simulinkl and Python.rar_ABS_ABS simulink_ABS 控制_python simulink

import re import requests import numpy as np import pandas as pd def warn(*args, **kw): pass import warnings warnings.warn = warn print('*' * 30 + '东华理工大学' + '*' * 30) print('*' * 30 + '作者:杨航锋' + '*' * 30) print('*' * 30 + '版本:v1.0' + '*' * 30) print('\n') print('请输你学号:') username = input() print('请输入密码:') password = input() print('\n') login_url = 'https://cas.ecit.cn/index.jsp?service=http://portal.ecit.cn/Authentication' def get_LT(login_url): html = requests.get(login_url, verify=False).text regex = re.compile('<input type="hidden" name="lt" value="(.*?)" />') lt = re.findall(regex, html)[0] return lt LT = get_LT(login_url) data = { 'lt': LT, 'password': password, 'username': username } headers = { 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8', 'Accept-Encoding': 'gzip, deflate, br', 'Accept-Language': 'zh-CN,zh;q=0.8,en-US;q=0.5,en;q=0.3', 'Connection': 'keep-alive', 'Host': 'cas.ecit.cn', 'Referer': 'https://cas.ecit.cn/index.jsp?service=http://portal.ecit.cn/Authentication', 'Upgrade-Insecure-Requests': '1', 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64; rv:48.0) Gecko/20100101 Firefox/48.0' } s = requests.Session() s.post(login_url, data=data, headers=headers, verify=False) html = s.get('http://jw.ecit.cn').text reg = re.compile('<a href="(.*?)">') start_url = re.findall(reg, html)[0] s.post(start_url) grade_url = 'http://jw.ecit.cn/gradeLnAllAction.do?type=ln&oper=qbinfo&lnxndm=2016-2017%D1%A7%C4%EA%B5%DA%D2%BB%D1%A7%C6%DA(%C1%BD%D1%A7%C6%DA)#qb_2016-2017%E5%AD%A6%E5%B9%B4%E7%AC%AC%E4%B8%80%E5%AD%A6%E6%9C%9F(%E4%B8%A4%E5%AD%A6%E6%9C%9F)' grade_html = s.get(grade_url).text cloumn_name_reg = re.compile('<th align="center" width="10%" class="sortable">\s*(.*?)\s*</th>') cloumn_name = re.findall(cloumn_name_reg, grade_html)[0:7] del cloumn_name[3] grade_reg = re.compile('<td align="center">\s*(.*?)\s*</td>') grade_pre_list = re.findall(grade_reg, grade_html) grade_pre1_list = [i for i in grade_pre_list if not i.startswith('&nbsp')] grade_list = [] for _ in grade_pre1_list: if not _.startswith('<p'): grade_list.append(_) else: reg_ = re.compile('<p align="center">(.*?)&nbsp;</P>') grade = re.findall(reg_, _)[0] grade_list.append(grade) grade_data_ = pd.DataFrame() grade_data = np.array(grade_list).reshape(-1, 6) for i, j in zip(cloumn_name, range(6)): grade_data_[i] = grade_data[:, j] print('1:打印最新的五门成绩') print('2:保存所有的成绩到本地文件夹') print('3:打印学位课成绩并计算平均学分绩') print('\n') select = input('请输入你的请求:') if select == '1': print(grade_data_[-5:]) elif select == '2': grade_data_.to_csv('./grade_data.csv', index=False) print('成绩已保存在运行此程序的文件夹') elif select == '3': xw_grade = grade_data_[(grade_data_['课程名'] == '*数学分析(I)') | (grade_data_['课程名'] == '高等代数(I)') | (grade_data_['课程名'] == 'C语言程序设计基础') | (grade_data_['课程名'] == '大学英语（II）') | (grade_data_['课程名'] == '*常微分方程') | (grade_data_['课程名'] == '*概率论') | (grade_data_['课程名'] == '数据结构')] print(xw_grade) print('\n') avg_grade = np.sum((xw_grade.学分.astype(float) * xw_grade.成绩.astype(float))) / \ np.sum(xw_grade.学分.astype(float)) print('平均学分绩={0}'.format(avg_grade)) input('按任意键结束'