⚒️ 重大重构 LoveACE V2
引入了 mongodb 对数据库进行了一定程度的数据加密 性能改善 代码简化 统一错误模型和响应 使用 apifox 作为文档
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348
loveace/router/endpoint/jwc/model/plan.py
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348
loveace/router/endpoint/jwc/model/plan.py
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import re
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from typing import List, Optional
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from pydantic import BaseModel, Field
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class PlanCompletionCourse(BaseModel):
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"""培养方案课程完成情况"""
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flag_id: str = Field("", description="课程标识ID")
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flag_type: str = Field("", description="节点类型：001=分类, 002=子分类, kch=课程")
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course_code: str = Field("", description="课程代码，如 PDA2121005")
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course_name: str = Field("", description="课程名称")
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is_passed: bool = Field(False, description="是否通过（基于CSS图标解析）")
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status_description: str = Field("", description="状态描述：未修读/已通过/未通过")
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credits: Optional[float] = Field(None, description="学分")
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score: Optional[str] = Field(None, description="成绩")
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exam_date: Optional[str] = Field(None, description="考试日期")
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course_type: str = Field("", description="课程类型：必修/任选等")
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parent_id: str = Field("", description="父节点ID")
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level: int = Field(0, description="层级：0=根分类，1=子分类，2=课程")
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@classmethod
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def from_ztree_node(cls, node: dict) -> "PlanCompletionCourse":
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"""从 zTree 节点数据创建课程对象"""
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# 解析name字段中的信息
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name = node.get("name", "")
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flag_id = node.get("flagId", "")
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flag_type = node.get("flagType", "")
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parent_id = node.get("pId", "")
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# 根据CSS图标判断通过状态
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is_passed = False
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status_description = "未修读"
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if "fa-smile-o fa-1x green" in name:
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is_passed = True
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status_description = "已通过"
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elif "fa-meh-o fa-1x light-grey" in name:
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is_passed = False
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status_description = "未修读"
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elif "fa-frown-o fa-1x red" in name:
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is_passed = False
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status_description = "未通过"
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# 从name中提取纯文本内容
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# 移除HTML标签和图标
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clean_name = re.sub(r"<[^>]*>", "", name)
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clean_name = re.sub(r" ", " ", clean_name).strip()
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# 解析课程信息
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course_code = ""
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course_name = ""
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credits = None
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score = None
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exam_date = None
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course_type = ""
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if flag_type == "kch": # 课程节点
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# 解析课程代码：[PDA2121005]形势与政策
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code_match = re.search(r"\[([^\]]+)\]", clean_name)
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if code_match:
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course_code = code_match.group(1)
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remaining_text = clean_name.split("]", 1)[1].strip()
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# 解析学分信息：[0.3学分]
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credit_match = re.search(r"\[([0-9.]+)学分\]", remaining_text)
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if credit_match:
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credits = float(credit_match.group(1))
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remaining_text = re.sub(
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r"\[[0-9.]+学分\]", "", remaining_text
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).strip()
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# 处理复杂的括号内容
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# 例如：85.0(20250626 成绩，都没把日期解析上，中国近现代史纲要)
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# 或者：(任选,87.0(20250119))
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# 找到最外层的括号
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paren_match = re.search(
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r"\(([^)]+(?:\([^)]*\)[^)]*)*)\)$", remaining_text
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)
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if paren_match:
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paren_content = paren_match.group(1)
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course_name_candidate = re.sub(
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r"\([^)]+(?:\([^)]*\)[^)]*)*\)$", "", remaining_text
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).strip()
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# 检查括号内容的格式
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if "，" in paren_content:
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# 处理包含中文逗号的复杂格式
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parts = paren_content.split("，")
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# 最后一部分可能是课程名
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last_part = parts[-1].strip()
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if (
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re.search(r"[\u4e00-\u9fff]", last_part)
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and len(last_part) > 1
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):
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# 最后一部分包含中文，很可能是真正的课程名
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course_name = last_part
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# 从前面的部分提取成绩和其他信息
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remaining_parts = "，".join(parts[:-1])
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# 提取成绩
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score_match = re.search(r"([0-9.]+)", remaining_parts)
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if score_match:
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score = score_match.group(1)
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# 提取日期
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date_match = re.search(r"(\d{8})", remaining_parts)
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if date_match:
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exam_date = date_match.group(1)
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# 提取课程类型（如果有的话）
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if len(parts) > 2:
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potential_type = parts[0].strip()
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if not re.search(r"[0-9.]", potential_type):
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course_type = potential_type
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else:
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# 最后一部分不是课程名，使用括号外的内容
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course_name = (
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course_name_candidate
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if course_name_candidate
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else "未知课程"
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)
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# 从整个括号内容提取信息
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score_match = re.search(r"([0-9.]+)", paren_content)
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if score_match:
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score = score_match.group(1)
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date_match = re.search(r"(\d{8})", paren_content)
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if date_match:
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exam_date = date_match.group(1)
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elif "," in paren_content:
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# 处理标准格式：(任选,87.0(20250119))
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type_score_parts = paren_content.split(",", 1)
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if len(type_score_parts) == 2:
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course_type = type_score_parts[0].strip()
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score_info = type_score_parts[1].strip()
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# 解析成绩和日期
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score_date_match = re.search(
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r"([0-9.]+)\((\d{8})\)", score_info
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)
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if score_date_match:
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score = score_date_match.group(1)
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exam_date = score_date_match.group(2)
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else:
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score_match = re.search(r"([0-9.]+)", score_info)
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if score_match:
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score = score_match.group(1)
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# 使用括号外的内容作为课程名
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course_name = (
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course_name_candidate
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if course_name_candidate
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else "未知课程"
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)
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else:
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# 括号内只有简单内容
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course_name = (
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course_name_candidate
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if course_name_candidate
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else "未知课程"
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)
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# 尝试从括号内容提取成绩
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score_match = re.search(r"([0-9.]+)", paren_content)
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if score_match:
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score = score_match.group(1)
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# 尝试提取日期
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date_match = re.search(r"(\d{8})", paren_content)
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if date_match:
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exam_date = date_match.group(1)
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else:
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# 没有括号，直接使用剩余文本作为课程名
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course_name = remaining_text
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# 清理课程名
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course_name = re.sub(r"\s+", " ", course_name).strip()
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course_name = course_name.strip("，,。.")
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# 如果课程名为空或太短，尝试从原始名称提取
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if not course_name or len(course_name) < 2:
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chinese_match = re.search(
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r"[\u4e00-\u9fff]+(?:[\u4e00-\u9fff\s]*[\u4e00-\u9fff]+)*",
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clean_name,
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)
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if chinese_match:
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course_name = chinese_match.group(0).strip()
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else:
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course_name = clean_name
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else:
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# 分类节点
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course_name = clean_name
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# 清理分类名称中的多余括号，但保留重要信息
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# 如果是包含学分信息的分类名，保留学分信息
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if not re.search(r"学分", course_name):
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# 删除分类名称中的统计信息括号，如 "通识通修(已完成20.0/需要20.0)"
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course_name = re.sub(r"\([^)]*完成[^)]*\)", "", course_name).strip()
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# 删除其他可能的统计括号
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course_name = re.sub(
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r"\([^)]*\d+\.\d+/[^)]*\)", "", course_name
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).strip()
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# 清理多余的空格和空括号
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course_name = re.sub(r"\(\s*\)", "", course_name).strip()
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course_name = re.sub(r"\s+", " ", course_name).strip()
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# 确定层级
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level = 0
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if flag_type == "002":
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level = 1
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elif flag_type == "kch":
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level = 2
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return cls(
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flag_id=flag_id,
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flag_type=flag_type,
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course_code=course_code,
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course_name=course_name,
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is_passed=is_passed,
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status_description=status_description,
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credits=credits,
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score=score,
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exam_date=exam_date,
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course_type=course_type,
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parent_id=parent_id,
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level=level,
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)
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class PlanCompletionCategory(BaseModel):
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"""培养方案分类完成情况"""
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category_id: str = Field("", description="分类ID")
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category_name: str = Field("", description="分类名称")
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min_credits: float = Field(0.0, description="最低修读学分")
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completed_credits: float = Field(0.0, description="通过学分")
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total_courses: int = Field(0, description="已修课程门数")
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passed_courses: int = Field(0, description="已及格课程门数")
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failed_courses: int = Field(0, description="未及格课程门数")
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missing_required_courses: int = Field(0, description="必修课缺修门数")
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subcategories: List["PlanCompletionCategory"] = Field(
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default_factory=list, description="子分类"
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)
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courses: List[PlanCompletionCourse] = Field(
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default_factory=list, description="课程列表"
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)
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@classmethod
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def from_ztree_node(cls, node: dict) -> "PlanCompletionCategory":
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"""从 zTree 节点创建分类对象"""
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name = node.get("name", "")
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flag_id = node.get("flagId", "")
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# 移除HTML标签获取纯文本
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clean_name = re.sub(r"<[^>]*>", "", name)
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clean_name = re.sub(r" ", " ", clean_name).strip()
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# 解析分类统计信息
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# 格式：通识通修(最低修读学分:68,通过学分:34.4,已修课程门数:26,已及格课程门数:26,未及格课程门数:0,必修课缺修门数:12)
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stats_match = re.search(
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r"([^(]+)\(最低修读学分:([0-9.]+),通过学分:([0-9.]+),已修课程门数:(\d+),已及格课程门数:(\d+),未及格课程门数:(\d+),必修课缺修门数:(\d+)\)",
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clean_name,
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)
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if stats_match:
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category_name = stats_match.group(1)
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min_credits = float(stats_match.group(2))
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completed_credits = float(stats_match.group(3))
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total_courses = int(stats_match.group(4))
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passed_courses = int(stats_match.group(5))
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failed_courses = int(stats_match.group(6))
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missing_required_courses = int(stats_match.group(7))
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else:
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# 子分类可能没有完整的统计信息
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category_name = clean_name
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min_credits = 0.0
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completed_credits = 0.0
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total_courses = 0
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passed_courses = 0
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failed_courses = 0
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missing_required_courses = 0
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return cls(
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category_id=flag_id,
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category_name=category_name,
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min_credits=min_credits,
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completed_credits=completed_credits,
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total_courses=total_courses,
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passed_courses=passed_courses,
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failed_courses=failed_courses,
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missing_required_courses=missing_required_courses,
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)
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class PlanCompletionInfo(BaseModel):
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"""培养方案完成情况总信息"""
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plan_name: str = Field("", description="培养方案名称")
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major: str = Field("", description="专业名称")
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grade: str = Field("", description="年级")
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categories: List[PlanCompletionCategory] = Field(
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default_factory=list, description="分类列表"
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)
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total_categories: int = Field(0, description="总分类数")
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total_courses: int = Field(0, description="总课程数")
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passed_courses: int = Field(0, description="已通过课程数")
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failed_courses: int = Field(0, description="未通过课程数")
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unread_courses: int = Field(0, description="未修读课程数")
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def calculate_statistics(self):
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"""计算统计信息"""
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total_courses = 0
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passed_courses = 0
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failed_courses = 0
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unread_courses = 0
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def count_courses(categories: List[PlanCompletionCategory]):
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nonlocal total_courses, passed_courses, failed_courses, unread_courses
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for category in categories:
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for course in category.courses:
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total_courses += 1
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if course.is_passed:
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passed_courses += 1
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elif course.status_description == "未通过":
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failed_courses += 1
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else:
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unread_courses += 1
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# 递归处理子分类
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count_courses(category.subcategories)
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count_courses(self.categories)
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self.total_categories = len(self.categories)
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self.total_courses = total_courses
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self.passed_courses = passed_courses
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self.failed_courses = failed_courses
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self.unread_courses = unread_courses
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