相关debug
ROBOTSTXT_OBEY = False
# scrapy 解决数据保存乱码问题
FEED_EXPORT_ENCODING = 'utf-8'
最后一步:开始爬取数据命令并保存数据为指定的文件 执行的时候可能报错:No module named 'win32api' 可以下载指定版本安装
scrapy crawl baidu -o baidu.json
深度爬取百度首页及导航菜单相关页内容
# -*- coding: utf-8 -*-
import scrapy
from scrapyProject.BaiduItems import BaiduItems
class BaiduSpider(scrapy.Spider):
name = 'baidu'
# 由于tab包含其他域名,需要添加域名否则无法爬取
allowed_domains = [
'www.baidu.com',
'v.baidu.com',
'map.baidu.com',
'news.baidu.com',
'tieba.baidu.com',
'xueshu.baidu.com'
]
start_urls = ['https://www.baidu.com/']
def parse(self, response):
item = BaiduItems()
item['title'] = response.xpath('//title/text()').extract()
yield item
for sel in response.xpath('//a[@class="mnav"]'):
item = BaiduItems()
item['nav'] = sel.xpath('text()').extract()
item['href'] = sel.xpath('@href').extract()
yield item
# 根据提取的nav地址建立新的请求并执行回调函数
yield scrapy.Request(item['href'][0],callback=self.parse_newpage)
pass
# 深度提取tab网页标题信息
def parse_newpage(self, response):
item = BaiduItems()
item['title'] = response.xpath('//title/text()').extract()
yield item
pass
绕过登录进行爬取 a.解决图片验证 pytesseract