from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional
import tomllib


@dataclass
class ThesisConfig:
    """论文配置数据（学生信息、元数据等，不包含正文内容）。"""

    student_name: str = "<None>"
    student_id: str = "<None>"
    college: str = "<None>"
    major: str = "<None>"
    class_: str = "<None>"
    advisor: str = "<None>"
    advisor_title: str = "<None>"
    title: str = "<None>"

    title_from_md: bool = True
    body_start_keywords: list[str] = field(default_factory=lambda: ["绪论", "引言"])
    body_end_keywords: list[str] = field(
        default_factory=lambda: ["致谢", "参考文献", "附录"]
    )

    def to_dict(self) -> dict:
        """转成模板渲染用的扁平字典，排除 options 命名空间。"""
        return {
            "student_name": self.student_name,
            "student_id": self.student_id,
            "college": self.college,
            "major": self.major,
            "class": self.class_,
            "advisor": self.advisor,
            "advisor_title": self.advisor_title,
            "title": self.title,
        }


def load_config(path: str | Path) -> ThesisConfig:
    """从 TOML 文件加载论文配置。"""
    path = Path(path)
    with open(path, "rb") as f:
        raw = tomllib.load(f)

    meta = raw.get("metadata", {})
    opts = raw.get("options", {})

    return ThesisConfig(
        student_name=meta.get("student_name", "<None>"),
        student_id=meta.get("student_id", "<None>"),
        college=meta.get("college", "<None>"),
        major=meta.get("major", "<None>"),
        class_=meta.get("class", "<None>"),
        advisor=meta.get("advisor", "<None>"),
        advisor_title=meta.get("advisor_title", "<None>"),
        title=meta.get("title", "<None>"),
        title_from_md=opts.get("title_from_md", True),
        body_start_keywords=opts.get("body_start_keywords", ["绪论", "引言"]),
        body_end_keywords=opts.get(
            "body_end_keywords", ["致谢", "参考文献", "附录"]
        ),
    )