使用scrapy爬取百度股票

# -*- coding: utf-8 -*-
import scrapy
import re
import random
from scrapy.http.response.html import HtmlResponse
class StocksSpider(scrapy.Spider):
    def __init__(self):
        self.user_agent_list = [             "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/22.0.1207.1 Safari/537.1"             "Mozilla/5.0 (X11; CrOS i686 2268.111.0) AppleWebKit/536.11 (KHTML, like Gecko) Chrome/20.0.1132.57 Safari/536.11",             "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.6 (KHTML, like Gecko) Chrome/20.0.1092.0 Safari/536.6",             "Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.6 (KHTML, like Gecko) Chrome/20.0.1090.0 Safari/536.6",             "Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/19.77.34.5 Safari/537.1",             "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/536.5 (KHTML, like Gecko) Chrome/19.0.1084.9 Safari/536.5",             "Mozilla/5.0 (Windows NT 6.0) AppleWebKit/536.5 (KHTML, like Gecko) Chrome/19.0.1084.36 Safari/536.5",             "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3",             "Mozilla/5.0 (Windows NT 5.1) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3",             "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_8_0) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3",             "Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1062.0 Safari/536.3",             "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1062.0 Safari/536.3",             "Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3",             "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3",             "Mozilla/5.0 (Windows NT 6.1) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3",             "Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.0 Safari/536.3",             "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/535.24 (KHTML, like Gecko) Chrome/19.0.1055.1 Safari/535.24",             "Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/535.24 (KHTML, like Gecko) Chrome/19.0.1055.1 Safari/535.24"
        ]
        self.ua = random.choice(self.user_agent_list)
        self.header = {
            ‘Accept-Encoding‘: ‘gzip, deflate, sdch, br‘,
            ‘Accept-Language‘: ‘zh-CN,zh;q=0.8‘,
            ‘Connection‘: ‘keep-alive‘,
            ‘Referer‘: ‘https://gupiao.baidu.com/‘,
            ‘User-Agent‘: self.ua
        }
    name = ‘stocks‘
    start_urls = [‘http://quote.eastmoney.com/stocklist.html‘]

    def parse(self, response):
        for href in response.css(‘a::attr(href)‘).extract():

            try:
                stock = re.findall(r‘[s][hz]\d{6}‘,href)[0]
                url = ‘http://gupiao.baidu.com/stock/‘+stock+‘.html‘
                yield scrapy.Request(url,callback=self.parse_stock,headers=self.header)
            except:
                continue
    def parse_stock(self,response):
        infoDict = {}
        stockInfo = response.css(‘.stock-bets‘).extract()[0]
        name = response.css(‘.stock-bets .bets-name‘).extract()[0]
        KeyList = response.css(‘.stock-bets dt‘).extract()
        ValueList = response.css(‘.stock-bets dd‘).extract()
        for i in range(len(KeyList)):
            key = re.findall(r‘>.*</dt>‘,KeyList[i])[0][1:-5]
            try:
                value = re.findall(r‘\d+.?.*</dd>‘, ValueList[i])[0][0:-5]
            except:
                value = ‘--‘
            infoDict[key] = value
        infoDict.update(
            {‘股票名称‘:re.findall(‘\s.*\(‘,name)[0].split()[0] +
                    re.findall(‘\>.*\<‘,name)[0][1:-1]}
        )
        yield infoDict

# -*- coding: utf-8 -*-

# Define your item pipelines here
#
# Don‘t forget to add your pipeline to the ITEM_PIPELINES setting
# See: http://doc.scrapy.org/en/latest/topics/item-pipeline.html


class BaidustocksPipeline(object):
    def process_item(self, item, spider):
        return item


class BaiduStocksInfoPipeline(object):
    def open_spider(self,spider):
        self.f = open(‘BaiduStockInfo1.txt‘,‘w‘,encoding=‘utf-8‘)

    def colse_spider(self,spider):
        self.f.close()

    def process_item(self,item,spider):
        try:
            line = str(dict(item)) +‘\n‘
            self.f.write(line)
        except:
            pass
        return item