python 股票数据爬取（两种方法）

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股票HTML网页分析：

东方财富网可以看到股票信息：

http://quote.eastmoney.com/stocklist.html

查看源代码：

<li><a target="_blank" href="http://quote.eastmoney.com/sh201008.html">R001(201008)</a></li>            <li><a target="_blank" href="http://quote.eastmoney.com/sh201010.html">R004(201010)</a></li><li><a target="_blank" href="http://quote.eastmoney.com/sh202001.html">RC001(202001)</a></li>

可以在href中提取股票的代码，
想了解股票的具体信息，需要去百度股票查找，方法为：
'https://gupiao.baidu.com/stock/股票代码.html
查看具体股票的源代码：

<div class="stock-info" data-spm="2">    <div class="stock-bets">        <h1>            <a class="bets-name" href="/stock/sz300388.html">            国祯环保 (<span>300388</span>)            </a>            <span class="state f-up">已休市 2017-09-29  15:00:03            </span>        </h1>        <div class="price s-stop ">                        <strong  class="_close">--</strong>            <span>--</span>            <span>--</span>                    </div>        <div class="bets-content">                                                        <div class="line1">                    <dl><dt>今开</dt><dd class="">19.92</dd></dl>                    <dl><dt>成交量</dt><dd>8917手</dd></dl>                    <dl><dt>最高</dt><dd class="s-up">20.15</dd></dl>                    <dl><dt>涨停</dt><dd class="s-up">21.96</dd></dl>                    <dl><dt>内盘</dt><dd>4974手</dd></dl>                    <dl><dt>成交额</dt><dd>1786.10万</dd></dl>                    <dl><dt>委比</dt><dd>-50.69%</dd></dl>                    <dl><dt>流通市值</dt><dd>59.98亿</dd></dl>                    <dl><dt class="mt-1">市盈率<sup>MRQ</sup></dt><dd>50.59</dd></dl>                    <dl><dt>每股收益</dt><dd>0.20</dd></dl>                    <dl><dt>总股本</dt><dd>3.06亿</dd></dl>                    <div class="clear"></div>                </div>                <div class="line2">                    <dl><dt>昨收</dt><dd>19.96</dd></dl>                    <dl><dt>换手率</dt><dd>0.30%</dd></dl>                    <dl><dt>最低</dt><dd class="s-down">19.92</dd>                    </dl>                    <dl><dt>跌停</dt><dd class="s-down">                        17.96</dd></dl>                    <dl><dt>外盘</dt><dd>3943手</dd></dl>                    <dl><dt>振幅</dt><dd>1.15%</dd></dl>                    <dl><dt>量比</dt><dd>0.11</dd></dl>                    <dl><dt>总市值</dt><dd>61.35亿</dd></dl>                    <dl><dt>市净率</dt><dd>3.91</dd></dl>                    <dl><dt>每股净资产</dt><dd>5.14</dd></dl>                    <dl><dt>流通股本</dt><dd>2.99亿</dd></dl>                </div>         <div class="clear"></div>        </div>    </div>

发现股票名称在class="bets-name"的a标签中，其他的数据都在dt和dd标签中

方法一：采用bs4库和正则表达式

import requestsfrom bs4 import BeautifulSoupimport re#优化，可以减少程序判断编码所花费的时间def getHTMLText(url, code='UTF-8'):    try:        r = requests.get(url)        r.raise_for_status()        r.encoding = code        return r.text    except:        return ""def getStockList(url, stockList):    html = getHTMLText(url, 'GB2312')    soup = BeautifulSoup(html, 'html.parser')    aInformaton = soup.find_all('a')    for ainfo in aInformaton:        try:            stockList.append(re.findall(r'[s][hz]\d{6}', ainfo.attrs['href'])[0])        except:            continuedef getStockInformation(detailUrl, outputFile, stockList):    count = 0    for name in stockList:        count = count + 1        stockUrl = detailUrl + name + '.html'        html = getHTMLText(stockUrl)        try:            if html == "":                continue            stockDict = {}            soup = BeautifulSoup(html, 'html.parser')            stockinfo = soup.find('div', attrs={'class': 'stock-bets'})            stockname = stockinfo.find('a', attrs={'class': 'bets-name'})            # 当标签内部还有标签时，利用text可以得到正确的文字，利用string可能会产生None            stockDict["股票名称"] = stockname.text.split()[0]            stockKey = stockinfo.find_all('dt')            stockValue = stockinfo.find_all('dd')            for i in range(len(stockKey)):                stockDict[stockKey[i].string] = stockValue[i].string            #\r移动到行首，end=""不进行换行            print("\r{:5.2f}%".format((count / len(stockList) * 100)), end='')            #追加写模式'a'            f = open(outputFile, 'a')            f.write(str(stockDict) + '\n')            f.close()        except:            print("{:5.2f}%".format((count / len(stockList) * 100)), end='')            continuedef main():    listUrl = 'http://quote.eastmoney.com/stocklist.html'    detailUrl = 'https://gupiao.baidu.com/stock/'    outputFile = 'C:/Users/Administrator/Desktop/out.txt'    stockList = []    getStockList(listUrl, stockList)    getStockInformation(detailUrl, outputFile, stockList)main()

方法2.采用Scrapy框架和正则表达式库

（1）建立工程和Spider模板（保存为stocks.py文件）

在命令行中进入：E:\PythonProject\BaiduStocks

输入：scrapy startproject BaiduStocks 建立了scrapy工程

输入：scrapy genspider stocks baidu.com 建立spider模板，baidu.com是指爬虫限定的爬取域名，在stocks.py文件删去即可

（2）编写spider爬虫（即stocks.py文件）

采用css选择器，可以返回选择的标签元素，通过方法extract()可以提取标签元素为字符串从而实现匹配正则表达式的处理

正则表达式详解：

<a class="bets-name" href="/stock/sz300388.html">            国祯环保 (<span>300388</span>)            </a>

re.findall('.*\(', stockname)[0].split()[0] + '('+re.findall('\>.*\<', stockname)[0][1:-1]+')'

匹配结果：国祯环保（300388）

因为'('为正则表达式语法里的基本符号，所以需要转义

正则表达式从每行开始匹配，匹配之后返回[' 国祯环保 (']，采用split将空白字符分割，返回['国祯环保'，‘(’]

# -*- coding: utf-8 -*-import scrapyimport reclass StocksSpider(scrapy.Spider):    name = 'stocks'    start_urls = ['http://quote.eastmoney.com/stocklist.html']    def parse(self, response):        fo=open(r'E:\PythonProject\BaiduStocks\oo.txt','a')        #fo.write(str(response.css('a').extract()))        count=0        for href in response.css('a').extract():            try:                if count == 300:                    break                count=count+1                stockname=re.findall(r'[s][hz]\d{6}',href)[0]                stockurl='https://gupiao.baidu.com/stock/' + stockname + '.html'                #fo.write(stockurl)                yield scrapy.Request(url= stockurl,headers={"User-Agent":"Chrome/10"} ,callback=self.stock_parse)            except:                continue        pass    def stock_parse(self,response):        ffo=open(r'E:\PythonProject\BaiduStocks\stockparse.txt','a')        stockDict={}        #提取标签中class="stock-bets"的标签元素        stockinfo=response.css('.stock-bets')        #将提取出来的标签转化为字符串列表，然后取第一个        stockname=stockinfo.css('.bets-name').extract()[0]        #ffo.write(stockname)        keyList=stockinfo.css('dt').extract()        #ffo.write(str(keyList))        valueList=stockinfo.css('dd').extract()        stockDict['股票名称'] = re.findall('.*\(', stockname)[0].split()[0] + '('+re.findall('\>.*\<', stockname)[0][1:-1]+')'        for i in range(len(keyList)):            stockkey=re.findall(r'>.*</dt>',keyList[i])[0][1:-5]            stockvalue=re.findall(r'>.*</dd>',valueList[i])[0][1:-5]            stockDict[stockkey]=stockvalue        yield stockDict

（3）编写PipeLine（即pipelines.py文件）

系统自动生成了Item处理类BaiduStocksPipeline，我们不采用系统生成，新建一个BaiduStocksinfoPipeline类，并书写Item处理函数

# -*- 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.htmlclass BaidustocksPipeline(object):    def process_item(self, item, spider):        return itemclass BaidustocksinfoPipeline(object):    #爬虫打开时执行    def open_spider(self,spider):        self.f=open(r'E:\PythonProject\BaiduStocks\BaiduStocks\asdqwe.txt','a')    # 爬虫关闭时执行    def close_spider(self,spider):        self.f.close()            #处理Item项    def process_item(self,item,spider):        try:            self.f.write(str(item)+'\n')        except:            pass        return item

此时要修改配置文件setting.py文件

ITEM_PIPELINES = {    'BaiduStocks.pipelines.BaidustocksinfoPipeline': 300,}

（4）运行爬虫：scrapy crawl stocks

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