pip install scrapy

scrapy startproject questions

# -*- coding: utf-8 -*-
import scrapy
import time
import numpy
import re
from questions.items import QuestionsItem
class xueersiSpider(scrapy.Spider):
  name = "xueersi" # 爬虫名字
  allowed_domains = ["tiku.xueersi.com"] # 目标的域名
　　# 爬取的目标地址
  start_urls = [
    "http://tiku.xueersi.com/shiti/list_1_1_0_0_4_0_1",
    "http://tiku.xueersi.com/shiti/list_1_2_0_0_4_0_1",
    "http://tiku.xueersi.com/shiti/list_1_3_0_0_4_0_1",
  ]
  levels = ['偏易','中档','偏难']
  subjects = ['英语','语文','数学']
　　 # 爬虫开始的时候，自动调用该方法，如果该方法不存在会自动调用parse方法
  # def start_requests(self):
  #   yield scrapy.Request('http://tiku.xueersi.com/shiti/list_1_2_0_0_4_0_39',callback=self.getquestion)
　　# start_requests方法不存在时，parse方法自动被调用
  def parse(self, response):
　　　　　# xpath的选择器语法不多介绍，可以直接查看官方文档
    arr = response.xpath("//ul[@class='pagination']/li/a/text()").extract()
    total_page = arr[3]
　　　　　# 获取分页
    for index in range(int(total_page)):
      yield scrapy.Request(response.url.replace('_0_0_4_0_1',"_0_0_4_0_"+str(index)),callback=self.getquestion) # 发出新的请求，获取每个分页所有题目
  # 获取题目
  def getquestion(self,response):
    for res in response.xpath('//div[@class="main-wrap"]/ul[@class="items"]/li'):
      item = QuestionsItem() # 实例化Item类
      # 获取问题
      questions = res.xpath('./div[@class="content-area"]').re(r'<div class="content-area">"info"]').re(ur'难度：([\s\S]+"info"]/a/@href').extract()[0]
          request = scrapy.Request(url,callback=self.getanswer)
          request.meta['item'] = item # 缓存item数据，传递给下一个请求
          yield request
      #for option in options:
  # 获取答案      
  def getanswer(self,response):
    
    res = response.xpath('//div[@class="part"]').re(ur'<td>([\s\S]+"htmlcode">

# -*- 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 QuestionsItem(scrapy.Item):
  content = scrapy.Field()
  subject = scrapy.Field()
  level = scrapy.Field()
  answer = scrapy.Field()
  options = scrapy.Field()
  analysis = scrapy.Field()
  source = scrapy.Field()
  answer_url = scrapy.Field()
  pass


pipelines.py 输出管道（本例子输出的数据写入本地数据库）：


# -*- 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
import pymysql
import md5
class QuestionsPipeline(object):
  def __init__(self): 
    # 建立数据库连接 
    self.connect = pymysql.connect('localhost','root','','question',use_unicode=True,charset='utf8') 
    # 获取游标 
    self.cursor = self.connect.cursor() 
    print("connecting mysql success!") 
    self.answer = ['A','B','C','D']
  def process_item(self, item, spider):
    content = pymysql.escape_string(item['content'])
　　　　 # 获取题目hash值，使用该字段过滤重复的题目
    m1 = md5.new()  
    m1.update(content)
    hash = m1.hexdigest()
    selectstr = "select id from question where hash='%s'"%(hash)
    self.cursor.execute(selectstr)
    res = self.cursor.fetchone()
    # 过滤相同的题目
    if not res:
　　　　　　　# 插入题目
      sqlstr = "insert into question(content,source,subject,level,answer,analysis,hash,answer_url) VALUES('%s','%s','%s','%s','%s','%s','%s','%s')"%(content,pymysql.escape_string(item['source']),item['subject'],item['level'],item['answer'],pymysql.escape_string(item['analysis']),hash,item['answer_url'])
      self.cursor.execute(sqlstr)
      qid = self.cursor.lastrowid
　　　　　　　# 插入选项
      for index in range(len(item['options'])):
        option = item['options'][index]
        answer = self.answer.index(item['answer'])
        if answer==index:
          ans = '2'
        else:
          ans = '1'
        sqlstr = "insert into options(content,qid,answer) VALUES('%s','%s','%s')"%(pymysql.escape_string(option[0]),qid,ans)
        self.cursor.execute(sqlstr)
      self.connect.commit() 
      #self.connect.close() 
    return item
 


爬虫构建完毕后，在项目的根目录下运行


scrapy crawl xueersi # scrapy crawl 爬虫的名称


更多关于python爬虫库scrapy使用方法请查看下面的相关链接