曲牌名
获取来源
之前爬取过元代的诗,众所周知,曲牌名出自于元代,唐诗,宋词,元曲
收集曲牌名
import pandas as pd import xlwt #读取yuan代的诗词 def read(file): data=pd.read_excel(file) title=data.title # 存储一个曲排名列表 qu_list=[] for it in title: if it.find('·')!=-1: # 根据诗词名获取对应的曲牌名 qu=it.split('·') qu_list.append(qu[0]) new_qu=list(set(qu_list)) #将曲牌名进行保存 xl = xlwt.Workbook() # 调用对象的add_sheet方法 sheet1 = xl.add_sheet('sheet1', cell_overwrite_ok=True) sheet1.write(0, 0, "qu_name") for i in range(0, len(new_qu)): sheet1.write(i + 1, 0, new_qu[i]) xl.save("qupai_name.xlsx") if __name__ == '__main__': file='data/yuan.xlsx' read(file)
成果展示
飞花令
获取来源
古诗词网上有专门的飞花令字词,因此我们的来源就是它
爬取飞花令
import requests from bs4 import BeautifulSoup from lxml import etree headers = {'user-agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.131 Safari/537.36'}#创建头部信息 hc=[] url='https://www.xungushici.com/feihualings' r=requests.get(url,headers=headers) content=r.content.decode('utf-8') soup = BeautifulSoup(content, 'html.parser') ul=soup.find('ul',class_='list-unstyled d-flex flex-row flex-wrap align-items-center w-100') li_list=ul.find_all('li',class_='m-1 badge badge-light') word=[] for it in li_list: word.append(it.a.text) import xlwt xl = xlwt.Workbook() # 调用对象的add_sheet方法 sheet1 = xl.add_sheet('sheet1', cell_overwrite_ok=True) sheet1.write(0,0,"word") for i in range(0,len(word)): sheet1.write(i+1,0,word[i]) xl.save("word.xlsx")
结果展示
诗句-飞花令
思路
通过遍历爬取的50万首古诗,分析每个句子是否有包含的飞花令中的关键字,如果有将其存储起来:诗句、作者、诗名、关键字
BUG
如果用xlwt来存储,最多存储65536行数据,用openpyxl可以存储100万行数据。由于我们的诗句数据过大,因此需采用openpyxl来进行存储
代码
import pandas as pd import xlwt import openpyxl #读取飞花令 def read_word(): data=pd.read_excel('data2/word.xlsx') words=data.word return words #遍历诗句 def read(file,words,write_file): data=pd.read_excel(file) title=data.title content=data.content author=data.author #进行切分出单句 ans_sentens = [] ans_author = [] ans_title = [] ans_key = [] for i in range(len(title)): print("第"+str(i)+"个") cont=content[i] aut=author[i] tit=title[i] sents=cont.replace('\n','').split('。') for it in sents: key_list = [] for k in words: if it.find(k)!=-1: key_list.append(k) if len(key_list)!=0: ans_sentens.append(it) ans_author.append(aut) ans_title.append(tit) ans_key.append(",".join(key_list)) #存储对应的key,author,title,sentenous xl = openpyxl.Workbook() # 调用对象的add_sheet方法 sheet1 = xl.create_sheet(index=0) sheet1.cell(1, 1, "sentens") sheet1.cell(1, 2, "author") sheet1.cell(1, 3, "title") sheet1.cell(1, 4, "keys") for i in range(0, len(ans_key)): sheet1.cell(i + 2, 1, ans_sentens[i]) sheet1.cell(i + 2, 2, ans_author[i]) sheet1.cell(i + 2, 3, ans_title[i]) sheet1.cell(i + 2, 4, ans_key[i]) xl.save(write_file) print("保存成功到-"+write_file) #获取指定文件夹下的excel import os def get_filename(path,filetype): # 输入路径、文件类型例如'.xlsx' name = [] for root,dirs,files in os.walk(path): for i in files: if os.path.splitext(i)[1]==filetype: name.append(i) return name # 输出由有后缀的文件名组成的列表 if __name__ == '__main__': file='data/' words=read_word() list = get_filename(file, '.xlsx') for i in range(len(list)): new_file=file+list[i] print(new_file) sentences_file = "sentences/sentence" + str(i+1) + ".xlsx" read(new_file,words,sentences_file)
结果展示
明日任务
先学习常见的中文分词工具,分出对应的相关实体,做个小demo尝试
中文分词,试图将诗人个人经历,逐个分段,梳理出这几类关键信息:人物,时间,事件,地点。将文本抽取为规则化的数据格式。