example_usage.ipynb

{
 "cells": [
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-09-04T11:46:44.572451Z",
     "start_time": "2024-09-04T11:46:44.568681Z"
    }
   },
   "cell_type": "code",
   "source": [
    "from data import Course\n",
    "from ouc_course_tool import *\n",
    "from data.schedule import CourseTable\n",
    "from tests.test_config import ConfigOfTest\n",
    "from ouc_course_tool.core.search_param_handle import search_param_handle\n",
    "from ouc_course_tool.util import draw_course_table"
   ],
   "id": "37aeed355a6062c4",
   "outputs": [],
   "execution_count": 7
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "导入包 和 设置绘图函数",
   "id": "db757333283b61a5"
  },
  {
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "end_time": "2024-09-04T11:46:44.594958Z",
     "start_time": "2024-09-04T11:46:44.590464Z"
    }
   },
   "cell_type": "code",
   "source": [
    "test_config = ConfigOfTest('./tests/test_resource/account_local.ini')\n",
    "tesseract_cmd_path = 'D:/Tools/Tesseract/tesseract.exe'\n",
    "\n",
    "login_config = LoginConfig(test_config.get_username(), test_config.get_password(), tesseract_cmd_path)"
   ],
   "id": "initial_id",
   "outputs": [],
   "execution_count": 8
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "设置 Tesseract 图片识别软件\n",
    "EXAMPLE DOWNLOAD URL: https://digi.bib.uni-mannheim.de/tesseract/tesseract-ocr-w64-setup-5.3.4.20240503.exe\n",
    "\n",
    "设置 全局变量（包括账号和密码）\n",
    "设置 登录配置\n"
   ],
   "id": "f792c3011f1d5b45"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-09-04T12:24:59.107276Z",
     "start_time": "2024-09-04T12:24:57.702578Z"
    }
   },
   "cell_type": "code",
   "source": [
    "session_id = AccountValidation(login_config).get_login_session_id()\n",
    "print(session_id)\n"
   ],
   "id": "c31a4020a3b01217",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "E7E2FAA5D9778D5EFB337CA37D7A0611\n"
     ]
    }
   ],
   "execution_count": 47
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-09-04T12:25:06.565442Z",
     "start_time": "2024-09-04T12:25:06.547516Z"
    }
   },
   "cell_type": "code",
   "source": "session_id = '31FA679E258E1A061F68A40097D7BAEE'",
   "id": "66c479e158ed97e7",
   "outputs": [],
   "execution_count": 48
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "获取登录 ID",
   "id": "4f10a81a39de5596"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-09-04T12:25:12.606153Z",
     "start_time": "2024-09-04T12:25:12.593227Z"
    }
   },
   "cell_type": "code",
   "source": [
    "fetcher_config = CourseFetcherConfig(session_id=session_id)\n",
    "course_fetcher = CourseFetcher(config=fetcher_config)"
   ],
   "id": "4e1379036780659f",
   "outputs": [],
   "execution_count": 49
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "设置 搜索配置",
   "id": "d51d9f1c6a4eda34"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-09-04T11:46:54.509293Z",
     "start_time": "2024-09-04T11:46:46.204292Z"
    }
   },
   "cell_type": "code",
   "source": [
    "target_course = [\n",
    "    '围棋-选修',\n",
    "    '概率-公共',\n",
    "    '形势与政策-公共',\n",
    "    '毛泽东思想-公共',\n",
    "    '网球-公共',\n",
    "    '离散数学-智能科学-2023',\n",
    "    '计算机系统基础-智能科学-2023',\n",
    "    '人工智能先导实践-智能科学-2023',\n",
    "    '人工智能导论-智能科学-2022',\n",
    "    '机器人学导论-智能科学-2022',\n",
    "]\n",
    "mul_params = search_param_handle(target_course, campus=3, year_and_term='2024-1')\n",
    "courses_list = course_fetcher.get_courses_from_mul_params(mul_params)"
   ],
   "id": "f709d8ca614ecb3e",
   "outputs": [],
   "execution_count": 11
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "目标选课",
   "id": "d699d3dd16c0dda0"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-09-04T11:58:50.231023Z",
     "start_time": "2024-09-04T11:58:50.221790Z"
    }
   },
   "cell_type": "code",
   "source": [
    "importance_course = [\n",
    "    '离散数学',\n",
    "    '概率统计',\n",
    "    '人工智能导论',\n",
    "    '围棋'\n",
    "]\n",
    "\n",
    "unnecessary_course = [\n",
    "    '篮球',\n",
    "    '足球',\n",
    "]\n",
    "\n",
    "no_overflow_course = [\n",
    "    # '概率',\n",
    "    # '形势与政策',\n",
    "    '毛泽东思想',\n",
    "    # '网球',\n",
    "]\n",
    "\n",
    "no_8_course = [\n",
    "    # '概率',\n",
    "    # '形势与政策',\n",
    "    # '毛泽东思想',\n",
    "    # '计算机系统基础',\n",
    "]\n",
    "\n",
    "def is_in_course(target, course_list):\n",
    "    for temp_course in course_list:\n",
    "        if temp_course in target:\n",
    "            return True\n",
    "\n",
    "def limit_function(course):\n",
    "    \n",
    "    # 重要的不限制的课\n",
    "    if is_in_course(course.course_name, importance_course):\n",
    "        return False\n",
    "    \n",
    "    # 不要的课\n",
    "    if is_in_course(course.course_name, unnecessary_course):\n",
    "        return True\n",
    "    \n",
    "    # 超人数 不选\n",
    "    if is_in_course(course.course_name, no_overflow_course):\n",
    "        if float(course.limit) < int(course.selected_count) * 1:\n",
    "            return True\n",
    "    \n",
    "    # 早八 不选\n",
    "    if is_in_course(course.course_name, no_8_course):\n",
    "        for time in course.get_class_time_list():\n",
    "            if time.start_period == 1:\n",
    "                return True\n",
    "        \n",
    "table = CourseTable.calculate_course(courses_list, limit_function)\n",
    "# table = CourseTable.calculate_course(courses_list, None)\n",
    "table.print_courses()\n",
    "\n",
    "selection_number_list = map(lambda temp_course: int(temp_course.selection_number), table.selected_courses)\n",
    "selection_number_list = sorted(list(selection_number_list), reverse=True)\n",
    "selection_number_list = map(lambda temp_course: str(temp_course).rjust(8, '0'), selection_number_list)"
   ],
   "id": "b270f43367654055",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "围棋与中国文化\n",
      "07001044 齐祥明\n",
      "\n",
      "概率统计\n",
      "16001079 王雯\n",
      "\n",
      "形势与政策-2024秋\n",
      "19000170 梁山\n",
      "\n",
      "毛泽东思想和中国特色社会主义理论体系概论\n",
      "19000017 隋筱童\n",
      "\n",
      "体育(初级网球)\n",
      "18003229 常晓峰\n",
      "\n",
      "离散数学Ⅱ\n",
      "02003004 马慧\n",
      "\n",
      "计算机系统基础\n",
      "02003003 蒋永国\n",
      "\n",
      "人工智能先导实践\n",
      "02003066 徐建良\n",
      "\n",
      "人工智能导论\n",
      "02003125 贺佩兰\n",
      "\n",
      "机器人学导论\n",
      "02003012 梁馨月\n",
      "\n"
     ]
    }
   ],
   "execution_count": 23
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-09-04T11:50:03.234926Z",
     "start_time": "2024-09-04T11:50:03.081213Z"
    }
   },
   "cell_type": "code",
   "source": [
    "over_flow = 0\n",
    "for course in table.selected_courses:\n",
    "    n1, n2 = int(course.limit), int(course.selected_count)\n",
    "    print(course.course_name, str(n1) + \"/\" + str(n2), \"!!!!!! 超出人数\" + str(n2 - n1) if n1 < n2 else \"\")\n",
    "    over_flow += n2 - n1 if n1 < n2 else 0\n",
    "print('总计超出人数', over_flow)\n",
    "\n",
    "draw_course_table(table.selected_courses)"
   ],
   "id": "d19474ee2e26dfbc",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[009101251913]围棋与中国文化 40/62 !!!!!! 超出人数22\n",
      "[008401101063]概率统计 120/42 \n",
      "[008101202411]形势与政策-2024秋专题 1400/352 \n",
      "[008101101035]毛泽东思想和中国特色社会主义理论体系概论 160/86 \n",
      "[008201103047]体育(初级网球) 40/62 !!!!!! 超出人数22\n",
      "[080502201309]离散数学Ⅱ 60/103 !!!!!! 超出人数43\n",
      "[080502201205]计算机系统基础 80/78 \n",
      "[080503202301]人工智能先导实践 50/59 !!!!!! 超出人数9\n",
      "[080502101345]人工智能导论 25/71 !!!!!! 超出人数46\n",
      "[080503201305]机器人学导论 50/45 \n",
      "总计超出人数 142\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1000x700 with 1 Axes>"
      ],
      "image/png": "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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 20
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "设置限制函数 并且 获得课程表",
   "id": "688831136bb2a33b"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-09-04T12:25:49.020569Z",
     "start_time": "2024-09-04T12:25:48.785078Z"
    }
   },
   "cell_type": "code",
   "source": [
    "common_params = CourseFetcherParams()\n",
    "common_params.set_keyword('人工智能先导实践')\n",
    "common_params.kcfw = 'Specialty'\n",
    "common_params.sel_nj = 2023\n",
    "\n",
    "result: list[Course] = course_fetcher.get_courses_by_params(common_params)\n",
    "\n",
    "for course in result:\n",
    "    if \"西海岸\" in course.campus:\n",
    "        print(course.get_class_time_list())\n",
    "        print(course.instructor ,course.limit, course.selected_count, course.selection_number)"
   ],
   "id": "381eabf0ea9ea77b",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[周次: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17] 星期: 五 (7-8节) 单周]\n",
      "徐建良 50 61 02003066\n"
     ]
    }
   ],
   "execution_count": 50
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}