forked from hnu202311020126/iSmartAuto
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60 lines
1.6 KiB
60 lines
1.6 KiB
import json
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from collections import deque
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from bs4 import BeautifulSoup
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from loguru import logger
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from .formatter import fix
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from .generator import Generators
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_output = deque()
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# 解码题目与答案 xml
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def decode(que, ans, qt_type):
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getattr(Generators, f'type_{qt_type}')(que, ans, _output)
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# 生成每个 paper 的答案
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def unescape(node, book_id):
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paper_id = node.task['paperId']
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with open(f'.cache/books/{book_id}/{paper_id}.json', 'r') as fp:
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task = json.load(fp)
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paper = BeautifulSoup(task['paperData'], 'lxml-xml')
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answer = BeautifulSoup(task['answerData'], 'lxml-xml')
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questions = paper.select('element[knowledge]:has(> question_type)')
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if questions:
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for que in questions:
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qt_type = int(que.select_one('question_type').text)
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decode(que, answer, qt_type)
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return True
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return False
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# 深搜创建目录树
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def dfs(node, book_id, depth=2):
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if title := node.task['name']:
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logger.info(f'{". " * (depth - 1)}{title}')
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title = fix(title, ('rm_head',))
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_output.append(f'{"#" * depth} {title}\n')
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flag = False
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if 'paperId' in node.task:
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flag = unescape(node, book_id)
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for ch in node.children:
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if dfs(ch, book_id, depth + 1):
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flag = True
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if not flag:
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_output.pop()
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return flag
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def generate_md(root): # 生成答案
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book_id = root.task['book_id']
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for ch in root.children:
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dfs(ch, book_id)
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with open('.cache/answer.md', 'w', encoding='utf-8') as file:
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while len(_output):
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line = _output.popleft()
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file.write(line + '\n')
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logger.info('Done.')
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