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fc6afdea9d
配置类 ThesisConfig 现在使用 metadata 字典直接透传 TOML 配置， 无需为每个变量单独声明字段。新增模板变量只需修改 TOML 文件， 无需修改 Python 代码。 BREAKING CHANGE: 配置文件结构发生改变，从单独字段改为统一的 metadata 节点。
144 lines
4.4 KiB
Python
144 lines
4.4 KiB
Python
"""
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论文生成编排器。
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组装 配置 + 解析 + 模板渲染 + 正文注入 的完整流水线。
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"""
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from collections import defaultdict
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from pathlib import Path
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from docxtpl import DocxTemplate
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from docx import Document
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from .config import load_config, ThesisConfig
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from .parser import parse_markdown
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from .body import body_to_paragraphs, replace_placeholder
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from .references import references_to_paragraphs
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# 解析器可能产生的字段（用于填充报告）
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_PARSER_FIELDS = [
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"title",
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"abstact_cn_context",
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"abstract_cn_keywords",
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"abstract_en_context",
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"abstract_en_keywords",
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"acknowledgement",
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"reference",
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"appendix",
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"body_md",
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]
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def generate_thesis(
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template_path: str | Path,
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data_path: str | Path,
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config_path: str | Path | None = None,
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output_path: str | Path = "output.docx",
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) -> dict:
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"""执行从数据到 Word 的完整论文生成流程。
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Parameters
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----------
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template_path : str | Path
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docxtpl 模板文件路径（.docx）。
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data_path : str | Path
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Markdown 论文正文文件路径（.md）。
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config_path : str | Path | None
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TOML 配置文件路径。为 ``None`` 时尝试自动查找。
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output_path : str | Path
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输出 Word 文件路径。
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"""
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data_path = Path(data_path)
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# 1. 加载配置
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if config_path is None:
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candidates = [
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Path("thesis_config.toml"),
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data_path.with_suffix(".toml"),
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]
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config_path = next((p for p in candidates if p.exists()), None)
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config: ThesisConfig | None = None
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if config_path and Path(config_path).exists():
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config = load_config(config_path)
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print(f"[配置] 配置文件: {config_path}")
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else:
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config = ThesisConfig()
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print("[配置] 未找到配置文件，使用默认值。")
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# 2. 解析 Markdown
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with open(data_path, "r", encoding="utf-8") as f:
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md_text = f.read()
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context = parse_markdown(
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md_text,
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body_start_kw=config.body_start_keywords,
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body_end_kw=config.body_end_keywords,
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)
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# 3. 合并配置 → 上下文（配置填充解析器未产生的空白）
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for k, v in config.to_dict().items():
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if k == "title" and config.title_from_md and context.get("title"):
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continue # 以 markdown 标题为准
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context.setdefault(k, v)
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# 4. 用 defaultdict 兜底缺失键
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ctx = defaultdict(lambda: "<None>", context)
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# 5. 解析正文为段落列表
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body_md = ctx.get("body_md", "")
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body_paragraphs = (
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body_to_paragraphs(body_md, level_offset=config.level_offset, body_style=config.body_style)
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if body_md else []
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)
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# 6. 解析参考文献为段落列表
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ref_text = ctx.get("reference", "")
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ref_paragraphs = references_to_paragraphs(ref_text, ref_style=config.reference_style)
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# 7. 占位符（替代模板变量，后处理时替换）
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ctx["body_placeholder"] = "__CONTEXT_PLACEHOLDER__"
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ctx["reference"] = "__REFERENCE_PLACEHOLDER__"
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# 7. 渲染模板
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doc = DocxTemplate(str(template_path))
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doc.render(ctx)
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# 8. 保存临时文件，再做后处理
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temp_path = Path(output_path).with_suffix(".tmp")
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doc.save(str(temp_path))
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# 9. 正文注入＋参考文献注入
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final_doc = Document(str(temp_path))
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replace_placeholder(
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final_doc, "__CONTEXT_PLACEHOLDER__", body_paragraphs,
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default_body_style=config.body_style,
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)
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replace_placeholder(
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final_doc, "__REFERENCE_PLACEHOLDER__", ref_paragraphs,
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default_body_style=config.reference_style,
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)
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final_doc.save(str(output_path))
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temp_path.unlink(missing_ok=True)
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print(f"[完成] 论文生成完成: {output_path}")
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# 10. 字段填充报告（动态收集所有模板与解析字段）
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report_fields = list(dict.fromkeys([*config.metadata.keys(), *_PARSER_FIELDS]))
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print("\n--- 字段填充情况 ---")
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for key in report_fields:
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val = ctx.get(key, "<None>")
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if val == "<None>":
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print(f" [缺失] {key}")
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else:
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preview = str(val)[:60].replace("\n", " ")
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print(f" [OK] {key}: {preview}...")
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missing = [k for k in report_fields if ctx.get(k, "<None>") == "<None>"]
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if missing:
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print("\n[警告] 以下字段缺失，已填充 '<None>'：")
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for f in missing:
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print(f" - {f}")
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return dict(ctx)
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