基于深度学习的小学生作文标点修正系统——教师端网站前端（九）

工作总结前后端交互用python生成展示数据python读取docx文件csv文件转为字典数据，读取学生的信息随机选择学生的信息，与示例数据组合字典格式存储为csv文件

工作总结

前后端交互

配合后端改了改前端代码

用python生成展示数据

python读取docx文件

from docx import Document path = r"学生端输入文本.docx" document = Document(path) tpath = r"教师端输入（完全正确的文本）.docx" tdocument = Document(tpath) length = len(tdocument.paragraphs) print(length) high = 0 low = 0 for tparagraph in tdocument.paragraphs: high += 1 if tparagraph.text == "低年级": high -= 3 print("高年级：",high) low = length-3-high print("低年级：",low) # print(tparagraph.text)

csv文件转为字典数据，读取学生的信息

import csv students = [] with open("user.csv",'r',encoding="utf-8") as f: reader = csv.reader(f) fieldnames = next(reader)#获取数据的第一列，作为后续要转为字典的键名 生成器，next方法获取 # print(fieldnames) csv_reader = csv.DictReader(f,fieldnames=fieldnames) #self._fieldnames = fieldnames # list of keys for the dict 以list的形式存放键名 for row in csv_reader: d={} for k,v in row.items(): d[k]=v students.append(d) print(students)

随机选择学生的信息，与示例数据组合

import random highData=[] for i in range(10): single = {} stu = random.randint(1,5) + 4 single['sid'] = students[stu]['sid'] single['sname'] = students[stu]['sname'] single['sclass'] = students[stu]['sclass'] single['tid'] = str(random.randint(1,3) + 1000) single['compos'] = document.paragraphs[i+3].text single['revise'] = tdocument.paragraphs[i+1].text single['trevise'] = '无' single['label'] = 0 highData.append(single) print(highData) lowData=[] for i in range(10): single = {} stu = random.randint(1,5) - 1 single['sid'] = students[stu]['sid'] single['sname'] = students[stu]['sname'] single['sclass'] = students[stu]['sclass'] single['tid'] = str(random.randint(1,3) + 1000) single['compos'] = document.paragraphs[i+25].text single['revise'] = tdocument.paragraphs[i+23].text single['trevise'] = '无' single['label'] = 0 lowData.append(single) print(lowData)

字典格式存储为csv文件

import pandas as pd pd.DataFrame(highData).to_csv('highData.csv') pd.DataFrame(lowData).to_csv('lowData.csv')