forked from hnu202311020126/iSmartAuto
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123 lines
3.9 KiB
123 lines
3.9 KiB
import json
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import os
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import pickle
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import urllib.parse as parser
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from bs4 import BeautifulSoup
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from loguru import logger
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from random import random, randint
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from configs import configs
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from .devtools import Browser
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from .markdown import generate_md
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from .spider import Spider
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random_args = { # 不同题型对应的随机时长和分数范围
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'1': { # 单选题
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'time': (20, 60), # 完成时长 / 秒
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'score': 1 # 得分 (归一化, 向上随机取至满分)
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},
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'2': { # 多选题
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'time': (40, 120),
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'score': 0.9
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},
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'3': { # 判断题
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'time': (20, 50),
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'score': 1
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},
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'4': { # 填空题
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'time': (60, 180),
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'score': 1
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},
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'6': { # 连线题
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'time': (60, 180),
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'score': 0.8
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},
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'8': { # 匹配题
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'time': (30, 90),
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'score': 1
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},
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'9': { # 口语跟读
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'time': (15, 30),
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'score': 0.8
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},
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'10': { # 短文改错
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'time': (120, 180),
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'score': 0.7
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},
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'11': { # 选词填空
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'time': (30, 90),
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'score': 0.9
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}
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}
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def _random_progress(paper):
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paper = BeautifulSoup(paper, 'lxml-xml')
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questions = paper.select('element[knowledge]:has(> question_type)')
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if questions:
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total_score = 0
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my_score, my_time = 0, 0
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for que in questions:
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qt_type = que.select_one('question_type').text
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qt_score = int(que.select_one('question_score').text)
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total_score += qt_score
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rate = 1 - (1 - random_args[qt_type]['score']) * random()
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my_score += qt_score * rate
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my_time += randint(*random_args[qt_type]['time'])
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return int(100 * my_score / total_score), my_time
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return 100, 5
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async def export(): # 导出某书籍的答案
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browser = Browser.connect()
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page = await browser.wait_for_book()
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params = dict(parser.parse_qsl(parser.urlsplit(page.url).query))
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# noinspection PyTypeChecker
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book_id, course_id = params['bookId'], params['courseId']
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if not os.path.exists(f'.cache/books/{book_id}'):
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async with Spider() as spider:
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await spider.login(**configs['user'])
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book = await spider.book_info(book_id)
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book['courseId'] = course_id
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tasks = await spider.get_tasks(book, tree=True)
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await spider.download_tree(tasks)
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with open(f'.cache/books/{book_id}/Tree.pck', 'rb') as fp:
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generate_md(pickle.load(fp))
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async def finish(): # 直接完成某书籍的任务
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browser = Browser.connect()
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page = await browser.wait_for_book()
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params = dict(parser.parse_qsl(parser.urlsplit(page.url).query))
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# noinspection PyTypeChecker
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book_id, course_id = params['bookId'], params['courseId']
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async with Spider() as spider:
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await spider.login(**configs['user'])
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if not os.path.exists(f'.cache/books/{book_id}'):
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book = await spider.book_info(book_id)
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book['courseId'] = course_id
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tasks = await spider.get_tasks(book, tree=True)
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await spider.download_tree(tasks)
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user_id = (await spider.get_user())['data']['uid']
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logger.info('正在提交任务...')
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for file in os.listdir(f'.cache/books/{book_id}'):
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paper_id, ext = os.path.splitext(file)
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if ext != '.json':
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continue
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with open(f'.cache/books/{book_id}/{file}') as fp:
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data = json.load(fp)
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task = data['task']
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paper = data['paperData']
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score, time = _random_progress(paper)
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result = await page.submit(book_id, task['chapterId'], task['id'], score, time, 100, user_id)
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if result['wasThrown'] or not result['result']['value']:
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logger.warning(f'任务 {task["name"]} [paperId: {paper_id}] 可能提交失败，请留意最终结果！')
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logger.info('全部提交完成！')
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async def finish_all(): # Todo: 全刷了？
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pass
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