马振威的作业一

代码

  from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.common.keys import Keys

browser = webdriver.Edge()
browser.get('https://www.szse.cn/disclosure/listed/fixed/index.html')

element = browser.find_element(By.ID, 'input_code')
element.send_keys('炬申股份' + Keys.RETURN)

element = browser.find_element(By.ID, 'disclosure-table')
innerHTML = element.get_attribute('innerHTML')

f = open('innerHTML.html','w',encoding='utf-8')
f.write(innerHTML)
f.close()
browser.quit()

import re
import pandas as pd


class DisclosureTable():
    '''
    解析深交所定期报告页搜索表格
    '''
    def __init__(self, innerHTML):
        self.html = innerHTML
        self.prefix = 'https://disc.szse.cn/download'
        self.prefix_href = 'https://www.szse.cn/'
        #
        p_a = re.compile('(.*?)', re.DOTALL)
        p_span = re.compile('(.*?)', re.DOTALL)
        self.get_code = lambda txt: p_a.search(txt).group(1).strip()
        self.get_time = lambda txt: p_span.search(txt).group(1).strip()
        #
        self.txt_to_df()

    def txt_to_df(self):
        # html table text to DataFrame
        html = self.html
        p = re.compile('(.*?)', re.DOTALL)
        trs = p.findall(html)

        p2 = re.compile('(.*?)', re.DOTALL)
        tds = [p2.findall(tr) for tr in trs[1:]]

        df = pd.DataFrame({'证券代码': [td[0] for td in tds],
                           '简称': [td[1] for td in tds],
                           '公告标题': [td[2] for td in tds],
                           '公告时间': [td[3] for td in tds]})
        self.df_txt = df

    def get_link(self, txt):
        p_txt = '(.*?)'
        p = re.compile(p_txt, re.DOTALL)
        matchObj = p.search(txt)
        attachpath = matchObj.group(1).strip()
        href       = matchObj.group(2).strip()
        title      = matchObj.group(3).strip()
        return([attachpath, href, title])

    def get_data(self):
        get_code = self.get_code
        get_time = self.get_time
        get_link = self.get_link
        #
        df = self.df_txt
        codes = [get_code(td) for td in df['证券代码']]
        short_names = [get_code(td) for td in df['简称']]
        ahts = [get_link(td) for td in df['公告标题']]
        times = [get_time(td) for td in df['公告时间']]
        #
        prefix = self.prefix
        prefix_href = self.prefix
        df = pd.DataFrame({'证券代码': codes,
                           '简称': short_names,
                           '公告标题': [aht[2] for aht in ahts],
                           'attachpath': [prefix + aht[0] for aht in ahts],
                           'href': [prefix_href + aht[1] for aht in ahts],
                           '公告时间': times
            })
        self.df_data = df
        return(df)


f = open('innerHTML.html',encoding='utf-8')
html = f.read()
f.close()

dt = DisclosureTable(html)
df = dt.get_data()
df.to_csv('data.csv')

结果

解释

匹配最后一个单词时使用search方法，匹配的正则表达式表示以空格开头，以.结尾，中间为重复一次或多次通配符的内容，匹配成功后输出第2组，也就是单词部分，最后计算单词长度。