Python 爬虫-股票数据的Scrapy爬虫

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2017-08-06 19:52:21

目标：获取上交所和深交所所有股票的名称和交易信息
输出：保存到文件中

技术路线：scrapy

获取股票列表：
东方财富网：http://quote.eastmoney.com/stocklist.html
获取个股信息：
百度股票：https://gupiao.baidu.com/stock/
单个股票：https://gupiao.baidu.com/stock/sz002439.html

程序框架

编写spider处理链接爬取和页面解析，编写pipelines处理信息存储。

一、具体流程

步骤1：建立工程和Spider模板
步骤2：编写Spider
步骤3：编写ITEM Pipelines

建立工程和Spider模板

\>scrapy startproject BaiduStocks
\>cd BaiduStocks
\>scrapy genspider stocks baidu.com
进一步修改spiders/stocks.py文件

编写Spider
- 配置stocks.py文件
- 修改对返回页面的处理
- 修改对新增URL爬取请求的处理

stocks.py修改前

stock.py修改后

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

import scrapy

import re

import random

class StocksSpider(scrapy.Spider):

    name = "stocks"

    start_urls = ['http://quote.eastmoney.com/stocklist.html']

    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"]

    def parse(self, response):

        ua = random.choice(self.user_agent_list)

        headers = {

          'Accept-Encoding':'gzip, deflate, sdch, br',

          'Accept-Language':'zh-CN,zh;q=0.8',

          'Connection':'keep-alive',

          'Referer':'https://gupiao.baidu.com/',

          'User-Agent':ua

          }#构造请求头

        for href in response.css('a::attr(href)').extract():

            try:

                stock = re.findall(r"[s][hz]\d{6}",href)[0]

                url = "https://gupiao.baidu.com/stock/"+stock+".html"

                yield scrapy.Request(url,callback=self.parse_stock,headers = headers)

            except:

                continue

    def parse_stock(self,response):

        #itempipline模块接受的是字典类型的数据

        infodict = {}

        name = response.css('.bets-name').extract()[0]

        keylist = response.css('dt').extract()

        vallist = response.css('dd').extract()

        for i in range(len(keylist)):

            key = re.findall(r".*>(.*)</dt>",keylist[i])[0]

            try:

                val = re.findall(r">[-]?\d+\.?.*</dd>",vallist[i])[0][1:-5]

            except:

                val = "--"

            infodict[key] = val

        infodict.update({"股票名称":re.findall(r"\s+.*\(",name)[0].split()[0]+re.findall(r"\d+</s",name)[0][0:-3]})

        yield infodict

Scrapy中提供了css选择器，可以使用css选择器进行html页面的提取。

主要的使用方法有：

<HTML>.css('a::attr(href)').extract() ：这样会提取到a标签下的href属性的值，并提取为字符串，返回一个列表

<HTML>.css('a').extract() ：这样会提取所有a标签以及全部内容，转成字符串，返回一个列表

<HTML>.css('.calc').extract()：这样会提取所有类型为calc的标签及其全部内容，转成字符串，返回一个列表

<HTML>.css('.calc')：不提取的话，会返回一个选择器类型，可以继续对类型为calc的便签内容进行继续提取

编写Pipelines

配置pipelines.py文件
定义对爬取项（Scraped Item）的处理类，每一个类处理一个items
配置ITEM_PIPELINES选项

pipelines.py修改前：

pipelines.py修改后

# -*- 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

#每一个类都是对一个itme进行处理的类

class BaidustocksPipeline(object):

    def process_item(self, item, spider):

        return item

class Baidustocksinfopipeline(object):

    def open_spider(self,spider):

        self.f = open("Baidustockinfo.txt",'w')

    def close_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